ipcc_testset.jsonl

{"id":"450623f7-e644-4bfa-88d5-90f31dd15d99","question":"What are the consequences of global warming exceeding 2\u00b0C for climate resilient development in some regions and sub-regions?","reference_answer":"Climate resilient development will not be possible in some regions and sub-regions if global warming exceeds 2\u00b0C.","reference_context":"Document 196: Accelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\n\nDocument 244: Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence). System \ntransitions151 consistent with pathways that limit warming to 1.5\u00b0C \n(>50%) with no or limited overshoot are more rapid and pronounced \nin the near-term than in those that limit warming to 2\u00b0C (>67%) \n(high con\ufb01dence). Such a systemic change is unprecedented in terms \nof scale, but not necessarily in terms of speed (medium con\ufb01dence). \nThe system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors.\n\nDocument 193: (high con\ufb01dence) {WGII SPM B.5.4, WGII SPM C.2.4; \nWGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5; SRCCL SPM B.3, \nSRCCL SPM B.7.3, SRCCL Figure SPM.3}\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\nModelled pathways that assume using resources more ef\ufb01ciently or shift \nglobal development towards sustainability include fewer challenges, such \nas dependence on CDR and pressure on land and biodiversity, and have \nthe most pronounced synergies with respect to sustainable development \n(high con\ufb01dence). {WGIII SPM C.3.6; SR1.5 SPM D.4.2} \nStrengthening climate change mitigation action entails more \nrapid transitions and higher up-front investments, but brings \nbene\ufb01ts from avoiding damages from climate change and \nreduced adaptation costs. The aggregate effects of climate change \nmitigation on global GDP (excluding damages from climate change and \nadaptation costs) are small compared to global projected GDP growth. \nProjected estimates of global aggregate net economic damages and \nthe costs of adaptation generally increase with global warming level. \n(high con\ufb01dence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, \nWGIII SPM C.12.3} \nCost-bene\ufb01t analysis remains limited in its ability to represent all \ndamages from climate change, including non-monetary damages, \nor to capture the heterogeneous nature of damages and the risk of \ncatastrophic damages (high con\ufb01dence).\n\nDocument 199: Coastal cities and \nsettlements play an important role in advancing climate resilient \ndevelopment due to the high number of people living in the Low \nElevation Coastal Zone, the escalating and climate compounded risk \nthat they face, and their vital role in national economies and beyond \n(high con\ufb01dence). {WGII SPM.D.3, WGII SPM D.3.3; WGIII SPM E.2, \nWGIII SPM E.2.2; SR1.5 SPM D.6}\nObserved adverse impacts and related losses and damages, \nprojected risks, trends in vulnerability, and adaptation limits \ndemonstrate that transformation for sustainability and climate \nresilient development action is more urgent than previously \nassessed (very high con\ufb01dence). Climate resilient development \nintegrates adaptation and GHG mitigation to advance \nsustainable development for all. Climate resilient development \npathways have been constrained by past development, emissions and \nclimate change and are progressively constrained by every increment \nof warming, in particular beyond 1.5\u00b0C (very high con\ufb01dence). \nClimate resilient development will not be possible in some regions \nand sub-regions if global warming exceeds 2\u00b0C (medium con\ufb01dence). \nSafeguarding biodiversity and ecosystems is fundamental to climate \nresilient development, but biodiversity and ecosystem services have \nlimited capacity to adapt to increasing global warming levels, making \nclimate resilient development progressively harder to achieve beyond \n1.5\u00b0C warming (very high con\ufb01dence). {WGII SPM D.1, WGII SPM D.1.1, \nWGII SPM D.4, WGII SPM D.4.3, WGII SPM D.5.1; WGIII SPM D.1.1} \nThe cumulative scienti\ufb01c evidence is unequivocal: climate change \nis a threat to human well-being and planetary health (very \nhigh con\ufb01dence). Any further delay in concerted anticipatory \nglobal action on adaptation and mitigation will miss a brief and \nrapidly closing window of opportunity to secure a liveable and \nsustainable future for all (very high con\ufb01dence). Opportunities for \nnear-term action are assessed in the following section.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":196,"topic":"Climate Change Action"}}
{"id":"79f98d3d-766b-4cbf-800f-03e87966e3e5","question":"What is the projected decline in coral reefs with a global warming of 1.5\u00b0C?","reference_answer":"Coral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of global warming.","reference_context":"Document 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 111: 68\nSection 3\nSection 1\nSection 3\nSection 3: Long-Term Climate and Development Futures\n3.1 Long-Term Climate Change, Impacts and Related Risks\nFuture warming will be driven by future emissions and will affect all major climate system components, with \nevery region experiencing multiple and co-occurring changes. Many climate-related risks are assessed to be \nhigher than in previous assessments, and projected long-term impacts are up to multiple times higher than \ncurrently observed. Multiple climatic and non-climatic risks will interact, resulting in compounding and cascading \nrisks across sectors and regions. Sea level rise, as well as other irreversible changes, will continue for thousands \nof years, at rates depending on future emissions. (high con\ufb01dence)\n3.1.1. Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating.\n\nDocument 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).\n\nDocument 134: 74\nSection 3\nSection 1\nSection 3\nFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. \nProjected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without \nadditional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species \nlosses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as de\ufb01ned by conditions beyond the estimated historical \n(1850\u20132005) maximum mean annual temperature experienced by each species, at GWLs of 1.5\u00b0C, 2\u00b0C, 3\u00b0C and 4\u00b0C. Underpinning projections of temperature are from 21 Earth \nsystem models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure \nto hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991\u20132005) and at GWLs of 1.7\u00b0C to 2.3\u00b0C \n(mean = 1.9\u00b0C; 13 climate models), 2.4\u00b0C to 3.1\u00b0C (2.7\u00b0C; 16 climate models) and 4.2\u00b0C to 5.4\u00b0C (4.7\u00b0C; 15 climate models). Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":123,"topic":"Climate Change Risks"}}
{"id":"1ee224a2-62af-4877-b172-baec006512e6","question":"What is the expected uncertainty range in the total potential for mitigation options according to the IPCC report?","reference_answer":"The uncertainty in the total potential is typically 25\u201350%.","reference_context":"Document 251: Where a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such \nas geographical location, resource availability, and regional circumstances, and the colours indicate the range of estimates. The uncertainty in the total potential is typically 25\u201350%. \nWhen interpreting this \ufb01gure, the following should be taken into account: (1) The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) \nbeing displaced, the rate of new technology adoption, and several other factors; (2) Different options have different feasibilities beyond the cost aspects, which are not re\ufb02ected in \nthe \ufb01gure; and (3) Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included. \nPanel (b) displays the indicative potential of demand-side mitigation options for 2050. Potentials are estimated based on approximately 500 bottom-up studies representing all \nglobal regions. The baseline (white bar) is provided by the sectoral mean GHG emissions in 2050 of the two scenarios (IEA-STEPS and IP_ModAct) consistent with policies announced \nby national governments until 2020. The green arrow represents the demand-side emissions reductions potentials. The range in potential is shown by a line connecting dots displaying \nthe highest and the lowest potentials reported in the literature. Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns \nenabled by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in end-use sectors (buildings, land transport, \nfood) by 40\u201370% by 2050 compared to baseline scenarios, while some regions and socioeconomic groups require additional energy and resources. The last row shows how demand-\nside mitigation options in other sectors can in\ufb02uence overall electricity demand. The dark grey bar shows the projected increase in electricity demand above the 2050 baseline due \nto increasing electri\ufb01cation in the other sectors.\n\nDocument 250: Synergies with mitigation are identi\ufb01ed as high, medium, and low. The right-hand side of panel (a) provides an overview of selected \nmitigation options and their estimated costs and potentials in 2030. Relative potentials and costs will vary by place, context and time and in the longer term compared to 2030. Costs \nare net lifetime discounted monetary costs of avoided greenhouse gas emissions calculated relative to a reference technology. The potential (horizontal axis) is the quantity of net \nGHG emission reduction that can be achieved by a given mitigation option relative to a speci\ufb01ed emission baseline. Net GHG emission reductions are the sum of reduced emissions \nand\/or enhanced sinks. The baseline used consists of current policy (around 2019) reference scenarios from the AR6 scenarios database (25\u201375 percentile values). The mitigation \npotentials are assessed independently for each option and are not necessarily additive. Health system mitigation options are included mostly in settlement and infrastructure \n(e.g., ef\ufb01cient healthcare buildings) and cannot be identi\ufb01ed separately. Fuel switching in industry refers to switching to electricity, hydrogen, bioenergy and natural gas. The length \nof the solid bars represents the mitigation potential of an option. Potentials are broken down into cost categories, indicated by different colours (see legend). Only discounted lifetime \nmonetary costs are considered. Where a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such \nas geographical location, resource availability, and regional circumstances, and the colours indicate the range of estimates. The uncertainty in the total potential is typically 25\u201350%. \nWhen interpreting this \ufb01gure, the following should be taken into account: (1) The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) \nbeing displaced, the rate of new technology adoption, and several other factors; (2) Different options have different feasibilities beyond the cost aspects, which are not re\ufb02ected in \nthe \ufb01gure; and (3) Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included. \nPanel (b) displays the indicative potential of demand-side mitigation options for 2050.\n\nDocument 252: The green arrow represents the demand-side emissions reductions potentials. The range in potential is shown by a line connecting dots displaying \nthe highest and the lowest potentials reported in the literature. Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns \nenabled by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in end-use sectors (buildings, land transport, \nfood) by 40\u201370% by 2050 compared to baseline scenarios, while some regions and socioeconomic groups require additional energy and resources. The last row shows how demand-\nside mitigation options in other sectors can in\ufb02uence overall electricity demand. The dark grey bar shows the projected increase in electricity demand above the 2050 baseline due \nto increasing electri\ufb01cation in the other sectors. Based on a bottom-up assessment, this projected increase in electricity demand can be avoided through demand-side mitigation \noptions in the domains of infrastructure use and socio-cultural factors that in\ufb02uence electricity usage in industry, land transport, and buildings (green arrow). {WGII Figure SPM.4, \nWGII Cross-Chapter Box FEASIB in Chapter 18; WGIII SPM C.10, WGIII 12.2.1, WGIII 12.2.2, WGIII Figure SPM.6, WGIII Figure SPM.7}\n4.5.1. Energy Systems\nRapid and deep reductions in GHG emissions require major \nenergy system transitions (high con\ufb01dence). Adaptation options \ncan help reduce climate-related risks to the energy system \n(very high con\ufb01dence). Net zero CO2 energy systems entail: a \nsubstantial reduction in overall fossil fuel use, minimal use of \nunabated fossil fuels153, and use of Carbon Capture and Storage in \nthe remaining fossil fuel systems; electricity systems that emit no \nnet CO2; widespread electrification; alternative energy carriers in \napplications less amenable to electrification; energy conservation \nand efficiency; and greater integration across the energy system \n(high confidence).\n\nDocument 248: WASH, nutrition and diets)\nGreen infrastructure and\necosystem services\nSustainable land use and urban planning\nSustainable urban water management\nClimate services, including\nEarly Warning Systems\nLivelihood diversi\ufb01cation\nDisaster risk management\nSocial safety nets\nRisk spreading and sharing\nPlanned relocation and resettlement\nHuman migration\nAgroforestry\nSustainable aquaculture and \ufb01sheries\nEf\ufb01cient livestock systems\nBiodiversity management and\necosystem connectivity\nIntegrated coastal zone management\nWater use ef\ufb01ciency and water\nresource management\nImproved cropland management\nCoastal defence and hardening\nForest-based adaptation\nResilient power systems\nEnergy reliability (e.g.\ndiversi\ufb01cation, access, stability)\nImprove water use ef\ufb01ciency\nPotential\nfeasibility\nup to 1.5\u00b0C\nENERGY SUPPLY\nLAND, WATER, FOOD\nHEALTH\nSETTLEMENTS AND\nINFRASTRUCTURE\nSOCIETY, LIVELIHOOD\nAND ECONOMY\nINDUSTRY AND WASTE\n20\n10\n0\n20\n10\n0\nElectricity\nLand transport\nBuildings\nIndustry\nFood\n67% \n66% \n29% \n44% \n73% reduction (before \nadditional electri\ufb01cation) \nAdditional electri\ufb01cation (+60%)\nGtCO2-eq\/yr \nGtCO2\/yr \nKey\nTotal emissions (2050)\nPercentage of possible reduction \nDemand-side mitigation potential\nPotential range\n% \nEf\ufb01cient lighting, appliances\nand equipment\nEf\ufb01cient shipping and aviation\nAvoid demand for energy services\nEf\ufb01cient buildings\nElectric vehicles\nPublic transport and bicycling\nBiofuels for transport\nOnsite renewables\nFuel ef\ufb01cient vehicles\nShift to sustainable healthy diets\noptions costing 100 USD tCO2-eq-1 or \nless could reduce global emissions by \nat least half of the 2019 level by 2030\nb) Potential of demand-side \nmitigation options by 2050\nthe range of GHG emissions \nreduction potential is 40-70% \nin these end-use sectors","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":251,"topic":"Climate Change Action"}}
{"id":"16264bd2-510a-4368-a9d6-0a5fef7feb65","question":"What is the effect of increasing cumulative net CO2 emissions on the effectiveness of natural land and ocean carbon sinks?","reference_answer":"The proportion of emissions taken up by land and ocean decreases with increasing cumulative net CO2 emissions.","reference_context":"Document 166: While \nnatural land and ocean carbon sinks are projected to take up, in absolute \nterms, a progressively larger amount of CO2 under higher compared to \nlower CO2 emissions scenarios, they become less effective, that is, the \nproportion of emissions taken up by land and ocean decreases with \nincreasing cumulative net CO2 emissions (high con\ufb01dence). Additional \necosystem responses to warming not yet fully included in climate models, \nsuch as GHG \ufb02uxes from wetlands, permafrost thaw, and wild\ufb01res, \nwould further increase concentrations of these gases in the atmosphere \n(high con\ufb01dence). In scenarios where CO2 concentrations peak and \ndecline during the 21st century, the land and ocean begin to take up less \ncarbon in response to declining atmospheric CO2 concentrations (high \ncon\ufb01dence) and turn into a weak net source by 2100 in the very low \nGHG emissions scenario (medium confidence)133. {WGI SPM B.4, \nWGI SPM B.4.1, WGI SPM B.4.2, WGI SPM B.4.3}\n\nDocument 165: {WGI SPM D.1.3}\n131 Uncertainties for total carbon budgets have not been assessed and could affect the speci\ufb01c calculated fractions. \n132 See footnote 131. \n133 These projected adjustments of carbon sinks to stabilisation or decline of atmospheric CO2 concentrations are accounted for in calculations of remaining carbon budgets. \n{WGI SPM footnote 32}\nIf the annual CO2 emissions between 2020\u20132030 stayed, on average, \nat the same level as 2019, the resulting cumulative emissions would \nalmost exhaust the remaining carbon budget for 1.5\u00b0C (50%), and \nexhaust more than a third of the remaining carbon budget for 2\u00b0C \n(67%) (Figure 3.5). Based on central estimates only, historical cumulative \nnet CO2 emissions between 1850 and 2019 (2400 \u00b1240 GtCO2) amount \nto about four-\ufb01fths131 of the total carbon budget for a 50% probability of \nlimiting global warming to 1.5\u00b0C (central estimate about 2900 GtCO2) and \nto about two-thirds132 of the total carbon budget for a 67% probability \nto limit global warming to 2\u00b0C (central estimate about 3550 GtCO2). \n{WGI Table SPM.2; WGIII SPM B.1.3, WGIII Table 2.1}\nIn scenarios with increasing CO2 emissions, the land and ocean \ncarbon sinks are projected to be less effective at slowing the \naccumulation of CO2 in the atmosphere (high con\ufb01dence). While \nnatural land and ocean carbon sinks are projected to take up, in absolute \nterms, a progressively larger amount of CO2 under higher compared to \nlower CO2 emissions scenarios, they become less effective, that is, the \nproportion of emissions taken up by land and ocean decreases with \nincreasing cumulative net CO2 emissions (high con\ufb01dence). Additional \necosystem responses to warming not yet fully included in climate models, \nsuch as GHG \ufb02uxes from wetlands, permafrost thaw, and wild\ufb01res, \nwould further increase concentrations of these gases in the atmosphere \n(high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":166,"topic":"Climate Change Projections"}}
{"id":"c31c6857-c505-45ef-98e5-aa524c4b05e7","question":"What does hatching represent on the maps depicting changes in maize yield and fisheries catch potential?","reference_answer":"Hatching indicates areas where less than 70% of the climate-crop model combinations agree on the sign of impact for maize yield, and where the two climate-fisheries models disagree in the direction of change for fisheries catch potential.","reference_context":"Document 135: Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C). Median yield changes \nfrom an ensemble of 12 crop models, each driven by bias-adjusted outputs from 5 Earth system models from the Agricultural Model Intercomparison and Improvement Project \n(AgMIP) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Maps depict 2080\u20132099 compared to 1986\u20132005 for current growing regions (>10 ha), with the \ncorresponding range of future global warming levels shown under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively. Hatching indicates areas where <70% of the climate-crop model \ncombinations agree on the sign of impact. (c2) Changes in maximum \ufb01sheries catch potential by 2081\u20132099 relative to 1986-2005 at projected GWLs of 0.9\u00b0C to 2.0\u00b0C (1.5\u00b0C) \nand 3.4\u00b0C to 5.2\u00b0C (4.3\u00b0C). GWLs by 2081\u20132100 under RCP2.6 and RCP8.5. Hatching indicates where the two climate-\ufb01sheries models disagree in the direction of change. Large \nrelative changes in low yielding regions may correspond to small absolute changes. Biodiversity and \ufb01sheries in Antarctica were not analysed due to data limitations. Food security \nis also affected by crop and \ufb01shery failures not presented here. {WGII Fig.\n\nDocument 134: 74\nSection 3\nSection 1\nSection 3\nFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. \nProjected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without \nadditional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species \nlosses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as de\ufb01ned by conditions beyond the estimated historical \n(1850\u20132005) maximum mean annual temperature experienced by each species, at GWLs of 1.5\u00b0C, 2\u00b0C, 3\u00b0C and 4\u00b0C. Underpinning projections of temperature are from 21 Earth \nsystem models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure \nto hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991\u20132005) and at GWLs of 1.7\u00b0C to 2.3\u00b0C \n(mean = 1.9\u00b0C; 13 climate models), 2.4\u00b0C to 3.1\u00b0C (2.7\u00b0C; 16 climate models) and 4.2\u00b0C to 5.4\u00b0C (4.7\u00b0C; 15 climate models). Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C).\n\nDocument 136: Hatching indicates areas where <70% of the climate-crop model \ncombinations agree on the sign of impact. (c2) Changes in maximum \ufb01sheries catch potential by 2081\u20132099 relative to 1986-2005 at projected GWLs of 0.9\u00b0C to 2.0\u00b0C (1.5\u00b0C) \nand 3.4\u00b0C to 5.2\u00b0C (4.3\u00b0C). GWLs by 2081\u20132100 under RCP2.6 and RCP8.5. Hatching indicates where the two climate-\ufb01sheries models disagree in the direction of change. Large \nrelative changes in low yielding regions may correspond to small absolute changes. Biodiversity and \ufb01sheries in Antarctica were not analysed due to data limitations. Food security \nis also affected by crop and \ufb01shery failures not presented here. {WGII Fig. TS.5, WGII Fig TS.9, WGII Annex I: Global to Regional Atlas Figure AI.15, Figure AI.22, Figure AI.23, Figure \nAI.29; WGII 7.3.1.2, 7.2.4.1, SROCC Figure SPM.3} (3.1.2, Cross-Section Box.2)","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":135,"topic":"Climate Change Assessment"}}
{"id":"6b0c9e5c-4b16-4fc3-be76-542889257d64","question":"What are the global reasons for concern (RFCs) compared between AR5 (2014) and AR6 (2022) in terms of global surface temperature change relative to 1850-1900?","reference_answer":"The global reasons for concern (RFCs) in terms of global surface temperature change relative to 1850-1900 are depicted with a temperature scale ranging from 0\u00b0C to 5\u00b0C, showing various impacts such as damage to salt marshes, rocky shores, seagrass meadows, warm-water corals, and kelp forests, as well as risks like wildfire, dryland water scarcity, heat-related morbidity and mortality, and permafrost degradation, with a confidence level assigned to transition range and midpoint of transition. The comparison is shown through a visual scale with dots indicating the level of impact or risk, which increases with higher temperatures.","reference_context":"Document 137: 75\nLong-Term Climate and Development Futures\nSection 3\nSalt\nmarshes\nRocky\nshores\nSeagrass\nmeadows\nEpipelagic\nWarm-water\ncorals\nKelp\nforests\nAR5 AR6\nAR5 AR6\nAR5 AR6\nAR5 AR6\nAR5 AR6\nGlobal surface temperature change\nrelative to 1850\u20131900\nGlobal Reasons for Concern (RFCs) \nin AR5 (2014) vs. AR6 (2022)\n\u00b0C\n0\n1\n1.5\n2\n3\n4\n5\n0\n1\n1.5\n2\n3\n4\n5\n\u00b0C\n0\n\u20131\n2000 2015\n2050\n2100\n1\n2\n3\n4\n5\nvery low\nlow\nintermediate\nhigh\nvery high\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\ndamage\nWild\ufb01re\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\nDryland\nwater \nscarcity\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n0\n2\n3\n4\n1.5\n1\nIncomplete\nadaptation\nProactive\nadaptation\nLimited\nadaptation\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\nHeat-related morbidity and mortality\nhigh\nChallenges to Adaptation\nlow\n\u2022\u2022\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\nCon\ufb01dence level\nassigned to \ntransition range\nmidpoint of transition\nRisk\/impact\nLow\nVery high\nVery high\nHigh\nModerate\nUndetectable\n\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\u2022\nTransition range\n\u00b0C\n\u00b0C\nPermafrost \ndegradation\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\ne.g.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":137,"topic":"Climate Change Assessment"}}
{"id":"975c0cb8-2813-467e-92d8-1d5d6d439e84","question":"What are some land-related adaptation actions that can have mitigation co-benefits, according to the IPCC report?","reference_answer":"Land-related adaptation actions that can have mitigation co-benefits include sustainable food production, improved and sustainable forest management, soil organic carbon management, ecosystem conservation and land restoration, reduced deforestation and degradation, and reduced food loss and waste.","reference_context":"Document 70: Some land-related adaptation actions such as sustainable \nfood production, improved and sustainable forest management, \nsoil organic carbon management, ecosystem conservation and land \nrestoration, reduced deforestation and degradation, and reduced \nfood loss and waste are being undertaken, and can have mitigation \nco-bene\ufb01ts (high con\ufb01dence). Adaptation actions that increase the \nresilience of biodiversity and ecosystem services to climate change \ninclude responses like minimising additional stresses or disturbances, \nreducing fragmentation, increasing natural habitat extent, connectivity \nand heterogeneity, and protecting small-scale refugia where \nmicroclimate conditions can allow species to persist (high con\ufb01dence). \nMost innovations in urban adaptation have occurred through advances \n83 \nDocumented adaptation refers to published literature on adaptation policies, measures and actions that has been implemented and documented in peer reviewed literature, as \nopposed to adaptation that may have been planned, but not implemented. \n84 \nEffectiveness refers here to the extent to which an adaptation option is anticipated or observed to reduce climate-related risk.\n85 \n See Annex I: Glossary. \n86 \nIrrigation is effective in reducing drought risk and climate impacts in many regions and has several livelihood bene\ufb01ts, but needs appropriate management to avoid potential \nadverse outcomes, which can include accelerated depletion of groundwater and other water sources and increased soil salinization (medium con\ufb01dence). \n87 \nEbA is recognised internationally under the Convention on Biological Diversity (CBD14\/5). A related concept is Nature-based Solutions (NbS), see Annex I: Glossary.\nin disaster risk management, social safety nets and green\/blue \ninfrastructure (medium con\ufb01dence). Many adaptation measures that \nbene\ufb01t health and well-being are found in other sectors (e.g., food, \nlivelihoods, social protection, water and sanitation, infrastructure) \n(high con\ufb01dence).\n\nDocument 69: Various tools, measures and processes are available \nthat can enable, accelerate and sustain adaptation implementation \n(high con\ufb01dence). Growing public and political awareness of climate \nimpacts and risks has resulted in at least 170 countries and many cities \nincluding adaptation in their climate policies and planning processes \n(high con\ufb01dence). Decision support tools and climate services are \nincreasingly being used (very high con\ufb01dence) and pilot projects and \nlocal experiments are being implemented in different sectors (high \ncon\ufb01dence). {WGII SPM C.1, WGII SPM.C.1.1, WGII TS.D.1.3, WGII TS.D.10}\nAdaptation to water-related risks and impacts make up the majority (~60%) \nof all documented83 adaptation (high con\ufb01dence). A large number of \nthese adaptation responses are in the agriculture sector and these \ninclude on-farm water management, water storage, soil moisture \nconservation, and irrigation. Other adaptations in agriculture include \ncultivar improvements, agroforestry, community-based adaptation and \nfarm and landscape diversi\ufb01cation among others (high con\ufb01dence). \nFor inland \ufb02ooding, combinations of non-structural measures like \nearly warning systems, enhancing natural water retention such as by \nrestoring wetlands and rivers, and land use planning such as no build \nzones or upstream forest management, can reduce \ufb02ood risk (medium \ncon\ufb01dence). Some land-related adaptation actions such as sustainable \nfood production, improved and sustainable forest management, \nsoil organic carbon management, ecosystem conservation and land \nrestoration, reduced deforestation and degradation, and reduced \nfood loss and waste are being undertaken, and can have mitigation \nco-bene\ufb01ts (high con\ufb01dence). Adaptation actions that increase the \nresilience of biodiversity and ecosystem services to climate change \ninclude responses like minimising additional stresses or disturbances, \nreducing fragmentation, increasing natural habitat extent, connectivity \nand heterogeneity, and protecting small-scale refugia where \nmicroclimate conditions can allow species to persist (high con\ufb01dence).\n\nDocument 71: 85 \n See Annex I: Glossary. \n86 \nIrrigation is effective in reducing drought risk and climate impacts in many regions and has several livelihood bene\ufb01ts, but needs appropriate management to avoid potential \nadverse outcomes, which can include accelerated depletion of groundwater and other water sources and increased soil salinization (medium con\ufb01dence). \n87 \nEbA is recognised internationally under the Convention on Biological Diversity (CBD14\/5). A related concept is Nature-based Solutions (NbS), see Annex I: Glossary.\nin disaster risk management, social safety nets and green\/blue \ninfrastructure (medium con\ufb01dence). Many adaptation measures that \nbene\ufb01t health and well-being are found in other sectors (e.g., food, \nlivelihoods, social protection, water and sanitation, infrastructure) \n(high con\ufb01dence). {WGII SPM C.2.1, WGII SPM C.2.2, WGII TS.D.1.2, \nWGII TS.D.1.4, WGII TS.D.4.2, WGII TS.D.8.3, WGII 4 ES; SRCCL SPM B.1.1}\nAdaptation can generate multiple additional bene\ufb01ts such as improving \nagricultural productivity, innovation, health and well-being, food \nsecurity, livelihood, and biodiversity conservation as well as reduction \nof risks and damages (very high con\ufb01dence). {WGII SPM C1.1} \nGlobally tracked adaptation \ufb01nance has shown an upward trend \nsince AR5, but represents only a small portion of total climate \n\ufb01nance, is uneven and has developed heterogeneously across \nregions and sectors (high con\ufb01dence). Adaptation \ufb01nance has come \npredominantly from public sources, largely through grants, concessional \nand non-concessional instruments (very high con\ufb01dence). Globally, \nprivate-sector \ufb01nancing of adaptation from a variety of sources such \nas commercial \ufb01nancial institutions, institutional investors, other \nprivate equity, non-\ufb01nancial corporations, as well as communities \nand households has been limited, especially in developing countries \n(high con\ufb01dence).\n\nDocument 74: 56\nSection 2\nSection 1\nSection 2\nwetlands, rangelands, mangroves and forests); while afforestation and \nreforestation, restoration of high-carbon ecosystems, agroforestry, and \nthe reclamation of degraded soils take more time to deliver measurable \nresults. Signi\ufb01cant synergies exist between adaptation and mitigation, \nfor example through sustainable land management approaches. \nAgroecological principles and practices and other approaches \nthat work with natural processes support food security, nutrition, \nhealth and well-being, livelihoods and biodiversity, sustainability and \necosystem services. (high con\ufb01dence) {WGII SPM C.2.1, WGII SPM C.2.2, \nWGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; \nSROCC SPM C.2}\nCombinations of non-structural measures like early warning systems \nand structural measures like levees have reduced loss of lives in case \nof inland \ufb02ooding (medium con\ufb01dence) and early warning systems \nalong with \ufb02ood-proo\ufb01ng of buildings have proven to be cost-effective \nin the context of coastal \ufb02ooding under current sea level rise (high \ncon\ufb01dence). Heat Health Action Plans that include early warning and \nresponse systems are effective adaptation options for extreme heat \n(high con\ufb01dence). Effective adaptation options for water, food and \nvector-borne diseases include improving access to potable water, \nreducing exposure of water and sanitation systems to extreme weather \nevents, and improved early warning systems, surveillance, and vaccine \ndevelopment (very high con\ufb01dence). Adaptation options such as \ndisaster risk management, early warning systems, climate services \nand social safety nets have broad applicability across multiple sectors \n(high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":70,"topic":"Climate Change Action"}}
{"id":"93792c40-7312-43a3-b931-5824d4bf71cc","question":"What percentage of the heating in the climate system is accounted for by ocean warming?","reference_answer":"Ocean warming accounted for 91% of the heating in the climate system.","reference_context":"Document 29: Emissions from international aviation and shipping are not included. {WGIII Figure SPM.2}\n2.1.2. Observed Climate System Changes and Impacts to \nDate\nIt is unequivocal that human in\ufb02uence has warmed the \natmosphere, ocean and land. Widespread and rapid changes in \nthe atmosphere, ocean, cryosphere and biosphere have occurred \n(Table 2.1). The scale of recent changes across the climate system as \na whole and the present state of many aspects of the climate system \nare unprecedented over many centuries to many thousands of years. It \nis very likely that GHG emissions were the main driver74 of tropospheric \nwarming and extremely likely that human-caused stratospheric ozone \ndepletion was the main driver of stratospheric cooling between 1979 \nand the mid-1990s. It is virtually certain that the global upper ocean \n(0-700m) has warmed since the 1970s and extremely likely that \nhuman in\ufb02uence is the main driver. Ocean warming accounted for \n91% of the heating in the climate system, with land warming, ice loss \nand atmospheric warming accounting for about 5%, 3% and 1%, \nrespectively (high con\ufb01dence). Global mean sea level increased by 0.20 \n[0.15 to 0.25] m between 1901 and 2018. The average rate of sea level \nrise was 1.3 [0.6 to 2.1]mm yr-1 between 1901 and 1971, increasing to \n1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and further increasing \nto 3.7 [3.2 to \u20134.2] mm yr-1 between 2006 and 2018 (high con\ufb01dence). \nHuman in\ufb02uence was very likely the main driver of these increases \nsince at least 1971 (Figure 3.4).\n\nDocument 10: 42\nSection 2\nSection 1\nSection 2\n2.1 Observed Changes, Impacts and Attribution\nHuman activities, principally through emissions of greenhouse gases, have unequivocally caused global warming, \nwith global surface temperature reaching 1.1\u00b0C above 1850\u20131900 in 2011\u20132020. Global greenhouse gas emissions \nhave continued to increase over 2010\u20132019, with unequal historical and ongoing contributions arising from \nunsustainable energy use, land use and land-use change, lifestyles and patterns of consumption and production \nacross regions, between and within countries, and between individuals (high con\ufb01dence). Human-caused climate \nchange is already affecting many weather and climate extremes in every region across the globe. This has led to \nwidespread adverse impacts on food and water security, human health and on economies and society and related \nlosses and damages63 to nature and people (high con\ufb01dence). Vulnerable communities who have historically \ncontributed the least to current climate change are disproportionately affected (high con\ufb01dence).\n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\nSection 2: Current Status and Trends\n2.1.1. Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900.\n\nDocument 28: The height of each rectangle shows per capita emissions, the width shows the population of the region, so that the area of the rectangles \nrefers to the total emissions for each region. Emissions from international aviation and shipping are not included. In the case of two regions, the area for CO2-LULUCF is below the \naxis, indicating net CO2 removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr\u20131 (GWP100-AR6)) for the time period \n1990\u20132019. Percentage values refer to the contribution of each region to total GHG emissions in each respective time period. The single-year peak of emissions in 1997 was due to \nhigher CO2-LULUCF emissions from a forest and peat \ufb01re event in South East Asia. Regions are as grouped in Annex II of WGIII. Panel (d) shows population, gross domestic product \n(GDP) per person, emission indicators by region in 2019 for total GHG per person, and total GHG emissions intensity, together with production-based and consumption-based CO2-FFI data, \nwhich is assessed in this report up to 2018. Consumption-based emissions are emissions released to the atmosphere in order to generate the goods and services consumed by a \ncertain entity (e.g., region). Emissions from international aviation and shipping are not included. {WGIII Figure SPM.2}\n2.1.2. Observed Climate System Changes and Impacts to \nDate\nIt is unequivocal that human in\ufb02uence has warmed the \natmosphere, ocean and land. Widespread and rapid changes in \nthe atmosphere, ocean, cryosphere and biosphere have occurred \n(Table 2.1). The scale of recent changes across the climate system as \na whole and the present state of many aspects of the climate system \nare unprecedented over many centuries to many thousands of years. It \nis very likely that GHG emissions were the main driver74 of tropospheric \nwarming and extremely likely that human-caused stratospheric ozone \ndepletion was the main driver of stratospheric cooling between 1979 \nand the mid-1990s.\n\nDocument 30: Global mean sea level increased by 0.20 \n[0.15 to 0.25] m between 1901 and 2018. The average rate of sea level \nrise was 1.3 [0.6 to 2.1]mm yr-1 between 1901 and 1971, increasing to \n1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and further increasing \nto 3.7 [3.2 to \u20134.2] mm yr-1 between 2006 and 2018 (high con\ufb01dence). \nHuman in\ufb02uence was very likely the main driver of these increases \nsince at least 1971 (Figure 3.4). Human in\ufb02uence is very likely the main \ndriver of the global retreat of glaciers since the 1990s and the decrease \nin Arctic sea ice area between 1979\u20131988 and 2010\u20132019. Human \nin\ufb02uence has also very likely contributed to decreased Northern Hemisphere \nspring snow cover and surface melting of the Greenland ice sheet. It is \nvirtually certain that human-caused CO2 emissions are the main driver \nof current global acidi\ufb01cation of the surface open ocean. {WGI SPM A.1, \nWGI SPM A.1.3, WGI SPM A.1.5, WGI SPM A.1.6, WG1 SPM A1.7, \nWGI SPM A.2, WG1.SPM A.4.2; SROCC SPM.A.1, SROCC SPM A.2}\nHuman-caused climate change is already affecting many weather and \nclimate extremes in every region across the globe. Evidence of observed \nchanges in extremes such as heatwaves, heavy precipitation, droughts, \nand tropical cyclones, and, in particular, their attribution to human \nin\ufb02uence, has strengthened since AR5 (Figure 2.3).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":29,"topic":"Others"}}
{"id":"5e5d127f-4a64-4ab5-9729-2b6c2e5203c8","question":"What is the range of years for achieving 100% net zero CO2 pathways according to the data?","reference_answer":"2050-2055 [2035-2070] and 2055-2060 [2045-2070]","reference_context":"Document 169: 84\nSection 3\nSection 1\nSection 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n2030 \n43 \n[34-60]\n41 \n[31-59]\n48 \n[35-61]\n23 \n[0-44]\n21 \n[1-42]\n27 \n[13-45]\n5 \n[0-14]\n10  \n[0-27]\n2040\n \n \n \n \n \n2050 \n84 \n[73-98]\n85 \n[72-100]\n84 \n[76-93]\n75 \n[62-91]\n64 \n[53-77]\n63 \n[52-76]\n68 \n[56-83]\n49  \n[35-65]\n29\n[11-48]\n5\n[-2 to 18]\nNet zero \nCO2  \n(% net zero \npathways) \n \n2050-2055 (100%) \n[2035-2070]\n2055-2060 \n(100%) \n[2045-2070]\n2070-2075 \n(93%) \n[2055-.]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.\n\nDocument 170: ]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.]\n \n2020 to \nnet zero \nCO2  \n510 \n[330-710]\n550 \n[340-760]\n460 \n[320-590]\n720 \n[530-930]\n890 \n[640-1160]\n860 \n[640-1180]\n910 \n[720-1150]\n1210\n[970-1490]\n1780\n[1400-2360]\n2020\u2013\n2100 \n320 \n[-210-570]\n160 \n[-220-620]\n360 \n[10-540]\n400 \n[-90-620]\n800 \n[510-1140]\n790 \n[480-1150]\n800 \n[560-1050]\n1160 \n[700-1490]\n \nat peak \nwarming\n \n1.6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":169,"topic":"Climate Change Scenarios"}}
{"id":"d876c070-4c60-419d-9758-91c720dca225","question":"How can climate services contribute to reducing vulnerability and exposure of human systems?","reference_answer":"Climate services that are demand-driven and inclusive of different users and providers can improve agricultural practices, inform better water use and efficiency, and enable resilient infrastructure planning.","reference_context":"Document 270: Climate services that are demand-driven and \ninclusive of different users and providers can improve agricultural \npractices, inform better water use and ef\ufb01ciency, and enable resilient \ninfrastructure planning (high con\ufb01dence). Policy mixes that include \nweather and health insurance, social protection and adaptive safety \nnets, contingent \ufb01nance and reserve funds, and universal access to \nearly warning systems combined with effective contingency plans, can \nreduce vulnerability and exposure of human systems (high con\ufb01dence). \nIntegrating climate adaptation into social protection programs, \nincluding cash transfers and public works programs, is highly feasible \nand increases resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). Social safety nets \ncan build adaptive capacities, reduce socioeconomic vulnerability, and \nreduce risk linked to hazards (robust evidence, medium agreement). \n{WGII SPM C.2.9, WGII SPM C.2.13, WGII Cross-Chapter Box FEASIB in \nChapter 18; SRCCL SPM C.1.4, SRCCL SPM D.1.2}\nReducing future risks of involuntary migration and displacement \ndue to climate change is possible through cooperative, international \nefforts to enhance institutional adaptive capacity and sustainable \ndevelopment (high con\ufb01dence). Increasing adaptive capacity minimises \nrisk associated with involuntary migration and immobility and improves \nthe degree of choice under which migration decisions are made, while \npolicy interventions can remove barriers and expand the alternatives for \nsafe, orderly and regular migration that allows vulnerable people to adapt \nto climate change (high con\ufb01dence). {WGII SPM C.2.12, WGII TS.D.8.6, \nWGII Cross-Chapter Box MIGRATE in Chapter 7}\nAccelerating commitment and follow-through by the private \nsector is promoted for instance by building business cases for \nadaptation, accountability and transparency mechanisms, and \nmonitoring and evaluation of adaptation progress (medium \ncon\ufb01dence).\n\nDocument 271: Increasing adaptive capacity minimises \nrisk associated with involuntary migration and immobility and improves \nthe degree of choice under which migration decisions are made, while \npolicy interventions can remove barriers and expand the alternatives for \nsafe, orderly and regular migration that allows vulnerable people to adapt \nto climate change (high con\ufb01dence). {WGII SPM C.2.12, WGII TS.D.8.6, \nWGII Cross-Chapter Box MIGRATE in Chapter 7}\nAccelerating commitment and follow-through by the private \nsector is promoted for instance by building business cases for \nadaptation, accountability and transparency mechanisms, and \nmonitoring and evaluation of adaptation progress (medium \ncon\ufb01dence). Integrated pathways for managing climate risks will \nbe most suitable when so-called \u2018low-regret\u2019 anticipatory options are \nestablished jointly across sectors in a timely manner and are feasible \nand effective in their local context, and when path dependencies and \nmaladaptations across sectors are avoided (high con\ufb01dence). Sustained \nadaptation actions are strengthened by mainstreaming adaptation into \ninstitutional budget and policy planning cycles, statutory planning, \nmonitoring and evaluation frameworks and into recovery efforts \nfrom disaster events (high con\ufb01dence). Instruments that incorporate \nadaptation such as policy and legal frameworks, behavioural incentives, \nand economic instruments that address market failures, such as \nclimate risk disclosure, inclusive and deliberative processes strengthen \nadaptation actions by public and private actors (medium con\ufb01dence). \n{WGII SPM C.5.1, WGII SPM C.5.2, WGII TS.D.10.4}\n\nDocument 269: Climate literacy \nand information provided through climate services and community \napproaches, including those that are informed by Indigenous Knowledge \nand local knowledge, can accelerate behavioural changes and planning \n(high con\ufb01dence). Educational and information programmes, using \nthe arts, participatory modelling and citizen science can facilitate \nawareness, heighten risk perception, and in\ufb02uence behaviours (high \ncon\ufb01dence). The way choices are presented can enable adoption of low \nGHG intensive socio-cultural options, such as shifts to balanced, sustainable \nhealthy diets, reduced food waste, and active mobility (high con\ufb01dence). \nJudicious labelling, framing, and communication of social norms can \nincrease the effect of mandates, subsidies, or taxes (medium con\ufb01dence). \n{WGII SPM C.5.3, WGII TS.D.10.1; WGIII SPM C.10, WGIII SPM C.10.2, \nWGIII SPM C.10.3, WGIII SPM E.2.2, WGIII Figure SPM.6, WGIII TS.6.1, \n5.4; SR1.5 SPM D.5.6; SROCC SPM C.4}\nA range of adaptation options, such as disaster risk management, \nearly warning systems, climate services and risk spreading and \nsharing approaches, have broad applicability across sectors \nand provide greater risk reduction bene\ufb01ts when combined \n(high con\ufb01dence). Climate services that are demand-driven and \ninclusive of different users and providers can improve agricultural \npractices, inform better water use and ef\ufb01ciency, and enable resilient \ninfrastructure planning (high con\ufb01dence). Policy mixes that include \nweather and health insurance, social protection and adaptive safety \nnets, contingent \ufb01nance and reserve funds, and universal access to \nearly warning systems combined with effective contingency plans, can \nreduce vulnerability and exposure of human systems (high con\ufb01dence). \nIntegrating climate adaptation into social protection programs, \nincluding cash transfers and public works programs, is highly feasible \nand increases resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence).\n\nDocument 241: Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence). Equity remains a \ncentral element in the UN climate regime, notwithstanding shifts \nin differentiation between states over time and challenges in \nassessing fair shares. Ambitious mitigation pathways imply large and \nsometimes disruptive changes in economic structure, with signi\ufb01cant \ndistributional consequences, within and between countries, including \nshifting of income and employment during the transition from high to \nlow emissions activities (high con\ufb01dence). While some jobs may be lost, \nlow-emissions development can also open up opportunities to enhance \nskills and create jobs (high con\ufb01dence). Broadening equitable access \nto \ufb01nance, technologies and governance that facilitate mitigation, and \nconsideration of climate justice can help equitable sharing of bene\ufb01ts \n4.4 Equity and Inclusion in Climate Change Action","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":270,"topic":"Climate Change Action"}}
{"id":"f953c775-9499-4d62-abd7-ccf7af1cc395","question":"What percentage of the global population lives in countries with per capita emissions greater than 6 tCO2-eq?","reference_answer":"Around 48% of the global population in 2019 lives in countries emitting on average more than 6 tCO2-eq per capita.","reference_context":"Document 20: Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence). In 2019, approximately 34% (20 GtCO2-eq) \nof net global GHG emissions came from the energy sector, 24% \n(14 GtCO2-eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% \n(8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2-eq) from buildings71 \n(high con\ufb01dence). Average annual GHG emissions growth between \n69 \nGHG emission metrics are used to express emissions of different GHGs in a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalents (CO2-eq) using \nthe Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports \ncontain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of \nmetric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the complexity of the physical climate \nsystem and its response to past and future GHG emissions.\n\nDocument 19: (high confidence) \n{WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, \nWGIII Figure SPM.2}\nRegional contributions to global human-caused GHG emissions \ncontinue to differ widely. Historical contributions of CO2 emissions \nvary substantially across regions in terms of total magnitude, but also \nin terms of contributions to CO2-FFI (1650 \u00b1 73 GtCO2-eq) and net \nCO2-LULUCF (760 \u00b1 220 GtCO2-eq) emissions (Figure 2.2). Variations \nin regional and national per capita emissions partly re\ufb02ect different \ndevelopment stages, but they also vary widely at similar income \nlevels. Average per capita net anthropogenic GHG emissions in 2019 \nranged from 2.6 tCO2-eq to 19 tCO2-eq across regions (Figure 2.2). \nLeast Developed Countries (LDCs) and Small Island Developing States (SIDS) \nhave much lower per capita emissions (1.7 tCO2-eq and 4.6 tCO2-eq, \nrespectively) than the global average (6.9 tCO2-eq), excluding \nCO2-LULUCF\n. Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence).\n\nDocument 21: Average annual GHG emissions growth between \n69 \nGHG emission metrics are used to express emissions of different GHGs in a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalents (CO2-eq) using \nthe Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports \ncontain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of \nmetric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the complexity of the physical climate \nsystem and its response to past and future GHG emissions. {WGI SPM D.1.8, WGI 7.6; WGIII SPM B.1, WGIII Cross-Chapter Box 2.2} (Annex I: Glossary)\n70 \nTerritorial emissions\n71 \nGHG emission levels are rounded to two signi\ufb01cant digits; as a consequence, small differences in sums due to rounding may occur. {WGIII SPM footnote 8}\n72 \nComprising a gross sink of -12.5 (\u00b13.2) GtCO2 yr-1 resulting from responses of all land to both anthropogenic environmental change and natural climate variability, and \nnet anthropogenic CO2-LULUCF emissions +5.9 (\u00b14.1) GtCO2 yr-1 based on book-keeping models. {WGIII SPM Footnote 14}\n73 \nThis estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirect emissions from outside urban areas related to \nthe production of electricity, goods and services consumed in cities. These estimates include all CO2 and CH4 emission categories except for aviation and marine bunker fuels, \nland-use change, forestry and agriculture.\n\nDocument 18: 44\nSection 2\nSection 1\nSection 2\nAverage annual GHG emissions during 2010\u20132019 were higher \nthan in any previous decade, but the rate of growth between \n2010 and 2019 (1.3% yr-1) was lower than that between 2000 \nand 2009 (2.1% yr-1)69. Historical cumulative net CO2 emissions from \n1850 to 2019 were 2400 \u00b1240 GtCO2. Of these, more than half (58%) \noccurred between 1850 and 1989 [1400 \u00b1195 GtCO2], and about 42% \nbetween 1990 and 2019 [1000 \u00b190 GtCO2]. Global net anthropogenic \nGHG emissions have been estimated to be 59\u00b16.6 GtCO2-eq in 2019, \nabout 12% (6.5 GtCO2-eq) higher than in 2010 and 54% (21 GtCO2-eq) \nhigher than in 1990. By 2019, the largest growth in gross emissions \noccurred in CO2 from fossil fuels and industry (CO2-FFI) followed by \nCH4, whereas the highest relative growth occurred in fluorinated \ngases (F-gases), starting from low levels in 1990. (high confidence) \n{WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, \nWGIII Figure SPM.2}\nRegional contributions to global human-caused GHG emissions \ncontinue to differ widely. Historical contributions of CO2 emissions \nvary substantially across regions in terms of total magnitude, but also \nin terms of contributions to CO2-FFI (1650 \u00b1 73 GtCO2-eq) and net \nCO2-LULUCF (760 \u00b1 220 GtCO2-eq) emissions (Figure 2.2). Variations \nin regional and national per capita emissions partly re\ufb02ect different \ndevelopment stages, but they also vary widely at similar income \nlevels.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":20,"topic":"Global GHG Emissions"}}
{"id":"d49639f8-d424-46a8-b375-a3d56509caaa","question":"What are the benefits of ecosystem-based solutions for sea level rise and land subsidence?","reference_answer":"Ecosystem-based solutions such as wetlands provide co-benefits for the environment and climate mitigation, and reduce costs for flood defenses. However, they have site-specific physical limits, at least above 1.5\u00baC of global warming, and lose effectiveness at high rates of sea level rise beyond 0.5 to 1 cm yr-1.","reference_context":"Document 261: 106\nSection 4\nSection 1\nSection 4\nand marginalised communities including people living in informal \nsettlements (high con\ufb01dence). {WGII SPM C.2.5, WGII SPM C.2.6, WGII \nSPM C.2.7, WGII SPM D.3.2, WGII TS.E.1.4, WGII Cross-Chapter Box FEAS; \nWGIII SPM C.6, WGIII SPM C.6.2, WGIII SPM D.1.3, WGIII SPM D.2.1}\nResponses to ongoing sea level rise and land subsidence in low-lying \ncoastal cities and settlements and small islands include protection, \naccommodation, advance and planned relocation. These responses \nare more effective if combined and\/or sequenced, planned well ahead, \naligned with sociocultural values and development priorities, and \nunderpinned by inclusive community engagement processes. (high \ncon\ufb01dence) {WGII SPM C.2.8}\n4.5.4. Land, Ocean, Food, and Water\nThere is substantial mitigation and adaptation potential from \noptions in agriculture, forestry and other land use, and in the \noceans, that could be upscaled in the near term across most \nregions (high con\ufb01dence) (Figure 4.5). Conservation, improved \nmanagement, and restoration of forests and other ecosystems offer \nthe largest share of economic mitigation potential, with reduced \ndeforestation in tropical regions having the highest total mitigation \npotential. Ecosystem restoration, reforestation, and afforestation can \nlead to trade-offs due to competing demands on land. Minimizing \ntrade-offs requires integrated approaches to meet multiple objectives \nincluding food security. Demand-side measures (shifting to sustainable \nhealthy diets and reducing food loss\/waste) and sustainable agricultural \nintensi\ufb01cation can reduce ecosystem conversion and CH4 and N2O emissions, \nand free up land for reforestation and ecosystem restoration. \nSustainably sourced agriculture and forest products, including \nlong-lived wood products, can be used instead of more GHG-intensive \nproducts in other sectors.\n\nDocument 265: Enhancing natural water retention \nsuch as by restoring wetlands and rivers, land use planning such as no \nbuild zones or upstream forest management, can further reduce \ufb02ood risk \n(medium con\ufb01dence). For inland \ufb02ooding, combinations of non-structural \nmeasures like early warning systems and structural measures like levees \nhave reduced loss of lives (medium confidence), but hard defences \nagainst flooding or sea level rise can also be maladaptive \n(high con\ufb01dence). {WGII SPM C.2.1, WGII SPM C.4.1, WGII SPM C.4.2, \nWGII SPM C.2.5}\nProtection and restoration of coastal \u2018blue carbon\u2019 ecosystems \n(e.g., mangroves, tidal marshes and seagrass meadows) could \nreduce emissions and\/or increase carbon uptake and storage (medium \ncon\ufb01dence). Coastal wetlands protect against coastal erosion \nand \ufb02ooding (very high con\ufb01dence). Strengthening precautionary \napproaches, such as rebuilding overexploited or depleted \ufb01sheries, and \nresponsiveness of existing \ufb01sheries management strategies reduces \nnegative climate change impacts on \ufb01sheries, with bene\ufb01ts for regional \neconomies and livelihoods (medium con\ufb01dence). Ecosystem-based \nmanagement in fisheries and aquaculture supports food security, \nbiodiversity, human health and well-being (high confidence). \n{WGII SPM C.2.2, WGII SPM C.2; SROCC SPM C2.3, SROCC SPM C.2.4} \n4.5.5. Health and Nutrition\nHuman health will bene\ufb01t from integrated mitigation and \nadaptation options that mainstream health into food, \ninfrastructure, social protection, and water policies (very high \ncon\ufb01dence). Balanced and sustainable healthy diets156 and reduced \nfood loss and waste present important opportunities for adaptation \nand mitigation while generating signi\ufb01cant co-bene\ufb01ts in terms \nof biodiversity and human health (high con\ufb01dence).\n\nDocument 157: 79\nLong-Term Climate and Development Futures\nSection 3\nlong-term planning and implementation of adaptation actions with \nbene\ufb01ts to many sectors and systems. (high con\ufb01dence) {WGII SPM C.4, \nWGII SPM.C.4.1, WGII SPM C.4.2, WGII SPM C.4.3}\nSea level rise poses a distinctive and severe adaptation challenge \nas it implies both dealing with slow onset changes and increases \nin the frequency and magnitude of extreme sea level events (high \ncon\ufb01dence). Such adaptation challenges would occur much earlier \nunder high rates of sea level rise (high con\ufb01dence). Responses to ongoing \nsea level rise and land subsidence include protection, accommodation, \nadvance and planned relocation (high con\ufb01dence). These responses \nare more effective if combined and\/or sequenced, planned well ahead, \naligned with sociocultural values and underpinned by inclusive \ncommunity engagement processes (high con\ufb01dence). Ecosystem-based \nsolutions such as wetlands provide co-bene\ufb01ts for the environment \nand climate mitigation, and reduce costs for \ufb02ood defences (medium \ncon\ufb01dence), but have site-speci\ufb01c physical limits, at least above 1.5\u00baC \nof global warming (high con\ufb01dence) and lose effectiveness at high \nrates of sea level rise beyond 0.5 to 1 cm yr-1 (medium con\ufb01dence). \nSeawalls can be maladaptive as they effectively reduce impacts in the \nshort term but can also result in lock-ins and increase exposure to climate \nrisks in the long term unless they are integrated into a long-term adaptive \nplan (high con\ufb01dence). {WGI SPM C.2.5; WGII SPM C.2.8, WGII SPM C.4.1; \nWGII 13.10, WGII Cross-Chapter Box SLR; SROCC SPM B.9, SROCC SPM C.3.2, \nSROCC Figure SPM.4, SROCC Figure SPM.5c} (Figure 3.4)\n\nDocument 74: 56\nSection 2\nSection 1\nSection 2\nwetlands, rangelands, mangroves and forests); while afforestation and \nreforestation, restoration of high-carbon ecosystems, agroforestry, and \nthe reclamation of degraded soils take more time to deliver measurable \nresults. Signi\ufb01cant synergies exist between adaptation and mitigation, \nfor example through sustainable land management approaches. \nAgroecological principles and practices and other approaches \nthat work with natural processes support food security, nutrition, \nhealth and well-being, livelihoods and biodiversity, sustainability and \necosystem services. (high con\ufb01dence) {WGII SPM C.2.1, WGII SPM C.2.2, \nWGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; \nSROCC SPM C.2}\nCombinations of non-structural measures like early warning systems \nand structural measures like levees have reduced loss of lives in case \nof inland \ufb02ooding (medium con\ufb01dence) and early warning systems \nalong with \ufb02ood-proo\ufb01ng of buildings have proven to be cost-effective \nin the context of coastal \ufb02ooding under current sea level rise (high \ncon\ufb01dence). Heat Health Action Plans that include early warning and \nresponse systems are effective adaptation options for extreme heat \n(high con\ufb01dence). Effective adaptation options for water, food and \nvector-borne diseases include improving access to potable water, \nreducing exposure of water and sanitation systems to extreme weather \nevents, and improved early warning systems, surveillance, and vaccine \ndevelopment (very high con\ufb01dence). Adaptation options such as \ndisaster risk management, early warning systems, climate services \nand social safety nets have broad applicability across multiple sectors \n(high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":261,"topic":"Climate Change Action"}}
{"id":"57a4649a-8d7f-4d7d-8184-27b018661ed0","question":"What is the range of global GHG emissions reduction potential in end-use sectors by 2050 compared to baseline scenarios?","reference_answer":"40\u201370%","reference_context":"Document 252: The green arrow represents the demand-side emissions reductions potentials. The range in potential is shown by a line connecting dots displaying \nthe highest and the lowest potentials reported in the literature. Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns \nenabled by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in end-use sectors (buildings, land transport, \nfood) by 40\u201370% by 2050 compared to baseline scenarios, while some regions and socioeconomic groups require additional energy and resources. The last row shows how demand-\nside mitigation options in other sectors can in\ufb02uence overall electricity demand. The dark grey bar shows the projected increase in electricity demand above the 2050 baseline due \nto increasing electri\ufb01cation in the other sectors. Based on a bottom-up assessment, this projected increase in electricity demand can be avoided through demand-side mitigation \noptions in the domains of infrastructure use and socio-cultural factors that in\ufb02uence electricity usage in industry, land transport, and buildings (green arrow). {WGII Figure SPM.4, \nWGII Cross-Chapter Box FEASIB in Chapter 18; WGIII SPM C.10, WGIII 12.2.1, WGIII 12.2.2, WGIII Figure SPM.6, WGIII Figure SPM.7}\n4.5.1. Energy Systems\nRapid and deep reductions in GHG emissions require major \nenergy system transitions (high con\ufb01dence). Adaptation options \ncan help reduce climate-related risks to the energy system \n(very high con\ufb01dence). Net zero CO2 energy systems entail: a \nsubstantial reduction in overall fossil fuel use, minimal use of \nunabated fossil fuels153, and use of Carbon Capture and Storage in \nthe remaining fossil fuel systems; electricity systems that emit no \nnet CO2; widespread electrification; alternative energy carriers in \napplications less amenable to electrification; energy conservation \nand efficiency; and greater integration across the energy system \n(high confidence).\n\nDocument 251: Where a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such \nas geographical location, resource availability, and regional circumstances, and the colours indicate the range of estimates. The uncertainty in the total potential is typically 25\u201350%. \nWhen interpreting this \ufb01gure, the following should be taken into account: (1) The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) \nbeing displaced, the rate of new technology adoption, and several other factors; (2) Different options have different feasibilities beyond the cost aspects, which are not re\ufb02ected in \nthe \ufb01gure; and (3) Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included. \nPanel (b) displays the indicative potential of demand-side mitigation options for 2050. Potentials are estimated based on approximately 500 bottom-up studies representing all \nglobal regions. The baseline (white bar) is provided by the sectoral mean GHG emissions in 2050 of the two scenarios (IEA-STEPS and IP_ModAct) consistent with policies announced \nby national governments until 2020. The green arrow represents the demand-side emissions reductions potentials. The range in potential is shown by a line connecting dots displaying \nthe highest and the lowest potentials reported in the literature. Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns \nenabled by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in end-use sectors (buildings, land transport, \nfood) by 40\u201370% by 2050 compared to baseline scenarios, while some regions and socioeconomic groups require additional energy and resources. The last row shows how demand-\nside mitigation options in other sectors can in\ufb02uence overall electricity demand. The dark grey bar shows the projected increase in electricity demand above the 2050 baseline due \nto increasing electri\ufb01cation in the other sectors.\n\nDocument 248: WASH, nutrition and diets)\nGreen infrastructure and\necosystem services\nSustainable land use and urban planning\nSustainable urban water management\nClimate services, including\nEarly Warning Systems\nLivelihood diversi\ufb01cation\nDisaster risk management\nSocial safety nets\nRisk spreading and sharing\nPlanned relocation and resettlement\nHuman migration\nAgroforestry\nSustainable aquaculture and \ufb01sheries\nEf\ufb01cient livestock systems\nBiodiversity management and\necosystem connectivity\nIntegrated coastal zone management\nWater use ef\ufb01ciency and water\nresource management\nImproved cropland management\nCoastal defence and hardening\nForest-based adaptation\nResilient power systems\nEnergy reliability (e.g.\ndiversi\ufb01cation, access, stability)\nImprove water use ef\ufb01ciency\nPotential\nfeasibility\nup to 1.5\u00b0C\nENERGY SUPPLY\nLAND, WATER, FOOD\nHEALTH\nSETTLEMENTS AND\nINFRASTRUCTURE\nSOCIETY, LIVELIHOOD\nAND ECONOMY\nINDUSTRY AND WASTE\n20\n10\n0\n20\n10\n0\nElectricity\nLand transport\nBuildings\nIndustry\nFood\n67% \n66% \n29% \n44% \n73% reduction (before \nadditional electri\ufb01cation) \nAdditional electri\ufb01cation (+60%)\nGtCO2-eq\/yr \nGtCO2\/yr \nKey\nTotal emissions (2050)\nPercentage of possible reduction \nDemand-side mitigation potential\nPotential range\n% \nEf\ufb01cient lighting, appliances\nand equipment\nEf\ufb01cient shipping and aviation\nAvoid demand for energy services\nEf\ufb01cient buildings\nElectric vehicles\nPublic transport and bicycling\nBiofuels for transport\nOnsite renewables\nFuel ef\ufb01cient vehicles\nShift to sustainable healthy diets\noptions costing 100 USD tCO2-eq-1 or \nless could reduce global emissions by \nat least half of the 2019 level by 2030\nb) Potential of demand-side \nmitigation options by 2050\nthe range of GHG emissions \nreduction potential is 40-70% \nin these end-use sectors\n\nDocument 253: Energy Systems\nRapid and deep reductions in GHG emissions require major \nenergy system transitions (high con\ufb01dence). Adaptation options \ncan help reduce climate-related risks to the energy system \n(very high con\ufb01dence). Net zero CO2 energy systems entail: a \nsubstantial reduction in overall fossil fuel use, minimal use of \nunabated fossil fuels153, and use of Carbon Capture and Storage in \nthe remaining fossil fuel systems; electricity systems that emit no \nnet CO2; widespread electrification; alternative energy carriers in \napplications less amenable to electrification; energy conservation \nand efficiency; and greater integration across the energy system \n(high confidence). Large contributions to emissions reductions can \ncome from options costing less than USD 20 tCO2-eq\u20131, including \nsolar and wind energy, energy ef\ufb01ciency improvements, and CH4 \n(methane) emissions reductions (from coal mining, oil and gas, and \nwaste) (medium confidence).154 Many of these response options are \ntechnically viable and are supported by the public (high confidence). \nMaintaining emission-intensive systems may, in some regions and \nsectors, be more expensive than transitioning to low emission \nsystems (high confidence). {WGII SPM C.2.10; WGIII SPM C.4.1, \nWGIII SPM C.4.2, WGIII SPM C.12.1, WGIII SPM E.1.1, WGIII TS.5.1} \nClimate change and related extreme events will affect future energy \nsystems, including hydropower production, bioenergy yields, thermal \npower plant ef\ufb01ciencies, and demands for heating and cooling (high \n153 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50\u201380% of fugitive methane emissions from energy supply. {WGIII SPM footnote 54}\n154 The mitigation potentials and mitigation costs of individual technologies in a speci\ufb01c context or region may differ greatly from the provided estimates (medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":252,"topic":"Climate Change Action"}}
{"id":"0447bba5-e350-46fe-9c3f-03825c091c70","question":"What are the categories of the assessed modelled global pathways that limit warming to 1.5\u00b0C with no or limited overshoot according to the IPCC report?","reference_answer":"The categories of the assessed modelled global pathways that limit warming to 1.5\u00b0C with no or limited overshoot are C1 according to the IPCC report.","reference_context":"Document 85: Panel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n \n- Limit to 2\u00b0C (>67%) or return warming to 1.5\u00b0C (>50%) after a high overshoot, NDCs until 2030: Pathways with GHG emissions until 2030 associated with the \nimplementation of NDCs announced prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2\u00b0C (C3b, WGIII Table SPM.2) or to return \nwarming to 1.5\u00b0C with a probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, WGIII Table SPM.2). \n \n- Limit to 2\u00b0C (>67%) with immediate action: Pathways that limit warming to 2\u00b0C (>67%) with immediate action after 2020 (C3a, WGIII Table SPM.2). \n \n- Limit to 1.5\u00b0C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5\u00b0C with no or limited overshoot (C1, WGIII Table SPM.2 C1). \nAll these pathways assume immediate action after 2020. Past GHG emissions for 2010-2015 used to project global warming outcomes of the modelled pathways are shown by a \nblack line. Panel b shows a snapshot of the GHG emission ranges of the modelled pathways in 2030 and projected emissions outcomes from near-term policy assessments in 2030 \nfrom WGIII Chapter 4.2 (Tables 4.2 and 4.3; median and full range). GHG emissions are CO2-equivalent using GWP100 from AR6 WGI. {WGIII Figure SPM.4, WGIII 3.5, 4.2, Table 4.2, \nTable 4.3, Cross-Chapter Box 4 in Chapter 4} (Table 3.1, Cross-Section Box.2)\n\nDocument 84: 59\nCurrent Status and Trends\nSection 2\na) Global GHG emissions\nb) 2030\n10\n20\n30\n0\n40\n50\n60\n70\n10\n20\n30\n0\n40\n50\n60\n70\nGHG emissions (GtCO2-eq\/yr)\n2020\n2025\n2015\n2010\n2030\n2035\n2040\n2045\n2050\nLimit warming to 2\u00baC (>67%)\nor 1.5 (>50%) after high\novershoot with NDCs until 2030\nTrend from implemented policies\n2019\nLimit warming to\n1.5\u00baC (>50%) with \nno or limited overshoot\nLimit warming \nto 2\u00baC (>67%)\nto be on-track to limit \nwarming to 1.5\u00b0C, \nwe need much more \nreduction by 2030\n-4%\n+5%\n-26%\n-43%\nProjected global GHG emissions from NDCs announced prior to \nCOP26 would make it likely that warming will exceed 1.5\u00b0C and \nalso make it harder after 2030 to limit warming to below 2\u00b0C\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nFigure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), and projected emission outcomes from near-term policy assessments for 2030 (Panel b). \nPanel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n\nDocument 102: The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8). Methods to project global warming associated with the \nmodelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII \nTable 3.1} (Table 3.1, Cross-Section Box.2 Figure 1)\n102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019.\n\nDocument 182: Top row: GHG, CO2 and CH4 emissions over time (in \nGtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour \n(blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows \npathways that limit warming to 2\u00b0C (>67%) (C3). Bottom row: Panel (c) shows median (vertical line), likely (bar) and very likely (thin lines) timing of reaching net zero GHG \nand CO2 emissions for global modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) (left) or 2\u00b0C (>67%) (C3) (right). {WGIII Figure SPM.5}\n3.3.3 Sectoral Contributions to Mitigation\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) or \nlower by 2100 involve rapid and deep and in most cases immediate \nGHG emissions reductions in all sectors (see also 4.1, 4.5). Reductions \nin GHG emissions in industry, transport, buildings, and urban areas \ncan be achieved through a combination of energy ef\ufb01ciency and \nconservation and a transition to low-GHG technologies and energy \ncarriers (see also 4.5, Figure 4.4). Socio-cultural options and behavioural \nchange can reduce global GHG emissions of end-use sectors, with most \nof the potential in developed countries, if combined with improved \n136 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage is available. When CO2 is captured directly from the \natmosphere (DACCS), or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO2 capture and subsurface injection is a mature technology for \ngas processing and enhanced oil recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production, where it \nis a critical mitigation option.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":85,"topic":"Climate Change Scenarios"}}
{"id":"843fe220-c247-4821-85fc-f2b469d289f1","question":"What are the three complementary roles of Carbon Dioxide Removal (CDR) according to the IPCC report?","reference_answer":"CDR can fulfill three complementary roles: 1) lowering net CO2 or net GHG emissions in the near term, 2) counterbalancing 'hard-to-abate' residual emissions to help reach net zero CO2 or GHG emissions, and 3) achieving net negative CO2 or GHG emissions if deployed at levels exceeding annual residual emissions.","reference_context":"Document 193: (high con\ufb01dence) {WGII SPM B.5.4, WGII SPM C.2.4; \nWGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5; SRCCL SPM B.3, \nSRCCL SPM B.7.3, SRCCL Figure SPM.3}\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\nModelled pathways that assume using resources more ef\ufb01ciently or shift \nglobal development towards sustainability include fewer challenges, such \nas dependence on CDR and pressure on land and biodiversity, and have \nthe most pronounced synergies with respect to sustainable development \n(high con\ufb01dence). {WGIII SPM C.3.6; SR1.5 SPM D.4.2} \nStrengthening climate change mitigation action entails more \nrapid transitions and higher up-front investments, but brings \nbene\ufb01ts from avoiding damages from climate change and \nreduced adaptation costs. The aggregate effects of climate change \nmitigation on global GDP (excluding damages from climate change and \nadaptation costs) are small compared to global projected GDP growth. \nProjected estimates of global aggregate net economic damages and \nthe costs of adaptation generally increase with global warming level. \n(high con\ufb01dence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, \nWGIII SPM C.12.3} \nCost-bene\ufb01t analysis remains limited in its ability to represent all \ndamages from climate change, including non-monetary damages, \nor to capture the heterogeneous nature of damages and the risk of \ncatastrophic damages (high con\ufb01dence).\n\nDocument 196: Accelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\n\nDocument 195: {WGII SPM B.4, WGII \nSPM B.6; WGIII SPM C.12, WGIII SPM C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; \nSR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6}\nConsidering other sustainable development dimensions, such as the \npotentially strong economic bene\ufb01ts on human health from air quality \nimprovement, may enhance the estimated bene\ufb01ts of mitigation \n(medium con\ufb01dence). The economic effects of strengthened mitigation \naction vary across regions and countries, depending notably on economic \nstructure, regional emissions reductions, policy design and level of \ninternational cooperation (high con\ufb01dence). Ambitious mitigation \npathways imply large and sometimes disruptive changes in economic \nstructure, with implications for near-term actions (Section 4.2), equity \n(Section 4.4), sustainability (Section 4.6), and \ufb01nance (Section 4.8) \n(high con\ufb01dence). {WGIII SPM C.12.2, WGIII SPM D.3.2, WGIII TS.4.2}\n3.4 Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development\nMitigation and adaptation can lead to synergies and trade-offs with sustainable development (high con\ufb01dence). \nAccelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence).\n\nDocument 186: All assessed modelled pathways \nthat limit warming to 2\u00b0C (>67%) or lower by 2100 include land-based \nmitigation and land-use change, with most including different \ncombinations of reforestation, afforestation, reduced deforestation, and \nbioenergy. However, accumulated carbon in vegetation and soils is at \nrisk from future loss (or sink reversal) triggered by climate change and \ndisturbances such as \ufb02ood, drought, \ufb01re, or pest outbreaks, or future \npoor management. (high con\ufb01dence) {WGI SPM B.4.3; WGII SPM B.2.3, \nWGII SPM B.5.4; WGIII SPM C.9, WGIII SPM C.11.3, WGIII SPM D.2.3, \nWGIII TS.4.2, 3.4; SR1.5 SPM C.2.5; SRCCL SPM B.1.4, SRCCL SPM B.3, \nSRCCL SPM B.7}\nIn addition to deep, rapid, and sustained emission reductions, \nCDR can ful\ufb01l three complementary roles: lowering net CO2 \nor net GHG emissions in the near term; counterbalancing \n\u2018hard-to-abate\u2019 residual emissions (e.g., some emissions from \nagriculture, aviation, shipping, industrial processes) to help reach \nnet zero CO2 or GHG emissions, and achieving net negative \nCO2 or GHG emissions if deployed at levels exceeding annual \nresidual emissions (high con\ufb01dence). CDR methods vary in terms \nof their maturity, removal process, time scale of carbon storage, storage \nmedium, mitigation potential, cost, co-bene\ufb01ts, impacts and risks, and \ngovernance requirements (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":193,"topic":"Climate Change Action"}}
{"id":"50b11d0b-f672-41e7-b345-21910f823499","question":"What are the observed impacts of climate change on urban infrastructure and the well-being of urban residents?","reference_answer":"Urban infrastructure, including transportation, water, sanitation, and energy systems, has been compromised by extreme and slow-onset events, with resulting economic losses, disruptions of services, and impacts to well-being. Observed impacts are concentrated amongst economically and socially marginalized urban residents, such as those living in informal settlements.","reference_context":"Document 51: Individual livelihoods have been \naffected through changes in agricultural productivity, impacts on human \nhealth and food security, destruction of homes and infrastructure, and loss \nof property and income, with adverse effects on gender and social equity \n(high con\ufb01dence). Tropical cyclones have reduced economic growth in \nthe short-term (high con\ufb01dence). Event attribution studies and physical \nunderstanding indicate that human-caused climate change increases \nheavy precipitation associated with tropical cyclones (high con\ufb01dence). \nWild\ufb01res in many regions have affected built assets, economic activity, \nand health (medium to high con\ufb01dence). In cities and settlements, climate \nimpacts to key infrastructure are leading to losses and damages across water \nand food systems, and affect economic activity, with impacts extending \nbeyond the area directly impacted by the climate hazard (high con\ufb01dence). \n{WGI SPM A.3.4; WGII SPM B.1.6, WGII SPM B.5.2, WGII SPM B.5.3} \nClimate change has caused widespread adverse impacts \nand related losses and damages to nature and people (high \ncon\ufb01dence). Losses and damages are unequally distributed across \nsystems, regions and sectors (high con\ufb01dence). Cultural losses, related \n80 \nSee Annex 1: Glossary. \n81 \nGovernance: The structures, processes and actions through which private and public actors interact to address societal goals. This includes formal and informal institutions and \nthe associated norms, rules, laws and procedures for deciding, managing, implementing and monitoring policies and measures at any geographic or political scale, from global \nto local. {WGII SPM Footnote 31}\nto tangible and intangible heritage, threaten adaptive capacity and may \nresult in irrevocable losses of sense of belonging, valued cultural practices, \nidentity and home, particularly for Indigenous Peoples and those more \ndirectly reliant on the environment for subsistence (medium con\ufb01dence). \nFor example, changes in snow cover, lake and river ice, and permafrost \nin many Arctic regions, are harming the livelihoods and cultural identity \nof Arctic residents including Indigenous populations (high con\ufb01dence).\n\nDocument 50: Compound extreme events include increases in the \nfrequency of concurrent heatwaves and droughts (high con\ufb01dence); \ufb01re \nweather in some regions (medium con\ufb01dence); and compound \ufb02ooding in \nsome locations (medium con\ufb01dence). Multiple risks interact, generating \nnew sources of vulnerability to climate hazards, and compounding \noverall risk (high con\ufb01dence). Compound climate hazards can overwhelm \nadaptive capacity and substantially increase damage (high con\ufb01dence)). \n{WGI SPM A.3.5; WGII SPM. B.5.1, WGII TS.C.11.3}\nEconomic \nimpacts \nattributable \nto \nclimate \nchange \nare \nincreasingly \naffecting peoples\u2019 livelihoods and are causing economic and \nsocietal impacts across national boundaries (high con\ufb01dence). \nEconomic damages from climate change have been detected in \nclimate-exposed sectors, with regional effects to agriculture, forestry, \n\ufb01shery, energy, and tourism, and through outdoor labour productivity \n(high con\ufb01dence) with some exceptions of positive impacts in regions \nwith low energy demand and comparative advantages in agricultural \nmarkets and tourism (high con\ufb01dence). Individual livelihoods have been \naffected through changes in agricultural productivity, impacts on human \nhealth and food security, destruction of homes and infrastructure, and loss \nof property and income, with adverse effects on gender and social equity \n(high con\ufb01dence). Tropical cyclones have reduced economic growth in \nthe short-term (high con\ufb01dence). Event attribution studies and physical \nunderstanding indicate that human-caused climate change increases \nheavy precipitation associated with tropical cyclones (high con\ufb01dence). \nWild\ufb01res in many regions have affected built assets, economic activity, \nand health (medium to high con\ufb01dence). In cities and settlements, climate \nimpacts to key infrastructure are leading to losses and damages across water \nand food systems, and affect economic activity, with impacts extending \nbeyond the area directly impacted by the climate hazard (high con\ufb01dence).\n\nDocument 49: 51\nCurrent Status and Trends\nSection 2\n(high con\ufb01dence) (Figure 2.3). Climate change impacts on health are \nmediated through natural and human systems, including economic \nand social conditions and disruptions (high con\ufb01dence). Climate and \nweather extremes are increasingly driving displacement in Africa, \nAsia, North America (high con\ufb01dence), and Central and South America \n(medium con\ufb01dence) (Figure 2.3), with small island states in the \nCaribbean and South Paci\ufb01c being disproportionately affected relative \nto their small population size (high con\ufb01dence). Through displacement \nand involuntary migration from extreme weather and climate \nevents, climate change has generated and perpetuated vulnerability \n(medium con\ufb01dence). {WGII SPM B.1.4, WGII SPM B.1.7}\nHuman in\ufb02uence has likely increased the chance of compound \nextreme events80 since the 1950s. Concurrent and repeated climate \nhazards have occurred in all regions, increasing impacts and \nrisks to health, ecosystems, infrastructure, livelihoods and food \n(high con\ufb01dence). Compound extreme events include increases in the \nfrequency of concurrent heatwaves and droughts (high con\ufb01dence); \ufb01re \nweather in some regions (medium con\ufb01dence); and compound \ufb02ooding in \nsome locations (medium con\ufb01dence). Multiple risks interact, generating \nnew sources of vulnerability to climate hazards, and compounding \noverall risk (high con\ufb01dence). Compound climate hazards can overwhelm \nadaptive capacity and substantially increase damage (high con\ufb01dence)). \n{WGI SPM A.3.5; WGII SPM. B.5.1, WGII TS.C.11.3}\nEconomic \nimpacts \nattributable \nto \nclimate \nchange \nare \nincreasingly \naffecting peoples\u2019 livelihoods and are causing economic and \nsocietal impacts across national boundaries (high con\ufb01dence).\n\nDocument 45: {WGII SPM footnote 29}\nIn urban settings, climate change has caused adverse impacts on \nhuman health, livelihoods and key infrastructure (high con\ufb01dence). \nHot extremes including heatwaves have intensi\ufb01ed in cities (high \ncon\ufb01dence), where they have also worsened air pollution events \n(medium con\ufb01dence) and limited functioning of key infrastructure \n(high con\ufb01dence). Urban infrastructure, including transportation, water, \nsanitation and energy systems have been compromised by extreme \nand slow-onset events79, with resulting economic losses, disruptions of \nservices and impacts to well-being (high con\ufb01dence). Observed impacts \nare concentrated amongst economically and socially marginalised urban \nresidents, e.g., those living in informal settlements (high con\ufb01dence). \nCities intensify human-caused warming locally (very high con\ufb01dence), \nwhile urbanisation also increases mean and heavy precipitation over and\/or \ndownwind of cities (medium con\ufb01dence) and resulting runoff intensity \n(high con\ufb01dence). {WGI SPM C.2.6; WGII SPM B.1.5, WGII Figure TS.9, \nWGII 6 ES}\nClimate change has adversely affected human physical health globally \nand mental health in assessed regions (very high con\ufb01dence), and is \ncontributing to humanitarian crises where climate hazards interact \nwith high vulnerability (high con\ufb01dence). In all regions increases in \nextreme heat events have resulted in human mortality and morbidity \n(very high con\ufb01dence). The occurrence of climate-related food-borne and \nwater-borne diseases has increased (very high con\ufb01dence). The incidence \nof vector-borne diseases has increased from range expansion and\/or \nincreased reproduction of disease vectors (high con\ufb01dence). Animal and \nhuman diseases, including zoonoses, are emerging in new areas (high \ncon\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":51,"topic":"Climate Change Impacts"}}
{"id":"7609a763-7491-410b-9729-fffb09eefb6d","question":"What are the projected impacts of climate change on the availability of snowmelt water for irrigation in some snowmelt dependent river basins?","reference_answer":"Climate change is projected to decline snowmelt water availability for irrigation in some snowmelt dependent river basins by up to 20% (medium confidence).","reference_context":"Document 231: {WGI SPM B.2.4, WGI SPM C.2.2, WGI SPM C.2.6, WGI 11.7} \n\u2022 High risks from dryland water scarcity, wild\ufb01re damage, and \npermafrost degradation (medium con\ufb01dence). {SRCCL SPM A.5.3.}\n\u2022 Continued sea level rise and increased frequency and \nmagnitude of extreme sea level events encroaching on coastal \nhuman settlements and damaging coastal infrastructure (high \ncon\ufb01dence), committing low-lying coastal ecosystems to \nsubmergence and loss (medium con\ufb01dence), expanding land \nsalinization (very high con\ufb01dence), with cascading to risks to \nlivelihoods, health, well-being, cultural values, food and water \nsecurity (high con\ufb01dence). {WGI SPM C.2.5, WGI SPM C.2.6; \nWGII SPM B.3.1, WGII SPM B.5.2; SRCCL SPM A.5.6; SROCC SPM B.3.4, \nSROCC SPM 3.6, SROCC SPM B.9.1} (Figure 3.4, 4.3)\n\u2022 Climate change will signi\ufb01cantly increase ill health and premature \ndeaths from the near to long term (high con\ufb01dence). Further \nwarming will increase climate-sensitive food-borne, water-borne, \nand vector-borne disease risks (high con\ufb01dence), and mental health \nchallenges including anxiety and stress (very high con\ufb01dence). \n{WGII SPM B.4.4}\n\nDocument 230: {WGI SPM B.2.2, \nWGI TS Figure TS.6; WGII SPM B.1.4, WGII SPM B.4.4, \nWGII Figure SPM.2} \n\u2022 Increasing frequency of marine heatwaves will increase risks \nof biodiversity loss in the oceans, including from mass mortality \nevents (high con\ufb01dence). {WGI SPM B.2.3; WGII SPM B.1.2, \nWGII Figure SPM.2; SROCC SPM B.5.1}\n\u2022 Near-term risks for biodiversity loss are moderate to high in \nforest ecosystems (medium con\ufb01dence) and kelp and seagrass \necosystems (high to very high con\ufb01dence) and are high to very \nhigh in Arctic sea-ice and terrestrial ecosystems (high con\ufb01dence) \nand warm-water coral reefs (very high con\ufb01dence). {WGII SPM B.3.1} \n\u2022 More intense and frequent extreme rainfall and associated \ufb02ooding \nin many regions including coastal and other low-lying cities \n(medium to high con\ufb01dence), and increased proportion of and \npeak wind speeds of intense tropical cyclones (high con\ufb01dence). \n{WGI SPM B.2.4, WGI SPM C.2.2, WGI SPM C.2.6, WGI 11.7} \n\u2022 High risks from dryland water scarcity, wild\ufb01re damage, and \npermafrost degradation (medium con\ufb01dence). {SRCCL SPM A.5.3.}\n\u2022 Continued sea level rise and increased frequency and \nmagnitude of extreme sea level events encroaching on coastal \nhuman settlements and damaging coastal infrastructure (high \ncon\ufb01dence), committing low-lying coastal ecosystems to \nsubmergence and loss (medium con\ufb01dence), expanding land \nsalinization (very high con\ufb01dence), with cascading to risks to \nlivelihoods, health, well-being, cultural values, food and water \nsecurity (high con\ufb01dence).\n\nDocument 232: 99\nNear-Term Responses in a Changing Climate\nSection 4\n\u2022 Cryosphere-related changes in \ufb02oods, landslides, and water \navailability have the potential to lead to severe consequences for \npeople, infrastructure and the economy in most mountain regions \n(high con\ufb01dence). {WGII TS C.4.2}\n\u2022 The projected increase in frequency and intensity of heavy \nprecipitation (high con\ufb01dence) will increase rain-generated local \n\ufb02ooding (medium con\ufb01dence). {WGI Figure SPM.6, WGI SPM B.2.2; \nWGII TS C.4.5}\nMultiple climate change risks will increasingly compound and \ncascade in the near term (high con\ufb01dence). Many regions are \nprojected to experience an increase in the probability of compound \nevents with higher global warming (high con\ufb01dence) including \nconcurrent heatwaves and drought. Risks to health and food \nproduction will be made more severe from the interaction of sudden \nfood production losses from heat and drought, exacerbated by heat-\ninduced labour productivity losses (high con\ufb01dence) (Figure 4.3). These \ninteracting impacts will increase food prices, reduce household incomes, \nand lead to health risks of malnutrition and climate-related mortality \nwith no or low levels of adaptation, especially in tropical regions (high \ncon\ufb01dence). Concurrent and cascading risks from climate change to \nfood systems, human settlements, infrastructure and health will make \nthese risks more severe and more dif\ufb01cult to manage, including when \ninteracting with non-climatic risk drivers such as competition for land \nbetween urban expansion and food production, and pandemics (high \ncon\ufb01dence). Loss of ecosystems and their services has cascading and \nlong-term impacts on people globally, especially for Indigenous Peoples \nand local communities who are directly dependent on ecosystems, to \nmeet basic needs (high con\ufb01dence). Increasing transboundary risks \nare projected across the food, energy and water sectors as impacts \nfrom weather and climate extremes propagate through supply-chains, \nmarkets, and natural resource \ufb02ows (high con\ufb01dence) and may interact \nwith impacts from other crises such as pandemics.\n\nDocument 127: For further explanations of global \nrisk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}\nchanges in food availability and diet quality are estimated to increase \nnutrition-related diseases and the number of undernourished people, \naffecting tens (under low vulnerability and low warming) to hundreds of \nmillions of people (under high vulnerability and high warming), particularly \namong low-income households in low- and middle-income countries in \nsub-Saharan Africa, South Asia and Central America (high con\ufb01dence). \nFor example, snowmelt water availability for irrigation is projected \nto decline in some snowmelt dependent river basins by up to 20% \n(medium con\ufb01dence). Climate change risks to cities, settlements \nand key infrastructure will rise sharply in the mid and long term with \nfurther global warming, especially in places already exposed to high \ntemperatures, along coastlines, or with high vulnerabilities (high \ncon\ufb01dence). {WGII SPM B.3.3, WGII SPM B.4.2, WGII SPM B.4.5, WGII TS C.3.3, \nWGII TS.C.12.2} (Figure 3.3)\nAt global warming of 3\u00b0C, additional risks in many sectors and regions \nreach high or very high levels, implying widespread systemic impacts, \nirreversible change and many additional adaptation limits (see Section 3.2) \n(high con\ufb01dence). For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":231,"topic":"Climate Change Impacts"}}
{"id":"c36a7201-fe69-4159-8980-7d839c8b9a07","question":"What are the expected benefits of accelerated implementation of adaptation responses according to the IPCC report?","reference_answer":"Accelerated implementation of adaptation will improve well-being by reducing losses and damages, especially for vulnerable populations, and bring benefits to human well-being.","reference_context":"Document 213: Positive (solid \ufb01lled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to \nGHG emissions from the year 2019. The category \u201cenergy supply (including electricity)\u201d includes bioenergy with carbon capture and storage and direct air carbon capture and storage. \n{WGIII Box TS.5, WGIII 3.3, WGIII 3.4, WGIII 6.6, WGIII 10.3, WGIII 11.3} (Cross-Section Box.2)\nAccelerated implementation of adaptation will improve well-being by reducing losses and damages, especially \nfor vulnerable populations. Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4).\n\nDocument 212: 95\nNear-Term Responses in a Changing Climate\nSection 4\n4.2 Bene\ufb01ts of Strengthening Near-Term Action\nFigure 4.1: Sectoral emissions in pathways that limit warming to 1.5\u00b0C. Panel (a) shows sectoral CO2 and non-CO2 emissions in global modelled pathways that limit \nwarming to 1.5\u00b0C (>50%) with no or limited overshoot. The horizontal lines illustrate halving 2015 emissions (base year of the pathways) (dashed) and reaching net zero emissions \n(solid line). The range shows the 5\u201395th percentile of the emissions across the pathways. The timing strongly differs by sector, with the CO2 emissions from the electricity\/fossil fuel \nindustries sector and\u00a0land-use change generally reaching net zero earlier.\u00a0Non-CO2 emissions from agriculture are also substantially reduced compared to pathways without climate \npolicy but do not typically reach zero. Panel (b) Although all pathways include strongly reduced emissions, there are different pathways as indicated by the illustrative mitigation \npathways used in IPCC WGIII. The pathways emphasise routes consistent with limiting warming to 1.5\u00b0C with a high reliance on net negative emissions (IMP-Neg), high resource \nef\ufb01ciency (IMP-LD), a focus on sustainable development (IMP-SP) or renewables (IMP-Ren) and consistent with 2\u00b0C based on a less rapid introduction of mitigation measures followed \nby a subsequent gradual strengthening (IMP-GS). Positive (solid \ufb01lled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to \nGHG emissions from the year 2019. The category \u201cenergy supply (including electricity)\u201d includes bioenergy with carbon capture and storage and direct air carbon capture and storage. \n{WGIII Box TS.5, WGIII 3.3, WGIII 3.4, WGIII 6.6, WGIII 10.3, WGIII 11.3} (Cross-Section Box.2)\nAccelerated implementation of adaptation will improve well-being by reducing losses and damages, especially \nfor vulnerable populations.\n\nDocument 214: Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4). (high con\ufb01dence) {WGI SPM B.1, WGI SPM B.1.3, WGI \nSPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM \nC.2, WGII SPM C.3.1, WGII Figure SPM.4b; SROCC SPM C.3.4, SROCC \nFigure 3.4, SROCC Figure SPM.5}\nNear-term actions that limit global warming to close to 1.5\u00b0C \nwould substantially reduce projected losses and damages related \nto climate change in human systems and ecosystems, compared \nto higher warming levels, but cannot eliminate them all (very \nhigh con\ufb01dence). The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).\n\nDocument 208: {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems. In modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited \novershoot and in those that limit warming to 2\u00b0C (>67%) and assume immediate action, global GHG emissions \nare projected to peak in the early 2020s followed by rapid and deep reductions. As adaptation options often have \nlong implementation times, accelerated implementation of adaptation, particularly in this decade, is important \nto close adaptation gaps. (high con\ufb01dence)","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":213,"topic":"Climate Change Action"}}
{"id":"53160032-26c6-4f27-a047-1e245a55bb22","question":"How do the SSP scenarios differ from the RCP scenarios in terms of greenhouse gas and air pollutant futures?","reference_answer":"The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs. They are similar but not identical, with differences in concentration trajectories for different GHGs.","reference_context":"Document 108: where \u2018SSPx\u2019 refers to the Shared Socio-economic Pathway or \u2018SSP\u2019 describing the socio-economic trends \nunderlying the scenario, and \u2018y\u2019 refers to the approximate level of radiative forcing (in watts per square metre, or Wm\u20132) resulting from the \nscenario in the year 2100.\n** The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate 2100 radiative \nforcing levels (in W m-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs. They are similar but not \nidentical, with differences in concentration trajectories for different GHGs. The overall radiative forcing tends to be higher for the SSPs compared \nto the RCPs with the same label (medium con\ufb01dence). {WGI TS.1.3.1}\n*** Limited overshoot refers to exceeding 1.5\u00b0C global warming by up to about 0.1\u00b0C, high overshoot by 0.1\u00b0C-0.3\u00b0C, in both cases for up to \nseveral decades.\n\nDocument 104: {WGIII SPM C.1.4; SRCCL Box SPM.1}\n105 SSP-based scenarios are referred to as SSPx-y, where \u2018SSPx\u2019 refers to the Shared Socio-economic Pathway describing the socioeconomic trends underlying the scenarios, and \n\u2018y\u2019 refers to the level of radiative forcing (in watts per square metre, or Wm\u20132) resulting from the scenario in the year 2100. {WGI SPM footnote 22}\n106 Very high emission scenarios have become less likely but cannot be ruled out. Temperature levels > 4\u00b0C may result from very high emission scenarios, but can also occur from \nlower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher than the best estimate. {WGIII SPM C.1.3}\n107 RCP-based scenarios are referred to as RCPy, where \u2018y\u2019 refers to the approximate level of radiative forcing (in watts per square metre, or Wm\u20132) resulting from the scenario in the \nyear 2100. {WGII SPM footnote 21}\n108 Denoted \u2018>50%\u2019 in this report.\n109 The climate response to emissions is investigated with climate models, paleoclimatic insights and other lines of evidence. The assessment outcomes are used to categorise \nthousands of scenarios via simple physically-based climate models (emulators). {WGI TS.1.2.2}\n\nDocument 107: 0 \nand SSP1-2.6\nCategory \nin WGIII\nCategory description\nGHG emissions scenarios\n(SSPx-y*) in WGI & WGII \nRCPy** in\nWGI & WGII\nC1\nlimit warming to 1.5\u00b0C (>50%)\nwith no or limited overshoot\nVery low (SSP1-1.9)\nLow (SSP1-2.6) \nRCP2.6\nC2\nreturn warming to 1.5\u00b0C (>50%)\nafter a high overshoot\nC3\nlimit warming to 2\u00b0C (>67%)\nC4\nlimit warming to 2\u00b0C (>50%)\nC5\nlimit warming to 2.5\u00b0C (>50%)\nC6\nlimit warming to 3\u00b0C (>50%)\nIntermediate (SSP2-4.5)\nRCP 4.5\nRCP 8.5\nC7\nlimit warming to 4\u00b0C (>50%)\nHigh (SSP3-7.0)\nC8\nexceed warming of 4\u00b0C (>50%)\nVery high (SSP5-8.5)\nScenarios and warming levels structure our understanding across the \ncause-effect chain from emissions to climate change and risks\nCO2 emissions for SSP-based scenarios \nand C1-C8 categories\nVulnerability\nHazard\nResponse\nRisk\nExposure\nClimatic\nImpact-\nDrivers\n0\n1\n2\n3\n4\n5\n\u00b0C\nin\ufb02uence\nshape\n* The terminology SSPx-y is used, where \u2018SSPx\u2019 refers to the Shared Socio-economic Pathway or \u2018SSP\u2019 describing the socio-economic trends \nunderlying the scenario, and \u2018y\u2019 refers to the approximate level of radiative forcing (in watts per square metre, or Wm\u20132) resulting from the \nscenario in the year 2100.\n** The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate 2100 radiative \nforcing levels (in W m-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs. They are similar but not \nidentical, with differences in concentration trajectories for different GHGs.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":108,"topic":"Others"}}
{"id":"b0dfac4f-64eb-4178-b241-2f96f3baa177","question":"What is the range of harmonised GHG emissions across the pathways for 2019 as assessed in the IPCC report?","reference_answer":"The 2019 range of harmonised GHG emissions across the pathways is 53\u201358 GtCO2-eq.","reference_context":"Document 21: Average annual GHG emissions growth between \n69 \nGHG emission metrics are used to express emissions of different GHGs in a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalents (CO2-eq) using \nthe Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports \ncontain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of \nmetric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the complexity of the physical climate \nsystem and its response to past and future GHG emissions. {WGI SPM D.1.8, WGI 7.6; WGIII SPM B.1, WGIII Cross-Chapter Box 2.2} (Annex I: Glossary)\n70 \nTerritorial emissions\n71 \nGHG emission levels are rounded to two signi\ufb01cant digits; as a consequence, small differences in sums due to rounding may occur. {WGIII SPM footnote 8}\n72 \nComprising a gross sink of -12.5 (\u00b13.2) GtCO2 yr-1 resulting from responses of all land to both anthropogenic environmental change and natural climate variability, and \nnet anthropogenic CO2-LULUCF emissions +5.9 (\u00b14.1) GtCO2 yr-1 based on book-keeping models. {WGIII SPM Footnote 14}\n73 \nThis estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirect emissions from outside urban areas related to \nthe production of electricity, goods and services consumed in cities. These estimates include all CO2 and CH4 emission categories except for aviation and marine bunker fuels, \nland-use change, forestry and agriculture.\n\nDocument 20: Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence). In 2019, approximately 34% (20 GtCO2-eq) \nof net global GHG emissions came from the energy sector, 24% \n(14 GtCO2-eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% \n(8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2-eq) from buildings71 \n(high con\ufb01dence). Average annual GHG emissions growth between \n69 \nGHG emission metrics are used to express emissions of different GHGs in a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalents (CO2-eq) using \nthe Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports \ncontain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of \nmetric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the complexity of the physical climate \nsystem and its response to past and future GHG emissions.\n\nDocument 19: (high confidence) \n{WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, \nWGIII Figure SPM.2}\nRegional contributions to global human-caused GHG emissions \ncontinue to differ widely. Historical contributions of CO2 emissions \nvary substantially across regions in terms of total magnitude, but also \nin terms of contributions to CO2-FFI (1650 \u00b1 73 GtCO2-eq) and net \nCO2-LULUCF (760 \u00b1 220 GtCO2-eq) emissions (Figure 2.2). Variations \nin regional and national per capita emissions partly re\ufb02ect different \ndevelopment stages, but they also vary widely at similar income \nlevels. Average per capita net anthropogenic GHG emissions in 2019 \nranged from 2.6 tCO2-eq to 19 tCO2-eq across regions (Figure 2.2). \nLeast Developed Countries (LDCs) and Small Island Developing States (SIDS) \nhave much lower per capita emissions (1.7 tCO2-eq and 4.6 tCO2-eq, \nrespectively) than the global average (6.9 tCO2-eq), excluding \nCO2-LULUCF\n. Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence).\n\nDocument 82: Emissions projections for 2030 and gross differences in emissions are based on emissions of 52\u201356 GtCO2-eq yr\u20131 in 2019 as assumed in underlying model \nstudies97. (medium con\ufb01dence) {WGIII Table SPM.1} (Table 3.1, Cross-Section Box.2) \n95 \nAbatement here refers to human interventions that reduce the amount of GHGs that are released from fossil fuel infrastructure to the atmosphere. {WGIII SPM footnote 34}\n96 \nWGI provides carbon budgets that are in line with limiting global warming to temperature limits with different likelihoods, such as 50%, 67% or 83%. {WGI Table SPM.2}\n97 \nThe 2019 range of harmonised GHG emissions across the pathways [53\u201358 GtCO2-eq] is within the uncertainty ranges of 2019 emissions assessed in WGIII Chapter 2 [53\u201366 GtCO2-eq].\nEmission and implementation gaps associated with projected \nglobal emissions in 2030 under Nationally Determined \nContributions (NDCs) and implemented policies\nImplied by policies \nimplemented by the end \nof 2020 (GtCO2-eq\/yr)\nImplied by Nationally Determined Contributions \n(NDCs) announced prior to COP26\nUnconditional \nelements (GtCO2-eq\/yr)\nIncluding conditional \nelements (GtCO2-eq\/yr)\nMedian projected global emissions \n(min\u2013max)*\nImplementation gap between \nimplemented policies and NDCs \n(median)\nEmissions gap between NDCs and \npathways that limit warming to \n2\u00b0C (>67%) with immediate action \nEmissions gap between NDCs and \npathways that limit warming to \n1.5\u00b0C (>50%) with no or limited \novershoot with immediate action \n57 [52\u201360]\n\u2013\n\u2013\n\u2013\n4\n7\n53 [50\u201357]\n50 [47\u201355]\n10\u201316\n6\u201314\n19\u201326\n16\u201323\n*Emissions projections for 2030 and gross differences in emissions are based on emissions of 52\u201356 GtCO2-eq\/yr in 2019 as assumed in underlying model studies.","conversation_history":[],"metadata":{"question_type":"simple","seed_document_id":21,"topic":"Global GHG Emissions"}}
{"id":"eeda3bd9-732c-4f9c-9a3a-8aaa5ea67b3d","question":"Considering the findings of the IPCC report, what are the identified barriers impeding the uptake of low-emission technologies in developing nations, particularly the least developed among them?","reference_answer":"Adoption of low-emission technologies lags in most developing countries, particularly least developed ones, due in part to weaker enabling conditions, including limited finance, technology development and transfer, and capacity building.","reference_context":"Document 296: (high confidence) {WGIII SPM B.4, WGIII SPM B.4.4, \nWGIII SPM E.4.3, WGIII SPM E4.4}\nInternational cooperation on innovation systems and technology \ndevelopment and transfer, accompanied by capacity building, \nknowledge sharing, and technical and \ufb01nancial support can \naccelerate the global diffusion of mitigation technologies, \npractices and policies and align these with other development \nobjectives (high con\ufb01dence). Choice architecture can help end-users \nadopt technology and low-GHG-intensive options (high con\ufb01dence). \nAdoption of low-emission technologies lags in most developing countries, \nparticularly least developed ones, due in part to weaker enabling \nconditions, including limited \ufb01nance, technology development and \ntransfer, and capacity building (medium con\ufb01dence). {WGIII SPM B.4.2, \nWGIII SPM E.6.2, WGIII SPM C.10.4, WGIII 16.5}\nHigher mitigation investment \ufb02ows required for \nall sectors and regions to limit global warming\nActual yearly \ufb02ows compared to average annual needs \nin billions USD (2015) per year\nMultiplication \nfactors*\n0\n1000\n1500\n2000\n2500\n3000\n500\n2017\n2018\n2019\n2020\nAnnual mitigation investment \nneeds (averaged until 2030)\nIEA data mean \n2017\u20132020\nAverage \ufb02ows\n0\n1000\n1500\n2000\n2500\n3000\n500\n*Multiplication factors indicate the x-fold increase between yearly \nmitigation \ufb02ows to average yearly mitigation investment needs. \nGlobally, current mitigation \ufb01nancial \ufb02ows are a factor of three \nto six below the average levels up to 2030.\n\nDocument 286: Financial and \ntechnological resources enable effective and ongoing implementation \nof adaptation, especially when supported by institutions with a strong \nunderstanding of adaptation needs and capacity (high con\ufb01dence). \nAverage annual modelled mitigation investment requirements for \n2020 to 2030 in scenarios that limit warming to 2\u00b0C or 1.5\u00b0C are a \nfactor of three to six greater than current levels, and total mitigation \ninvestments (public, private, domestic and international) would need \nto increase across all sectors and regions (medium con\ufb01dence). Even \nif extensive global mitigation efforts are implemented, there will be a \nlarge need for \ufb01nancial, technical, and human resources for adaptation \n(high con\ufb01dence). {WGII SPM C.1.2, WGII SPM C2.11, WGII SPM C.3, \nWGII SPM C.3.2, WGII SPM C3.5, WGII SPM C.5, WGII SPM C.5.4, \nWGII SPM D.1, WGII SPM D.1.1, WGII SPM D.1.2, WGII SPM C.5.4; \nWGIII SPM D.2.4, WGIII SPM E.5, WGIII SPM E.5.1, WGIII 15.2} \n(Section 2.3.2, 2.3.3, 4.4, Figure 4.6)\napproaches (high con\ufb01dence). There is no consistent evidence that \ncurrent emission trading systems have led to signi\ufb01cant emissions \nleakage (medium con\ufb01dence). {WGIII SPM E4.2, WGIII SPM E.4.6} \nRemoving fossil fuel subsidies would reduce emissions, improve \npublic revenue and macroeconomic performance, and yield \nother environmental and sustainable development bene\ufb01ts such \nas improved public revenue, macroeconomic and sustainability \nperformance; subsidy removal can have adverse distributional \nimpacts especially on the most economically vulnerable \ngroups which, in some cases, can be mitigated by measures \nsuch as re-distributing revenue saved, and depend on national \ncircumstances (high con\ufb01dence).\n\nDocument 295: 113\nNear-Term Responses in a Changing Climate\nSection 4\n4.8.3. Technology Innovation, Adoption, Diffusion and \nTransfer \nEnhancing \ntechnology \ninnovation \nsystems \ncan \nprovide \nopportunities to lower emissions growth and create social and \nenvironmental co-bene\ufb01ts. Policy packages tailored to national \ncontexts and technological characteristics have been effective \nin supporting low-emission innovation and technology diffusion. \nSupport for successful low-carbon technological innovation \nincludes public policies such as training and R&D, complemented by \nregulatory and market-based instruments that create incentives and \nmarket opportunities such as appliance performance standards and \nbuilding codes. (high confidence) {WGIII SPM B.4, WGIII SPM B.4.4, \nWGIII SPM E.4.3, WGIII SPM E4.4}\nInternational cooperation on innovation systems and technology \ndevelopment and transfer, accompanied by capacity building, \nknowledge sharing, and technical and \ufb01nancial support can \naccelerate the global diffusion of mitigation technologies, \npractices and policies and align these with other development \nobjectives (high con\ufb01dence). Choice architecture can help end-users \nadopt technology and low-GHG-intensive options (high con\ufb01dence). \nAdoption of low-emission technologies lags in most developing countries, \nparticularly least developed ones, due in part to weaker enabling \nconditions, including limited \ufb01nance, technology development and \ntransfer, and capacity building (medium con\ufb01dence).\n\nDocument 254: {WGIII SPM footnote 54}\n154 The mitigation potentials and mitigation costs of individual technologies in a speci\ufb01c context or region may differ greatly from the provided estimates (medium con\ufb01dence). \n{WGIII SPM C.12.1}\ncon\ufb01dence). The most feasible energy system adaptation options \nsupport infrastructure resilience, reliable power systems and ef\ufb01cient \nwater use for existing and new energy generation systems (very \nhigh con\ufb01dence). Adaptations for hydropower and thermo-electric \npower generation are effective in most regions up to 1.5\u00b0C to 2\u00b0C, \nwith decreasing effectiveness at higher levels of warming (medium \ncon\ufb01dence). Energy generation diversi\ufb01cation (e.g., wind, solar, small-\nscale hydroelectric) and demand side management (e.g., storage and \nenergy ef\ufb01ciency improvements) can increase energy reliability and \nreduce vulnerabilities to climate change, especially in rural populations \n(high con\ufb01dence). Climate responsive energy markets, updated design \nstandards on energy assets according to current and projected climate \nchange, smart-grid technologies, robust transmission systems and \nimproved capacity to respond to supply de\ufb01cits have high feasibility \nin the medium- to long-term, with mitigation co-bene\ufb01ts (very high \ncon\ufb01dence). {WGII SPM B.5.3, WGII SPM C.2.10; WGIII TS.5.1}\n4.5.2. Industry\nThere are several options to reduce industrial emissions \nthat differ by type of industry; many industries are disrupted \nby climate change, especially from extreme events (high \ncon\ufb01dence). Reducing industry emissions will entail coordinated \naction throughout value chains to promote all mitigation options, \nincluding demand management, energy and materials ef\ufb01ciency, \ncircular material \ufb02ows, as well as abatement technologies and","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":296,"topic":"Others"}}
{"id":"99ec911e-cbe1-4806-8e42-90ce644e39ee","question":"In the context of the IPCC report's maps, what is the significance of hatching when considering the consensus on impact direction among climate-crop model combinations for maize yield and among climate-fisheries models for maximum fisheries catch potential?","reference_answer":"Hatching indicates areas where less than 70% of the climate-crop model combinations agree on the sign of impact for maize yield, and where the two climate-fisheries models disagree in the direction of change for fisheries catch potential.","reference_context":"Document 136: Hatching indicates areas where <70% of the climate-crop model \ncombinations agree on the sign of impact. (c2) Changes in maximum \ufb01sheries catch potential by 2081\u20132099 relative to 1986-2005 at projected GWLs of 0.9\u00b0C to 2.0\u00b0C (1.5\u00b0C) \nand 3.4\u00b0C to 5.2\u00b0C (4.3\u00b0C). GWLs by 2081\u20132100 under RCP2.6 and RCP8.5. Hatching indicates where the two climate-\ufb01sheries models disagree in the direction of change. Large \nrelative changes in low yielding regions may correspond to small absolute changes. Biodiversity and \ufb01sheries in Antarctica were not analysed due to data limitations. Food security \nis also affected by crop and \ufb01shery failures not presented here. {WGII Fig. TS.5, WGII Fig TS.9, WGII Annex I: Global to Regional Atlas Figure AI.15, Figure AI.22, Figure AI.23, Figure \nAI.29; WGII 7.3.1.2, 7.2.4.1, SROCC Figure SPM.3} (3.1.2, Cross-Section Box.2)\n\nDocument 135: Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C). Median yield changes \nfrom an ensemble of 12 crop models, each driven by bias-adjusted outputs from 5 Earth system models from the Agricultural Model Intercomparison and Improvement Project \n(AgMIP) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Maps depict 2080\u20132099 compared to 1986\u20132005 for current growing regions (>10 ha), with the \ncorresponding range of future global warming levels shown under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively. Hatching indicates areas where <70% of the climate-crop model \ncombinations agree on the sign of impact. (c2) Changes in maximum \ufb01sheries catch potential by 2081\u20132099 relative to 1986-2005 at projected GWLs of 0.9\u00b0C to 2.0\u00b0C (1.5\u00b0C) \nand 3.4\u00b0C to 5.2\u00b0C (4.3\u00b0C). GWLs by 2081\u20132100 under RCP2.6 and RCP8.5. Hatching indicates where the two climate-\ufb01sheries models disagree in the direction of change. Large \nrelative changes in low yielding regions may correspond to small absolute changes. Biodiversity and \ufb01sheries in Antarctica were not analysed due to data limitations. Food security \nis also affected by crop and \ufb01shery failures not presented here. {WGII Fig.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":136,"topic":"Climate Change Risks"}}
{"id":"25068a04-a269-43c3-9422-6759b109fd6a","question":"In the context of the IPCC report, could you enumerate the ancillary advantages of transitioning to clean energy systems, particularly those that intersect with multiple Sustainable Development Goals?","reference_answer":"Clean energy supply systems have multiple co-benefits, including improvements in air quality and health.","reference_context":"Document 272: 108\nSection 4\nSection 1\nSection 4\nMany mitigation and adaptation actions have multiple synergies \nwith Sustainable Development Goals (SDGs), but some actions \ncan also have trade-offs. Potential synergies with SDGs exceed \npotential trade-offs. Synergies and trade-offs are context specific \nand depend on: means and scale of implementation, intra- and \ninter-sectoral interactions, cooperation between countries and regions, \nthe sequencing, timing and stringency of actions, governance, and \npolicy design. Eradicating extreme poverty, energy poverty, and \nproviding decent living standards to all, consistent with near-\nterm sustainable development objectives, can be achieved \nwithout significant global emissions growth. (high confidence) \n{WGII SPM C.2.3, WGII Figure SPM.4b; WGIII SPM B.3.3, WGIII SPM C.9.2, \nWGIII SPM D.1.2, WGIII SPM D.1.4, WGIII Figure SPM.8} (Figure 4.5)\nSeveral mitigation and adaptation options can harness near-\nterm synergies and reduce trade-offs to advance sustainable \ndevelopment in energy, urban and land systems (Figure 4.5) \n(high con\ufb01dence). Clean energy supply systems have multiple \nco-benefits, including improvements in air quality and health. \nHeat Health Action Plans that include early warning and response \nsystems, approaches that mainstream health into food, livelihoods, \nsocial protection, water and sanitation benefit health and well-\nbeing. There are potential synergies between multiple Sustainable \nDevelopment Goals and sustainable land use and urban planning \nwith more green spaces, reduced air pollution, and demand-side \nmitigation including shifts to balanced, sustainable healthy diets. \nElectri\ufb01cation combined with low-GHG energy, and shifts to public \ntransport can enhance health, employment, and can contribute to \nenergy security and deliver equity. Conservation, protection and \nrestoration of terrestrial, freshwater, coastal and ocean ecosystems, \ntogether with targeted management to adapt to unavoidable impacts \nof climate change can generate multiple additional bene\ufb01ts, such as \nagricultural productivity, food security, and biodiversity conservation.\n\nDocument 191: 88\nSection 3\nSection 1\nSection 3\n3.4.1 Synergies and trade-offs, costs and bene\ufb01ts\nMitigation and adaptation options can lead to synergies and \ntrade-offs with other aspects of sustainable development \n(see also Section 4.6, Figure 4.4). Synergies and trade-offs depend \non the pace and magnitude of changes and the development context \nincluding inequalities, with consideration of climate justice. The \npotential or effectiveness of some adaptation and mitigation options \ndecreases as climate change intensi\ufb01es (see also Sections 3.2, 3.3.3, \n4.5). (high con\ufb01dence) {WGII SPM C.2, WGII Figure SPM.4b; WGIII SPM D.1, \nWGIII SPM D.1.2, WGIII TS.5.1, WGIII Figure SPM.8; SR1.5 SPM D.3, \nSR1.5 SPM D.4; SRCCL SPM B.2, SRCCL SPM B.3, SRCCL SPM D.3.2, \nSRCCL Figure SPM.3}\nIn the energy sector, transitions to low-emission systems will have \nmultiple co-bene\ufb01ts, including improvements in air quality and health. \nThere are potential synergies between sustainable development and, \nfor instance, energy ef\ufb01ciency and renewable energy. (high con\ufb01dence) \n{WGIII SPM C.4.2, WGIII SPM D.1.3}\nFor agriculture, land, and food systems, many land management \noptions and demand-side response options (e.g., dietary choices, \nreduced post-harvest losses, reduced food waste) can contribute to \neradicating poverty and eliminating hunger while promoting good health \nand well-being, clean water and sanitation, and life on land (medium \nconfidence). In contrast, certain adaptation options that promote \nintensification of production, such as irrigation, may have negative \neffects on sustainability (e.g., for biodiversity, ecosystem services, \ngroundwater depletion, and water quality) (high confidence).\n\nDocument 276: 109\nNear-Term Responses in a Changing Climate\nSection 4\nNear-term adaptation and mitigation actions have more synergies \nthan trade-offs with Sustainable Development Goals (SDGs)\nSynergies and trade-offs depend on context and scale\nEnergy systems\nSDGs\nUrban and infrastructure\nLand system\nOcean \necosystems\nSociety, \nlivelihoods, and \neconomies\nIndustry\nAdaptation\nMitigation\nAdaptation\nMitigation\nAdaptation\nMitigation\nAdaptation\nAdaptation\nMitigation\nLimited evidence\/no evidence\/no assessment\nBoth synergies and trade-offs\/mixed\nTrade-offs\nSynergies\nKey\nFigure 4.5: Potential synergies and trade-offs between the portfolio of climate change mitigation and adaptation options and the Sustainable Development \nGoals (SDGs). This \ufb01gure presents a high-level summary of potential synergies and trade-offs assessed in WGII Figure SPM.4b and WGIII Figure SPM.8, based on the qualitative and \nquantitative assessment of each individual mitigation or option. The SDGs serve as an analytical framework for the assessment of different sustainable development dimensions, which \nextend beyond the time frame of 2030 SDG targets. Synergies and trade-offs across all individual options within a sector\/system are aggregated into sector\/system potentials for the \nwhole mitigation or adaptation portfolio. The length of each bar represents the total number of mitigation or adaptation options under each system\/sector. The number of adaptation \nand mitigation options vary across system\/sector, and have been normalised to 100% so that bars are comparable across mitigation, adaptation, system\/sector, and SDGs. Positive \nlinks shown in WGII Figure SPM.4b and WGIII Figure SPM.8 are counted and aggregated to generate the percentage share of synergies, represented here by the blue proportion \nwithin the bars. Negative links shown in WGII Figure SPM.4b and WGIII Figure SPM.8 are counted and aggregated to generate the percentage share of trade-offs and is represented \nby orange proportion within the bars.\n\nDocument 273: Clean energy supply systems have multiple \nco-benefits, including improvements in air quality and health. \nHeat Health Action Plans that include early warning and response \nsystems, approaches that mainstream health into food, livelihoods, \nsocial protection, water and sanitation benefit health and well-\nbeing. There are potential synergies between multiple Sustainable \nDevelopment Goals and sustainable land use and urban planning \nwith more green spaces, reduced air pollution, and demand-side \nmitigation including shifts to balanced, sustainable healthy diets. \nElectri\ufb01cation combined with low-GHG energy, and shifts to public \ntransport can enhance health, employment, and can contribute to \nenergy security and deliver equity. Conservation, protection and \nrestoration of terrestrial, freshwater, coastal and ocean ecosystems, \ntogether with targeted management to adapt to unavoidable impacts \nof climate change can generate multiple additional bene\ufb01ts, such as \nagricultural productivity, food security, and biodiversity conservation. \n(high confidence) {WGII SPM C.1.1, WGII C.2.4, WGII SPM D.1, \nWGII Figure SPM.4, WGII Cross-Chapter Box HEALTH in Chapter 17, \nWGII Cross-Chapter Box FEASIB in Chapter 18; WGIII SPM C.4.2, \nWGIII SPM D.1.3, WGIII SPM D.2, WGIII Figure SPM.8; SRCCL SPM B.4.6}\nWhen implementing mitigation and adaptation together, and \ntaking trade-offs into account, multiple co-bene\ufb01ts and synergies \nfor human well-being as well as ecosystem and planetary health \ncan be realised (high con\ufb01dence). There is a strong link between \nsustainable development, vulnerability and climate risks. Social safety \nnets that support climate change adaptation have strong co-bene\ufb01ts \nwith development goals such as education, poverty alleviation, gender \ninclusion and food security. Land restoration contributes to mitigation \nand adaptation with synergies via enhanced ecosystem services and \nwith economically positive returns and co-bene\ufb01ts for poverty reduction \nand improved livelihoods.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":272,"topic":"Climate Change Action"}}
{"id":"ffc88789-4386-4581-a770-b3c106c662b6","question":"Considering the pathways aligned with maintaining a global temperature rise to 1.5\u00b0C with no or limited overshoot, what is the anticipated reduction percentage for methane emissions by the year 2030, as compared to the levels recorded in 2019?","reference_answer":"34 [21 to 57]%","reference_context":"Document 207: In pathways \nthat limit warming to 1.5\u00b0C (>50%) with no or limited overshoot, net \nglobal GHG emissions are projected to fall by 43 [34 to 60]%143 below \n2019 levels by 2030, 60 [49 to 77]% by 2035, 69 [58 to 90]% by 2040 \nand 84 [73 to 98]% by 2050 (high con\ufb01dence) (Section 2.3.1, Table 2.2, \nFigure 2.5, Table 3.1)144. Global modelled pathways that limit warming \nto 2\u00b0C (>67%) have reductions in GHG emissions below 2019 levels \nof 21 [1 to 42]% by 2030, 35 [22 to 55] % by 2035, 46 [34 to 63] \n% by 2040 and 64 [53 to 77]% by 2050145 (high con\ufb01dence). Global \nGHG emissions associated with NDCs announced prior to COP26 would \nmake it likely that warming would exceed 1.5\u00b0C (high con\ufb01dence) \nand limiting warming to 2\u00b0C (>67%) would then imply a rapid \nacceleration of emission reductions during 2030\u20132050, around \n70% faster than in pathways where immediate action is taken to \nlimit warming to 2\u00b0C (>67%) (medium con\ufb01dence) (Section 2.3.1) \nContinued investments in unabated high-emitting infrastructure146 and \nlimited development and deployment of low-emitting alternatives \nprior to 2030 would act as barriers to this acceleration and increase \nfeasibility risks (high confidence). {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems.\n\nDocument 209: 93\nNear-Term Responses in a Changing Climate\nSection 4\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) \nor lower by 2100 involve reductions in both net CO2 emissions \nand non-CO2 emissions (see Figure 3.6) (high confidence). \nFor example, in pathways that limit warming to 1.5\u00b0C (>50%) \nwith no or limited overshoot, global CH4 (methane) emissions are \nreduced by 34 [21 to 57]% below 2019 levels by 2030 and by \n44 [31 to 63]% in 2040 (high confidence). Global CH4 emissions \nare reduced by 24 [9 to 53]% below 2019 levels by 2030 and by \n37 [20 to 60]% in 2040 in modelled pathways that limit warming to \n2\u00b0C with action starting in 2020 (>67%) (high con\ufb01dence). {WGIII SPM \nC1.2, WGIII Table SPM.2, WGIII 3.3; SR1.5 SPM C.1, SR1.5 SPM C.1.2} \n(Cross-Section Box.2)\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) \nor lower by 2100 involve GHG emission reductions in all sectors \n(high con\ufb01dence). The contributions of different sectors vary across \nmodelled mitigation pathways. In most global modelled mitigation \npathways, emissions from land-use, land-use change and forestry, via \nreforestation and reduced deforestation, and from the energy supply \nsector reach net zero CO2 emissions earlier than the buildings, industry \nand transport sectors (Figure 4.1). Strategies can rely on combinations \nof different options (Figure 4.1, Section 4.5), but doing less in one \nsector needs to be compensated by further reductions in other sectors if \nwarming is to be limited.\n\nDocument 84: 59\nCurrent Status and Trends\nSection 2\na) Global GHG emissions\nb) 2030\n10\n20\n30\n0\n40\n50\n60\n70\n10\n20\n30\n0\n40\n50\n60\n70\nGHG emissions (GtCO2-eq\/yr)\n2020\n2025\n2015\n2010\n2030\n2035\n2040\n2045\n2050\nLimit warming to 2\u00baC (>67%)\nor 1.5 (>50%) after high\novershoot with NDCs until 2030\nTrend from implemented policies\n2019\nLimit warming to\n1.5\u00baC (>50%) with \nno or limited overshoot\nLimit warming \nto 2\u00baC (>67%)\nto be on-track to limit \nwarming to 1.5\u00b0C, \nwe need much more \nreduction by 2030\n-4%\n+5%\n-26%\n-43%\nProjected global GHG emissions from NDCs announced prior to \nCOP26 would make it likely that warming will exceed 1.5\u00b0C and \nalso make it harder after 2030 to limit warming to below 2\u00b0C\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nFigure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), and projected emission outcomes from near-term policy assessments for 2030 (Panel b). \nPanel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n\nDocument 162: 82\nSection 3\nSection 1\nSection 3\n3.3 Mitigation Pathways\nLimiting human-caused global warming requires net zero anthropogenic CO2 emissions. Pathways consistent \nwith 1.5\u00b0C and 2\u00b0C carbon budgets imply rapid, deep, and in most cases immediate GHG emission reductions in \nall sectors (high con\ufb01dence). Exceeding a warming level and returning (i.e. overshoot) implies increased risks \nand potential irreversible impacts; achieving and sustaining global net negative CO2 emissions would reduce \nwarming (high con\ufb01dence).\n3.3.1 Remaining Carbon Budgets\nLimiting global temperature increase to a speci\ufb01c level requires \nlimiting cumulative net CO2 emissions to within a \ufb01nite carbon \nbudget126, along with strong reductions in other GHGs. For every \n1000 GtCO2 emitted by human activity, global mean temperature rises \nby likely 0.27\u00b0C to 0.63\u00b0C (best estimate of 0.45\u00b0C). This relationship \nimplies that there is a \ufb01nite carbon budget that cannot be exceeded in \norder to limit warming to any given level. {WGI SPM D.1, WGI SPM D.1.1; \nSR1.5 SPM C.1.3} (Figure 3.5)\nThe best estimates of the remaining carbon budget (RCB) from \nthe beginning of 2020 for limiting warming to 1.5\u00b0C with a 50% \nlikelihood127 is estimated to be 500 GtCO2; for 2\u00b0C (67% likelihood) \nthis is 1150 GtCO2.128 Remaining carbon budgets have been quanti\ufb01ed \nbased on the assessed value of TCRE and its uncertainty, estimates of \nhistorical warming, climate system feedbacks such as emissions from \nthawing permafrost, and the global surface temperature change after \nglobal anthropogenic CO2 emissions reach net zero, as well as variations \nin projected warming from non-CO2 emissions due in part to mitigation \naction. The stronger the reductions in non-CO2 emissions the lower the \nresulting temperatures are for a given RCB or the larger RCB for the \nsame level of temperature change.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":207,"topic":"Others"}}
{"id":"8a5ceff4-e915-4a54-adac-a51f8a90e10e","question":"In the context of the Global Extreme Sea Level Analysis version 2 database, what is the significance of the absence of a circle on the data visualizations, especially considering the implications for assessing sea level changes?","reference_answer":"The absence of a circle indicates an inability to perform an assessment due to a lack of data, but does not indicate absence of increasing frequencies.","reference_context":"Document 237: A peak-over-threshold (99.7%) method \nwas applied to the historical tide gauge observations available in the Global Extreme Sea Level Analysis version 2 database, which is the same information as WGI Figure 9.32, \nexcept here the panel uses relative sea level projections under SSP2-4.5 for the year 2040 instead of 2050 The absence of a circle indicates an inability to perform an assessment \ndue to a lack of data, but does not indicate absence of increasing frequencies. Panel (c) Climate hazards can initiate risk cascades that affect multiple sectors and propagate across \nregions following complex natural and societal connections. This example of a compound heat wave and a drought event striking an agricultural region shows how multiple risks are \ninterconnected and lead to cascading biophysical, economic, and societal impacts even in distant regions, with vulnerable groups such as smallholder farmers, children and pregnant \nwomen particularly impacted. {WGI Figure 9.32; WGII SPM B4.3, WGII SPM B1.3, WGII SPM B.5.1, WGII TS Figure TS.9, WGII TS Figure TS.10 (c), WGII Fig 5.2, WGII TS.B.2.3, \nWGII TS.B.2.3, WGII TS.B.3.3, WGII 9.11.1.2}\u00a0\nActions that prioritise equity, climate justice, social justice and inclusion lead to more sustainable outcomes, \nco-bene\ufb01ts, reduce trade-offs, support transformative change and advance climate resilient development. \nAdaptation responses are immediately needed to reduce rising climate risks, especially for the most vulnerable. \nEquity, inclusion and just transitions are key to progress on adaptation and deeper societal ambitions for \naccelerated mitigation. (high con\ufb01dence)\nAdaptation and mitigation actions, across scales, sectors and \nregions, that prioritise equity, climate justice, rights-based \napproaches, social justice and inclusivity, lead to more \nsustainable outcomes, reduce trade-offs, support transformative \nchange and advance climate resilient development (high \ncon\ufb01dence).\n\nDocument 236: 101\nNear-Term Responses in a Changing Climate\nSection 4\nFigure 4.3: Every region faces more severe or frequent compound and\/or cascading climate risks in the near term. Changes in risk result from changes in the degree \nof the hazard, the population exposed, and the degree of vulnerability of people, assets, or ecosystems. Panel (a) Coastal \ufb02ooding events affect many of the highly populated regions \nof the world where large percentages of the population are exposed.\u00a0The panel shows near-term projected increase of population exposed to 100-year \ufb02ooding events depicted \nas the increase from the year 2020 to 2040 (due to sea level rise and population change), based on the intermediate GHG emissions scenario (SSP2-4.5) and current adaptation \nmeasures. Out-migration from coastal areas due to future sea level rise is not considered in the scenario. Panel (b) projected median probability in the year 2040 for extreme water \nlevels resulting from a combination of mean sea level rise, tides and storm surges, which have a historical 1% average annual probability. A peak-over-threshold (99.7%) method \nwas applied to the historical tide gauge observations available in the Global Extreme Sea Level Analysis version 2 database, which is the same information as WGI Figure 9.32, \nexcept here the panel uses relative sea level projections under SSP2-4.5 for the year 2040 instead of 2050 The absence of a circle indicates an inability to perform an assessment \ndue to a lack of data, but does not indicate absence of increasing frequencies. Panel (c) Climate hazards can initiate risk cascades that affect multiple sectors and propagate across \nregions following complex natural and societal connections. This example of a compound heat wave and a drought event striking an agricultural region shows how multiple risks are \ninterconnected and lead to cascading biophysical, economic, and societal impacts even in distant regions, with vulnerable groups such as smallholder farmers, children and pregnant \nwomen particularly impacted.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":237,"topic":"Climate Change Action"}}
{"id":"3fe9895f-1726-4926-87b1-90decff61105","question":"According to the most recent assessments by the IPCC, what are the anticipated severe impacts on infrastructure, economy, and communities in mountainous regions as a result of changes in the cryosphere, and with what level of scientific confidence are these projections made?","reference_answer":"Cryosphere-related changes in floods, landslides, and water availability have the potential to lead to severe consequences for people, infrastructure and the economy in most mountain regions (high confidence).","reference_context":"Document 232: 99\nNear-Term Responses in a Changing Climate\nSection 4\n\u2022 Cryosphere-related changes in \ufb02oods, landslides, and water \navailability have the potential to lead to severe consequences for \npeople, infrastructure and the economy in most mountain regions \n(high con\ufb01dence). {WGII TS C.4.2}\n\u2022 The projected increase in frequency and intensity of heavy \nprecipitation (high con\ufb01dence) will increase rain-generated local \n\ufb02ooding (medium con\ufb01dence). {WGI Figure SPM.6, WGI SPM B.2.2; \nWGII TS C.4.5}\nMultiple climate change risks will increasingly compound and \ncascade in the near term (high con\ufb01dence). Many regions are \nprojected to experience an increase in the probability of compound \nevents with higher global warming (high con\ufb01dence) including \nconcurrent heatwaves and drought. Risks to health and food \nproduction will be made more severe from the interaction of sudden \nfood production losses from heat and drought, exacerbated by heat-\ninduced labour productivity losses (high con\ufb01dence) (Figure 4.3). These \ninteracting impacts will increase food prices, reduce household incomes, \nand lead to health risks of malnutrition and climate-related mortality \nwith no or low levels of adaptation, especially in tropical regions (high \ncon\ufb01dence). Concurrent and cascading risks from climate change to \nfood systems, human settlements, infrastructure and health will make \nthese risks more severe and more dif\ufb01cult to manage, including when \ninteracting with non-climatic risk drivers such as competition for land \nbetween urban expansion and food production, and pandemics (high \ncon\ufb01dence). Loss of ecosystems and their services has cascading and \nlong-term impacts on people globally, especially for Indigenous Peoples \nand local communities who are directly dependent on ecosystems, to \nmeet basic needs (high con\ufb01dence). Increasing transboundary risks \nare projected across the food, energy and water sectors as impacts \nfrom weather and climate extremes propagate through supply-chains, \nmarkets, and natural resource \ufb02ows (high con\ufb01dence) and may interact \nwith impacts from other crises such as pandemics.\n\nDocument 233: Concurrent and cascading risks from climate change to \nfood systems, human settlements, infrastructure and health will make \nthese risks more severe and more dif\ufb01cult to manage, including when \ninteracting with non-climatic risk drivers such as competition for land \nbetween urban expansion and food production, and pandemics (high \ncon\ufb01dence). Loss of ecosystems and their services has cascading and \nlong-term impacts on people globally, especially for Indigenous Peoples \nand local communities who are directly dependent on ecosystems, to \nmeet basic needs (high con\ufb01dence). Increasing transboundary risks \nare projected across the food, energy and water sectors as impacts \nfrom weather and climate extremes propagate through supply-chains, \nmarkets, and natural resource \ufb02ows (high con\ufb01dence) and may interact \nwith impacts from other crises such as pandemics. Risks also arise from \nsome responses intended to reduce the risks of climate change, including \nrisks from maladaptation and adverse side effects of some emissions \nreduction and carbon dioxide removal measures, such as afforestation of \nnaturally unforested land or poorly implemented bioenergy compounding \nclimate-related risks to biodiversity, food and water security, and \nlivelihoods (high con\ufb01dence) (see Section 3.4.1 and 4.5). {WGI SPM.2.7; \nWGII SPM B.2.1, WGII SPM B.5, WGII SPM B.5.1, WGII SPM B.5.2, \nWGII SPM B.5.3, WGII SPM B.5.4, WGII Cross-Chapter Box COVID in Chapter 7; \nWGIII SPM C.11.2; SRCCL SPM A.5, SRCCL SPM A.6.5} (Figure 4.3)\nWith every increment of global warming losses and damages will \nincrease (very high con\ufb01dence), become increasingly dif\ufb01cult \nto avoid and be strongly concentrated among the poorest \nvulnerable populations (high con\ufb01dence). Adaptation does not \nprevent all losses and damages, even with effective adaptation and \nbefore reaching soft and hard limits.\n\nDocument 236: 101\nNear-Term Responses in a Changing Climate\nSection 4\nFigure 4.3: Every region faces more severe or frequent compound and\/or cascading climate risks in the near term. Changes in risk result from changes in the degree \nof the hazard, the population exposed, and the degree of vulnerability of people, assets, or ecosystems. Panel (a) Coastal \ufb02ooding events affect many of the highly populated regions \nof the world where large percentages of the population are exposed.\u00a0The panel shows near-term projected increase of population exposed to 100-year \ufb02ooding events depicted \nas the increase from the year 2020 to 2040 (due to sea level rise and population change), based on the intermediate GHG emissions scenario (SSP2-4.5) and current adaptation \nmeasures. Out-migration from coastal areas due to future sea level rise is not considered in the scenario. Panel (b) projected median probability in the year 2040 for extreme water \nlevels resulting from a combination of mean sea level rise, tides and storm surges, which have a historical 1% average annual probability. A peak-over-threshold (99.7%) method \nwas applied to the historical tide gauge observations available in the Global Extreme Sea Level Analysis version 2 database, which is the same information as WGI Figure 9.32, \nexcept here the panel uses relative sea level projections under SSP2-4.5 for the year 2040 instead of 2050 The absence of a circle indicates an inability to perform an assessment \ndue to a lack of data, but does not indicate absence of increasing frequencies. Panel (c) Climate hazards can initiate risk cascades that affect multiple sectors and propagate across \nregions following complex natural and societal connections. This example of a compound heat wave and a drought event striking an agricultural region shows how multiple risks are \ninterconnected and lead to cascading biophysical, economic, and societal impacts even in distant regions, with vulnerable groups such as smallholder farmers, children and pregnant \nwomen particularly impacted.\n\nDocument 129: 72\nSection 3\nSection 1\nSection 3\nProjected adverse impacts and related losses and damages from \nclimate change escalate with every increment of global warming \n(very high con\ufb01dence), but they will also strongly depend on \nsocio-economic development trajectories and adaptation actions \nto reduce vulnerability and exposure (high con\ufb01dence). For \nexample, development pathways with higher demand for food, animal \nfeed, and water, more resource-intensive consumption and production, \nand limited technological improvements result in higher risks from \nwater scarcity in drylands, land degradation and food insecurity (high \ncon\ufb01dence). Changes in, for example, demography or investments in \nhealth systems have effect on a variety of health-related outcomes \nincluding heat-related morbidity and mortality (Figure 3.3 Panel d). \n{WGII SPM B.3, WGII SPM B.4, WGII Figure SPM.3; SRCCL SPM A.6}\nWith every increment of warming, climate change impacts and \nrisks will become increasingly complex and more dif\ufb01cult to \nmanage. Many regions are projected to experience an increase in \nthe probability of compound events with higher global warming, such \nas concurrent heatwaves and droughts, compound \ufb02ooding and \ufb01re \nweather. In addition, multiple climatic and non-climatic risk drivers \nsuch as biodiversity loss or violent con\ufb02ict will interact, resulting \nin compounding overall risk and risks cascading across sectors and \nregions. Furthermore, risks can arise from some responses that are \nintended to reduce the risks of climate change, e.g., adverse side effects \nof some emission reduction and carbon dioxide removal (CDR) measures \n(see 3.4.1).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":232,"topic":"Climate Change Impacts"}}
{"id":"829d3d20-0516-48d7-b87a-39133c8b665c","question":"Since the year 2010, what specific percentage decreases in unit costs have been observed for solar energy, wind energy, and lithium-ion batteries, and how have these trends affected their deployment?","reference_answer":"From 2010-2019, there have been sustained decreases in the unit costs of solar energy (by 85%), wind energy (by 55%), and lithium-ion batteries (by 85%).","reference_context":"Document 60: 53\nCurrent Status and Trends\nSection 2\nthan single policies (high con\ufb01dence). Combining mitigation with \npolicies to shift development pathways, policies that induce lifestyle or \nbehaviour changes, for example, measures promoting walkable urban \nareas combined with electri\ufb01cation and renewable energy can create \nhealth co-bene\ufb01ts from cleaner air and enhanced active mobility (high \ncon\ufb01dence). Climate governance enables mitigation by providing an \noverall direction, setting targets, mainstreaming climate action across \npolicy domains and levels, based on national circumstances and in the \ncontext of international cooperation. Effective governance enhances \nregulatory certainty, creating specialised organisations and creating the \ncontext to mobilise \ufb01nance (medium con\ufb01dence). These functions can \nbe promoted by climate-relevant laws, which are growing in number, or \nclimate strategies, among others, based on national and sub-national \ncontext (medium con\ufb01dence). Effective and equitable climate \ngovernance builds on engagement with civil society actors, political \nactors, businesses, youth, labour, media, Indigenous Peoples and local \ncommunities (medium con\ufb01dence). {WGIII SPM E.2.2, WGIII SPM E.3, \nWGIII SPM E.3.1, WGIII SPM E.4.2, WGIII SPM E.4.3, WGIII SPM E.4.4}\nThe unit costs of several low-emission technologies, including \nsolar, wind and lithium-ion batteries, have fallen consistently \nsince 2010 (Figure 2.4). Design and process innovations in \ncombination with the use of digital technologies have led to \nnear-commercial availability of many low or zero emissions \noptions in buildings, transport and industry. From 2010-2019, \nthere have been sustained decreases in the unit costs of solar energy \n(by 85%), wind energy (by 55%), and lithium-ion batteries (by 85%), \nand large increases in their deployment, e.g., >10\u00d7 for solar and >100\u00d7 for \nelectric vehicles (EVs), albeit varying widely across regions (Figure 2.4).\n\nDocument 62: Integrated design \nin construction and retro\ufb01t of buildings has led to increasing examples \nof zero energy or zero carbon buildings. Technological innovation \nmade possible the widespread adoption of LED lighting. Digital \ntechnologies including sensors, the internet of things, robotics, and \narti\ufb01cial intelligence can improve energy management in all sectors; \nthey can increase energy ef\ufb01ciency, and promote the adoption of many \nlow-emission technologies, including decentralised renewable energy, \nwhile creating economic opportunities. However, some of these climate \nchange mitigation gains can be reduced or counterbalanced by growth in \ndemand for goods and services due to the use of digital devices. Several \nmitigation options, notably solar energy, wind energy, electri\ufb01cation of \nurban systems, urban green infrastructure, energy ef\ufb01ciency, demand \nside management, improved forest- and crop\/grassland management, \nand reduced food waste and loss, are technically viable, are becoming \nincreasingly cost effective and are generally supported by the public, and \nthis enables expanded deployment in many regions. (high con\ufb01dence) \n{WGIII SPM B.4.3, WGIII SPM C.5.2, WGIII SPM C.7.2, WGIII SPM E.1.1, \nWGIII TS.6.5}\nThe magnitude of global climate \ufb01nance \ufb02ows has increased \nand \ufb01nancing channels have broadened (high con\ufb01dence). \nAnnual tracked total \ufb01nancial \ufb02ows for climate mitigation and \nadaptation increased by up to 60% between 2013\/14 and 2019\/20, \nbut average growth has slowed since 2018 (medium con\ufb01dence) and \nmost climate \ufb01nance stays within national borders (high con\ufb01dence). \nMarkets for green bonds, environmental, social and governance and \nsustainable \ufb01nance products have expanded signi\ufb01cantly since AR5 \n(high con\ufb01dence). Investors, central banks, and \ufb01nancial regulators are \ndriving increased awareness of climate risk to support climate policy \ndevelopment and implementation (high con\ufb01dence).\n\nDocument 279: The synergies and trade-offs differ depending on the context and the scale of implementation. Scale of implementation particularly matters when there is \ncompetition for scarce resources. For the sake of uniformity, we are not reporting the con\ufb01dence levels because there is knowledge gap in adaptation option wise relation with SDGs \nand their con\ufb01dence level which is evident from WGII \ufb01g SPM.4b. {WGII Figure SPM.4b; WGIII Figure SPM.8}\nEffective climate governance enables mitigation and adaptation \nby providing overall direction based on national circumstances, \nsetting targets and priorities, mainstreaming climate action across \npolicy domains and levels, based on national circumstances and \nin the context of international cooperation. Effective governance \nenhances monitoring and evaluation and regulatory certainty, \nprioritising inclusive, transparent and equitable decision-making, \nand improves access to \ufb01nance and technology (high con\ufb01dence). \nThese functions can be promoted by climate-relevant laws and \nplans, which are growing in number across sectors and regions, \nadvancing mitigation outcomes and adaptation benefits (high \nconfidence). Climate laws have been growing in number and \nhave helped deliver mitigation and adaptation outcomes (medium \ncon\ufb01dence). {WGII SPM C.5, WGII SPM C.5.1, WGII SPM C5.4, WGII SPM C.5.6; \nWGIII SPM B.5.2, WGIII SPM E.3.1}\nEffective \nmunicipal, \nnational \nand \nsub-national \nclimate \ninstitutions, such as expert and co-ordinating bodies, enable \nco-produced, multi-scale decision-processes, build consensus \nfor action among diverse interests, and inform strategy settings \n(high con\ufb01dence). This requires adequate institutional capacity at \nall levels (high con\ufb01dence). Vulnerabilities and climate risks are often \nreduced through carefully designed and implemented laws, policies, \nparticipatory processes, and interventions that address context \nspeci\ufb01c inequities such as based on gender, ethnicity, disability, age, \nlocation and income (high con\ufb01dence).\n\nDocument 63: Annual tracked total \ufb01nancial \ufb02ows for climate mitigation and \nadaptation increased by up to 60% between 2013\/14 and 2019\/20, \nbut average growth has slowed since 2018 (medium con\ufb01dence) and \nmost climate \ufb01nance stays within national borders (high con\ufb01dence). \nMarkets for green bonds, environmental, social and governance and \nsustainable \ufb01nance products have expanded signi\ufb01cantly since AR5 \n(high con\ufb01dence). Investors, central banks, and \ufb01nancial regulators are \ndriving increased awareness of climate risk to support climate policy \ndevelopment and implementation (high con\ufb01dence). Accelerated \ninternational \ufb01nancial cooperation is a critical enabler of low-GHG and \njust transitions (high con\ufb01dence). {WGIII SPM B.5.4, WGIII SPM E.5, \nWGIII TS.6.3, WGIII TS.6.4}\nEconomic instruments have been effective in reducing emissions, \ncomplemented by regulatory instruments mainly at the national \nand also sub-national and regional level (high con\ufb01dence). By 2020, \nover 20% of global GHG emissions were covered by carbon taxes or \nemissions trading systems, although coverage and prices have been \ninsuf\ufb01cient to achieve deep reductions (medium con\ufb01dence). Equity and \ndistributional impacts of carbon pricing instruments can be addressed \nby using revenue from carbon taxes or emissions trading to support \nlow-income households, among other approaches (high con\ufb01dence). \nThe mix of policy instruments which reduced costs and stimulated \nadoption of solar energy, wind energy and lithium-ion batteries \nincludes public R&D, funding for demonstration and pilot projects, and \ndemand-pull instruments such as deployment subsidies to attain scale \n(high con\ufb01dence) (Figure 2.4).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":60,"topic":"Climate Change Action"}}
{"id":"0a967dcb-9040-403a-b328-d6eca73e0182","question":"In the context of the IPCC's latest assessment report, what is the updated range for equilibrium climate sensitivity, and how does this compare to the range presented in the AR5?","reference_answer":"The likely range of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C to 4.0\u00b0C.","reference_context":"Document 111: 68\nSection 3\nSection 1\nSection 3\nSection 3: Long-Term Climate and Development Futures\n3.1 Long-Term Climate Change, Impacts and Related Risks\nFuture warming will be driven by future emissions and will affect all major climate system components, with \nevery region experiencing multiple and co-occurring changes. Many climate-related risks are assessed to be \nhigher than in previous assessments, and projected long-term impacts are up to multiple times higher than \ncurrently observed. Multiple climatic and non-climatic risks will interact, resulting in compounding and cascading \nrisks across sectors and regions. Sea level rise, as well as other irreversible changes, will continue for thousands \nof years, at rates depending on future emissions. (high con\ufb01dence)\n3.1.1. Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating.\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 112: Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating. The assessed best estimates and \nvery likely ranges of warming for 2081-2100 with respect to 1850\u20131900 \nvary from 1.4 [1.0 to 1.8]\u00b0C in the very low GHG emissions scenario \n(SSP1-1.9) to 2.7 [2.1 to 3.5]\u00b0C in the intermediate GHG emissions \nscenario (SSP2-4.5) and 4.4 [3.3 to 5.7]\u00b0C in the very high GHG emissions \nscenario (SSP5-8.5)113. {WGI SPM B.1.1, WGI Table SPM.1, WGI Figure \nSPM.4} (Cross-Section Box.2 Figure 1)\nModelled pathways consistent with the continuation of policies \nimplemented by the end of 2020 lead to global warming of \n3.2 [2.2 to 3.5]\u00b0C (5\u201395% range) by 2100 (medium con\ufb01dence) \n(see also Section 2.3.1). Pathways of >4\u00b0C (\u226550%) by 2100 would \nimply a reversal of current technology and\/or mitigation policy trends \n(medium con\ufb01dence).\n\nDocument 129: 72\nSection 3\nSection 1\nSection 3\nProjected adverse impacts and related losses and damages from \nclimate change escalate with every increment of global warming \n(very high con\ufb01dence), but they will also strongly depend on \nsocio-economic development trajectories and adaptation actions \nto reduce vulnerability and exposure (high con\ufb01dence). For \nexample, development pathways with higher demand for food, animal \nfeed, and water, more resource-intensive consumption and production, \nand limited technological improvements result in higher risks from \nwater scarcity in drylands, land degradation and food insecurity (high \ncon\ufb01dence). Changes in, for example, demography or investments in \nhealth systems have effect on a variety of health-related outcomes \nincluding heat-related morbidity and mortality (Figure 3.3 Panel d). \n{WGII SPM B.3, WGII SPM B.4, WGII Figure SPM.3; SRCCL SPM A.6}\nWith every increment of warming, climate change impacts and \nrisks will become increasingly complex and more dif\ufb01cult to \nmanage. Many regions are projected to experience an increase in \nthe probability of compound events with higher global warming, such \nas concurrent heatwaves and droughts, compound \ufb02ooding and \ufb01re \nweather. In addition, multiple climatic and non-climatic risk drivers \nsuch as biodiversity loss or violent con\ufb02ict will interact, resulting \nin compounding overall risk and risks cascading across sectors and \nregions. Furthermore, risks can arise from some responses that are \nintended to reduce the risks of climate change, e.g., adverse side effects \nof some emission reduction and carbon dioxide removal (CDR) measures \n(see 3.4.1).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":111,"topic":"Climate Change Assessment"}}
{"id":"ed51743b-2f7b-4e43-b093-06b869311a79","question":"Considering the findings of the IPCC report, how might climate change exacerbate challenges to food production and the availability of drinking water, and which regions are expected to be most vulnerable to these impacts?","reference_answer":"The projected impacts include risk to food and water security due to increased temperature extremes, rainfall variability and drought, risk of malnutrition (micronutrient deficiency), and loss of livelihood due to reduced food production from crops, livestock and fisheries.","reference_context":"Document 142: especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics, in particular vector-borne diseases\n-Coral reef ecosystems degradation due to coral bleaching\n-Risk to food security due to frequent\/extreme droughts\n-Damages to life and infrastructure due to \ufb02oods, landslides, sea level rise, storm \nsurges and coastal erosion \nNorth \nAmerica\n-Climate-sensitive mental health outcomes, human mortality and morbidity due to \nincreasing average temperature, weather and climate extremes, and compound \nclimate hazards\n-Risk of degradation of marine, coastal and terrestrial ecosystems, including loss of \nbiodiversity, function, and protective services \n-Risk to freshwater resources with consequences for ecosystems, reduced surface water \navailability for irrigated agriculture, other human uses, and degraded water quality \n-Risk to food and nutritional security through changes in agriculture, livestock, hunting, \n\ufb01sheries, and aquaculture productivity and access\n-Risks to well-being, livelihoods and economic activities from cascading and \ncompounding climate hazards, including risks to coastal cities, settlements and \ninfrastructure from sea level rise\nDelayed\nimpacts of\nsea level\nrise in the\nMediterranean\nFood\nproduction\nfrom crops,\n\ufb01sheries and\nlivestock\nin Africa\nMortality and\nmorbidity\nfrom heat and\ninfectious\ndisease\nin Africa\nBiodiversity\nand\necosystems\nin Africa\nHealth and\nwellbeing\nin the\nMediterranean\nWater scarcity\nto people in\nsoutheastern\nEurope\nCoastal\n\ufb02ooding to\npeople\nand\ninfrastructures\nin Europe\nHeat stress,\n\nDocument 141: risk to food security and economic disruption due to \ndestruction of settlements and infrastructure\n-Economic decline and livelihood failure of \ufb01sheries, agriculture, tourism and from \nbiodiversity loss from traditional agroecosystems \n-Reduced habitability of reef and non-reef islands leading to increased displacement\n-Risk to water security in almost every small island \nAfrica -Species extinction and reduction or irreversible loss of ecosystems and their services, \nincluding freshwater, land and ocean ecosystems\n-Risk to food security, risk of malnutrition (micronutrient de\ufb01ciency), and loss of \nlivelihood due to reduced food production from crops, livestock and \ufb01sheries\n-Risks to marine ecosystem health and to livelihoods in coastal communities\n-Increased human mortality and morbidity due to increased heat and infectious diseases \n(including vector-borne and diarrhoeal diseases)\n-Reduced economic output and growth, and increased inequality and poverty rates \n-Increased risk to water and energy security due to drought and heat\nAus-\ntralasia\n-Degradation of tropical shallow coral reefs and associated biodiversity and \necosystem service values\n-Loss of human and natural systems in low-lying coastal areas due to sea level rise\n-Impact on livelihoods and incomes due to decline in agricultural production\n-Increase in heat-related mortality and morbidity for people and wildlife\n-Loss of alpine biodiversity in Australia due to less snow\nAsia -Urban infrastructure damage and impacts on human well-being and health due to \n\ufb02ooding, especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics,\n\nDocument 140: 76\nSection 3\nSection 1\nSection 3\n0\n1\n1.5\n2\n3\n4\n0\n1\n1.5\n2\n3\n4\n\u00b0C\n\u00b0C\n0\n1\n1.5\n2\n3\n4\n0\n1\n1.5\n2\n3\n4\n\u00b0C\n\u00b0C\nEurope -Risks to people, economies and infrastructures due to coastal and inland \ufb02ooding\n-Stress and mortality to people due to increasing temperatures and heat extremes\n-Marine and terrestrial ecosystems disruptions\n-Water scarcity to multiple interconnected sectors\n-Losses in crop production, due to compound heat and dry conditions, and extreme \nweather\nSmall\nIslands\n-Loss of terrestrial, marine and coastal biodiversity and ecosystem services\n-Loss of lives and assets, risk to food security and economic disruption due to \ndestruction of settlements and infrastructure\n-Economic decline and livelihood failure of \ufb01sheries, agriculture, tourism and from \nbiodiversity loss from traditional agroecosystems \n-Reduced habitability of reef and non-reef islands leading to increased displacement\n-Risk to water security in almost every small island \nAfrica -Species extinction and reduction or irreversible loss of ecosystems and their services, \nincluding freshwater, land and ocean ecosystems\n-Risk to food security, risk of malnutrition (micronutrient de\ufb01ciency), and loss of \nlivelihood due to reduced food production from crops, livestock and \ufb01sheries\n-Risks to marine ecosystem health and to livelihoods in coastal communities\n-Increased human mortality and morbidity due to increased heat and infectious diseases \n(including vector-borne and diarrhoeal diseases)\n-Reduced economic output and growth,\n\nDocument 230: {WGI SPM B.2.2, \nWGI TS Figure TS.6; WGII SPM B.1.4, WGII SPM B.4.4, \nWGII Figure SPM.2} \n\u2022 Increasing frequency of marine heatwaves will increase risks \nof biodiversity loss in the oceans, including from mass mortality \nevents (high con\ufb01dence). {WGI SPM B.2.3; WGII SPM B.1.2, \nWGII Figure SPM.2; SROCC SPM B.5.1}\n\u2022 Near-term risks for biodiversity loss are moderate to high in \nforest ecosystems (medium con\ufb01dence) and kelp and seagrass \necosystems (high to very high con\ufb01dence) and are high to very \nhigh in Arctic sea-ice and terrestrial ecosystems (high con\ufb01dence) \nand warm-water coral reefs (very high con\ufb01dence). {WGII SPM B.3.1} \n\u2022 More intense and frequent extreme rainfall and associated \ufb02ooding \nin many regions including coastal and other low-lying cities \n(medium to high con\ufb01dence), and increased proportion of and \npeak wind speeds of intense tropical cyclones (high con\ufb01dence). \n{WGI SPM B.2.4, WGI SPM C.2.2, WGI SPM C.2.6, WGI 11.7} \n\u2022 High risks from dryland water scarcity, wild\ufb01re damage, and \npermafrost degradation (medium con\ufb01dence). {SRCCL SPM A.5.3.}\n\u2022 Continued sea level rise and increased frequency and \nmagnitude of extreme sea level events encroaching on coastal \nhuman settlements and damaging coastal infrastructure (high \ncon\ufb01dence), committing low-lying coastal ecosystems to \nsubmergence and loss (medium con\ufb01dence), expanding land \nsalinization (very high con\ufb01dence), with cascading to risks to \nlivelihoods, health, well-being, cultural values, food and water \nsecurity (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":142,"topic":"Climate Change Impacts"}}
{"id":"3c5988cb-9956-40ce-87e9-a45f57fa00fd","question":"Considering the latest IPCC report, what are the anticipated changes in the occurrence and severity of marine heatwaves as global temperatures continue to rise?","reference_answer":"Additional warming will lead to more frequent and intense marine heatwaves.","reference_context":"Document 152: 78\nSection 3\nSection 1\nSection 3\nimpacts on populations in low elevation coastal zones. If global \nwarming increases, some compound extreme events124 will \nbecome more frequent, with higher likelihood of unprecedented \nintensities, durations or spatial extent (high confidence). The \nAtlantic Meridional Overturning Circulation is very likely to weaken \nover the 21st century for all considered scenarios (high con\ufb01dence), \nhowever an abrupt collapse is not expected before 2100 (medium \ncon\ufb01dence). If such a low probability event were to occur, it would very \nlikely cause abrupt shifts in regional weather patterns and water cycle, \n124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound \ufb02ooding. {WGI SPM Footnote 18}\nsuch as a southward shift in the tropical rain belt, and large impacts \non ecosystems and human activities. A sequence of large explosive \nvolcanic eruptions within decades, as have occurred in the past, is a \nlow-likelihood high-impact event that would lead to substantial cooling \nglobally and regional climate perturbations over several decades. \n{WGI SPM B.5.3, WGI SPM C.3, WGI SPM C.3.1, WGI SPM C.3.2, \nWGI SPM C.3.3, WGI SPM C.3.4, WGI SPM C.3.5, WGI Figure SPM.8, \nWGI Box TS.3, WGI Figure TS.6, WGI Box 9.4; WGII SPM B.4.5, WGII SPM C.2.8; \nSROCC SPM B.2.7} (Figure 3.4, Cross-Section Box.2)\n3.2 Long-term Adaptation Options and Limits\nWith increasing warming, adaptation options will become more constrained and less effective. At higher levels \nof warming, losses and damages will increase, and additional human and natural systems will reach adaptation \nlimits. Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation.\n\nDocument 129: 72\nSection 3\nSection 1\nSection 3\nProjected adverse impacts and related losses and damages from \nclimate change escalate with every increment of global warming \n(very high con\ufb01dence), but they will also strongly depend on \nsocio-economic development trajectories and adaptation actions \nto reduce vulnerability and exposure (high con\ufb01dence). For \nexample, development pathways with higher demand for food, animal \nfeed, and water, more resource-intensive consumption and production, \nand limited technological improvements result in higher risks from \nwater scarcity in drylands, land degradation and food insecurity (high \ncon\ufb01dence). Changes in, for example, demography or investments in \nhealth systems have effect on a variety of health-related outcomes \nincluding heat-related morbidity and mortality (Figure 3.3 Panel d). \n{WGII SPM B.3, WGII SPM B.4, WGII Figure SPM.3; SRCCL SPM A.6}\nWith every increment of warming, climate change impacts and \nrisks will become increasingly complex and more dif\ufb01cult to \nmanage. Many regions are projected to experience an increase in \nthe probability of compound events with higher global warming, such \nas concurrent heatwaves and droughts, compound \ufb02ooding and \ufb01re \nweather. In addition, multiple climatic and non-climatic risk drivers \nsuch as biodiversity loss or violent con\ufb02ict will interact, resulting \nin compounding overall risk and risks cascading across sectors and \nregions. Furthermore, risks can arise from some responses that are \nintended to reduce the risks of climate change, e.g., adverse side effects \nof some emission reduction and carbon dioxide removal (CDR) measures \n(see 3.4.1).\n\nDocument 236: 101\nNear-Term Responses in a Changing Climate\nSection 4\nFigure 4.3: Every region faces more severe or frequent compound and\/or cascading climate risks in the near term. Changes in risk result from changes in the degree \nof the hazard, the population exposed, and the degree of vulnerability of people, assets, or ecosystems. Panel (a) Coastal \ufb02ooding events affect many of the highly populated regions \nof the world where large percentages of the population are exposed.\u00a0The panel shows near-term projected increase of population exposed to 100-year \ufb02ooding events depicted \nas the increase from the year 2020 to 2040 (due to sea level rise and population change), based on the intermediate GHG emissions scenario (SSP2-4.5) and current adaptation \nmeasures. Out-migration from coastal areas due to future sea level rise is not considered in the scenario. Panel (b) projected median probability in the year 2040 for extreme water \nlevels resulting from a combination of mean sea level rise, tides and storm surges, which have a historical 1% average annual probability. A peak-over-threshold (99.7%) method \nwas applied to the historical tide gauge observations available in the Global Extreme Sea Level Analysis version 2 database, which is the same information as WGI Figure 9.32, \nexcept here the panel uses relative sea level projections under SSP2-4.5 for the year 2040 instead of 2050 The absence of a circle indicates an inability to perform an assessment \ndue to a lack of data, but does not indicate absence of increasing frequencies. Panel (c) Climate hazards can initiate risk cascades that affect multiple sectors and propagate across \nregions following complex natural and societal connections. This example of a compound heat wave and a drought event striking an agricultural region shows how multiple risks are \ninterconnected and lead to cascading biophysical, economic, and societal impacts even in distant regions, with vulnerable groups such as smallholder farmers, children and pregnant \nwomen particularly impacted.\n\nDocument 118: {WGI SPM D.1.7, WGI Box TS.7} (Cross-Section Box.2)\nContinued GHG emissions will further affect all major climate \nsystem components, and many changes will be irreversible on \ncentennial to millennial time scales. Many changes in the climate \nsystem become larger in direct relation to increasing global warming. \nWith every additional increment of global warming, changes in \nextremes continue to become larger. Additional warming will lead to \nmore frequent and intense marine heatwaves and is projected to further \namplify permafrost thawing and loss of seasonal snow cover, glaciers, \nland ice and Arctic sea ice (high con\ufb01dence). Continued global warming \nis projected to further intensify the global water cycle, including its \nvariability, global monsoon precipitation117, and very wet and very dry \nweather and climate events and seasons (high con\ufb01dence). The portion \nof global land experiencing detectable changes in seasonal mean \nprecipitation is projected to increase (medium con\ufb01dence) with more \nvariable precipitation and surface water \ufb02ows over most land regions \nwithin seasons (high con\ufb01dence) and from year to year (medium \ncon\ufb01dence). Many changes due to past and future GHG emissions are \nirreversible118 on centennial to millennial time scales, especially in the \nocean, ice sheets and global sea level (see 3.1.3). Ocean acidi\ufb01cation \n(virtually certain), ocean deoxygenation (high con\ufb01dence) and global \nmean sea level (virtually certain) will continue to increase in the 21st century, \nat rates dependent on future emissions.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":152,"topic":"Climate Change Risks"}}
{"id":"a00931ae-a7b9-4cc3-836b-2ad8330e427e","question":"According to the latest IPCC assessment, what were the precise atmospheric concentrations of carbon dioxide, methane, and nitrous oxide in parts per million and parts per billion respectively for the year 2021, and how do these figures compare to those reported in previous years?","reference_answer":"For the year 2021, the atmospheric concentrations are 415 ppm CO2, 1896 ppb CH4, and 335 ppb N2O.","reference_context":"Document 14: 68 \nFor 2021 (the most recent year for which \ufb01nal numbers are available) concentrations using the same observational products and methods as in AR6 WGI are: 415 ppm CO2; \n1896 ppb CH4; and 335 ppb N2O. Note that the CO2 is reported here using the WMO-CO2-X2007 scale to be consistent with WGI. Operational CO2 reporting has since been \nupdated to use the WMO-CO2-X2019 scale.\nthe past six decades, with regional differences (high con\ufb01dence). In 2019, \natmospheric CO2 concentrations reached 410 parts per million (ppm), CH4 \nreached 1866 parts per billion (ppb) and nitrous oxide (N2O) reached 332 ppb68. \nOther major contributors to warming are tropospheric ozone (O3) and \nhalogenated gases. Concentrations of CH4 and N2O have increased to \nlevels unprecedented in at least 800,000 years (very high con\ufb01dence), \nand there is high con\ufb01dence that current CO2 concentrations are \nhigher than at any time over at least the past two million years. Since \n1750, increases in CO2 (47%) and CH4 (156%) concentrations far \nexceed \u2013 and increases in N2O (23%) are similar to \u2013 the natural \nmulti-millennial changes between glacial and interglacial periods over at \nleast the past 800,000 years (very high con\ufb01dence). The net cooling effect \nwhich arises from anthropogenic aerosols peaked in the late 20th century \n(high con\ufb01dence). {WGI SPM A1.1, WGI SPM A1.3, WGI SPM A.2.1, \nWGI Figure SPM.2, WGI TS 2.2, WGI 2ES, WGI Figure 6.1}\n\nDocument 16: Land-Use \nChange and \nForestry \n(LULUCF)\nwarmest \nmulti-century \nperiod in more \nthan 100,000 \nyears\n410 ppm CO2\n1866 ppb CH4\n332 ppb N2O\n200\n400 Parts per billion (ppb)\nNitrous oxide\n\u00b0C\n0\n0.5\n1\n1.5\nKey\n*Other human drivers are predominantly cooling aerosols, but also \nwarming aerosols, land-use change (land-use re\ufb02ectance) and ozone.\nFigure 2.1: The causal chain from emissions to resulting \nwarming of the climate system. Emissions of GHG have \nincreased rapidly over recent decades (panel (a)). Global net \nanthropogenic GHG emissions include CO2 from fossil fuel \ncombustion and industrial processes (CO2-FFI) (dark green); \nnet CO2 from land use, land-use change and forestry (CO2-LULUCF) \n(green); CH4; N2O; and \ufb02uorinated gases (HFCs, PFCs, SF6, NF3) \n(light blue). These emissions have led to increases in the atmospheric \nconcentrations of several GHGs including the three major well-mixed \nGHGs CO2, CH4 and N2O (panel (b), annual values). To indicate their \nrelative importance each subpanel\u2019s vertical extent for CO2, CH4 and \nN2O is scaled to match the assessed individual direct effect (and, \nin the case of CH4 indirect effect via atmospheric chemistry impacts \non tropospheric ozone) of historical emissions on temperature \nchange from 1850\u20131900 to 2010\u20132019. This estimate arises from \nan assessment of effective radiative forcing and climate sensitivity. \nThe global surface temperature (shown as annual anomalies from \na 1850\u20131900 baseline) has increased by around 1.1\u00b0C since \n1850\u20131900 (panel (c)). The vertical bar on the right shows the \nestimated temperature (very likely range) during the warmest \nmulti-century period in at least the last 100,000 years, which \noccurred around 6500 years ago during the current interglacial \nperiod (Holocene).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":14,"topic":"Others"}}
{"id":"71786da5-a1f5-438b-9c71-45082c670abb","question":"Considering the necessity to limit global warming to 2\u00b0C with an 83% probability, what proportion of the world's coal reserves must remain unutilized?","reference_answer":"About 80% of coal reserves cannot be burned if warming is limited to 2\u00b0C.","reference_context":"Document 167: 83\nLong-Term Climate and Development Futures\nSection 3\n0\n1000\n500\n1500\n2000\n2020\na) Carbon budgets and emissions\nLifetime emissions from fossil fuel \ninfrastructure without additional abatement, \nif historical operating patterns are maintained\n2020\u20132030 CO2 emissions \nassuming constant at 2019 level\n1.5\u00b0C (>50% chance)\n2\u00b0C (83% chance)\n2\u00b0C (>67% chance)\nExisting\nExisting and\n planned\nHistorical emissions 1850-2019\n2\u00b0C\n(83%)\n1.5\u00b0C\n(>50%)\nCarbon budgets\n1000\n0\n2000\nRemaining \ncarbon budgets\ndiferent emissions \nscenarios and their \nranges of warming \nRemaining carbon budgets to limit warming to 1.5\u00b0C could \nsoon be exhausted, and those for 2\u00b0C largely depleted\nRemaining carbon budgets are similar to emissions from use of existing \nand planned fossil fuel infrastructure, without additional abatement\nthese emissions determine how \nmuch warming we will experience\nWarming since 1850-1900\n\u00b0C\nCumulative CO2 emissions (GtCO2) since 1850\nHistorical global\nwarming\nSSP1-1.9\nSSP1-2.6\nSSP2-4.5\nSSP3-7.0\nSSP5-8.5\n1000\n2000\n3000 \n4000\n4500\n\u20130.5\n0\n0.5\n1\n1.5\n2\n2.5\n3\nhistorical\nsince 2020\nCumulative CO2 emissions (GtCO2)\nthis line indicates \nmaximum emissions \nto stay within 2\u00b0C \nof warming (with \n83% chance)\nEvery ton of CO2 adds to global warming\nb) Cumulative CO2 emissions and warming until 2050\nFigure 3.5: Cumulative past, projected, and committed emissions, and associated global temperature changes.\n\nDocument 81: 58\nSection 2\nSection 1\nSection 2\nProjected cumulative future CO2 emissions over the lifetime of existing \nfossil fuel infrastructure without additional abatement95 exceed the \ntotal cumulative net CO2 emissions in pathways that limit warming to \n1.5\u00b0C (>50%) with no or limited overshoot. They are approximately \nequal to total cumulative net CO2 emissions in pathways that limit \nwarming to 2\u00b0C with a likelihood of 83%96 (see Figure 3.5). Limiting \nwarming to 2\u00b0C (>67%) or lower will result in stranded assets. \nAbout 80% of coal, 50% of gas, and 30% of oil reserves cannot be \nburned and emitted if warming is limited to 2\u00b0C. Signi\ufb01cantly more \nreserves are expected to remain unburned if warming is limited to \n1.5\u00b0C. (high con\ufb01dence) {WGIII SPM B.7, WGIII Box 6.3}\n95 \nAbatement here refers to human interventions that reduce the amount of GHGs that are released from fossil fuel infrastructure to the atmosphere. {WGIII SPM footnote 34}\n96 \nWGI provides carbon budgets that are in line with limiting global warming to temperature limits with different likelihoods, such as 50%, 67% or 83%. {WGI Table SPM.2}\nTable 2.2 Projected global emissions in 2030 associated with policies implemented by the end of 2020 and NDCs announced prior to COP26, and associated \nemissions gaps. Emissions projections for 2030 and gross differences in emissions are based on emissions of 52\u201356 GtCO2-eq yr\u20131 in 2019 as assumed in underlying model \nstudies97. (medium con\ufb01dence) {WGIII Table SPM.1} (Table 3.1, Cross-Section Box.2) \n95 \nAbatement here refers to human interventions that reduce the amount of GHGs that are released from fossil fuel infrastructure to the atmosphere. {WGIII SPM footnote 34}\n96 \nWGI provides carbon budgets that are in line with limiting global warming to temperature limits with different likelihoods, such as 50%, 67% or 83%.\n\nDocument 168: Panel (a) Assessed remaining carbon budgets to limit \nwarming more likely than not to 1.5\u00b0C, to 2\u00b0C with a 83% and 67% likelihood, compared to cumulative emissions corresponding to constant 2019 emissions until 2030, existing and \nplanned fossil fuel infrastructures (in GtCO2). For remaining carbon budgets, thin lines indicate the uncertainty due to the contribution of non-CO2 warming. For lifetime emissions from \nfossil fuel infrastructure, thin lines indicate the assessed sensitivity range. Panel (b) Relationship between cumulative CO2 emissions and the increase in global surface temperature. \nHistorical data (thin black line) shows historical CO2 emissions versus observed global surface temperature increase relative to the period 1850-1900. The grey range with its central \nline shows a corresponding estimate of the human-caused share of historical warming. Coloured areas show the assessed very likely range of global surface temperature projections, \nand thick coloured central lines show the median estimate as a function of cumulative CO2 emissions for the selected scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. \nProjections until 2050 use the cumulative CO2 emissions of each respective scenario, and the projected global warming includes the contribution from all anthropogenic forcers. {WGI SPM D.1, \nWGI Figure SPM.10, WGI Table SPM.2; WGIII SPM B.1, WGIII SPM B.7, WGIII 2.7; SR1.5 SPM C.1.3}\n\nDocument 181: 86\nSection 3\nSection 1\nSection 3\n2000\n2020\n2040\n2060\n2080\n2100\n0\n20\n40\n60\n2000\n2020\n2040\n2060\n2080\n2100\n0\n20\n40\n60\n2000\n2020\n2040\n2060\n2080\n2100\n2000\n2020\n2040\n2060\n2080\n2100\nGigatons of CO2 equivalent per year (GtCO2-eq\/yr) \nCO2\nGHG\nCO2\nGHG\nCH4\nCO2\nGHG\nCH4\na) While keeping warming to 1.5\u00b0C    \n(>50%) with no or limited overshoot\nb) While keeping warming to  2\u00b0C    (>67%)\nc) Timing for net zero \nnet zero\nnet zero\nHistorical\nHistorical\nPolicies in place in 2020\nPolicies in place in 2020\nGHGs reach net zero \nlater than CO2\nnot all \nscenarios \nreach net \nzero GHG \nby 2100\nGlobal modelled pathways that limit warming to 1.5\u00b0C (>50%) with \nno or limited overshoot reach  net zero  CO2 emissions around 2050\nTotal  greenhouse gases (GHG)  reach net zero later\nFigure 3.6: Total GHG, CO2 and CH4 emissions and timing of reaching net zero in different mitigation pathways. Top row: GHG, CO2 and CH4 emissions over time (in \nGtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour \n(blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows \npathways that limit warming to 2\u00b0C (>67%) (C3).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":167,"topic":"Climate Change Projections"}}
{"id":"c858090c-f5f4-4aa1-9300-b6b7e3e72ec1","question":"In the context of the IPCC AR6 WGI report, how do the various colors and patterns of hexagons in the inhabited regions figure correspond to the confidence levels and data availability regarding observed climatic changes?","reference_answer":"The colors in the figure represent the four outcomes of the assessment on observed changes. Striped hexagons (white and light-grey) indicate low agreement in the type of change for the region as a whole, and grey hexagons indicate limited data and\/or literature that prevents an assessment of the region as a whole. Other colors indicate at least medium confidence in the observed change.","reference_context":"Document 47: Panel (a) The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size \nin their approximate geographical location (see legend for regional acronyms). All assessments are made for each region as a whole and for the 1950s to the present. Assessments made \non different time scales or more local spatial scales might differ from what is shown in the \ufb01gure. The colours in each panel represent the four outcomes of the assessment on observed \nchanges. Striped hexagons (white and light-grey) are used where there is low agreement in the type of change for the region as a whole, and grey hexagons are used when there is limited \ndata and\/or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium con\ufb01dence in the observed change. The con\ufb01dence level for the human \nin\ufb02uence on these observed changes is based on assessing trend detection and attribution and event attribution literature, and it is indicated by the number of dots: three dots for \nhigh con\ufb01dence, two dots for medium con\ufb01dence and one dot for low con\ufb01dence (single, \ufb01lled dot: limited agreement; single, empty dot: limited evidence). For hot extremes, the evidence \nis mostly drawn from changes in metrics based on daily maximum temperatures; regional studies using other indices (heatwave duration, frequency and intensity) are used in addition. For \nheavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or \ufb01ve-day precipitation amounts using global and regional studies. Agricultural and \necological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence on changes in surface soil moisture, water \nbalance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. Panel (b) shows the average level of vulnerability amongst a \ncountry\u2019s population against 2019 CO2-FFI emissions per- capita per country for the 180 countries for which both sets of metrics are available. Vulnerability information is based on two \nglobal indicator systems, namely INFORM and World Risk Index.\n\nDocument 48: For hot extremes, the evidence \nis mostly drawn from changes in metrics based on daily maximum temperatures; regional studies using other indices (heatwave duration, frequency and intensity) are used in addition. For \nheavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or \ufb01ve-day precipitation amounts using global and regional studies. Agricultural and \necological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence on changes in surface soil moisture, water \nbalance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. Panel (b) shows the average level of vulnerability amongst a \ncountry\u2019s population against 2019 CO2-FFI emissions per- capita per country for the 180 countries for which both sets of metrics are available. Vulnerability information is based on two \nglobal indicator systems, namely INFORM and World Risk Index. Countries with a relatively low average vulnerability often have groups with high vulnerability within their population and \nvice versa. The underlying data includes, for example, information on poverty, inequality, health care infrastructure or insurance coverage. Panel (c) Observed impacts on ecosystems \nand human systems attributed to climate change at global and regional scales. Global assessments focus on large studies, multi-species, meta-analyses and large reviews. Regional \nassessments consider evidence on impacts across an entire region and do not focus on any country in particular. For human systems, the direction of impacts is assessed and both \nadverse and positive impacts have been observed e.g., adverse impacts in one area or food item may occur with positive impacts in another area or food item (for more details and \nmethodology see WGII SMTS.1).  Physical water availability includes balance of water available from various sources including ground water, water quality and demand for water. \nGlobal mental health and displacement assessments re\ufb02ect only assessed regions. Con\ufb01dence levels re\ufb02ect the assessment of attribution of the observed impact to climate change. \n{WGI Figure SPM.3, Table TS.5, Interactive Atlas; WGII Figure SPM.2, WGII SMTS.1, WGII 8.3.1, Figure 8.5; ; WGIII 2.2.3}\n\nDocument 46: {WGI SPM C.2.6; WGII SPM B.1.5, WGII Figure TS.9, \nWGII 6 ES}\nClimate change has adversely affected human physical health globally \nand mental health in assessed regions (very high con\ufb01dence), and is \ncontributing to humanitarian crises where climate hazards interact \nwith high vulnerability (high con\ufb01dence). In all regions increases in \nextreme heat events have resulted in human mortality and morbidity \n(very high con\ufb01dence). The occurrence of climate-related food-borne and \nwater-borne diseases has increased (very high con\ufb01dence). The incidence \nof vector-borne diseases has increased from range expansion and\/or \nincreased reproduction of disease vectors (high con\ufb01dence). Animal and \nhuman diseases, including zoonoses, are emerging in new areas (high \ncon\ufb01dence). In assessed regions, some mental health challenges are \nassociated with increasing temperatures (high con\ufb01dence), trauma from \nextreme events (very high con\ufb01dence), and loss of livelihoods and culture \nFigure 2.3: Both vulnerability to current climate extremes and historical contribution to climate change are highly heterogeneous with many of those who have \nleast contributed to climate change to date being most vulnerable to its impacts. Panel (a) The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size \nin their approximate geographical location (see legend for regional acronyms). All assessments are made for each region as a whole and for the 1950s to the present. Assessments made \non different time scales or more local spatial scales might differ from what is shown in the \ufb01gure. The colours in each panel represent the four outcomes of the assessment on observed \nchanges. Striped hexagons (white and light-grey) are used where there is low agreement in the type of change for the region as a whole, and grey hexagons are used when there is limited \ndata and\/or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium con\ufb01dence in the observed change.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":47,"topic":"Climate Change Assessment"}}
{"id":"716d38bb-fd29-434e-9e96-ecec84d9ca6e","question":"Considering the IPCC's assessment, if a significant volcanic eruption were to transpire imminently, how might this event influence the trajectory of anthropogenic climate change effects within a short-term temporal frame, and what would be the expected duration of such an impact?","reference_answer":"If a large explosive volcanic eruption were to occur in the near term, it would temporarily and partially mask human-caused climate change by reducing global surface temperature and precipitation, especially over land, for one to three years (medium confidence).","reference_context":"Document 226: 98\nSection 4\nSection 1\nSection 4\nGlobal warming will continue to increase in the near term (2021\u20132040) \nmainly due to increased cumulative CO2 emissions in nearly all \nconsidered scenarios and pathways. In the near term, every \nregion in the world is projected to face further increases in \nclimate hazards (medium to high con\ufb01dence, depending on \nregion and hazard), increasing multiple risks to ecosystems \nand humans (very high con\ufb01dence). In the near term, natural \nvariability149 will modulate human-caused changes, either attenuating \nor amplifying projected changes, especially at regional scales, with little \neffect on centennial global warming. Those modulations are important \nto consider in adaptation planning. Global surface temperature in any \nsingle year can vary above or below the long-term human-induced \ntrend, due to natural variability. By 2030, global surface temperature \nin any individual year could exceed 1.5\u00b0C relative to 1850\u20131900 with a \nprobability between 40% and 60%, across the five scenarios assessed \nin WGI (medium confidence). The occurrence of individual years with \nglobal surface temperature change above a certain level does not \nimply that this global warming level has been reached. If a large \nexplosive volcanic eruption were to occur in the near term150 , it \nwould temporarily and partially mask human-caused climate change \nby reducing global surface temperature and precipitation, especially \nover land, for one to three years (medium con\ufb01dence). {WGI SPM B.1.3, \nWGI SPM B.1.4, WGI SPM C.1, WGI SPM C.2, WGI Cross-Section Box TS.1, \nWGI Cross-Chapter Box 4.1; WGII SPM B.3, WGII SPM B.3.1; \nWGIII Box SPM.1 Figure 1}\nThe level of risk for humans and ecosystems will depend on near-term \ntrends in vulnerability, exposure, level of socio-economic \ndevelopment and adaptation (high con\ufb01dence).\n\nDocument 203: 92\nSection 4\nSection 1\nSection 4\nSection 4 : Near-Term Responses in a Changing Climate\n4.1 The Timing and Urgency of Climate Action\nThe magnitude and rate of climate change and associated risks \ndepend strongly on near-term mitigation and adaptation actions \n(very high con\ufb01dence). Global warming is more likely than not to reach \n1.5\u00b0C between 2021 and 2040 even under the very low GHG emission \nscenarios (SSP1-1.9), and likely or very likely to exceed 1.5\u00b0C under \nhigher emissions scenarios141. Many adaptation options have medium \nor high feasibility up to 1.5\u00b0C (medium to high con\ufb01dence, depending \non option), but hard limits to adaptation have already been reached \nin some ecosystems and the effectiveness of adaptation to reduce \nclimate risk will decrease with increasing warming (high con\ufb01dence). \nSocietal choices and actions implemented in this decade determine the \nextent to which medium- and long-term pathways will deliver higher or \nlower climate resilient development (high con\ufb01dence). Climate resilient \ndevelopment prospects are increasingly limited if current greenhouse \ngas emissions do not rapidly decline, especially if 1.5\u00b0C global warming \nis exceeded in the near term (high con\ufb01dence). Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}.\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 227: If a large \nexplosive volcanic eruption were to occur in the near term150 , it \nwould temporarily and partially mask human-caused climate change \nby reducing global surface temperature and precipitation, especially \nover land, for one to three years (medium con\ufb01dence). {WGI SPM B.1.3, \nWGI SPM B.1.4, WGI SPM C.1, WGI SPM C.2, WGI Cross-Section Box TS.1, \nWGI Cross-Chapter Box 4.1; WGII SPM B.3, WGII SPM B.3.1; \nWGIII Box SPM.1 Figure 1}\nThe level of risk for humans and ecosystems will depend on near-term \ntrends in vulnerability, exposure, level of socio-economic \ndevelopment and adaptation (high con\ufb01dence). In the near term, \nmany climate-associated risks to natural and human systems depend \nmore strongly on changes in these systems\u2019 vulnerability and exposure \nthan on differences in climate hazards between emissions scenarios \n(high con\ufb01dence). Future exposure to climatic hazards is increasing \nglobally due to socio-economic development trends including growing \ninequality, and when urbanisation or migration increase exposure \n(high con\ufb01dence). Urbanisation increases hot extremes (very high \ncon\ufb01dence) and precipitation runoff intensity (high con\ufb01dence). \nIncreasing urbanisation in low-lying and coastal zones will be a major \ndriver of increasing exposure to extreme river\ufb02ow events and sea level \nrise hazards, increasing risks (high con\ufb01dence) (Figure 4.3). Vulnerability \nwill also rise rapidly in low-lying Small Island Developing States and \natolls in the context of sea level rise (high con\ufb01dence) (see Figure 3.4 and \nFigure 4.3). Human vulnerability will concentrate in informal settlements \nand rapidly growing smaller settlements; and vulnerability in rural \nareas will be heightened by reduced habitability and high reliance on \nclimate-sensitive livelihoods (high con\ufb01dence). Human and ecosystem \nvulnerability are interdependent (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":226,"topic":"Climate Change Assessment"}}
{"id":"7c120e3b-bd55-40ef-97dc-476348cf8294","question":"Considering the IPCC's projections, what is the anticipated reduction in global greenhouse gas emissions by the year 2050, expressed as a percentage relative to 2019 levels, under the pathways that are designed to keep temperature increases to no more than 1.5\u00b0C above pre-industrial levels with a greater than 50% likelihood and minimal overshoot?","reference_answer":"84 [73 to 98]%","reference_context":"Document 208: {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems. In modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited \novershoot and in those that limit warming to 2\u00b0C (>67%) and assume immediate action, global GHG emissions \nare projected to peak in the early 2020s followed by rapid and deep reductions. As adaptation options often have \nlong implementation times, accelerated implementation of adaptation, particularly in this decade, is important \nto close adaptation gaps. (high con\ufb01dence)\n\nDocument 214: Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4). (high con\ufb01dence) {WGI SPM B.1, WGI SPM B.1.3, WGI \nSPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM \nC.2, WGII SPM C.3.1, WGII Figure SPM.4b; SROCC SPM C.3.4, SROCC \nFigure 3.4, SROCC Figure SPM.5}\nNear-term actions that limit global warming to close to 1.5\u00b0C \nwould substantially reduce projected losses and damages related \nto climate change in human systems and ecosystems, compared \nto higher warming levels, but cannot eliminate them all (very \nhigh con\ufb01dence). The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).\n\nDocument 213: Positive (solid \ufb01lled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to \nGHG emissions from the year 2019. The category \u201cenergy supply (including electricity)\u201d includes bioenergy with carbon capture and storage and direct air carbon capture and storage. \n{WGIII Box TS.5, WGIII 3.3, WGIII 3.4, WGIII 6.6, WGIII 10.3, WGIII 11.3} (Cross-Section Box.2)\nAccelerated implementation of adaptation will improve well-being by reducing losses and damages, especially \nfor vulnerable populations. Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4).\n\nDocument 207: In pathways \nthat limit warming to 1.5\u00b0C (>50%) with no or limited overshoot, net \nglobal GHG emissions are projected to fall by 43 [34 to 60]%143 below \n2019 levels by 2030, 60 [49 to 77]% by 2035, 69 [58 to 90]% by 2040 \nand 84 [73 to 98]% by 2050 (high con\ufb01dence) (Section 2.3.1, Table 2.2, \nFigure 2.5, Table 3.1)144. Global modelled pathways that limit warming \nto 2\u00b0C (>67%) have reductions in GHG emissions below 2019 levels \nof 21 [1 to 42]% by 2030, 35 [22 to 55] % by 2035, 46 [34 to 63] \n% by 2040 and 64 [53 to 77]% by 2050145 (high con\ufb01dence). Global \nGHG emissions associated with NDCs announced prior to COP26 would \nmake it likely that warming would exceed 1.5\u00b0C (high con\ufb01dence) \nand limiting warming to 2\u00b0C (>67%) would then imply a rapid \nacceleration of emission reductions during 2030\u20132050, around \n70% faster than in pathways where immediate action is taken to \nlimit warming to 2\u00b0C (>67%) (medium con\ufb01dence) (Section 2.3.1) \nContinued investments in unabated high-emitting infrastructure146 and \nlimited development and deployment of low-emitting alternatives \nprior to 2030 would act as barriers to this acceleration and increase \nfeasibility risks (high confidence). {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":208,"topic":"Climate Change Action"}}
{"id":"075f797b-96f5-491a-a3b9-6f5c2a321988","question":"According to the IPCC report, how does the integration of varied knowledge systems and the forging of partnerships, specifically with marginalized groups, contribute to the advancement of climate resilient development?","reference_answer":"Drawing on diverse knowledge and partnerships, including with women, youth, Indigenous Peoples, local communities, and ethnic minorities can facilitate climate resilient development and has allowed locally appropriate and socially acceptable solutions.","reference_context":"Document 281: Multi-level, \nhybrid and cross-sector governance facilitates appropriate consideration \nfor co-bene\ufb01ts and trade-offs, particularly in land sectors where decision \nprocesses range from farm level to national scale (high con\ufb01dence). \nConsideration of climate justice can help to facilitate shifting development \npathways towards sustainability. {WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, \nSRCCL TS.1}\nDrawing on diverse knowledge and partnerships, including \nwith women, youth, Indigenous Peoples, local communities, and \nethnic minorities can facilitate climate resilient development \nand has allowed locally appropriate and socially acceptable \nsolutions (high con\ufb01dence). {WGII SPM D.2, D.2.1}\nMany regulatory and economic instruments have already been \ndeployed successfully. These instruments could support deep \nemissions reductions if scaled up and applied more widely. \nPractical experience has informed instrument design and helped to \nimprove predictability, environmental effectiveness, economic ef\ufb01ciency, \nand equity. (high con\ufb01dence) {WGII SPM E.4; WGIII SPM E.4.2}\nScaling up and enhancing the use of regulatory instruments, \nconsistent with national circumstances, can improve mitigation \noutcomes in sectoral applications (high con\ufb01dence), and \nregulatory instruments that include \ufb02exibility mechanisms \ncan reduce costs of cutting emissions (medium con\ufb01dence). \n{WGII SPM C.5.4; WGIII SPM E.4.1} \nWhere implemented, carbon pricing instruments have incentivized \nlow-cost emissions reduction measures, but have been less \neffective, on their own and at prevailing prices during the \nassessment period, to promote higher-cost measures necessary \nfor further reductions (medium con\ufb01dence).\n\nDocument 282: Practical experience has informed instrument design and helped to \nimprove predictability, environmental effectiveness, economic ef\ufb01ciency, \nand equity. (high con\ufb01dence) {WGII SPM E.4; WGIII SPM E.4.2}\nScaling up and enhancing the use of regulatory instruments, \nconsistent with national circumstances, can improve mitigation \noutcomes in sectoral applications (high con\ufb01dence), and \nregulatory instruments that include \ufb02exibility mechanisms \ncan reduce costs of cutting emissions (medium con\ufb01dence). \n{WGII SPM C.5.4; WGIII SPM E.4.1} \nWhere implemented, carbon pricing instruments have incentivized \nlow-cost emissions reduction measures, but have been less \neffective, on their own and at prevailing prices during the \nassessment period, to promote higher-cost measures necessary \nfor further reductions (medium con\ufb01dence). Revenue from carbon \ntaxes or emissions trading can be used for equity and distributional \ngoals, for example to support low-income households, among other \n4.7 Governance and Policy for Near-Term Climate Change Action\nEffective climate action requires political commitment, well-aligned multi-level governance and institutional \nframeworks, laws, policies and strategies. It needs clear goals, adequate \ufb01nance and \ufb01nancing tools, coordination \nacross multiple policy domains, and inclusive governance processes. Many mitigation and adaptation policy \ninstruments have been deployed successfully, and could support deep emissions reductions and climate resilience \nif scaled up and applied widely, depending on national circumstances. Adaptation and mitigation action bene\ufb01ts \nfrom drawing on diverse knowledge. (high con\ufb01dence)\n\nDocument 242: 102\nSection 4\nSection 1\nSection 4\nand burdens, especially for vulnerable countries and communities. \n{WGIII SPM D.3, WGIII SPM D.3.2, WGIII SPM D.3.3, WGIII SPM D.3.4, \nWGIII TS Box TS.4}\nDevelopment priorities among countries also re\ufb02ect different \nstarting points and contexts, and enabling conditions for \nshifting development pathways towards increased sustainability \nwill therefore differ, giving rise to different needs (high \ncon\ufb01dence). Implementing just transition principles through collective \nand participatory decision-making processes is an effective way of \nintegrating equity principles into policies at all scales depending \non national circumstances, while in several countries just transition \ncommissions, task forces and national policies have been established \n(medium con\ufb01dence). {WGIII SPM D.3.1, WGIII SPM D.3.3}\nMany economic and regulatory instruments have been \neffective in reducing emissions and practical experience has \ninformed instrument design to improve them while addressing \ndistributional goals and social acceptance (high con\ufb01dence). The \ndesign of behavioural interventions, including the way that choices are \npresented to consumers work synergistically with price signals, making \nthe combination more effective (medium con\ufb01dence). Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence).\n\nDocument 280: This requires adequate institutional capacity at \nall levels (high con\ufb01dence). Vulnerabilities and climate risks are often \nreduced through carefully designed and implemented laws, policies, \nparticipatory processes, and interventions that address context \nspeci\ufb01c inequities such as based on gender, ethnicity, disability, age, \nlocation and income (high con\ufb01dence). Policy support is in\ufb02uenced by \nIndigenous Peoples, businesses, and actors in civil society, including, \nyouth, labour, media, and local communities, and effectiveness is \nenhanced by partnerships between many different groups in society \n(high con\ufb01dence). Climate-related litigation is growing, with a large \nnumber of cases in some developed countries and with a much smaller \nnumber in some developing countries, and in some cases has in\ufb02uenced \nthe outcome and ambition of climate governance (medium con\ufb01dence). \n{WGII SPM C2.6, WGII SPM C.5.2, WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.3.1; WGIII SPM E3.2, WGIII SPM E.3.3}\nEffective climate governance is enabled by inclusive decision \nprocesses, allocation of appropriate resources, and institutional \nreview, monitoring and evaluation (high con\ufb01dence). Multi-level, \nhybrid and cross-sector governance facilitates appropriate consideration \nfor co-bene\ufb01ts and trade-offs, particularly in land sectors where decision \nprocesses range from farm level to national scale (high con\ufb01dence). \nConsideration of climate justice can help to facilitate shifting development \npathways towards sustainability. {WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, \nSRCCL TS.1}\nDrawing on diverse knowledge and partnerships, including \nwith women, youth, Indigenous Peoples, local communities, and \nethnic minorities can facilitate climate resilient development \nand has allowed locally appropriate and socially acceptable \nsolutions (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":281,"topic":"Climate Change Action"}}
{"id":"09fc5c21-f68c-49a1-906b-856b88e68399","question":"Considering the near-term projections, how are cumulative CO2 emissions expected to influence climate hazards, and what are the potential implications for ecosystem and human risk levels?","reference_answer":"Global warming will continue to increase in the near term (2021\u20132040) mainly due to increased cumulative CO2 emissions.","reference_context":"Document 227: If a large \nexplosive volcanic eruption were to occur in the near term150 , it \nwould temporarily and partially mask human-caused climate change \nby reducing global surface temperature and precipitation, especially \nover land, for one to three years (medium con\ufb01dence). {WGI SPM B.1.3, \nWGI SPM B.1.4, WGI SPM C.1, WGI SPM C.2, WGI Cross-Section Box TS.1, \nWGI Cross-Chapter Box 4.1; WGII SPM B.3, WGII SPM B.3.1; \nWGIII Box SPM.1 Figure 1}\nThe level of risk for humans and ecosystems will depend on near-term \ntrends in vulnerability, exposure, level of socio-economic \ndevelopment and adaptation (high con\ufb01dence). In the near term, \nmany climate-associated risks to natural and human systems depend \nmore strongly on changes in these systems\u2019 vulnerability and exposure \nthan on differences in climate hazards between emissions scenarios \n(high con\ufb01dence). Future exposure to climatic hazards is increasing \nglobally due to socio-economic development trends including growing \ninequality, and when urbanisation or migration increase exposure \n(high con\ufb01dence). Urbanisation increases hot extremes (very high \ncon\ufb01dence) and precipitation runoff intensity (high con\ufb01dence). \nIncreasing urbanisation in low-lying and coastal zones will be a major \ndriver of increasing exposure to extreme river\ufb02ow events and sea level \nrise hazards, increasing risks (high con\ufb01dence) (Figure 4.3). Vulnerability \nwill also rise rapidly in low-lying Small Island Developing States and \natolls in the context of sea level rise (high con\ufb01dence) (see Figure 3.4 and \nFigure 4.3). Human vulnerability will concentrate in informal settlements \nand rapidly growing smaller settlements; and vulnerability in rural \nareas will be heightened by reduced habitability and high reliance on \nclimate-sensitive livelihoods (high con\ufb01dence). Human and ecosystem \nvulnerability are interdependent (high con\ufb01dence).\n\nDocument 228: Urbanisation increases hot extremes (very high \ncon\ufb01dence) and precipitation runoff intensity (high con\ufb01dence). \nIncreasing urbanisation in low-lying and coastal zones will be a major \ndriver of increasing exposure to extreme river\ufb02ow events and sea level \nrise hazards, increasing risks (high con\ufb01dence) (Figure 4.3). Vulnerability \nwill also rise rapidly in low-lying Small Island Developing States and \natolls in the context of sea level rise (high con\ufb01dence) (see Figure 3.4 and \nFigure 4.3). Human vulnerability will concentrate in informal settlements \nand rapidly growing smaller settlements; and vulnerability in rural \nareas will be heightened by reduced habitability and high reliance on \nclimate-sensitive livelihoods (high con\ufb01dence). Human and ecosystem \nvulnerability are interdependent (high con\ufb01dence). Vulnerability to \nclimate change for ecosystems will be strongly in\ufb02uenced by past, \npresent, and future patterns of human development, including from \nunsustainable consumption and production, increasing demographic \npressures, and persistent unsustainable use and management of \n149 See Annex I: Glossary. The main internal variability phenomena include El Ni\u00f1o\u2013Southern Oscillation, Paci\ufb01c Decadal Variability and Atlantic Multi-decadal Variability through \ntheir regional influence. The internal variability of global surface temperature in any single year is estimated to be about \u00b10.25\u00b0C (5 to 95% range, high confidence). \n{WGI SPM footnote 29, WGI SPM footnote 37}\n150 Based on 2500-year reconstructions, eruptions with a radiative forcing more negative than \u20131 Wm-2, related to the radiative effect of volcanic stratospheric aerosols in the \nliterature assessed in this report, occur on average twice per century. {WGI SPM footnote 38}\nland, ocean, and water (high con\ufb01dence). Several near-term risks can \nbe moderated with adaptation (high con\ufb01dence).\n\nDocument 226: 98\nSection 4\nSection 1\nSection 4\nGlobal warming will continue to increase in the near term (2021\u20132040) \nmainly due to increased cumulative CO2 emissions in nearly all \nconsidered scenarios and pathways. In the near term, every \nregion in the world is projected to face further increases in \nclimate hazards (medium to high con\ufb01dence, depending on \nregion and hazard), increasing multiple risks to ecosystems \nand humans (very high con\ufb01dence). In the near term, natural \nvariability149 will modulate human-caused changes, either attenuating \nor amplifying projected changes, especially at regional scales, with little \neffect on centennial global warming. Those modulations are important \nto consider in adaptation planning. Global surface temperature in any \nsingle year can vary above or below the long-term human-induced \ntrend, due to natural variability. By 2030, global surface temperature \nin any individual year could exceed 1.5\u00b0C relative to 1850\u20131900 with a \nprobability between 40% and 60%, across the five scenarios assessed \nin WGI (medium confidence). The occurrence of individual years with \nglobal surface temperature change above a certain level does not \nimply that this global warming level has been reached. If a large \nexplosive volcanic eruption were to occur in the near term150 , it \nwould temporarily and partially mask human-caused climate change \nby reducing global surface temperature and precipitation, especially \nover land, for one to three years (medium con\ufb01dence). {WGI SPM B.1.3, \nWGI SPM B.1.4, WGI SPM C.1, WGI SPM C.2, WGI Cross-Section Box TS.1, \nWGI Cross-Chapter Box 4.1; WGII SPM B.3, WGII SPM B.3.1; \nWGIII Box SPM.1 Figure 1}\nThe level of risk for humans and ecosystems will depend on near-term \ntrends in vulnerability, exposure, level of socio-economic \ndevelopment and adaptation (high con\ufb01dence).\n\nDocument 232: 99\nNear-Term Responses in a Changing Climate\nSection 4\n\u2022 Cryosphere-related changes in \ufb02oods, landslides, and water \navailability have the potential to lead to severe consequences for \npeople, infrastructure and the economy in most mountain regions \n(high con\ufb01dence). {WGII TS C.4.2}\n\u2022 The projected increase in frequency and intensity of heavy \nprecipitation (high con\ufb01dence) will increase rain-generated local \n\ufb02ooding (medium con\ufb01dence). {WGI Figure SPM.6, WGI SPM B.2.2; \nWGII TS C.4.5}\nMultiple climate change risks will increasingly compound and \ncascade in the near term (high con\ufb01dence). Many regions are \nprojected to experience an increase in the probability of compound \nevents with higher global warming (high con\ufb01dence) including \nconcurrent heatwaves and drought. Risks to health and food \nproduction will be made more severe from the interaction of sudden \nfood production losses from heat and drought, exacerbated by heat-\ninduced labour productivity losses (high con\ufb01dence) (Figure 4.3). These \ninteracting impacts will increase food prices, reduce household incomes, \nand lead to health risks of malnutrition and climate-related mortality \nwith no or low levels of adaptation, especially in tropical regions (high \ncon\ufb01dence). Concurrent and cascading risks from climate change to \nfood systems, human settlements, infrastructure and health will make \nthese risks more severe and more dif\ufb01cult to manage, including when \ninteracting with non-climatic risk drivers such as competition for land \nbetween urban expansion and food production, and pandemics (high \ncon\ufb01dence). Loss of ecosystems and their services has cascading and \nlong-term impacts on people globally, especially for Indigenous Peoples \nand local communities who are directly dependent on ecosystems, to \nmeet basic needs (high con\ufb01dence). Increasing transboundary risks \nare projected across the food, energy and water sectors as impacts \nfrom weather and climate extremes propagate through supply-chains, \nmarkets, and natural resource \ufb02ows (high con\ufb01dence) and may interact \nwith impacts from other crises such as pandemics.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":227,"topic":"Climate Change Impacts"}}
{"id":"0ac75b7c-744b-4470-ac08-cd396047446b","question":"Within the context of the IPCC's assessment, what is the updated likely range of equilibrium climate sensitivity, and how does this compare to the range presented in the AR5 report?","reference_answer":"The likely range of equilibrium climate sensitivity is 2.5\u00b0C to 4.0\u00b0C, with a best estimate of 3.0\u00b0C.","reference_context":"Document 112: Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating. The assessed best estimates and \nvery likely ranges of warming for 2081-2100 with respect to 1850\u20131900 \nvary from 1.4 [1.0 to 1.8]\u00b0C in the very low GHG emissions scenario \n(SSP1-1.9) to 2.7 [2.1 to 3.5]\u00b0C in the intermediate GHG emissions \nscenario (SSP2-4.5) and 4.4 [3.3 to 5.7]\u00b0C in the very high GHG emissions \nscenario (SSP5-8.5)113. {WGI SPM B.1.1, WGI Table SPM.1, WGI Figure \nSPM.4} (Cross-Section Box.2 Figure 1)\nModelled pathways consistent with the continuation of policies \nimplemented by the end of 2020 lead to global warming of \n3.2 [2.2 to 3.5]\u00b0C (5\u201395% range) by 2100 (medium con\ufb01dence) \n(see also Section 2.3.1). Pathways of >4\u00b0C (\u226550%) by 2100 would \nimply a reversal of current technology and\/or mitigation policy trends \n(medium con\ufb01dence).\n\nDocument 111: 68\nSection 3\nSection 1\nSection 3\nSection 3: Long-Term Climate and Development Futures\n3.1 Long-Term Climate Change, Impacts and Related Risks\nFuture warming will be driven by future emissions and will affect all major climate system components, with \nevery region experiencing multiple and co-occurring changes. Many climate-related risks are assessed to be \nhigher than in previous assessments, and projected long-term impacts are up to multiple times higher than \ncurrently observed. Multiple climatic and non-climatic risks will interact, resulting in compounding and cascading \nrisks across sectors and regions. Sea level rise, as well as other irreversible changes, will continue for thousands \nof years, at rates depending on future emissions. (high con\ufb01dence)\n3.1.1. Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating.\n\nDocument 205: The best estimates [and very likely ranges] of global warming for the different scenarios in the \nnear term are: 1.5 [1.2 to 1.7]\u00b0C (SSP1-1.9); 1.5 [1.2 to 1.8]\u00b0C (SSP1-2.6); 1.5 [1.2 to 1.8]\u00b0C (SSP2-4.5); 1.5 [1.2 to 1.8]\u00b0C (SSP3-7.0); and 1.6[1.3 to 1.9]\u00b0C (SSP5-8.5). \n{WGI SPM B.1.3, WGI Table SPM.1} (Cross-Section Box.2)\n142 Values in parentheses indicate the likelihood of limiting warming to the level speci\ufb01ed (see Cross-Section Box.2).\n143 Median and very likely range [5th to 95th percentile]. {WGIII SPM footnote 30}\n144 These numbers for CO2 are 48 [36 to 69]% in 2030, 65 [50 to 96] % in 2035, 80 [61 to109] % in 2040 and 99 [79 to 119]% in 2050.\n145 These numbers for CO2 are 22 [1 to 44]% in 2030, 37 [21 to 59] % in 2035, 51 [36 to 70] % in 2040 and 73 [55 to 90]% in 2050.\n146 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply.\n\nDocument 114: {WGIII SPM C.1.3}\n112  Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21}\n113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]\u00b0C (SSP1-1.9); 1.8 [1.3 to 2.4]\u00b0C (SSP1-2.6); 2.7 [2.1 to 3.5]\u00b0C (SSP2-4.5); 3.6 [2.8 to 4.6]\u00b0C \n(SSP3-7.0); and 4.4 [3.3 to 5.7]\u00b0C (SSP5-8.5). {WGI Table SPM.1} (Cross-Section Box.2)\n114 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). In all scenarios considered by WGI except the very high emissions scenario, the midpoint of the \n\ufb01rst 20-year running average period during which the assessed global warming reaches 1.5\u00b0C lies in the \ufb01rst half of the 2030s. In the very high GHG emissions scenario, this \nmid-point is in the late 2020s. The median \ufb01ve-year interval at which a 1.5\u00b0C global warming level is reached (50% probability) in categories of modelled pathways considered \nin WGIII is 2030\u20132035.","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":112,"topic":"Others"}}
{"id":"0be4ee2b-ec91-404b-8493-740facb844c3","question":"Considering the IPCC report, what are the specific barriers in developing countries, especially the least developed ones, that hinder the uptake of low-emission technologies, despite the recognized need for such innovations?","reference_answer":"The lag in adoption of low-emission technologies in most developing countries is due in part to weaker enabling conditions, including limited finance, technology development and transfer, and capacity building.","reference_context":"Document 295: 113\nNear-Term Responses in a Changing Climate\nSection 4\n4.8.3. Technology Innovation, Adoption, Diffusion and \nTransfer \nEnhancing \ntechnology \ninnovation \nsystems \ncan \nprovide \nopportunities to lower emissions growth and create social and \nenvironmental co-bene\ufb01ts. Policy packages tailored to national \ncontexts and technological characteristics have been effective \nin supporting low-emission innovation and technology diffusion. \nSupport for successful low-carbon technological innovation \nincludes public policies such as training and R&D, complemented by \nregulatory and market-based instruments that create incentives and \nmarket opportunities such as appliance performance standards and \nbuilding codes. (high confidence) {WGIII SPM B.4, WGIII SPM B.4.4, \nWGIII SPM E.4.3, WGIII SPM E4.4}\nInternational cooperation on innovation systems and technology \ndevelopment and transfer, accompanied by capacity building, \nknowledge sharing, and technical and \ufb01nancial support can \naccelerate the global diffusion of mitigation technologies, \npractices and policies and align these with other development \nobjectives (high con\ufb01dence). Choice architecture can help end-users \nadopt technology and low-GHG-intensive options (high con\ufb01dence). \nAdoption of low-emission technologies lags in most developing countries, \nparticularly least developed ones, due in part to weaker enabling \nconditions, including limited \ufb01nance, technology development and \ntransfer, and capacity building (medium con\ufb01dence).\n\nDocument 299: 114\nSection 4\nSection 1\nSection 4\nInternational cooperation on innovation works best when tailored to \nand bene\ufb01cial for local value chains, when partners collaborate on an \nequal footing, and when capacity building is an integral part of the \neffort (medium con\ufb01dence). {WGIII SPM E.4.4, WGIII SPM E.6.2}\nTechnological innovation can have trade-offs that include \nexternalities such as new and greater environmental impacts and \nsocial inequalities; rebound effects leading to lower net emission \nreductions or even emission increases; and overdependence on \nforeign knowledge and providers (high con\ufb01dence). Appropriately \ndesigned policies and governance have helped address distributional \nimpacts and rebound effects (high con\ufb01dence). For example, digital \ntechnologies can promote large increases in energy ef\ufb01ciency through \ncoordination and an economic shift to services (high con\ufb01dence). \nHowever, societal digitalization can induce greater consumption of \ngoods and energy and increased electronic waste as well as negatively \nimpacting labour markets and worsening inequalities between \nand within countries (medium con\ufb01dence). Digitalisation requires \nappropriate governance and policies in order to enhance mitigation \npotential (high con\ufb01dence). Effective policy packages can help to \nrealise synergies, avoid trade-offs and\/or reduce rebound effects: \nthese might include a mix of ef\ufb01ciency targets, performance standards, \ninformation provision, carbon pricing, \ufb01nance and technical assistance \n(high con\ufb01dence). {WGIII SPM B.4.2, WGIII SPM B.4.3, WGIII SPM E.4.4, \nWGIII TS 6.5, WGIII Cross-Chapter Box 11 on Digitalization in Chapter 16}\nTechnology transfer to expand use of digital technologies for land use \nmonitoring, sustainable land management, and improved agricultural \nproductivity supports reduced emissions from deforestation and land \nuse change while also improving GHG accounting and standardisation \n(medium con\ufb01dence).\n\nDocument 296: (high confidence) {WGIII SPM B.4, WGIII SPM B.4.4, \nWGIII SPM E.4.3, WGIII SPM E4.4}\nInternational cooperation on innovation systems and technology \ndevelopment and transfer, accompanied by capacity building, \nknowledge sharing, and technical and \ufb01nancial support can \naccelerate the global diffusion of mitigation technologies, \npractices and policies and align these with other development \nobjectives (high con\ufb01dence). Choice architecture can help end-users \nadopt technology and low-GHG-intensive options (high con\ufb01dence). \nAdoption of low-emission technologies lags in most developing countries, \nparticularly least developed ones, due in part to weaker enabling \nconditions, including limited \ufb01nance, technology development and \ntransfer, and capacity building (medium con\ufb01dence). {WGIII SPM B.4.2, \nWGIII SPM E.6.2, WGIII SPM C.10.4, WGIII 16.5}\nHigher mitigation investment \ufb02ows required for \nall sectors and regions to limit global warming\nActual yearly \ufb02ows compared to average annual needs \nin billions USD (2015) per year\nMultiplication \nfactors*\n0\n1000\n1500\n2000\n2500\n3000\n500\n2017\n2018\n2019\n2020\nAnnual mitigation investment \nneeds (averaged until 2030)\nIEA data mean \n2017\u20132020\nAverage \ufb02ows\n0\n1000\n1500\n2000\n2500\n3000\n500\n*Multiplication factors indicate the x-fold increase between yearly \nmitigation \ufb02ows to average yearly mitigation investment needs. \nGlobally, current mitigation \ufb01nancial \ufb02ows are a factor of three \nto six below the average levels up to 2030.\n\nDocument 90: Current development pathways may create behavioural, \nspatial, economic and social barriers to accelerated mitigation at all \nscales (high con\ufb01dence). Choices made by policymakers, citizens, the \nprivate sector and other stakeholders in\ufb02uence societies\u2019 development \npathways (high con\ufb01dence). Structural factors of national circumstances \nand capabilities (e.g., economic and natural endowments, political \nsystems and cultural factors and gender considerations) affect the \nbreadth and depth of climate governance (medium con\ufb01dence). The \nextent to which civil society actors, political actors, businesses, youth, \nlabour, media, Indigenous Peoples, and local communities are engaged \nin\ufb02uences political support for climate change mitigation and eventual \npolicy outcomes (medium con\ufb01dence). {WGIII SPM C.3.6, WGIII SPM E.1.1, \nWGIII SPM E.2.1, WGIII SPM E.3.3}\nThe adoption of low-emission technologies lags in most \ndeveloping countries, particularly least developed ones, \ndue in part to weaker enabling conditions, including limited \n\ufb01nance, technology development and transfer, and capacity \n(medium con\ufb01dence). In many countries, especially those with \nlimited institutional capacity, several adverse side-effects have \nbeen observed as a result of diffusion of low-emission technology, \ne.g., low-value employment, and dependency on foreign knowledge \nand suppliers (medium con\ufb01dence). Low-emission innovation along \nwith strengthened enabling conditions can reinforce development \nbene\ufb01ts, which can, in turn, create feedbacks towards greater public \nsupport for policy (medium con\ufb01dence). Persistent and region-speci\ufb01c \nbarriers also continue to hamper the economic and political feasibility \nof deploying AFOLU mitigation options (medium con\ufb01dence). Barriers to \nimplementation of AFOLU mitigation include insuf\ufb01cient institutional and \n\ufb01nancial support, uncertainty over long-term additionality and trade-offs, \nweak governance, insecure land ownership, low incomes and the lack \nof access to alternative sources of income, and the risk of reversal (high \ncon\ufb01dence).","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":295,"topic":"Climate Change Action"}}
{"id":"cfdfc64a-7bdb-4ed1-877a-350fa613dfe6","question":"Considering a scenario of approximately 2\u00b0C global warming, how might food security be affected, specifically regarding the availability and quality of diets, and what populations are predicted to be most at risk?","reference_answer":"With about 2\u00b0C warming, climate-related changes in food availability and diet quality are estimated to increase nutrition-related diseases and the number of undernourished people, affecting tens to hundreds of millions of people, particularly among low-income households in low- and middle-income countries in sub-Saharan Africa, South Asia and Central America (high confidence).","reference_context":"Document 125: {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a). With about 2\u00b0C warming, climate-related \n120 Undetectable risk level indicates no associated impacts are detectable and attributable to climate change; moderate risk indicates associated impacts are both detectable and \nattributable to climate change with at least medium con\ufb01dence, also accounting for the other speci\ufb01c criteria for key risks; high risk indicates severe and widespread impacts that \nare judged to be high on one or more criteria for assessing key risks; and very high risk level indicates very high risk of severe impacts and the presence of signi\ufb01cant irreversibility \nor the persistence of climate-related hazards, combined with limited ability to adapt due to the nature of the hazard or impacts\/risks. {WGII Figure SPM.3}\n121 The Reasons for Concern (RFC) framework communicates scienti\ufb01c understanding about accrual of risk for \ufb01ve broad categories (WGII Figure SPM.3). RFC1: Unique and \nthreatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive \nproperties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots.\n\nDocument 126: {WGII Figure SPM.3}\n121 The Reasons for Concern (RFC) framework communicates scienti\ufb01c understanding about accrual of risk for \ufb01ve broad categories (WGII Figure SPM.3). RFC1: Unique and \nthreatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive \nproperties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme weather events: risks\/impacts to \nhuman health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wild\ufb01res, and coastal \ufb02ooding. RFC3: \nDistribution of impacts: risks\/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability. \nRFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives affected, species lost \nor ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused by global warming, \nsuch as ice sheet instability or thermohaline circulation slowing. Assessment methods include a structured expert elicitation based on the literature described in WGII SM16.6 \nand are identical to AR5 but are enhanced by a structured approach to improve robustness and facilitate comparison between AR5 and AR6. For further explanations of global \nrisk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}\nchanges in food availability and diet quality are estimated to increase \nnutrition-related diseases and the number of undernourished people, \naffecting tens (under low vulnerability and low warming) to hundreds of \nmillions of people (under high vulnerability and high warming), particularly \namong low-income households in low- and middle-income countries in \nsub-Saharan Africa, South Asia and Central America (high con\ufb01dence). \nFor example, snowmelt water availability for irrigation is projected \nto decline in some snowmelt dependent river basins by up to 20% \n(medium con\ufb01dence).\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 105: 64\nSection 2\nSection 1\nSection 2\nGlobal Warming Levels (GWLs)\nFor many climate and risk variables, the geographical patterns of changes in climatic impact-drivers110 and climate impacts for a level of global \nwarming111 are common to all scenarios considered and independent of timing when that level is reached. This motivates the use of GWLs as a \ndimension of integration. {WGI Box SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2)\nRisks\nDynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result \nin risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the \nReasons for Concern (RFCs) \u2013 \ufb01ve globally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature. \nRisks can also arise from climate change mitigation or adaptation responses when the response does not achieve its intended objective, or when \nit results in adverse effects for other societal objectives. {WGII SPM A, WGII Figure SPM.3, WGII Box TS.1, WGII Figure TS.4; SR1.5 Figure SPM.2; \nSROCC Errata Figure SPM.3; SRCCL Figure SPM.2} (3.1.2, Cross-Section Box.2 Figure 1, Figure 3.3)\n110 See Annex I: Glossary\n111 See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850\u20131900. The assessed time of when a certain global warming level \nis reached under a particular scenario is de\ufb01ned here as the mid-point of the \ufb01rst 20-year running average period during which the assessed average global surface temperature \nchange exceeds the level of global warming. {WGI SPM footnote 26, Cross-Section Box TS.1}","conversation_history":[],"metadata":{"question_type":"complex","seed_document_id":125,"topic":"Climate Change Risks"}}
{"id":"23671ece-c821-4737-a256-1c197bf4beb7","question":"Considering the interplay between climate change mitigation actions and the Sustainable Development Goals (SDGs), what are the projected CO2 emissions for the very low and low GHG emissions scenarios under the Shared Socioeconomic Pathways (SSPs), specifically SSP1-1.9 and SSP1-2.6?","reference_answer":"The very low and low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 emissions.","reference_context":"Document 100: 63\nCurrent Status and Trends\nSection 2\nCross-Section Box.2: Scenarios, Global Warming Levels, and Risks\nModelled scenarios and pathways102 are used to explore future emissions, climate change, related impacts and risks, and possible mitigation and \nadaptation strategies and are based on a range of assumptions, including socio-economic variables and mitigation options. These are quantitative \nprojections and are neither predictions nor forecasts. Global modelled emission pathways, including those based on cost effective approaches \ncontain regionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition of these assumptions. Most \ndo not make explicit assumptions about global equity, environmental justice or intra-regional income distribution. IPCC is neutral with regard \nto the assumptions underlying the scenarios in the literature assessed in this report, which do not cover all possible futures103. {WGI Box SPM.1; \nWGII Box SPM.1; WGIII Box SPM.1; SROCC Box SPM.1; SRCCL Box SPM.1} \nSocio-economic Development, Scenarios, and Pathways\nThe \ufb01ve Shared Socio-economic Pathways (SSP1 to SSP5) were designed to span a range of challenges to climate change mitigation and adaptation. \nFor the assessment of climate impacts, risk and adaptation, the SSPs are used for future exposure, vulnerability and challenges to adaptation. \nDepending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels104. \nThere are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1). \n{WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box TS.5, WGIII Annex III; SRCCL Box SPM.1, SRCCL Figure SPM.2}\nWGI assessed the climate response to \ufb01ve illustrative scenarios based on SSPs105 that cover the range of possible future development of anthropogenic \ndrivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and \nair pollution controls for aerosols and non-CH4 ozone precursors.\n\nDocument 101: Depending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels104. \nThere are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1). \n{WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box TS.5, WGIII Annex III; SRCCL Box SPM.1, SRCCL Figure SPM.2}\nWGI assessed the climate response to \ufb01ve illustrative scenarios based on SSPs105 that cover the range of possible future development of anthropogenic \ndrivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and \nair pollution controls for aerosols and non-CH4 ozone precursors. The high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5) have \nCO2 emissions that roughly double from current levels by 2100 and 2050, respectively106. The intermediate GHG emissions scenario (SSP2-4.5) \nhas CO2 emissions remaining around current levels until the middle of the century. The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8).\n\nDocument 103: WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019. The underlying assumptions on global GDP growth range from 2.5 to 3.5% per year in the 2019\u20132050 period \nand 1.3 to 2.1% per year in the 2050\u20132100 (5\u201395th percentile). {WGIII Box SPM.1}\n104 High mitigation challenges, for example, due to assumptions of slow technological change, high levels of global population growth, and high fragmentation as in the Shared \nSocio-economic Pathway SSP3, may render modelled pathways that limit warming to 2\u00b0C (> 67%) or lower infeasible (medium con\ufb01dence). {WGIII SPM C.1.4; SRCCL Box SPM.1}\n105 SSP-based scenarios are referred to as SSPx-y, where \u2018SSPx\u2019 refers to the Shared Socio-economic Pathway describing the socioeconomic trends underlying the scenarios, and \n\u2018y\u2019 refers to the level of radiative forcing (in watts per square metre, or Wm\u20132) resulting from the scenario in the year 2100. {WGI SPM footnote 22}\n106 Very high emission scenarios have become less likely but cannot be ruled out. Temperature levels > 4\u00b0C may result from very high emission scenarios, but can also occur from \nlower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher than the best estimate.\n\nDocument 102: The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8). Methods to project global warming associated with the \nmodelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII \nTable 3.1} (Table 3.1, Cross-Section Box.2 Figure 1)\n102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019.","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":100,"distracting_context":"109\nNear-Term Responses in a Changing Climate\nSection 4\nNear-term adaptation and mitigation actions have more synergies \nthan trade-offs with Sustainable Development Goals (SDGs)\nSynergies and trade-offs depend on context and scale\nEnergy systems\nSDGs\nUrban and infrastructure\nLand system\nOcean \necosystems\nSociety, \nlivelihoods, and \neconomies\nIndustry\nAdaptation\nMitigation\nAdaptation\nMitigation\nAdaptation\nMitigation\nAdaptation\nAdaptation\nMitigation\nLimited evidence\/no evidence\/no assessment\nBoth synergies and trade-offs\/mixed\nTrade-offs\nSynergies\nKey\nFigure 4.5: Potential synergies and trade-offs between the portfolio of climate change mitigation and adaptation options and the Sustainable Development \nGoals (SDGs). This \ufb01gure presents a high-level summary of potential synergies and trade-offs assessed in WGII Figure SPM.4b and WGIII Figure SPM.8, based on the qualitative and \nquantitative assessment of each individual mitigation or option. The SDGs serve as an analytical framework for the assessment of different sustainable development dimensions, which \nextend beyond the time frame of 2030 SDG targets. Synergies and trade-offs across all individual options within a sector\/system are aggregated into sector\/system potentials for the \nwhole mitigation or adaptation portfolio. The length of each bar represents the total number of mitigation or adaptation options under each system\/sector. The number of adaptation \nand mitigation options vary across system\/sector, and have been normalised to 100% so that bars are comparable across mitigation, adaptation, system\/sector, and SDGs. Positive \nlinks shown in WGII Figure SPM.4b and WGIII Figure SPM.8 are counted and aggregated to generate the percentage share of synergies, represented here by the blue proportion \nwithin the bars. Negative links shown in WGII Figure SPM.4b and WGIII Figure SPM.8 are counted and aggregated to generate the percentage share of trade-offs and is represented \nby orange proportion within the bars.","topic":"Climate Change Scenarios"}}
{"id":"7d5fc062-03ea-4821-9f8c-ced60e7e1f63","question":"Considering the regional variations in greenhouse gas emissions as detailed in the IPCC report, what is the projected range of equilibrium climate sensitivity, and how might this range differ across various regions?","reference_answer":"The likely range of equilibrium climate sensitivity is 2.5\u00b0C to 4.0\u00b0C, with a best estimate of 3.0\u00b0C.","reference_context":"Document 113: {WGI SPM B.1.1, WGI Table SPM.1, WGI Figure \nSPM.4} (Cross-Section Box.2 Figure 1)\nModelled pathways consistent with the continuation of policies \nimplemented by the end of 2020 lead to global warming of \n3.2 [2.2 to 3.5]\u00b0C (5\u201395% range) by 2100 (medium con\ufb01dence) \n(see also Section 2.3.1). Pathways of >4\u00b0C (\u226550%) by 2100 would \nimply a reversal of current technology and\/or mitigation policy trends \n(medium con\ufb01dence). However, such warming could occur in emissions \npathways consistent with policies implemented by the end of 2020 if \nclimate sensitivity or carbon cycle feedbacks are higher than the best \nestimate (high con\ufb01dence). {WGIII SPM C.1.3}\n112  Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21}\n113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]\u00b0C (SSP1-1.9); 1.8 [1.3 to 2.4]\u00b0C (SSP1-2.6); 2.7 [2.1 to 3.5]\u00b0C (SSP2-4.5); 3.6 [2.8 to 4.6]\u00b0C \n(SSP3-7.0); and 4.4 [3.3 to 5.7]\u00b0C (SSP5-8.5).\n\nDocument 114: {WGIII SPM C.1.3}\n112  Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21}\n113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]\u00b0C (SSP1-1.9); 1.8 [1.3 to 2.4]\u00b0C (SSP1-2.6); 2.7 [2.1 to 3.5]\u00b0C (SSP2-4.5); 3.6 [2.8 to 4.6]\u00b0C \n(SSP3-7.0); and 4.4 [3.3 to 5.7]\u00b0C (SSP5-8.5). {WGI Table SPM.1} (Cross-Section Box.2)\n114 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). In all scenarios considered by WGI except the very high emissions scenario, the midpoint of the \n\ufb01rst 20-year running average period during which the assessed global warming reaches 1.5\u00b0C lies in the \ufb01rst half of the 2030s. In the very high GHG emissions scenario, this \nmid-point is in the late 2020s. The median \ufb01ve-year interval at which a 1.5\u00b0C global warming level is reached (50% probability) in categories of modelled pathways considered \nin WGIII is 2030\u20132035.\n\nDocument 205: The best estimates [and very likely ranges] of global warming for the different scenarios in the \nnear term are: 1.5 [1.2 to 1.7]\u00b0C (SSP1-1.9); 1.5 [1.2 to 1.8]\u00b0C (SSP1-2.6); 1.5 [1.2 to 1.8]\u00b0C (SSP2-4.5); 1.5 [1.2 to 1.8]\u00b0C (SSP3-7.0); and 1.6[1.3 to 1.9]\u00b0C (SSP5-8.5). \n{WGI SPM B.1.3, WGI Table SPM.1} (Cross-Section Box.2)\n142 Values in parentheses indicate the likelihood of limiting warming to the level speci\ufb01ed (see Cross-Section Box.2).\n143 Median and very likely range [5th to 95th percentile]. {WGIII SPM footnote 30}\n144 These numbers for CO2 are 48 [36 to 69]% in 2030, 65 [50 to 96] % in 2035, 80 [61 to109] % in 2040 and 99 [79 to 119]% in 2050.\n145 These numbers for CO2 are 22 [1 to 44]% in 2030, 37 [21 to 59] % in 2035, 51 [36 to 70] % in 2040 and 73 [55 to 90]% in 2050.\n146 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply.\n\nDocument 112: Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating. The assessed best estimates and \nvery likely ranges of warming for 2081-2100 with respect to 1850\u20131900 \nvary from 1.4 [1.0 to 1.8]\u00b0C in the very low GHG emissions scenario \n(SSP1-1.9) to 2.7 [2.1 to 3.5]\u00b0C in the intermediate GHG emissions \nscenario (SSP2-4.5) and 4.4 [3.3 to 5.7]\u00b0C in the very high GHG emissions \nscenario (SSP5-8.5)113. {WGI SPM B.1.1, WGI Table SPM.1, WGI Figure \nSPM.4} (Cross-Section Box.2 Figure 1)\nModelled pathways consistent with the continuation of policies \nimplemented by the end of 2020 lead to global warming of \n3.2 [2.2 to 3.5]\u00b0C (5\u201395% range) by 2100 (medium con\ufb01dence) \n(see also Section 2.3.1). Pathways of >4\u00b0C (\u226550%) by 2100 would \nimply a reversal of current technology and\/or mitigation policy trends \n(medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":113,"distracting_context":"45\nCurrent Status and Trends\nSection 2\nKey\nPopulation (millions)\n0\n2000\n4000\n6000\n8000\n0\n5\n10\n15\n20\nMiddle East \nAfrica \nEastern Asia\nSouth-East Asia and Paci\ufb01c \nLatin America and Caribbean\nEurope\nSouthern Asia\nNorth America \nAustralia, Japan and New Zealand \nEastern Europe and West-Central Asia\nAfrica\nAustralia, Japan and New Zealand\nEastern Asia\nEastern Europe and West-Central Asia\nEurope\nInternational \nshipping and aviation\nLatin America and Caribbean\nMiddle East\nNorth America\nSouth-East Asia and Paci\ufb01c\nSouthern Asia\n0\n200\n400\n600\n50\n60\n30\n20\n10\n0\n4%\n16%\n4%\n2%\n8%\n12% 11% 10%\n7%\n2%\n23%\nCO2\nGHG\nGHG\n2019\n1990\n1850\nTimeframes represented in these graphs\nd) Regional indicators (2019) and regional production vs consumption accounting (2018)\nProduction-based emissions (tCO2FFI per person, based on 2018 data)\n1.2\n10\n8.4\n9.2\n6.5\n2.8\n8.7\n16\n2.6\n1.6\nConsumption-based emissions (tCO2FFI per person, based on 2018 data)\n0.84\n11\n6.7\n6.2\n7.8\n2.8\n7.6\n17\n2.5\n1.5\nPopulation (million persons, 2019)\n1292\n157\n1471\n291\n620\n646\n252\n366\n674\n1836\nGHG per capita (tCO2-eq per person)\n3.9\n13\n11\n13\n7.8\n9.2\n13\n19\n7.9\n2.6\nGDP per capita (USD1000PPP 2017 per person) 1\n5.0\n43\n17\n20\n43\n15\n20\n61\n12\n6.2\nNet GHG 2019 2 (production basis)\nCO2FFI, 2018,","topic":"Others"}}
{"id":"d5b1198c-2e03-4059-a12e-e1cb238da330","question":"Considering the varying development priorities and contexts among countries as outlined in the IPCC report, what are the specific risks to food and nutritional security that North America faces, and how might these differ from vulnerabilities in other regions?","reference_answer":"The risks to food and nutritional security in North America highlighted in the report include changes in agriculture, livestock, hunting, fisheries, and aquaculture productivity and access.","reference_context":"Document 143: and degraded water quality \n-Risk to food and nutritional security through changes in agriculture, livestock, hunting, \n\ufb01sheries, and aquaculture productivity and access\n-Risks to well-being, livelihoods and economic activities from cascading and \ncompounding climate hazards, including risks to coastal cities, settlements and \ninfrastructure from sea level rise\nDelayed\nimpacts of\nsea level\nrise in the\nMediterranean\nFood\nproduction\nfrom crops,\n\ufb01sheries and\nlivestock\nin Africa\nMortality and\nmorbidity\nfrom heat and\ninfectious\ndisease\nin Africa\nBiodiversity\nand\necosystems\nin Africa\nHealth and\nwellbeing\nin the\nMediterranean\nWater scarcity\nto people in\nsoutheastern\nEurope\nCoastal\n\ufb02ooding to\npeople\nand\ninfrastructures\nin Europe\nHeat stress,\nmortality\nand\nmorbidity\nto people\nin Europe\nWater quality\nand\navailability\nin the\nMediterranean\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\nCosts and \ndamages\nrelated to\nmaintenance and\nreconstruction of\ntransportation\ninfrastructure in\nNorth America\nLyme\ndisease in\nNorth\nAmerica\nunder\nincomplete\nadaptation\nscenario\nLoss and\ndegradation of\ncoral reefs in \nAustralia\nReduced\nviability of\ntourism-\nrelated\nactivities in\nNorth\nAmerica\nCascading\nimpacts on\ncities and\nsettlements\nin Australasia\nChanges in\n\ufb01sheries catch\nfor Pollock\nand\nPaci\ufb01c Cod\nin the Arctic\nCosts\nand losses\nfor key \ninfrastructure\nin the Arctic\nSea-ice\ndependent\necosystems\n in the\nAntarctic\nChanges \nin krill\n\ufb01sheries\nin the\nAntarctic\nSea-ice\necosystems\nfrom sea-ice\n change in\nthe Arctic\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\n\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\n\u2022\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022 \u2022\u2022\u2022\n\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\u2022\n\u2022\u2022\n\u2022\n\u2022\u2022 \u2022\u2022\u2022\ne) Examples of key risks in different regions\nAbsence of risk diagrams does not imply absence of risks within a region.\n\nDocument 141: risk to food security and economic disruption due to \ndestruction of settlements and infrastructure\n-Economic decline and livelihood failure of \ufb01sheries, agriculture, tourism and from \nbiodiversity loss from traditional agroecosystems \n-Reduced habitability of reef and non-reef islands leading to increased displacement\n-Risk to water security in almost every small island \nAfrica -Species extinction and reduction or irreversible loss of ecosystems and their services, \nincluding freshwater, land and ocean ecosystems\n-Risk to food security, risk of malnutrition (micronutrient de\ufb01ciency), and loss of \nlivelihood due to reduced food production from crops, livestock and \ufb01sheries\n-Risks to marine ecosystem health and to livelihoods in coastal communities\n-Increased human mortality and morbidity due to increased heat and infectious diseases \n(including vector-borne and diarrhoeal diseases)\n-Reduced economic output and growth, and increased inequality and poverty rates \n-Increased risk to water and energy security due to drought and heat\nAus-\ntralasia\n-Degradation of tropical shallow coral reefs and associated biodiversity and \necosystem service values\n-Loss of human and natural systems in low-lying coastal areas due to sea level rise\n-Impact on livelihoods and incomes due to decline in agricultural production\n-Increase in heat-related mortality and morbidity for people and wildlife\n-Loss of alpine biodiversity in Australia due to less snow\nAsia -Urban infrastructure damage and impacts on human well-being and health due to \n\ufb02ooding, especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics,\n\nDocument 142: especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics, in particular vector-borne diseases\n-Coral reef ecosystems degradation due to coral bleaching\n-Risk to food security due to frequent\/extreme droughts\n-Damages to life and infrastructure due to \ufb02oods, landslides, sea level rise, storm \nsurges and coastal erosion \nNorth \nAmerica\n-Climate-sensitive mental health outcomes, human mortality and morbidity due to \nincreasing average temperature, weather and climate extremes, and compound \nclimate hazards\n-Risk of degradation of marine, coastal and terrestrial ecosystems, including loss of \nbiodiversity, function, and protective services \n-Risk to freshwater resources with consequences for ecosystems, reduced surface water \navailability for irrigated agriculture, other human uses, and degraded water quality \n-Risk to food and nutritional security through changes in agriculture, livestock, hunting, \n\ufb01sheries, and aquaculture productivity and access\n-Risks to well-being, livelihoods and economic activities from cascading and \ncompounding climate hazards, including risks to coastal cities, settlements and \ninfrastructure from sea level rise\nDelayed\nimpacts of\nsea level\nrise in the\nMediterranean\nFood\nproduction\nfrom crops,\n\ufb01sheries and\nlivestock\nin Africa\nMortality and\nmorbidity\nfrom heat and\ninfectious\ndisease\nin Africa\nBiodiversity\nand\necosystems\nin Africa\nHealth and\nwellbeing\nin the\nMediterranean\nWater scarcity\nto people in\nsoutheastern\nEurope\nCoastal\n\ufb02ooding to\npeople\nand\ninfrastructures\nin Europe\nHeat stress,","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":143,"distracting_context":"102\nSection 4\nSection 1\nSection 4\nand burdens, especially for vulnerable countries and communities. \n{WGIII SPM D.3, WGIII SPM D.3.2, WGIII SPM D.3.3, WGIII SPM D.3.4, \nWGIII TS Box TS.4}\nDevelopment priorities among countries also re\ufb02ect different \nstarting points and contexts, and enabling conditions for \nshifting development pathways towards increased sustainability \nwill therefore differ, giving rise to different needs (high \ncon\ufb01dence). Implementing just transition principles through collective \nand participatory decision-making processes is an effective way of \nintegrating equity principles into policies at all scales depending \non national circumstances, while in several countries just transition \ncommissions, task forces and national policies have been established \n(medium con\ufb01dence). {WGIII SPM D.3.1, WGIII SPM D.3.3}\nMany economic and regulatory instruments have been \neffective in reducing emissions and practical experience has \ninformed instrument design to improve them while addressing \ndistributional goals and social acceptance (high con\ufb01dence). The \ndesign of behavioural interventions, including the way that choices are \npresented to consumers work synergistically with price signals, making \nthe combination more effective (medium con\ufb01dence). Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence).","topic":"Climate Change Impacts"}}
{"id":"c99e8c23-f80c-411c-bc3d-91521d14b021","question":"Considering the specific challenges faced by Indigenous Peoples and local communities, such as threats to food security and economic disruption due to environmental changes, how has their involvement, as noted in the IPCC report, impacted climate action and contributed to addressing these challenges?","reference_answer":"Engaging Indigenous Peoples and local communities using just-transition and rights-based decision-making approaches, implemented through collective and participatory decision-making processes has enabled deeper ambition and accelerated action in different ways, and at all scales, depending on national circumstances (medium confidence).","reference_context":"Document 58: Engaging \nIndigenous Peoples and local communities using just-transition and \nrights-based decision-making approaches, implemented through \ncollective and participatory decision-making processes has enabled \ndeeper ambition and accelerated action in different ways, and at all \nscales, depending on national circumstances (medium con\ufb01dence). \nThe media helps shape the public discourse about climate change. This \ncan usefully build public support to accelerate climate action (medium \nevidence, high agreement). In some instances, public discourses of \nmedia and organised counter movements have impeded climate \naction, exacerbating helplessness and disinformation and fuelling \npolarisation, with negative implications for climate action (medium \ncon\ufb01dence). {WGII SPM C.5.1, WGII SPM D.2, WGII TS.D.9, WGII TS.D.9.7, \nWGII TS.E.2.1, WGII 18.4; WGIII SPM D.3.3, WGIII SPM E.3.3, WGIII TS.6.1, \nWGIII 6.7, WGIII 13 ES, WGIII Box.13.7}\n2.2.2. Mitigation Actions to Date\nThere has been a consistent expansion of policies and laws \naddressing mitigation since AR5 (high con\ufb01dence). Climate \ngovernance supports mitigation by providing frameworks through \nwhich diverse actors interact, and a basis for policy development and \nimplementation (medium con\ufb01dence). Many regulatory and economic \ninstruments have already been deployed successfully (high con\ufb01dence). \nBy 2020, laws primarily focussed on reducing GHG emissions existed in \n56 countries covering 53% of global emissions (medium con\ufb01dence). \nThe application of diverse policy instruments for mitigation at the \nnational and sub-national levels has grown consistently across a \nrange of sectors (high con\ufb01dence). Policy coverage is uneven across \nsectors and remains limited for emissions from agriculture, and from \nindustrial materials and feedstocks (high con\ufb01dence).\n\nDocument 59: Mitigation Actions to Date\nThere has been a consistent expansion of policies and laws \naddressing mitigation since AR5 (high con\ufb01dence). Climate \ngovernance supports mitigation by providing frameworks through \nwhich diverse actors interact, and a basis for policy development and \nimplementation (medium con\ufb01dence). Many regulatory and economic \ninstruments have already been deployed successfully (high con\ufb01dence). \nBy 2020, laws primarily focussed on reducing GHG emissions existed in \n56 countries covering 53% of global emissions (medium con\ufb01dence). \nThe application of diverse policy instruments for mitigation at the \nnational and sub-national levels has grown consistently across a \nrange of sectors (high con\ufb01dence). Policy coverage is uneven across \nsectors and remains limited for emissions from agriculture, and from \nindustrial materials and feedstocks (high con\ufb01dence). {WGIII SPM B.5, \nWGIII SPM B.5.2, WGIII SPM E.3, WGIII SPM E.4}\nPractical experience has informed economic instrument design \nand helped to improve predictability, environmental effectiveness, \neconomic ef\ufb01ciency, alignment with distributional goals, and social \nacceptance (high con\ufb01dence). Low-emission technological innovation \nis strengthened through the combination of technology-push policies, \ntogether with policies that create incentives for behaviour change and \nmarket opportunities (high con\ufb01dence) (Section 4.8.3). Comprehensive \nand consistent policy packages have been found to be more effective \n2.2 Responses Undertaken to Date\n\nDocument 57: In addition, the 2030 Agenda for Sustainable \nDevelopment, adopted in 2015 by UN member states, sets out 17 \nSustainable Development Goals (SDGs) and seeks to align efforts \nglobally to prioritise ending extreme poverty, protect the planet and \npromote more peaceful, prosperous and inclusive societies. If achieved, \nthese agreements would reduce climate change, and the impacts on \nhealth, well-being, migration, and con\ufb02ict, among others (very high \ncon\ufb01dence). {WGII TS.A.1, WGII 7 ES} \nSince AR5, rising public awareness and an increasing diversity \nof actors, have overall helped accelerate political commitment \nand global efforts to address climate change (medium \n82 \nSee Annex I: Glossary.\ncon\ufb01dence). Mass social movements have emerged as catalysing \nagents in some regions, often building on prior movements including \nIndigenous Peoples-led movements, youth movements, human \nrights movements, gender activism, and climate litigation, which is \nraising awareness and, in some cases, has in\ufb02uenced the outcome \nand ambition of climate governance (medium con\ufb01dence). Engaging \nIndigenous Peoples and local communities using just-transition and \nrights-based decision-making approaches, implemented through \ncollective and participatory decision-making processes has enabled \ndeeper ambition and accelerated action in different ways, and at all \nscales, depending on national circumstances (medium con\ufb01dence). \nThe media helps shape the public discourse about climate change. This \ncan usefully build public support to accelerate climate action (medium \nevidence, high agreement). In some instances, public discourses of \nmedia and organised counter movements have impeded climate \naction, exacerbating helplessness and disinformation and fuelling \npolarisation, with negative implications for climate action (medium \ncon\ufb01dence).\n\nDocument 280: This requires adequate institutional capacity at \nall levels (high con\ufb01dence). Vulnerabilities and climate risks are often \nreduced through carefully designed and implemented laws, policies, \nparticipatory processes, and interventions that address context \nspeci\ufb01c inequities such as based on gender, ethnicity, disability, age, \nlocation and income (high con\ufb01dence). Policy support is in\ufb02uenced by \nIndigenous Peoples, businesses, and actors in civil society, including, \nyouth, labour, media, and local communities, and effectiveness is \nenhanced by partnerships between many different groups in society \n(high con\ufb01dence). Climate-related litigation is growing, with a large \nnumber of cases in some developed countries and with a much smaller \nnumber in some developing countries, and in some cases has in\ufb02uenced \nthe outcome and ambition of climate governance (medium con\ufb01dence). \n{WGII SPM C2.6, WGII SPM C.5.2, WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.3.1; WGIII SPM E3.2, WGIII SPM E.3.3}\nEffective climate governance is enabled by inclusive decision \nprocesses, allocation of appropriate resources, and institutional \nreview, monitoring and evaluation (high con\ufb01dence). Multi-level, \nhybrid and cross-sector governance facilitates appropriate consideration \nfor co-bene\ufb01ts and trade-offs, particularly in land sectors where decision \nprocesses range from farm level to national scale (high con\ufb01dence). \nConsideration of climate justice can help to facilitate shifting development \npathways towards sustainability. {WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, \nSRCCL TS.1}\nDrawing on diverse knowledge and partnerships, including \nwith women, youth, Indigenous Peoples, local communities, and \nethnic minorities can facilitate climate resilient development \nand has allowed locally appropriate and socially acceptable \nsolutions (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":58,"distracting_context":"risk to food security and economic disruption due to \ndestruction of settlements and infrastructure\n-Economic decline and livelihood failure of \ufb01sheries, agriculture, tourism and from \nbiodiversity loss from traditional agroecosystems \n-Reduced habitability of reef and non-reef islands leading to increased displacement\n-Risk to water security in almost every small island \nAfrica -Species extinction and reduction or irreversible loss of ecosystems and their services, \nincluding freshwater, land and ocean ecosystems\n-Risk to food security, risk of malnutrition (micronutrient de\ufb01ciency), and loss of \nlivelihood due to reduced food production from crops, livestock and \ufb01sheries\n-Risks to marine ecosystem health and to livelihoods in coastal communities\n-Increased human mortality and morbidity due to increased heat and infectious diseases \n(including vector-borne and diarrhoeal diseases)\n-Reduced economic output and growth, and increased inequality and poverty rates \n-Increased risk to water and energy security due to drought and heat\nAus-\ntralasia\n-Degradation of tropical shallow coral reefs and associated biodiversity and \necosystem service values\n-Loss of human and natural systems in low-lying coastal areas due to sea level rise\n-Impact on livelihoods and incomes due to decline in agricultural production\n-Increase in heat-related mortality and morbidity for people and wildlife\n-Loss of alpine biodiversity in Australia due to less snow\nAsia -Urban infrastructure damage and impacts on human well-being and health due to \n\ufb02ooding, especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics,","topic":"Climate Change Action"}}
{"id":"0dcb1aa9-fda3-4330-bdc1-3a36a9cbcec4","question":"Considering the emphasis on global CO2 and non-CO2 emissions reductions in the IPCC report, which regions are categorized under Australasia, and how might their contributions to these emissions be characterized?","reference_answer":"The regions included in Australasia are NAU (Northern Australia), CAU (Central Australia), EAU (Eastern Australia), SAU (Southern Australia), NZ (New Zealand), and Small Islands: CAR (Caribbean), PAC (Pacific Small Islands).","reference_context":"Document 40: SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nHot extremes\nHeavy precipitation\nAgricultural and ecological drought \nincluding heatwaves\nHazard\nDimension of Risk:\n\nDocument 39: WCA (West Central Asia), \nECA (East Central Asia), TIB (Tibetan \nPlateau), EAS (East Asia), ARP (Arabian \nPeninsula), SAS (South Asia), SEA (South East \nAsia), Australasia: NAU (Northern Australia), \nCAU (Central Australia), EAU (Eastern \nAustralia), SAU (Southern Australia), NZ \n(New Zealand), Small Islands: CAR \n(Caribbean), PAC (Paci\ufb01c Small Islands)\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":40,"distracting_context":"93\nNear-Term Responses in a Changing Climate\nSection 4\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) \nor lower by 2100 involve reductions in both net CO2 emissions \nand non-CO2 emissions (see Figure 3.6) (high confidence). \nFor example, in pathways that limit warming to 1.5\u00b0C (>50%) \nwith no or limited overshoot, global CH4 (methane) emissions are \nreduced by 34 [21 to 57]% below 2019 levels by 2030 and by \n44 [31 to 63]% in 2040 (high confidence). Global CH4 emissions \nare reduced by 24 [9 to 53]% below 2019 levels by 2030 and by \n37 [20 to 60]% in 2040 in modelled pathways that limit warming to \n2\u00b0C with action starting in 2020 (>67%) (high con\ufb01dence). {WGIII SPM \nC1.2, WGIII Table SPM.2, WGIII 3.3; SR1.5 SPM C.1, SR1.5 SPM C.1.2} \n(Cross-Section Box.2)\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) \nor lower by 2100 involve GHG emission reductions in all sectors \n(high con\ufb01dence). The contributions of different sectors vary across \nmodelled mitigation pathways. In most global modelled mitigation \npathways, emissions from land-use, land-use change and forestry, via \nreforestation and reduced deforestation, and from the energy supply \nsector reach net zero CO2 emissions earlier than the buildings, industry \nand transport sectors (Figure 4.1). Strategies can rely on combinations \nof different options (Figure 4.1, Section 4.5), but doing less in one \nsector needs to be compensated by further reductions in other sectors if \nwarming is to be limited.","topic":"Climate Change Risks"}}
{"id":"4a758a0c-5cb6-4bda-af98-3019c56c5a18","question":"Considering the various Shared Socioeconomic Pathways (SSPs) and their associated mitigation strategies, what is the updated likely range of equilibrium climate sensitivity as reported in the IPCC's Sixth Assessment Report (AR6)?","reference_answer":"The likely range of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C to 4.0\u00b0C, with a best estimate of 3.0\u00b0C.","reference_context":"Document 145: 77\nLong-Term Climate and Development Futures\nSection 3\nFigure 3.3: Synthetic risk diagrams of global and sectoral assessments and examples of regional key risks. The burning embers result from a literature based \nexpert elicitation. Panel (a): Left - Global surface temperature changes in \u00b0C relative to 1850\u20131900. These changes were obtained by combining CMIP6 model simulations with \nobservational constraints based on past simulated warming, as well as an updated assessment of equilibrium climate sensitivity. Very likely ranges are shown for the low and high \nGHG emissions scenarios (SSP1-2.6 and SSP3-7.0). Right - Global Reasons for Concern, comparing AR6 (thick embers) and AR5 (thin embers) assessments. Diagrams are shown for \neach RFC, assuming low to no adaptation (i.e., adaptation is fragmented, localised and comprises incremental adjustments to existing practices). However, the transition to a very \nhigh-risk level has an emphasis on irreversibility and adaptation limits. The horizontal line denotes the present global warming of 1.1\u00b0C which is used to separate the observed, past \nimpacts below the line from the future projected risks above it. Lines connect the midpoints of the transition from moderate to high risk across AR5 and AR6. Panel (b): Risks for \nland-based systems and ocean\/coastal ecosystems. Diagrams shown for each risk assume low to no adaptation. Text bubbles indicate examples of impacts at a given warming level. \nPanel (c): Left - Global mean sea level change in centimetres, relative to 1900. The historical changes (black) are observed by tide gauges before 1992 and altimeters afterwards. \nThe future changes to 2100 (coloured lines and shading) are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models, and \nlikely ranges are shown for SSP1-2.6 and SSP3-7.0.\n\nDocument 109: 66\nSection 2\nSection 1\nSection 2\nCross-Section Box.2 Figure 1:\u00a0Schematic of the AR6 framework for assessing future greenhouse gas emissions, climate change, \nrisks, impacts and mitigation. Panel (a) The integrated framework encompasses socio-economic development and policy, emissions pathways \nand global surface temperature responses to the \ufb01ve scenarios considered by WGI (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and \neight global mean temperature change categorisations (C1\u2013C8) assessed by WGIII, and the WGII risk assessment. The dashed arrow indicates \nthat the in\ufb02uence from impacts\/risks to socio-economic changes is not yet considered in the scenarios assessed in the AR6. Emissions include \nGHGs, aerosols, and ozone precursors. CO2 emissions are shown as an example on the left. The assessed global surface temperature changes \nacross the 21st century relative to 1850-1900 for the \ufb01ve GHG emissions scenarios are shown as an example in the centre. Very likely ranges \nare shown for SSP1-2.6 and SSP3-7.0. Projected temperature outcomes at 2100 relative to 1850-1900 are shown for C1 to C8 categories with \nmedian (line) and the combined very likely range across scenarios (bar). On the right, future risks due to increasing warming are represented by \nan example \u2018burning ember\u2019 \ufb01gure (see 3.1.2 for the de\ufb01nition of RFC1). Panel (b) Description and relationship of scenarios considered across \nAR6 Working Group reports. Panel (c) Illustration of risk arising from the interaction of hazard (driven by changes in climatic impact-drivers) \nwith vulnerability, exposure and response to climate change. {WGI TS1.4, Figure 4.11; WGII Figure 1.5, WGII Figure 14.8; WGIII Table SPM.2, \nWGIII Figure 3.11}\n\nDocument 111: 68\nSection 3\nSection 1\nSection 3\nSection 3: Long-Term Climate and Development Futures\n3.1 Long-Term Climate Change, Impacts and Related Risks\nFuture warming will be driven by future emissions and will affect all major climate system components, with \nevery region experiencing multiple and co-occurring changes. Many climate-related risks are assessed to be \nhigher than in previous assessments, and projected long-term impacts are up to multiple times higher than \ncurrently observed. Multiple climatic and non-climatic risks will interact, resulting in compounding and cascading \nrisks across sectors and regions. Sea level rise, as well as other irreversible changes, will continue for thousands \nof years, at rates depending on future emissions. (high con\ufb01dence)\n3.1.1. Long-term Climate Change\nThe uncertainty range on assessed future changes in global \nsurface temperature is narrower than in the AR5. For the \ufb01rst \ntime in an IPCC assessment cycle, multi-model projections of global \nsurface temperature, ocean warming and sea level are constrained \nusing observations and the assessed climate sensitivity. The likely \nrange of equilibrium climate sensitivity has been narrowed to 2.5\u00b0C \nto 4.0\u00b0C (with a best estimate of 3.0\u00b0C) based on multiple lines of \nevidence112, including improved understanding of cloud feedbacks. For \nrelated emissions scenarios, this leads to narrower uncertainty ranges \nfor long-term projected global temperature change than in AR5. \n{WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}\nFuture warming depends on future GHG emissions, with \ncumulative net CO2 dominating.\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":145,"distracting_context":"Depending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels104. \nThere are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1). \n{WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box TS.5, WGIII Annex III; SRCCL Box SPM.1, SRCCL Figure SPM.2}\nWGI assessed the climate response to \ufb01ve illustrative scenarios based on SSPs105 that cover the range of possible future development of anthropogenic \ndrivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and \nair pollution controls for aerosols and non-CH4 ozone precursors. The high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5) have \nCO2 emissions that roughly double from current levels by 2100 and 2050, respectively106. The intermediate GHG emissions scenario (SSP2-4.5) \nhas CO2 emissions remaining around current levels until the middle of the century. The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8).","topic":"Climate Change Assessment"}}
{"id":"9835e668-34ad-41a3-81b3-0c4f47c442db","question":"In the context of the projected scenarios and adaptation strategies outlined in the IPCC report, which sector is identified as having the highest percentage of adaptation responses to manage water-related risks and impacts?","reference_answer":"Agriculture accounts for the majority (~60%) of all documented adaptation responses to water-related risks and impacts.","reference_context":"Document 69: Various tools, measures and processes are available \nthat can enable, accelerate and sustain adaptation implementation \n(high con\ufb01dence). Growing public and political awareness of climate \nimpacts and risks has resulted in at least 170 countries and many cities \nincluding adaptation in their climate policies and planning processes \n(high con\ufb01dence). Decision support tools and climate services are \nincreasingly being used (very high con\ufb01dence) and pilot projects and \nlocal experiments are being implemented in different sectors (high \ncon\ufb01dence). {WGII SPM C.1, WGII SPM.C.1.1, WGII TS.D.1.3, WGII TS.D.10}\nAdaptation to water-related risks and impacts make up the majority (~60%) \nof all documented83 adaptation (high con\ufb01dence). A large number of \nthese adaptation responses are in the agriculture sector and these \ninclude on-farm water management, water storage, soil moisture \nconservation, and irrigation. Other adaptations in agriculture include \ncultivar improvements, agroforestry, community-based adaptation and \nfarm and landscape diversi\ufb01cation among others (high con\ufb01dence). \nFor inland \ufb02ooding, combinations of non-structural measures like \nearly warning systems, enhancing natural water retention such as by \nrestoring wetlands and rivers, and land use planning such as no build \nzones or upstream forest management, can reduce \ufb02ood risk (medium \ncon\ufb01dence). Some land-related adaptation actions such as sustainable \nfood production, improved and sustainable forest management, \nsoil organic carbon management, ecosystem conservation and land \nrestoration, reduced deforestation and degradation, and reduced \nfood loss and waste are being undertaken, and can have mitigation \nco-bene\ufb01ts (high con\ufb01dence). Adaptation actions that increase the \nresilience of biodiversity and ecosystem services to climate change \ninclude responses like minimising additional stresses or disturbances, \nreducing fragmentation, increasing natural habitat extent, connectivity \nand heterogeneity, and protecting small-scale refugia where \nmicroclimate conditions can allow species to persist (high con\ufb01dence).\n\nDocument 74: 56\nSection 2\nSection 1\nSection 2\nwetlands, rangelands, mangroves and forests); while afforestation and \nreforestation, restoration of high-carbon ecosystems, agroforestry, and \nthe reclamation of degraded soils take more time to deliver measurable \nresults. Signi\ufb01cant synergies exist between adaptation and mitigation, \nfor example through sustainable land management approaches. \nAgroecological principles and practices and other approaches \nthat work with natural processes support food security, nutrition, \nhealth and well-being, livelihoods and biodiversity, sustainability and \necosystem services. (high con\ufb01dence) {WGII SPM C.2.1, WGII SPM C.2.2, \nWGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; \nSROCC SPM C.2}\nCombinations of non-structural measures like early warning systems \nand structural measures like levees have reduced loss of lives in case \nof inland \ufb02ooding (medium con\ufb01dence) and early warning systems \nalong with \ufb02ood-proo\ufb01ng of buildings have proven to be cost-effective \nin the context of coastal \ufb02ooding under current sea level rise (high \ncon\ufb01dence). Heat Health Action Plans that include early warning and \nresponse systems are effective adaptation options for extreme heat \n(high con\ufb01dence). Effective adaptation options for water, food and \nvector-borne diseases include improving access to potable water, \nreducing exposure of water and sanitation systems to extreme weather \nevents, and improved early warning systems, surveillance, and vaccine \ndevelopment (very high con\ufb01dence). Adaptation options such as \ndisaster risk management, early warning systems, climate services \nand social safety nets have broad applicability across multiple sectors \n(high con\ufb01dence).\n\nDocument 70: Some land-related adaptation actions such as sustainable \nfood production, improved and sustainable forest management, \nsoil organic carbon management, ecosystem conservation and land \nrestoration, reduced deforestation and degradation, and reduced \nfood loss and waste are being undertaken, and can have mitigation \nco-bene\ufb01ts (high con\ufb01dence). Adaptation actions that increase the \nresilience of biodiversity and ecosystem services to climate change \ninclude responses like minimising additional stresses or disturbances, \nreducing fragmentation, increasing natural habitat extent, connectivity \nand heterogeneity, and protecting small-scale refugia where \nmicroclimate conditions can allow species to persist (high con\ufb01dence). \nMost innovations in urban adaptation have occurred through advances \n83 \nDocumented adaptation refers to published literature on adaptation policies, measures and actions that has been implemented and documented in peer reviewed literature, as \nopposed to adaptation that may have been planned, but not implemented. \n84 \nEffectiveness refers here to the extent to which an adaptation option is anticipated or observed to reduce climate-related risk.\n85 \n See Annex I: Glossary. \n86 \nIrrigation is effective in reducing drought risk and climate impacts in many regions and has several livelihood bene\ufb01ts, but needs appropriate management to avoid potential \nadverse outcomes, which can include accelerated depletion of groundwater and other water sources and increased soil salinization (medium con\ufb01dence). \n87 \nEbA is recognised internationally under the Convention on Biological Diversity (CBD14\/5). A related concept is Nature-based Solutions (NbS), see Annex I: Glossary.\nin disaster risk management, social safety nets and green\/blue \ninfrastructure (medium con\ufb01dence). Many adaptation measures that \nbene\ufb01t health and well-being are found in other sectors (e.g., food, \nlivelihoods, social protection, water and sanitation, infrastructure) \n(high con\ufb01dence).\n\nDocument 270: Climate services that are demand-driven and \ninclusive of different users and providers can improve agricultural \npractices, inform better water use and ef\ufb01ciency, and enable resilient \ninfrastructure planning (high con\ufb01dence). Policy mixes that include \nweather and health insurance, social protection and adaptive safety \nnets, contingent \ufb01nance and reserve funds, and universal access to \nearly warning systems combined with effective contingency plans, can \nreduce vulnerability and exposure of human systems (high con\ufb01dence). \nIntegrating climate adaptation into social protection programs, \nincluding cash transfers and public works programs, is highly feasible \nand increases resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). Social safety nets \ncan build adaptive capacities, reduce socioeconomic vulnerability, and \nreduce risk linked to hazards (robust evidence, medium agreement). \n{WGII SPM C.2.9, WGII SPM C.2.13, WGII Cross-Chapter Box FEASIB in \nChapter 18; SRCCL SPM C.1.4, SRCCL SPM D.1.2}\nReducing future risks of involuntary migration and displacement \ndue to climate change is possible through cooperative, international \nefforts to enhance institutional adaptive capacity and sustainable \ndevelopment (high con\ufb01dence). Increasing adaptive capacity minimises \nrisk associated with involuntary migration and immobility and improves \nthe degree of choice under which migration decisions are made, while \npolicy interventions can remove barriers and expand the alternatives for \nsafe, orderly and regular migration that allows vulnerable people to adapt \nto climate change (high con\ufb01dence). {WGII SPM C.2.12, WGII TS.D.8.6, \nWGII Cross-Chapter Box MIGRATE in Chapter 7}\nAccelerating commitment and follow-through by the private \nsector is promoted for instance by building business cases for \nadaptation, accountability and transparency mechanisms, and \nmonitoring and evaluation of adaptation progress (medium \ncon\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":69,"distracting_context":"with the 5th-95th percentile \ninterval in square brackets. \nPercentage of net zero \npathways is denoted in \nround brackets. \nThree dots (\u2026) denotes net \nzero not reached for that \npercentile.\nMedian cumulative net CO2 \nemissions across the \nprojected scenarios in this \ncategory until reaching \nnet-zero or until 2100, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected temperature \nchange of pathways in this \ncategory (50% probability \nacross the range of climate \nuncertainties), relative to \n1850-1900, at peak \nwarming and in 2100, for \nthe median value across the \nscenarios and the 5th-95th \npercentile interval in square \nbrackets.\nMedian likelihood that the \nprojected pathways in this \ncategory stay below a given \nglobal warming level, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected median GHG \nemissions reductions of \npathways in the year across \nthe scenarios compared to \nmodelled 2019, with the \n5th-95th percentile in \nbrackets. Negative numbers \nindicate increase in \nemissions compared to 2019\nModelled global emissions \npathways categorised by \nprojected global warming \nlevels (GWL). Detailed \nlikelihood definitions are \nprovided in SPM Box1.  \nThe five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.","topic":"Climate Change Action"}}
{"id":"ec0fa280-55c5-4074-9eb5-13a487c4e766","question":"Considering the financial and technological resource requirements for adaptation highlighted in the IPCC report, what are the projected consequences of failing to meet these investment needs for urgent, effective, and equitable adaptation and mitigation actions against climate change?","reference_answer":"Without urgent, effective and equitable adaptation and mitigation actions, climate change increasingly threatens the health and livelihoods of people around the globe, ecosystem health, and biodiversity, with severe adverse consequences for current and future generations.","reference_context":"Document 204: Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}. (Cross-Section \nBox.2, Figure 2.1, Figure 2.3)\n141 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). The best estimates [and very likely ranges] of global warming for the different scenarios in the \nnear term are: 1.5 [1.2 to 1.7]\u00b0C (SSP1-1.9); 1.5 [1.2 to 1.8]\u00b0C (SSP1-2.6); 1.5 [1.2 to 1.8]\u00b0C (SSP2-4.5); 1.5 [1.2 to 1.8]\u00b0C (SSP3-7.0); and 1.6[1.3 to 1.9]\u00b0C (SSP5-8.5).\n\nDocument 114: {WGIII SPM C.1.3}\n112  Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21}\n113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]\u00b0C (SSP1-1.9); 1.8 [1.3 to 2.4]\u00b0C (SSP1-2.6); 2.7 [2.1 to 3.5]\u00b0C (SSP2-4.5); 3.6 [2.8 to 4.6]\u00b0C \n(SSP3-7.0); and 4.4 [3.3 to 5.7]\u00b0C (SSP5-8.5). {WGI Table SPM.1} (Cross-Section Box.2)\n114 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). In all scenarios considered by WGI except the very high emissions scenario, the midpoint of the \n\ufb01rst 20-year running average period during which the assessed global warming reaches 1.5\u00b0C lies in the \ufb01rst half of the 2030s. In the very high GHG emissions scenario, this \nmid-point is in the late 2020s. The median \ufb01ve-year interval at which a 1.5\u00b0C global warming level is reached (50% probability) in categories of modelled pathways considered \nin WGIII is 2030\u20132035.\n\nDocument 203: 92\nSection 4\nSection 1\nSection 4\nSection 4 : Near-Term Responses in a Changing Climate\n4.1 The Timing and Urgency of Climate Action\nThe magnitude and rate of climate change and associated risks \ndepend strongly on near-term mitigation and adaptation actions \n(very high con\ufb01dence). Global warming is more likely than not to reach \n1.5\u00b0C between 2021 and 2040 even under the very low GHG emission \nscenarios (SSP1-1.9), and likely or very likely to exceed 1.5\u00b0C under \nhigher emissions scenarios141. Many adaptation options have medium \nor high feasibility up to 1.5\u00b0C (medium to high con\ufb01dence, depending \non option), but hard limits to adaptation have already been reached \nin some ecosystems and the effectiveness of adaptation to reduce \nclimate risk will decrease with increasing warming (high con\ufb01dence). \nSocietal choices and actions implemented in this decade determine the \nextent to which medium- and long-term pathways will deliver higher or \nlower climate resilient development (high con\ufb01dence). Climate resilient \ndevelopment prospects are increasingly limited if current greenhouse \ngas emissions do not rapidly decline, especially if 1.5\u00b0C global warming \nis exceeded in the near term (high con\ufb01dence). Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}.\n\nDocument 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":204,"distracting_context":"Financial and \ntechnological resources enable effective and ongoing implementation \nof adaptation, especially when supported by institutions with a strong \nunderstanding of adaptation needs and capacity (high con\ufb01dence). \nAverage annual modelled mitigation investment requirements for \n2020 to 2030 in scenarios that limit warming to 2\u00b0C or 1.5\u00b0C are a \nfactor of three to six greater than current levels, and total mitigation \ninvestments (public, private, domestic and international) would need \nto increase across all sectors and regions (medium con\ufb01dence). Even \nif extensive global mitigation efforts are implemented, there will be a \nlarge need for \ufb01nancial, technical, and human resources for adaptation \n(high con\ufb01dence). {WGII SPM C.1.2, WGII SPM C2.11, WGII SPM C.3, \nWGII SPM C.3.2, WGII SPM C3.5, WGII SPM C.5, WGII SPM C.5.4, \nWGII SPM D.1, WGII SPM D.1.1, WGII SPM D.1.2, WGII SPM C.5.4; \nWGIII SPM D.2.4, WGIII SPM E.5, WGIII SPM E.5.1, WGIII 15.2} \n(Section 2.3.2, 2.3.3, 4.4, Figure 4.6)\napproaches (high con\ufb01dence). There is no consistent evidence that \ncurrent emission trading systems have led to signi\ufb01cant emissions \nleakage (medium con\ufb01dence). {WGIII SPM E4.2, WGIII SPM E.4.6} \nRemoving fossil fuel subsidies would reduce emissions, improve \npublic revenue and macroeconomic performance, and yield \nother environmental and sustainable development bene\ufb01ts such \nas improved public revenue, macroeconomic and sustainability \nperformance; subsidy removal can have adverse distributional \nimpacts especially on the most economically vulnerable \ngroups which, in some cases, can be mitigated by measures \nsuch as re-distributing revenue saved, and depend on national \ncircumstances (high con\ufb01dence).","topic":"Climate Change Scenarios"}}
{"id":"bd9d6d19-000c-48c0-b3f5-82b512900fa5","question":"Considering the regional disparities highlighted in the IPCC report, how are the projected impacts on fisheries expected to vary by region in response to ocean physical and biogeochemical changes?","reference_answer":"Projected regional impacts reflect fisheries and marine ecosystem responses to ocean physical and biogeochemical conditions such as temperature, oxygen level and net primary production. Models do not represent changes in fishing activities and some extreme climatic conditions.","reference_context":"Document 133: Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\nFuture climate change is projected to increase the severity of impacts \nacross natural and human systems and will increase regional differences\nAreas with little or no \nproduction, or not assessed\n1Projected temperature conditions above \nthe estimated historical (1850-2005) \nmaximum mean annual temperature \nexperienced by each species, assuming \nno species relocation. \n2Includes 30,652 species of birds, \nmammals, reptiles, amphibians, marine \n\ufb01sh, benthic marine invertebrates, krill, \ncephalopods, corals, and seagrasses.\na) Risk of \nspecies losses\nb) Heat-humidity \nrisks to \nhuman health\nc) Food production \nimpacts\n3Projected regional impacts utilize a global threshold beyond which daily mean surface air temperature and relative humidity may induce \nhyperthermia that poses a risk of mortality. The duration and intensity of heatwaves are not presented here. Heat-related health outcomes \nvary by location and are highly moderated by socio-economic, occupational and other non-climatic determinants of individual health and \nsocio-economic vulnerability. The threshold used in these maps is based on a single study that synthesized data from 783 cases to \ndetermine the relationship between heat-humidity conditions and mortality drawn largely from observations in temperate climates.\nHistorical 1991\u20132005\n\nDocument 132: 73\nLong-Term Climate and Development Futures\nSection 3\nc1) Maize yield4\nc2) Fisheries yield5\nChanges (%) in \nmaximum catch \npotential\nChanges (%) in yield\n \n \n-20\n-10\n-3\n-30\n-25\n-15\n-35%\n+20\n+30\n+35%\n+10\n+3\n+25\n+15\n1\n0 days\n300\n100\n200\n10\n150\n250\n50\n365 days\n0.1\n0%\n80\n10\n40\n1\n20\n60\n5\n100%\nAreas with model disagreement\nExamples of impacts without additional adaptation\n2.4 \u2013 3.1\u00b0C\n4.2 \u2013 5.4\u00b0C\n1.5\u00b0C\n3.0\u00b0C\n1.7 \u2013 2.3\u00b0C\n0.9 \u2013 2.0\u00b0C\n3.4 \u2013 5.2\u00b0C\n1.6 \u2013 2.4\u00b0C\n3.3 \u2013 4.8\u00b0C\n3.9 \u2013 6.0\u00b0C\n2.0\u00b0C\n4.0\u00b0C\nPercentage of animal \nspecies and seagrasses \nexposed to potentially \ndangerous temperature \nconditions1, 2\nDays per year where \ncombined temperature and \nhumidity conditions pose a risk \nof mortality to individuals3\n5Projected regional impacts re\ufb02ect \ufb01sheries and marine ecosystem responses to ocean physical and biogeochemical conditions such as \ntemperature, oxygen level and net primary production. Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\n\nDocument 134: 74\nSection 3\nSection 1\nSection 3\nFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. \nProjected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without \nadditional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species \nlosses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as de\ufb01ned by conditions beyond the estimated historical \n(1850\u20132005) maximum mean annual temperature experienced by each species, at GWLs of 1.5\u00b0C, 2\u00b0C, 3\u00b0C and 4\u00b0C. Underpinning projections of temperature are from 21 Earth \nsystem models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure \nto hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991\u20132005) and at GWLs of 1.7\u00b0C to 2.3\u00b0C \n(mean = 1.9\u00b0C; 13 climate models), 2.4\u00b0C to 3.1\u00b0C (2.7\u00b0C; 16 climate models) and 4.2\u00b0C to 5.4\u00b0C (4.7\u00b0C; 15 climate models). Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C).\n\nDocument 120: Increases in hot and decreases in \ncold climatic impact-drivers, such as temperature extremes, are \nprojected in all regions (high con\ufb01dence). At 1.5\u00b0C global warming, \nheavy precipitation and \ufb02ooding events are projected to intensify \nand become more frequent in most regions in Africa, Asia (high \ncon\ufb01dence), North America (medium to high con\ufb01dence) and Europe \n(medium con\ufb01dence). At 2\u00b0C or above, these changes expand to more \nregions and\/or become more signi\ufb01cant (high con\ufb01dence), and more \nfrequent and\/or severe agricultural and ecological droughts are projected \nin Europe, Africa, Australasia and North, Central and South America \n(medium to high con\ufb01dence). Other projected regional changes include \n117 Particularly over South and South East Asia, East Asia and West Africa apart from the far west Sahel. {WGI SPM B.3.3}\n118 See Annex I: Glossary.\n119 See Annex I: Glossary.\nintensification of tropical cyclones and\/or extratropical storms \n(medium con\ufb01dence), and increases in aridity and \ufb01re weather119 \n(medium to high con\ufb01dence). Compound heatwaves and droughts \nbecome likely more frequent, including concurrently at multiple \nlocations (high con\ufb01dence). {WGI SPM C.2, WGI SPM C.2.1, WGI SPM C.2.2, \nWGI SPM C.2.3, WGI SPM C.2.4, WGI SPM C.2.7}","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":133,"distracting_context":"51\nCurrent Status and Trends\nSection 2\n(high con\ufb01dence) (Figure 2.3). Climate change impacts on health are \nmediated through natural and human systems, including economic \nand social conditions and disruptions (high con\ufb01dence). Climate and \nweather extremes are increasingly driving displacement in Africa, \nAsia, North America (high con\ufb01dence), and Central and South America \n(medium con\ufb01dence) (Figure 2.3), with small island states in the \nCaribbean and South Paci\ufb01c being disproportionately affected relative \nto their small population size (high con\ufb01dence). Through displacement \nand involuntary migration from extreme weather and climate \nevents, climate change has generated and perpetuated vulnerability \n(medium con\ufb01dence). {WGII SPM B.1.4, WGII SPM B.1.7}\nHuman in\ufb02uence has likely increased the chance of compound \nextreme events80 since the 1950s. Concurrent and repeated climate \nhazards have occurred in all regions, increasing impacts and \nrisks to health, ecosystems, infrastructure, livelihoods and food \n(high con\ufb01dence). Compound extreme events include increases in the \nfrequency of concurrent heatwaves and droughts (high con\ufb01dence); \ufb01re \nweather in some regions (medium con\ufb01dence); and compound \ufb02ooding in \nsome locations (medium con\ufb01dence). Multiple risks interact, generating \nnew sources of vulnerability to climate hazards, and compounding \noverall risk (high con\ufb01dence). Compound climate hazards can overwhelm \nadaptive capacity and substantially increase damage (high con\ufb01dence)). \n{WGI SPM A.3.5; WGII SPM. B.5.1, WGII TS.C.11.3}\nEconomic \nimpacts \nattributable \nto \nclimate \nchange \nare \nincreasingly \naffecting peoples\u2019 livelihoods and are causing economic and \nsocietal impacts across national boundaries (high con\ufb01dence).","topic":"Climate Change Risks"}}
{"id":"1b98d3f1-5433-4f73-8c6e-17e6f121d652","question":"Given the synergies between sustainable development and energy efficiency, what is the confidence level in the assertion that demand-side measures could substantially lower global greenhouse gas emissions in end-use sectors by the year 2050 relative to baseline scenarios, while also considering the potential socio-economic and environmental impacts of such measures?","reference_answer":"high confidence","reference_context":"Document 254: {WGIII SPM footnote 54}\n154 The mitigation potentials and mitigation costs of individual technologies in a speci\ufb01c context or region may differ greatly from the provided estimates (medium con\ufb01dence). \n{WGIII SPM C.12.1}\ncon\ufb01dence). The most feasible energy system adaptation options \nsupport infrastructure resilience, reliable power systems and ef\ufb01cient \nwater use for existing and new energy generation systems (very \nhigh con\ufb01dence). Adaptations for hydropower and thermo-electric \npower generation are effective in most regions up to 1.5\u00b0C to 2\u00b0C, \nwith decreasing effectiveness at higher levels of warming (medium \ncon\ufb01dence). Energy generation diversi\ufb01cation (e.g., wind, solar, small-\nscale hydroelectric) and demand side management (e.g., storage and \nenergy ef\ufb01ciency improvements) can increase energy reliability and \nreduce vulnerabilities to climate change, especially in rural populations \n(high con\ufb01dence). Climate responsive energy markets, updated design \nstandards on energy assets according to current and projected climate \nchange, smart-grid technologies, robust transmission systems and \nimproved capacity to respond to supply de\ufb01cits have high feasibility \nin the medium- to long-term, with mitigation co-bene\ufb01ts (very high \ncon\ufb01dence). {WGII SPM B.5.3, WGII SPM C.2.10; WGIII TS.5.1}\n4.5.2. Industry\nThere are several options to reduce industrial emissions \nthat differ by type of industry; many industries are disrupted \nby climate change, especially from extreme events (high \ncon\ufb01dence). Reducing industry emissions will entail coordinated \naction throughout value chains to promote all mitigation options, \nincluding demand management, energy and materials ef\ufb01ciency, \ncircular material \ufb02ows, as well as abatement technologies and\n\nDocument 246: The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change. (high con\ufb01dence) (Figure 4.4). {WGIII SPM C.10}\n4.5 Near-Term Mitigation and Adaptation Actions\nRapid and far-reaching transitions across all sectors and systems are necessary to achieve deep and sustained \nemissions reductions and secure a liveable and sustainable future for all. These system transitions involve a \nsigni\ufb01cant upscaling of a wide portfolio of mitigation and adaptation options. Feasible, effective and low-cost \noptions for mitigation and adaptation are already available, with differences across systems and regions. (high \ncon\ufb01dence)\n\nDocument 302: Such measures can also achieve \ngreater bene\ufb01ts through cascading effects across sectors \n(medium con\ufb01dence). For example, the feasibility of using land for \nboth agriculture and centralised solar production can increase when \nsuch options are combined (high con\ufb01dence). Similarly, integrated \ntransport and energy infrastructure planning and operations can \ntogether reduce the environmental, social, and economic impacts of \ndecarbonising the transport and energy sectors (high con\ufb01dence). The \nimplementation of packages of multiple city-scale mitigation strategies \ncan have cascading effects across sectors and reduce GHG emissions \nboth within and outside a city\u2019s administrative boundaries (very high \ncon\ufb01dence). Integrated design approaches to the construction and \nretro\ufb01t of buildings provide increasing examples of zero energy or \nzero carbon buildings in several regions. To minimise maladaptation, \nmulti-sectoral, multi-actor and inclusive planning with \ufb02exible \npathways encourages low-regret and timely actions that keep options \nopen, ensure bene\ufb01ts in multiple sectors and systems and suggest the \navailable solution space for adapting to long-term climate change \n(very high con\ufb01dence). Trade-offs in terms of employment, water \nuse, land-use competition and biodiversity, as well as access to, \nand the affordability of, energy, food, and water can be avoided \nby well-implemented land-based mitigation options, especially those \nthat do not threaten existing sustainable land uses and land rights, with \nframeworks for integrated policy implementation (high con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, \nWGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.1.5, \nWGIII SPM E.1.2}\nMitigation and adaptation when implemented together, and \ncombined with broader sustainable development objectives, \nwould yield multiple bene\ufb01ts for human well-being as well as \necosystem and planetary health (high con\ufb01dence).\n\nDocument 215: The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).  Comprehensive, effective, and innovative \nresponses integrating adaptation and mitigation can harness synergies \nand reduce trade-offs between adaptation and mitigation, as well as in \nmeeting requirements for \ufb01nancing (very high con\ufb01dence) (see Section \n4.5, 4.6, 4.8 and 4.9). {WGII SPM B.3, WGII SPM B.4, WGII SPM B.6.2, \nWGII SPM C.2, WGII SPM C.3, WGII SPM D.1, WGII SPM D.4.3, WGII SPM D.5, \nWG II TS D.1.4, WG II TS.D.5, WGII TS D.7.5; WGIII SPM B.6.3,WGIII SPM B.6.4, \nWGIII SPM C.9, WGIII SPM D.2, WGIII SPM E.13; SR1.5 SPM C.2.7, \nSR1.5 D.1.3, SR1.5 D.5.2}\nMitigation actions will have other sustainable development \nco-bene\ufb01ts (high con\ufb01dence). Mitigation will improve air quality and \nhuman health in the near term notably because many air pollutants are \n148 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply.","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":254,"distracting_context":"There are potential synergies between sustainable development and, \nfor instance, energy ef\ufb01ciency and renewable energy. (high con\ufb01dence) \n{WGIII SPM C.4.2, WGIII SPM D.1.3}\nFor agriculture, land, and food systems, many land management \noptions and demand-side response options (e.g., dietary choices, \nreduced post-harvest losses, reduced food waste) can contribute to \neradicating poverty and eliminating hunger while promoting good health \nand well-being, clean water and sanitation, and life on land (medium \nconfidence). In contrast, certain adaptation options that promote \nintensification of production, such as irrigation, may have negative \neffects on sustainability (e.g., for biodiversity, ecosystem services, \ngroundwater depletion, and water quality) (high confidence). {WGII \nTS.D.5.5; WGIII SPM D.10; SRCCL SPM B.2.3}\nReforestation, improved forest management, soil carbon sequestration, \npeatland restoration and coastal blue carbon management are \nexamples of CDR methods that can enhance biodiversity and ecosystem \nfunctions, employment and local livelihoods, depending on context139. \nHowever, afforestation or production of biomass crops for bioenergy \nwith carbon dioxide capture and storage or biochar can have adverse \nsocio-economic and environmental impacts, including on biodiversity, \nfood and water security, local livelihoods and the rights of Indigenous \nPeoples, especially if implemented at large scales and where land \ntenure is insecure. (high con\ufb01dence) {WGII SPM B.5.4, WGII SPM C.2.4; \nWGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5; SRCCL SPM B.3, \nSRCCL SPM B.7.3, SRCCL Figure SPM.3}\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence).","topic":"Climate Change Action"}}
{"id":"3bc80e8e-a5ff-460e-a164-8b335a25f09e","question":"Considering the increased rates of sea level rise reported by the IPCC, what are the projected benefits of accelerated adaptation responses for coastal communities vulnerable to these changes?","reference_answer":"Accelerated implementation of adaptation responses will improve well-being by reducing losses and damages, especially for vulnerable populations, enhance sustainable development co-benefits, and bring benefits to human well-being.","reference_context":"Document 213: Positive (solid \ufb01lled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to \nGHG emissions from the year 2019. The category \u201cenergy supply (including electricity)\u201d includes bioenergy with carbon capture and storage and direct air carbon capture and storage. \n{WGIII Box TS.5, WGIII 3.3, WGIII 3.4, WGIII 6.6, WGIII 10.3, WGIII 11.3} (Cross-Section Box.2)\nAccelerated implementation of adaptation will improve well-being by reducing losses and damages, especially \nfor vulnerable populations. Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4).\n\nDocument 212: 95\nNear-Term Responses in a Changing Climate\nSection 4\n4.2 Bene\ufb01ts of Strengthening Near-Term Action\nFigure 4.1: Sectoral emissions in pathways that limit warming to 1.5\u00b0C. Panel (a) shows sectoral CO2 and non-CO2 emissions in global modelled pathways that limit \nwarming to 1.5\u00b0C (>50%) with no or limited overshoot. The horizontal lines illustrate halving 2015 emissions (base year of the pathways) (dashed) and reaching net zero emissions \n(solid line). The range shows the 5\u201395th percentile of the emissions across the pathways. The timing strongly differs by sector, with the CO2 emissions from the electricity\/fossil fuel \nindustries sector and\u00a0land-use change generally reaching net zero earlier.\u00a0Non-CO2 emissions from agriculture are also substantially reduced compared to pathways without climate \npolicy but do not typically reach zero. Panel (b) Although all pathways include strongly reduced emissions, there are different pathways as indicated by the illustrative mitigation \npathways used in IPCC WGIII. The pathways emphasise routes consistent with limiting warming to 1.5\u00b0C with a high reliance on net negative emissions (IMP-Neg), high resource \nef\ufb01ciency (IMP-LD), a focus on sustainable development (IMP-SP) or renewables (IMP-Ren) and consistent with 2\u00b0C based on a less rapid introduction of mitigation measures followed \nby a subsequent gradual strengthening (IMP-GS). Positive (solid \ufb01lled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to \nGHG emissions from the year 2019. The category \u201cenergy supply (including electricity)\u201d includes bioenergy with carbon capture and storage and direct air carbon capture and storage. \n{WGIII Box TS.5, WGIII 3.3, WGIII 3.4, WGIII 6.6, WGIII 10.3, WGIII 11.3} (Cross-Section Box.2)\nAccelerated implementation of adaptation will improve well-being by reducing losses and damages, especially \nfor vulnerable populations.\n\nDocument 214: Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4). (high con\ufb01dence) {WGI SPM B.1, WGI SPM B.1.3, WGI \nSPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM \nC.2, WGII SPM C.3.1, WGII Figure SPM.4b; SROCC SPM C.3.4, SROCC \nFigure 3.4, SROCC Figure SPM.5}\nNear-term actions that limit global warming to close to 1.5\u00b0C \nwould substantially reduce projected losses and damages related \nto climate change in human systems and ecosystems, compared \nto higher warming levels, but cannot eliminate them all (very \nhigh con\ufb01dence). The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).\n\nDocument 208: {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems. In modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited \novershoot and in those that limit warming to 2\u00b0C (>67%) and assume immediate action, global GHG emissions \nare projected to peak in the early 2020s followed by rapid and deep reductions. As adaptation options often have \nlong implementation times, accelerated implementation of adaptation, particularly in this decade, is important \nto close adaptation gaps. (high con\ufb01dence)","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":213,"distracting_context":"Global mean sea level increased by 0.20 \n[0.15 to 0.25] m between 1901 and 2018. The average rate of sea level \nrise was 1.3 [0.6 to 2.1]mm yr-1 between 1901 and 1971, increasing to \n1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and further increasing \nto 3.7 [3.2 to \u20134.2] mm yr-1 between 2006 and 2018 (high con\ufb01dence). \nHuman in\ufb02uence was very likely the main driver of these increases \nsince at least 1971 (Figure 3.4). Human in\ufb02uence is very likely the main \ndriver of the global retreat of glaciers since the 1990s and the decrease \nin Arctic sea ice area between 1979\u20131988 and 2010\u20132019. Human \nin\ufb02uence has also very likely contributed to decreased Northern Hemisphere \nspring snow cover and surface melting of the Greenland ice sheet. It is \nvirtually certain that human-caused CO2 emissions are the main driver \nof current global acidi\ufb01cation of the surface open ocean. {WGI SPM A.1, \nWGI SPM A.1.3, WGI SPM A.1.5, WGI SPM A.1.6, WG1 SPM A1.7, \nWGI SPM A.2, WG1.SPM A.4.2; SROCC SPM.A.1, SROCC SPM A.2}\nHuman-caused climate change is already affecting many weather and \nclimate extremes in every region across the globe. Evidence of observed \nchanges in extremes such as heatwaves, heavy precipitation, droughts, \nand tropical cyclones, and, in particular, their attribution to human \nin\ufb02uence, has strengthened since AR5 (Figure 2.3).","topic":"Climate Change Action"}}
{"id":"921c9f23-d15c-43a3-8ab3-00275aec9957","question":"Considering the IPCC's assessment that with each increment of global warming, losses and damages will increase and be concentrated among the poorest vulnerable populations, what are the primary constraints in transitioning from incremental to transformational adaptation as outlined in the report?","reference_answer":"The primary constraints in transitioning from incremental to transformational adaptation are vested interests, economic lock-ins, institutional path dependencies, and prevalent practices, cultures, norms, and belief systems.","reference_context":"Document 95: 62\nSection 2\nSection 1\nSection 2\n\ufb01re-adapted ecosystems, or hard defences against \ufb02ooding) and human \nsettlements (e.g. stranded assets and vulnerable communities that \ncannot afford to shift away or adapt and require an increase in social \nsafety nets). Maladaptation especially affects marginalised and vulnerable \ngroups adversely (e.g., Indigenous Peoples, ethnic minorities, low-income \nhouseholds, people living in informal settlements), reinforcing and \nentrenching existing inequities. Maladaptation can be avoided by \ufb02exible, \nmulti-sectoral, inclusive and long-term planning and implementation of \nadaptation actions with bene\ufb01ts to many sectors and systems. (high \ncon\ufb01dence) {WGII SPM C.4, WGII SPM C.4.3, WGII TS.D.3.1}\nSystemic barriers constrain the implementation of adaptation \noptions in vulnerable sectors, regions and social groups (high \ncon\ufb01dence). Key barriers include limited resources, lack of private-sector \nand civic engagement, insuf\ufb01cient mobilisation of \ufb01nance, lack of political \ncommitment, limited research and\/or slow and low uptake of adaptation \nscience and a low sense of urgency. Inequity and poverty also constrain \nadaptation, leading to soft limits and resulting in disproportionate \nexposure and impacts for most vulnerable groups (high con\ufb01dence). The \nlargest adaptation gaps exist among lower income population groups \n(high con\ufb01dence). \nAs adaptation options often have long implementation \ntimes, long-term planning and accelerated implementation, particularly \nin this decade, is important to close adaptation gaps, recognising that \nconstraints remain for some regions (high con\ufb01dence). Prioritisation of \noptions and transitions from incremental to transformational adaptation \nare limited due to vested interests, economic lock-ins, institutional \npath dependencies and prevalent practices, cultures, norms and belief \nsystems (high con\ufb01dence).\n\nDocument 92: Most often, maladaptation is an unintended consequence. See Annex I: Glossary.\n2.3.2. Adaptation Gaps and Barriers \nDespite progress, adaptation gaps exist between current \nlevels of adaptation and levels needed to respond to impacts \nand reduce climate risks (high con\ufb01dence). While progress in \nadaptation implementation is observed across all sectors and regions \n(very high con\ufb01dence), many adaptation initiatives prioritise immediate \nand near-term climate risk reduction, e.g., through hard \ufb02ood protection, \nwhich reduces the opportunity for transformational adaptation99 (high \ncon\ufb01dence). Most observed adaptation is fragmented, small in scale, \nincremental, sector-speci\ufb01c, and focused more on planning rather than \nimplementation (high con\ufb01dence). Further, observed adaptation is \nunequally distributed across regions and the largest adaptation gaps \nexist among lower population income groups (high con\ufb01dence). In the \nurban context, the largest adaptation gaps exist in projects that manage \ncomplex risks, for example in the food\u2013energy\u2013water\u2013health nexus or \nthe inter-relationships of air quality and climate risk (high con\ufb01dence). \nMany funding, knowledge and practice gaps remain for effective \nimplementation, monitoring and evaluation and current adaptation \nefforts are not expected to meet existing goals (high con\ufb01dence). \nAt current rates of adaptation planning and implementation the \nadaptation gap will continue to grow (high con\ufb01dence). {WGII SPM C.1, \nWGII SPM C.1.2, WGII SPM C.4.1, WGII TS.D.1.3, WGII TS.D.1.4} \nSoft and hard adaptation limits100 have already been reached in \nsome sectors and regions, in spite of adaptation having buffered \nsome climate impacts (high con\ufb01dence). Ecosystems already \nreaching hard adaptation limits include some warm water coral reefs, \nsome coastal wetlands, some rainforests, and some polar and mountain \necosystems (high con\ufb01dence).\n\nDocument 156: For example, inclusive, integrated \nand long-term planning at local, municipal, sub-national and national \nscales, together with effective regulation and monitoring systems \nand \ufb01nancial and technological resources and capabilities foster \nurban and rural system transition. There are a range of cross-cutting \nadaptation options, such as disaster risk management, early warning \nsystems, climate services and risk spreading and sharing that have \nbroad applicability across sectors and provide greater bene\ufb01ts to other \nadaptation options when combined. Transitioning from incremental to \ntransformational adaptation, and addressing a range of constraints, \nprimarily in the \ufb01nancial, governance, institutional and policy domains, \ncan help overcome soft adaptation limits. However, adaptation does \nnot prevent all losses and damages, even with effective adaptation and \nbefore reaching soft and hard limits. (high con\ufb01dence) {WGII SPM C.2, \nWGII SPM C.2.6, WGII SPM.C.2.13, WGII SPM C.3.1, WGII SPM.C.3.4, \nWGII SPM C.3.5, WGII Figure TS.6 Panel (e)}\nMaladaptive responses to climate change can create lock-ins of \nvulnerability, exposure and risks that are dif\ufb01cult and expensive \nto change and exacerbate existing inequalities. Actions that focus \non sectors and risks in isolation and on short-term gains often lead \nto maladaptation. Adaptation options can become maladaptive due \nto their environmental impacts that constrain ecosystem services and \ndecrease biodiversity and ecosystem resilience to climate change or by \ncausing adverse outcomes for different groups, exacerbating inequity. \nMaladaptation can be avoided by \ufb02exible, multi-sectoral, inclusive and\n\nDocument 240: Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence). {WGII SPM B.2, WGII SPM B.2.4, \nWGII SPM B.3.2, WGII SPM B.3.3, WGII SPM C.1, WGII SPM C.1.2, \nWGII SPM C.2.9}\nMeaningful participation and inclusive planning, informed by \ncultural values, Indigenous Knowledge, local knowledge, and \nscienti\ufb01c knowledge can help address adaptation gaps and \navoid maladaptation (high con\ufb01dence). Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":95,"distracting_context":"{WGI SPM.2.7; \nWGII SPM B.2.1, WGII SPM B.5, WGII SPM B.5.1, WGII SPM B.5.2, \nWGII SPM B.5.3, WGII SPM B.5.4, WGII Cross-Chapter Box COVID in Chapter 7; \nWGIII SPM C.11.2; SRCCL SPM A.5, SRCCL SPM A.6.5} (Figure 4.3)\nWith every increment of global warming losses and damages will \nincrease (very high con\ufb01dence), become increasingly dif\ufb01cult \nto avoid and be strongly concentrated among the poorest \nvulnerable populations (high con\ufb01dence). Adaptation does not \nprevent all losses and damages, even with effective adaptation and \nbefore reaching soft and hard limits. Losses and damages will be \nunequally distributed across systems, regions and sectors and are \nnot comprehensively addressed by current \ufb01nancial, governance and \ninstitutional arrangements, particularly in vulnerable developing \ncountries. (high con\ufb01dence). {WGII SPM B.4, WGII SPM C.3, WGII SPM C.3.5}","topic":"Climate Change Action"}}
{"id":"dcfca80a-fd4e-4cd9-9dc3-a00a9bae3cae","question":"Considering the limitations of models in representing certain extreme climatic conditions and ecosystem responses, how might delayed mitigation action influence the efficacy of adaptation strategies, as articulated in the IPCC report?","reference_answer":"Delayed mitigation action will decrease the effectiveness of many adaptation options, including Ecosystem-based Adaptation and many water-related options, as well as increasing mitigation feasibility risks, such as for options based on ecosystems.","reference_context":"Document 254: {WGIII SPM footnote 54}\n154 The mitigation potentials and mitigation costs of individual technologies in a speci\ufb01c context or region may differ greatly from the provided estimates (medium con\ufb01dence). \n{WGIII SPM C.12.1}\ncon\ufb01dence). The most feasible energy system adaptation options \nsupport infrastructure resilience, reliable power systems and ef\ufb01cient \nwater use for existing and new energy generation systems (very \nhigh con\ufb01dence). Adaptations for hydropower and thermo-electric \npower generation are effective in most regions up to 1.5\u00b0C to 2\u00b0C, \nwith decreasing effectiveness at higher levels of warming (medium \ncon\ufb01dence). Energy generation diversi\ufb01cation (e.g., wind, solar, small-\nscale hydroelectric) and demand side management (e.g., storage and \nenergy ef\ufb01ciency improvements) can increase energy reliability and \nreduce vulnerabilities to climate change, especially in rural populations \n(high con\ufb01dence). Climate responsive energy markets, updated design \nstandards on energy assets according to current and projected climate \nchange, smart-grid technologies, robust transmission systems and \nimproved capacity to respond to supply de\ufb01cits have high feasibility \nin the medium- to long-term, with mitigation co-bene\ufb01ts (very high \ncon\ufb01dence). {WGII SPM B.5.3, WGII SPM C.2.10; WGIII TS.5.1}\n4.5.2. Industry\nThere are several options to reduce industrial emissions \nthat differ by type of industry; many industries are disrupted \nby climate change, especially from extreme events (high \ncon\ufb01dence). Reducing industry emissions will entail coordinated \naction throughout value chains to promote all mitigation options, \nincluding demand management, energy and materials ef\ufb01ciency, \ncircular material \ufb02ows, as well as abatement technologies and\n\nDocument 246: The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change. (high con\ufb01dence) (Figure 4.4). {WGIII SPM C.10}\n4.5 Near-Term Mitigation and Adaptation Actions\nRapid and far-reaching transitions across all sectors and systems are necessary to achieve deep and sustained \nemissions reductions and secure a liveable and sustainable future for all. These system transitions involve a \nsigni\ufb01cant upscaling of a wide portfolio of mitigation and adaptation options. Feasible, effective and low-cost \noptions for mitigation and adaptation are already available, with differences across systems and regions. (high \ncon\ufb01dence)\n\nDocument 302: Such measures can also achieve \ngreater bene\ufb01ts through cascading effects across sectors \n(medium con\ufb01dence). For example, the feasibility of using land for \nboth agriculture and centralised solar production can increase when \nsuch options are combined (high con\ufb01dence). Similarly, integrated \ntransport and energy infrastructure planning and operations can \ntogether reduce the environmental, social, and economic impacts of \ndecarbonising the transport and energy sectors (high con\ufb01dence). The \nimplementation of packages of multiple city-scale mitigation strategies \ncan have cascading effects across sectors and reduce GHG emissions \nboth within and outside a city\u2019s administrative boundaries (very high \ncon\ufb01dence). Integrated design approaches to the construction and \nretro\ufb01t of buildings provide increasing examples of zero energy or \nzero carbon buildings in several regions. To minimise maladaptation, \nmulti-sectoral, multi-actor and inclusive planning with \ufb02exible \npathways encourages low-regret and timely actions that keep options \nopen, ensure bene\ufb01ts in multiple sectors and systems and suggest the \navailable solution space for adapting to long-term climate change \n(very high con\ufb01dence). Trade-offs in terms of employment, water \nuse, land-use competition and biodiversity, as well as access to, \nand the affordability of, energy, food, and water can be avoided \nby well-implemented land-based mitigation options, especially those \nthat do not threaten existing sustainable land uses and land rights, with \nframeworks for integrated policy implementation (high con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, \nWGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.1.5, \nWGIII SPM E.1.2}\nMitigation and adaptation when implemented together, and \ncombined with broader sustainable development objectives, \nwould yield multiple bene\ufb01ts for human well-being as well as \necosystem and planetary health (high con\ufb01dence).\n\nDocument 215: The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).  Comprehensive, effective, and innovative \nresponses integrating adaptation and mitigation can harness synergies \nand reduce trade-offs between adaptation and mitigation, as well as in \nmeeting requirements for \ufb01nancing (very high con\ufb01dence) (see Section \n4.5, 4.6, 4.8 and 4.9). {WGII SPM B.3, WGII SPM B.4, WGII SPM B.6.2, \nWGII SPM C.2, WGII SPM C.3, WGII SPM D.1, WGII SPM D.4.3, WGII SPM D.5, \nWG II TS D.1.4, WG II TS.D.5, WGII TS D.7.5; WGIII SPM B.6.3,WGIII SPM B.6.4, \nWGIII SPM C.9, WGIII SPM D.2, WGIII SPM E.13; SR1.5 SPM C.2.7, \nSR1.5 D.1.3, SR1.5 D.5.2}\nMitigation actions will have other sustainable development \nco-bene\ufb01ts (high con\ufb01dence). Mitigation will improve air quality and \nhuman health in the near term notably because many air pollutants are \n148 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply.","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":254,"distracting_context":"Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\nFuture climate change is projected to increase the severity of impacts \nacross natural and human systems and will increase regional differences\nAreas with little or no \nproduction, or not assessed\n1Projected temperature conditions above \nthe estimated historical (1850-2005) \nmaximum mean annual temperature \nexperienced by each species, assuming \nno species relocation. \n2Includes 30,652 species of birds, \nmammals, reptiles, amphibians, marine \n\ufb01sh, benthic marine invertebrates, krill, \ncephalopods, corals, and seagrasses.\na) Risk of \nspecies losses\nb) Heat-humidity \nrisks to \nhuman health\nc) Food production \nimpacts\n3Projected regional impacts utilize a global threshold beyond which daily mean surface air temperature and relative humidity may induce \nhyperthermia that poses a risk of mortality. The duration and intensity of heatwaves are not presented here. Heat-related health outcomes \nvary by location and are highly moderated by socio-economic, occupational and other non-climatic determinants of individual health and \nsocio-economic vulnerability. The threshold used in these maps is based on a single study that synthesized data from 783 cases to \ndetermine the relationship between heat-humidity conditions and mortality drawn largely from observations in temperate climates.\nHistorical 1991\u20132005","topic":"Climate Change Action"}}
{"id":"4a07b257-181c-4f00-9355-08b20b6461f0","question":"Given the context of water-intensive industries' efforts to reduce water stress, how might the projected demand-side measures contribute to the reduction of global GHG emissions by 2050 in comparison to baseline scenarios, particularly in urban systems where integrated planning incorporates physical, natural, and social infrastructure?","reference_answer":"Demand-side measures can reduce global GHG emissions in end-use sectors by 40 to 70% by 2050 compared to baseline scenarios.","reference_context":"Document 245: The system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors. This report \nhas a particular focus on the following system transitions: energy; industry; cities, settlements and infrastructure; land, ocean, food and water; health and nutrition; and society, \nlivelihood and economies. {WGII SPM A, WGII Figure SPM.1, WGII Figure SPM.4; SR1.5 SPM C.2}\n152 See Annex I: Glossary.\nglobal GHG emissions by at least half the 2019 level by 2030 (options \ncosting less than USD 20 tCO2-eq\u20131 are estimated to make up more \nthan half of this potential) (high con\ufb01dence) (Figure 4.4). The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change.\n\nDocument 246: The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change. (high con\ufb01dence) (Figure 4.4). {WGIII SPM C.10}\n4.5 Near-Term Mitigation and Adaptation Actions\nRapid and far-reaching transitions across all sectors and systems are necessary to achieve deep and sustained \nemissions reductions and secure a liveable and sustainable future for all. These system transitions involve a \nsigni\ufb01cant upscaling of a wide portfolio of mitigation and adaptation options. Feasible, effective and low-cost \noptions for mitigation and adaptation are already available, with differences across systems and regions. (high \ncon\ufb01dence)\n\nDocument 244: Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence). System \ntransitions151 consistent with pathways that limit warming to 1.5\u00b0C \n(>50%) with no or limited overshoot are more rapid and pronounced \nin the near-term than in those that limit warming to 2\u00b0C (>67%) \n(high con\ufb01dence). Such a systemic change is unprecedented in terms \nof scale, but not necessarily in terms of speed (medium con\ufb01dence). \nThe system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors.\n\nDocument 253: Energy Systems\nRapid and deep reductions in GHG emissions require major \nenergy system transitions (high con\ufb01dence). Adaptation options \ncan help reduce climate-related risks to the energy system \n(very high con\ufb01dence). Net zero CO2 energy systems entail: a \nsubstantial reduction in overall fossil fuel use, minimal use of \nunabated fossil fuels153, and use of Carbon Capture and Storage in \nthe remaining fossil fuel systems; electricity systems that emit no \nnet CO2; widespread electrification; alternative energy carriers in \napplications less amenable to electrification; energy conservation \nand efficiency; and greater integration across the energy system \n(high confidence). Large contributions to emissions reductions can \ncome from options costing less than USD 20 tCO2-eq\u20131, including \nsolar and wind energy, energy ef\ufb01ciency improvements, and CH4 \n(methane) emissions reductions (from coal mining, oil and gas, and \nwaste) (medium confidence).154 Many of these response options are \ntechnically viable and are supported by the public (high confidence). \nMaintaining emission-intensive systems may, in some regions and \nsectors, be more expensive than transitioning to low emission \nsystems (high confidence). {WGII SPM C.2.10; WGIII SPM C.4.1, \nWGIII SPM C.4.2, WGIII SPM C.12.1, WGIII SPM E.1.1, WGIII TS.5.1} \nClimate change and related extreme events will affect future energy \nsystems, including hydropower production, bioenergy yields, thermal \npower plant ef\ufb01ciencies, and demands for heating and cooling (high \n153 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50\u201380% of fugitive methane emissions from energy supply. {WGIII SPM footnote 54}\n154 The mitigation potentials and mitigation costs of individual technologies in a speci\ufb01c context or region may differ greatly from the provided estimates (medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":245,"distracting_context":"Water intensive industries (e.g., mining) can undertake measures to \nreduce water stress, such as water recycling and reuse, using brackish \nor saline sources, working to improve water use ef\ufb01ciency. However, \nresidual risks will remain, especially at higher levels of warming \n(medium con\ufb01dence). {WGII TS.B.9.1, WGII 16.5.2, WGII 4.6.3} (Section 3.2)\n4.5.3. Cities, Settlements and Infrastructure\nUrban systems are critical for achieving deep emissions \nreductions and advancing climate resilient development, \nparticularly when this involves integrated planning that \nincorporates physical, natural and social infrastructure (high \ncon\ufb01dence). Deep emissions reductions and integrated adaptation \nactions are advanced by: integrated, inclusive land use planning \nand decision-making; compact urban form by co-locating jobs and \nhousing; reducing or changing urban energy and material consumption; \nelectri\ufb01cation in combination with low emissions sources; improved \nwater and waste management infrastructure; and enhancing carbon \nuptake and storage in the urban environment (e.g. bio-based building \nmaterials, permeable surfaces and urban green and blue infrastructure). \nCities can achieve net zero emissions if emissions are reduced within \nand outside of their administrative boundaries through supply chains, \ncreating bene\ufb01cial cascading effects across other sectors. (high con\ufb01dence) \n{WGII SPM C.5.6, WGII SPM D.1.3, WGII SPM D.3; WGIII SPM C.6, WGIII \nSPM C.6.2, WGIII TS 5.4, SR1.5 SPM C.2.4}\nConsidering climate change impacts and risks (e.g., through climate \nservices) in the design and planning of urban and rural settlements \nand infrastructure is critical for resilience and enhancing human \nwell-being. Effective mitigation can be advanced at each of the design, \nconstruction, retro\ufb01t, use and disposal stages for buildings. Mitigation \ninterventions for buildings include: at the construction phase, low-\n155 A set of measures and daily practices that avoid demand for energy, materials, land and water while delivering human well-being for all within planetary boundaries.","topic":"Climate Change Action"}}
{"id":"9a3eb20b-e68f-472f-acb1-bda91d20d1f0","question":"Considering the importance of sustainable development and the need to support climate change adaptation, what is the anticipated impact of unabated greenhouse gas emissions on the occurrence and severity of marine heatwaves, and how might this intersect with efforts to ensure ecosystem services and support vulnerable communities?","reference_answer":"Additional warming will lead to more frequent and intense marine heatwaves (high confidence).","reference_context":"Document 118: {WGI SPM D.1.7, WGI Box TS.7} (Cross-Section Box.2)\nContinued GHG emissions will further affect all major climate \nsystem components, and many changes will be irreversible on \ncentennial to millennial time scales. Many changes in the climate \nsystem become larger in direct relation to increasing global warming. \nWith every additional increment of global warming, changes in \nextremes continue to become larger. Additional warming will lead to \nmore frequent and intense marine heatwaves and is projected to further \namplify permafrost thawing and loss of seasonal snow cover, glaciers, \nland ice and Arctic sea ice (high con\ufb01dence). Continued global warming \nis projected to further intensify the global water cycle, including its \nvariability, global monsoon precipitation117, and very wet and very dry \nweather and climate events and seasons (high con\ufb01dence). The portion \nof global land experiencing detectable changes in seasonal mean \nprecipitation is projected to increase (medium con\ufb01dence) with more \nvariable precipitation and surface water \ufb02ows over most land regions \nwithin seasons (high con\ufb01dence) and from year to year (medium \ncon\ufb01dence). Many changes due to past and future GHG emissions are \nirreversible118 on centennial to millennial time scales, especially in the \nocean, ice sheets and global sea level (see 3.1.3). Ocean acidi\ufb01cation \n(virtually certain), ocean deoxygenation (high con\ufb01dence) and global \nmean sea level (virtually certain) will continue to increase in the 21st century, \nat rates dependent on future emissions.\n\nDocument 119: The portion \nof global land experiencing detectable changes in seasonal mean \nprecipitation is projected to increase (medium con\ufb01dence) with more \nvariable precipitation and surface water \ufb02ows over most land regions \nwithin seasons (high con\ufb01dence) and from year to year (medium \ncon\ufb01dence). Many changes due to past and future GHG emissions are \nirreversible118 on centennial to millennial time scales, especially in the \nocean, ice sheets and global sea level (see 3.1.3). Ocean acidi\ufb01cation \n(virtually certain), ocean deoxygenation (high con\ufb01dence) and global \nmean sea level (virtually certain) will continue to increase in the 21st century, \nat rates dependent on future emissions. {WGI SPM B.2, WGI SPM B.2.2, \nWGI SPM B.2.3, WGI SPM B.2.5, WGI SPM B.3, WGI SPM B.3.1, \nWGI SPM B.3.2, WGI SPM B.4, WGI SPM B.5, WGI SPM B.5.1, WGI SPM B.5.3, \nWGI Figure SPM.8} (Figure 3.1)\nWith further global warming, every region is projected to \nincreasingly experience concurrent and multiple changes \nin climatic impact-drivers. Increases in hot and decreases in \ncold climatic impact-drivers, such as temperature extremes, are \nprojected in all regions (high con\ufb01dence). At 1.5\u00b0C global warming, \nheavy precipitation and \ufb02ooding events are projected to intensify \nand become more frequent in most regions in Africa, Asia (high \ncon\ufb01dence), North America (medium to high con\ufb01dence) and Europe \n(medium con\ufb01dence).\n\nDocument 117: 69\nLong-Term Climate and Development Futures\nSection 3\npolicies limit this additional warming and lead to strong bene\ufb01ts \nfor air quality (high con\ufb01dence). In high and very high GHG \nemissions scenarios (SSP3-7.0 and SSP5-8.5), combined changes \nin SLCF emissions, such as CH4, aerosol and ozone precursors, lead to a \nnet global warming by 2100 of likely 0.4\u00b0C to 0.9\u00b0C relative to 2019. \nThis is due to projected increases in atmospheric concentration of CH4, \ntropospheric ozone, hydro\ufb02uorocarbons and, when strong air pollution \ncontrol is considered, reductions of cooling aerosols. In low and very \nlow GHG emissions scenarios (SSP1-1.9 and SSP1-2.6), air pollution \ncontrol policies, reductions in CH4 and other ozone precursors lead to a \nnet cooling, whereas reductions in anthropogenic cooling aerosols lead \nto a net warming (high con\ufb01dence). Altogether, this causes a likely net \nwarming of 0.0\u00b0C to 0.3\u00b0C due to SLCF changes in 2100 relative to 2019 \nand strong reductions in global surface ozone and particulate matter \n(high con\ufb01dence). {WGI SPM D.1.7, WGI Box TS.7} (Cross-Section Box.2)\nContinued GHG emissions will further affect all major climate \nsystem components, and many changes will be irreversible on \ncentennial to millennial time scales. Many changes in the climate \nsystem become larger in direct relation to increasing global warming. \nWith every additional increment of global warming, changes in \nextremes continue to become larger. Additional warming will lead to \nmore frequent and intense marine heatwaves and is projected to further \namplify permafrost thawing and loss of seasonal snow cover, glaciers, \nland ice and Arctic sea ice (high con\ufb01dence).\n\nDocument 226: 98\nSection 4\nSection 1\nSection 4\nGlobal warming will continue to increase in the near term (2021\u20132040) \nmainly due to increased cumulative CO2 emissions in nearly all \nconsidered scenarios and pathways. In the near term, every \nregion in the world is projected to face further increases in \nclimate hazards (medium to high con\ufb01dence, depending on \nregion and hazard), increasing multiple risks to ecosystems \nand humans (very high con\ufb01dence). In the near term, natural \nvariability149 will modulate human-caused changes, either attenuating \nor amplifying projected changes, especially at regional scales, with little \neffect on centennial global warming. Those modulations are important \nto consider in adaptation planning. Global surface temperature in any \nsingle year can vary above or below the long-term human-induced \ntrend, due to natural variability. By 2030, global surface temperature \nin any individual year could exceed 1.5\u00b0C relative to 1850\u20131900 with a \nprobability between 40% and 60%, across the five scenarios assessed \nin WGI (medium confidence). The occurrence of individual years with \nglobal surface temperature change above a certain level does not \nimply that this global warming level has been reached. If a large \nexplosive volcanic eruption were to occur in the near term150 , it \nwould temporarily and partially mask human-caused climate change \nby reducing global surface temperature and precipitation, especially \nover land, for one to three years (medium con\ufb01dence). {WGI SPM B.1.3, \nWGI SPM B.1.4, WGI SPM C.1, WGI SPM C.2, WGI Cross-Section Box TS.1, \nWGI Cross-Chapter Box 4.1; WGII SPM B.3, WGII SPM B.3.1; \nWGIII Box SPM.1 Figure 1}\nThe level of risk for humans and ecosystems will depend on near-term \ntrends in vulnerability, exposure, level of socio-economic \ndevelopment and adaptation (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":118,"distracting_context":"There is a strong link between \nsustainable development, vulnerability and climate risks. Social safety \nnets that support climate change adaptation have strong co-bene\ufb01ts \nwith development goals such as education, poverty alleviation, gender \ninclusion and food security. Land restoration contributes to mitigation \nand adaptation with synergies via enhanced ecosystem services and \nwith economically positive returns and co-bene\ufb01ts for poverty reduction \nand improved livelihoods. Trade-offs can be evaluated and minimised \nby giving emphasis to capacity building, \ufb01nance, technology transfer, \ninvestments; governance, development, context speci\ufb01c gender-based \nand other social equity considerations with meaningful participation \nof Indigenous Peoples, local communities and vulnerable populations. \n(high con\ufb01dence). {WGII SPM C.2.9, WGII SPM C.5.6, WGII SPM D.5.2, \nWGII Cross-Chapter Box on Gender in Chapter 18; WGIII SPM C.9.2, \nWGIII SPM D.1.2, WGIII SPM D.1.4, WGIII SPM D.2; SRCCL SPM D.2.2, SRCCL TS.4}\nContext \nrelevant \ndesign \nand \nimplementation \nrequires \nconsidering people\u2019s needs, biodiversity, and other sustainable \ndevelopment dimensions (very high con\ufb01dence). Countries at \nall stages of economic development seek to improve the well-being \nof people, and their development priorities re\ufb02ect different starting \npoints and contexts. Different contexts include but are not limited to \nsocial, economic, environmental, cultural, or political circumstances, \nresource endowment, capabilities, international environment, and prior \ndevelopment. n regions with high dependency on fossil fuels for, among \nother things, revenue and employment generation, mitigating risks for \nsustainable development requires policies that promote economic and \nenergy sector diversi\ufb01cation and considerations of just transitions \nprinciples, processes and practices (high con\ufb01dence). For individuals and \nhouseholds in low-lying coastal areas, in Small Islands, and smallholder \nfarmers transitioning from incremental to transformational adaptation \ncan help overcome soft adaptation limits (high con\ufb01dence).","topic":"Climate Change Impacts"}}
{"id":"26550848-0f54-4895-b03c-52aa0b8e1d0b","question":"Considering the various adaptation options outlined in the IPCC report, such as those effective in the agriculture sector and ecosystem-based approaches, what factors does the report identify as influencing the timing at which different countries might achieve net zero emissions?","reference_answer":"The timing of when different countries reach net zero emissions is influenced by the potential to reduce GHG emissions and undertake carbon dioxide removal, the associated costs, availability of policy mechanisms to balance emissions and removals between sectors and countries, equity and capacity considerations, and the incorporation of equity principles.","reference_context":"Document 88: (high con\ufb01dence) {WGIII Box TS.6, WGIII Cross-Chapter Box 3}\nThe adoption and implementation of net zero emission targets by countries and regions also depend on equity and capacity \nconsiderations (high con\ufb01dence). The formulation of net zero pathways by countries will bene\ufb01t from clarity on scope, plans-of-action, and \nfairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global \nmodelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the \ncountry-level timing of net zero (high con\ufb01dence). The Paris Agreement also recognizes that peaking of emissions will occur later in developing \ncountries than developed countries (Article 4.1). {WGIII Box TS.6, WGIII Cross-Chapter Box 3, WGIII 14.3}\nMore information on country-level net zero pledges is provided in Section 2.3.1, on the timing of global net zero emissions in Section 3.3.2, and \non sectoral aspects of net zero in Section 4.1.\n98 \nSee footnote 12 above.\n\nDocument 87: {WGI SPM D.1.8; WGIII Box TS.6, WGIII Cross-Chapter Box 2}\nAchieving global net zero GHG emissions requires all remaining CO2 and metric-weighted98 non-CO2 GHG emissions to be \ncounterbalanced by durably stored CO2 removals (high con\ufb01dence). Some non-CO2 emissions, such as CH4 and N2O from agriculture, \ncannot be fully eliminated using existing and anticipated technical measures. {WGIII SPM C.2.4, WGIII SPM C.11.4, WGIII Cross-Chapter Box 3}\nGlobal net zero CO2 or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that \nothers reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions \nvary by sector and region. If and when net zero emissions for a given sector or region are reached depends on multiple factors, including \nthe potential to reduce GHG emissions and undertake carbon dioxide removal, the associated costs, and the availability of policy \nmechanisms to balance emissions and removals between sectors and countries. (high con\ufb01dence) {WGIII Box TS.6, WGIII Cross-Chapter Box 3}\nThe adoption and implementation of net zero emission targets by countries and regions also depend on equity and capacity \nconsiderations (high con\ufb01dence). The formulation of net zero pathways by countries will bene\ufb01t from clarity on scope, plans-of-action, and \nfairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global \nmodelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the \ncountry-level timing of net zero (high con\ufb01dence). The Paris Agreement also recognizes that peaking of emissions will occur later in developing \ncountries than developed countries (Article 4.1).\n\nDocument 89: 61\nCurrent Status and Trends\nSection 2\nMany countries have signalled an intention to achieve net \nzero GHG or net zero CO2 emissions by around mid-century \n(Cross-Section Box.1). More than 100 countries have either adopted, \nannounced or are discussing net zero GHG or net zero CO2 emissions \ncommitments, covering more than two-thirds of global GHG emissions. \nA growing number of cities are setting climate targets, including net zero \nGHG targets. Many companies and institutions have also announced \nnet zero emissions targets in recent years. The various net zero emission \npledges differ across countries in terms of scope and speci\ufb01city, and \nlimited policies are to date in place to deliver on them. {WGIII SPM C.6.4, \nWGIII TS.4.1, WGIII Table TS.1, WGIII 13.9, WGIII 14.3, WGIII 14.5} \nAll mitigation strategies face implementation challenges, \nincluding technology risks, scaling, and costs (high con\ufb01dence). \nAlmost all mitigation options also face institutional barriers that \nneed to be addressed to enable their application at scale (medium \ncon\ufb01dence). Current development pathways may create behavioural, \nspatial, economic and social barriers to accelerated mitigation at all \nscales (high con\ufb01dence). Choices made by policymakers, citizens, the \nprivate sector and other stakeholders in\ufb02uence societies\u2019 development \npathways (high con\ufb01dence). Structural factors of national circumstances \nand capabilities (e.g., economic and natural endowments, political \nsystems and cultural factors and gender considerations) affect the \nbreadth and depth of climate governance (medium con\ufb01dence). The \nextent to which civil society actors, political actors, businesses, youth, \nlabour, media, Indigenous Peoples, and local communities are engaged \nin\ufb02uences political support for climate change mitigation and eventual \npolicy outcomes (medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":88,"distracting_context":"{WGII SPM C.3.2, WGII SPM C.5.4; \nWGII TS.D.1.6, WGII Cross-Chapter Box FINANCE; WGIII SPM E.5.4}\nThere are adaptation options which are effective84 in reducing \nclimate risks85 for speci\ufb01c contexts, sectors and regions and \ncontribute positively to sustainable development and other \nsocietal goals. In the agriculture sector, cultivar improvements, \non-farm water management and storage, soil moisture conservation, \nirrigation86, agroforestry, community-based adaptation, and farm and \nlandscape level diversi\ufb01cation, and sustainable land management \napproaches, provide multiple bene\ufb01ts and reduce climate risks. \nReduction of food loss and waste, and adaptation measures in support \nof balanced diets contribute to nutrition, health, and biodiversity bene\ufb01ts. \n(high con\ufb01dence) {WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.2; \nSRCCL B.2, SRCCL SPM C.2.1}\nEcosystem-based Adaptation87 approaches such as urban greening, \nrestoration of wetlands and upstream forest ecosystems reduce \na range of climate change risks, including \ufb02ood risks, urban heat \nand provide multiple co-bene\ufb01ts. Some land-based adaptation \noptions provide immediate bene\ufb01ts (e.g., conservation of peatlands,","topic":"Others"}}
{"id":"7d86d153-e374-4aa7-bfab-ba522318f843","question":"Considering the minimal impact on global GDP growth, what are the estimated reductions in global GHG emissions by 2050 for scenarios that aim to cap warming at 1.5\u00b0C and 2\u00b0C, and how do these reductions correlate with the projected increase in mitigation costs and economic benefits of reduced climate impacts and adaptation needs?","reference_answer":"In pathways that limit warming to 1.5\u00b0C, global GHG emissions are projected to fall by 84 [73 to 98]% by 2050. For pathways that limit warming to 2\u00b0C, the reduction is projected to be 64 [53 to 77]% by 2050.","reference_context":"Document 208: {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems. In modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited \novershoot and in those that limit warming to 2\u00b0C (>67%) and assume immediate action, global GHG emissions \nare projected to peak in the early 2020s followed by rapid and deep reductions. As adaptation options often have \nlong implementation times, accelerated implementation of adaptation, particularly in this decade, is important \nto close adaptation gaps. (high con\ufb01dence)\n\nDocument 214: Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4). (high con\ufb01dence) {WGI SPM B.1, WGI SPM B.1.3, WGI \nSPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM \nC.2, WGII SPM C.3.1, WGII Figure SPM.4b; SROCC SPM C.3.4, SROCC \nFigure 3.4, SROCC Figure SPM.5}\nNear-term actions that limit global warming to close to 1.5\u00b0C \nwould substantially reduce projected losses and damages related \nto climate change in human systems and ecosystems, compared \nto higher warming levels, but cannot eliminate them all (very \nhigh con\ufb01dence). The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).\n\nDocument 213: Positive (solid \ufb01lled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to \nGHG emissions from the year 2019. The category \u201cenergy supply (including electricity)\u201d includes bioenergy with carbon capture and storage and direct air carbon capture and storage. \n{WGIII Box TS.5, WGIII 3.3, WGIII 3.4, WGIII 6.6, WGIII 10.3, WGIII 11.3} (Cross-Section Box.2)\nAccelerated implementation of adaptation will improve well-being by reducing losses and damages, especially \nfor vulnerable populations. Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4).\n\nDocument 207: In pathways \nthat limit warming to 1.5\u00b0C (>50%) with no or limited overshoot, net \nglobal GHG emissions are projected to fall by 43 [34 to 60]%143 below \n2019 levels by 2030, 60 [49 to 77]% by 2035, 69 [58 to 90]% by 2040 \nand 84 [73 to 98]% by 2050 (high con\ufb01dence) (Section 2.3.1, Table 2.2, \nFigure 2.5, Table 3.1)144. Global modelled pathways that limit warming \nto 2\u00b0C (>67%) have reductions in GHG emissions below 2019 levels \nof 21 [1 to 42]% by 2030, 35 [22 to 55] % by 2035, 46 [34 to 63] \n% by 2040 and 64 [53 to 77]% by 2050145 (high con\ufb01dence). Global \nGHG emissions associated with NDCs announced prior to COP26 would \nmake it likely that warming would exceed 1.5\u00b0C (high con\ufb01dence) \nand limiting warming to 2\u00b0C (>67%) would then imply a rapid \nacceleration of emission reductions during 2030\u20132050, around \n70% faster than in pathways where immediate action is taken to \nlimit warming to 2\u00b0C (>67%) (medium con\ufb01dence) (Section 2.3.1) \nContinued investments in unabated high-emitting infrastructure146 and \nlimited development and deployment of low-emitting alternatives \nprior to 2030 would act as barriers to this acceleration and increase \nfeasibility risks (high confidence). {WGIII SPM B.6.3, WGIII 3.5.2, \nWGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, \nWGIII Table SPM.2} (Cross-Section Box.2)\nDeep, rapid, and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate \nchange for humans and ecosystems.","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":208,"distracting_context":"The aggregate effects of climate change \nmitigation on global GDP (excluding damages from climate change and \nadaptation costs) are small compared to global projected GDP growth. \nProjected estimates of global aggregate net economic damages and \nthe costs of adaptation generally increase with global warming level. \n(high con\ufb01dence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, \nWGIII SPM C.12.3} \nCost-bene\ufb01t analysis remains limited in its ability to represent all \ndamages from climate change, including non-monetary damages, \nor to capture the heterogeneous nature of damages and the risk of \ncatastrophic damages (high con\ufb01dence). Even without accounting for \nthese factors or for the co-bene\ufb01ts of mitigation, the global bene\ufb01ts \nof limiting warming to 2\u00b0C exceed the cost of mitigation (medium \ncon\ufb01dence). This \ufb01nding is robust against a wide range of assumptions \nabout social preferences on inequalities and discounting over time \n(medium con\ufb01dence). Limiting global warming to 1.5\u00b0C instead of 2\u00b0C \nwould increase the costs of mitigation, but also increase the bene\ufb01ts \nin terms of reduced impacts and related risks (see 3.1.1, 3.1.2) and \nreduced adaptation needs (high confidence)140. {WGII SPM B.4, WGII \nSPM B.6; WGIII SPM C.12, WGIII SPM C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; \nSR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6}\nConsidering other sustainable development dimensions, such as the \npotentially strong economic bene\ufb01ts on human health from air quality \nimprovement, may enhance the estimated bene\ufb01ts of mitigation \n(medium con\ufb01dence). The economic effects of strengthened mitigation \naction vary across regions and countries, depending notably on economic \nstructure, regional emissions reductions, policy design and level of \ninternational cooperation (high con\ufb01dence).","topic":"Climate Change Action"}}
{"id":"7f108c2d-2528-4abb-b6d3-efc7ffdc6a01","question":"Considering the mitigation potentials and varying regional impacts as noted in the IPCC report, how does climate change affect food security in different regions, particularly in the context of warming, changing precipitation patterns, loss of cryospheric elements, and increased frequency and intensity of climatic extremes?","reference_answer":"Climate change has reduced food security due to warming, changing precipitation patterns, loss of cryospheric elements, and greater frequency and intensity of climatic extremes, thereby hindering efforts to meet Sustainable Development Goals.","reference_context":"Document 43: Roughly half of the world\u2019s population currently experiences severe water \nscarcity for at least some part of the year due to a combination of climatic \nand non-climatic drivers (medium con\ufb01dence) (Figure 2.3). Unsustainable \nagricultural expansion, driven in part by unbalanced diets77, increases \necosystem and human vulnerability and leads to competition for land \nand\/or water resources (high con\ufb01dence). Increasing weather and climate \nextreme events have exposed millions of people to acute food insecurity78 \nand reduced water security, with the largest impacts observed in many \nlocations and\/or communities in Africa, Asia, Central and South America, \nLDCs, Small Islands and the Arctic, and for small-scale food producers, \nlow-income households and Indigenous Peoples globally (high con\ufb01dence). \n{WGII SPM B.1.3, WGII SPM.B.2.3, WGII Figure SPM.2, WGII TS B.2.3, \nWGII TS Figure TS. 6; SRCCL SPM A.2.8, SRCCL SPM A.5.3; SROCC SPM A.5.4., \nSROCC SPM A.7.1, SROCC SPM A.8.1, SROCC Figure SPM.2} \n77 \nBalanced diets feature plant-based foods, such as those based on coarse grains, legumes fruits and vegetables, nuts and seeds, and animal-source foods produced in resilient, \nsustainable and low-GHG emissions systems, as described in SRCCL. {WGII SPM Footnote 32}\n78 \nAcute food insecurity can occur at any time with a severity that threatens lives, livelihoods or both, regardless of the causes, context or duration, as a result of shocks risking \ndeterminants of food security and nutrition, and is used to assess the need for humanitarian action.\n\nDocument 42: 50\nSection 2\nSection 1\nSection 2\nClimate change has reduced food security and affected water \nsecurity due to warming, changing precipitation patterns, \nreduction and loss of cryospheric elements, and greater frequency \nand intensity of climatic extremes, thereby hindering efforts to \nmeet Sustainable Development Goals (high con\ufb01dence). Although \noverall agricultural productivity has increased, climate change has slowed \nthis growth in agricultural productivity over the past 50 years globally \n(medium con\ufb01dence), with related negative crop yield impacts mainly \nrecorded in mid- and low latitude regions, and some positive impacts \nin some high latitude regions (high con\ufb01dence). Ocean warming in \nthe 20th century and beyond has contributed to an overall decrease \nin maximum catch potential (medium con\ufb01dence), compounding the \nimpacts from over\ufb01shing for some \ufb01sh stocks (high con\ufb01dence). Ocean \nwarming and ocean acidi\ufb01cation have adversely affected food production \nfrom shell\ufb01sh aquaculture and \ufb01sheries in some oceanic regions (high \ncon\ufb01dence). Current levels of global warming are associated with \nmoderate risks from increased dryland water scarcity (high con\ufb01dence). \nRoughly half of the world\u2019s population currently experiences severe water \nscarcity for at least some part of the year due to a combination of climatic \nand non-climatic drivers (medium con\ufb01dence) (Figure 2.3). Unsustainable \nagricultural expansion, driven in part by unbalanced diets77, increases \necosystem and human vulnerability and leads to competition for land \nand\/or water resources (high con\ufb01dence). Increasing weather and climate \nextreme events have exposed millions of people to acute food insecurity78 \nand reduced water security, with the largest impacts observed in many \nlocations and\/or communities in Africa, Asia, Central and South America, \nLDCs, Small Islands and the Arctic, and for small-scale food producers, \nlow-income households and Indigenous Peoples globally (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":43,"distracting_context":"{WGIII SPM footnote 54}\n154 The mitigation potentials and mitigation costs of individual technologies in a speci\ufb01c context or region may differ greatly from the provided estimates (medium con\ufb01dence). \n{WGIII SPM C.12.1}\ncon\ufb01dence). The most feasible energy system adaptation options \nsupport infrastructure resilience, reliable power systems and ef\ufb01cient \nwater use for existing and new energy generation systems (very \nhigh con\ufb01dence). Adaptations for hydropower and thermo-electric \npower generation are effective in most regions up to 1.5\u00b0C to 2\u00b0C, \nwith decreasing effectiveness at higher levels of warming (medium \ncon\ufb01dence). Energy generation diversi\ufb01cation (e.g., wind, solar, small-\nscale hydroelectric) and demand side management (e.g., storage and \nenergy ef\ufb01ciency improvements) can increase energy reliability and \nreduce vulnerabilities to climate change, especially in rural populations \n(high con\ufb01dence). Climate responsive energy markets, updated design \nstandards on energy assets according to current and projected climate \nchange, smart-grid technologies, robust transmission systems and \nimproved capacity to respond to supply de\ufb01cits have high feasibility \nin the medium- to long-term, with mitigation co-bene\ufb01ts (very high \ncon\ufb01dence). {WGII SPM B.5.3, WGII SPM C.2.10; WGIII TS.5.1}\n4.5.2. Industry\nThere are several options to reduce industrial emissions \nthat differ by type of industry; many industries are disrupted \nby climate change, especially from extreme events (high \ncon\ufb01dence). Reducing industry emissions will entail coordinated \naction throughout value chains to promote all mitigation options, \nincluding demand management, energy and materials ef\ufb01ciency, \ncircular material \ufb02ows, as well as abatement technologies and","topic":"Climate Change Impacts"}}
{"id":"ddb84564-35bf-4fc6-adbf-37efcb3bc653","question":"Considering the findings of the IPCC report, how much did the unit costs of solar energy, wind energy, and lithium-ion batteries decrease from 2010 to 2019, and how might these reductions contribute to the feasibility of system transitions in energy as outlined by the report?","reference_answer":"From 2010-2019, the unit costs of solar energy decreased by 85%, wind energy by 55%, and lithium-ion batteries by 85%.","reference_context":"Document 61: Design and process innovations in \ncombination with the use of digital technologies have led to \nnear-commercial availability of many low or zero emissions \noptions in buildings, transport and industry. From 2010-2019, \nthere have been sustained decreases in the unit costs of solar energy \n(by 85%), wind energy (by 55%), and lithium-ion batteries (by 85%), \nand large increases in their deployment, e.g., >10\u00d7 for solar and >100\u00d7 for \nelectric vehicles (EVs), albeit varying widely across regions (Figure 2.4). \nElectricity from PV and wind is now cheaper than electricity from \nfossil sources in many regions, electric vehicles are increasingly \ncompetitive with internal combustion engines, and large-scale \nbattery storage on electricity grids is increasingly viable. In \ncomparison to modular small-unit size technologies, the empirical \nrecord shows that multiple large-scale mitigation technologies, with \nfewer opportunities for learning, have seen minimal cost reductions \nand their adoption has grown slowly. Maintaining emission-intensive \nsystems may, in some regions and sectors, be more expensive than \ntransitioning to low emission systems. (high con\ufb01dence) {WGIII SPM B.4, \nWGIII SPM B.4.1, WGIII SPM C.4.2, WGIII SPM C.5.2, WGIII SPM C.7.2, \nWGIII SPM C.8, WGIII Figure SPM.3, WGIII Figure SPM.3}\nFor almost all basic materials \u2013 primary metals, building materials and \nchemicals \u2013 many low- to zero-GHG intensity production processes are \nat the pilot to near-commercial and in some cases commercial stage \nbut they are not yet established industrial practice. Integrated design \nin construction and retro\ufb01t of buildings has led to increasing examples \nof zero energy or zero carbon buildings. Technological innovation \nmade possible the widespread adoption of LED lighting. Digital \ntechnologies including sensors, the internet of things, robotics, and \narti\ufb01cial intelligence can improve energy management in all sectors; \nthey can increase energy ef\ufb01ciency, and promote the adoption of many \nlow-emission technologies, including decentralised renewable energy, \nwhile creating economic opportunities.\n\nDocument 62: Integrated design \nin construction and retro\ufb01t of buildings has led to increasing examples \nof zero energy or zero carbon buildings. Technological innovation \nmade possible the widespread adoption of LED lighting. Digital \ntechnologies including sensors, the internet of things, robotics, and \narti\ufb01cial intelligence can improve energy management in all sectors; \nthey can increase energy ef\ufb01ciency, and promote the adoption of many \nlow-emission technologies, including decentralised renewable energy, \nwhile creating economic opportunities. However, some of these climate \nchange mitigation gains can be reduced or counterbalanced by growth in \ndemand for goods and services due to the use of digital devices. Several \nmitigation options, notably solar energy, wind energy, electri\ufb01cation of \nurban systems, urban green infrastructure, energy ef\ufb01ciency, demand \nside management, improved forest- and crop\/grassland management, \nand reduced food waste and loss, are technically viable, are becoming \nincreasingly cost effective and are generally supported by the public, and \nthis enables expanded deployment in many regions. (high con\ufb01dence) \n{WGIII SPM B.4.3, WGIII SPM C.5.2, WGIII SPM C.7.2, WGIII SPM E.1.1, \nWGIII TS.6.5}\nThe magnitude of global climate \ufb01nance \ufb02ows has increased \nand \ufb01nancing channels have broadened (high con\ufb01dence). \nAnnual tracked total \ufb01nancial \ufb02ows for climate mitigation and \nadaptation increased by up to 60% between 2013\/14 and 2019\/20, \nbut average growth has slowed since 2018 (medium con\ufb01dence) and \nmost climate \ufb01nance stays within national borders (high con\ufb01dence). \nMarkets for green bonds, environmental, social and governance and \nsustainable \ufb01nance products have expanded signi\ufb01cantly since AR5 \n(high con\ufb01dence). Investors, central banks, and \ufb01nancial regulators are \ndriving increased awareness of climate risk to support climate policy \ndevelopment and implementation (high con\ufb01dence).\n\nDocument 60: 53\nCurrent Status and Trends\nSection 2\nthan single policies (high con\ufb01dence). Combining mitigation with \npolicies to shift development pathways, policies that induce lifestyle or \nbehaviour changes, for example, measures promoting walkable urban \nareas combined with electri\ufb01cation and renewable energy can create \nhealth co-bene\ufb01ts from cleaner air and enhanced active mobility (high \ncon\ufb01dence). Climate governance enables mitigation by providing an \noverall direction, setting targets, mainstreaming climate action across \npolicy domains and levels, based on national circumstances and in the \ncontext of international cooperation. Effective governance enhances \nregulatory certainty, creating specialised organisations and creating the \ncontext to mobilise \ufb01nance (medium con\ufb01dence). These functions can \nbe promoted by climate-relevant laws, which are growing in number, or \nclimate strategies, among others, based on national and sub-national \ncontext (medium con\ufb01dence). Effective and equitable climate \ngovernance builds on engagement with civil society actors, political \nactors, businesses, youth, labour, media, Indigenous Peoples and local \ncommunities (medium con\ufb01dence). {WGIII SPM E.2.2, WGIII SPM E.3, \nWGIII SPM E.3.1, WGIII SPM E.4.2, WGIII SPM E.4.3, WGIII SPM E.4.4}\nThe unit costs of several low-emission technologies, including \nsolar, wind and lithium-ion batteries, have fallen consistently \nsince 2010 (Figure 2.4). Design and process innovations in \ncombination with the use of digital technologies have led to \nnear-commercial availability of many low or zero emissions \noptions in buildings, transport and industry. From 2010-2019, \nthere have been sustained decreases in the unit costs of solar energy \n(by 85%), wind energy (by 55%), and lithium-ion batteries (by 85%), \nand large increases in their deployment, e.g., >10\u00d7 for solar and >100\u00d7 for \nelectric vehicles (EVs), albeit varying widely across regions (Figure 2.4).","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":61,"distracting_context":"The system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors. This report \nhas a particular focus on the following system transitions: energy; industry; cities, settlements and infrastructure; land, ocean, food and water; health and nutrition; and society, \nlivelihood and economies. {WGII SPM A, WGII Figure SPM.1, WGII Figure SPM.4; SR1.5 SPM C.2}\n152 See Annex I: Glossary.\nglobal GHG emissions by at least half the 2019 level by 2030 (options \ncosting less than USD 20 tCO2-eq\u20131 are estimated to make up more \nthan half of this potential) (high con\ufb01dence) (Figure 4.4). The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change.","topic":"Climate Change Action"}}
{"id":"b478d76f-4a57-45fc-aa35-5aac8baa4404","question":"Considering the socio-economic disparities highlighted in the IPCC Sixth Assessment Report, what does the Synthesis Report summarize regarding the role of individuals with high socio-economic status in climate change mitigation and adaptation?","reference_answer":"The Synthesis Report (SYR) of the IPCC Sixth Assessment Report (AR6) summarizes the state of knowledge of climate change, its widespread impacts and risks, and climate change mitigation and adaptation, based on peer-reviewed scientific, technical, and socio-economic literature since the publication of the IPCC\u2019s Fifth Assessment Report (AR5) in 2014.","reference_context":"Document 3: 38\nSection 1 \nSection 1\nThis Synthesis Report (SYR) of the IPCC Sixth Assessment Report (AR6) \nsummarises the state of knowledge of climate change, its widespread \nimpacts and risks, and climate change mitigation and adaptation, based \non the peer-reviewed scienti\ufb01c, technical and socio-economic literature \nsince the publication of the IPCC\u2019s Fifth Assessment Report (AR5) in \n2014.\nThe assessment is undertaken within the context of the evolving \ninternational landscape, in particular, developments in the UN \nFramework Convention on Climate Change (UNFCCC) process, \nincluding the outcomes of the Kyoto Protocol and the adoption of the \nParis Agreement. It re\ufb02ects the increasing diversity of those involved in \nclimate action. \nThis report integrates the main \ufb01ndings of the AR6 Working Group \nreports58 and the three AR6 Special Reports59. It recognizes the \ninterdependence of climate, ecosystems and biodiversity, and human \nsocieties; the value of diverse forms of knowledge; and the close \nlinkages between climate change adaptation, mitigation, ecosystem \nhealth, human well-being and sustainable development. Building on \nmultiple analytical frameworks, including those from the physical and \nsocial sciences, this report identi\ufb01es opportunities for transformative \naction which are effective, feasible, just and equitable using concepts \nof systems transitions and resilient development pathways60. Different \nregional classi\ufb01cation schemes61 are used for physical, social and \neconomic aspects, re\ufb02ecting the underlying literature.\nAfter this introduction, Section 2, \u2018Current Status and Trends\u2019, opens \nwith the assessment of observational evidence for our changing \nclimate, historical and current drivers of human-induced climate \nchange, and its impacts. It assesses the current implementation of \nadaptation and mitigation response options. Section 3, \u2018Long-Term \nClimate and Development Futures\u2019, provides a long-term assessment of \nclimate change to 2100 and beyond in a broad range of socio-economic \n58 \nThe three Working Group contributions to AR6 are: Climate Change 2021: The Physical Science Basis; Climate Change 2022: Impacts, Adaptation and Vulnerability; and Climate \nChange 2022: Mitigation of Climate Change, respectively.\n\nDocument 4: Different \nregional classi\ufb01cation schemes61 are used for physical, social and \neconomic aspects, re\ufb02ecting the underlying literature.\nAfter this introduction, Section 2, \u2018Current Status and Trends\u2019, opens \nwith the assessment of observational evidence for our changing \nclimate, historical and current drivers of human-induced climate \nchange, and its impacts. It assesses the current implementation of \nadaptation and mitigation response options. Section 3, \u2018Long-Term \nClimate and Development Futures\u2019, provides a long-term assessment of \nclimate change to 2100 and beyond in a broad range of socio-economic \n58 \nThe three Working Group contributions to AR6 are: Climate Change 2021: The Physical Science Basis; Climate Change 2022: Impacts, Adaptation and Vulnerability; and Climate \nChange 2022: Mitigation of Climate Change, respectively. Their assessments cover scienti\ufb01c literature accepted for publication respectively by 31 January 2021, 1 September \n2021 and 11 October 2021.\n59 \nThe three Special Reports are : Global Warming of 1.5\u00b0C (2018): an IPCC Special Report on the impacts of global warming of 1.5\u00b0C above pre-industrial levels and related \nglobal greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate \npoverty (SR1.5); Climate Change and Land (2019): an IPCC Special Report on climate change, deserti\ufb01cation, land degradation, sustainable land management, food security, and \ngreenhouse gas \ufb02uxes in terrestrial ecosystems (SRCCL); and The Ocean and Cryosphere in a Changing Climate (2019) (SROCC). The Special Reports cover scienti\ufb01c literature \naccepted for publication respectively by 15 May 2018, 7 April 2019 and 15 May 2019.\n60 \nThe Glossary (Annex I) includes de\ufb01nitions of these, and other terms and concepts used in this report drawn from the AR6 joint Working Group Glossary.\n\nDocument 106: 65\nCurrent Status and Trends\nSection 2\nwhich drives\nthat change\nin\ufb02uence\nEmissions\na) AR6 integrated assessment framework on future climate, impacts and mitigation\nClimate\nImpacts \/ Risks\nMitigation Policy\nAdaptation Policy\nSocio-economic changes\n0\n1\n2\n3\n4\n5\n6\n7\n\u00b0C\nb) Scenarios and pathways across AR6 Working Group reports\nc) Determinants of risk\nTemperature for SSP-based scenarios over the \n21st century and C1-C8 at 2100\nRisks\ncan be \nrepresented as \n\u201cburning embers\u201d\nC1-C8 in 2100\nincreasing risk\n2050\n2100\n0\n50\n100\n2050\n2100\nGtCO2\/yr\nSSP1-1.9\nSSP1-2.6\nSSP2-4.5\nSSP3-7.0\nSSP5-8.5\nSSP1-1.9\nSSP1-2.6\nSSP2-4.5\nSSP3-7.0\nSSP5-8.5\nRFC1\nUnique and\nthreatened systems\ncolor shading shows \nC1-C8 category\ncolor shading shows \nrange for SSP3-7.0 \nand SSP1-2.6\nCategory \nin WGIII\nCategory description\nGHG emissions scenarios\n(SSPx-y*) in WGI & WGII \nRCPy** in\nWGI & WGII\nC1\nlimit warming to 1.5\u00b0C (>50%)\nwith no or limited overshoot\nVery low (SSP1-1.9)\nLow (SSP1-2.6) \nRCP2.6\nC2\nreturn warming to 1.5\u00b0C (>50%)\nafter a high overshoot\nC3\nlimit warming to 2\u00b0C (>67%)\nC4\nlimit warming to 2\u00b0C (>50%)\nC5\nlimit warming to 2.5\u00b0C (>50%)\nC6\nlimit warming to 3\u00b0C (>50%)\nIntermediate (SSP2-4.5)\nRCP 4.5\nRCP 8.\n\nDocument 0: 35\nClimate Change 2023\nSynthesis Report\nIPCC, 2023: Sections. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth \nAssessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, \nGeneva, Switzerland, pp. 35-115, doi: 10.59327\/IPCC\/AR6-9789291691647\nThese Sections should be cited as:","conversation_history":[],"metadata":{"question_type":"distracting element","seed_document_id":3,"distracting_context":"Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence). Eradicating extreme poverty, energy poverty, and \nproviding decent living standards to all in these regions in the context of \nachieving sustainable development objectives, in the near term, can be \nachieved without signi\ufb01cant global emissions growth (high con\ufb01dence). \nTechnology development, transfer, capacity building and \ufb01nancing can \nsupport developing countries\/ regions leapfrogging or transitioning to \nlow-emissions transport systems thereby providing multiple co-bene\ufb01ts \n(high con\ufb01dence). Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence).","topic":"Climate Change Assessment"}}
{"id":"cbdf560f-af47-42ff-8fce-1f480bdb7767","question":"As a policymaker working on integrating climate adaptation into our social protection programs, I'm looking to address adaptation gaps. Could you explain what factors increase the vulnerability to climate change specifically for Indigenous Peoples and local communities, considering historical inequities related to gender, ethnicity, and income?","reference_answer":"Vulnerability is exacerbated by inequity and marginalisation linked to gender, ethnicity, low income or combinations thereof, especially for many Indigenous Peoples and local communities.","reference_context":"Document 240: Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence). {WGII SPM B.2, WGII SPM B.2.4, \nWGII SPM B.3.2, WGII SPM B.3.3, WGII SPM C.1, WGII SPM C.1.2, \nWGII SPM C.2.9}\nMeaningful participation and inclusive planning, informed by \ncultural values, Indigenous Knowledge, local knowledge, and \nscienti\ufb01c knowledge can help address adaptation gaps and \navoid maladaptation (high con\ufb01dence). Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence).\n\nDocument 239: {WGII SPM B.5.1, WGII SPM C.2.9, \nWGII SPM D.2.1, WGII TS Box TS.4; WGIII SPM D.3, WGIII SPM D.3.3, \nWGIII SPM WGIII SPM E.3, SR1.5 SPM D.4.5} (Figure 4.3c)\nRegions and people with considerable development constraints \nhave high vulnerability to climatic hazards. Adaptation \noutcomes for the most vulnerable within and across countries \nand regions are enhanced through approaches focusing on \nequity, inclusivity, and rights-based approaches, including 3.3 to \n3.6 billion people living in contexts that are highly vulnerable \nto climate change (high con\ufb01dence). Vulnerability is higher in \nlocations with poverty, governance challenges and limited access \nto basic services and resources, violent con\ufb02ict and high levels of \nclimate-sensitive livelihoods (e.g., smallholder farmers, pastoralists, \n\ufb01shing communities) (high con\ufb01dence). Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence).\n\nDocument 241: Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence). Equity remains a \ncentral element in the UN climate regime, notwithstanding shifts \nin differentiation between states over time and challenges in \nassessing fair shares. Ambitious mitigation pathways imply large and \nsometimes disruptive changes in economic structure, with signi\ufb01cant \ndistributional consequences, within and between countries, including \nshifting of income and employment during the transition from high to \nlow emissions activities (high con\ufb01dence). While some jobs may be lost, \nlow-emissions development can also open up opportunities to enhance \nskills and create jobs (high con\ufb01dence). Broadening equitable access \nto \ufb01nance, technologies and governance that facilitate mitigation, and \nconsideration of climate justice can help equitable sharing of bene\ufb01ts \n4.4 Equity and Inclusion in Climate Change Action\n\nDocument 238: Adaptation responses are immediately needed to reduce rising climate risks, especially for the most vulnerable. \nEquity, inclusion and just transitions are key to progress on adaptation and deeper societal ambitions for \naccelerated mitigation. (high con\ufb01dence)\nAdaptation and mitigation actions, across scales, sectors and \nregions, that prioritise equity, climate justice, rights-based \napproaches, social justice and inclusivity, lead to more \nsustainable outcomes, reduce trade-offs, support transformative \nchange and advance climate resilient development (high \ncon\ufb01dence). Redistributive policies across sectors and regions that \nshield the poor and vulnerable, social safety nets, equity, inclusion \nand just transitions, at all scales can enable deeper societal ambitions \nand resolve trade-offs with sustainable development goals.(SDGs), \nparticularly education, hunger, poverty, gender and energy access (high \ncon\ufb01dence). Mitigation efforts embedded within the wider development \ncontext can increase the pace, depth and breadth of emission reductions \n(medium con\ufb01dence). Equity, inclusion and just transitions at all \nscales enable deeper societal ambitions for accelerated mitigation, \nand climate action more broadly (high con\ufb01dence). The complexity in \nrisk of rising food prices, reduced household incomes, and health and \nclimate-related malnutrition (particularly maternal malnutrition and \nchild undernutrition) and mortality increases with little or low levels \nof adaptation (high con\ufb01dence). {WGII SPM B.5.1, WGII SPM C.2.9, \nWGII SPM D.2.1, WGII TS Box TS.4; WGIII SPM D.3, WGIII SPM D.3.3, \nWGIII SPM WGIII SPM E.3, SR1.5 SPM D.4.5} (Figure 4.3c)\nRegions and people with considerable development constraints \nhave high vulnerability to climatic hazards. Adaptation \noutcomes for the most vulnerable within and across countries \nand regions are enhanced through approaches focusing on \nequity, inclusivity, and rights-based approaches, including 3.3 to \n3.6 billion people living in contexts that are highly vulnerable \nto climate change (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":240,"situational_context":"A policymaker is seeking information to address the adaptation gaps and vulnerabilities exacerbated by historical inequities, as they work on integrating climate adaptation into social protection programs.","topic":"Climate Change Action"}}
{"id":"b39f99e1-e2e6-4caa-9a74-c4091506ade6","question":"As a policymaker looking to develop equitable policies, how does the IPCC report describe the importance of equity, inclusion, and just transitions in climate change adaptation and mitigation?","reference_answer":"Equity, inclusion, and just transitions are key to progress on adaptation and deeper societal ambitions for accelerated mitigation, leading to more sustainable outcomes, reducing trade-offs, supporting transformative change, and advancing climate resilient development.","reference_context":"Document 238: Adaptation responses are immediately needed to reduce rising climate risks, especially for the most vulnerable. \nEquity, inclusion and just transitions are key to progress on adaptation and deeper societal ambitions for \naccelerated mitigation. (high con\ufb01dence)\nAdaptation and mitigation actions, across scales, sectors and \nregions, that prioritise equity, climate justice, rights-based \napproaches, social justice and inclusivity, lead to more \nsustainable outcomes, reduce trade-offs, support transformative \nchange and advance climate resilient development (high \ncon\ufb01dence). Redistributive policies across sectors and regions that \nshield the poor and vulnerable, social safety nets, equity, inclusion \nand just transitions, at all scales can enable deeper societal ambitions \nand resolve trade-offs with sustainable development goals.(SDGs), \nparticularly education, hunger, poverty, gender and energy access (high \ncon\ufb01dence). Mitigation efforts embedded within the wider development \ncontext can increase the pace, depth and breadth of emission reductions \n(medium con\ufb01dence). Equity, inclusion and just transitions at all \nscales enable deeper societal ambitions for accelerated mitigation, \nand climate action more broadly (high con\ufb01dence). The complexity in \nrisk of rising food prices, reduced household incomes, and health and \nclimate-related malnutrition (particularly maternal malnutrition and \nchild undernutrition) and mortality increases with little or low levels \nof adaptation (high con\ufb01dence). {WGII SPM B.5.1, WGII SPM C.2.9, \nWGII SPM D.2.1, WGII TS Box TS.4; WGIII SPM D.3, WGIII SPM D.3.3, \nWGIII SPM WGIII SPM E.3, SR1.5 SPM D.4.5} (Figure 4.3c)\nRegions and people with considerable development constraints \nhave high vulnerability to climatic hazards. Adaptation \noutcomes for the most vulnerable within and across countries \nand regions are enhanced through approaches focusing on \nequity, inclusivity, and rights-based approaches, including 3.3 to \n3.6 billion people living in contexts that are highly vulnerable \nto climate change (high con\ufb01dence).\n\nDocument 241: Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence). Equity remains a \ncentral element in the UN climate regime, notwithstanding shifts \nin differentiation between states over time and challenges in \nassessing fair shares. Ambitious mitigation pathways imply large and \nsometimes disruptive changes in economic structure, with signi\ufb01cant \ndistributional consequences, within and between countries, including \nshifting of income and employment during the transition from high to \nlow emissions activities (high con\ufb01dence). While some jobs may be lost, \nlow-emissions development can also open up opportunities to enhance \nskills and create jobs (high con\ufb01dence). Broadening equitable access \nto \ufb01nance, technologies and governance that facilitate mitigation, and \nconsideration of climate justice can help equitable sharing of bene\ufb01ts \n4.4 Equity and Inclusion in Climate Change Action\n\nDocument 240: Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence). {WGII SPM B.2, WGII SPM B.2.4, \nWGII SPM B.3.2, WGII SPM B.3.3, WGII SPM C.1, WGII SPM C.1.2, \nWGII SPM C.2.9}\nMeaningful participation and inclusive planning, informed by \ncultural values, Indigenous Knowledge, local knowledge, and \nscienti\ufb01c knowledge can help address adaptation gaps and \navoid maladaptation (high con\ufb01dence). Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence).\n\nDocument 244: Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence). System \ntransitions151 consistent with pathways that limit warming to 1.5\u00b0C \n(>50%) with no or limited overshoot are more rapid and pronounced \nin the near-term than in those that limit warming to 2\u00b0C (>67%) \n(high con\ufb01dence). Such a systemic change is unprecedented in terms \nof scale, but not necessarily in terms of speed (medium con\ufb01dence). \nThe system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":238,"situational_context":"A policymaker is seeking information on the social aspects of climate change adaptation and mitigation to inform equitable policy development.","topic":"Climate Change Action"}}
{"id":"5718faa5-e9d3-48a5-b119-e7ef1609488b","question":"As a policy advisor preparing for an environmental summit, I need to understand the urgency of climate action. Can you tell me, under the very low GHG emission scenarios, what is the likelihood that global warming will reach 1.5\u00b0C between 2021 and 2040?","reference_answer":"Global warming is more likely than not to reach 1.5\u00b0C between 2021 and 2040 even under the very low GHG emission scenarios (SSP1-1.9).","reference_context":"Document 203: 92\nSection 4\nSection 1\nSection 4\nSection 4 : Near-Term Responses in a Changing Climate\n4.1 The Timing and Urgency of Climate Action\nThe magnitude and rate of climate change and associated risks \ndepend strongly on near-term mitigation and adaptation actions \n(very high con\ufb01dence). Global warming is more likely than not to reach \n1.5\u00b0C between 2021 and 2040 even under the very low GHG emission \nscenarios (SSP1-1.9), and likely or very likely to exceed 1.5\u00b0C under \nhigher emissions scenarios141. Many adaptation options have medium \nor high feasibility up to 1.5\u00b0C (medium to high con\ufb01dence, depending \non option), but hard limits to adaptation have already been reached \nin some ecosystems and the effectiveness of adaptation to reduce \nclimate risk will decrease with increasing warming (high con\ufb01dence). \nSocietal choices and actions implemented in this decade determine the \nextent to which medium- and long-term pathways will deliver higher or \nlower climate resilient development (high con\ufb01dence). Climate resilient \ndevelopment prospects are increasingly limited if current greenhouse \ngas emissions do not rapidly decline, especially if 1.5\u00b0C global warming \nis exceeded in the near term (high con\ufb01dence). Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}.\n\nDocument 204: Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}. (Cross-Section \nBox.2, Figure 2.1, Figure 2.3)\n141 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). The best estimates [and very likely ranges] of global warming for the different scenarios in the \nnear term are: 1.5 [1.2 to 1.7]\u00b0C (SSP1-1.9); 1.5 [1.2 to 1.8]\u00b0C (SSP1-2.6); 1.5 [1.2 to 1.8]\u00b0C (SSP2-4.5); 1.5 [1.2 to 1.8]\u00b0C (SSP3-7.0); and 1.6[1.3 to 1.9]\u00b0C (SSP5-8.5).\n\nDocument 214: Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4). (high con\ufb01dence) {WGI SPM B.1, WGI SPM B.1.3, WGI \nSPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM \nC.2, WGII SPM C.3.1, WGII Figure SPM.4b; SROCC SPM C.3.4, SROCC \nFigure 3.4, SROCC Figure SPM.5}\nNear-term actions that limit global warming to close to 1.5\u00b0C \nwould substantially reduce projected losses and damages related \nto climate change in human systems and ecosystems, compared \nto higher warming levels, but cannot eliminate them all (very \nhigh con\ufb01dence). The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).\n\nDocument 215: The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).  Comprehensive, effective, and innovative \nresponses integrating adaptation and mitigation can harness synergies \nand reduce trade-offs between adaptation and mitigation, as well as in \nmeeting requirements for \ufb01nancing (very high con\ufb01dence) (see Section \n4.5, 4.6, 4.8 and 4.9). {WGII SPM B.3, WGII SPM B.4, WGII SPM B.6.2, \nWGII SPM C.2, WGII SPM C.3, WGII SPM D.1, WGII SPM D.4.3, WGII SPM D.5, \nWG II TS D.1.4, WG II TS.D.5, WGII TS D.7.5; WGIII SPM B.6.3,WGIII SPM B.6.4, \nWGIII SPM C.9, WGIII SPM D.2, WGIII SPM E.13; SR1.5 SPM C.2.7, \nSR1.5 D.1.3, SR1.5 D.5.2}\nMitigation actions will have other sustainable development \nco-bene\ufb01ts (high con\ufb01dence). Mitigation will improve air quality and \nhuman health in the near term notably because many air pollutants are \n148 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":203,"situational_context":"A policy advisor is seeking information on the urgency of climate action to prepare a briefing for an upcoming environmental summit.","topic":"Others"}}
{"id":"f4b9dfa7-1a9c-4af8-9bb5-08f02869563d","question":"As a researcher looking into the difficulties of crafting accurate climate projections, I'm curious why the IPCC report indicates that the development of synthetic diagrams was limited for regions like Small Islands, Asia, and Central and South America?","reference_answer":"The development was limited due to the paucity of adequately downscaled climate projections, uncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries within a region, and the resulting few numbers of impact and risk projections for different warming levels.","reference_context":"Document 144: The development of synthetic diagrams for Small \nIslands, Asia and Central and South America was limited due to the paucity of adequately downscaled climate projections, with \nuncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries within a region, and \nthe resulting few numbers of impact and risk projections for different warming levels.\nThe risks listed are of at least medium con\ufb01dence level:","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":144,"situational_context":"A researcher is delving into the challenges of creating accurate climate projections for diverse regions highlighted in the IPCC report.","topic":"Climate Change Risks"}}
{"id":"ab83090b-daa7-4229-8f73-2276b061b957","question":"As a concerned citizen, I'm eager to understand how the pace of climate change might be affected by prompt mitigation efforts. Can you tell me what the IPCC report says about the projected consequences of delayed mitigation actions on global warming and our adaptation options?","reference_answer":"Delayed mitigation action will further increase global warming which will decrease the effectiveness of many adaptation options, including Ecosystem-based Adaptation and many water-related options, as well as increasing mitigation feasibility risks, such as for options based on ecosystems.","reference_context":"Document 215: The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).  Comprehensive, effective, and innovative \nresponses integrating adaptation and mitigation can harness synergies \nand reduce trade-offs between adaptation and mitigation, as well as in \nmeeting requirements for \ufb01nancing (very high con\ufb01dence) (see Section \n4.5, 4.6, 4.8 and 4.9). {WGII SPM B.3, WGII SPM B.4, WGII SPM B.6.2, \nWGII SPM C.2, WGII SPM C.3, WGII SPM D.1, WGII SPM D.4.3, WGII SPM D.5, \nWG II TS D.1.4, WG II TS.D.5, WGII TS D.7.5; WGIII SPM B.6.3,WGIII SPM B.6.4, \nWGIII SPM C.9, WGIII SPM D.2, WGIII SPM E.13; SR1.5 SPM C.2.7, \nSR1.5 D.1.3, SR1.5 D.5.2}\nMitigation actions will have other sustainable development \nco-bene\ufb01ts (high con\ufb01dence). Mitigation will improve air quality and \nhuman health in the near term notably because many air pollutants are \n148 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply.\n\nDocument 214: Deep, rapid, and sustained mitigation actions would reduce future adaptation costs \nand losses and damages, enhance sustainable development co-bene\ufb01ts, avoid locking-in emission sources, \nand reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front \ninvestments and disruptive changes, which can be moderated by a range of enabling conditions and removal or \nreduction of barriers to feasibility. (high con\ufb01dence)\nAccelerated implementation of adaptation responses will bring \nbene\ufb01ts to human well-being (high con\ufb01dence) (Section 4.3). \u00a0As \nadaptation options often have long implementation times, long-term \nplanning and accelerated implementation, particularly in this decade, is \nimportant to close adaptation gaps, recognising that constraints remain \nfor some regions. The bene\ufb01ts to vulnerable populations would be high \n(see Section 4.4). (high con\ufb01dence) {WGI SPM B.1, WGI SPM B.1.3, WGI \nSPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM \nC.2, WGII SPM C.3.1, WGII Figure SPM.4b; SROCC SPM C.3.4, SROCC \nFigure 3.4, SROCC Figure SPM.5}\nNear-term actions that limit global warming to close to 1.5\u00b0C \nwould substantially reduce projected losses and damages related \nto climate change in human systems and ecosystems, compared \nto higher warming levels, but cannot eliminate them all (very \nhigh con\ufb01dence). The magnitude and rate of climate change and \nassociated risks depend strongly on near-term mitigation and adaptation \nactions, and projected adverse impacts and related losses and damages \nescalate with every increment of global warming (very high con\ufb01dence). \nDelayed mitigation action will further increase global warming which \nwill decrease the effectiveness of many adaptation options, including \nEcosystem-based Adaptation and many water-related options, as well \nas increasing mitigation feasibility risks, such as for options based on \necosystems (high con\ufb01dence).\n\nDocument 246: The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change. (high con\ufb01dence) (Figure 4.4). {WGIII SPM C.10}\n4.5 Near-Term Mitigation and Adaptation Actions\nRapid and far-reaching transitions across all sectors and systems are necessary to achieve deep and sustained \nemissions reductions and secure a liveable and sustainable future for all. These system transitions involve a \nsigni\ufb01cant upscaling of a wide portfolio of mitigation and adaptation options. Feasible, effective and low-cost \noptions for mitigation and adaptation are already available, with differences across systems and regions. (high \ncon\ufb01dence)\n\nDocument 216: Mitigation will improve air quality and \nhuman health in the near term notably because many air pollutants are \n148 In this context, \u2018unabated fossil fuels\u2019 refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout the life \ncycle; for example, capturing 90% or more CO2 from power plants, or 50 to 80% of fugitive methane emissions from energy supply. {WGIII SPM footnote 54}\nco-emitted by GHG emitting sectors and because methane emissions \nleads to surface ozone formation (high con\ufb01dence). The bene\ufb01ts from \nair quality improvement include prevention of air pollution-related \npremature deaths, chronic diseases and damages to ecosystems \nand crops. The economic bene\ufb01ts for human health from air quality \nimprovement arising from mitigation action can be of the same order \nof magnitude as mitigation costs, and potentially even larger (medium \ncon\ufb01dence). As methane has a short lifetime but is a potent GHG, \nstrong, rapid and sustained reductions in methane emissions can limit \nnear-term warming and improve air quality by reducing global surface \nozone (high con\ufb01dence). {WGI SPM D.1.7, WGI SPM D.2.2, WGI 6.7, \nWGI TS Box TS.7, WGI 6 Box 6.2, WGI Figure 6.3, WGI Figure 6.16, \nWGI Figure 6.17; WGII TS.D.8.3, WGII Cross-Chapter Box HEALTH, \nWGII 5 ES, WGII 7 ES; WGII 7.3.1.2; WGIII Figure SPM.8, WGIII SPM \nC.2.3, WGIII SPM C.4.2, WGIII TS.4.2}\nChallenges from delayed adaptation and mitigation actions \ninclude the risk of cost escalation, lock-in of infrastructure, \nstranded assets, and reduced feasibility and effectiveness \nof adaptation and mitigation options (high con\ufb01dence). The \ncontinued installation of unabated fossil fuel148 infrastructure \nwill \u2018lock-in\u2019 GHG emissions (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":215,"situational_context":"A concerned citizen is seeking information on how the rate of climate change could be influenced by immediate mitigation and adaptation efforts.","topic":"Climate Change Action"}}
{"id":"0dcb800f-d747-4384-acc8-36ab4dacc221","question":"As a policy advisor, I'm looking to understand the implications of greenhouse gas emissions scenarios on global warming limits to inform our upcoming environmental legislation. Could you tell me what the projected global warming outcomes are for the modelled pathways based on policies implemented until the end of 2020?","reference_answer":"The projected global warming outcomes of the modelled pathways based on policies implemented until the end of 2020 are in line with the trend from implemented policies, which are extended with comparable ambition levels beyond 2030.","reference_context":"Document 85: Panel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n \n- Limit to 2\u00b0C (>67%) or return warming to 1.5\u00b0C (>50%) after a high overshoot, NDCs until 2030: Pathways with GHG emissions until 2030 associated with the \nimplementation of NDCs announced prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2\u00b0C (C3b, WGIII Table SPM.2) or to return \nwarming to 1.5\u00b0C with a probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, WGIII Table SPM.2). \n \n- Limit to 2\u00b0C (>67%) with immediate action: Pathways that limit warming to 2\u00b0C (>67%) with immediate action after 2020 (C3a, WGIII Table SPM.2). \n \n- Limit to 1.5\u00b0C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5\u00b0C with no or limited overshoot (C1, WGIII Table SPM.2 C1). \nAll these pathways assume immediate action after 2020. Past GHG emissions for 2010-2015 used to project global warming outcomes of the modelled pathways are shown by a \nblack line. Panel b shows a snapshot of the GHG emission ranges of the modelled pathways in 2030 and projected emissions outcomes from near-term policy assessments in 2030 \nfrom WGIII Chapter 4.2 (Tables 4.2 and 4.3; median and full range). GHG emissions are CO2-equivalent using GWP100 from AR6 WGI. {WGIII Figure SPM.4, WGIII 3.5, 4.2, Table 4.2, \nTable 4.3, Cross-Chapter Box 4 in Chapter 4} (Table 3.1, Cross-Section Box.2)\n\nDocument 84: 59\nCurrent Status and Trends\nSection 2\na) Global GHG emissions\nb) 2030\n10\n20\n30\n0\n40\n50\n60\n70\n10\n20\n30\n0\n40\n50\n60\n70\nGHG emissions (GtCO2-eq\/yr)\n2020\n2025\n2015\n2010\n2030\n2035\n2040\n2045\n2050\nLimit warming to 2\u00baC (>67%)\nor 1.5 (>50%) after high\novershoot with NDCs until 2030\nTrend from implemented policies\n2019\nLimit warming to\n1.5\u00baC (>50%) with \nno or limited overshoot\nLimit warming \nto 2\u00baC (>67%)\nto be on-track to limit \nwarming to 1.5\u00b0C, \nwe need much more \nreduction by 2030\n-4%\n+5%\n-26%\n-43%\nProjected global GHG emissions from NDCs announced prior to \nCOP26 would make it likely that warming will exceed 1.5\u00b0C and \nalso make it harder after 2030 to limit warming to below 2\u00b0C\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nFigure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), and projected emission outcomes from near-term policy assessments for 2030 (Panel b). \nPanel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n\nDocument 102: The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8). Methods to project global warming associated with the \nmodelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII \nTable 3.1} (Table 3.1, Cross-Section Box.2 Figure 1)\n102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019.\n\nDocument 182: Top row: GHG, CO2 and CH4 emissions over time (in \nGtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour \n(blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows \npathways that limit warming to 2\u00b0C (>67%) (C3). Bottom row: Panel (c) shows median (vertical line), likely (bar) and very likely (thin lines) timing of reaching net zero GHG \nand CO2 emissions for global modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) (left) or 2\u00b0C (>67%) (C3) (right). {WGIII Figure SPM.5}\n3.3.3 Sectoral Contributions to Mitigation\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) or \nlower by 2100 involve rapid and deep and in most cases immediate \nGHG emissions reductions in all sectors (see also 4.1, 4.5). Reductions \nin GHG emissions in industry, transport, buildings, and urban areas \ncan be achieved through a combination of energy ef\ufb01ciency and \nconservation and a transition to low-GHG technologies and energy \ncarriers (see also 4.5, Figure 4.4). Socio-cultural options and behavioural \nchange can reduce global GHG emissions of end-use sectors, with most \nof the potential in developed countries, if combined with improved \n136 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage is available. When CO2 is captured directly from the \natmosphere (DACCS), or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO2 capture and subsurface injection is a mature technology for \ngas processing and enhanced oil recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production, where it \nis a critical mitigation option.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":85,"situational_context":"A policy advisor is seeking to understand the implications of various greenhouse gas emissions scenarios on global warming limits to inform upcoming environmental legislation.","topic":"Climate Change Scenarios"}}
{"id":"f14637cc-be44-46c5-a402-6950dd9322e1","question":"As a policymaker interested in the intersection of climate change adaptation and social equity, I'm drafting some legislative proposals. Could you tell me what is necessary to achieve deep emissions reductions and ensure a liveable and sustainable future for all, considering these broad societal aspects?","reference_answer":"Rapid and far-reaching transitions across all sectors and systems are necessary to achieve deep emissions reductions and secure a liveable and sustainable future for all.","reference_context":"Document 238: Adaptation responses are immediately needed to reduce rising climate risks, especially for the most vulnerable. \nEquity, inclusion and just transitions are key to progress on adaptation and deeper societal ambitions for \naccelerated mitigation. (high con\ufb01dence)\nAdaptation and mitigation actions, across scales, sectors and \nregions, that prioritise equity, climate justice, rights-based \napproaches, social justice and inclusivity, lead to more \nsustainable outcomes, reduce trade-offs, support transformative \nchange and advance climate resilient development (high \ncon\ufb01dence). Redistributive policies across sectors and regions that \nshield the poor and vulnerable, social safety nets, equity, inclusion \nand just transitions, at all scales can enable deeper societal ambitions \nand resolve trade-offs with sustainable development goals.(SDGs), \nparticularly education, hunger, poverty, gender and energy access (high \ncon\ufb01dence). Mitigation efforts embedded within the wider development \ncontext can increase the pace, depth and breadth of emission reductions \n(medium con\ufb01dence). Equity, inclusion and just transitions at all \nscales enable deeper societal ambitions for accelerated mitigation, \nand climate action more broadly (high con\ufb01dence). The complexity in \nrisk of rising food prices, reduced household incomes, and health and \nclimate-related malnutrition (particularly maternal malnutrition and \nchild undernutrition) and mortality increases with little or low levels \nof adaptation (high con\ufb01dence). {WGII SPM B.5.1, WGII SPM C.2.9, \nWGII SPM D.2.1, WGII TS Box TS.4; WGIII SPM D.3, WGIII SPM D.3.3, \nWGIII SPM WGIII SPM E.3, SR1.5 SPM D.4.5} (Figure 4.3c)\nRegions and people with considerable development constraints \nhave high vulnerability to climatic hazards. Adaptation \noutcomes for the most vulnerable within and across countries \nand regions are enhanced through approaches focusing on \nequity, inclusivity, and rights-based approaches, including 3.3 to \n3.6 billion people living in contexts that are highly vulnerable \nto climate change (high con\ufb01dence).\n\nDocument 241: Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence). Equity remains a \ncentral element in the UN climate regime, notwithstanding shifts \nin differentiation between states over time and challenges in \nassessing fair shares. Ambitious mitigation pathways imply large and \nsometimes disruptive changes in economic structure, with signi\ufb01cant \ndistributional consequences, within and between countries, including \nshifting of income and employment during the transition from high to \nlow emissions activities (high con\ufb01dence). While some jobs may be lost, \nlow-emissions development can also open up opportunities to enhance \nskills and create jobs (high con\ufb01dence). Broadening equitable access \nto \ufb01nance, technologies and governance that facilitate mitigation, and \nconsideration of climate justice can help equitable sharing of bene\ufb01ts \n4.4 Equity and Inclusion in Climate Change Action\n\nDocument 240: Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence). {WGII SPM B.2, WGII SPM B.2.4, \nWGII SPM B.3.2, WGII SPM B.3.3, WGII SPM C.1, WGII SPM C.1.2, \nWGII SPM C.2.9}\nMeaningful participation and inclusive planning, informed by \ncultural values, Indigenous Knowledge, local knowledge, and \nscienti\ufb01c knowledge can help address adaptation gaps and \navoid maladaptation (high con\ufb01dence). Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence).\n\nDocument 244: Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence). System \ntransitions151 consistent with pathways that limit warming to 1.5\u00b0C \n(>50%) with no or limited overshoot are more rapid and pronounced \nin the near-term than in those that limit warming to 2\u00b0C (>67%) \n(high con\ufb01dence). Such a systemic change is unprecedented in terms \nof scale, but not necessarily in terms of speed (medium con\ufb01dence). \nThe system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":238,"situational_context":"A policymaker is seeking to understand the intersection of climate change adaptation and social equity to inform upcoming legislative proposals.","topic":"Climate Change Action"}}
{"id":"fbce86a9-23b9-47ec-926f-4aa06a8d9680","question":"As a researcher looking into the latest IPCC report, could you tell me what the probability is of peak global warming remaining under 1.5\u00b0C according to the data they've provided?","reference_answer":"38% [33-58%]","reference_context":"Document 169: 84\nSection 3\nSection 1\nSection 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n2030 \n43 \n[34-60]\n41 \n[31-59]\n48 \n[35-61]\n23 \n[0-44]\n21 \n[1-42]\n27 \n[13-45]\n5 \n[0-14]\n10  \n[0-27]\n2040\n \n \n \n \n \n2050 \n84 \n[73-98]\n85 \n[72-100]\n84 \n[76-93]\n75 \n[62-91]\n64 \n[53-77]\n63 \n[52-76]\n68 \n[56-83]\n49  \n[35-65]\n29\n[11-48]\n5\n[-2 to 18]\nNet zero \nCO2  \n(% net zero \npathways) \n \n2050-2055 (100%) \n[2035-2070]\n2055-2060 \n(100%) \n[2045-2070]\n2070-2075 \n(93%) \n[2055-.]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.\n\nDocument 170: ]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.]\n \n2020 to \nnet zero \nCO2  \n510 \n[330-710]\n550 \n[340-760]\n460 \n[320-590]\n720 \n[530-930]\n890 \n[640-1160]\n860 \n[640-1180]\n910 \n[720-1150]\n1210\n[970-1490]\n1780\n[1400-2360]\n2020\u2013\n2100 \n320 \n[-210-570]\n160 \n[-220-620]\n360 \n[10-540]\n400 \n[-90-620]\n800 \n[510-1140]\n790 \n[480-1150]\n800 \n[560-1050]\n1160 \n[700-1490]\n \nat peak \nwarming\n \n1.6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":169,"situational_context":"A researcher is analyzing the probability of peak global warming staying below 1.5\u00b0C as outlined in the latest IPCC report.","topic":"Climate Change Scenarios"}}
{"id":"242c809d-99c9-4bc3-a011-07d1db5bdbf0","question":"As an environmental science student preparing for a university presentation on the projected impacts of climate change on various ecosystems, could you tell me what the IPCC report says about the expected effects on coral reefs if global warming reaches 1.5\u00b0C?","reference_answer":"Coral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of global warming.","reference_context":"Document 140: 76\nSection 3\nSection 1\nSection 3\n0\n1\n1.5\n2\n3\n4\n0\n1\n1.5\n2\n3\n4\n\u00b0C\n\u00b0C\n0\n1\n1.5\n2\n3\n4\n0\n1\n1.5\n2\n3\n4\n\u00b0C\n\u00b0C\nEurope -Risks to people, economies and infrastructures due to coastal and inland \ufb02ooding\n-Stress and mortality to people due to increasing temperatures and heat extremes\n-Marine and terrestrial ecosystems disruptions\n-Water scarcity to multiple interconnected sectors\n-Losses in crop production, due to compound heat and dry conditions, and extreme \nweather\nSmall\nIslands\n-Loss of terrestrial, marine and coastal biodiversity and ecosystem services\n-Loss of lives and assets, risk to food security and economic disruption due to \ndestruction of settlements and infrastructure\n-Economic decline and livelihood failure of \ufb01sheries, agriculture, tourism and from \nbiodiversity loss from traditional agroecosystems \n-Reduced habitability of reef and non-reef islands leading to increased displacement\n-Risk to water security in almost every small island \nAfrica -Species extinction and reduction or irreversible loss of ecosystems and their services, \nincluding freshwater, land and ocean ecosystems\n-Risk to food security, risk of malnutrition (micronutrient de\ufb01ciency), and loss of \nlivelihood due to reduced food production from crops, livestock and \ufb01sheries\n-Risks to marine ecosystem health and to livelihoods in coastal communities\n-Increased human mortality and morbidity due to increased heat and infectious diseases \n(including vector-borne and diarrhoeal diseases)\n-Reduced economic output and growth,\n\nDocument 141: risk to food security and economic disruption due to \ndestruction of settlements and infrastructure\n-Economic decline and livelihood failure of \ufb01sheries, agriculture, tourism and from \nbiodiversity loss from traditional agroecosystems \n-Reduced habitability of reef and non-reef islands leading to increased displacement\n-Risk to water security in almost every small island \nAfrica -Species extinction and reduction or irreversible loss of ecosystems and their services, \nincluding freshwater, land and ocean ecosystems\n-Risk to food security, risk of malnutrition (micronutrient de\ufb01ciency), and loss of \nlivelihood due to reduced food production from crops, livestock and \ufb01sheries\n-Risks to marine ecosystem health and to livelihoods in coastal communities\n-Increased human mortality and morbidity due to increased heat and infectious diseases \n(including vector-borne and diarrhoeal diseases)\n-Reduced economic output and growth, and increased inequality and poverty rates \n-Increased risk to water and energy security due to drought and heat\nAus-\ntralasia\n-Degradation of tropical shallow coral reefs and associated biodiversity and \necosystem service values\n-Loss of human and natural systems in low-lying coastal areas due to sea level rise\n-Impact on livelihoods and incomes due to decline in agricultural production\n-Increase in heat-related mortality and morbidity for people and wildlife\n-Loss of alpine biodiversity in Australia due to less snow\nAsia -Urban infrastructure damage and impacts on human well-being and health due to \n\ufb02ooding, especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics,\n\nDocument 142: especially in coastal cities and settlements\n-Biodiversity loss and habitat shifts as well as associated disruptions in dependent \nhuman systems across freshwater, land, and ocean ecosystems\n-More frequent, extensive coral bleaching and subsequent coral mortality induced by \nocean warming and acidi\ufb01cation, sea level rise, marine heat waves and resource \nextraction\n-Decline in coastal \ufb01shery resources due to sea level rise, decrease in precipitation in \nsome parts and increase in temperature\n-Risk to food and water security due to increased temperature extremes, rainfall \nvariability and drought\nCentral\nand\nSouth\nAmerica\n-Risk to water security\n-Severe health effects due to increasing epidemics, in particular vector-borne diseases\n-Coral reef ecosystems degradation due to coral bleaching\n-Risk to food security due to frequent\/extreme droughts\n-Damages to life and infrastructure due to \ufb02oods, landslides, sea level rise, storm \nsurges and coastal erosion \nNorth \nAmerica\n-Climate-sensitive mental health outcomes, human mortality and morbidity due to \nincreasing average temperature, weather and climate extremes, and compound \nclimate hazards\n-Risk of degradation of marine, coastal and terrestrial ecosystems, including loss of \nbiodiversity, function, and protective services \n-Risk to freshwater resources with consequences for ecosystems, reduced surface water \navailability for irrigated agriculture, other human uses, and degraded water quality \n-Risk to food and nutritional security through changes in agriculture, livestock, hunting, \n\ufb01sheries, and aquaculture productivity and access\n-Risks to well-being, livelihoods and economic activities from cascading and \ncompounding climate hazards, including risks to coastal cities, settlements and \ninfrastructure from sea level rise\nDelayed\nimpacts of\nsea level\nrise in the\nMediterranean\nFood\nproduction\nfrom crops,\n\ufb01sheries and\nlivestock\nin Africa\nMortality and\nmorbidity\nfrom heat and\ninfectious\ndisease\nin Africa\nBiodiversity\nand\necosystems\nin Africa\nHealth and\nwellbeing\nin the\nMediterranean\nWater scarcity\nto people in\nsoutheastern\nEurope\nCoastal\n\ufb02ooding to\npeople\nand\ninfrastructures\nin Europe\nHeat stress,\n\nDocument 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":140,"situational_context":"A concerned environmental science student is researching the projected impacts of climate change on different regions around the world for a university presentation.","topic":"Climate Change Impacts"}}
{"id":"168b22ff-f0be-4577-876f-5460ea122778","question":"As an environmental policy advisor, I'm looking for detailed insights into the effectiveness of adaptation strategies. Could you tell me about the projected impact on tropical marine species and global land area biome shifts if global warming reaches 4\u00b0C?","reference_answer":"Beyond 4\u00b0C of warming, projected impacts include local extinction of ~50% of tropical marine species and biome shifts across 35% of global land area.","reference_context":"Document 154: Globally, adaptation options related \nto agroforestry and forestry have a sharp decline in effectiveness at 3\u00b0C, \nwith a substantial increase in residual risk (medium con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, \nWGII Figure TS.6 Panel (e), 4.7.2} \nWith increasing global warming, more limits to adaptation will be \nreached and losses and damages, strongly concentrated among the \npoorest vulnerable populations, will increase (high con\ufb01dence). \nAlready below 1.5\u00b0C, autonomous and evolutionary adaptation \nresponses by terrestrial and aquatic ecosystems will increasingly \nface hard limits (high con\ufb01dence) (Section 2.1.2). Above 1.5\u00b0C, some \necosystem-based adaptation measures will lose their effectiveness \nin providing bene\ufb01ts to people as these ecosystems will reach hard \nadaptation limits (high con\ufb01dence). Adaptation to address the risks of \nheat stress, heat mortality and reduced capacities for outdoor work \nfor humans face soft and hard limits across regions that become \nsigni\ufb01cantly more severe at 1.5\u00b0C, and are particularly relevant for \nregions with warm climates (high con\ufb01dence). Above 1.5\u00b0C global \nwarming level, limited freshwater resources pose potential hard limits \nfor small islands and for regions dependent on glacier and snow melt \n124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound \ufb02ooding. {WGI SPM Footnote 18}\n125 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation responses can be incorporated in climate \nimpact models, and projections of future adaptation depend on currently available technologies or approaches. {WGII 4.7.2}\n(medium confidence). By 2\u00b0C, soft limits are projected for multiple \nstaple crops, particularly in tropical regions (high con\ufb01dence).\n\nDocument 153: At higher levels \nof warming, losses and damages will increase, and additional human and natural systems will reach adaptation \nlimits. Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation. Maladaptation \ncan create lock-ins of vulnerability, exposure and risks but can be avoided by long-term planning and the \nimplementation of adaptation actions that are \ufb02exible, multi-sectoral and inclusive. (high con\ufb01dence)\nThe effectiveness of adaptation to reduce climate risk is documented \nfor speci\ufb01c contexts, sectors and regions and will decrease with \nincreasing warming (high con\ufb01dence)125. For example, common \nadaptation responses in agriculture \u2013 adopting improved cultivars and \nagronomic practices, and changes in cropping patterns and crop \nsystems \u2013 will become less effective from 2\u00b0C to higher levels of \nwarming (high confidence). The effectiveness of most water-related \nadaptation options to reduce projected risks declines with increasing \nwarming (high confidence). Adaptations for hydropower and \nthermo-electric power generation are effective in most regions up to \n1.5\u00b0C to 2\u00b0C, with decreasing effectiveness at higher levels of warming \n(medium con\ufb01dence). Ecosystem-based Adaptation is vulnerable to \nclimate change impacts, with effectiveness declining with increasing \nglobal warming (high con\ufb01dence). Globally, adaptation options related \nto agroforestry and forestry have a sharp decline in effectiveness at 3\u00b0C, \nwith a substantial increase in residual risk (medium con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, \nWGII Figure TS.6 Panel (e), 4.7.2} \nWith increasing global warming, more limits to adaptation will be \nreached and losses and damages, strongly concentrated among the \npoorest vulnerable populations, will increase (high con\ufb01dence). \nAlready below 1.5\u00b0C, autonomous and evolutionary adaptation \nresponses by terrestrial and aquatic ecosystems will increasingly \nface hard limits (high con\ufb01dence) (Section 2.1.2).\n\nDocument 155: Above 1.5\u00b0C global \nwarming level, limited freshwater resources pose potential hard limits \nfor small islands and for regions dependent on glacier and snow melt \n124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound \ufb02ooding. {WGI SPM Footnote 18}\n125 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation responses can be incorporated in climate \nimpact models, and projections of future adaptation depend on currently available technologies or approaches. {WGII 4.7.2}\n(medium confidence). By 2\u00b0C, soft limits are projected for multiple \nstaple crops, particularly in tropical regions (high con\ufb01dence). By 3\u00b0C, \nsoft limits are projected for some water management measures for \nmany regions, with hard limits projected for parts of Europe (medium \ncon\ufb01dence). {WGII SPM C.3, WGII SPM C.3.3, WGII SPM C.3.4, WGII SPM C.3.5, \nWGII TS.D.2.2, WGII TS.D.2.3; SR1.5 SPM B.6; SROCC SPM C.1}\nIntegrated, cross-cutting multi-sectoral solutions increase the \neffectiveness of adaptation. For example, inclusive, integrated \nand long-term planning at local, municipal, sub-national and national \nscales, together with effective regulation and monitoring systems \nand \ufb01nancial and technological resources and capabilities foster \nurban and rural system transition. There are a range of cross-cutting \nadaptation options, such as disaster risk management, early warning \nsystems, climate services and risk spreading and sharing that have \nbroad applicability across sectors and provide greater bene\ufb01ts to other \nadaptation options when combined. Transitioning from incremental to \ntransformational adaptation, and addressing a range of constraints, \nprimarily in the \ufb01nancial, governance, institutional and policy domains, \ncan help overcome soft adaptation limits. However, adaptation does \nnot prevent all losses and damages, even with effective adaptation and \nbefore reaching soft and hard limits.\n\nDocument 128: For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence). {WGII SPM B.4.1, WGII SPM B.4.2, \nWGII Figure SPM.3, WGII TS Appendix AII, WGII Appendix I Global to \nRegional Atlas Figure AI.46} (Figure 3.2, Figure 3.3)\nGlobal warming of 4\u00b0C and above is projected to lead to far-reaching \nimpacts on natural and human systems (high con\ufb01dence). Beyond \n4\u00b0C of warming, projected impacts on natural systems include local \nextinction of ~50% of tropical marine species (medium con\ufb01dence) \nand biome shifts across 35% of global land area (medium con\ufb01dence). \nAt this level of warming, approximately 10% of the global land area \nis projected to face both increasing high and decreasing low extreme \nstream\ufb02ow, affecting, without additional adaptation, over 2.1 billion people \n(medium con\ufb01dence) and about 4 billion people are projected to \nexperience water scarcity (medium con\ufb01dence). At 4\u00b0C of warming, the \nglobal burned area is projected to increase by 50 to 70% and the \nfire frequency by ~30% compared to today (medium confidence). \n{WGII SPM B.4.1, WGII SPM B.4.2, WGII TS.C.1.2, WGII TS.C.2.3, \nWGII TS.C.4.1, WGII TS.C.4.4} (Figure 3.2, Figure 3.3)","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":154,"situational_context":"An environmental policy advisor is seeking detailed insights into the effectiveness of adaptation strategies in the face of escalating global warming.","topic":"Others"}}
{"id":"52666a64-1e62-4b10-b1ff-4c78041fe802","question":"As an environmental policy maker looking to inform our future climate strategies, could you tell me by which year the very low and low GHG emissions scenarios SSP1-1.9 and SSP1-2.6 project CO2 emissions to decline to net zero?","reference_answer":"The very low GHG emissions scenario SSP1-1.9 projects CO2 emissions to decline to net zero around 2050, and the low GHG emissions scenario SSP1-2.6 projects CO2 emissions to decline to net zero around 2070.","reference_context":"Document 173: The five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.8]\n[1.6-1.8]\n[1.6-1.8]\n[1.7-2.0]\n[1.9-2.5]\n[1.1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.\n\nDocument 102: The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8). Methods to project global warming associated with the \nmodelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII \nTable 3.1} (Table 3.1, Cross-Section Box.2 Figure 1)\n102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019.\n\nDocument 172: with the 5th-95th percentile \ninterval in square brackets. \nPercentage of net zero \npathways is denoted in \nround brackets. \nThree dots (\u2026) denotes net \nzero not reached for that \npercentile.\nMedian cumulative net CO2 \nemissions across the \nprojected scenarios in this \ncategory until reaching \nnet-zero or until 2100, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected temperature \nchange of pathways in this \ncategory (50% probability \nacross the range of climate \nuncertainties), relative to \n1850-1900, at peak \nwarming and in 2100, for \nthe median value across the \nscenarios and the 5th-95th \npercentile interval in square \nbrackets.\nMedian likelihood that the \nprojected pathways in this \ncategory stay below a given \nglobal warming level, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected median GHG \nemissions reductions of \npathways in the year across \nthe scenarios compared to \nmodelled 2019, with the \n5th-95th percentile in \nbrackets. Negative numbers \nindicate increase in \nemissions compared to 2019\nModelled global emissions \npathways categorised by \nprojected global warming \nlevels (GWL). Detailed \nlikelihood definitions are \nprovided in SPM Box1.  \nThe five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.\n\nDocument 174: 1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.5\u00b0C \n(>50%) \nafter a \nhigh \novershoot\nlimit \nwarming \nto 2\u00b0C \n(>67%) \n\u2026\nwith \naction \nstarting \nin 2020 \n\u2026\nNDCs \nuntil \n2030 \nlimit\nwarming\nto 2\u00b0C\n(>50%)\nlimit\nwarming\nto 2.5\u00b0C\n(>50%)\nlimit\nwarming\nto 3\u00b0C\n(>50%)\n[212]\nCategory \n(2) \n[# pathways]\nC1\n[97]\nC1a\n[50]\nC1b\n[47]\nC2\n[133]\nC3\n[311]\nC3a \n[204]\nC3b\n[97]\nC4\n[159]\nC5\nC6\n[97]\nTable 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":173,"situational_context":"An environmental policy maker is seeking detailed projections on emissions pathways and their impact on global warming levels to inform future climate strategies.","topic":"Climate Change Scenarios"}}
{"id":"c91e4bed-1d2c-4906-aef9-4efd8bfc705e","question":"As a researcher analyzing the impact of human activities on global warming and the effectiveness of land and ocean sinks in absorbing CO2 emissions, I'm curious to know, what is the likely range of total human-caused global surface temperature increase from 1850\u20131900 to 2010\u20132019?","reference_answer":"The likely range of total human-caused global surface temperature increase from 1850\u20131900 to 2010\u20132019 is 0.8\u00b0C to 1.3\u00b0C.","reference_context":"Document 12: It is likely that well-mixed GHGs67 contributed a warming \nof 1.0\u00b0C to 2.0\u00b0C, and other human drivers (principally aerosols) \ncontributed a cooling of 0.0\u00b0C to 0.8\u00b0C, natural (solar and volcanic) \ndrivers changed global surface temperature by \u00b10.1\u00b0C and internal \nvariability changed it by \u00b10.2\u00b0C. {WGI SPM A.1, WGI SPM A.1.2, \nWGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2}\nObserved increases in well-mixed GHG concentrations since around \n1750 are unequivocally caused by GHG emissions from human activities. \nLand and ocean sinks have taken up a near-constant proportion \n(globally about 56% per year) of CO2 emissions from human activities over \n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\n64 \nThe estimated increase in global surface temperature since AR5 is principally due to further warming since 2003\u20132012 (+0.19 [0.16 to 0.22]\u00b0C). Additionally, methodological \nadvances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements \nhave also increased the estimate of global surface temperature change by approximately 0.1\u00b0C, but this increase does not represent additional physical warming since AR5 \n{WGI SPM A1.2 and footnote 10}\n65 \nFor 1850\u20131900 to 2013\u20132022 the updated calculations are 1.15 [1.00 to 1.25]\u00b0C for global surface temperature, 1.65 [1.36 to 1.90]\u00b0C for land temperatures and \n0.93 [0.73 to 1.04]\u00b0C for ocean temperatures above 1850\u20131900 using the exact same datasets (updated by 2 years) and methods as employed in WGI.\n\nDocument 11: Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900. Global \nsurface temperature has increased faster since 1970 than in any other \n50-year period over at least the last 2000 years (high con\ufb01dence). The \nlikely range of total human-caused global surface temperature increase \nfrom 1850\u20131900 to 2010\u2013201966 is 0.8\u00b0C to 1.3\u00b0C, with a best estimate \nof 1.07\u00b0C. It is likely that well-mixed GHGs67 contributed a warming \nof 1.0\u00b0C to 2.0\u00b0C, and other human drivers (principally aerosols) \ncontributed a cooling of 0.0\u00b0C to 0.8\u00b0C, natural (solar and volcanic) \ndrivers changed global surface temperature by \u00b10.1\u00b0C and internal \nvariability changed it by \u00b10.2\u00b0C. {WGI SPM A.1, WGI SPM A.1.2, \nWGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2}\nObserved increases in well-mixed GHG concentrations since around \n1750 are unequivocally caused by GHG emissions from human activities.\n\nDocument 13: Additionally, methodological \nadvances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements \nhave also increased the estimate of global surface temperature change by approximately 0.1\u00b0C, but this increase does not represent additional physical warming since AR5 \n{WGI SPM A1.2 and footnote 10}\n65 \nFor 1850\u20131900 to 2013\u20132022 the updated calculations are 1.15 [1.00 to 1.25]\u00b0C for global surface temperature, 1.65 [1.36 to 1.90]\u00b0C for land temperatures and \n0.93 [0.73 to 1.04]\u00b0C for ocean temperatures above 1850\u20131900 using the exact same datasets (updated by 2 years) and methods as employed in WGI. \n66 \nThe period distinction with the observed assessment arises because the attribution studies consider this slightly earlier period. The observed warming to 2010\u20132019 is \n1.06 [0.88 to 1.21]\u00b0C. {WGI SPM footnote 11}\n67 \nContributions from emissions to the 2010\u20132019 warming relative to 1850\u20131900 assessed from radiative forcing studies are: CO2 0.8 [0.5 to 1.2]\u00b0C; methane 0.5 [0.3 to 0.8]\u00b0C; \nnitrous oxide 0.1 [0.0 to 0.2]\u00b0C and \ufb02uorinated gases 0.1 [0.0 to 0.2]\u00b0C.\n68 \nFor 2021 (the most recent year for which \ufb01nal numbers are available) concentrations using the same observational products and methods as in AR6 WGI are: 415 ppm CO2; \n1896 ppb CH4; and 335 ppb N2O. Note that the CO2 is reported here using the WMO-CO2-X2007 scale to be consistent with WGI. Operational CO2 reporting has since been \nupdated to use the WMO-CO2-X2019 scale.\nthe past six decades, with regional differences (high con\ufb01dence).\n\nDocument 10: 42\nSection 2\nSection 1\nSection 2\n2.1 Observed Changes, Impacts and Attribution\nHuman activities, principally through emissions of greenhouse gases, have unequivocally caused global warming, \nwith global surface temperature reaching 1.1\u00b0C above 1850\u20131900 in 2011\u20132020. Global greenhouse gas emissions \nhave continued to increase over 2010\u20132019, with unequal historical and ongoing contributions arising from \nunsustainable energy use, land use and land-use change, lifestyles and patterns of consumption and production \nacross regions, between and within countries, and between individuals (high con\ufb01dence). Human-caused climate \nchange is already affecting many weather and climate extremes in every region across the globe. This has led to \nwidespread adverse impacts on food and water security, human health and on economies and society and related \nlosses and damages63 to nature and people (high con\ufb01dence). Vulnerable communities who have historically \ncontributed the least to current climate change are disproportionately affected (high con\ufb01dence).\n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\nSection 2: Current Status and Trends\n2.1.1. Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":12,"situational_context":"A researcher is analyzing the impact of human activities on global warming and the effectiveness of land and ocean sinks in absorbing CO2 emissions.","topic":"Others"}}
{"id":"c8d99e2f-04c0-45f6-a9cc-3fb651e3bc50","question":"As an environmental science major researching the impact of climate change on global water scarcity and food security for my university project, could you explain the main factors contributing to the severe water scarcity experienced by roughly half of the world's population?","reference_answer":"Severe water scarcity experienced by roughly half of the world's population is due to a combination of climatic and non-climatic drivers.","reference_context":"Document 43: Roughly half of the world\u2019s population currently experiences severe water \nscarcity for at least some part of the year due to a combination of climatic \nand non-climatic drivers (medium con\ufb01dence) (Figure 2.3). Unsustainable \nagricultural expansion, driven in part by unbalanced diets77, increases \necosystem and human vulnerability and leads to competition for land \nand\/or water resources (high con\ufb01dence). Increasing weather and climate \nextreme events have exposed millions of people to acute food insecurity78 \nand reduced water security, with the largest impacts observed in many \nlocations and\/or communities in Africa, Asia, Central and South America, \nLDCs, Small Islands and the Arctic, and for small-scale food producers, \nlow-income households and Indigenous Peoples globally (high con\ufb01dence). \n{WGII SPM B.1.3, WGII SPM.B.2.3, WGII Figure SPM.2, WGII TS B.2.3, \nWGII TS Figure TS. 6; SRCCL SPM A.2.8, SRCCL SPM A.5.3; SROCC SPM A.5.4., \nSROCC SPM A.7.1, SROCC SPM A.8.1, SROCC Figure SPM.2} \n77 \nBalanced diets feature plant-based foods, such as those based on coarse grains, legumes fruits and vegetables, nuts and seeds, and animal-source foods produced in resilient, \nsustainable and low-GHG emissions systems, as described in SRCCL. {WGII SPM Footnote 32}\n78 \nAcute food insecurity can occur at any time with a severity that threatens lives, livelihoods or both, regardless of the causes, context or duration, as a result of shocks risking \ndeterminants of food security and nutrition, and is used to assess the need for humanitarian action.\n\nDocument 42: 50\nSection 2\nSection 1\nSection 2\nClimate change has reduced food security and affected water \nsecurity due to warming, changing precipitation patterns, \nreduction and loss of cryospheric elements, and greater frequency \nand intensity of climatic extremes, thereby hindering efforts to \nmeet Sustainable Development Goals (high con\ufb01dence). Although \noverall agricultural productivity has increased, climate change has slowed \nthis growth in agricultural productivity over the past 50 years globally \n(medium con\ufb01dence), with related negative crop yield impacts mainly \nrecorded in mid- and low latitude regions, and some positive impacts \nin some high latitude regions (high con\ufb01dence). Ocean warming in \nthe 20th century and beyond has contributed to an overall decrease \nin maximum catch potential (medium con\ufb01dence), compounding the \nimpacts from over\ufb01shing for some \ufb01sh stocks (high con\ufb01dence). Ocean \nwarming and ocean acidi\ufb01cation have adversely affected food production \nfrom shell\ufb01sh aquaculture and \ufb01sheries in some oceanic regions (high \ncon\ufb01dence). Current levels of global warming are associated with \nmoderate risks from increased dryland water scarcity (high con\ufb01dence). \nRoughly half of the world\u2019s population currently experiences severe water \nscarcity for at least some part of the year due to a combination of climatic \nand non-climatic drivers (medium con\ufb01dence) (Figure 2.3). Unsustainable \nagricultural expansion, driven in part by unbalanced diets77, increases \necosystem and human vulnerability and leads to competition for land \nand\/or water resources (high con\ufb01dence). Increasing weather and climate \nextreme events have exposed millions of people to acute food insecurity78 \nand reduced water security, with the largest impacts observed in many \nlocations and\/or communities in Africa, Asia, Central and South America, \nLDCs, Small Islands and the Arctic, and for small-scale food producers, \nlow-income households and Indigenous Peoples globally (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":43,"situational_context":"A concerned environmental science major is researching the impact of climate change on global water scarcity and food security for a university project.","topic":"Climate Change Impacts"}}
{"id":"5b032d70-8109-453c-8f46-9a39c24ecd32","question":"As an environmental policy advisor preparing for an international sustainability conference, could you inform me about the effective adaptation strategies for water, food, and vector-borne diseases that the IPCC report recommends?","reference_answer":"Effective adaptation options for water, food, and vector-borne diseases include improving access to potable water, reducing exposure of water and sanitation systems to extreme weather events, improved early warning systems, surveillance, and vaccine development.","reference_context":"Document 75: Heat Health Action Plans that include early warning and \nresponse systems are effective adaptation options for extreme heat \n(high con\ufb01dence). Effective adaptation options for water, food and \nvector-borne diseases include improving access to potable water, \nreducing exposure of water and sanitation systems to extreme weather \nevents, and improved early warning systems, surveillance, and vaccine \ndevelopment (very high con\ufb01dence). Adaptation options such as \ndisaster risk management, early warning systems, climate services \nand social safety nets have broad applicability across multiple sectors \n(high con\ufb01dence). {WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.9, \nWGII SPM C.2.11, WGII SPM C.2.13; SROCC SPM C.3.2}\nIntegrated, multi-sectoral solutions that address social inequities, \ndifferentiate responses based on climate risk and cut across systems, \nincrease the feasibility and effectiveness of adaptation in multiple \nsectors (high con\ufb01dence). {WGII SPM C.2}\n\nDocument 267: 107\nNear-Term Responses in a Changing Climate\nSection 4\nImproved access to clean energy sources and technologies, and shifts \nto active mobility (e.g., walking and cycling) and public transport can \ndeliver socioeconomic, air quality and health benefits, especially \nfor women and children (high confidence). {WGII SPM C.2.2, WGII \nSPM C.2.11, WGII Cross-Chapter Box HEALTH; WGIII SPM C.2.2, \nWGIII SPM C.4.2, WGIII SPM C.9.1, WGIII SPM C.10.4, WGIII SPM \nD.1.3, WGIII Figure SPM.6, WGIII Figure SPM.8; SRCCL SPM B.6.2, \nSRCCL SPM B.6.3, SRCCL B.4.6, SRCCL SPM C.2.4}\nEffective adaptation options exist to help protect human health \nand well-being (high con\ufb01dence). Health Action Plans that include \nearly warning and response systems are effective for extreme heat (high \ncon\ufb01dence). Effective options for water-borne and food-borne diseases \ninclude improving access to potable water, reducing exposure of water and \nsanitation systems to \ufb02ooding and extreme weather events, and improved \nearly warning systems (very high con\ufb01dence). For vector-borne diseases, \neffective adaptation options include surveillance, early warning \nsystems, and vaccine development (very high con\ufb01dence). Effective \nadaptation options for reducing mental health risks under climate \nchange include improving surveillance and access to mental health \ncare, and monitoring of psychosocial impacts from extreme weather \nevents (high con\ufb01dence). A key pathway to climate resilience in the \nhealth sector is universal access to healthcare (high con\ufb01dence). \n{WGII SPM C.2.11, WGII 7.4.6}\n4.5.6 Society, Livelihoods, and Economies\nEnhancing knowledge on risks and available adaptation options \npromotes societal responses, and behaviour and lifestyle changes \nsupported by policies, infrastructure and technology can help \nreduce global GHG emissions (high con\ufb01dence).\n\nDocument 74: 56\nSection 2\nSection 1\nSection 2\nwetlands, rangelands, mangroves and forests); while afforestation and \nreforestation, restoration of high-carbon ecosystems, agroforestry, and \nthe reclamation of degraded soils take more time to deliver measurable \nresults. Signi\ufb01cant synergies exist between adaptation and mitigation, \nfor example through sustainable land management approaches. \nAgroecological principles and practices and other approaches \nthat work with natural processes support food security, nutrition, \nhealth and well-being, livelihoods and biodiversity, sustainability and \necosystem services. (high con\ufb01dence) {WGII SPM C.2.1, WGII SPM C.2.2, \nWGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; \nSROCC SPM C.2}\nCombinations of non-structural measures like early warning systems \nand structural measures like levees have reduced loss of lives in case \nof inland \ufb02ooding (medium con\ufb01dence) and early warning systems \nalong with \ufb02ood-proo\ufb01ng of buildings have proven to be cost-effective \nin the context of coastal \ufb02ooding under current sea level rise (high \ncon\ufb01dence). Heat Health Action Plans that include early warning and \nresponse systems are effective adaptation options for extreme heat \n(high con\ufb01dence). Effective adaptation options for water, food and \nvector-borne diseases include improving access to potable water, \nreducing exposure of water and sanitation systems to extreme weather \nevents, and improved early warning systems, surveillance, and vaccine \ndevelopment (very high con\ufb01dence). Adaptation options such as \ndisaster risk management, early warning systems, climate services \nand social safety nets have broad applicability across multiple sectors \n(high con\ufb01dence).\n\nDocument 268: For vector-borne diseases, \neffective adaptation options include surveillance, early warning \nsystems, and vaccine development (very high con\ufb01dence). Effective \nadaptation options for reducing mental health risks under climate \nchange include improving surveillance and access to mental health \ncare, and monitoring of psychosocial impacts from extreme weather \nevents (high con\ufb01dence). A key pathway to climate resilience in the \nhealth sector is universal access to healthcare (high con\ufb01dence). \n{WGII SPM C.2.11, WGII 7.4.6}\n4.5.6 Society, Livelihoods, and Economies\nEnhancing knowledge on risks and available adaptation options \npromotes societal responses, and behaviour and lifestyle changes \nsupported by policies, infrastructure and technology can help \nreduce global GHG emissions (high con\ufb01dence). Climate literacy \nand information provided through climate services and community \napproaches, including those that are informed by Indigenous Knowledge \nand local knowledge, can accelerate behavioural changes and planning \n(high con\ufb01dence). Educational and information programmes, using \nthe arts, participatory modelling and citizen science can facilitate \nawareness, heighten risk perception, and in\ufb02uence behaviours (high \ncon\ufb01dence). The way choices are presented can enable adoption of low \nGHG intensive socio-cultural options, such as shifts to balanced, sustainable \nhealthy diets, reduced food waste, and active mobility (high con\ufb01dence). \nJudicious labelling, framing, and communication of social norms can \nincrease the effect of mandates, subsidies, or taxes (medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":75,"situational_context":"An environmental policy advisor is researching effective climate adaptation strategies to present at an upcoming international sustainability conference.","topic":"Climate Change Action"}}
{"id":"4b3559bf-708b-4bb1-acf3-35328787e62d","question":"As a researcher analyzing the IPCC report to understand human contributions to climate change indicators, could you tell me what the assessed confidence level is for the human contribution to the cooling of the lower stratosphere since the mid-20th century?","reference_answer":"The assessed confidence level for the human contribution to the cooling of the lower stratosphere since the mid-20th century is 'very likely'.","reference_context":"Document 35: 47\nCurrent Status and Trends\nSection 2\nTable 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate system components, and their attribution to human \nin\ufb02uence. The colour coding indicates the assessed con\ufb01dence in \/ likelihood76 of the observed change and the human contribution as a driver or main driver (speci\ufb01ed in that case) \nwhere available (see colour key). Otherwise, explanatory text is provided. {WGI Table TS.1}\n76 \nBased on scienti\ufb01c understanding, key \ufb01ndings can be formulated as statements of fact or associated with an assessed level of con\ufb01dence indicated using the IPCC calibrated language.\n\nDocument 36: 47\nCurrent Status and Trends\nSection 2\nTable 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate system components, and their attribution to human \nin\ufb02uence. The colour coding indicates the assessed con\ufb01dence in \/ likelihood76 of the observed change and the human contribution as a driver or main driver (speci\ufb01ed in that case) \nwhere available (see colour key). Otherwise, explanatory text is provided. {WGI Table TS.1}\n76 \nBased on scienti\ufb01c understanding, key \ufb01ndings can be formulated as statements of fact or associated with an assessed level of con\ufb01dence indicated using the IPCC calibrated language.\nlikely range of human contribution \n([0.8-1.3\u00b0C]) encompasses the very likely \nrange of observed warming ([0.9-1.2\u00b0C])\nObserved change\nassessment \nHuman contribution\nassessment \nMain driver\nMain driver 1979 - mid-1990s\nSouthern Hemisphere\nMain driver\nMain driver\nMain driver\nLimited evidence & medium agreement \nMain driver\nMain driver\nMain driver\nMain driver\nChange in indicator\nWarming of global mean surface air temperature since 1850-1900\nWarming of the troposphere since 1979\nCooling of the lower stratosphere since the mid-20th century\nLarge-scale precipitation and upper troposphere humidity changes since 1979\nExpansion of the zonal mean Hadley Circulation since the 1980s\nOcean heat content increase since the 1970s\nSalinity changes since the mid-20th century\nGlobal mean sea level rise since 1970\nArctic sea ice loss since 1979\nReduction in Northern Hemisphere springtime snow cover since 1950\nGreenland ice sheet mass loss since 1990s\nAntarctic ice sheet mass loss since 1990s\nRetreat of glaciers\nIncreased amplitude of the seasonal cycle of\natmospheric CO2 since the early 1960s\nAcidi\ufb01cation of the global surface ocean\nMean surface air temperature over land\n(about 40% larger than global mean warming)\nWarming of the global climate system since preindustrial times\nmedium\ncon\ufb01dence\nlikely \/ high\ncon\ufb01dence\nvery likely\nextremely\nlikely\nvirtually\ncertain\nfact\nAtmosphere \nand water cycle\nOcean\nCryosphere\nCarbon cycle\nLand climate\nSynthesis\nKey","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":35,"situational_context":"A researcher is analyzing the IPCC report to understand the human contributions to climate change indicators.","topic":"Climate Change Assessment"}}
{"id":"77e2d88d-b5e1-4cd8-aadd-a9c67d7a881b","question":"As an environmental science professor deeply concerned about biodiversity, I'm examining the latest IPCC report to understand the consequences of climate change on various species. Could you tell me what the estimated range of species extinction risk is at a global warming level of 1.5\u00b0C?","reference_answer":"At a global warming level of 1.5\u00b0C, 3 to 14% of the tens of thousands of species assessed will likely face a very high risk of extinction.","reference_context":"Document 134: 74\nSection 3\nSection 1\nSection 3\nFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. \nProjected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without \nadditional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species \nlosses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as de\ufb01ned by conditions beyond the estimated historical \n(1850\u20132005) maximum mean annual temperature experienced by each species, at GWLs of 1.5\u00b0C, 2\u00b0C, 3\u00b0C and 4\u00b0C. Underpinning projections of temperature are from 21 Earth \nsystem models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure \nto hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991\u20132005) and at GWLs of 1.7\u00b0C to 2.3\u00b0C \n(mean = 1.9\u00b0C; 13 climate models), 2.4\u00b0C to 3.1\u00b0C (2.7\u00b0C; 16 climate models) and 4.2\u00b0C to 5.4\u00b0C (4.7\u00b0C; 15 climate models). Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C).\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 105: 64\nSection 2\nSection 1\nSection 2\nGlobal Warming Levels (GWLs)\nFor many climate and risk variables, the geographical patterns of changes in climatic impact-drivers110 and climate impacts for a level of global \nwarming111 are common to all scenarios considered and independent of timing when that level is reached. This motivates the use of GWLs as a \ndimension of integration. {WGI Box SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2)\nRisks\nDynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result \nin risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the \nReasons for Concern (RFCs) \u2013 \ufb01ve globally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature. \nRisks can also arise from climate change mitigation or adaptation responses when the response does not achieve its intended objective, or when \nit results in adverse effects for other societal objectives. {WGII SPM A, WGII Figure SPM.3, WGII Box TS.1, WGII Figure TS.4; SR1.5 Figure SPM.2; \nSROCC Errata Figure SPM.3; SRCCL Figure SPM.2} (3.1.2, Cross-Section Box.2 Figure 1, Figure 3.3)\n110 See Annex I: Glossary\n111 See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850\u20131900. The assessed time of when a certain global warming level \nis reached under a particular scenario is de\ufb01ned here as the mid-point of the \ufb01rst 20-year running average period during which the assessed average global surface temperature \nchange exceeds the level of global warming. {WGI SPM footnote 26, Cross-Section Box TS.1}\n\nDocument 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":134,"situational_context":"A concerned environmental science professor is examining the potential consequences of climate change on biodiversity and human health as outlined in the latest IPCC report.","topic":"Climate Change Assessment"}}
{"id":"48a4e6fa-b223-406b-b85d-ff59eab56e2b","question":"As a concerned citizen, I'm trying to grasp the potential impacts of various greenhouse gas emissions scenarios on our planet. Could you tell me what the IPCC report says about the projected consequences if we don't take urgent, effective, and equitable adaptation and mitigation actions?","reference_answer":"Without urgent, effective, and equitable adaptation and mitigation actions, climate change increasingly threatens the health and livelihoods of people around the globe, ecosystem health, and biodiversity, with severe adverse consequences for current and future generations.","reference_context":"Document 204: Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}. (Cross-Section \nBox.2, Figure 2.1, Figure 2.3)\n141 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). The best estimates [and very likely ranges] of global warming for the different scenarios in the \nnear term are: 1.5 [1.2 to 1.7]\u00b0C (SSP1-1.9); 1.5 [1.2 to 1.8]\u00b0C (SSP1-2.6); 1.5 [1.2 to 1.8]\u00b0C (SSP2-4.5); 1.5 [1.2 to 1.8]\u00b0C (SSP3-7.0); and 1.6[1.3 to 1.9]\u00b0C (SSP5-8.5).\n\nDocument 114: {WGIII SPM C.1.3}\n112  Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I: Glossary). {WGI SPM footnote 21}\n113 The best estimates [and very likely ranges] for the different scenarios are: 1.4 [1.0 to 1.8]\u00b0C (SSP1-1.9); 1.8 [1.3 to 2.4]\u00b0C (SSP1-2.6); 2.7 [2.1 to 3.5]\u00b0C (SSP2-4.5); 3.6 [2.8 to 4.6]\u00b0C \n(SSP3-7.0); and 4.4 [3.3 to 5.7]\u00b0C (SSP5-8.5). {WGI Table SPM.1} (Cross-Section Box.2)\n114 In the near term (2021\u20132040), the 1.5\u00b0C global warming level is very likely to be exceeded under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under \nthe intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely \nthan not to be reached under the very low GHG emissions scenario (SSP1-1.9). In all scenarios considered by WGI except the very high emissions scenario, the midpoint of the \n\ufb01rst 20-year running average period during which the assessed global warming reaches 1.5\u00b0C lies in the \ufb01rst half of the 2030s. In the very high GHG emissions scenario, this \nmid-point is in the late 2020s. The median \ufb01ve-year interval at which a 1.5\u00b0C global warming level is reached (50% probability) in categories of modelled pathways considered \nin WGIII is 2030\u20132035.\n\nDocument 203: 92\nSection 4\nSection 1\nSection 4\nSection 4 : Near-Term Responses in a Changing Climate\n4.1 The Timing and Urgency of Climate Action\nThe magnitude and rate of climate change and associated risks \ndepend strongly on near-term mitigation and adaptation actions \n(very high con\ufb01dence). Global warming is more likely than not to reach \n1.5\u00b0C between 2021 and 2040 even under the very low GHG emission \nscenarios (SSP1-1.9), and likely or very likely to exceed 1.5\u00b0C under \nhigher emissions scenarios141. Many adaptation options have medium \nor high feasibility up to 1.5\u00b0C (medium to high con\ufb01dence, depending \non option), but hard limits to adaptation have already been reached \nin some ecosystems and the effectiveness of adaptation to reduce \nclimate risk will decrease with increasing warming (high con\ufb01dence). \nSocietal choices and actions implemented in this decade determine the \nextent to which medium- and long-term pathways will deliver higher or \nlower climate resilient development (high con\ufb01dence). Climate resilient \ndevelopment prospects are increasingly limited if current greenhouse \ngas emissions do not rapidly decline, especially if 1.5\u00b0C global warming \nis exceeded in the near term (high con\ufb01dence). Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}.\n\nDocument 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":204,"situational_context":"A concerned citizen is seeking to understand the potential impacts of different greenhouse gas emissions scenarios on global warming and climate change.","topic":"Climate Change Scenarios"}}
{"id":"0ea0afdf-e3db-455f-b2f4-d70ad498b55a","question":"As a policy maker concerned with rising sea levels and climate change, can you explain the significance of coastal cities in advancing climate resilient development?","reference_answer":"Coastal cities and settlements play an important role in advancing climate resilient development due to the high number of people living in the Low Elevation Coastal Zone, the escalating and climate compounded risk that they face, and their vital role in national economies and beyond (high confidence).","reference_context":"Document 199: Coastal cities and \nsettlements play an important role in advancing climate resilient \ndevelopment due to the high number of people living in the Low \nElevation Coastal Zone, the escalating and climate compounded risk \nthat they face, and their vital role in national economies and beyond \n(high con\ufb01dence). {WGII SPM.D.3, WGII SPM D.3.3; WGIII SPM E.2, \nWGIII SPM E.2.2; SR1.5 SPM D.6}\nObserved adverse impacts and related losses and damages, \nprojected risks, trends in vulnerability, and adaptation limits \ndemonstrate that transformation for sustainability and climate \nresilient development action is more urgent than previously \nassessed (very high con\ufb01dence). Climate resilient development \nintegrates adaptation and GHG mitigation to advance \nsustainable development for all. Climate resilient development \npathways have been constrained by past development, emissions and \nclimate change and are progressively constrained by every increment \nof warming, in particular beyond 1.5\u00b0C (very high con\ufb01dence). \nClimate resilient development will not be possible in some regions \nand sub-regions if global warming exceeds 2\u00b0C (medium con\ufb01dence). \nSafeguarding biodiversity and ecosystems is fundamental to climate \nresilient development, but biodiversity and ecosystem services have \nlimited capacity to adapt to increasing global warming levels, making \nclimate resilient development progressively harder to achieve beyond \n1.5\u00b0C warming (very high con\ufb01dence). {WGII SPM D.1, WGII SPM D.1.1, \nWGII SPM D.4, WGII SPM D.4.3, WGII SPM D.5.1; WGIII SPM D.1.1} \nThe cumulative scienti\ufb01c evidence is unequivocal: climate change \nis a threat to human well-being and planetary health (very \nhigh con\ufb01dence). Any further delay in concerted anticipatory \nglobal action on adaptation and mitigation will miss a brief and \nrapidly closing window of opportunity to secure a liveable and \nsustainable future for all (very high con\ufb01dence). Opportunities for \nnear-term action are assessed in the following section.\n\nDocument 198: {WGII SPM C.5.4, \nWGII SPM D.1, WGII SPM D.1.1, WGII SPM D.1.2, WGII SPM D.2, \nWGII SPM D.3, WGII SPM D.5, WGII SPM D.5.1, WGII SPM D.5.2; \nWGIII SPM D.1, WGIII SPM D.2, WGIII SPM D.2.4, WGIII SPM E.2.2, \nWGIII SPM E.2.3, WGIII SPM E.5.3, WGIII Cross-Chapter Box 5} \nPolicies that shift development pathways towards sustainability \ncan broaden the portfolio of available mitigation and adaptation \nresponses (medium con\ufb01dence). Combining mitigation with action \nto shift development pathways, such as broader sectoral policies, \napproaches that induce lifestyle or behaviour changes, \ufb01nancial \nregulation, or macroeconomic policies can overcome barriers and \nopen up a broader range of mitigation options (high con\ufb01dence). \nIntegrated, inclusive planning and investment in everyday decision-\nmaking about urban infrastructure can signi\ufb01cantly increase the \nadaptive capacity of urban and rural settlements. Coastal cities and \nsettlements play an important role in advancing climate resilient \ndevelopment due to the high number of people living in the Low \nElevation Coastal Zone, the escalating and climate compounded risk \nthat they face, and their vital role in national economies and beyond \n(high con\ufb01dence). {WGII SPM.D.3, WGII SPM D.3.3; WGIII SPM E.2, \nWGIII SPM E.2.2; SR1.5 SPM D.6}\nObserved adverse impacts and related losses and damages, \nprojected risks, trends in vulnerability, and adaptation limits \ndemonstrate that transformation for sustainability and climate \nresilient development action is more urgent than previously \nassessed (very high con\ufb01dence). Climate resilient development \nintegrates adaptation and GHG mitigation to advance \nsustainable development for all.\n\nDocument 196: Accelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\n\nDocument 301: {SRCCL SPM C.2.1, SRCCL SPM D.1.2, SRCCL SPM D.1.4, \nSRCCL 7.4.4, SRCCL 7.4.6}\nClimate resilient development strategies that treat climate, \necosystems and biodiversity, and human society as parts of an \nintegrated system are the most effective (high con\ufb01dence). Human \nand ecosystem vulnerability are interdependent (high con\ufb01dence). \nClimate resilient development is enabled when decision-making processes \nand actions are integrated across sectors (very high con\ufb01dence). \nSynergies with and progress towards the Sustainable Development \nGoals enhance prospects for climate resilient development. Choices and \nactions that treat humans and ecosystems as an integrated system build \non diverse knowledge about climate risk, equitable, just and inclusive \napproaches, and ecosystem stewardship. {WGII SPM B.2, WGII Figure \nSPM.5, WGII SPM D.2, WGII SPM D2.1, WGII SPM 2.2, WGII SPM D4, \nWGII SPM D4.1, WGII SPM D4.2, WGII SPM D5.2, WGII Figure SPM.5}\nApproaches that align goals and actions across sectors provide \nopportunities for multiple and large-scale bene\ufb01ts and avoided \ndamages in the near term. Such measures can also achieve \ngreater bene\ufb01ts through cascading effects across sectors \n(medium con\ufb01dence). For example, the feasibility of using land for \nboth agriculture and centralised solar production can increase when \nsuch options are combined (high con\ufb01dence). Similarly, integrated \ntransport and energy infrastructure planning and operations can \ntogether reduce the environmental, social, and economic impacts of \ndecarbonising the transport and energy sectors (high con\ufb01dence). The \nimplementation of packages of multiple city-scale mitigation strategies \ncan have cascading effects across sectors and reduce GHG emissions \nboth within and outside a city\u2019s administrative boundaries (very high \ncon\ufb01dence). Integrated design approaches to the construction and \nretro\ufb01t of buildings provide increasing examples of zero energy or \nzero carbon buildings in several regions.","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":199,"situational_context":"A policy maker is seeking information on how coastal cities can advance climate resilient development in the face of rising sea levels and climate change.","topic":"Climate Change Action"}}
{"id":"3e1c1062-e592-4523-9764-8848f2630130","question":"As a researcher studying the socio-economic impacts of climate change on different regions, I'm curious why the IPCC report had limited synthetic diagrams for Small Islands, Asia, and Central and South America. Could you explain the reasons behind this limitation?","reference_answer":"The development was limited due to the scarcity of adequately downscaled climate projections, uncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries within a region, and the few numbers of impact and risk projections for different warming levels.","reference_context":"Document 144: The development of synthetic diagrams for Small \nIslands, Asia and Central and South America was limited due to the paucity of adequately downscaled climate projections, with \nuncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries within a region, and \nthe resulting few numbers of impact and risk projections for different warming levels.\nThe risks listed are of at least medium con\ufb01dence level:","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":144,"situational_context":"A researcher is delving into the specifics of climate projections and their socio-economic impacts on diverse regions as outlined in the IPCC report.","topic":"Climate Change Risks"}}
{"id":"c8fc047e-7e02-4ae6-b190-ac02309f5ebc","question":"As an environmental policy maker looking into urban infrastructure development strategies, could you explain how the latest IPCC report describes the potential benefits of integrating green\/natural and grey\/physical infrastructure adaptation responses?","reference_answer":"Combining green\/natural and grey\/physical infrastructure adaptation responses has potential to reduce adaptation costs and contribute to flood control, sanitation, water resources management, landslide prevention, and coastal protection.","reference_context":"Document 260: Urban greening can \nprovide local cooling (very high con\ufb01dence). Combining green\/natural \nand grey\/physical infrastructure adaptation responses has potential \nto reduce adaptation costs and contribute to \ufb02ood control, sanitation, \nwater resources management, landslide prevention and coastal \nprotection (medium con\ufb01dence). Globally, more \ufb01nancing is directed \nat grey\/physical infrastructure than green\/natural infrastructure \nand social infrastructure (medium con\ufb01dence), and there is limited \nevidence of investment in informal settlements (medium to high \ncon\ufb01dence). The greatest gains in well-being in urban areas can be \nachieved by prioritising \ufb01nance to reduce climate risk for low-income\n\nDocument 259: Advances in battery technologies could facilitate \nthe electri\ufb01cation of heavy-duty trucks and compliment conventional \nelectric rail systems (medium con\ufb01dence). Sustainable biofuels can offer \nadditional mitigation bene\ufb01ts in land-based transport in the short and \nmedium term (medium con\ufb01dence). Sustainable biofuels, low-emissions \nhydrogen, and derivatives (including synthetic fuels) can support \nmitigation of CO2 emissions from shipping, aviation, and heavy-duty \nland transport but require production process improvements and cost \nreductions (medium con\ufb01dence). Key infrastructure systems including \nsanitation, water, health, transport, communications and energy will \nbe increasingly vulnerable if design standards do not account for \nchanging climate conditions (high con\ufb01dence). {WGII SPM B.2.5; \nWGIII SPM C.6.2, WGIII SPM C.8, WGIII SPM C.8.1, WGIII SPM C.8.2, \nWGIII SPM C.10.2, WGIII SPM C.10.3, WGIII SPM C.10.4} \nGreen\/natural and blue infrastructure such as urban forestry, green \nroofs, ponds and lakes, and river restoration can mitigate climate change \nthrough carbon uptake and storage, avoided emissions, and reduced \nenergy use while reducing risk from extreme events such as heatwaves, \nheavy precipitation and droughts, and advancing co-bene\ufb01ts for health, \nwell-being and livelihoods (medium con\ufb01dence). Urban greening can \nprovide local cooling (very high con\ufb01dence). Combining green\/natural \nand grey\/physical infrastructure adaptation responses has potential \nto reduce adaptation costs and contribute to \ufb02ood control, sanitation, \nwater resources management, landslide prevention and coastal \nprotection (medium con\ufb01dence). Globally, more \ufb01nancing is directed \nat grey\/physical infrastructure than green\/natural infrastructure \nand social infrastructure (medium con\ufb01dence), and there is limited \nevidence of investment in informal settlements (medium to high \ncon\ufb01dence).","conversation_history":[],"metadata":{"question_type":"situational","seed_document_id":260,"situational_context":"An environmental policy maker is seeking information on the latest IPCC report to guide urban infrastructure development strategies.","topic":"Climate Change Action"}}
{"id":"03c9551b-7445-4d48-9fa3-8eef85392398","question":"What do the square brackets and three dots (...) signify in the context of emissions pathways and net zero in the IPCC report?","reference_answer":"In the IPCC report's assessment, the square brackets represent the 5th-95th percentile interval for the projected scenarios, while three dots (...) denote that net zero is not reached for that percentile.","reference_context":"Document 172: with the 5th-95th percentile \ninterval in square brackets. \nPercentage of net zero \npathways is denoted in \nround brackets. \nThree dots (\u2026) denotes net \nzero not reached for that \npercentile.\nMedian cumulative net CO2 \nemissions across the \nprojected scenarios in this \ncategory until reaching \nnet-zero or until 2100, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected temperature \nchange of pathways in this \ncategory (50% probability \nacross the range of climate \nuncertainties), relative to \n1850-1900, at peak \nwarming and in 2100, for \nthe median value across the \nscenarios and the 5th-95th \npercentile interval in square \nbrackets.\nMedian likelihood that the \nprojected pathways in this \ncategory stay below a given \nglobal warming level, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected median GHG \nemissions reductions of \npathways in the year across \nthe scenarios compared to \nmodelled 2019, with the \n5th-95th percentile in \nbrackets. Negative numbers \nindicate increase in \nemissions compared to 2019\nModelled global emissions \npathways categorised by \nprojected global warming \nlevels (GWL). Detailed \nlikelihood definitions are \nprovided in SPM Box1.  \nThe five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.\n\nDocument 175: 1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs. {WGIII Table SPM.2}\n1 Detailed explanations on the Table are provided in WGIII Box SPM.1 and WGIII Table SPM.2. The relationship between the temperature categories and SSP\/RCPs is discussed \nin Cross-Section Box.2. Values in the table refer to the 50th and [5\u201395th] percentile values across the pathways falling within a given category as de\ufb01ned in WGIII Box SPM.1. \nThe three dots (\u2026) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net zero is not reached). Based on the assessment of climate emulators \nin AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment of the resulting warming of the pathways. For the \u2018Temperature Change\u2019 \nand \u2018Likelihood\u2019 columns, the non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming \nestimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges in the \u201clikelihood\u201d column, the median warming for every pathway in that category \nis calculated for each of the two climate model emulators (MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate \nemulators\u2019 uncertainty. All global warming levels are relative to 1850-1900. \n2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4.\n\nDocument 173: The five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.8]\n[1.6-1.8]\n[1.6-1.8]\n[1.7-2.0]\n[1.9-2.5]\n[1.1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.\n\nDocument 174: 1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.5\u00b0C \n(>50%) \nafter a \nhigh \novershoot\nlimit \nwarming \nto 2\u00b0C \n(>67%) \n\u2026\nwith \naction \nstarting \nin 2020 \n\u2026\nNDCs \nuntil \n2030 \nlimit\nwarming\nto 2\u00b0C\n(>50%)\nlimit\nwarming\nto 2.5\u00b0C\n(>50%)\nlimit\nwarming\nto 3\u00b0C\n(>50%)\n[212]\nCategory \n(2) \n[# pathways]\nC1\n[97]\nC1a\n[50]\nC1b\n[47]\nC2\n[133]\nC3\n[311]\nC3a \n[204]\nC3b\n[97]\nC4\n[159]\nC5\nC6\n[97]\nTable 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What do the square brackets represent in the IPCC report's assessment of emissions pathways?","answer":"In the IPCC report's assessment, the square brackets represent the 5th-95th percentile interval for the projected scenarios."},{"question":"What is the significance of the three dots (...) in the context of net zero in the IPCC report?","answer":"In the IPCC report, three dots (...) denote that net zero is not reached for that percentile."}],"seed_document_id":172,"topic":"Climate Change Scenarios"}}
{"id":"8636fa1c-4fb0-4cdd-8b13-8835f9e3c61f","question":"According to the 2018 data, what are the GHG emissions intensity in terms of tCO2-eq per USD1000PPP for Africa and North America, and what percentage of the global population lives in countries emitting more than 6 tCO2-eq per capita and less than 3 tCO2-eq per capita?","reference_answer":"Based on the 2018 data, the GHG emissions intensity for Africa is 0.78 tCO2-eq per USD1000PPP and for North America is 0.31 tCO2-eq per USD1000PPP. Around 48% of the global population lives in countries emitting more than 6 tCO2-eq per capita, and another 41% live in countries emitting less than 3 tCO2-eq per capita.","reference_context":"Document 25: 6\n1.6\nConsumption-based emissions (tCO2FFI per person, based on 2018 data)\n0.84\n11\n6.7\n6.2\n7.8\n2.8\n7.6\n17\n2.5\n1.5\nPopulation (million persons, 2019)\n1292\n157\n1471\n291\n620\n646\n252\n366\n674\n1836\nGHG per capita (tCO2-eq per person)\n3.9\n13\n11\n13\n7.8\n9.2\n13\n19\n7.9\n2.6\nGDP per capita (USD1000PPP 2017 per person) 1\n5.0\n43\n17\n20\n43\n15\n20\n61\n12\n6.2\nNet GHG 2019 2 (production basis)\nCO2FFI, 2018, per person\nGHG emissions intensity (tCO2-eq \/ USD1000PPP 2017) \n0.78\n0.30\n0.62\n0.64\n0.18\n0.61\n0.64\n0.31\n0.65\n0.42\nAfrica\nAustralia, \nJapan, \nNew \nZealand\nEastern \nAsia\nEastern \nEurope, \nWest-\nCentral Asia\nEurope\nLatin \nAmerica \nand \nCaribbean\nMiddle \nEast\nNorth \nAmerica\nSouth-East \nAsia and \nPacifc\nSouthern \nAsia\n1 GDP per capita in 2019 in USD2017 currency purchasing power basis.\n2 Includes CO2FFI, CO2LULUCF and Other GHGs, excluding international aviation and shipping.\n\nDocument 26: 2\nNet GHG 2019 2 (production basis)\nCO2FFI, 2018, per person\nGHG emissions intensity (tCO2-eq \/ USD1000PPP 2017) \n0.78\n0.30\n0.62\n0.64\n0.18\n0.61\n0.64\n0.31\n0.65\n0.42\nAfrica\nAustralia, \nJapan, \nNew \nZealand\nEastern \nAsia\nEastern \nEurope, \nWest-\nCentral Asia\nEurope\nLatin \nAmerica \nand \nCaribbean\nMiddle \nEast\nNorth \nAmerica\nSouth-East \nAsia and \nPacifc\nSouthern \nAsia\n1 GDP per capita in 2019 in USD2017 currency purchasing power basis.\n2 Includes CO2FFI, CO2LULUCF and Other GHGs, excluding international aviation and shipping.\nThe regional groupings used in this \ufb01gure are for statistical \npurposes only and are described in WGIII Annex II, Part I.\nc) Global net anthropogenic GHG emissions by region (1990\u20132019)\n2000\n1990\n2010\n2019\nEastern Asia\nNorth America\nLatin America and Caribbean\nSouth-East Asia and Paci\ufb01c\nAfrica\nSouthern Asia\nEurope\nEastern Europe and West-Central Asia\nMiddle East\nAustralia, Japan and New Zealand\nInternational shipping and aviation\n13%\n18%\n10%\n7%\n7%\n7%\n16%\n14%\n3%\n5%\n2%\n16%\n19%\n11%\n7%\n8%\n8%\n2%\n5%\n8%\n4%\n13%\n27%\n24%\n12%\n14%\n10%\n11%\n9%\n7%\n9%\n8%\n8%\n8%\n2%\n2%\n7%\n5%\n4%\n5%\n3%\n6%\n10%\n8%\nTotal:\n38 GtCO2-eq\n42 GtCO2-eq\n53 GtCO2-eq\n59 GtCO2-eq\nEmissions have grown in most regions but are distributed unevenly, \nboth in the present day and cumulatively since 1850\nb) Net anthropogenic GHG emissions per capita \nand for total population, per region (2019)\na) Historical cumulative net anthropogenic \nCO2 emissions per region (1850\u20132019)\nGHG emissions (tCO2-eq per capita)\n\/\nCO2 emissions (GtCO2)\nNet CO2 from land use, land use change, forestry (CO2LULUCF)\nOther GHG emissions\nFossil fuel and industry (CO2FFI)\nAll GHG emissions\nGHG emissions per year (GtCO2-eq\/yr)\n\nDocument 24: 45\nCurrent Status and Trends\nSection 2\nKey\nPopulation (millions)\n0\n2000\n4000\n6000\n8000\n0\n5\n10\n15\n20\nMiddle East \nAfrica \nEastern Asia\nSouth-East Asia and Paci\ufb01c \nLatin America and Caribbean\nEurope\nSouthern Asia\nNorth America \nAustralia, Japan and New Zealand \nEastern Europe and West-Central Asia\nAfrica\nAustralia, Japan and New Zealand\nEastern Asia\nEastern Europe and West-Central Asia\nEurope\nInternational \nshipping and aviation\nLatin America and Caribbean\nMiddle East\nNorth America\nSouth-East Asia and Paci\ufb01c\nSouthern Asia\n0\n200\n400\n600\n50\n60\n30\n20\n10\n0\n4%\n16%\n4%\n2%\n8%\n12% 11% 10%\n7%\n2%\n23%\nCO2\nGHG\nGHG\n2019\n1990\n1850\nTimeframes represented in these graphs\nd) Regional indicators (2019) and regional production vs consumption accounting (2018)\nProduction-based emissions (tCO2FFI per person, based on 2018 data)\n1.2\n10\n8.4\n9.2\n6.5\n2.8\n8.7\n16\n2.6\n1.6\nConsumption-based emissions (tCO2FFI per person, based on 2018 data)\n0.84\n11\n6.7\n6.2\n7.8\n2.8\n7.6\n17\n2.5\n1.5\nPopulation (million persons, 2019)\n1292\n157\n1471\n291\n620\n646\n252\n366\n674\n1836\nGHG per capita (tCO2-eq per person)\n3.9\n13\n11\n13\n7.8\n9.2\n13\n19\n7.9\n2.6\nGDP per capita (USD1000PPP 2017 per person) 1\n5.0\n43\n17\n20\n43\n15\n20\n61\n12\n6.2\nNet GHG 2019 2 (production basis)\nCO2FFI, 2018,\n\nDocument 20: Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence). In 2019, approximately 34% (20 GtCO2-eq) \nof net global GHG emissions came from the energy sector, 24% \n(14 GtCO2-eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% \n(8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2-eq) from buildings71 \n(high con\ufb01dence). Average annual GHG emissions growth between \n69 \nGHG emission metrics are used to express emissions of different GHGs in a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalents (CO2-eq) using \nthe Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports \ncontain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of \nmetric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the complexity of the physical climate \nsystem and its response to past and future GHG emissions.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the GHG emissions intensity in terms of tCO2-eq per USD1000PPP for Africa and North America according to the 2018 data?","answer":"The GHG emissions intensity for Africa is 0.78 tCO2-eq per USD1000PPP and for North America is 0.31 tCO2-eq per USD1000PPP based on the 2018 data."},{"question":"What percentage of the global population lives in countries emitting more than 6 tCO2-eq per capita and less than 3 tCO2-eq per capita?","answer":"Around 48% of the global population lives in countries emitting more than 6 tCO2-eq per capita, and another 41% live in countries emitting less than 3 tCO2-eq per capita."}],"seed_document_id":25,"topic":"Global GHG Emissions"}}
{"id":"57a6a9a6-2eb1-40ae-af8c-d807e9e152a6","question":"What are some of the concurrent and cascading risks to human systems posed by climate change, and how will these be exacerbated in terms of food systems and health?","reference_answer":"Climate change poses concurrent and cascading risks to food systems, human settlements, infrastructure, and health, which will be exacerbated by factors such as sudden food production losses from heat and drought, reduced labour productivity due to heat, increased food prices, decreased household incomes, and heightened health risks of malnutrition and climate-related mortality, particularly in tropical regions. These risks are intensified when combined with non-climatic drivers like land competition and pandemics.","reference_context":"Document 233: Concurrent and cascading risks from climate change to \nfood systems, human settlements, infrastructure and health will make \nthese risks more severe and more dif\ufb01cult to manage, including when \ninteracting with non-climatic risk drivers such as competition for land \nbetween urban expansion and food production, and pandemics (high \ncon\ufb01dence). Loss of ecosystems and their services has cascading and \nlong-term impacts on people globally, especially for Indigenous Peoples \nand local communities who are directly dependent on ecosystems, to \nmeet basic needs (high con\ufb01dence). Increasing transboundary risks \nare projected across the food, energy and water sectors as impacts \nfrom weather and climate extremes propagate through supply-chains, \nmarkets, and natural resource \ufb02ows (high con\ufb01dence) and may interact \nwith impacts from other crises such as pandemics. Risks also arise from \nsome responses intended to reduce the risks of climate change, including \nrisks from maladaptation and adverse side effects of some emissions \nreduction and carbon dioxide removal measures, such as afforestation of \nnaturally unforested land or poorly implemented bioenergy compounding \nclimate-related risks to biodiversity, food and water security, and \nlivelihoods (high con\ufb01dence) (see Section 3.4.1 and 4.5). {WGI SPM.2.7; \nWGII SPM B.2.1, WGII SPM B.5, WGII SPM B.5.1, WGII SPM B.5.2, \nWGII SPM B.5.3, WGII SPM B.5.4, WGII Cross-Chapter Box COVID in Chapter 7; \nWGIII SPM C.11.2; SRCCL SPM A.5, SRCCL SPM A.6.5} (Figure 4.3)\nWith every increment of global warming losses and damages will \nincrease (very high con\ufb01dence), become increasingly dif\ufb01cult \nto avoid and be strongly concentrated among the poorest \nvulnerable populations (high con\ufb01dence). Adaptation does not \nprevent all losses and damages, even with effective adaptation and \nbefore reaching soft and hard limits.\n\nDocument 232: 99\nNear-Term Responses in a Changing Climate\nSection 4\n\u2022 Cryosphere-related changes in \ufb02oods, landslides, and water \navailability have the potential to lead to severe consequences for \npeople, infrastructure and the economy in most mountain regions \n(high con\ufb01dence). {WGII TS C.4.2}\n\u2022 The projected increase in frequency and intensity of heavy \nprecipitation (high con\ufb01dence) will increase rain-generated local \n\ufb02ooding (medium con\ufb01dence). {WGI Figure SPM.6, WGI SPM B.2.2; \nWGII TS C.4.5}\nMultiple climate change risks will increasingly compound and \ncascade in the near term (high con\ufb01dence). Many regions are \nprojected to experience an increase in the probability of compound \nevents with higher global warming (high con\ufb01dence) including \nconcurrent heatwaves and drought. Risks to health and food \nproduction will be made more severe from the interaction of sudden \nfood production losses from heat and drought, exacerbated by heat-\ninduced labour productivity losses (high con\ufb01dence) (Figure 4.3). These \ninteracting impacts will increase food prices, reduce household incomes, \nand lead to health risks of malnutrition and climate-related mortality \nwith no or low levels of adaptation, especially in tropical regions (high \ncon\ufb01dence). Concurrent and cascading risks from climate change to \nfood systems, human settlements, infrastructure and health will make \nthese risks more severe and more dif\ufb01cult to manage, including when \ninteracting with non-climatic risk drivers such as competition for land \nbetween urban expansion and food production, and pandemics (high \ncon\ufb01dence). Loss of ecosystems and their services has cascading and \nlong-term impacts on people globally, especially for Indigenous Peoples \nand local communities who are directly dependent on ecosystems, to \nmeet basic needs (high con\ufb01dence). Increasing transboundary risks \nare projected across the food, energy and water sectors as impacts \nfrom weather and climate extremes propagate through supply-chains, \nmarkets, and natural resource \ufb02ows (high con\ufb01dence) and may interact \nwith impacts from other crises such as pandemics.\n\nDocument 129: 72\nSection 3\nSection 1\nSection 3\nProjected adverse impacts and related losses and damages from \nclimate change escalate with every increment of global warming \n(very high con\ufb01dence), but they will also strongly depend on \nsocio-economic development trajectories and adaptation actions \nto reduce vulnerability and exposure (high con\ufb01dence). For \nexample, development pathways with higher demand for food, animal \nfeed, and water, more resource-intensive consumption and production, \nand limited technological improvements result in higher risks from \nwater scarcity in drylands, land degradation and food insecurity (high \ncon\ufb01dence). Changes in, for example, demography or investments in \nhealth systems have effect on a variety of health-related outcomes \nincluding heat-related morbidity and mortality (Figure 3.3 Panel d). \n{WGII SPM B.3, WGII SPM B.4, WGII Figure SPM.3; SRCCL SPM A.6}\nWith every increment of warming, climate change impacts and \nrisks will become increasingly complex and more dif\ufb01cult to \nmanage. Many regions are projected to experience an increase in \nthe probability of compound events with higher global warming, such \nas concurrent heatwaves and droughts, compound \ufb02ooding and \ufb01re \nweather. In addition, multiple climatic and non-climatic risk drivers \nsuch as biodiversity loss or violent con\ufb02ict will interact, resulting \nin compounding overall risk and risks cascading across sectors and \nregions. Furthermore, risks can arise from some responses that are \nintended to reduce the risks of climate change, e.g., adverse side effects \nof some emission reduction and carbon dioxide removal (CDR) measures \n(see 3.4.1).\n\nDocument 225: Multiple climatic and non-climatic risks will interact, resulting in increased \ncompounding and cascading impacts becoming more dif\ufb01cult to manage (high con\ufb01dence). Losses and damages \nwill increase with increasing global warming (very high con\ufb01dence), while strongly concentrated among the \npoorest vulnerable populations (high con\ufb01dence). Continuing with current unsustainable development patterns \nwould increase exposure and vulnerability of ecosystems and people to climate hazards (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are some of the concurrent and cascading risks to human systems posed by climate change?","answer":"Concurrent and cascading risks from climate change to food systems, human settlements, infrastructure, and health will make these risks more severe and difficult to manage, especially when interacting with non-climatic risk drivers such as competition for land and pandemics."},{"question":"How will the impacts of climate change on food systems and health be exacerbated?","answer":"The impacts on food systems and health will be exacerbated by sudden food production losses from heat and drought, heat-induced labour productivity losses, leading to increased food prices, reduced household incomes, and health risks of malnutrition and climate-related mortality, especially in tropical regions."}],"seed_document_id":233,"topic":"Others"}}
{"id":"90548459-324f-4cb4-9c93-97285e59dbbb","question":"What do the non-bracketed values represent in the 'Temperature Change' and 'Likelihood' columns of the IPCC pathways categories, and what is the projected timing for CO2 emissions to reach net zero according to the very low and low GHG emissions scenarios?","reference_answer":"The non-bracketed values in the 'Temperature Change' and 'Likelihood' columns represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model emulator. CO2 emissions are projected to reach net zero around 2050 for the very low GHG emissions scenario (SSP1-1.9) and around 2070 for the low GHG emissions scenario (SSP1-2.6).","reference_context":"Document 175: 1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs. {WGIII Table SPM.2}\n1 Detailed explanations on the Table are provided in WGIII Box SPM.1 and WGIII Table SPM.2. The relationship between the temperature categories and SSP\/RCPs is discussed \nin Cross-Section Box.2. Values in the table refer to the 50th and [5\u201395th] percentile values across the pathways falling within a given category as de\ufb01ned in WGIII Box SPM.1. \nThe three dots (\u2026) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net zero is not reached). Based on the assessment of climate emulators \nin AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment of the resulting warming of the pathways. For the \u2018Temperature Change\u2019 \nand \u2018Likelihood\u2019 columns, the non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming \nestimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges in the \u201clikelihood\u201d column, the median warming for every pathway in that category \nis calculated for each of the two climate model emulators (MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate \nemulators\u2019 uncertainty. All global warming levels are relative to 1850-1900. \n2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4.\n\nDocument 174: 1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.5\u00b0C \n(>50%) \nafter a \nhigh \novershoot\nlimit \nwarming \nto 2\u00b0C \n(>67%) \n\u2026\nwith \naction \nstarting \nin 2020 \n\u2026\nNDCs \nuntil \n2030 \nlimit\nwarming\nto 2\u00b0C\n(>50%)\nlimit\nwarming\nto 2.5\u00b0C\n(>50%)\nlimit\nwarming\nto 3\u00b0C\n(>50%)\n[212]\nCategory \n(2) \n[# pathways]\nC1\n[97]\nC1a\n[50]\nC1b\n[47]\nC2\n[133]\nC3\n[311]\nC3a \n[204]\nC3b\n[97]\nC4\n[159]\nC5\nC6\n[97]\nTable 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs.\n\nDocument 176: For the \u2018Temperature Change\u2019 \nand \u2018Likelihood\u2019 columns, the non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming \nestimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges in the \u201clikelihood\u201d column, the median warming for every pathway in that category \nis calculated for each of the two climate model emulators (MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate \nemulators\u2019 uncertainty. All global warming levels are relative to 1850-1900. \n2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4. \n3 Global emission reductions in mitigation pathways are reported on a pathway-by-pathway basis relative to harmonised modelled global emissions in 2019 rather than\n\nDocument 102: The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8). Methods to project global warming associated with the \nmodelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII \nTable 3.1} (Table 3.1, Cross-Section Box.2 Figure 1)\n102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What do the non-bracketed values represent in the 'Temperature Change' and 'Likelihood' columns of the IPCC pathways categories?","answer":"The non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model emulator."},{"question":"What is the projected timing for CO2 emissions to reach net zero according to the very low and low GHG emissions scenarios?","answer":"According to the very low and low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6), CO2 emissions are projected to decline to net zero around 2050 and 2070, respectively."}],"seed_document_id":175,"topic":"Climate Change Scenarios"}}
{"id":"5fc93af0-de27-4126-a67a-e7934d9727d2","question":"What are the potential impacts, risks, and roles associated with the deployment of Carbon Dioxide Removal (CDR) methods in climate change mitigation?","reference_answer":"The impacts and risks of CDR deployment are highly variable and can affect ecosystems, biodiversity, and people depending on the method and context, while the roles of CDR in climate change mitigation include lowering net emissions in the near term, counterbalancing residual emissions to reach net zero, and achieving net negative emissions if deployed at sufficient levels.","reference_context":"Document 193: (high con\ufb01dence) {WGII SPM B.5.4, WGII SPM C.2.4; \nWGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5; SRCCL SPM B.3, \nSRCCL SPM B.7.3, SRCCL Figure SPM.3}\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\nModelled pathways that assume using resources more ef\ufb01ciently or shift \nglobal development towards sustainability include fewer challenges, such \nas dependence on CDR and pressure on land and biodiversity, and have \nthe most pronounced synergies with respect to sustainable development \n(high con\ufb01dence). {WGIII SPM C.3.6; SR1.5 SPM D.4.2} \nStrengthening climate change mitigation action entails more \nrapid transitions and higher up-front investments, but brings \nbene\ufb01ts from avoiding damages from climate change and \nreduced adaptation costs. The aggregate effects of climate change \nmitigation on global GDP (excluding damages from climate change and \nadaptation costs) are small compared to global projected GDP growth. \nProjected estimates of global aggregate net economic damages and \nthe costs of adaptation generally increase with global warming level. \n(high con\ufb01dence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, \nWGIII SPM C.12.3} \nCost-bene\ufb01t analysis remains limited in its ability to represent all \ndamages from climate change, including non-monetary damages, \nor to capture the heterogeneous nature of damages and the risk of \ncatastrophic damages (high con\ufb01dence).\n\nDocument 196: Accelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence). {WGIII SPM C.11.2}\n140 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5\u00b0C. {WGIII SPM footnote 68}\n\nDocument 195: {WGII SPM B.4, WGII \nSPM B.6; WGIII SPM C.12, WGIII SPM C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; \nSR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6}\nConsidering other sustainable development dimensions, such as the \npotentially strong economic bene\ufb01ts on human health from air quality \nimprovement, may enhance the estimated bene\ufb01ts of mitigation \n(medium con\ufb01dence). The economic effects of strengthened mitigation \naction vary across regions and countries, depending notably on economic \nstructure, regional emissions reductions, policy design and level of \ninternational cooperation (high con\ufb01dence). Ambitious mitigation \npathways imply large and sometimes disruptive changes in economic \nstructure, with implications for near-term actions (Section 4.2), equity \n(Section 4.4), sustainability (Section 4.6), and \ufb01nance (Section 4.8) \n(high con\ufb01dence). {WGIII SPM C.12.2, WGIII SPM D.3.2, WGIII TS.4.2}\n3.4 Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development\nMitigation and adaptation can lead to synergies and trade-offs with sustainable development (high con\ufb01dence). \nAccelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence).\n\nDocument 186: All assessed modelled pathways \nthat limit warming to 2\u00b0C (>67%) or lower by 2100 include land-based \nmitigation and land-use change, with most including different \ncombinations of reforestation, afforestation, reduced deforestation, and \nbioenergy. However, accumulated carbon in vegetation and soils is at \nrisk from future loss (or sink reversal) triggered by climate change and \ndisturbances such as \ufb02ood, drought, \ufb01re, or pest outbreaks, or future \npoor management. (high con\ufb01dence) {WGI SPM B.4.3; WGII SPM B.2.3, \nWGII SPM B.5.4; WGIII SPM C.9, WGIII SPM C.11.3, WGIII SPM D.2.3, \nWGIII TS.4.2, 3.4; SR1.5 SPM C.2.5; SRCCL SPM B.1.4, SRCCL SPM B.3, \nSRCCL SPM B.7}\nIn addition to deep, rapid, and sustained emission reductions, \nCDR can ful\ufb01l three complementary roles: lowering net CO2 \nor net GHG emissions in the near term; counterbalancing \n\u2018hard-to-abate\u2019 residual emissions (e.g., some emissions from \nagriculture, aviation, shipping, industrial processes) to help reach \nnet zero CO2 or GHG emissions, and achieving net negative \nCO2 or GHG emissions if deployed at levels exceeding annual \nresidual emissions (high con\ufb01dence). CDR methods vary in terms \nof their maturity, removal process, time scale of carbon storage, storage \nmedium, mitigation potential, cost, co-bene\ufb01ts, impacts and risks, and \ngovernance requirements (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the potential impacts and risks associated with the deployment of Carbon Dioxide Removal (CDR) methods?","answer":"The impacts, risks, and co-benefits of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-specific context, implementation and scale."},{"question":"What roles can Carbon Dioxide Removal (CDR) fulfill in climate change mitigation?","answer":"CDR can fulfill three complementary roles: lowering net CO2 or net GHG emissions in the near term; counterbalancing 'hard-to-abate' residual emissions to help reach net zero CO2 or GHG emissions; and achieving net negative CO2 or GHG emissions if deployed at levels exceeding annual residual emissions."}],"seed_document_id":193,"topic":"Climate Change Action"}}
{"id":"1c85d42e-cadd-4efb-8890-4a3fd2b11708","question":"In the context of the IPCC report, what do the three dots (...) signify in the projected global warming levels and how are the projected pathways categorized?","reference_answer":"The three dots (...) in the IPCC report's projected global warming levels signify that the value cannot be given, while the projected pathways are categorized according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels.","reference_context":"Document 172: with the 5th-95th percentile \ninterval in square brackets. \nPercentage of net zero \npathways is denoted in \nround brackets. \nThree dots (\u2026) denotes net \nzero not reached for that \npercentile.\nMedian cumulative net CO2 \nemissions across the \nprojected scenarios in this \ncategory until reaching \nnet-zero or until 2100, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected temperature \nchange of pathways in this \ncategory (50% probability \nacross the range of climate \nuncertainties), relative to \n1850-1900, at peak \nwarming and in 2100, for \nthe median value across the \nscenarios and the 5th-95th \npercentile interval in square \nbrackets.\nMedian likelihood that the \nprojected pathways in this \ncategory stay below a given \nglobal warming level, with \nthe 5th-95th percentile \ninterval in square brackets.\nProjected median GHG \nemissions reductions of \npathways in the year across \nthe scenarios compared to \nmodelled 2019, with the \n5th-95th percentile in \nbrackets. Negative numbers \nindicate increase in \nemissions compared to 2019\nModelled global emissions \npathways categorised by \nprojected global warming \nlevels (GWL). Detailed \nlikelihood definitions are \nprovided in SPM Box1.  \nThe five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.\n\nDocument 175: 1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs. {WGIII Table SPM.2}\n1 Detailed explanations on the Table are provided in WGIII Box SPM.1 and WGIII Table SPM.2. The relationship between the temperature categories and SSP\/RCPs is discussed \nin Cross-Section Box.2. Values in the table refer to the 50th and [5\u201395th] percentile values across the pathways falling within a given category as de\ufb01ned in WGIII Box SPM.1. \nThe three dots (\u2026) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net zero is not reached). Based on the assessment of climate emulators \nin AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment of the resulting warming of the pathways. For the \u2018Temperature Change\u2019 \nand \u2018Likelihood\u2019 columns, the non-bracketed values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming \nestimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges in the \u201clikelihood\u201d column, the median warming for every pathway in that category \nis calculated for each of the two climate model emulators (MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate \nemulators\u2019 uncertainty. All global warming levels are relative to 1850-1900. \n2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4.\n\nDocument 173: The five illustrative scenarios \n(SSPx-yy) considered by AR6 \nWGI and the Illustrative \n(Mitigation) Pathways \nassessed in WGIII are \naligned with the tempera-\nture categories and are \nindicated in a separate \ncolumn. Global emission \npathways contain regionally \ndifferentiated information. \nThis assessment focuses on \ntheir global characteristics.\n-.\n(41%)\n[2080-.]\n.-.\n(12%) \n[2090-.]\nno\nnet-zero\nno\npeaking\nby 2100\nno\nnet-zero\nno\nnet-zero\n1780\n[1260-2360]\n2790\n[2440-3520]\n[1.4-1.6]\n[1.4-1.6]\n[1.5-1.6]\n[1.5-1.8]\n[1.6-1.8]\n[1.6-1.8]\n[1.6-1.8]\n[1.7-2.0]\n[1.9-2.5]\n[1.1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.\n\nDocument 174: 1-1.5]\n[1.1-1.4]\n[1.3-1.5]\n[1.2-1.5]\n[1.5-1.8]\n[1.5-1.8]\n[1.5-1.7]\n[1.5-2.0]\n[1.9-2.5]\n[2.4-2.9]\n2.2\n2.1\n2.7\n4\n[0-10]\n37\n[18-59]\n[83-98]\n71\n0\n[0-0]\n8\n[2-18]\n[53-88]\nCategory\/\nsubset \nlabel \nlimit \nwarming \nto 1.5\u00b0C \n(>50%) \nwith no \nor \nlimited \novershoot\n\u2026\nwith \nnet zero \nGHGs \n\u2026 \nwithout \nnet zero \nGHGs\nreturn \nwarming \nto 1.5\u00b0C \n(>50%) \nafter a \nhigh \novershoot\nlimit \nwarming \nto 2\u00b0C \n(>67%) \n\u2026\nwith \naction \nstarting \nin 2020 \n\u2026\nNDCs \nuntil \n2030 \nlimit\nwarming\nto 2\u00b0C\n(>50%)\nlimit\nwarming\nto 2.5\u00b0C\n(>50%)\nlimit\nwarming\nto 3\u00b0C\n(>50%)\n[212]\nCategory \n(2) \n[# pathways]\nC1\n[97]\nC1a\n[50]\nC1b\n[47]\nC2\n[133]\nC3\n[311]\nC3a \n[204]\nC3b\n[97]\nC4\n[159]\nC5\nC6\n[97]\nTable 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global \nwarming outcomes. Pathways are categorised (columns), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) \nand 2100 warming levels. Values shown are for the median [p50] and 5\u201395th percentiles [p5\u2013p95], noting that not all pathways achieve net zero CO2 or GHGs.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What do the three dots (...) signify in the context of the IPCC report's projected global warming levels?","answer":"The three dots (...) denote that the value cannot be given, either because the value is after 2100 or, for net zero, net zero is not reached."},{"question":"How are the projected pathways categorized in the IPCC report?","answer":"Projected pathways are categorized according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels."}],"seed_document_id":172,"topic":"Climate Change Scenarios"}}
{"id":"33a4eb9d-0a9a-45a4-b7a2-af9c022d46d9","question":"By what year do 100% of the net zero CO2 pathways need to be achieved according to the data provided, and what is the likelihood of peak global warming staying below 1.5\u00b0C?","reference_answer":"100% of the net zero CO2 pathways need to be achieved by 2050-2055, and the likelihood of peak global warming staying below 1.5\u00b0C is 38% [33-58%].","reference_context":"Document 169: 84\nSection 3\nSection 1\nSection 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n2030 \n43 \n[34-60]\n41 \n[31-59]\n48 \n[35-61]\n23 \n[0-44]\n21 \n[1-42]\n27 \n[13-45]\n5 \n[0-14]\n10  \n[0-27]\n2040\n \n \n \n \n \n2050 \n84 \n[73-98]\n85 \n[72-100]\n84 \n[76-93]\n75 \n[62-91]\n64 \n[53-77]\n63 \n[52-76]\n68 \n[56-83]\n49  \n[35-65]\n29\n[11-48]\n5\n[-2 to 18]\nNet zero \nCO2  \n(% net zero \npathways) \n \n2050-2055 (100%) \n[2035-2070]\n2055-2060 \n(100%) \n[2045-2070]\n2070-2075 \n(93%) \n[2055-.]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.\n\nDocument 170: ]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.]\n \n2020 to \nnet zero \nCO2  \n510 \n[330-710]\n550 \n[340-760]\n460 \n[320-590]\n720 \n[530-930]\n890 \n[640-1160]\n860 \n[640-1180]\n910 \n[720-1150]\n1210\n[970-1490]\n1780\n[1400-2360]\n2020\u2013\n2100 \n320 \n[-210-570]\n160 \n[-220-620]\n360 \n[10-540]\n400 \n[-90-620]\n800 \n[510-1140]\n790 \n[480-1150]\n800 \n[560-1050]\n1160 \n[700-1490]\n \nat peak \nwarming\n \n1.6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"By what year do 100% of the net zero CO2 pathways need to be achieved according to the data provided?","answer":"100% of the net zero CO2 pathways need to be achieved by 2050-2055."},{"question":"What is the likelihood of peak global warming staying below 1.5\u00b0C?","answer":"The likelihood of peak global warming staying below 1.5\u00b0C is 38% [33-58%]."}],"seed_document_id":169,"topic":"Climate Change Scenarios"}}
{"id":"d558c88a-d388-455b-a225-911f32dc1826","question":"What does the area of the rectangles represent in the regional GHG emissions figures, and what has been the main driver of the global upper ocean warming since the 1970s?","reference_answer":"In the regional GHG emissions figures, the area of the rectangles represents the total emissions for each region, and human influence has been the main driver of the global upper ocean warming since the 1970s.","reference_context":"Document 28: The height of each rectangle shows per capita emissions, the width shows the population of the region, so that the area of the rectangles \nrefers to the total emissions for each region. Emissions from international aviation and shipping are not included. In the case of two regions, the area for CO2-LULUCF is below the \naxis, indicating net CO2 removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr\u20131 (GWP100-AR6)) for the time period \n1990\u20132019. Percentage values refer to the contribution of each region to total GHG emissions in each respective time period. The single-year peak of emissions in 1997 was due to \nhigher CO2-LULUCF emissions from a forest and peat \ufb01re event in South East Asia. Regions are as grouped in Annex II of WGIII. Panel (d) shows population, gross domestic product \n(GDP) per person, emission indicators by region in 2019 for total GHG per person, and total GHG emissions intensity, together with production-based and consumption-based CO2-FFI data, \nwhich is assessed in this report up to 2018. Consumption-based emissions are emissions released to the atmosphere in order to generate the goods and services consumed by a \ncertain entity (e.g., region). Emissions from international aviation and shipping are not included. {WGIII Figure SPM.2}\n2.1.2. Observed Climate System Changes and Impacts to \nDate\nIt is unequivocal that human in\ufb02uence has warmed the \natmosphere, ocean and land. Widespread and rapid changes in \nthe atmosphere, ocean, cryosphere and biosphere have occurred \n(Table 2.1). The scale of recent changes across the climate system as \na whole and the present state of many aspects of the climate system \nare unprecedented over many centuries to many thousands of years. It \nis very likely that GHG emissions were the main driver74 of tropospheric \nwarming and extremely likely that human-caused stratospheric ozone \ndepletion was the main driver of stratospheric cooling between 1979 \nand the mid-1990s.\n\nDocument 27: 46\nSection 2\nSection 1\nSection 2\nFigure 2.2: Regional GHG emissions, and the regional proportion of total cumulative production-based CO2 emissions from 1850 to 2019. Panel (a) shows the \nshare of historical cumulative net anthropogenic CO2 emissions per region from 1850 to 2019 in GtCO2. This includes CO2-FFI and CO2-LULUCF. Other GHG emissions are not included. \nCO2-LULUCF emissions are subject to high uncertainties, re\ufb02ected by a global uncertainty estimate of \u00b170% (90% con\ufb01dence interval). Panel (b) shows the distribution of regional \nGHG emissions in tonnes CO2-eq per capita by region in 2019. GHG emissions are categorised into: CO2-FFI; net CO2-LULUCF; and other GHG emissions (CH4, N2O, \ufb02uorinated gases, \nexpressed in CO2-eq using GWP100-AR6). The height of each rectangle shows per capita emissions, the width shows the population of the region, so that the area of the rectangles \nrefers to the total emissions for each region. Emissions from international aviation and shipping are not included. In the case of two regions, the area for CO2-LULUCF is below the \naxis, indicating net CO2 removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr\u20131 (GWP100-AR6)) for the time period \n1990\u20132019. Percentage values refer to the contribution of each region to total GHG emissions in each respective time period. The single-year peak of emissions in 1997 was due to \nhigher CO2-LULUCF emissions from a forest and peat \ufb01re event in South East Asia. Regions are as grouped in Annex II of WGIII.\n\nDocument 29: Emissions from international aviation and shipping are not included. {WGIII Figure SPM.2}\n2.1.2. Observed Climate System Changes and Impacts to \nDate\nIt is unequivocal that human in\ufb02uence has warmed the \natmosphere, ocean and land. Widespread and rapid changes in \nthe atmosphere, ocean, cryosphere and biosphere have occurred \n(Table 2.1). The scale of recent changes across the climate system as \na whole and the present state of many aspects of the climate system \nare unprecedented over many centuries to many thousands of years. It \nis very likely that GHG emissions were the main driver74 of tropospheric \nwarming and extremely likely that human-caused stratospheric ozone \ndepletion was the main driver of stratospheric cooling between 1979 \nand the mid-1990s. It is virtually certain that the global upper ocean \n(0-700m) has warmed since the 1970s and extremely likely that \nhuman in\ufb02uence is the main driver. Ocean warming accounted for \n91% of the heating in the climate system, with land warming, ice loss \nand atmospheric warming accounting for about 5%, 3% and 1%, \nrespectively (high con\ufb01dence). Global mean sea level increased by 0.20 \n[0.15 to 0.25] m between 1901 and 2018. The average rate of sea level \nrise was 1.3 [0.6 to 2.1]mm yr-1 between 1901 and 1971, increasing to \n1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and further increasing \nto 3.7 [3.2 to \u20134.2] mm yr-1 between 2006 and 2018 (high con\ufb01dence). \nHuman in\ufb02uence was very likely the main driver of these increases \nsince at least 1971 (Figure 3.4).","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What does the area of the rectangles represent in the regional GHG emissions figures?","answer":"In the regional GHG emissions figures, the area of the rectangles refers to the total emissions for each region."},{"question":"What has been the main driver of the global upper ocean warming since the 1970s?","answer":"Human influence is the main driver of the global upper ocean warming since the 1970s."}],"seed_document_id":28,"topic":"Others"}}
{"id":"c091970e-c0cb-47be-a678-5d19818d9676","question":"According to the report, what is the likelihood of peak global warming staying below 1.5\u00b0C and by what year do modelled pathways reach net zero CO2 emissions to limit warming to 1.5\u00b0C with no or limited overshoot?","reference_answer":"The likelihood of peak global warming staying below 1.5\u00b0C ranges from 11% to 38%, and modelled pathways that aim to limit warming to 1.5\u00b0C with no or limited overshoot reach net zero CO2 emissions around 2050.","reference_context":"Document 170: ]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.]\n \n2020 to \nnet zero \nCO2  \n510 \n[330-710]\n550 \n[340-760]\n460 \n[320-590]\n720 \n[530-930]\n890 \n[640-1160]\n860 \n[640-1180]\n910 \n[720-1150]\n1210\n[970-1490]\n1780\n[1400-2360]\n2020\u2013\n2100 \n320 \n[-210-570]\n160 \n[-220-620]\n360 \n[10-540]\n400 \n[-90-620]\n800 \n[510-1140]\n790 \n[480-1150]\n800 \n[560-1050]\n1160 \n[700-1490]\n \nat peak \nwarming\n \n1.6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.\n\nDocument 169: 84\nSection 3\nSection 1\nSection 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n2030 \n43 \n[34-60]\n41 \n[31-59]\n48 \n[35-61]\n23 \n[0-44]\n21 \n[1-42]\n27 \n[13-45]\n5 \n[0-14]\n10  \n[0-27]\n2040\n \n \n \n \n \n2050 \n84 \n[73-98]\n85 \n[72-100]\n84 \n[76-93]\n75 \n[62-91]\n64 \n[53-77]\n63 \n[52-76]\n68 \n[56-83]\n49  \n[35-65]\n29\n[11-48]\n5\n[-2 to 18]\nNet zero \nCO2  \n(% net zero \npathways) \n \n2050-2055 (100%) \n[2035-2070]\n2055-2060 \n(100%) \n[2045-2070]\n2070-2075 \n(93%) \n[2055-.]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.\n\nDocument 181: 86\nSection 3\nSection 1\nSection 3\n2000\n2020\n2040\n2060\n2080\n2100\n0\n20\n40\n60\n2000\n2020\n2040\n2060\n2080\n2100\n0\n20\n40\n60\n2000\n2020\n2040\n2060\n2080\n2100\n2000\n2020\n2040\n2060\n2080\n2100\nGigatons of CO2 equivalent per year (GtCO2-eq\/yr) \nCO2\nGHG\nCO2\nGHG\nCH4\nCO2\nGHG\nCH4\na) While keeping warming to 1.5\u00b0C    \n(>50%) with no or limited overshoot\nb) While keeping warming to  2\u00b0C    (>67%)\nc) Timing for net zero \nnet zero\nnet zero\nHistorical\nHistorical\nPolicies in place in 2020\nPolicies in place in 2020\nGHGs reach net zero \nlater than CO2\nnot all \nscenarios \nreach net \nzero GHG \nby 2100\nGlobal modelled pathways that limit warming to 1.5\u00b0C (>50%) with \nno or limited overshoot reach  net zero  CO2 emissions around 2050\nTotal  greenhouse gases (GHG)  reach net zero later\nFigure 3.6: Total GHG, CO2 and CH4 emissions and timing of reaching net zero in different mitigation pathways. Top row: GHG, CO2 and CH4 emissions over time (in \nGtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour \n(blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows \npathways that limit warming to 2\u00b0C (>67%) (C3).\n\nDocument 171: 6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.0\u00b0C \n90 \n[86-97]\n90 \n[85-97]\n89 \n[87-96]\n82 \n[71-93]\n76 \n[68-91]\n78 \n[69-91]\n73 \n[67-87]\n59\n[50-77]\n<3.0\u00b0C \n100 \n[99-100]\n100 \n[99-100]\n100 \n[99-100]\n100 \n[99-100]\n99 \n[98-100]\n100 \n[98-100]\n99 \n[98-99]\n98\n91\n \n[95-99]\n p50\n[p5-p95] (1)\nGHG emissions \nreductions\nfrom 2019 (%) (3)\u00a0\nEmissions milestones (4)\u00a0\nCumulative CO2\nemissions [Gt CO2](6)\nLikelihood of peak \nglobal warming staying \nbelow (%)\nGlobal mean \ntemperature \nchanges 50% \nprobability (\u00b0C)\n69\n[58-90]\n66\n[58-89]\n70\n[62-87]\n55\n[40-71]\n46\n[34-63]\n47\n[35-63]\n46\n[34-63]\n31\n[20-5]\n18\n[4-33]\n3\n[-14 to 14]\n6\n[-1 to 18]\n2\n[-10 to 11]\nMedian 5-year intervals at \nwhich projected CO2 & GHG \nemissions  of pathways in \nthis category reach net-zero, \nwith the 5th-95th percentile \ninterval in square brackets.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What is the likelihood of peak global warming staying below 1.5\u00b0C according to the report?","answer":"The likelihood of peak global warming staying below 1.5\u00b0C ranges from 11% to 38%, with different confidence intervals provided for various scenarios."},{"question":"By what year do global modelled pathways that limit warming to 1.5\u00b0C with no or limited overshoot reach net zero CO2 emissions?","answer":"Global modelled pathways that limit warming to 1.5\u00b0C with no or limited overshoot reach net zero CO2 emissions around 2050."}],"seed_document_id":170,"topic":"Climate Change Scenarios"}}
{"id":"b8fa390c-cf2f-4359-8faa-8df81e999b4c","question":"What role do individuals with high socio-economic status play in emissions and what potential do they have in terms of emissions reductions, and how can the revenue from carbon taxes or emissions trading be used?","reference_answer":"Individuals with high socio-economic status play a significant role in contributing to emissions but also have the highest potential for emissions reductions as citizens, investors, consumers, role models, and professionals, while the revenue from carbon taxes or emissions trading can be used to support equity and distributional goals, such as helping low-income households.","reference_context":"Document 242: 102\nSection 4\nSection 1\nSection 4\nand burdens, especially for vulnerable countries and communities. \n{WGIII SPM D.3, WGIII SPM D.3.2, WGIII SPM D.3.3, WGIII SPM D.3.4, \nWGIII TS Box TS.4}\nDevelopment priorities among countries also re\ufb02ect different \nstarting points and contexts, and enabling conditions for \nshifting development pathways towards increased sustainability \nwill therefore differ, giving rise to different needs (high \ncon\ufb01dence). Implementing just transition principles through collective \nand participatory decision-making processes is an effective way of \nintegrating equity principles into policies at all scales depending \non national circumstances, while in several countries just transition \ncommissions, task forces and national policies have been established \n(medium con\ufb01dence). {WGIII SPM D.3.1, WGIII SPM D.3.3}\nMany economic and regulatory instruments have been \neffective in reducing emissions and practical experience has \ninformed instrument design to improve them while addressing \ndistributional goals and social acceptance (high con\ufb01dence). The \ndesign of behavioural interventions, including the way that choices are \npresented to consumers work synergistically with price signals, making \nthe combination more effective (medium con\ufb01dence). Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence).\n\nDocument 243: Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence). Eradicating extreme poverty, energy poverty, and \nproviding decent living standards to all in these regions in the context of \nachieving sustainable development objectives, in the near term, can be \nachieved without signi\ufb01cant global emissions growth (high con\ufb01dence). \nTechnology development, transfer, capacity building and \ufb01nancing can \nsupport developing countries\/ regions leapfrogging or transitioning to \nlow-emissions transport systems thereby providing multiple co-bene\ufb01ts \n(high con\ufb01dence). Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence).\n\nDocument 281: Multi-level, \nhybrid and cross-sector governance facilitates appropriate consideration \nfor co-bene\ufb01ts and trade-offs, particularly in land sectors where decision \nprocesses range from farm level to national scale (high con\ufb01dence). \nConsideration of climate justice can help to facilitate shifting development \npathways towards sustainability. {WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, \nSRCCL TS.1}\nDrawing on diverse knowledge and partnerships, including \nwith women, youth, Indigenous Peoples, local communities, and \nethnic minorities can facilitate climate resilient development \nand has allowed locally appropriate and socially acceptable \nsolutions (high con\ufb01dence). {WGII SPM D.2, D.2.1}\nMany regulatory and economic instruments have already been \ndeployed successfully. These instruments could support deep \nemissions reductions if scaled up and applied more widely. \nPractical experience has informed instrument design and helped to \nimprove predictability, environmental effectiveness, economic ef\ufb01ciency, \nand equity. (high con\ufb01dence) {WGII SPM E.4; WGIII SPM E.4.2}\nScaling up and enhancing the use of regulatory instruments, \nconsistent with national circumstances, can improve mitigation \noutcomes in sectoral applications (high con\ufb01dence), and \nregulatory instruments that include \ufb02exibility mechanisms \ncan reduce costs of cutting emissions (medium con\ufb01dence). \n{WGII SPM C.5.4; WGIII SPM E.4.1} \nWhere implemented, carbon pricing instruments have incentivized \nlow-cost emissions reduction measures, but have been less \neffective, on their own and at prevailing prices during the \nassessment period, to promote higher-cost measures necessary \nfor further reductions (medium con\ufb01dence).\n\nDocument 282: Practical experience has informed instrument design and helped to \nimprove predictability, environmental effectiveness, economic ef\ufb01ciency, \nand equity. (high con\ufb01dence) {WGII SPM E.4; WGIII SPM E.4.2}\nScaling up and enhancing the use of regulatory instruments, \nconsistent with national circumstances, can improve mitigation \noutcomes in sectoral applications (high con\ufb01dence), and \nregulatory instruments that include \ufb02exibility mechanisms \ncan reduce costs of cutting emissions (medium con\ufb01dence). \n{WGII SPM C.5.4; WGIII SPM E.4.1} \nWhere implemented, carbon pricing instruments have incentivized \nlow-cost emissions reduction measures, but have been less \neffective, on their own and at prevailing prices during the \nassessment period, to promote higher-cost measures necessary \nfor further reductions (medium con\ufb01dence). Revenue from carbon \ntaxes or emissions trading can be used for equity and distributional \ngoals, for example to support low-income households, among other \n4.7 Governance and Policy for Near-Term Climate Change Action\nEffective climate action requires political commitment, well-aligned multi-level governance and institutional \nframeworks, laws, policies and strategies. It needs clear goals, adequate \ufb01nance and \ufb01nancing tools, coordination \nacross multiple policy domains, and inclusive governance processes. Many mitigation and adaptation policy \ninstruments have been deployed successfully, and could support deep emissions reductions and climate resilience \nif scaled up and applied widely, depending on national circumstances. Adaptation and mitigation action bene\ufb01ts \nfrom drawing on diverse knowledge. (high con\ufb01dence)","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What role do individuals with high socio-economic status play in emissions, and what potential do they have in terms of emissions reductions?","answer":"Individuals with high socio-economic status contribute disproportionately to emissions and have the highest potential for emissions reductions, for example, as citizens, investors, consumers, role models, and professionals."},{"question":"How can the revenue from carbon taxes or emissions trading be used?","answer":"Revenue from carbon taxes or emissions trading can be used for equity and distributional goals, for example to support low-income households."}],"seed_document_id":242,"topic":"Climate Change Action"}}
{"id":"1a3c940f-c9ab-4123-ae64-35a8e0955297","question":"According to the IPCC report, what are the consequences of the current rates of adaptation planning and implementation, and how are losses and damages due to climate change distributed?","reference_answer":"The IPCC report indicates that at current rates of adaptation planning and implementation, the adaptation gap will continue to grow, with efforts falling short of meeting goals, and that losses and damages due to climate change are unequally distributed and not adequately addressed, especially in vulnerable developing countries.","reference_context":"Document 93: Many funding, knowledge and practice gaps remain for effective \nimplementation, monitoring and evaluation and current adaptation \nefforts are not expected to meet existing goals (high con\ufb01dence). \nAt current rates of adaptation planning and implementation the \nadaptation gap will continue to grow (high con\ufb01dence). {WGII SPM C.1, \nWGII SPM C.1.2, WGII SPM C.4.1, WGII TS.D.1.3, WGII TS.D.1.4} \nSoft and hard adaptation limits100 have already been reached in \nsome sectors and regions, in spite of adaptation having buffered \nsome climate impacts (high con\ufb01dence). Ecosystems already \nreaching hard adaptation limits include some warm water coral reefs, \nsome coastal wetlands, some rainforests, and some polar and mountain \necosystems (high con\ufb01dence). Individuals and households in low lying \ncoastal areas in Australasia and Small Islands and smallholder farmers \nin Central and South America, Africa, Europe and Asia have reached \nsoft limits (medium con\ufb01dence), resulting from \ufb01nancial, governance, \ninstitutional and policy constraints and can be overcome by addressing \nthese constraints (high con\ufb01dence). Transitioning from incremental to \ntransformational adaptation can help overcome soft adaptation limits \n(high con\ufb01dence). {WGII SPM C.3, WGII SPM C.3.1, WGII SPM C.3.2, \nWGII SPM C.3.3, WGII SPM.C.3.4, WGII 16 ES}\nAdaptation does not prevent all losses and damages, even with \neffective adaptation and before reaching soft and hard limits. Losses \nand damages are unequally distributed across systems, regions and \nsectors and are not comprehensively addressed by current \ufb01nancial, \ngovernance and institutional arrangements, particularly in vulnerable \ndeveloping countries. (high con\ufb01dence) {WGII SPM.C.3.5}\nThere is increased evidence of maladaptation101 in various sectors \nand regions.\n\nDocument 92: Most often, maladaptation is an unintended consequence. See Annex I: Glossary.\n2.3.2. Adaptation Gaps and Barriers \nDespite progress, adaptation gaps exist between current \nlevels of adaptation and levels needed to respond to impacts \nand reduce climate risks (high con\ufb01dence). While progress in \nadaptation implementation is observed across all sectors and regions \n(very high con\ufb01dence), many adaptation initiatives prioritise immediate \nand near-term climate risk reduction, e.g., through hard \ufb02ood protection, \nwhich reduces the opportunity for transformational adaptation99 (high \ncon\ufb01dence). Most observed adaptation is fragmented, small in scale, \nincremental, sector-speci\ufb01c, and focused more on planning rather than \nimplementation (high con\ufb01dence). Further, observed adaptation is \nunequally distributed across regions and the largest adaptation gaps \nexist among lower population income groups (high con\ufb01dence). In the \nurban context, the largest adaptation gaps exist in projects that manage \ncomplex risks, for example in the food\u2013energy\u2013water\u2013health nexus or \nthe inter-relationships of air quality and climate risk (high con\ufb01dence). \nMany funding, knowledge and practice gaps remain for effective \nimplementation, monitoring and evaluation and current adaptation \nefforts are not expected to meet existing goals (high con\ufb01dence). \nAt current rates of adaptation planning and implementation the \nadaptation gap will continue to grow (high con\ufb01dence). {WGII SPM C.1, \nWGII SPM C.1.2, WGII SPM C.4.1, WGII TS.D.1.3, WGII TS.D.1.4} \nSoft and hard adaptation limits100 have already been reached in \nsome sectors and regions, in spite of adaptation having buffered \nsome climate impacts (high con\ufb01dence). Ecosystems already \nreaching hard adaptation limits include some warm water coral reefs, \nsome coastal wetlands, some rainforests, and some polar and mountain \necosystems (high con\ufb01dence).\n\nDocument 96: Inequity and poverty also constrain \nadaptation, leading to soft limits and resulting in disproportionate \nexposure and impacts for most vulnerable groups (high con\ufb01dence). The \nlargest adaptation gaps exist among lower income population groups \n(high con\ufb01dence). \nAs adaptation options often have long implementation \ntimes, long-term planning and accelerated implementation, particularly \nin this decade, is important to close adaptation gaps, recognising that \nconstraints remain for some regions (high con\ufb01dence). Prioritisation of \noptions and transitions from incremental to transformational adaptation \nare limited due to vested interests, economic lock-ins, institutional \npath dependencies and prevalent practices, cultures, norms and belief \nsystems (high con\ufb01dence). Many funding, knowledge and practice \ngaps remain for effective implementation, monitoring and evaluation \nof adaptation (high con\ufb01dence), including, lack of climate literacy at \nall levels and limited availability of data and information (medium \ncon\ufb01dence); for example for Africa, severe climate data constraints and \ninequities in research funding and leadership reduce adaptive capacity \n(very high con\ufb01dence). {WGII SPM C.1.2, WGII SPM C.3.1, WGII TS.D.1.3, \nWGII TS.D.1.5, WGII TS.D.2.4}\n2.3.3. Lack of Finance as a Barrier to Climate Action \nInsuf\ufb01cient \ufb01nancing, and a lack of political frameworks and \nincentives for \ufb01nance, are key causes of the implementation \ngaps for both mitigation and adaptation (high con\ufb01dence). \nFinancial \ufb02ows remained heavily focused on mitigation, are \nuneven, and have developed heterogeneously across regions \nand sectors (high con\ufb01dence). In 2018, public and publicly mobilised \nprivate climate \ufb01nance \ufb02ows from developed to developing countries \nwere below the collective goal under the UNFCCC and Paris Agreement \nto mobilise USD 100 billion per year by 2020 in the context of \nmeaningful mitigation action and transparency on implementation \n(medium con\ufb01dence).\n\nDocument 94: Transitioning from incremental to \ntransformational adaptation can help overcome soft adaptation limits \n(high con\ufb01dence). {WGII SPM C.3, WGII SPM C.3.1, WGII SPM C.3.2, \nWGII SPM C.3.3, WGII SPM.C.3.4, WGII 16 ES}\nAdaptation does not prevent all losses and damages, even with \neffective adaptation and before reaching soft and hard limits. Losses \nand damages are unequally distributed across systems, regions and \nsectors and are not comprehensively addressed by current \ufb01nancial, \ngovernance and institutional arrangements, particularly in vulnerable \ndeveloping countries. (high con\ufb01dence) {WGII SPM.C.3.5}\nThere is increased evidence of maladaptation101 in various sectors \nand regions. Examples of maladaptation are observed in urban areas \n(e.g., new urban infrastructure that cannot be adjusted easily or affordably), \nagriculture (e.g., using high-cost irrigation in areas projected to have more \nintense drought conditions), ecosystems (e.g. \ufb01re suppression in naturally","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the consequences of the current rates of adaptation planning and implementation according to the IPCC report?","answer":"At current rates of adaptation planning and implementation, the adaptation gap will continue to grow, and current adaptation efforts are not expected to meet existing goals."},{"question":"What does the IPCC report say about the distribution of losses and damages due to climate change?","answer":"Losses and damages are unequally distributed across systems, regions, and sectors and are not comprehensively addressed by current financial, governance, and institutional arrangements, particularly in vulnerable developing countries."}],"seed_document_id":93,"topic":"Climate Change Action"}}
{"id":"89be67ef-fab6-48a7-9174-e98a4624e5fa","question":"What are the key strategies for reaching net zero CO2 and GHG emissions according to the IPCC report, and what are the potential barriers to implementing AFOLU mitigation options that can affect carbon stored in vegetation and soils?","reference_answer":"The key strategies for reaching net zero CO2 and GHG emissions include transitioning to very low- or zero-carbon energy sources, demand-side measures, improving efficiency, reducing non-CO2 GHG emissions, and carbon dioxide removal (CDR). The potential barriers to implementing AFOLU mitigation options are impacts of climate change, competing land demands, conflicts with food security and livelihoods, complex land ownership and management systems, and cultural aspects. These barriers can put at risk the carbon stored in vegetation and soils, making it susceptible to future loss or sink reversal due to climate change, disturbances, or poor management.","reference_context":"Document 184: Enabling \nconditions such as policy instruments, greater public support and technological innovation could reduce these barriers. (high con\ufb01dence) {WGIII SPM C.4.6}\ninfrastructure design and access. (high con\ufb01dence) {WGIII SPM C.3, \nWGIII SPM C.5, WGIII SPM C.6, WGIII SPM C.7.3, WGIII SPM C.8, \nWGIII SPM C.10.2} \nGlobal modelled mitigation pathways reaching net zero CO2 and \nGHG emissions include transitioning from fossil fuels without \ncarbon capture and storage (CCS) to very low- or zero-carbon \nenergy sources, such as renewables or fossil fuels with CCS, \ndemand-side measures and improving ef\ufb01ciency, reducing \nnon-CO2 GHG emissions, and CDR136. In global modelled pathways \nthat limit warming to 2\u00b0C or below, almost all electricity is supplied\n\nDocument 185: 87\nLong-Term Climate and Development Futures\nSection 3\nfrom zero or low-carbon sources in 2050, such as renewables or \nfossil fuels with CO2 capture and storage, combined with increased \nelectri\ufb01cation of energy demand. Such pathways meet energy service \ndemand with relatively low energy use, through e.g., enhanced energy \nef\ufb01ciency and behavioural changes and increased electri\ufb01cation of \nenergy end use. Modelled global pathways limiting global warming to \n1.5\u00b0C (>50%) with no or limited overshoot generally implement such \nchanges faster than pathways limiting global warming to 2\u00b0C (>67%). \n(high con\ufb01dence) {WGIII SPM C.3, WGIII SPM C.3.2, WGIII SPM C.4, \nWGIII TS.4.2; SR1.5 SPM C.2.2}\nAFOLU mitigation options, when sustainably implemented, can \ndeliver large-scale GHG emission reductions and enhanced CO2 \nremoval; however, barriers to implementation and trade-offs \nmay result from the impacts of climate change, competing \ndemands on land, con\ufb02icts with food security and livelihoods, \nthe complexity of land ownership and management systems, \nand cultural aspects (see 3.4.1). All assessed modelled pathways \nthat limit warming to 2\u00b0C (>67%) or lower by 2100 include land-based \nmitigation and land-use change, with most including different \ncombinations of reforestation, afforestation, reduced deforestation, and \nbioenergy. However, accumulated carbon in vegetation and soils is at \nrisk from future loss (or sink reversal) triggered by climate change and \ndisturbances such as \ufb02ood, drought, \ufb01re, or pest outbreaks, or future \npoor management.\n\nDocument 220: {WGII SPM D.2; WGIII SPM E.1, WGIII SPM E.2}\nBarriers to feasibility would need to be reduced or removed \nto deploy mitigation and adaptation options at scale. Many \nlimits to feasibility and effectiveness of responses can be overcome \nby addressing a range of barriers, including economic, technological, \ninstitutional, social, environmental and geophysical barriers. The \nfeasibility and effectiveness of options increase with integrated, \nmulti-sectoral solutions that differentiate responses based on climate \nrisk, cut across systems and address social inequities. Strengthened \nnear-term actions in modelled cost-effective pathways that limit global \nwarming to 2\u00b0C or lower, reduce the overall risk to the feasibility of the \nsystem transitions, compared to modelled pathways with delayed or \nuncoordinated action. (high con\ufb01dence) {WGII SPM C.2, WGII SPM C.3, \nWGII SPM C.5; WGIII SPM E.1, WGIII SPM E.1.3}\nIntegrating ambitious climate actions with macroeconomic \npolicies under global uncertainty would provide benefits \n(high confidence). This encompasses three main directions: \n(a) economy-wide mainstreaming packages supporting options to \nimproved sustainable low-emission economic recovery, development \nand job creation programs (Sections 4.4, 4.5, 4.6, 4.8, 4.9) (b) safety \nnets and social protection in the transition (Section 4.4, 4.7); and \n(c) broadened access to \ufb01nance, technology and capacity-building \nand coordinated support to low-emission infrastructure (\u2018leap-frog\u2019 \npotential), especially in developing regions, and under debt stress \n(high con\ufb01dence).\n\nDocument 243: Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence). Eradicating extreme poverty, energy poverty, and \nproviding decent living standards to all in these regions in the context of \nachieving sustainable development objectives, in the near term, can be \nachieved without signi\ufb01cant global emissions growth (high con\ufb01dence). \nTechnology development, transfer, capacity building and \ufb01nancing can \nsupport developing countries\/ regions leapfrogging or transitioning to \nlow-emissions transport systems thereby providing multiple co-bene\ufb01ts \n(high con\ufb01dence). Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the key strategies for reaching net zero CO2 and GHG emissions according to the IPCC report?","answer":"Key strategies include transitioning from fossil fuels without carbon capture and storage (CCS) to very low- or zero-carbon energy sources, demand-side measures and improving efficiency, reducing non-CO2 GHG emissions, and carbon dioxide removal (CDR)."},{"question":"What are the potential barriers to implementing AFOLU mitigation options and how can they affect carbon stored in vegetation and soils?","answer":"Barriers to implementing AFOLU mitigation options include impacts of climate change, competing demands on land, conflicts with food security and livelihoods, complexity of land ownership and management systems, and cultural aspects. Accumulated carbon in vegetation and soils is at risk from future loss or sink reversal due to climate change and disturbances such as floods, droughts, fires, or pest outbreaks, or from future poor management."}],"seed_document_id":184,"topic":"Climate Change Action"}}
{"id":"0538a43b-ac86-46f5-855d-0c474aa6dd5c","question":"How much has the global surface temperature increased by 2011-2020 compared to 1850-1900, and what are the main human activities responsible for the observed increases in greenhouse gas concentrations since around 1750?","reference_answer":"The global surface temperature has increased by around 1.1\u00b0C above 1850\u20131900 in 2011\u20132020, and the main human activities responsible for the observed increases in greenhouse gas concentrations since around 1750 include emissions from unsustainable energy use, land use and land-use change, and certain patterns of consumption and production.","reference_context":"Document 10: 42\nSection 2\nSection 1\nSection 2\n2.1 Observed Changes, Impacts and Attribution\nHuman activities, principally through emissions of greenhouse gases, have unequivocally caused global warming, \nwith global surface temperature reaching 1.1\u00b0C above 1850\u20131900 in 2011\u20132020. Global greenhouse gas emissions \nhave continued to increase over 2010\u20132019, with unequal historical and ongoing contributions arising from \nunsustainable energy use, land use and land-use change, lifestyles and patterns of consumption and production \nacross regions, between and within countries, and between individuals (high con\ufb01dence). Human-caused climate \nchange is already affecting many weather and climate extremes in every region across the globe. This has led to \nwidespread adverse impacts on food and water security, human health and on economies and society and related \nlosses and damages63 to nature and people (high con\ufb01dence). Vulnerable communities who have historically \ncontributed the least to current climate change are disproportionately affected (high con\ufb01dence).\n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\nSection 2: Current Status and Trends\n2.1.1. Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900.\n\nDocument 11: Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900. Global \nsurface temperature has increased faster since 1970 than in any other \n50-year period over at least the last 2000 years (high con\ufb01dence). The \nlikely range of total human-caused global surface temperature increase \nfrom 1850\u20131900 to 2010\u2013201966 is 0.8\u00b0C to 1.3\u00b0C, with a best estimate \nof 1.07\u00b0C. It is likely that well-mixed GHGs67 contributed a warming \nof 1.0\u00b0C to 2.0\u00b0C, and other human drivers (principally aerosols) \ncontributed a cooling of 0.0\u00b0C to 0.8\u00b0C, natural (solar and volcanic) \ndrivers changed global surface temperature by \u00b10.1\u00b0C and internal \nvariability changed it by \u00b10.2\u00b0C. {WGI SPM A.1, WGI SPM A.1.2, \nWGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2}\nObserved increases in well-mixed GHG concentrations since around \n1750 are unequivocally caused by GHG emissions from human activities.\n\nDocument 12: It is likely that well-mixed GHGs67 contributed a warming \nof 1.0\u00b0C to 2.0\u00b0C, and other human drivers (principally aerosols) \ncontributed a cooling of 0.0\u00b0C to 0.8\u00b0C, natural (solar and volcanic) \ndrivers changed global surface temperature by \u00b10.1\u00b0C and internal \nvariability changed it by \u00b10.2\u00b0C. {WGI SPM A.1, WGI SPM A.1.2, \nWGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2}\nObserved increases in well-mixed GHG concentrations since around \n1750 are unequivocally caused by GHG emissions from human activities. \nLand and ocean sinks have taken up a near-constant proportion \n(globally about 56% per year) of CO2 emissions from human activities over \n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\n64 \nThe estimated increase in global surface temperature since AR5 is principally due to further warming since 2003\u20132012 (+0.19 [0.16 to 0.22]\u00b0C). Additionally, methodological \nadvances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements \nhave also increased the estimate of global surface temperature change by approximately 0.1\u00b0C, but this increase does not represent additional physical warming since AR5 \n{WGI SPM A1.2 and footnote 10}\n65 \nFor 1850\u20131900 to 2013\u20132022 the updated calculations are 1.15 [1.00 to 1.25]\u00b0C for global surface temperature, 1.65 [1.36 to 1.90]\u00b0C for land temperatures and \n0.93 [0.73 to 1.04]\u00b0C for ocean temperatures above 1850\u20131900 using the exact same datasets (updated by 2 years) and methods as employed in WGI.\n\nDocument 15: 43\nCurrent Status and Trends\nSection 2\nIncreased concentrations \nof GHGs in the atmosphere\nIncreased emissions of \ngreenhouse gases (GHGs)\nb)\na)\nc) Changes in global surface temperature\nCarbon dioxide\nMethane\nd) Humans are responsible\n0\n15\n30\n45\n60\n400\n350\n300\n1000\n1500\n500\n  \u20130.5\n\u20131.0\n0.0\n0.5\n1.0\n1.5\n2.0\nObserved\n\u20130.5\n\u20131.0\n0.0\n0.5\n1.0\n1.5\n2.0\nTotal human in\ufb02uence\nObserved warming\nWell-mixed GHG\nOther human drivers*\nSolar and volcanic drivers\nInternal variability\nObserved warming is driven by emissions \nfrom human activities with GHG warming \npartly masked by aerosol cooling 2010\u20132019 \n(change from 1850\u20131900) \n1.0\n0.2\nGlobal surface temperature has increased by \n1.1\u00b0C by 2011-2020 compared to 1850-1900\nConcentrations of GHGs have increased rapidly since 1850\n(scaled to match their assessed contributions to warming over 1850\u20131900 \nto 2010\u20132019)\nGreenhouse gas (GHG) emissions resulting \nfrom human activities continue to increase\nHuman activities are responsible for global warming\n1850\n1900\n1950\n2000\n2020\n1850\n1900\n1950\n2000\n2019\nNon-CO2 \nemissions\nCO2 from \nfossil fuels \nand industry \nParts per million (ppm)\nGHG Emissions (GtCO2-eq\/yr)\nParts per billion (ppb)\n\u00b0C\n1850\n1900\n1950\n2000\n2019\n\u00b0C\nCO2 from Land \nUse, Land-Use \nChange and \nForestry \n(LULUCF)\nwarmest \nmulti-century \nperiod in more \nthan 100,000 \nyears\n410 ppm CO2\n1866 ppb CH4\n332 ppb N2O\n200\n400 Parts per billion (ppb)\nNitrous oxide\n\u00b0C\n0\n0.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"How much has the global surface temperature increased by 2011-2020 compared to 1850-1900?","answer":"The global surface temperature has increased by around 1.1\u00b0C above 1850\u20131900 in 2011\u20132020."},{"question":"What are the main human activities responsible for the observed increases in greenhouse gas concentrations since around 1750?","answer":"The main human activities responsible for the observed increases in greenhouse gas concentrations since around 1750 are greenhouse gas emissions from human activities such as unsustainable energy use, land use and land-use change, and patterns of consumption and production."}],"seed_document_id":10,"topic":"Others"}}
{"id":"e049e1c2-322d-4369-8667-ccd3b0f144cb","question":"What is the purpose of the AR6 integrated assessment framework and the role of Shared Socio-economic Pathways (SSPs) as described in the IPCC report?","reference_answer":"The AR6 integrated assessment framework in the IPCC report is designed to assess future greenhouse gas emissions, climate change, risks, impacts, and mitigation, incorporating socio-economic development and policy, emissions pathways, and temperature responses to scenarios. Shared Socio-economic Pathways (SSPs) within this framework explore different challenges to mitigation and adaptation, shaping future vulnerability and exposure, and are linked to potential low or high warming levels based on GHG mitigation efforts.","reference_context":"Document 106: 65\nCurrent Status and Trends\nSection 2\nwhich drives\nthat change\nin\ufb02uence\nEmissions\na) AR6 integrated assessment framework on future climate, impacts and mitigation\nClimate\nImpacts \/ Risks\nMitigation Policy\nAdaptation Policy\nSocio-economic changes\n0\n1\n2\n3\n4\n5\n6\n7\n\u00b0C\nb) Scenarios and pathways across AR6 Working Group reports\nc) Determinants of risk\nTemperature for SSP-based scenarios over the \n21st century and C1-C8 at 2100\nRisks\ncan be \nrepresented as \n\u201cburning embers\u201d\nC1-C8 in 2100\nincreasing risk\n2050\n2100\n0\n50\n100\n2050\n2100\nGtCO2\/yr\nSSP1-1.9\nSSP1-2.6\nSSP2-4.5\nSSP3-7.0\nSSP5-8.5\nSSP1-1.9\nSSP1-2.6\nSSP2-4.5\nSSP3-7.0\nSSP5-8.5\nRFC1\nUnique and\nthreatened systems\ncolor shading shows \nC1-C8 category\ncolor shading shows \nrange for SSP3-7.0 \nand SSP1-2.6\nCategory \nin WGIII\nCategory description\nGHG emissions scenarios\n(SSPx-y*) in WGI & WGII \nRCPy** in\nWGI & WGII\nC1\nlimit warming to 1.5\u00b0C (>50%)\nwith no or limited overshoot\nVery low (SSP1-1.9)\nLow (SSP1-2.6) \nRCP2.6\nC2\nreturn warming to 1.5\u00b0C (>50%)\nafter a high overshoot\nC3\nlimit warming to 2\u00b0C (>67%)\nC4\nlimit warming to 2\u00b0C (>50%)\nC5\nlimit warming to 2.5\u00b0C (>50%)\nC6\nlimit warming to 3\u00b0C (>50%)\nIntermediate (SSP2-4.5)\nRCP 4.5\nRCP 8.\n\nDocument 109: 66\nSection 2\nSection 1\nSection 2\nCross-Section Box.2 Figure 1:\u00a0Schematic of the AR6 framework for assessing future greenhouse gas emissions, climate change, \nrisks, impacts and mitigation. Panel (a) The integrated framework encompasses socio-economic development and policy, emissions pathways \nand global surface temperature responses to the \ufb01ve scenarios considered by WGI (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and \neight global mean temperature change categorisations (C1\u2013C8) assessed by WGIII, and the WGII risk assessment. The dashed arrow indicates \nthat the in\ufb02uence from impacts\/risks to socio-economic changes is not yet considered in the scenarios assessed in the AR6. Emissions include \nGHGs, aerosols, and ozone precursors. CO2 emissions are shown as an example on the left. The assessed global surface temperature changes \nacross the 21st century relative to 1850-1900 for the \ufb01ve GHG emissions scenarios are shown as an example in the centre. Very likely ranges \nare shown for SSP1-2.6 and SSP3-7.0. Projected temperature outcomes at 2100 relative to 1850-1900 are shown for C1 to C8 categories with \nmedian (line) and the combined very likely range across scenarios (bar). On the right, future risks due to increasing warming are represented by \nan example \u2018burning ember\u2019 \ufb01gure (see 3.1.2 for the de\ufb01nition of RFC1). Panel (b) Description and relationship of scenarios considered across \nAR6 Working Group reports. Panel (c) Illustration of risk arising from the interaction of hazard (driven by changes in climatic impact-drivers) \nwith vulnerability, exposure and response to climate change. {WGI TS1.4, Figure 4.11; WGII Figure 1.5, WGII Figure 14.8; WGIII Table SPM.2, \nWGIII Figure 3.11}\n\nDocument 107: 0 \nand SSP1-2.6\nCategory \nin WGIII\nCategory description\nGHG emissions scenarios\n(SSPx-y*) in WGI & WGII \nRCPy** in\nWGI & WGII\nC1\nlimit warming to 1.5\u00b0C (>50%)\nwith no or limited overshoot\nVery low (SSP1-1.9)\nLow (SSP1-2.6) \nRCP2.6\nC2\nreturn warming to 1.5\u00b0C (>50%)\nafter a high overshoot\nC3\nlimit warming to 2\u00b0C (>67%)\nC4\nlimit warming to 2\u00b0C (>50%)\nC5\nlimit warming to 2.5\u00b0C (>50%)\nC6\nlimit warming to 3\u00b0C (>50%)\nIntermediate (SSP2-4.5)\nRCP 4.5\nRCP 8.5\nC7\nlimit warming to 4\u00b0C (>50%)\nHigh (SSP3-7.0)\nC8\nexceed warming of 4\u00b0C (>50%)\nVery high (SSP5-8.5)\nScenarios and warming levels structure our understanding across the \ncause-effect chain from emissions to climate change and risks\nCO2 emissions for SSP-based scenarios \nand C1-C8 categories\nVulnerability\nHazard\nResponse\nRisk\nExposure\nClimatic\nImpact-\nDrivers\n0\n1\n2\n3\n4\n5\n\u00b0C\nin\ufb02uence\nshape\n* The terminology SSPx-y is used, where \u2018SSPx\u2019 refers to the Shared Socio-economic Pathway or \u2018SSP\u2019 describing the socio-economic trends \nunderlying the scenario, and \u2018y\u2019 refers to the approximate level of radiative forcing (in watts per square metre, or Wm\u20132) resulting from the \nscenario in the year 2100.\n** The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate 2100 radiative \nforcing levels (in W m-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs. They are similar but not \nidentical, with differences in concentration trajectories for different GHGs.\n\nDocument 100: 63\nCurrent Status and Trends\nSection 2\nCross-Section Box.2: Scenarios, Global Warming Levels, and Risks\nModelled scenarios and pathways102 are used to explore future emissions, climate change, related impacts and risks, and possible mitigation and \nadaptation strategies and are based on a range of assumptions, including socio-economic variables and mitigation options. These are quantitative \nprojections and are neither predictions nor forecasts. Global modelled emission pathways, including those based on cost effective approaches \ncontain regionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition of these assumptions. Most \ndo not make explicit assumptions about global equity, environmental justice or intra-regional income distribution. IPCC is neutral with regard \nto the assumptions underlying the scenarios in the literature assessed in this report, which do not cover all possible futures103. {WGI Box SPM.1; \nWGII Box SPM.1; WGIII Box SPM.1; SROCC Box SPM.1; SRCCL Box SPM.1} \nSocio-economic Development, Scenarios, and Pathways\nThe \ufb01ve Shared Socio-economic Pathways (SSP1 to SSP5) were designed to span a range of challenges to climate change mitigation and adaptation. \nFor the assessment of climate impacts, risk and adaptation, the SSPs are used for future exposure, vulnerability and challenges to adaptation. \nDepending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels104. \nThere are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1). \n{WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box TS.5, WGIII Annex III; SRCCL Box SPM.1, SRCCL Figure SPM.2}\nWGI assessed the climate response to \ufb01ve illustrative scenarios based on SSPs105 that cover the range of possible future development of anthropogenic \ndrivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and \nair pollution controls for aerosols and non-CH4 ozone precursors.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What is the purpose of the AR6 integrated assessment framework as described in the IPCC report?","answer":"The AR6 integrated assessment framework is designed to assess future greenhouse gas emissions, climate change, risks, impacts, and mitigation. It encompasses socio-economic development and policy, emissions pathways, and global surface temperature responses to various scenarios."},{"question":"What are Shared Socio-economic Pathways (SSPs) and how are they used in the IPCC report?","answer":"Shared Socio-economic Pathways (SSPs) are used to explore a range of challenges to climate change mitigation and adaptation. In the IPCC report, they are used for future exposure, vulnerability, and challenges to adaptation, and depending on levels of GHG mitigation, they can be consistent with low or high warming levels."}],"seed_document_id":106,"topic":"Climate Change Scenarios"}}
{"id":"5e86dd79-37ec-47b0-81a6-944b8ee861a9","question":"What are some limitations of the models used to project the impacts of climate change on fisheries and maize yield, and which climatic impact-drivers are projected to increase in all regions with high confidence?","reference_answer":"The limitations of the models include not representing changes in fishing activities, pests, diseases, future agro-technological changes, some extreme climatic conditions, and the assumption that irrigated areas are not water-limited. With high confidence, it is projected that hot climatic impact-drivers will increase and cold ones will decrease in all regions.","reference_context":"Document 133: Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\nFuture climate change is projected to increase the severity of impacts \nacross natural and human systems and will increase regional differences\nAreas with little or no \nproduction, or not assessed\n1Projected temperature conditions above \nthe estimated historical (1850-2005) \nmaximum mean annual temperature \nexperienced by each species, assuming \nno species relocation. \n2Includes 30,652 species of birds, \nmammals, reptiles, amphibians, marine \n\ufb01sh, benthic marine invertebrates, krill, \ncephalopods, corals, and seagrasses.\na) Risk of \nspecies losses\nb) Heat-humidity \nrisks to \nhuman health\nc) Food production \nimpacts\n3Projected regional impacts utilize a global threshold beyond which daily mean surface air temperature and relative humidity may induce \nhyperthermia that poses a risk of mortality. The duration and intensity of heatwaves are not presented here. Heat-related health outcomes \nvary by location and are highly moderated by socio-economic, occupational and other non-climatic determinants of individual health and \nsocio-economic vulnerability. The threshold used in these maps is based on a single study that synthesized data from 783 cases to \ndetermine the relationship between heat-humidity conditions and mortality drawn largely from observations in temperate climates.\nHistorical 1991\u20132005\n\nDocument 132: 73\nLong-Term Climate and Development Futures\nSection 3\nc1) Maize yield4\nc2) Fisheries yield5\nChanges (%) in \nmaximum catch \npotential\nChanges (%) in yield\n \n \n-20\n-10\n-3\n-30\n-25\n-15\n-35%\n+20\n+30\n+35%\n+10\n+3\n+25\n+15\n1\n0 days\n300\n100\n200\n10\n150\n250\n50\n365 days\n0.1\n0%\n80\n10\n40\n1\n20\n60\n5\n100%\nAreas with model disagreement\nExamples of impacts without additional adaptation\n2.4 \u2013 3.1\u00b0C\n4.2 \u2013 5.4\u00b0C\n1.5\u00b0C\n3.0\u00b0C\n1.7 \u2013 2.3\u00b0C\n0.9 \u2013 2.0\u00b0C\n3.4 \u2013 5.2\u00b0C\n1.6 \u2013 2.4\u00b0C\n3.3 \u2013 4.8\u00b0C\n3.9 \u2013 6.0\u00b0C\n2.0\u00b0C\n4.0\u00b0C\nPercentage of animal \nspecies and seagrasses \nexposed to potentially \ndangerous temperature \nconditions1, 2\nDays per year where \ncombined temperature and \nhumidity conditions pose a risk \nof mortality to individuals3\n5Projected regional impacts re\ufb02ect \ufb01sheries and marine ecosystem responses to ocean physical and biogeochemical conditions such as \ntemperature, oxygen level and net primary production. Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\n\nDocument 134: 74\nSection 3\nSection 1\nSection 3\nFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. \nProjected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without \nadditional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species \nlosses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as de\ufb01ned by conditions beyond the estimated historical \n(1850\u20132005) maximum mean annual temperature experienced by each species, at GWLs of 1.5\u00b0C, 2\u00b0C, 3\u00b0C and 4\u00b0C. Underpinning projections of temperature are from 21 Earth \nsystem models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure \nto hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991\u20132005) and at GWLs of 1.7\u00b0C to 2.3\u00b0C \n(mean = 1.9\u00b0C; 13 climate models), 2.4\u00b0C to 3.1\u00b0C (2.7\u00b0C; 16 climate models) and 4.2\u00b0C to 5.4\u00b0C (4.7\u00b0C; 15 climate models). Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C).\n\nDocument 120: Increases in hot and decreases in \ncold climatic impact-drivers, such as temperature extremes, are \nprojected in all regions (high con\ufb01dence). At 1.5\u00b0C global warming, \nheavy precipitation and \ufb02ooding events are projected to intensify \nand become more frequent in most regions in Africa, Asia (high \ncon\ufb01dence), North America (medium to high con\ufb01dence) and Europe \n(medium con\ufb01dence). At 2\u00b0C or above, these changes expand to more \nregions and\/or become more signi\ufb01cant (high con\ufb01dence), and more \nfrequent and\/or severe agricultural and ecological droughts are projected \nin Europe, Africa, Australasia and North, Central and South America \n(medium to high con\ufb01dence). Other projected regional changes include \n117 Particularly over South and South East Asia, East Asia and West Africa apart from the far west Sahel. {WGI SPM B.3.3}\n118 See Annex I: Glossary.\n119 See Annex I: Glossary.\nintensification of tropical cyclones and\/or extratropical storms \n(medium con\ufb01dence), and increases in aridity and \ufb01re weather119 \n(medium to high con\ufb01dence). Compound heatwaves and droughts \nbecome likely more frequent, including concurrently at multiple \nlocations (high con\ufb01dence). {WGI SPM C.2, WGI SPM C.2.1, WGI SPM C.2.2, \nWGI SPM C.2.3, WGI SPM C.2.4, WGI SPM C.2.7}","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are some limitations of the models used to project the impacts of climate change on fisheries and maize yield?","answer":"Models do not represent changes in fishing activities, pests, diseases, future agro-technological changes, some extreme climatic conditions, and they assume that irrigated areas are not water-limited."},{"question":"What climatic impact-drivers are projected to increase in all regions with high confidence?","answer":"Increases in hot and decreases in cold climatic impact-drivers, such as temperature extremes, are projected in all regions with high confidence."}],"seed_document_id":133,"topic":"Climate Change Risks"}}
{"id":"2330c341-53ed-4c8a-bb7f-afa0e51b6682","question":"What are the potential trade-offs of technological innovation according to the IPCC report, and how can policy packages help in addressing these trade-offs and challenges of digitalisation and technological innovation?","reference_answer":"Technological innovation can involve trade-offs such as environmental impacts, social inequalities, rebound effects, and overdependence on foreign knowledge and providers, according to the IPCC report. Policy packages can address these challenges by implementing a mix of efficiency targets, performance standards, information provision, carbon pricing, finance, and technical assistance to realize synergies, avoid trade-offs, and reduce rebound effects.","reference_context":"Document 299: 114\nSection 4\nSection 1\nSection 4\nInternational cooperation on innovation works best when tailored to \nand bene\ufb01cial for local value chains, when partners collaborate on an \nequal footing, and when capacity building is an integral part of the \neffort (medium con\ufb01dence). {WGIII SPM E.4.4, WGIII SPM E.6.2}\nTechnological innovation can have trade-offs that include \nexternalities such as new and greater environmental impacts and \nsocial inequalities; rebound effects leading to lower net emission \nreductions or even emission increases; and overdependence on \nforeign knowledge and providers (high con\ufb01dence). Appropriately \ndesigned policies and governance have helped address distributional \nimpacts and rebound effects (high con\ufb01dence). For example, digital \ntechnologies can promote large increases in energy ef\ufb01ciency through \ncoordination and an economic shift to services (high con\ufb01dence). \nHowever, societal digitalization can induce greater consumption of \ngoods and energy and increased electronic waste as well as negatively \nimpacting labour markets and worsening inequalities between \nand within countries (medium con\ufb01dence). Digitalisation requires \nappropriate governance and policies in order to enhance mitigation \npotential (high con\ufb01dence). Effective policy packages can help to \nrealise synergies, avoid trade-offs and\/or reduce rebound effects: \nthese might include a mix of ef\ufb01ciency targets, performance standards, \ninformation provision, carbon pricing, \ufb01nance and technical assistance \n(high con\ufb01dence). {WGIII SPM B.4.2, WGIII SPM B.4.3, WGIII SPM E.4.4, \nWGIII TS 6.5, WGIII Cross-Chapter Box 11 on Digitalization in Chapter 16}\nTechnology transfer to expand use of digital technologies for land use \nmonitoring, sustainable land management, and improved agricultural \nproductivity supports reduced emissions from deforestation and land \nuse change while also improving GHG accounting and standardisation \n(medium con\ufb01dence).\n\nDocument 300: Digitalisation requires \nappropriate governance and policies in order to enhance mitigation \npotential (high con\ufb01dence). Effective policy packages can help to \nrealise synergies, avoid trade-offs and\/or reduce rebound effects: \nthese might include a mix of ef\ufb01ciency targets, performance standards, \ninformation provision, carbon pricing, \ufb01nance and technical assistance \n(high con\ufb01dence). {WGIII SPM B.4.2, WGIII SPM B.4.3, WGIII SPM E.4.4, \nWGIII TS 6.5, WGIII Cross-Chapter Box 11 on Digitalization in Chapter 16}\nTechnology transfer to expand use of digital technologies for land use \nmonitoring, sustainable land management, and improved agricultural \nproductivity supports reduced emissions from deforestation and land \nuse change while also improving GHG accounting and standardisation \n(medium con\ufb01dence). {SRCCL SPM C.2.1, SRCCL SPM D.1.2, SRCCL SPM D.1.4, \nSRCCL 7.4.4, SRCCL 7.4.6}\nClimate resilient development strategies that treat climate, \necosystems and biodiversity, and human society as parts of an \nintegrated system are the most effective (high con\ufb01dence). Human \nand ecosystem vulnerability are interdependent (high con\ufb01dence). \nClimate resilient development is enabled when decision-making processes \nand actions are integrated across sectors (very high con\ufb01dence). \nSynergies with and progress towards the Sustainable Development \nGoals enhance prospects for climate resilient development. Choices and \nactions that treat humans and ecosystems as an integrated system build \non diverse knowledge about climate risk, equitable, just and inclusive \napproaches, and ecosystem stewardship.\n\nDocument 295: 113\nNear-Term Responses in a Changing Climate\nSection 4\n4.8.3. Technology Innovation, Adoption, Diffusion and \nTransfer \nEnhancing \ntechnology \ninnovation \nsystems \ncan \nprovide \nopportunities to lower emissions growth and create social and \nenvironmental co-bene\ufb01ts. Policy packages tailored to national \ncontexts and technological characteristics have been effective \nin supporting low-emission innovation and technology diffusion. \nSupport for successful low-carbon technological innovation \nincludes public policies such as training and R&D, complemented by \nregulatory and market-based instruments that create incentives and \nmarket opportunities such as appliance performance standards and \nbuilding codes. (high confidence) {WGIII SPM B.4, WGIII SPM B.4.4, \nWGIII SPM E.4.3, WGIII SPM E4.4}\nInternational cooperation on innovation systems and technology \ndevelopment and transfer, accompanied by capacity building, \nknowledge sharing, and technical and \ufb01nancial support can \naccelerate the global diffusion of mitigation technologies, \npractices and policies and align these with other development \nobjectives (high con\ufb01dence). Choice architecture can help end-users \nadopt technology and low-GHG-intensive options (high con\ufb01dence). \nAdoption of low-emission technologies lags in most developing countries, \nparticularly least developed ones, due in part to weaker enabling \nconditions, including limited \ufb01nance, technology development and \ntransfer, and capacity building (medium con\ufb01dence).","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the potential trade-offs of technological innovation according to the IPCC report?","answer":"Technological innovation can have trade-offs that include new and greater environmental impacts, social inequalities, rebound effects leading to lower net emission reductions or even emission increases, and overdependence on foreign knowledge and providers."},{"question":"How can policy packages help in addressing the challenges of digitalisation and technological innovation?","answer":"Effective policy packages can help to realize synergies, avoid trade-offs, and\/or reduce rebound effects by including a mix of efficiency targets, performance standards, information provision, carbon pricing, finance, and technical assistance."}],"seed_document_id":299,"topic":"Climate Change Action"}}
{"id":"cda501dc-f8b4-41f1-b008-766499e7e640","question":"What does the yellow shading represent in the top panel (a) of Figure 2.4, and what is the significance of the vertical dashed line placed in 2010 in the bottom panel (b)?","reference_answer":"The yellow shading in the top panel (a) of Figure 2.4 indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020, corresponding to USD 55 to 148 per MWh, while the vertical dashed line in 2010 in the bottom panel (b) signifies the change in cumulative global adoption for each technology over the past decade.","reference_context":"Document 66: 54\nSection 2\nSection 1\nSection 2\nMarket cost, with range\nAdoption (note different scales)\nFossil fuel cost (2020)\nPassenger \nelectric vehicle \nPhotovoltaics\n(PV) \nOnshore\nwind \nOffshore\nwind\nKey\na) Market Cost\nb) Market Adoption\nRenewable electricity generation \nis increasingly price-competitive \nand some sectors are electrifying\nSince AR5, the unit costs of some \nforms of renewable energy and \nof batteries for passenger EVs \nhave fallen. \nSince AR5, the installed capacity \nof renewable energies has \nincreased multiple times.\n2000\n2020\n2010\n2010\n2010\n2010\n2010\n2010\n2010\n2010\n2010\nCost ($2020\/MWh)\n1200\n1600 Li-ion battery packs\n800\n400\n0\n150\n300\n450\n600\n0\nCost ($2020\/kWh)\nAdoption (millions of EVs)\n0\n2\n4\n6\n8\nAdoption (GW) -note differnt scales\n0\n200\n400\n600\n800\n0\n10\n20\n30\n40\nFossil fuel cost (2020)\nbelow this point, costs can \nbe less than fossil fuels\nFigure 2.4: Unit cost reductions and use in some rapidly changing mitigation technologies. The top panel (a) shows global costs per unit of energy (USD per MWh) \nfor some rapidly changing mitigation technologies. Solid blue lines indicate average unit cost in each year. Light blue shaded areas show the range between the 5th and 95th \npercentiles in each year. Yellow shading indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020 (corresponding to USD 55 to 148 per MWh). \nIn 2020, the levelised costs of energy (LCOE) of the three renewable energy technologies could compete with fossil fuels in many places. For batteries, costs shown are for 1 kWh \nof battery storage capacity; for the others, costs are LCOE, which includes installation, capital, operations, and maintenance costs per MWh of electricity produced.\n\nDocument 67: The top panel (a) shows global costs per unit of energy (USD per MWh) \nfor some rapidly changing mitigation technologies. Solid blue lines indicate average unit cost in each year. Light blue shaded areas show the range between the 5th and 95th \npercentiles in each year. Yellow shading indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020 (corresponding to USD 55 to 148 per MWh). \nIn 2020, the levelised costs of energy (LCOE) of the three renewable energy technologies could compete with fossil fuels in many places. For batteries, costs shown are for 1 kWh \nof battery storage capacity; for the others, costs are LCOE, which includes installation, capital, operations, and maintenance costs per MWh of electricity produced. The literature uses \nLCOE because it allows consistent comparisons of cost trends across a diverse set of energy technologies to be made. However, it does not include the costs of grid integration \nor climate impacts. Further, LCOE does not take into account other environmental and social externalities that may modify the overall (monetary and non-monetary) costs of \ntechnologies and alter their deployment. The bottom panel (b) shows cumulative global adoption for each technology, in GW of installed capacity for renewable energy and \nin millions of vehicles for battery-electric vehicles. A vertical dashed line is placed in 2010 to indicate the change over the past decade. The electricity production share re\ufb02ects \ndifferent capacity factors; for example, for the same amount of installed capacity, wind produces about twice as much electricity as solar PV. Renewable energy and battery \ntechnologies were selected as illustrative examples because they have recently shown rapid changes in costs and adoption, and because consistent data are available. Other \nmitigation options assessed in the WGIII report are not included as they do not meet these criteria. {WGIII Figure SPM.3, WGIII 2.5, 6.4}","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What does the yellow shading represent in the top panel (a) of Figure 2.4?","answer":"The yellow shading indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020, corresponding to USD 55 to 148 per MWh."},{"question":"What is the significance of the vertical dashed line placed in 2010 in the bottom panel (b) of Figure 2.4?","answer":"The vertical dashed line placed in 2010 indicates the change in cumulative global adoption for each technology over the past decade."}],"seed_document_id":66,"topic":"Others"}}
{"id":"67a05575-4ffa-406b-83c6-86794e673ae4","question":"What are the projected near-term GHG emissions pathways in line with policies implemented until the end of 2020 and what is the significance of the SSP1-1.9 and SSP1-2.6 scenarios in terms of CO2 emissions?","reference_answer":"The projected near-term GHG emissions pathways, based on policies implemented until the end of 2020, are categorized as 'Trend from implemented policies', while the SSP1-1.9 and SSP1-2.6 scenarios are significant as they envision CO2 emissions reaching net zero around 2050 and 2070, respectively, with subsequent net negative CO2 emissions.","reference_context":"Document 85: Panel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n \n- Limit to 2\u00b0C (>67%) or return warming to 1.5\u00b0C (>50%) after a high overshoot, NDCs until 2030: Pathways with GHG emissions until 2030 associated with the \nimplementation of NDCs announced prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2\u00b0C (C3b, WGIII Table SPM.2) or to return \nwarming to 1.5\u00b0C with a probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, WGIII Table SPM.2). \n \n- Limit to 2\u00b0C (>67%) with immediate action: Pathways that limit warming to 2\u00b0C (>67%) with immediate action after 2020 (C3a, WGIII Table SPM.2). \n \n- Limit to 1.5\u00b0C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5\u00b0C with no or limited overshoot (C1, WGIII Table SPM.2 C1). \nAll these pathways assume immediate action after 2020. Past GHG emissions for 2010-2015 used to project global warming outcomes of the modelled pathways are shown by a \nblack line. Panel b shows a snapshot of the GHG emission ranges of the modelled pathways in 2030 and projected emissions outcomes from near-term policy assessments in 2030 \nfrom WGIII Chapter 4.2 (Tables 4.2 and 4.3; median and full range). GHG emissions are CO2-equivalent using GWP100 from AR6 WGI. {WGIII Figure SPM.4, WGIII 3.5, 4.2, Table 4.2, \nTable 4.3, Cross-Chapter Box 4 in Chapter 4} (Table 3.1, Cross-Section Box.2)\n\nDocument 84: 59\nCurrent Status and Trends\nSection 2\na) Global GHG emissions\nb) 2030\n10\n20\n30\n0\n40\n50\n60\n70\n10\n20\n30\n0\n40\n50\n60\n70\nGHG emissions (GtCO2-eq\/yr)\n2020\n2025\n2015\n2010\n2030\n2035\n2040\n2045\n2050\nLimit warming to 2\u00baC (>67%)\nor 1.5 (>50%) after high\novershoot with NDCs until 2030\nTrend from implemented policies\n2019\nLimit warming to\n1.5\u00baC (>50%) with \nno or limited overshoot\nLimit warming \nto 2\u00baC (>67%)\nto be on-track to limit \nwarming to 1.5\u00b0C, \nwe need much more \nreduction by 2030\n-4%\n+5%\n-26%\n-43%\nProjected global GHG emissions from NDCs announced prior to \nCOP26 would make it likely that warming will exceed 1.5\u00b0C and \nalso make it harder after 2030 to limit warming to below 2\u00b0C\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nPast GHG emissions and \nuncertainty for 2015 and 2019\n(dot indicates the median)\nFigure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), and projected emission outcomes from near-term policy assessments for 2030 (Panel b). \nPanel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:\n \n- Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with comparable \nambition  levels beyond 2030 (29 scenarios across categories C5\u2013C7, WGIII Table SPM.2).\n\nDocument 102: The very low and low GHG emissions scenarios (SSP1-1.9 and \nSSP1-2.6) have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 \nemissions. In addition, Representative Concentration Pathways (RCPs)107 were used by WGI and WGII to assess regional climate changes, \nimpacts and risks. {WGI Box SPM.1} (Cross-Section Box.2 Figure 1)\nIn WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their \nprojected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5\u00b0C with more than 50% \nlikelihood108 with no or limited overshoot (C1) to pathways that exceed 4\u00b0C (C8). Methods to project global warming associated with the \nmodelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response109. {WGIII Box SPM.1,WGIII \nTable 3.1} (Table 3.1, Cross-Section Box.2 Figure 1)\n102 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate goals. WGI primarily used the term \nscenarios and WGIII mostly used the term modelled emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and \nmitigation pathways when referring to WGIII. {WGI Box SPM.1; WGIII footnote 44}\n103 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation\/abatement options globally. The other half look \nat existing policies and regionally and sectorally differentiated actions.  The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion \nin 2100 (5\u201395th percentile) starting from 7.6 billion in 2019.\n\nDocument 182: Top row: GHG, CO2 and CH4 emissions over time (in \nGtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour \n(blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows \npathways that limit warming to 2\u00b0C (>67%) (C3). Bottom row: Panel (c) shows median (vertical line), likely (bar) and very likely (thin lines) timing of reaching net zero GHG \nand CO2 emissions for global modelled pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) (left) or 2\u00b0C (>67%) (C3) (right). {WGIII Figure SPM.5}\n3.3.3 Sectoral Contributions to Mitigation\nAll global modelled pathways that limit warming to 2\u00b0C (>67%) or \nlower by 2100 involve rapid and deep and in most cases immediate \nGHG emissions reductions in all sectors (see also 4.1, 4.5). Reductions \nin GHG emissions in industry, transport, buildings, and urban areas \ncan be achieved through a combination of energy ef\ufb01ciency and \nconservation and a transition to low-GHG technologies and energy \ncarriers (see also 4.5, Figure 4.4). Socio-cultural options and behavioural \nchange can reduce global GHG emissions of end-use sectors, with most \nof the potential in developed countries, if combined with improved \n136 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage is available. When CO2 is captured directly from the \natmosphere (DACCS), or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO2 capture and subsurface injection is a mature technology for \ngas processing and enhanced oil recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production, where it \nis a critical mitigation option.","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the projected near-term GHG emissions pathways according to the policies implemented until the end of 2020?","answer":"The projected near-term GHG emissions pathways in line with policies implemented until the end of 2020 and extended with comparable ambition levels beyond 2030 are categorized as 'Trend from implemented policies'."},{"question":"What is the significance of the SSP1-1.9 and SSP1-2.6 scenarios in terms of CO2 emissions?","answer":"The SSP1-1.9 and SSP1-2.6 scenarios are significant because they have CO2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2 emissions."}],"seed_document_id":85,"topic":"Climate Change Scenarios"}}
{"id":"6b821c23-b4ca-4fbd-9127-e8f9acbb5cde","question":"What are the projected impacts on food availability, the number of undernourished people, and the IPCC AR6's assessment of risks associated with each Reason for Concern (RFC) at about 2\u00b0C global warming?","reference_answer":"At about 2\u00b0C global warming, food availability is expected to decrease and nutrition-related diseases are estimated to increase, affecting tens to hundreds of millions, particularly among low-income households in low- and middle-income countries. The IPCC AR6 indicates that the risks associated with the unequal distribution of impacts (RFC3), global aggregate impacts (RFC4), and large-scale singular events (RFC5) would be transitioning to high, with extreme weather events (RFC2) risks transitioning to very high, and unique and threatened systems (RFC1) risks being very high.","reference_context":"Document 125: {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a). With about 2\u00b0C warming, climate-related \n120 Undetectable risk level indicates no associated impacts are detectable and attributable to climate change; moderate risk indicates associated impacts are both detectable and \nattributable to climate change with at least medium con\ufb01dence, also accounting for the other speci\ufb01c criteria for key risks; high risk indicates severe and widespread impacts that \nare judged to be high on one or more criteria for assessing key risks; and very high risk level indicates very high risk of severe impacts and the presence of signi\ufb01cant irreversibility \nor the persistence of climate-related hazards, combined with limited ability to adapt due to the nature of the hazard or impacts\/risks. {WGII Figure SPM.3}\n121 The Reasons for Concern (RFC) framework communicates scienti\ufb01c understanding about accrual of risk for \ufb01ve broad categories (WGII Figure SPM.3). RFC1: Unique and \nthreatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive \nproperties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots.\n\nDocument 126: {WGII Figure SPM.3}\n121 The Reasons for Concern (RFC) framework communicates scienti\ufb01c understanding about accrual of risk for \ufb01ve broad categories (WGII Figure SPM.3). RFC1: Unique and \nthreatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive \nproperties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme weather events: risks\/impacts to \nhuman health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wild\ufb01res, and coastal \ufb02ooding. RFC3: \nDistribution of impacts: risks\/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability. \nRFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives affected, species lost \nor ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused by global warming, \nsuch as ice sheet instability or thermohaline circulation slowing. Assessment methods include a structured expert elicitation based on the literature described in WGII SM16.6 \nand are identical to AR5 but are enhanced by a structured approach to improve robustness and facilitate comparison between AR5 and AR6. For further explanations of global \nrisk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}\nchanges in food availability and diet quality are estimated to increase \nnutrition-related diseases and the number of undernourished people, \naffecting tens (under low vulnerability and low warming) to hundreds of \nmillions of people (under high vulnerability and high warming), particularly \namong low-income households in low- and middle-income countries in \nsub-Saharan Africa, South Asia and Central America (high con\ufb01dence). \nFor example, snowmelt water availability for irrigation is projected \nto decline in some snowmelt dependent river basins by up to 20% \n(medium con\ufb01dence).\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 105: 64\nSection 2\nSection 1\nSection 2\nGlobal Warming Levels (GWLs)\nFor many climate and risk variables, the geographical patterns of changes in climatic impact-drivers110 and climate impacts for a level of global \nwarming111 are common to all scenarios considered and independent of timing when that level is reached. This motivates the use of GWLs as a \ndimension of integration. {WGI Box SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2)\nRisks\nDynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result \nin risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the \nReasons for Concern (RFCs) \u2013 \ufb01ve globally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature. \nRisks can also arise from climate change mitigation or adaptation responses when the response does not achieve its intended objective, or when \nit results in adverse effects for other societal objectives. {WGII SPM A, WGII Figure SPM.3, WGII Box TS.1, WGII Figure TS.4; SR1.5 Figure SPM.2; \nSROCC Errata Figure SPM.3; SRCCL Figure SPM.2} (3.1.2, Cross-Section Box.2 Figure 1, Figure 3.3)\n110 See Annex I: Glossary\n111 See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850\u20131900. The assessed time of when a certain global warming level \nis reached under a particular scenario is de\ufb01ned here as the mid-point of the \ufb01rst 20-year running average period during which the assessed average global surface temperature \nchange exceeds the level of global warming. {WGI SPM footnote 26, Cross-Section Box TS.1}","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the projected impacts on food availability and the number of undernourished people with about 2\u00b0C global warming?","answer":"With about 2\u00b0C warming, climate-related changes in food availability and diet quality are estimated to increase nutrition-related diseases and the number of undernourished people, affecting tens to hundreds of millions of people, particularly among low-income households in low- and middle-income countries in sub-Saharan Africa, South Asia, and Central America (high confidence)."},{"question":"How does the IPCC AR6 assess the risks associated with each Reason for Concern (RFC) at 2\u00b0C of global warming?","answer":"At 2\u00b0C of global warming, the IPCC AR6 assesses that the overall risk levels associated with the unequal distribution of impacts (RFC3), global aggregate impacts (RFC4), and large-scale singular events (RFC5) would be transitioning to high (medium confidence), those associated with extreme weather events (RFC2) would be transitioning to very high (medium confidence), and those associated with unique and threatened systems (RFC1) would be very high (high confidence)."}],"seed_document_id":125,"topic":"Climate Change Risks"}}
{"id":"7121e886-3854-4d07-90b1-107d33293e15","question":"How can the integration of transport and energy infrastructure planning and operations benefit the environment, and what makes climate resilient development strategies most effective?","reference_answer":"Integrating transport and energy infrastructure planning and operations can effectively reduce environmental, social, and economic impacts, aiding in the decarbonisation of these sectors, while the most effective climate resilient development strategies are those that view climate, ecosystems, biodiversity, and human society as interconnected parts of a whole system, both with high confidence.","reference_context":"Document 302: Such measures can also achieve \ngreater bene\ufb01ts through cascading effects across sectors \n(medium con\ufb01dence). For example, the feasibility of using land for \nboth agriculture and centralised solar production can increase when \nsuch options are combined (high con\ufb01dence). Similarly, integrated \ntransport and energy infrastructure planning and operations can \ntogether reduce the environmental, social, and economic impacts of \ndecarbonising the transport and energy sectors (high con\ufb01dence). The \nimplementation of packages of multiple city-scale mitigation strategies \ncan have cascading effects across sectors and reduce GHG emissions \nboth within and outside a city\u2019s administrative boundaries (very high \ncon\ufb01dence). Integrated design approaches to the construction and \nretro\ufb01t of buildings provide increasing examples of zero energy or \nzero carbon buildings in several regions. To minimise maladaptation, \nmulti-sectoral, multi-actor and inclusive planning with \ufb02exible \npathways encourages low-regret and timely actions that keep options \nopen, ensure bene\ufb01ts in multiple sectors and systems and suggest the \navailable solution space for adapting to long-term climate change \n(very high con\ufb01dence). Trade-offs in terms of employment, water \nuse, land-use competition and biodiversity, as well as access to, \nand the affordability of, energy, food, and water can be avoided \nby well-implemented land-based mitigation options, especially those \nthat do not threaten existing sustainable land uses and land rights, with \nframeworks for integrated policy implementation (high con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, \nWGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.1.5, \nWGIII SPM E.1.2}\nMitigation and adaptation when implemented together, and \ncombined with broader sustainable development objectives, \nwould yield multiple bene\ufb01ts for human well-being as well as \necosystem and planetary health (high con\ufb01dence).\n\nDocument 303: {WGII SPM C.2, WGII SPM C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, \nWGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.1.5, \nWGIII SPM E.1.2}\nMitigation and adaptation when implemented together, and \ncombined with broader sustainable development objectives, \nwould yield multiple bene\ufb01ts for human well-being as well as \necosystem and planetary health (high con\ufb01dence). The range of \nsuch positive interactions is signi\ufb01cant in the landscape of near-term \nclimate policies across regions, sectors and systems. For example, \nAFOLU mitigation actions in land-use change and forestry, when \nsustainably implemented, can provide large-scale GHG emission \nreductions and removals that simultaneously bene\ufb01t biodiversity, food \nsecurity, wood supply and other ecosystem services but cannot fully \ncompensate for delayed mitigation action in other sectors. Adaptation \nmeasures in land, ocean and ecosystems similarly can have widespread \nbene\ufb01ts for food security, nutrition, health and well-being, ecosystems \nand biodiversity. Equally, urban systems are critical, interconnected \nsites for climate resilient development; urban policies that implement \nmultiple interventions can yield adaptation or mitigation gains with \nequity and human well-being. Integrated policy packages can improve \nthe ability to integrate considerations of equity, gender equality \nand justice. Coordinated cross-sectoral policies and planning can \nmaximise synergies and avoid or reduce trade-offs between mitigation \n4.9 Integration of Near-Term Actions Across Sectors and Systems \nThe feasibility, effectiveness and bene\ufb01ts of mitigation and adaptation actions are increased when multi-sectoral \nsolutions are undertaken that cut across systems. When such options are combined with broader sustainable \ndevelopment objectives, they can yield greater bene\ufb01ts for human well-being, social equity and justice, and \necosystem and planetary health. (high con\ufb01dence)\n\nDocument 301: {SRCCL SPM C.2.1, SRCCL SPM D.1.2, SRCCL SPM D.1.4, \nSRCCL 7.4.4, SRCCL 7.4.6}\nClimate resilient development strategies that treat climate, \necosystems and biodiversity, and human society as parts of an \nintegrated system are the most effective (high con\ufb01dence). Human \nand ecosystem vulnerability are interdependent (high con\ufb01dence). \nClimate resilient development is enabled when decision-making processes \nand actions are integrated across sectors (very high con\ufb01dence). \nSynergies with and progress towards the Sustainable Development \nGoals enhance prospects for climate resilient development. Choices and \nactions that treat humans and ecosystems as an integrated system build \non diverse knowledge about climate risk, equitable, just and inclusive \napproaches, and ecosystem stewardship. {WGII SPM B.2, WGII Figure \nSPM.5, WGII SPM D.2, WGII SPM D2.1, WGII SPM 2.2, WGII SPM D4, \nWGII SPM D4.1, WGII SPM D4.2, WGII SPM D5.2, WGII Figure SPM.5}\nApproaches that align goals and actions across sectors provide \nopportunities for multiple and large-scale bene\ufb01ts and avoided \ndamages in the near term. Such measures can also achieve \ngreater bene\ufb01ts through cascading effects across sectors \n(medium con\ufb01dence). For example, the feasibility of using land for \nboth agriculture and centralised solar production can increase when \nsuch options are combined (high con\ufb01dence). Similarly, integrated \ntransport and energy infrastructure planning and operations can \ntogether reduce the environmental, social, and economic impacts of \ndecarbonising the transport and energy sectors (high con\ufb01dence). The \nimplementation of packages of multiple city-scale mitigation strategies \ncan have cascading effects across sectors and reduce GHG emissions \nboth within and outside a city\u2019s administrative boundaries (very high \ncon\ufb01dence). Integrated design approaches to the construction and \nretro\ufb01t of buildings provide increasing examples of zero energy or \nzero carbon buildings in several regions.\n\nDocument 275: Countries at \nall stages of economic development seek to improve the well-being \nof people, and their development priorities re\ufb02ect different starting \npoints and contexts. Different contexts include but are not limited to \nsocial, economic, environmental, cultural, or political circumstances, \nresource endowment, capabilities, international environment, and prior \ndevelopment. n regions with high dependency on fossil fuels for, among \nother things, revenue and employment generation, mitigating risks for \nsustainable development requires policies that promote economic and \nenergy sector diversi\ufb01cation and considerations of just transitions \nprinciples, processes and practices (high con\ufb01dence). For individuals and \nhouseholds in low-lying coastal areas, in Small Islands, and smallholder \nfarmers transitioning from incremental to transformational adaptation \ncan help overcome soft adaptation limits (high con\ufb01dence). Effective \ngovernance is needed to limit trade-offs of some mitigation options \nsuch as large scale afforestation and bioenergy options due to risks \nfrom their deployment for food systems, biodiversity, other ecosystem \nfunctions and services, and livelihoods (high con\ufb01dence). Effective \ngovernance requires adequate institutional capacity at all levels \n(high confidence). {WGII SPM B.5.4, WGII SPM C.3.1, WGII SPM \nC.3.4; WGIII SPM D.1.3, WGIII SPM E.4.2; SR1.5 SPM C.3.4, \nSR1.5 SPM C.3.5, SR1.5 SPM Figure SPM.4, SR1.5 SPM D.4.3, \nSR1.5 SPM D.4.4}\n4.6 Co-Bene\ufb01ts of Adaptation and Mitigation for Sustainable Development Goals\nMitigation and adaptation actions have more synergies than trade-offs with Sustainable Development Goals \n(SDGs). Synergies and trade-offs depend on context and scale of implementation. Potential trade-offs can be \ncompensated or avoided with additional policies, investments and \ufb01nancial partnerships. (high con\ufb01dence)","conversation_history":[],"metadata":{"question_type":"double","original_questions":[{"question":"What are the benefits of integrating transport and energy infrastructure planning and operations?","answer":"Integrated transport and energy infrastructure planning and operations can reduce the environmental, social, and economic impacts of decarbonising the transport and energy sectors (high confidence)."},{"question":"How can climate resilient development strategies be most effective?","answer":"Climate resilient development strategies that treat climate, ecosystems and biodiversity, and human society as parts of an integrated system are the most effective (high confidence)."}],"seed_document_id":302,"topic":"Climate Change Action"}}
{"id":"8f9d4f9c-17ae-4ebd-8e8a-814c75d3f989","question":"What are the potential benefits of this approach?","reference_answer":"Combining green\/natural and grey\/physical infrastructure adaptation responses has potential to reduce adaptation costs and contribute to flood control, sanitation, water resources management, landslide prevention and coastal protection.","reference_context":"Document 260: Urban greening can \nprovide local cooling (very high con\ufb01dence). Combining green\/natural \nand grey\/physical infrastructure adaptation responses has potential \nto reduce adaptation costs and contribute to \ufb02ood control, sanitation, \nwater resources management, landslide prevention and coastal \nprotection (medium con\ufb01dence). Globally, more \ufb01nancing is directed \nat grey\/physical infrastructure than green\/natural infrastructure \nand social infrastructure (medium con\ufb01dence), and there is limited \nevidence of investment in informal settlements (medium to high \ncon\ufb01dence). The greatest gains in well-being in urban areas can be \nachieved by prioritising \ufb01nance to reduce climate risk for low-income\n\nDocument 259: Advances in battery technologies could facilitate \nthe electri\ufb01cation of heavy-duty trucks and compliment conventional \nelectric rail systems (medium con\ufb01dence). Sustainable biofuels can offer \nadditional mitigation bene\ufb01ts in land-based transport in the short and \nmedium term (medium con\ufb01dence). Sustainable biofuels, low-emissions \nhydrogen, and derivatives (including synthetic fuels) can support \nmitigation of CO2 emissions from shipping, aviation, and heavy-duty \nland transport but require production process improvements and cost \nreductions (medium con\ufb01dence). Key infrastructure systems including \nsanitation, water, health, transport, communications and energy will \nbe increasingly vulnerable if design standards do not account for \nchanging climate conditions (high con\ufb01dence). {WGII SPM B.2.5; \nWGIII SPM C.6.2, WGIII SPM C.8, WGIII SPM C.8.1, WGIII SPM C.8.2, \nWGIII SPM C.10.2, WGIII SPM C.10.3, WGIII SPM C.10.4} \nGreen\/natural and blue infrastructure such as urban forestry, green \nroofs, ponds and lakes, and river restoration can mitigate climate change \nthrough carbon uptake and storage, avoided emissions, and reduced \nenergy use while reducing risk from extreme events such as heatwaves, \nheavy precipitation and droughts, and advancing co-bene\ufb01ts for health, \nwell-being and livelihoods (medium con\ufb01dence). Urban greening can \nprovide local cooling (very high con\ufb01dence). Combining green\/natural \nand grey\/physical infrastructure adaptation responses has potential \nto reduce adaptation costs and contribute to \ufb02ood control, sanitation, \nwater resources management, landslide prevention and coastal \nprotection (medium con\ufb01dence). Globally, more \ufb01nancing is directed \nat grey\/physical infrastructure than green\/natural infrastructure \nand social infrastructure (medium con\ufb01dence), and there is limited \nevidence of investment in informal settlements (medium to high \ncon\ufb01dence).","conversation_history":[{"role":"user","content":"I'm considering the combination of green\/natural and grey\/physical infrastructure adaptation responses."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":260,"topic":"Climate Change Action"}}
{"id":"1ab36f54-99e1-426b-9961-06d821d7ebb2","question":"How much has it increased?","reference_answer":"The global surface temperature was around 1.1\u00b0C above 1850\u20131900 in 2011\u20132020.","reference_context":"Document 11: Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900. Global \nsurface temperature has increased faster since 1970 than in any other \n50-year period over at least the last 2000 years (high con\ufb01dence). The \nlikely range of total human-caused global surface temperature increase \nfrom 1850\u20131900 to 2010\u2013201966 is 0.8\u00b0C to 1.3\u00b0C, with a best estimate \nof 1.07\u00b0C. It is likely that well-mixed GHGs67 contributed a warming \nof 1.0\u00b0C to 2.0\u00b0C, and other human drivers (principally aerosols) \ncontributed a cooling of 0.0\u00b0C to 0.8\u00b0C, natural (solar and volcanic) \ndrivers changed global surface temperature by \u00b10.1\u00b0C and internal \nvariability changed it by \u00b10.2\u00b0C. {WGI SPM A.1, WGI SPM A.1.2, \nWGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2}\nObserved increases in well-mixed GHG concentrations since around \n1750 are unequivocally caused by GHG emissions from human activities.\n\nDocument 10: 42\nSection 2\nSection 1\nSection 2\n2.1 Observed Changes, Impacts and Attribution\nHuman activities, principally through emissions of greenhouse gases, have unequivocally caused global warming, \nwith global surface temperature reaching 1.1\u00b0C above 1850\u20131900 in 2011\u20132020. Global greenhouse gas emissions \nhave continued to increase over 2010\u20132019, with unequal historical and ongoing contributions arising from \nunsustainable energy use, land use and land-use change, lifestyles and patterns of consumption and production \nacross regions, between and within countries, and between individuals (high con\ufb01dence). Human-caused climate \nchange is already affecting many weather and climate extremes in every region across the globe. This has led to \nwidespread adverse impacts on food and water security, human health and on economies and society and related \nlosses and damages63 to nature and people (high con\ufb01dence). Vulnerable communities who have historically \ncontributed the least to current climate change are disproportionately affected (high con\ufb01dence).\n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\nSection 2: Current Status and Trends\n2.1.1. Observed Warming and its Causes\nGlobal surface temperature was around 1.1\u00b0C above 1850\u20131900 in \n2011\u20132020 (1.09 [0.95 to 1.20]\u00b0C)64, with larger increases \nover land (1.59 [1.34 to 1.83]\u00b0C) than over the ocean \n(0.88 [0.68 to 1.01]\u00b0C)65. Observed warming is human-caused, with \nwarming from greenhouse gases (GHG), dominated by CO2 and \nmethane (CH4), partly masked by aerosol cooling (Figure 2.1). \nGlobal surface temperature in the \ufb01rst two decades of the 21st century \n(2001\u20132020) was 0.99 [0.84 to 1.10]\u00b0C higher than 1850\u20131900.\n\nDocument 12: It is likely that well-mixed GHGs67 contributed a warming \nof 1.0\u00b0C to 2.0\u00b0C, and other human drivers (principally aerosols) \ncontributed a cooling of 0.0\u00b0C to 0.8\u00b0C, natural (solar and volcanic) \ndrivers changed global surface temperature by \u00b10.1\u00b0C and internal \nvariability changed it by \u00b10.2\u00b0C. {WGI SPM A.1, WGI SPM A.1.2, \nWGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2}\nObserved increases in well-mixed GHG concentrations since around \n1750 are unequivocally caused by GHG emissions from human activities. \nLand and ocean sinks have taken up a near-constant proportion \n(globally about 56% per year) of CO2 emissions from human activities over \n63 \nIn this report, the term \u2018losses and damages\u2019 refers to adverse observed impacts and\/or projected risks and can be economic and\/or non-economic. (See Annex I: Glossary)\n64 \nThe estimated increase in global surface temperature since AR5 is principally due to further warming since 2003\u20132012 (+0.19 [0.16 to 0.22]\u00b0C). Additionally, methodological \nadvances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements \nhave also increased the estimate of global surface temperature change by approximately 0.1\u00b0C, but this increase does not represent additional physical warming since AR5 \n{WGI SPM A1.2 and footnote 10}\n65 \nFor 1850\u20131900 to 2013\u20132022 the updated calculations are 1.15 [1.00 to 1.25]\u00b0C for global surface temperature, 1.65 [1.36 to 1.90]\u00b0C for land temperatures and \n0.93 [0.73 to 1.04]\u00b0C for ocean temperatures above 1850\u20131900 using the exact same datasets (updated by 2 years) and methods as employed in WGI.\n\nDocument 13: Additionally, methodological \nadvances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements \nhave also increased the estimate of global surface temperature change by approximately 0.1\u00b0C, but this increase does not represent additional physical warming since AR5 \n{WGI SPM A1.2 and footnote 10}\n65 \nFor 1850\u20131900 to 2013\u20132022 the updated calculations are 1.15 [1.00 to 1.25]\u00b0C for global surface temperature, 1.65 [1.36 to 1.90]\u00b0C for land temperatures and \n0.93 [0.73 to 1.04]\u00b0C for ocean temperatures above 1850\u20131900 using the exact same datasets (updated by 2 years) and methods as employed in WGI. \n66 \nThe period distinction with the observed assessment arises because the attribution studies consider this slightly earlier period. The observed warming to 2010\u20132019 is \n1.06 [0.88 to 1.21]\u00b0C. {WGI SPM footnote 11}\n67 \nContributions from emissions to the 2010\u20132019 warming relative to 1850\u20131900 assessed from radiative forcing studies are: CO2 0.8 [0.5 to 1.2]\u00b0C; methane 0.5 [0.3 to 0.8]\u00b0C; \nnitrous oxide 0.1 [0.0 to 0.2]\u00b0C and \ufb02uorinated gases 0.1 [0.0 to 0.2]\u00b0C.\n68 \nFor 2021 (the most recent year for which \ufb01nal numbers are available) concentrations using the same observational products and methods as in AR6 WGI are: 415 ppm CO2; \n1896 ppb CH4; and 335 ppb N2O. Note that the CO2 is reported here using the WMO-CO2-X2007 scale to be consistent with WGI. Operational CO2 reporting has since been \nupdated to use the WMO-CO2-X2019 scale.\nthe past six decades, with regional differences (high con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm interested in the change in global surface temperature from the period of 1850-1900 to the period of 2011-2020."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":11,"topic":"Others"}}
{"id":"2524915c-0afe-415c-92b5-514a05017c30","question":"What are some of the innovations mentioned?","reference_answer":"Innovations in adaptation and resilience finance include forecast-based\/anticipatory financing systems and regional risk insurance pools.","reference_context":"Document 72: {WGII SPM C1.1} \nGlobally tracked adaptation \ufb01nance has shown an upward trend \nsince AR5, but represents only a small portion of total climate \n\ufb01nance, is uneven and has developed heterogeneously across \nregions and sectors (high con\ufb01dence). Adaptation \ufb01nance has come \npredominantly from public sources, largely through grants, concessional \nand non-concessional instruments (very high con\ufb01dence). Globally, \nprivate-sector \ufb01nancing of adaptation from a variety of sources such \nas commercial \ufb01nancial institutions, institutional investors, other \nprivate equity, non-\ufb01nancial corporations, as well as communities \nand households has been limited, especially in developing countries \n(high con\ufb01dence). Public mechanisms and \ufb01nance can leverage \nprivate sector \ufb01nance for adaptation by addressing real and perceived \nregulatory, cost and market barriers, for example via public-private \npartnerships (high con\ufb01dence). Innovations in adaptation and \nresilience \ufb01nance, such as forecast-based\/anticipatory \ufb01nancing \nsystems and regional risk insurance pools, have been piloted and are \ngrowing in scale (high con\ufb01dence). {WGII SPM C.3.2, WGII SPM C.5.4; \nWGII TS.D.1.6, WGII Cross-Chapter Box FINANCE; WGIII SPM E.5.4}\nThere are adaptation options which are effective84 in reducing \nclimate risks85 for speci\ufb01c contexts, sectors and regions and \ncontribute positively to sustainable development and other \nsocietal goals. In the agriculture sector, cultivar improvements, \non-farm water management and storage, soil moisture conservation, \nirrigation86, agroforestry, community-based adaptation, and farm and \nlandscape level diversi\ufb01cation, and sustainable land management \napproaches, provide multiple bene\ufb01ts and reduce climate risks. \nReduction of food loss and waste, and adaptation measures in support \nof balanced diets contribute to nutrition, health, and biodiversity bene\ufb01ts.\n\nDocument 285: Increased \ufb01nance would \naddress soft limits to adaptation and rising climate risks while also averting \n157 Finance can originate from diverse sources, singly or in combination: public or private, local, national or international, bilateral or multilateral, and alternative sources \n(e.g., philanthropic, carbon offsets). It can be in the form of grants, technical assistance, loans (concessional and non-concessional), bonds, equity, risk insurance and \ufb01nancial \nguarantees (of various types).\nsome related losses and damages, particularly in vulnerable developing \ncountries (high con\ufb01dence). Enhanced mobilisation of and access to \n\ufb01nance, together with building capacity, are essential for implementation \nof adaptation actions and to reduce adaptation gaps given rising risks \nand costs, especially for the most vulnerable groups, regions and sectors \n(high con\ufb01dence). Public \ufb01nance is an important enabler of adaptation \nand mitigation, and can also leverage private \ufb01nance (high con\ufb01dence). \nAdaptation funding predominately comes from public sources, and \npublic mechanisms and \ufb01nance can leverage private sector \ufb01nance by \naddressing real and perceived regulatory, cost and market barriers, for \ninstance via public-private partnerships (high con\ufb01dence). Financial and \ntechnological resources enable effective and ongoing implementation \nof adaptation, especially when supported by institutions with a strong \nunderstanding of adaptation needs and capacity (high con\ufb01dence). \nAverage annual modelled mitigation investment requirements for \n2020 to 2030 in scenarios that limit warming to 2\u00b0C or 1.5\u00b0C are a \nfactor of three to six greater than current levels, and total mitigation \ninvestments (public, private, domestic and international) would need \nto increase across all sectors and regions (medium con\ufb01dence). Even \nif extensive global mitigation efforts are implemented, there will be a \nlarge need for \ufb01nancial, technical, and human resources for adaptation \n(high con\ufb01dence).\n\nDocument 98: Challenges \nremain for green bonds and similar products, in particular around \nintegrity and additionality, as well as the limited applicability of \nthese markets to many developing countries (high confidence). \n{WGII SPM C.3.2, WGII SPM C.5.4; WGIII SPM B.5.4, WGIII SPM E.5.1} \nCurrent global \ufb01nancial \ufb02ows for adaptation including from public \nand private \ufb01nance sources, are insuf\ufb01cient for and constrain \nimplementation of adaptation options, especially in developing \ncountries (high con\ufb01dence). There are widening disparities between \nthe estimated costs of adaptation and the documented \ufb01nance \nallocated to adaptation (high con\ufb01dence). Adaptation \ufb01nance \nneeds are estimated to be higher than those assessed in AR5, and \nthe enhanced mobilisation of and access to \ufb01nancial resources are \nessential for implementation of adaptation and to reduce adaptation \ngaps (high con\ufb01dence). Annual \ufb01nance \ufb02ows targeting adaptation for \nAfrica, for example, are billions of USD less than the lowest adaptation \ncost estimates for near-term climate change (high con\ufb01dence). Adverse \nclimate impacts can further reduce the availability of \ufb01nancial resources \nby causing losses and damages and impeding national economic \ngrowth, thereby further increasing \ufb01nancial constraints for adaptation \nparticularly for developing countries and LDCs (medium con\ufb01dence). \n{WGII SPM C.1.2, WGII SPM C.3.2, WGII SPM C.5.4, WGII TS.D.1.6} \nWithout effective mitigation and adaptation, losses and damages will \ncontinue to disproportionately affect the poorest and most vulnerable \npopulations. Accelerated \ufb01nancial support for developing countries \nfrom developed countries and other sources is a critical enabler to \nenhance mitigation action {WGIII SPM. E.5.3}. Many developing \ncountries lack comprehensive data at the scale needed and lack adequate \n\ufb01nancial resources needed for adaptation for reducing associated \neconomic and non-economic losses and damages.\n\nDocument 290: Tracked \ufb01nancial \ufb02ows fall short of the levels needed for \nadaptation and to achieve mitigation goals across all sectors and \nregions (high con\ufb01dence). These gaps create many opportunities \nand the challenge of closing gaps is largest in developing \ncountries (high con\ufb01dence). This includes a stronger alignment of \npublic \ufb01nance, lowering real and perceived regulatory, cost and market \nbarriers, and higher levels of public \ufb01nance to lower the risks associated \nwith low-emission investments. Up-front risks deter economically \nsound low carbon projects, and developing local capital markets are an \noption. Investors, \ufb01nancial intermediaries, central banks and \ufb01nancial \nregulators can shift the systemic underpricing of climate-related risks. A \nrobust labelling of bonds and transparency is needed to attract savers. \n(high con\ufb01dence) {WGII SPM C.5.4; WGIII SPM B.5.4, WGIII SPM E.4, \nWGIII SPM E.5.4, WGIII 15.2, WGIII 15.6.1, WGIII 15.6.2, WGIII 15.6.7}\nThe largest climate \ufb01nance gaps and opportunities are in \ndeveloping countries (high con\ufb01dence). Accelerated support \nfrom developed countries and multilateral institutions is a critical \nenabler to enhance mitigation and adaptation action and can address \ninequities in \ufb01nance, including its costs, terms and conditions, and \neconomic vulnerability to climate change. Scaled-up public grants for \nmitigation and adaptation funding for vulnerable regions, e.g., in Sub-\nSaharan Africa, would be cost-effective and have high social returns \nin terms of access to basic energy. Options for scaling up mitigation \nand adaptation in developing regions include: increased levels of public \n\ufb01nance and publicly mobilised private \ufb01nance \ufb02ows from developed \nto developing countries in the context of the USD 100 billion-a-year \ngoal of the Paris Agreement; increase the use of public guarantees \nto reduce risks and leverage private \ufb02ows at lower cost; local capital \nmarkets development; and building greater trust in international \ncooperation processes.","conversation_history":[{"role":"user","content":"I'm interested in the recent IPCC report, specifically in the section about adaptation and resilience finance."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":72,"topic":"Climate Change Action"}}
{"id":"22840227-c775-4d2d-a8f7-dcb95c46c845","question":"What is it?","reference_answer":"The uncertainty in the total potential is typically 25\u201350%.","reference_context":"Document 250: Synergies with mitigation are identi\ufb01ed as high, medium, and low. The right-hand side of panel (a) provides an overview of selected \nmitigation options and their estimated costs and potentials in 2030. Relative potentials and costs will vary by place, context and time and in the longer term compared to 2030. Costs \nare net lifetime discounted monetary costs of avoided greenhouse gas emissions calculated relative to a reference technology. The potential (horizontal axis) is the quantity of net \nGHG emission reduction that can be achieved by a given mitigation option relative to a speci\ufb01ed emission baseline. Net GHG emission reductions are the sum of reduced emissions \nand\/or enhanced sinks. The baseline used consists of current policy (around 2019) reference scenarios from the AR6 scenarios database (25\u201375 percentile values). The mitigation \npotentials are assessed independently for each option and are not necessarily additive. Health system mitigation options are included mostly in settlement and infrastructure \n(e.g., ef\ufb01cient healthcare buildings) and cannot be identi\ufb01ed separately. Fuel switching in industry refers to switching to electricity, hydrogen, bioenergy and natural gas. The length \nof the solid bars represents the mitigation potential of an option. Potentials are broken down into cost categories, indicated by different colours (see legend). Only discounted lifetime \nmonetary costs are considered. Where a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such \nas geographical location, resource availability, and regional circumstances, and the colours indicate the range of estimates. The uncertainty in the total potential is typically 25\u201350%. \nWhen interpreting this \ufb01gure, the following should be taken into account: (1) The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) \nbeing displaced, the rate of new technology adoption, and several other factors; (2) Different options have different feasibilities beyond the cost aspects, which are not re\ufb02ected in \nthe \ufb01gure; and (3) Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included. \nPanel (b) displays the indicative potential of demand-side mitigation options for 2050.\n\nDocument 251: Where a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such \nas geographical location, resource availability, and regional circumstances, and the colours indicate the range of estimates. The uncertainty in the total potential is typically 25\u201350%. \nWhen interpreting this \ufb01gure, the following should be taken into account: (1) The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) \nbeing displaced, the rate of new technology adoption, and several other factors; (2) Different options have different feasibilities beyond the cost aspects, which are not re\ufb02ected in \nthe \ufb01gure; and (3) Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included. \nPanel (b) displays the indicative potential of demand-side mitigation options for 2050. Potentials are estimated based on approximately 500 bottom-up studies representing all \nglobal regions. The baseline (white bar) is provided by the sectoral mean GHG emissions in 2050 of the two scenarios (IEA-STEPS and IP_ModAct) consistent with policies announced \nby national governments until 2020. The green arrow represents the demand-side emissions reductions potentials. The range in potential is shown by a line connecting dots displaying \nthe highest and the lowest potentials reported in the literature. Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns \nenabled by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in end-use sectors (buildings, land transport, \nfood) by 40\u201370% by 2050 compared to baseline scenarios, while some regions and socioeconomic groups require additional energy and resources. The last row shows how demand-\nside mitigation options in other sectors can in\ufb02uence overall electricity demand. The dark grey bar shows the projected increase in electricity demand above the 2050 baseline due \nto increasing electri\ufb01cation in the other sectors.\n\nDocument 249: 104\nSection 4\nSection 1\nSection 4\nFigure 4.4: Multiple Opportunities for scaling up climate action. Panel (a) presents selected mitigation and adaptation options across different systems. The left hand side \nof panel (a) shows climate responses and adaptation options assessed for their multidimensional feasibility at global scale, in the near term and up to 1.5\u00b0C global warming. As \nliterature above 1.5\u00b0C is limited, feasibility at higher levels of warming may change, which is currently not possible to assess robustly. The term response is used here in addition to \nadaptation because some responses, such as migration, relocation and resettlement may or may not be considered to be adaptation. Migration, when voluntary, safe and orderly, \nallows reduction of risks to climatic and non-climatic stressors. Forest based adaptation includes sustainable forest management, forest conservation and restoration, reforestation \nand afforestation. WASH refers to water, sanitation and hygiene. Six feasibility dimensions (economic, technological, institutional, social, environmental and geophysical) were used \nto calculate the potential feasibility of climate responses and adaptation options, along with their synergies with mitigation. For potential feasibility and feasibility dimensions, the \n\ufb01gure shows high, medium, or low feasibility. Synergies with mitigation are identi\ufb01ed as high, medium, and low. The right-hand side of panel (a) provides an overview of selected \nmitigation options and their estimated costs and potentials in 2030. Relative potentials and costs will vary by place, context and time and in the longer term compared to 2030. Costs \nare net lifetime discounted monetary costs of avoided greenhouse gas emissions calculated relative to a reference technology. The potential (horizontal axis) is the quantity of net \nGHG emission reduction that can be achieved by a given mitigation option relative to a speci\ufb01ed emission baseline. Net GHG emission reductions are the sum of reduced emissions \nand\/or enhanced sinks. The baseline used consists of current policy (around 2019) reference scenarios from the AR6 scenarios database (25\u201375 percentile values). The mitigation \npotentials are assessed independently for each option and are not necessarily additive.\n\nDocument 245: The system transitions make possible the transformative adaptation \nrequired for high levels of human health and well-being, economic and \nsocial resilience, ecosystem health, and planetary health. {WGII SPM \nA, WGII Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM \nC.2.1, SR1.5 SPM C.2, SR1.5 SPM C.5}\nFeasible, effective and low-cost options for mitigation and \nadaptation are already available (high con\ufb01dence) (Figure 4.4). \nMitigation options costing USD 100 tCO2-eq\u20131 or less could reduce \n151 System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors. This report \nhas a particular focus on the following system transitions: energy; industry; cities, settlements and infrastructure; land, ocean, food and water; health and nutrition; and society, \nlivelihood and economies. {WGII SPM A, WGII Figure SPM.1, WGII Figure SPM.4; SR1.5 SPM C.2}\n152 See Annex I: Glossary.\nglobal GHG emissions by at least half the 2019 level by 2030 (options \ncosting less than USD 20 tCO2-eq\u20131 are estimated to make up more \nthan half of this potential) (high con\ufb01dence) (Figure 4.4). The \navailability, feasibility152 and potential of mitigation or effectiveness \nof adaptation options in the near term differ across systems and \nregions (very high confidence). {WGII SPM C.2; WGIII SPM C.12, \nWGIII SPM E.1.1; SR1.5 SPM B.6} \nDemand-side measures and new ways of end-use service \nprovision can reduce global GHG emissions in end-use sectors by \n40 to 70% by 2050 compared to baseline scenarios, while some \nregions and socioeconomic groups require additional energy \nand resources. Demand-side mitigation encompasses changes in \ninfrastructure use, end-use technology adoption, and socio-cultural and \nbehavioural change.","conversation_history":[{"role":"user","content":"I'm curious about the total potential of mitigation options presented in the IPCC report, specifically regarding the estimated range of uncertainty."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":250,"topic":"Climate Change Action"}}
{"id":"5e23f933-57b1-4556-9ac0-e153ddd9ecdd","question":"What is the percentage contribution of each?","reference_answer":"In 2019, approximately 34% of net global GHG emissions came from the energy sector, 24% from industry, 22% from AFOLU (Agriculture, Forestry, and Other Land Use), 15% from transport, and 6% from buildings.","reference_context":"Document 18: 44\nSection 2\nSection 1\nSection 2\nAverage annual GHG emissions during 2010\u20132019 were higher \nthan in any previous decade, but the rate of growth between \n2010 and 2019 (1.3% yr-1) was lower than that between 2000 \nand 2009 (2.1% yr-1)69. Historical cumulative net CO2 emissions from \n1850 to 2019 were 2400 \u00b1240 GtCO2. Of these, more than half (58%) \noccurred between 1850 and 1989 [1400 \u00b1195 GtCO2], and about 42% \nbetween 1990 and 2019 [1000 \u00b190 GtCO2]. Global net anthropogenic \nGHG emissions have been estimated to be 59\u00b16.6 GtCO2-eq in 2019, \nabout 12% (6.5 GtCO2-eq) higher than in 2010 and 54% (21 GtCO2-eq) \nhigher than in 1990. By 2019, the largest growth in gross emissions \noccurred in CO2 from fossil fuels and industry (CO2-FFI) followed by \nCH4, whereas the highest relative growth occurred in fluorinated \ngases (F-gases), starting from low levels in 1990. (high confidence) \n{WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, \nWGIII Figure SPM.2}\nRegional contributions to global human-caused GHG emissions \ncontinue to differ widely. Historical contributions of CO2 emissions \nvary substantially across regions in terms of total magnitude, but also \nin terms of contributions to CO2-FFI (1650 \u00b1 73 GtCO2-eq) and net \nCO2-LULUCF (760 \u00b1 220 GtCO2-eq) emissions (Figure 2.2). Variations \nin regional and national per capita emissions partly re\ufb02ect different \ndevelopment stages, but they also vary widely at similar income \nlevels.\n\nDocument 19: (high confidence) \n{WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, \nWGIII Figure SPM.2}\nRegional contributions to global human-caused GHG emissions \ncontinue to differ widely. Historical contributions of CO2 emissions \nvary substantially across regions in terms of total magnitude, but also \nin terms of contributions to CO2-FFI (1650 \u00b1 73 GtCO2-eq) and net \nCO2-LULUCF (760 \u00b1 220 GtCO2-eq) emissions (Figure 2.2). Variations \nin regional and national per capita emissions partly re\ufb02ect different \ndevelopment stages, but they also vary widely at similar income \nlevels. Average per capita net anthropogenic GHG emissions in 2019 \nranged from 2.6 tCO2-eq to 19 tCO2-eq across regions (Figure 2.2). \nLeast Developed Countries (LDCs) and Small Island Developing States (SIDS) \nhave much lower per capita emissions (1.7 tCO2-eq and 4.6 tCO2-eq, \nrespectively) than the global average (6.9 tCO2-eq), excluding \nCO2-LULUCF\n. Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence).\n\nDocument 27: 46\nSection 2\nSection 1\nSection 2\nFigure 2.2: Regional GHG emissions, and the regional proportion of total cumulative production-based CO2 emissions from 1850 to 2019. Panel (a) shows the \nshare of historical cumulative net anthropogenic CO2 emissions per region from 1850 to 2019 in GtCO2. This includes CO2-FFI and CO2-LULUCF. Other GHG emissions are not included. \nCO2-LULUCF emissions are subject to high uncertainties, re\ufb02ected by a global uncertainty estimate of \u00b170% (90% con\ufb01dence interval). Panel (b) shows the distribution of regional \nGHG emissions in tonnes CO2-eq per capita by region in 2019. GHG emissions are categorised into: CO2-FFI; net CO2-LULUCF; and other GHG emissions (CH4, N2O, \ufb02uorinated gases, \nexpressed in CO2-eq using GWP100-AR6). The height of each rectangle shows per capita emissions, the width shows the population of the region, so that the area of the rectangles \nrefers to the total emissions for each region. Emissions from international aviation and shipping are not included. In the case of two regions, the area for CO2-LULUCF is below the \naxis, indicating net CO2 removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr\u20131 (GWP100-AR6)) for the time period \n1990\u20132019. Percentage values refer to the contribution of each region to total GHG emissions in each respective time period. The single-year peak of emissions in 1997 was due to \nhigher CO2-LULUCF emissions from a forest and peat \ufb01re event in South East Asia. Regions are as grouped in Annex II of WGIII.\n\nDocument 20: Around 48% of the global population in 2019 lives in countries \nemitting on average more than 6 tCO2-eq per capita, 35% of the global \npopulation live in countries emitting more than 9 tCO2-eq per capita70 \n(excluding CO2-LULUCF) while another 41% live in countries emitting less \nthan 3 tCO2-eq per capita. A substantial share of the population in these \nlow-emitting countries lack access to modern energy services. (high con\ufb01dence)\n{WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3}\nNet GHG emissions have increased since 2010 across all major \nsectors (high con\ufb01dence). In 2019, approximately 34% (20 GtCO2-eq) \nof net global GHG emissions came from the energy sector, 24% \n(14 GtCO2-eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% \n(8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2-eq) from buildings71 \n(high con\ufb01dence). Average annual GHG emissions growth between \n69 \nGHG emission metrics are used to express emissions of different GHGs in a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalents (CO2-eq) using \nthe Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports \ncontain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of \nmetric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the complexity of the physical climate \nsystem and its response to past and future GHG emissions.","conversation_history":[{"role":"user","content":"I'm interested in the statistical breakdown of net global GHG emissions in 2019 by different sectors."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":18,"topic":"Global GHG Emissions"}}
{"id":"02c61ea2-fbce-4f6a-8b23-58203bbf5a57","question":"What are the benefits of these?","reference_answer":"Human health will benefit from integrated mitigation and adaptation options that mainstream health into food, infrastructure, social protection, and water policies. Balanced and sustainable healthy diets and reduced food loss and waste present important opportunities for adaptation and mitigation while generating significant co-benefits in terms of biodiversity and human health.","reference_context":"Document 261: 106\nSection 4\nSection 1\nSection 4\nand marginalised communities including people living in informal \nsettlements (high con\ufb01dence). {WGII SPM C.2.5, WGII SPM C.2.6, WGII \nSPM C.2.7, WGII SPM D.3.2, WGII TS.E.1.4, WGII Cross-Chapter Box FEAS; \nWGIII SPM C.6, WGIII SPM C.6.2, WGIII SPM D.1.3, WGIII SPM D.2.1}\nResponses to ongoing sea level rise and land subsidence in low-lying \ncoastal cities and settlements and small islands include protection, \naccommodation, advance and planned relocation. These responses \nare more effective if combined and\/or sequenced, planned well ahead, \naligned with sociocultural values and development priorities, and \nunderpinned by inclusive community engagement processes. (high \ncon\ufb01dence) {WGII SPM C.2.8}\n4.5.4. Land, Ocean, Food, and Water\nThere is substantial mitigation and adaptation potential from \noptions in agriculture, forestry and other land use, and in the \noceans, that could be upscaled in the near term across most \nregions (high con\ufb01dence) (Figure 4.5). Conservation, improved \nmanagement, and restoration of forests and other ecosystems offer \nthe largest share of economic mitigation potential, with reduced \ndeforestation in tropical regions having the highest total mitigation \npotential. Ecosystem restoration, reforestation, and afforestation can \nlead to trade-offs due to competing demands on land. Minimizing \ntrade-offs requires integrated approaches to meet multiple objectives \nincluding food security. Demand-side measures (shifting to sustainable \nhealthy diets and reducing food loss\/waste) and sustainable agricultural \nintensi\ufb01cation can reduce ecosystem conversion and CH4 and N2O emissions, \nand free up land for reforestation and ecosystem restoration. \nSustainably sourced agriculture and forest products, including \nlong-lived wood products, can be used instead of more GHG-intensive \nproducts in other sectors.\n\nDocument 265: Enhancing natural water retention \nsuch as by restoring wetlands and rivers, land use planning such as no \nbuild zones or upstream forest management, can further reduce \ufb02ood risk \n(medium con\ufb01dence). For inland \ufb02ooding, combinations of non-structural \nmeasures like early warning systems and structural measures like levees \nhave reduced loss of lives (medium confidence), but hard defences \nagainst flooding or sea level rise can also be maladaptive \n(high con\ufb01dence). {WGII SPM C.2.1, WGII SPM C.4.1, WGII SPM C.4.2, \nWGII SPM C.2.5}\nProtection and restoration of coastal \u2018blue carbon\u2019 ecosystems \n(e.g., mangroves, tidal marshes and seagrass meadows) could \nreduce emissions and\/or increase carbon uptake and storage (medium \ncon\ufb01dence). Coastal wetlands protect against coastal erosion \nand \ufb02ooding (very high con\ufb01dence). Strengthening precautionary \napproaches, such as rebuilding overexploited or depleted \ufb01sheries, and \nresponsiveness of existing \ufb01sheries management strategies reduces \nnegative climate change impacts on \ufb01sheries, with bene\ufb01ts for regional \neconomies and livelihoods (medium con\ufb01dence). Ecosystem-based \nmanagement in fisheries and aquaculture supports food security, \nbiodiversity, human health and well-being (high confidence). \n{WGII SPM C.2.2, WGII SPM C.2; SROCC SPM C2.3, SROCC SPM C.2.4} \n4.5.5. Health and Nutrition\nHuman health will bene\ufb01t from integrated mitigation and \nadaptation options that mainstream health into food, \ninfrastructure, social protection, and water policies (very high \ncon\ufb01dence). Balanced and sustainable healthy diets156 and reduced \nfood loss and waste present important opportunities for adaptation \nand mitigation while generating signi\ufb01cant co-bene\ufb01ts in terms \nof biodiversity and human health (high con\ufb01dence).\n\nDocument 157: 79\nLong-Term Climate and Development Futures\nSection 3\nlong-term planning and implementation of adaptation actions with \nbene\ufb01ts to many sectors and systems. (high con\ufb01dence) {WGII SPM C.4, \nWGII SPM.C.4.1, WGII SPM C.4.2, WGII SPM C.4.3}\nSea level rise poses a distinctive and severe adaptation challenge \nas it implies both dealing with slow onset changes and increases \nin the frequency and magnitude of extreme sea level events (high \ncon\ufb01dence). Such adaptation challenges would occur much earlier \nunder high rates of sea level rise (high con\ufb01dence). Responses to ongoing \nsea level rise and land subsidence include protection, accommodation, \nadvance and planned relocation (high con\ufb01dence). These responses \nare more effective if combined and\/or sequenced, planned well ahead, \naligned with sociocultural values and underpinned by inclusive \ncommunity engagement processes (high con\ufb01dence). Ecosystem-based \nsolutions such as wetlands provide co-bene\ufb01ts for the environment \nand climate mitigation, and reduce costs for \ufb02ood defences (medium \ncon\ufb01dence), but have site-speci\ufb01c physical limits, at least above 1.5\u00baC \nof global warming (high con\ufb01dence) and lose effectiveness at high \nrates of sea level rise beyond 0.5 to 1 cm yr-1 (medium con\ufb01dence). \nSeawalls can be maladaptive as they effectively reduce impacts in the \nshort term but can also result in lock-ins and increase exposure to climate \nrisks in the long term unless they are integrated into a long-term adaptive \nplan (high con\ufb01dence). {WGI SPM C.2.5; WGII SPM C.2.8, WGII SPM C.4.1; \nWGII 13.10, WGII Cross-Chapter Box SLR; SROCC SPM B.9, SROCC SPM C.3.2, \nSROCC Figure SPM.4, SROCC Figure SPM.5c} (Figure 3.4)\n\nDocument 74: 56\nSection 2\nSection 1\nSection 2\nwetlands, rangelands, mangroves and forests); while afforestation and \nreforestation, restoration of high-carbon ecosystems, agroforestry, and \nthe reclamation of degraded soils take more time to deliver measurable \nresults. Signi\ufb01cant synergies exist between adaptation and mitigation, \nfor example through sustainable land management approaches. \nAgroecological principles and practices and other approaches \nthat work with natural processes support food security, nutrition, \nhealth and well-being, livelihoods and biodiversity, sustainability and \necosystem services. (high con\ufb01dence) {WGII SPM C.2.1, WGII SPM C.2.2, \nWGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; \nSROCC SPM C.2}\nCombinations of non-structural measures like early warning systems \nand structural measures like levees have reduced loss of lives in case \nof inland \ufb02ooding (medium con\ufb01dence) and early warning systems \nalong with \ufb02ood-proo\ufb01ng of buildings have proven to be cost-effective \nin the context of coastal \ufb02ooding under current sea level rise (high \ncon\ufb01dence). Heat Health Action Plans that include early warning and \nresponse systems are effective adaptation options for extreme heat \n(high con\ufb01dence). Effective adaptation options for water, food and \nvector-borne diseases include improving access to potable water, \nreducing exposure of water and sanitation systems to extreme weather \nevents, and improved early warning systems, surveillance, and vaccine \ndevelopment (very high con\ufb01dence). Adaptation options such as \ndisaster risk management, early warning systems, climate services \nand social safety nets have broad applicability across multiple sectors \n(high con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm looking into the integrated mitigation and adaptation options for human health as outlined in the IPCC report."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":261,"topic":"Climate Change Action"}}
{"id":"7ec472b4-140f-4e8d-bafc-263ed4db89cd","question":"What is the difference between these two?","reference_answer":"Achieving global net zero CO2 emissions requires all remaining anthropogenic CO2 emissions to be balanced by durably stored CO2 from anthropogenic removal, which is a requirement to stabilize CO2-induced global surface temperature increase. Net zero GHG emissions, on the other hand, require metric-weighted anthropogenic GHG emissions to equal CO2 removal. Net zero CO2 emissions are reached before net zero GHGs.","reference_context":"Document 86: 60\nSection 2\nSection 1\nSection 2\nCross-Section Box.1: Understanding Net Zero CO2 and Net Zero GHG Emissions \nLimiting human-caused global warming to a speci\ufb01c level requires limiting cumulative CO2 emissions, reaching net zero or net negative \nCO2 emissions, along with strong reductions in other GHG emissions (see 3.3.2). Future additional warming will depend on future emissions, \nwith total warming dominated by past and future cumulative CO2 emissions. {WGI SPM D.1.1, WGI Figure SPM.4; SR1.5 SPM A.2.2} \nReaching net zero CO2 emissions is different from reaching net zero GHG emissions. The timing of net zero for a basket of GHGs depends \non the emissions metric, such as global warming potential over a 100-year period, chosen to convert non-CO2 emissions into CO2-equivalent (high \ncon\ufb01dence). However, for a given emissions pathway, the physical climate response is independent of the metric chosen (high con\ufb01dence). \n{WGI SPM D.1.8; WGIII Box TS.6, WGIII Cross-Chapter Box 2}\nAchieving global net zero GHG emissions requires all remaining CO2 and metric-weighted98 non-CO2 GHG emissions to be \ncounterbalanced by durably stored CO2 removals (high con\ufb01dence). Some non-CO2 emissions, such as CH4 and N2O from agriculture, \ncannot be fully eliminated using existing and anticipated technical measures. {WGIII SPM C.2.4, WGIII SPM C.11.4, WGIII Cross-Chapter Box 3}\nGlobal net zero CO2 or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that \nothers reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions \nvary by sector and region.\n\nDocument 177: 85\nLong-Term Climate and Development Futures\nSection 3\n3.3.2 Net Zero Emissions: Timing and Implications\nFrom a physical science perspective, limiting human-caused \nglobal warming to a speci\ufb01c level requires limiting cumulative \nCO2 emissions, reaching net zero or net negative CO2 emissions, \nalong with strong reductions of other GHG emissions \n(see Cross-Section Box.1). Global modelled pathways that reach \nand sustain net zero GHG emissions are projected to result in \na gradual decline in surface temperature (high con\ufb01dence). \nReaching net zero GHG emissions primarily requires deep reductions in \nCO2, methane, and other GHG emissions, and implies net negative \nCO2 emissions.134 Carbon dioxide removal (CDR) will be necessary to \nachieve net negative CO2 emissions135. Achieving global net zero \nCO2 emissions, with remaining anthropogenic CO2 emissions balanced by \ndurably stored CO2 from anthropogenic removal, is a requirement to \nstabilise CO2-induced global surface temperature increase (see 3.3.3) \n(high con\ufb01dence). This is different from achieving net zero GHG \nemissions, where metric-weighted anthropogenic GHG emissions (see \nCross-Section Box.1) equal CO2 removal (high con\ufb01dence). Emissions \npathways that reach and sustain net zero GHG emissions de\ufb01ned by the \n100-year global warming potential imply net negative CO2 emissions \nand are projected to result in a gradual decline in surface temperature \nafter an earlier peak (high con\ufb01dence). While reaching net zero CO2 or net \nzero GHG emissions requires deep and rapid reductions in gross \nemissions, the deployment of CDR to counterbalance hard-\nto-abate residual emissions (e.g., some emissions from agriculture, \naviation, shipping, and industrial processes) is unavoidable (high \ncon\ufb01dence).\n\nDocument 87: {WGI SPM D.1.8; WGIII Box TS.6, WGIII Cross-Chapter Box 2}\nAchieving global net zero GHG emissions requires all remaining CO2 and metric-weighted98 non-CO2 GHG emissions to be \ncounterbalanced by durably stored CO2 removals (high con\ufb01dence). Some non-CO2 emissions, such as CH4 and N2O from agriculture, \ncannot be fully eliminated using existing and anticipated technical measures. {WGIII SPM C.2.4, WGIII SPM C.11.4, WGIII Cross-Chapter Box 3}\nGlobal net zero CO2 or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that \nothers reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions \nvary by sector and region. If and when net zero emissions for a given sector or region are reached depends on multiple factors, including \nthe potential to reduce GHG emissions and undertake carbon dioxide removal, the associated costs, and the availability of policy \nmechanisms to balance emissions and removals between sectors and countries. (high con\ufb01dence) {WGIII Box TS.6, WGIII Cross-Chapter Box 3}\nThe adoption and implementation of net zero emission targets by countries and regions also depend on equity and capacity \nconsiderations (high con\ufb01dence). The formulation of net zero pathways by countries will bene\ufb01t from clarity on scope, plans-of-action, and \nfairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global \nmodelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the \ncountry-level timing of net zero (high con\ufb01dence). The Paris Agreement also recognizes that peaking of emissions will occur later in developing \ncountries than developed countries (Article 4.1).\n\nDocument 179: Global net zero \nCO2 emissions are reached in the early 2050s in pathways that limit \nwarming to 1.5\u00b0C (>50%) with no or limited overshoot, and around \nthe early 2070s in pathways that limit warming to 2\u00b0C (>67%). While \nnon-CO2 GHG emissions are strongly reduced in all pathways that limit \nwarming to 2\u00b0C (>67%) or lower, residual emissions of CH4 and N2O \nand F-gases of about 8 [5\u201311] GtCO2-eq yr-1 remain at the time of \n134 Net zero GHG emissions de\ufb01ned by the 100-year global warming potential. See footnote 70.\n135 See Section 3.3.3 and 3.4.1.\nnet zero GHG, counterbalanced by net negative CO2 emissions. \n \nAs a result, net zero CO2 would be reached before net zero GHGs \n(high con\ufb01dence). {WGIII SPM C.2, WGIII SPM C.2.3, WGIII SPM C.2.4, \nWGIII Table SPM.2, WGIII 3.3} (Figure 3.6) \nthe global emissions reported in WGIII SPM Section B and WGIII Chapter 2; this ensures internal consistency in assumptions about emission sources and activities, as well as \nconsistency with temperature projections based on the physical climate science assessment by WGI (see WGIII SPM Footnote 49). Negative values (e.g., in C5, C6) represent \nan increase in emissions. The modelled GHG emissions in 2019 are 55 [53\u201358] GtCO2-eq, thus within the uncertainty ranges of estimates for 2019 emissions [53-66] GtCO2-eq \n(see 2.1.1). \n4 Emissions milestones are provided for 5-year intervals in order to be consistent with the underlying 5-year time-step data of the modelled pathways. Ranges in square \nbrackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile 5-year interval and the upper bound of the 95th percentile \n5-year interval.","conversation_history":[{"role":"user","content":"I'm interested in the difference between achieving global net zero CO2 emissions and net zero GHG emissions."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":86,"topic":"Climate Change Scenarios"}}
{"id":"34e87103-cbde-4852-8540-611191bda76b","question":"What do they include?","reference_answer":"Effective climate governance is influenced by factors such as providing overall direction based on national circumstances, setting targets and priorities, mainstreaming climate action across policy domains and levels, enhancing monitoring and evaluation, regulatory certainty, prioritizing inclusive, transparent and equitable decision-making, improving access to finance and technology, and drawing on diverse knowledge and partnerships.","reference_context":"Document 279: The synergies and trade-offs differ depending on the context and the scale of implementation. Scale of implementation particularly matters when there is \ncompetition for scarce resources. For the sake of uniformity, we are not reporting the con\ufb01dence levels because there is knowledge gap in adaptation option wise relation with SDGs \nand their con\ufb01dence level which is evident from WGII \ufb01g SPM.4b. {WGII Figure SPM.4b; WGIII Figure SPM.8}\nEffective climate governance enables mitigation and adaptation \nby providing overall direction based on national circumstances, \nsetting targets and priorities, mainstreaming climate action across \npolicy domains and levels, based on national circumstances and \nin the context of international cooperation. Effective governance \nenhances monitoring and evaluation and regulatory certainty, \nprioritising inclusive, transparent and equitable decision-making, \nand improves access to \ufb01nance and technology (high con\ufb01dence). \nThese functions can be promoted by climate-relevant laws and \nplans, which are growing in number across sectors and regions, \nadvancing mitigation outcomes and adaptation benefits (high \nconfidence). Climate laws have been growing in number and \nhave helped deliver mitigation and adaptation outcomes (medium \ncon\ufb01dence). {WGII SPM C.5, WGII SPM C.5.1, WGII SPM C5.4, WGII SPM C.5.6; \nWGIII SPM B.5.2, WGIII SPM E.3.1}\nEffective \nmunicipal, \nnational \nand \nsub-national \nclimate \ninstitutions, such as expert and co-ordinating bodies, enable \nco-produced, multi-scale decision-processes, build consensus \nfor action among diverse interests, and inform strategy settings \n(high con\ufb01dence). This requires adequate institutional capacity at \nall levels (high con\ufb01dence). Vulnerabilities and climate risks are often \nreduced through carefully designed and implemented laws, policies, \nparticipatory processes, and interventions that address context \nspeci\ufb01c inequities such as based on gender, ethnicity, disability, age, \nlocation and income (high con\ufb01dence).\n\nDocument 280: This requires adequate institutional capacity at \nall levels (high con\ufb01dence). Vulnerabilities and climate risks are often \nreduced through carefully designed and implemented laws, policies, \nparticipatory processes, and interventions that address context \nspeci\ufb01c inequities such as based on gender, ethnicity, disability, age, \nlocation and income (high con\ufb01dence). Policy support is in\ufb02uenced by \nIndigenous Peoples, businesses, and actors in civil society, including, \nyouth, labour, media, and local communities, and effectiveness is \nenhanced by partnerships between many different groups in society \n(high con\ufb01dence). Climate-related litigation is growing, with a large \nnumber of cases in some developed countries and with a much smaller \nnumber in some developing countries, and in some cases has in\ufb02uenced \nthe outcome and ambition of climate governance (medium con\ufb01dence). \n{WGII SPM C2.6, WGII SPM C.5.2, WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.3.1; WGIII SPM E3.2, WGIII SPM E.3.3}\nEffective climate governance is enabled by inclusive decision \nprocesses, allocation of appropriate resources, and institutional \nreview, monitoring and evaluation (high con\ufb01dence). Multi-level, \nhybrid and cross-sector governance facilitates appropriate consideration \nfor co-bene\ufb01ts and trade-offs, particularly in land sectors where decision \nprocesses range from farm level to national scale (high con\ufb01dence). \nConsideration of climate justice can help to facilitate shifting development \npathways towards sustainability. {WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, \nSRCCL TS.1}\nDrawing on diverse knowledge and partnerships, including \nwith women, youth, Indigenous Peoples, local communities, and \nethnic minorities can facilitate climate resilient development \nand has allowed locally appropriate and socially acceptable \nsolutions (high con\ufb01dence).\n\nDocument 278: 110\nSection 4\nSection 1\nSection 4\nin WGIII Figure SPM.8 under Urban systems, under Buildings and under Transport and adaptation options listed in WGII Figure SPM.4b under Urban and infrastructure systems. Land \nsystem comprises mitigation options listed in WGIII Figure SPM.8 under AFOLU and adaptation options listed in WGII Figure SPM.4b under Land and ocean systems: forest-based \nadaptation, agroforestry, biodiversity management and ecosystem connectivity, improved cropland management, ef\ufb01cient livestock management, water use ef\ufb01ciency and water \nresource management. Ocean ecosystems comprises adaptation options listed in WGII Figure SPM.4b under Land and ocean systems: coastal defence and hardening, integrated \ncoastal zone management and sustainable aquaculture and \ufb01sheries. Society, livelihood and economies comprises adaptation options listed in WGII Figure SPM.4b under Cross-\nsectoral; Industry comprises all those mitigation options listed in WGIII Figure SPM.8 under Industry. SDG 13 (Climate Action) is not listed because mitigation\/ adaptation is being \nconsidered in terms of interaction with SDGs and not vice versa (SPM SR1.5 Figure SPM.4 caption). The bars denote the strength of the connection and do not consider the strength \nof the impact on the SDGs. The synergies and trade-offs differ depending on the context and the scale of implementation. Scale of implementation particularly matters when there is \ncompetition for scarce resources. For the sake of uniformity, we are not reporting the con\ufb01dence levels because there is knowledge gap in adaptation option wise relation with SDGs \nand their con\ufb01dence level which is evident from WGII \ufb01g SPM.4b. {WGII Figure SPM.4b; WGIII Figure SPM.8}\nEffective climate governance enables mitigation and adaptation \nby providing overall direction based on national circumstances, \nsetting targets and priorities, mainstreaming climate action across \npolicy domains and levels, based on national circumstances and \nin the context of international cooperation. Effective governance \nenhances monitoring and evaluation and regulatory certainty, \nprioritising inclusive, transparent and equitable decision-making, \nand improves access to \ufb01nance and technology (high con\ufb01dence).\n\nDocument 281: Multi-level, \nhybrid and cross-sector governance facilitates appropriate consideration \nfor co-bene\ufb01ts and trade-offs, particularly in land sectors where decision \nprocesses range from farm level to national scale (high con\ufb01dence). \nConsideration of climate justice can help to facilitate shifting development \npathways towards sustainability. {WGII SPM C.5.5, WGII SPM C.5.6, \nWGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, \nSRCCL TS.1}\nDrawing on diverse knowledge and partnerships, including \nwith women, youth, Indigenous Peoples, local communities, and \nethnic minorities can facilitate climate resilient development \nand has allowed locally appropriate and socially acceptable \nsolutions (high con\ufb01dence). {WGII SPM D.2, D.2.1}\nMany regulatory and economic instruments have already been \ndeployed successfully. These instruments could support deep \nemissions reductions if scaled up and applied more widely. \nPractical experience has informed instrument design and helped to \nimprove predictability, environmental effectiveness, economic ef\ufb01ciency, \nand equity. (high con\ufb01dence) {WGII SPM E.4; WGIII SPM E.4.2}\nScaling up and enhancing the use of regulatory instruments, \nconsistent with national circumstances, can improve mitigation \noutcomes in sectoral applications (high con\ufb01dence), and \nregulatory instruments that include \ufb02exibility mechanisms \ncan reduce costs of cutting emissions (medium con\ufb01dence). \n{WGII SPM C.5.4; WGIII SPM E.4.1} \nWhere implemented, carbon pricing instruments have incentivized \nlow-cost emissions reduction measures, but have been less \neffective, on their own and at prevailing prices during the \nassessment period, to promote higher-cost measures necessary \nfor further reductions (medium con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm curious about the factors that influence the effectiveness of climate governance as outlined in the IPCC report."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":279,"topic":"Climate Change Action"}}
{"id":"b9428714-00bb-4a23-866f-f0310f1e104d","question":"What are some of these?","reference_answer":"Barriers to implementation of AFOLU mitigation include insufficient institutional and financial support, uncertainty over long-term additionality and trade-offs, weak governance, insecure land ownership, low incomes and the lack of access to alternative sources of income, and the risk of reversal.","reference_context":"Document 90: Current development pathways may create behavioural, \nspatial, economic and social barriers to accelerated mitigation at all \nscales (high con\ufb01dence). Choices made by policymakers, citizens, the \nprivate sector and other stakeholders in\ufb02uence societies\u2019 development \npathways (high con\ufb01dence). Structural factors of national circumstances \nand capabilities (e.g., economic and natural endowments, political \nsystems and cultural factors and gender considerations) affect the \nbreadth and depth of climate governance (medium con\ufb01dence). The \nextent to which civil society actors, political actors, businesses, youth, \nlabour, media, Indigenous Peoples, and local communities are engaged \nin\ufb02uences political support for climate change mitigation and eventual \npolicy outcomes (medium con\ufb01dence). {WGIII SPM C.3.6, WGIII SPM E.1.1, \nWGIII SPM E.2.1, WGIII SPM E.3.3}\nThe adoption of low-emission technologies lags in most \ndeveloping countries, particularly least developed ones, \ndue in part to weaker enabling conditions, including limited \n\ufb01nance, technology development and transfer, and capacity \n(medium con\ufb01dence). In many countries, especially those with \nlimited institutional capacity, several adverse side-effects have \nbeen observed as a result of diffusion of low-emission technology, \ne.g., low-value employment, and dependency on foreign knowledge \nand suppliers (medium con\ufb01dence). Low-emission innovation along \nwith strengthened enabling conditions can reinforce development \nbene\ufb01ts, which can, in turn, create feedbacks towards greater public \nsupport for policy (medium con\ufb01dence). Persistent and region-speci\ufb01c \nbarriers also continue to hamper the economic and political feasibility \nof deploying AFOLU mitigation options (medium con\ufb01dence). Barriers to \nimplementation of AFOLU mitigation include insuf\ufb01cient institutional and \n\ufb01nancial support, uncertainty over long-term additionality and trade-offs, \nweak governance, insecure land ownership, low incomes and the lack \nof access to alternative sources of income, and the risk of reversal (high \ncon\ufb01dence).\n\nDocument 91: Low-emission innovation along \nwith strengthened enabling conditions can reinforce development \nbene\ufb01ts, which can, in turn, create feedbacks towards greater public \nsupport for policy (medium con\ufb01dence). Persistent and region-speci\ufb01c \nbarriers also continue to hamper the economic and political feasibility \nof deploying AFOLU mitigation options (medium con\ufb01dence). Barriers to \nimplementation of AFOLU mitigation include insuf\ufb01cient institutional and \n\ufb01nancial support, uncertainty over long-term additionality and trade-offs, \nweak governance, insecure land ownership, low incomes and the lack \nof access to alternative sources of income, and the risk of reversal (high \ncon\ufb01dence). {WGIII SPM B.4.2, WGIII SPM C.9.1, WGIII SPM C.9.3} \n99 \nSee Annex I: Glossary. \n100  Adaptation limit: The point at which an actor\u2019s objectives (or system needs) cannot be secured from intolerable risks through adaptive actions. Hard adaptation limit \n- No adaptive actions are possible to avoid intolerable risks. Soft adaptation limit - Options are currently not available to avoid intolerable risks through adaptive action.\n101 Maladaptation refers to actions that may lead to increased risk of adverse climate-related outcomes, including via increased greenhouse gas emissions, increased or shifted vulnerability \nto climate change, more inequitable outcomes, or diminished welfare, now or in the future. Most often, maladaptation is an unintended consequence. See Annex I: Glossary.\n2.3.2. Adaptation Gaps and Barriers \nDespite progress, adaptation gaps exist between current \nlevels of adaptation and levels needed to respond to impacts \nand reduce climate risks (high con\ufb01dence). While progress in \nadaptation implementation is observed across all sectors and regions \n(very high con\ufb01dence), many adaptation initiatives prioritise immediate \nand near-term climate risk reduction, e.g., through hard \ufb02ood protection, \nwhich reduces the opportunity for transformational adaptation99 (high \ncon\ufb01dence). Most observed adaptation is fragmented, small in scale, \nincremental, sector-speci\ufb01c, and focused more on planning rather than \nimplementation (high con\ufb01dence).\n\nDocument 219: Societal choices and actions implemented in this decade will \ndetermine the extent to which medium and long-term development \npathways will deliver higher or lower climate resilient development \noutcomes. (high con\ufb01dence) {WGII SPM D.2, WGII SPM D.5, WGII Box TS.8; \nWGIII SPM D.3, WGIII SPM E.2, WGIII SPM E.3, WGIII SPM E.4, WGIII TS.2, \nWGIII TS.4.1, WGIII TS.6.4, WGIII 15.2, WGIII 15.6}\nEnabling conditions would need to be strengthened in the near-\nterm and barriers reduced or removed to realise opportunities \nfor deep and rapid adaptation and mitigation actions and \nclimate resilient development (high con\ufb01dence) (Figure 4.2). \nThese enabling conditions are differentiated by national, regional \nand local circumstances and geographies, according to capabilities, \nand include: equity and inclusion in climate action (see Section 4.4), \nrapid and far-reaching transitions in sectors and system (see Section \n4.5), measures to achieve synergies and reduce trade-\noffs with sustainable development goals (see Section 4.6), \ngovernance and policy improvements (see Section 4.7), access \nto finance, improved international cooperation and technology \nimprovements (see Section 4.8), and integration of near-term \nactions across sectors, systems and regions (see Section 4.9). \n{WGII SPM D.2; WGIII SPM E.1, WGIII SPM E.2}\nBarriers to feasibility would need to be reduced or removed \nto deploy mitigation and adaptation options at scale. Many \nlimits to feasibility and effectiveness of responses can be overcome \nby addressing a range of barriers, including economic, technological, \ninstitutional, social, environmental and geophysical barriers. The \nfeasibility and effectiveness of options increase with integrated, \nmulti-sectoral solutions that differentiate responses based on climate \nrisk, cut across systems and address social inequities.\n\nDocument 243: Individuals with \nhigh socio-economic status contribute disproportionately to emissions, \nand have the highest potential for emissions reductions, e.g., as \ncitizens, investors, consumers, role models, and professionals (high \ncon\ufb01dence). There are options on design of instruments such as taxes, \nsubsidies, prices, and consumption-based approaches, complemented \nby regulatory instruments to reduce high-emissions consumption while \nimproving equity and societal well-being (high con\ufb01dence). Behaviour \nand lifestyle changes to help end-users adopt low-GHG-intensive \noptions can be supported by policies, infrastructure and technology \nwith multiple co-bene\ufb01ts for societal well-being (high con\ufb01dence). \nBroadening equitable access to domestic and international \ufb01nance, \ntechnologies and capacity can also act as a catalyst for accelerating \nmitigation and shifting development pathways in low-income contexts \n(high con\ufb01dence). Eradicating extreme poverty, energy poverty, and \nproviding decent living standards to all in these regions in the context of \nachieving sustainable development objectives, in the near term, can be \nachieved without signi\ufb01cant global emissions growth (high con\ufb01dence). \nTechnology development, transfer, capacity building and \ufb01nancing can \nsupport developing countries\/ regions leapfrogging or transitioning to \nlow-emissions transport systems thereby providing multiple co-bene\ufb01ts \n(high con\ufb01dence). Climate resilient development is advanced when \nactors work in equitable, just and enabling ways to reconcile divergent \ninterests, values and worldviews, toward equitable and just outcomes \n(high con\ufb01dence). {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII \nSPM C.10.2, WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, \nWGIII TS.5.1, WGIII 5.4, WGIII 5.8, WGIII 15.2}\nRapid and far-reaching transitions across all sectors and systems \nare necessary to achieve deep emissions reductions and secure \na liveable and sustainable future for all (high con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm interested in the barriers to the implementation of AFOLU mitigation."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":90,"topic":"Climate Change Action"}}
{"id":"1f119fbe-24c2-42aa-b5b5-3f653ee38d61","question":"What does it say?","reference_answer":"Projected regional impacts on food production reflect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 enhancement of growth and water retention in currently cultivated areas. For maize yield, changes at projected global warming levels (GWLs) of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C) are indicated.","reference_context":"Document 133: Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\nFuture climate change is projected to increase the severity of impacts \nacross natural and human systems and will increase regional differences\nAreas with little or no \nproduction, or not assessed\n1Projected temperature conditions above \nthe estimated historical (1850-2005) \nmaximum mean annual temperature \nexperienced by each species, assuming \nno species relocation. \n2Includes 30,652 species of birds, \nmammals, reptiles, amphibians, marine \n\ufb01sh, benthic marine invertebrates, krill, \ncephalopods, corals, and seagrasses.\na) Risk of \nspecies losses\nb) Heat-humidity \nrisks to \nhuman health\nc) Food production \nimpacts\n3Projected regional impacts utilize a global threshold beyond which daily mean surface air temperature and relative humidity may induce \nhyperthermia that poses a risk of mortality. The duration and intensity of heatwaves are not presented here. Heat-related health outcomes \nvary by location and are highly moderated by socio-economic, occupational and other non-climatic determinants of individual health and \nsocio-economic vulnerability. The threshold used in these maps is based on a single study that synthesized data from 783 cases to \ndetermine the relationship between heat-humidity conditions and mortality drawn largely from observations in temperate climates.\nHistorical 1991\u20132005\n\nDocument 132: 73\nLong-Term Climate and Development Futures\nSection 3\nc1) Maize yield4\nc2) Fisheries yield5\nChanges (%) in \nmaximum catch \npotential\nChanges (%) in yield\n \n \n-20\n-10\n-3\n-30\n-25\n-15\n-35%\n+20\n+30\n+35%\n+10\n+3\n+25\n+15\n1\n0 days\n300\n100\n200\n10\n150\n250\n50\n365 days\n0.1\n0%\n80\n10\n40\n1\n20\n60\n5\n100%\nAreas with model disagreement\nExamples of impacts without additional adaptation\n2.4 \u2013 3.1\u00b0C\n4.2 \u2013 5.4\u00b0C\n1.5\u00b0C\n3.0\u00b0C\n1.7 \u2013 2.3\u00b0C\n0.9 \u2013 2.0\u00b0C\n3.4 \u2013 5.2\u00b0C\n1.6 \u2013 2.4\u00b0C\n3.3 \u2013 4.8\u00b0C\n3.9 \u2013 6.0\u00b0C\n2.0\u00b0C\n4.0\u00b0C\nPercentage of animal \nspecies and seagrasses \nexposed to potentially \ndangerous temperature \nconditions1, 2\nDays per year where \ncombined temperature and \nhumidity conditions pose a risk \nof mortality to individuals3\n5Projected regional impacts re\ufb02ect \ufb01sheries and marine ecosystem responses to ocean physical and biogeochemical conditions such as \ntemperature, oxygen level and net primary production. Models do not represent changes in \ufb01shing activities and some extreme climatic \nconditions. Projected changes in the Arctic regions have low con\ufb01dence due to uncertainties associated with modelling multiple interacting \ndrivers and ecosystem responses.\n4Projected regional impacts re\ufb02ect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO2 \nenhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited. \nModels do not represent pests, diseases, future agro-technological changes and some extreme climate responses.\n\nDocument 134: 74\nSection 3\nSection 1\nSection 3\nFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global warming levels (GWLs) relative to 1850-1900 levels. \nProjected risks and impacts shown on the maps are based on outputs from different subsets of Earth system models that were used to project each impact indicator without \nadditional adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and additional lines of evidence. (a) Risks of species \nlosses as indicated by the percentage of assessed species exposed to potentially dangerous temperature conditions, as de\ufb01ned by conditions beyond the estimated historical \n(1850\u20132005) maximum mean annual temperature experienced by each species, at GWLs of 1.5\u00b0C, 2\u00b0C, 3\u00b0C and 4\u00b0C. Underpinning projections of temperature are from 21 Earth \nsystem models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure \nto hypothermic conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991\u20132005) and at GWLs of 1.7\u00b0C to 2.3\u00b0C \n(mean = 1.9\u00b0C; 13 climate models), 2.4\u00b0C to 3.1\u00b0C (2.7\u00b0C; 16 climate models) and 4.2\u00b0C to 5.4\u00b0C (4.7\u00b0C; 15 climate models). Interquartile ranges of WGLs by 2081\u20132100 \nunder RCP2.6, RCP4.5 and RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII assessments. (c) Impacts \non food production: (c1) Changes in maize yield at projected GWLs of 1.6\u00b0C to 2.4\u00b0C (2.0\u00b0C), 3.3\u00b0C to 4.8\u00b0C (4.1\u00b0C) and 3.9\u00b0C to 6.0\u00b0C (4.9\u00b0C).\n\nDocument 120: Increases in hot and decreases in \ncold climatic impact-drivers, such as temperature extremes, are \nprojected in all regions (high con\ufb01dence). At 1.5\u00b0C global warming, \nheavy precipitation and \ufb02ooding events are projected to intensify \nand become more frequent in most regions in Africa, Asia (high \ncon\ufb01dence), North America (medium to high con\ufb01dence) and Europe \n(medium con\ufb01dence). At 2\u00b0C or above, these changes expand to more \nregions and\/or become more signi\ufb01cant (high con\ufb01dence), and more \nfrequent and\/or severe agricultural and ecological droughts are projected \nin Europe, Africa, Australasia and North, Central and South America \n(medium to high con\ufb01dence). Other projected regional changes include \n117 Particularly over South and South East Asia, East Asia and West Africa apart from the far west Sahel. {WGI SPM B.3.3}\n118 See Annex I: Glossary.\n119 See Annex I: Glossary.\nintensification of tropical cyclones and\/or extratropical storms \n(medium con\ufb01dence), and increases in aridity and \ufb01re weather119 \n(medium to high con\ufb01dence). Compound heatwaves and droughts \nbecome likely more frequent, including concurrently at multiple \nlocations (high con\ufb01dence). {WGI SPM C.2, WGI SPM C.2.1, WGI SPM C.2.2, \nWGI SPM C.2.3, WGI SPM C.2.4, WGI SPM C.2.7}","conversation_history":[{"role":"user","content":"The IPCC report discusses the projected regional impacts on food production."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":133,"topic":"Climate Change Risks"}}
{"id":"82fe1c23-12e8-4e1a-aea6-485a82c7c5ca","question":"What determines the extent to which they will deliver higher or lower outcomes?","reference_answer":"Societal choices and actions implemented in this decade determine the extent to which medium- and long-term pathways will deliver higher or lower climate resilient development.","reference_context":"Document 202: 91\nSection 4\nNear-Term Responses \nin a Changing Climate\n\nDocument 304: 115\nNear-Term Responses in a Changing Climate\nSection 4\nand adaptation. Effective action in all of the above areas will \nrequire near-term political commitment and follow-through, social \ncooperation, \ufb01nance, and more integrated cross-sectoral policies and \nsupport and actions. (high con\ufb01dence).  {WGII SPM C.1, WG II SPM C.2, \nWGII SPM C.2, WGII SPM C.5, WGII SPM D.2, WGII SPM D.3.2, \nWGII SPM D.3.3, WGII Figure SPM.4; WGIII SPM C.6.3, WGIII SPM C.8.2, \nWGIII SPM C.9, WGIII SPM C.9.1, WGIII SPM C.9.2, WGIII SPM D.2, \nWGIII SPM D.2.4, WGIII SPM D.3.2, WGIII SPM E.1, WGIII SPM E.2.4, \nWGIII Figure SPM.8, WGIII TS.7, WGIII TS Figure TS.29: SRCCL ES 7.4.8, \nSRCCL SPM B.6} (3.4, 4.4)\n\nDocument 203: 92\nSection 4\nSection 1\nSection 4\nSection 4 : Near-Term Responses in a Changing Climate\n4.1 The Timing and Urgency of Climate Action\nThe magnitude and rate of climate change and associated risks \ndepend strongly on near-term mitigation and adaptation actions \n(very high con\ufb01dence). Global warming is more likely than not to reach \n1.5\u00b0C between 2021 and 2040 even under the very low GHG emission \nscenarios (SSP1-1.9), and likely or very likely to exceed 1.5\u00b0C under \nhigher emissions scenarios141. Many adaptation options have medium \nor high feasibility up to 1.5\u00b0C (medium to high con\ufb01dence, depending \non option), but hard limits to adaptation have already been reached \nin some ecosystems and the effectiveness of adaptation to reduce \nclimate risk will decrease with increasing warming (high con\ufb01dence). \nSocietal choices and actions implemented in this decade determine the \nextent to which medium- and long-term pathways will deliver higher or \nlower climate resilient development (high con\ufb01dence). Climate resilient \ndevelopment prospects are increasingly limited if current greenhouse \ngas emissions do not rapidly decline, especially if 1.5\u00b0C global warming \nis exceeded in the near term (high con\ufb01dence). Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}.","conversation_history":[{"role":"user","content":"I'm interested in the factors that influence medium- and long-term pathways' effectiveness in achieving climate resilient development."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":202,"topic":"Others"}}
{"id":"74eddf58-7cfc-4142-8dc5-828476528b17","question":"What are these?","reference_answer":"Hot extremes, Heavy precipitation, Agricultural and ecological drought including heatwaves","reference_context":"Document 39: WCA (West Central Asia), \nECA (East Central Asia), TIB (Tibetan \nPlateau), EAS (East Asia), ARP (Arabian \nPeninsula), SAS (South Asia), SEA (South East \nAsia), Australasia: NAU (Northern Australia), \nCAU (Central Australia), EAU (Eastern \nAustralia), SAU (Southern Australia), NZ \n(New Zealand), Small Islands: CAR \n(Caribbean), PAC (Paci\ufb01c Small Islands)\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF\n\nDocument 38: SSA \n(Southern South America), Europe: GIC \n(Greenland\/Iceland), NEU (Northern Europe), \nWCE (Western and Central Europe), EEU \n(Eastern Europe), MED (Mediterranean), \nAfrica: MED (Mediterranean), SAH (Sahara), \nWAF (Western Africa), CAF (Central Africa), \nNEAF (North Eastern Africa), SEAF (South \nEastern Africa), WSAF (West Southern \nAfrica), ESAF (East Southern Africa), MDG \n(Madagascar), Asia: RAR (Russian Arctic), \nWSB (West Siberia), ESB (East Siberia), RFE \n(Russian Far East), WCA (West Central Asia), \nECA (East Central Asia), TIB (Tibetan \nPlateau), EAS (East Asia), ARP (Arabian \nPeninsula), SAS (South Asia), SEA (South East \nAsia), Australasia: NAU (Northern Australia), \nCAU (Central Australia), EAU (Eastern \nAustralia), SAU (Southern Australia), NZ \n(New Zealand), Small Islands: CAR \n(Caribbean), PAC (Paci\ufb01c Small Islands)\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF\n\nDocument 40: SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nNWN\nNEN\nGIC\nNEU\nRAR\nWNA\nCNA\nENA\nWCE\nEEU\nWSB\nESB\nRFE\nNCA\nMED\nWCA\nECA\nTIB\nEAS\nSCA\nCAR\nSAH\nARP\nSAS\nSEA\nNWS\nNSA\nWAF\nCAF\nNEAF\nNAU\nSAM\nNES\nWSAF SEAF\nCAU\nEAU\nSWS\nSES\nESAF\nSAU\nNZ\nSSA\nMDG\nPAC\nAfrica\nAsia\nAustralasia\nNorth\nAmerica\nCentral\nAmerica\nSouth\nAmerica\nEurope\nSmall\nIslands\nSmall\nIslands\nHot extremes\nHeavy precipitation\nAgricultural and ecological drought \nincluding heatwaves\nHazard\nDimension of Risk:","conversation_history":[{"role":"user","content":"The context mentions certain dimensions of risk."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":39,"topic":"Climate Change Risks"}}
{"id":"2e050286-b84a-455c-85db-98ac1a0e1d7a","question":"What does it state about the likelihood?","reference_answer":"The likelihood of peak global warming staying below 1.5\u00b0C ranges from 11% to 38%, with specific probabilities at 38% [33-58], 38% [34-60], 37% [33-56], 24% [15-42], 20% [13-41], 21% [14-42], 17% [12-35], and 11% [7-22].","reference_context":"Document 170: ]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.]\n \n2020 to \nnet zero \nCO2  \n510 \n[330-710]\n550 \n[340-760]\n460 \n[320-590]\n720 \n[530-930]\n890 \n[640-1160]\n860 \n[640-1180]\n910 \n[720-1150]\n1210\n[970-1490]\n1780\n[1400-2360]\n2020\u2013\n2100 \n320 \n[-210-570]\n160 \n[-220-620]\n360 \n[10-540]\n400 \n[-90-620]\n800 \n[510-1140]\n790 \n[480-1150]\n800 \n[560-1050]\n1160 \n[700-1490]\n \nat peak \nwarming\n \n1.6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.\n\nDocument 169: 84\nSection 3\nSection 1\nSection 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n2030 \n43 \n[34-60]\n41 \n[31-59]\n48 \n[35-61]\n23 \n[0-44]\n21 \n[1-42]\n27 \n[13-45]\n5 \n[0-14]\n10  \n[0-27]\n2040\n \n \n \n \n \n2050 \n84 \n[73-98]\n85 \n[72-100]\n84 \n[76-93]\n75 \n[62-91]\n64 \n[53-77]\n63 \n[52-76]\n68 \n[56-83]\n49  \n[35-65]\n29\n[11-48]\n5\n[-2 to 18]\nNet zero \nCO2  \n(% net zero \npathways) \n \n2050-2055 (100%) \n[2035-2070]\n2055-2060 \n(100%) \n[2045-2070]\n2070-2075 \n(93%) \n[2055-.]\n2070-2075 \n(91%) \n[2055-.]\n2065-2070 \n(97%) \n[2055-2090]\n2080-2085\n(86%)\n[2065-.]\nNet zero \nGHGs\n(5) \n(% net zero \npathways) \n \n2095-2100 \n(52%) \n[2050-.]\n2070-2075 \n(100%) \n[2050-2090]\n.-.\n(0%) \n[.-.]\n2070-2075 \n(87%) \n[2055-.]\n.-.\n(30%) \n[2075-.]\n.-. \n(24%) \n[2080-.]\n.-.\n(41%) \n[2075-.]\n.-.\n(31%) \n[2075-.\n\nDocument 181: 86\nSection 3\nSection 1\nSection 3\n2000\n2020\n2040\n2060\n2080\n2100\n0\n20\n40\n60\n2000\n2020\n2040\n2060\n2080\n2100\n0\n20\n40\n60\n2000\n2020\n2040\n2060\n2080\n2100\n2000\n2020\n2040\n2060\n2080\n2100\nGigatons of CO2 equivalent per year (GtCO2-eq\/yr) \nCO2\nGHG\nCO2\nGHG\nCH4\nCO2\nGHG\nCH4\na) While keeping warming to 1.5\u00b0C    \n(>50%) with no or limited overshoot\nb) While keeping warming to  2\u00b0C    (>67%)\nc) Timing for net zero \nnet zero\nnet zero\nHistorical\nHistorical\nPolicies in place in 2020\nPolicies in place in 2020\nGHGs reach net zero \nlater than CO2\nnot all \nscenarios \nreach net \nzero GHG \nby 2100\nGlobal modelled pathways that limit warming to 1.5\u00b0C (>50%) with \nno or limited overshoot reach  net zero  CO2 emissions around 2050\nTotal  greenhouse gases (GHG)  reach net zero later\nFigure 3.6: Total GHG, CO2 and CH4 emissions and timing of reaching net zero in different mitigation pathways. Top row: GHG, CO2 and CH4 emissions over time (in \nGtCO2eq) with historical emissions, projected emissions in line with policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour \n(blue, purple, and brown, respectively). Panel (a) (left) shows pathways that limit warming to 1.5\u00b0C (>50%) with no or limited overshoot (C1) and Panel (b) (right) shows \npathways that limit warming to 2\u00b0C (>67%) (C3).\n\nDocument 171: 6 \n1.6 \n1.6 \n1.7\n \n1.7 \n1.7 \n1.8 \n1.9\n2100\n \n1.3 \n1.2 \n1.4 \n1.4\n1.6 \n1.6 \n1.6 \n1.8\n \nLikelihood \nof peak \nglobal \nwarming \nstaying \nbelow (%) \no\n \n<1.5\u00b0C \n38 \n[33-58]\n38 \n[34-60]\n37 \n[33-56]\n24 \n[15-42]\n20 \n[13-41]\n21 \n[14-42]\n17 \n[12-35]\n11\n[7-22]\n<2.0\u00b0C \n90 \n[86-97]\n90 \n[85-97]\n89 \n[87-96]\n82 \n[71-93]\n76 \n[68-91]\n78 \n[69-91]\n73 \n[67-87]\n59\n[50-77]\n<3.0\u00b0C \n100 \n[99-100]\n100 \n[99-100]\n100 \n[99-100]\n100 \n[99-100]\n99 \n[98-100]\n100 \n[98-100]\n99 \n[98-99]\n98\n91\n \n[95-99]\n p50\n[p5-p95] (1)\nGHG emissions \nreductions\nfrom 2019 (%) (3)\u00a0\nEmissions milestones (4)\u00a0\nCumulative CO2\nemissions [Gt CO2](6)\nLikelihood of peak \nglobal warming staying \nbelow (%)\nGlobal mean \ntemperature \nchanges 50% \nprobability (\u00b0C)\n69\n[58-90]\n66\n[58-89]\n70\n[62-87]\n55\n[40-71]\n46\n[34-63]\n47\n[35-63]\n46\n[34-63]\n31\n[20-5]\n18\n[4-33]\n3\n[-14 to 14]\n6\n[-1 to 18]\n2\n[-10 to 11]\nMedian 5-year intervals at \nwhich projected CO2 & GHG \nemissions  of pathways in \nthis category reach net-zero, \nwith the 5th-95th percentile \ninterval in square brackets.","conversation_history":[{"role":"user","content":"The report addresses the likelihood of peak global warming staying below a certain threshold."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":170,"topic":"Climate Change Scenarios"}}
{"id":"9102f5fc-b4e5-4a12-881c-21d648b3b46d","question":"At what temperature does this occur?","reference_answer":"At 3\u00b0C.","reference_context":"Document 154: Globally, adaptation options related \nto agroforestry and forestry have a sharp decline in effectiveness at 3\u00b0C, \nwith a substantial increase in residual risk (medium con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, \nWGII Figure TS.6 Panel (e), 4.7.2} \nWith increasing global warming, more limits to adaptation will be \nreached and losses and damages, strongly concentrated among the \npoorest vulnerable populations, will increase (high con\ufb01dence). \nAlready below 1.5\u00b0C, autonomous and evolutionary adaptation \nresponses by terrestrial and aquatic ecosystems will increasingly \nface hard limits (high con\ufb01dence) (Section 2.1.2). Above 1.5\u00b0C, some \necosystem-based adaptation measures will lose their effectiveness \nin providing bene\ufb01ts to people as these ecosystems will reach hard \nadaptation limits (high con\ufb01dence). Adaptation to address the risks of \nheat stress, heat mortality and reduced capacities for outdoor work \nfor humans face soft and hard limits across regions that become \nsigni\ufb01cantly more severe at 1.5\u00b0C, and are particularly relevant for \nregions with warm climates (high con\ufb01dence). Above 1.5\u00b0C global \nwarming level, limited freshwater resources pose potential hard limits \nfor small islands and for regions dependent on glacier and snow melt \n124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound \ufb02ooding. {WGI SPM Footnote 18}\n125 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation responses can be incorporated in climate \nimpact models, and projections of future adaptation depend on currently available technologies or approaches. {WGII 4.7.2}\n(medium confidence). By 2\u00b0C, soft limits are projected for multiple \nstaple crops, particularly in tropical regions (high con\ufb01dence).\n\nDocument 153: At higher levels \nof warming, losses and damages will increase, and additional human and natural systems will reach adaptation \nlimits. Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation. Maladaptation \ncan create lock-ins of vulnerability, exposure and risks but can be avoided by long-term planning and the \nimplementation of adaptation actions that are \ufb02exible, multi-sectoral and inclusive. (high con\ufb01dence)\nThe effectiveness of adaptation to reduce climate risk is documented \nfor speci\ufb01c contexts, sectors and regions and will decrease with \nincreasing warming (high con\ufb01dence)125. For example, common \nadaptation responses in agriculture \u2013 adopting improved cultivars and \nagronomic practices, and changes in cropping patterns and crop \nsystems \u2013 will become less effective from 2\u00b0C to higher levels of \nwarming (high confidence). The effectiveness of most water-related \nadaptation options to reduce projected risks declines with increasing \nwarming (high confidence). Adaptations for hydropower and \nthermo-electric power generation are effective in most regions up to \n1.5\u00b0C to 2\u00b0C, with decreasing effectiveness at higher levels of warming \n(medium con\ufb01dence). Ecosystem-based Adaptation is vulnerable to \nclimate change impacts, with effectiveness declining with increasing \nglobal warming (high con\ufb01dence). Globally, adaptation options related \nto agroforestry and forestry have a sharp decline in effectiveness at 3\u00b0C, \nwith a substantial increase in residual risk (medium con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, \nWGII Figure TS.6 Panel (e), 4.7.2} \nWith increasing global warming, more limits to adaptation will be \nreached and losses and damages, strongly concentrated among the \npoorest vulnerable populations, will increase (high con\ufb01dence). \nAlready below 1.5\u00b0C, autonomous and evolutionary adaptation \nresponses by terrestrial and aquatic ecosystems will increasingly \nface hard limits (high con\ufb01dence) (Section 2.1.2).\n\nDocument 155: Above 1.5\u00b0C global \nwarming level, limited freshwater resources pose potential hard limits \nfor small islands and for regions dependent on glacier and snow melt \n124 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound \ufb02ooding. {WGI SPM Footnote 18}\n125 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation responses can be incorporated in climate \nimpact models, and projections of future adaptation depend on currently available technologies or approaches. {WGII 4.7.2}\n(medium confidence). By 2\u00b0C, soft limits are projected for multiple \nstaple crops, particularly in tropical regions (high con\ufb01dence). By 3\u00b0C, \nsoft limits are projected for some water management measures for \nmany regions, with hard limits projected for parts of Europe (medium \ncon\ufb01dence). {WGII SPM C.3, WGII SPM C.3.3, WGII SPM C.3.4, WGII SPM C.3.5, \nWGII TS.D.2.2, WGII TS.D.2.3; SR1.5 SPM B.6; SROCC SPM C.1}\nIntegrated, cross-cutting multi-sectoral solutions increase the \neffectiveness of adaptation. For example, inclusive, integrated \nand long-term planning at local, municipal, sub-national and national \nscales, together with effective regulation and monitoring systems \nand \ufb01nancial and technological resources and capabilities foster \nurban and rural system transition. There are a range of cross-cutting \nadaptation options, such as disaster risk management, early warning \nsystems, climate services and risk spreading and sharing that have \nbroad applicability across sectors and provide greater bene\ufb01ts to other \nadaptation options when combined. Transitioning from incremental to \ntransformational adaptation, and addressing a range of constraints, \nprimarily in the \ufb01nancial, governance, institutional and policy domains, \ncan help overcome soft adaptation limits. However, adaptation does \nnot prevent all losses and damages, even with effective adaptation and \nbefore reaching soft and hard limits.\n\nDocument 128: For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence). {WGII SPM B.4.1, WGII SPM B.4.2, \nWGII Figure SPM.3, WGII TS Appendix AII, WGII Appendix I Global to \nRegional Atlas Figure AI.46} (Figure 3.2, Figure 3.3)\nGlobal warming of 4\u00b0C and above is projected to lead to far-reaching \nimpacts on natural and human systems (high con\ufb01dence). Beyond \n4\u00b0C of warming, projected impacts on natural systems include local \nextinction of ~50% of tropical marine species (medium con\ufb01dence) \nand biome shifts across 35% of global land area (medium con\ufb01dence). \nAt this level of warming, approximately 10% of the global land area \nis projected to face both increasing high and decreasing low extreme \nstream\ufb02ow, affecting, without additional adaptation, over 2.1 billion people \n(medium con\ufb01dence) and about 4 billion people are projected to \nexperience water scarcity (medium con\ufb01dence). At 4\u00b0C of warming, the \nglobal burned area is projected to increase by 50 to 70% and the \nfire frequency by ~30% compared to today (medium confidence). \n{WGII SPM B.4.1, WGII SPM B.4.2, WGII TS.C.1.2, WGII TS.C.2.3, \nWGII TS.C.4.1, WGII TS.C.4.4} (Figure 3.2, Figure 3.3)","conversation_history":[{"role":"user","content":"I'm interested in the effectiveness of adaptation options related to agroforestry and forestry, specifically when a sharp decline is projected."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":154,"topic":"Others"}}
{"id":"45f011e1-555b-4919-816e-954eb44c70d3","question":"What are they according to that source?","reference_answer":"Vulnerability to climate change is exacerbated by factors such as poverty, governance challenges, limited access to basic services and resources, violent conflict, high levels of climate-sensitive livelihoods, inequity, and marginalisation linked to gender, ethnicity, low income, especially for many Indigenous Peoples and local communities.","reference_context":"Document 239: {WGII SPM B.5.1, WGII SPM C.2.9, \nWGII SPM D.2.1, WGII TS Box TS.4; WGIII SPM D.3, WGIII SPM D.3.3, \nWGIII SPM WGIII SPM E.3, SR1.5 SPM D.4.5} (Figure 4.3c)\nRegions and people with considerable development constraints \nhave high vulnerability to climatic hazards. Adaptation \noutcomes for the most vulnerable within and across countries \nand regions are enhanced through approaches focusing on \nequity, inclusivity, and rights-based approaches, including 3.3 to \n3.6 billion people living in contexts that are highly vulnerable \nto climate change (high con\ufb01dence). Vulnerability is higher in \nlocations with poverty, governance challenges and limited access \nto basic services and resources, violent con\ufb02ict and high levels of \nclimate-sensitive livelihoods (e.g., smallholder farmers, pastoralists, \n\ufb01shing communities) (high con\ufb01dence). Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence).\n\nDocument 240: Several risks can be moderated \nwith adaptation (high con\ufb01dence). The largest adaptation gaps \nexist among lower income population groups (high con\ufb01dence) and \nadaptation progress is unevenly distributed with observed adaptation \ngaps (high con\ufb01dence). Present development challenges causing high \nvulnerability are in\ufb02uenced by historical and ongoing patterns of \ninequity such as colonialism, especially for many Indigenous Peoples \nand local communities (high con\ufb01dence). Vulnerability is exacerbated \nby inequity and marginalisation linked to gender, ethnicity, low income \nor combinations thereof, especially for many Indigenous Peoples and \nlocal communities (high con\ufb01dence). {WGII SPM B.2, WGII SPM B.2.4, \nWGII SPM B.3.2, WGII SPM B.3.3, WGII SPM C.1, WGII SPM C.1.2, \nWGII SPM C.2.9}\nMeaningful participation and inclusive planning, informed by \ncultural values, Indigenous Knowledge, local knowledge, and \nscienti\ufb01c knowledge can help address adaptation gaps and \navoid maladaptation (high con\ufb01dence). Such actions with \ufb02exible \npathways may encourage low-regret and timely actions (very high \ncon\ufb01dence). Integrating climate adaptation into social protection \nprogrammes, including cash transfers and public works programmes, \nwould increase resilience to climate change, especially when supported \nby basic services and infrastructure (high con\ufb01dence). {WGII SPM C.2.3, \nWGII SPM C.4.3, WGII SPM C.4.4, WGII SPM C.2.9, WGII WPM D.3}\nEquity, inclusion, just transitions, broad and meaningful \nparticipation of all relevant actors in decision making at \nall scales enable deeper societal ambitions for accelerated \nmitigation, and climate action more broadly, and build social \ntrust, support transformative changes and an equitable sharing \nof bene\ufb01ts and burdens (high con\ufb01dence).\n\nDocument 53: LDCs and SIDS who have much \nlower per capita emissions (1.7 tCO2-eq, 4.6 tCO2-eq, respectively) than \nthe global average (6.9 tCO2-eq) excluding CO2-LULUCF, also have high \nvulnerability to climatic hazards, with global hotspots of high human \nvulnerability observed in West-, Central- and East Africa, South Asia, \nCentral and South America, SIDS and the Arctic (high con\ufb01dence). \nRegions and people with considerable development constraints have \nhigh vulnerability to climatic hazards (high con\ufb01dence). Vulnerability is \nhigher in locations with poverty, governance challenges and limited \naccess to basic services and resources, violent con\ufb02ict and high levels \nof climate-sensitive livelihoods (e.g., smallholder farmers, pastoralists, \n\ufb01shing communities) (high con\ufb01dence). Vulnerability at different spatial \nlevels is exacerbated by inequity and marginalisation linked to gender, \nethnicity, low income or combinations thereof (high con\ufb01dence), especially \nfor many Indigenous Peoples and local communities (high con\ufb01dence). \nApproximately 3.3 to 3.6 billion people live in contexts that are highly \nvulnerable to climate change (high con\ufb01dence). Between 2010 and \n2020, human mortality from \ufb02oods, droughts and storms was 15 times \nhigher in highly vulnerable regions, compared to regions with very low \nvulnerability (high con\ufb01dence). In the Arctic and in some high mountain \nregions, negative impacts of cryosphere change have been especially felt \namong Indigenous Peoples (high con\ufb01dence). Human and ecosystem \nvulnerability are interdependent (high con\ufb01dence). Vulnerability of \necosystems and people to climate change differs substantially among and \nwithin regions (very high con\ufb01dence), driven by patterns of intersecting \nsocio-economic development, unsustainable ocean and land use, \ninequity, marginalisation, historical and ongoing patterns of inequity \nsuch as colonialism, and governance81 (high con\ufb01dence).\n\nDocument 199: Coastal cities and \nsettlements play an important role in advancing climate resilient \ndevelopment due to the high number of people living in the Low \nElevation Coastal Zone, the escalating and climate compounded risk \nthat they face, and their vital role in national economies and beyond \n(high con\ufb01dence). {WGII SPM.D.3, WGII SPM D.3.3; WGIII SPM E.2, \nWGIII SPM E.2.2; SR1.5 SPM D.6}\nObserved adverse impacts and related losses and damages, \nprojected risks, trends in vulnerability, and adaptation limits \ndemonstrate that transformation for sustainability and climate \nresilient development action is more urgent than previously \nassessed (very high con\ufb01dence). Climate resilient development \nintegrates adaptation and GHG mitigation to advance \nsustainable development for all. Climate resilient development \npathways have been constrained by past development, emissions and \nclimate change and are progressively constrained by every increment \nof warming, in particular beyond 1.5\u00b0C (very high con\ufb01dence). \nClimate resilient development will not be possible in some regions \nand sub-regions if global warming exceeds 2\u00b0C (medium con\ufb01dence). \nSafeguarding biodiversity and ecosystems is fundamental to climate \nresilient development, but biodiversity and ecosystem services have \nlimited capacity to adapt to increasing global warming levels, making \nclimate resilient development progressively harder to achieve beyond \n1.5\u00b0C warming (very high con\ufb01dence). {WGII SPM D.1, WGII SPM D.1.1, \nWGII SPM D.4, WGII SPM D.4.3, WGII SPM D.5.1; WGIII SPM D.1.1} \nThe cumulative scienti\ufb01c evidence is unequivocal: climate change \nis a threat to human well-being and planetary health (very \nhigh con\ufb01dence). Any further delay in concerted anticipatory \nglobal action on adaptation and mitigation will miss a brief and \nrapidly closing window of opportunity to secure a liveable and \nsustainable future for all (very high con\ufb01dence). Opportunities for \nnear-term action are assessed in the following section.","conversation_history":[{"role":"user","content":"The factors mentioned in the IPCC report relate to the exacerbation of vulnerability in some regions and communities."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":239,"topic":"Others"}}
{"id":"119fc593-d2c9-4bef-bd6a-c77ef149c69a","question":"What does this document say about them?","reference_answer":"Combining mitigation and adaptation with sustainable development objectives would yield multiple benefits for human well-being as well as ecosystem and planetary health.","reference_context":"Document 303: {WGII SPM C.2, WGII SPM C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, \nWGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.1.5, \nWGIII SPM E.1.2}\nMitigation and adaptation when implemented together, and \ncombined with broader sustainable development objectives, \nwould yield multiple bene\ufb01ts for human well-being as well as \necosystem and planetary health (high con\ufb01dence). The range of \nsuch positive interactions is signi\ufb01cant in the landscape of near-term \nclimate policies across regions, sectors and systems. For example, \nAFOLU mitigation actions in land-use change and forestry, when \nsustainably implemented, can provide large-scale GHG emission \nreductions and removals that simultaneously bene\ufb01t biodiversity, food \nsecurity, wood supply and other ecosystem services but cannot fully \ncompensate for delayed mitigation action in other sectors. Adaptation \nmeasures in land, ocean and ecosystems similarly can have widespread \nbene\ufb01ts for food security, nutrition, health and well-being, ecosystems \nand biodiversity. Equally, urban systems are critical, interconnected \nsites for climate resilient development; urban policies that implement \nmultiple interventions can yield adaptation or mitigation gains with \nequity and human well-being. Integrated policy packages can improve \nthe ability to integrate considerations of equity, gender equality \nand justice. Coordinated cross-sectoral policies and planning can \nmaximise synergies and avoid or reduce trade-offs between mitigation \n4.9 Integration of Near-Term Actions Across Sectors and Systems \nThe feasibility, effectiveness and bene\ufb01ts of mitigation and adaptation actions are increased when multi-sectoral \nsolutions are undertaken that cut across systems. When such options are combined with broader sustainable \ndevelopment objectives, they can yield greater bene\ufb01ts for human well-being, social equity and justice, and \necosystem and planetary health. (high con\ufb01dence)\n\nDocument 195: {WGII SPM B.4, WGII \nSPM B.6; WGIII SPM C.12, WGIII SPM C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; \nSR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6}\nConsidering other sustainable development dimensions, such as the \npotentially strong economic bene\ufb01ts on human health from air quality \nimprovement, may enhance the estimated bene\ufb01ts of mitigation \n(medium con\ufb01dence). The economic effects of strengthened mitigation \naction vary across regions and countries, depending notably on economic \nstructure, regional emissions reductions, policy design and level of \ninternational cooperation (high con\ufb01dence). Ambitious mitigation \npathways imply large and sometimes disruptive changes in economic \nstructure, with implications for near-term actions (Section 4.2), equity \n(Section 4.4), sustainability (Section 4.6), and \ufb01nance (Section 4.8) \n(high con\ufb01dence). {WGIII SPM C.12.2, WGIII SPM D.3.2, WGIII TS.4.2}\n3.4 Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development\nMitigation and adaptation can lead to synergies and trade-offs with sustainable development (high con\ufb01dence). \nAccelerated and equitable mitigation and adaptation bring bene\ufb01ts from avoiding damages from climate \nchange and are critical to achieving sustainable development (high con\ufb01dence). Climate resilient development138 \npathways are progressively constrained by every increment of further warming (very high con\ufb01dence). There is a \nrapidly closing window of opportunity to secure a liveable and sustainable future for all (very high con\ufb01dence).\n138 See Annex I: Glossary.\n139 The impacts, risks, and co-bene\ufb01ts of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-speci\ufb01c context, \nimplementation and scale (high con\ufb01dence).\n\nDocument 198: {WGII SPM C.5.4, \nWGII SPM D.1, WGII SPM D.1.1, WGII SPM D.1.2, WGII SPM D.2, \nWGII SPM D.3, WGII SPM D.5, WGII SPM D.5.1, WGII SPM D.5.2; \nWGIII SPM D.1, WGIII SPM D.2, WGIII SPM D.2.4, WGIII SPM E.2.2, \nWGIII SPM E.2.3, WGIII SPM E.5.3, WGIII Cross-Chapter Box 5} \nPolicies that shift development pathways towards sustainability \ncan broaden the portfolio of available mitigation and adaptation \nresponses (medium con\ufb01dence). Combining mitigation with action \nto shift development pathways, such as broader sectoral policies, \napproaches that induce lifestyle or behaviour changes, \ufb01nancial \nregulation, or macroeconomic policies can overcome barriers and \nopen up a broader range of mitigation options (high con\ufb01dence). \nIntegrated, inclusive planning and investment in everyday decision-\nmaking about urban infrastructure can signi\ufb01cantly increase the \nadaptive capacity of urban and rural settlements. Coastal cities and \nsettlements play an important role in advancing climate resilient \ndevelopment due to the high number of people living in the Low \nElevation Coastal Zone, the escalating and climate compounded risk \nthat they face, and their vital role in national economies and beyond \n(high con\ufb01dence). {WGII SPM.D.3, WGII SPM D.3.3; WGIII SPM E.2, \nWGIII SPM E.2.2; SR1.5 SPM D.6}\nObserved adverse impacts and related losses and damages, \nprojected risks, trends in vulnerability, and adaptation limits \ndemonstrate that transformation for sustainability and climate \nresilient development action is more urgent than previously \nassessed (very high con\ufb01dence). Climate resilient development \nintegrates adaptation and GHG mitigation to advance \nsustainable development for all.\n\nDocument 302: Such measures can also achieve \ngreater bene\ufb01ts through cascading effects across sectors \n(medium con\ufb01dence). For example, the feasibility of using land for \nboth agriculture and centralised solar production can increase when \nsuch options are combined (high con\ufb01dence). Similarly, integrated \ntransport and energy infrastructure planning and operations can \ntogether reduce the environmental, social, and economic impacts of \ndecarbonising the transport and energy sectors (high con\ufb01dence). The \nimplementation of packages of multiple city-scale mitigation strategies \ncan have cascading effects across sectors and reduce GHG emissions \nboth within and outside a city\u2019s administrative boundaries (very high \ncon\ufb01dence). Integrated design approaches to the construction and \nretro\ufb01t of buildings provide increasing examples of zero energy or \nzero carbon buildings in several regions. To minimise maladaptation, \nmulti-sectoral, multi-actor and inclusive planning with \ufb02exible \npathways encourages low-regret and timely actions that keep options \nopen, ensure bene\ufb01ts in multiple sectors and systems and suggest the \navailable solution space for adapting to long-term climate change \n(very high con\ufb01dence). Trade-offs in terms of employment, water \nuse, land-use competition and biodiversity, as well as access to, \nand the affordability of, energy, food, and water can be avoided \nby well-implemented land-based mitigation options, especially those \nthat do not threaten existing sustainable land uses and land rights, with \nframeworks for integrated policy implementation (high con\ufb01dence). \n{WGII SPM C.2, WGII SPM C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, \nWGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.1.5, \nWGIII SPM E.1.2}\nMitigation and adaptation when implemented together, and \ncombined with broader sustainable development objectives, \nwould yield multiple bene\ufb01ts for human well-being as well as \necosystem and planetary health (high con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm looking into the benefits of combining mitigation and adaptation strategies with sustainable development objectives as outlined in the IPCC report."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":303,"topic":"Climate Change Action"}}
{"id":"4dfdbf6b-7f0d-4299-bfd1-d4a55ab51c7f","question":"What determines these?","reference_answer":"The magnitude and rate of climate change and associated risks depend strongly on near-term mitigation and adaptation actions.","reference_context":"Document 202: 91\nSection 4\nNear-Term Responses \nin a Changing Climate\n\nDocument 304: 115\nNear-Term Responses in a Changing Climate\nSection 4\nand adaptation. Effective action in all of the above areas will \nrequire near-term political commitment and follow-through, social \ncooperation, \ufb01nance, and more integrated cross-sectoral policies and \nsupport and actions. (high con\ufb01dence).  {WGII SPM C.1, WG II SPM C.2, \nWGII SPM C.2, WGII SPM C.5, WGII SPM D.2, WGII SPM D.3.2, \nWGII SPM D.3.3, WGII Figure SPM.4; WGIII SPM C.6.3, WGIII SPM C.8.2, \nWGIII SPM C.9, WGIII SPM C.9.1, WGIII SPM C.9.2, WGIII SPM D.2, \nWGIII SPM D.2.4, WGIII SPM D.3.2, WGIII SPM E.1, WGIII SPM E.2.4, \nWGIII Figure SPM.8, WGIII TS.7, WGIII TS Figure TS.29: SRCCL ES 7.4.8, \nSRCCL SPM B.6} (3.4, 4.4)\n\nDocument 203: 92\nSection 4\nSection 1\nSection 4\nSection 4 : Near-Term Responses in a Changing Climate\n4.1 The Timing and Urgency of Climate Action\nThe magnitude and rate of climate change and associated risks \ndepend strongly on near-term mitigation and adaptation actions \n(very high con\ufb01dence). Global warming is more likely than not to reach \n1.5\u00b0C between 2021 and 2040 even under the very low GHG emission \nscenarios (SSP1-1.9), and likely or very likely to exceed 1.5\u00b0C under \nhigher emissions scenarios141. Many adaptation options have medium \nor high feasibility up to 1.5\u00b0C (medium to high con\ufb01dence, depending \non option), but hard limits to adaptation have already been reached \nin some ecosystems and the effectiveness of adaptation to reduce \nclimate risk will decrease with increasing warming (high con\ufb01dence). \nSocietal choices and actions implemented in this decade determine the \nextent to which medium- and long-term pathways will deliver higher or \nlower climate resilient development (high con\ufb01dence). Climate resilient \ndevelopment prospects are increasingly limited if current greenhouse \ngas emissions do not rapidly decline, especially if 1.5\u00b0C global warming \nis exceeded in the near term (high con\ufb01dence). Without urgent, effective \nand equitable adaptation and mitigation actions, climate change \nincreasingly threatens the health and livelihoods of people around \nthe globe, ecosystem health, and biodiversity, with severe adverse \nconsequences for current and future generations (high con\ufb01dence). \n{WGI SPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII \nSPM B.4, WGII SPM C.2, WGII SPM C.3.3, WGII Figure SPM.4, WGII SPM \nD.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}.","conversation_history":[{"role":"user","content":"The magnitude and rate of climate change and associated risks are discussed in Section 4.1 of the IPCC report."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":202,"topic":"Others"}}
{"id":"4844e43b-6128-45fd-8679-138c38e21679","question":"What are they?","reference_answer":"At about 2\u00b0C warming, climate-related changes in food availability and diet quality are estimated to increase nutrition-related diseases and the number of undernourished people, affecting tens to hundreds of millions of people, particularly among low-income households in low- and middle-income countries in sub-Saharan Africa, South Asia, and Central America (high confidence).","reference_context":"Document 125: {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a). With about 2\u00b0C warming, climate-related \n120 Undetectable risk level indicates no associated impacts are detectable and attributable to climate change; moderate risk indicates associated impacts are both detectable and \nattributable to climate change with at least medium con\ufb01dence, also accounting for the other speci\ufb01c criteria for key risks; high risk indicates severe and widespread impacts that \nare judged to be high on one or more criteria for assessing key risks; and very high risk level indicates very high risk of severe impacts and the presence of signi\ufb01cant irreversibility \nor the persistence of climate-related hazards, combined with limited ability to adapt due to the nature of the hazard or impacts\/risks. {WGII Figure SPM.3}\n121 The Reasons for Concern (RFC) framework communicates scienti\ufb01c understanding about accrual of risk for \ufb01ve broad categories (WGII Figure SPM.3). RFC1: Unique and \nthreatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive \nproperties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots.\n\nDocument 126: {WGII Figure SPM.3}\n121 The Reasons for Concern (RFC) framework communicates scienti\ufb01c understanding about accrual of risk for \ufb01ve broad categories (WGII Figure SPM.3). RFC1: Unique and \nthreatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive \nproperties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme weather events: risks\/impacts to \nhuman health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wild\ufb01res, and coastal \ufb02ooding. RFC3: \nDistribution of impacts: risks\/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability. \nRFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives affected, species lost \nor ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused by global warming, \nsuch as ice sheet instability or thermohaline circulation slowing. Assessment methods include a structured expert elicitation based on the literature described in WGII SM16.6 \nand are identical to AR5 but are enhanced by a structured approach to improve robustness and facilitate comparison between AR5 and AR6. For further explanations of global \nrisk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}\nchanges in food availability and diet quality are estimated to increase \nnutrition-related diseases and the number of undernourished people, \naffecting tens (under low vulnerability and low warming) to hundreds of \nmillions of people (under high vulnerability and high warming), particularly \namong low-income households in low- and middle-income countries in \nsub-Saharan Africa, South Asia and Central America (high con\ufb01dence). \nFor example, snowmelt water availability for irrigation is projected \nto decline in some snowmelt dependent river basins by up to 20% \n(medium con\ufb01dence).\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 105: 64\nSection 2\nSection 1\nSection 2\nGlobal Warming Levels (GWLs)\nFor many climate and risk variables, the geographical patterns of changes in climatic impact-drivers110 and climate impacts for a level of global \nwarming111 are common to all scenarios considered and independent of timing when that level is reached. This motivates the use of GWLs as a \ndimension of integration. {WGI Box SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2)\nRisks\nDynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result \nin risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the \nReasons for Concern (RFCs) \u2013 \ufb01ve globally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature. \nRisks can also arise from climate change mitigation or adaptation responses when the response does not achieve its intended objective, or when \nit results in adverse effects for other societal objectives. {WGII SPM A, WGII Figure SPM.3, WGII Box TS.1, WGII Figure TS.4; SR1.5 Figure SPM.2; \nSROCC Errata Figure SPM.3; SRCCL Figure SPM.2} (3.1.2, Cross-Section Box.2 Figure 1, Figure 3.3)\n110 See Annex I: Glossary\n111 See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850\u20131900. The assessed time of when a certain global warming level \nis reached under a particular scenario is de\ufb01ned here as the mid-point of the \ufb01rst 20-year running average period during which the assessed average global surface temperature \nchange exceeds the level of global warming. {WGI SPM footnote 26, Cross-Section Box TS.1}","conversation_history":[{"role":"user","content":"I'm interested in the projected climate-related risks to food availability and diet quality at about 2\u00b0C warming, including which regions are most affected."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":125,"topic":"Climate Change Risks"}}
{"id":"21e24a14-7fcf-4004-8733-f380b24801d6","question":"What is it?","reference_answer":"The projected increase in extinction risk for endemic species in biodiversity hotspots is at least tenfold if warming rises from 1.5\u00b0C to 3\u00b0C.","reference_context":"Document 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).\n\nDocument 128: For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence). {WGII SPM B.4.1, WGII SPM B.4.2, \nWGII Figure SPM.3, WGII TS Appendix AII, WGII Appendix I Global to \nRegional Atlas Figure AI.46} (Figure 3.2, Figure 3.3)\nGlobal warming of 4\u00b0C and above is projected to lead to far-reaching \nimpacts on natural and human systems (high con\ufb01dence). Beyond \n4\u00b0C of warming, projected impacts on natural systems include local \nextinction of ~50% of tropical marine species (medium con\ufb01dence) \nand biome shifts across 35% of global land area (medium con\ufb01dence). \nAt this level of warming, approximately 10% of the global land area \nis projected to face both increasing high and decreasing low extreme \nstream\ufb02ow, affecting, without additional adaptation, over 2.1 billion people \n(medium con\ufb01dence) and about 4 billion people are projected to \nexperience water scarcity (medium con\ufb01dence). At 4\u00b0C of warming, the \nglobal burned area is projected to increase by 50 to 70% and the \nfire frequency by ~30% compared to today (medium confidence). \n{WGII SPM B.4.1, WGII SPM B.4.2, WGII TS.C.1.2, WGII TS.C.2.3, \nWGII TS.C.4.1, WGII TS.C.4.4} (Figure 3.2, Figure 3.3)\n\nDocument 127: For further explanations of global \nrisk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}\nchanges in food availability and diet quality are estimated to increase \nnutrition-related diseases and the number of undernourished people, \naffecting tens (under low vulnerability and low warming) to hundreds of \nmillions of people (under high vulnerability and high warming), particularly \namong low-income households in low- and middle-income countries in \nsub-Saharan Africa, South Asia and Central America (high con\ufb01dence). \nFor example, snowmelt water availability for irrigation is projected \nto decline in some snowmelt dependent river basins by up to 20% \n(medium con\ufb01dence). Climate change risks to cities, settlements \nand key infrastructure will rise sharply in the mid and long term with \nfurther global warming, especially in places already exposed to high \ntemperatures, along coastlines, or with high vulnerabilities (high \ncon\ufb01dence). {WGII SPM B.3.3, WGII SPM B.4.2, WGII SPM B.4.5, WGII TS C.3.3, \nWGII TS.C.12.2} (Figure 3.3)\nAt global warming of 3\u00b0C, additional risks in many sectors and regions \nreach high or very high levels, implying widespread systemic impacts, \nirreversible change and many additional adaptation limits (see Section 3.2) \n(high con\ufb01dence). For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm interested in the projected increase in extinction risk for endemic species in biodiversity hotspots with a rise in global warming from 1.5\u00b0C to 3\u00b0C."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":124,"topic":"Climate Change Risks"}}
{"id":"996e9d97-2382-4c38-a432-ac766fc937f5","question":"What is it?","reference_answer":"The projected increase in extinction risk for endemic species in biodiversity hotspots is at least tenfold if global warming rises from 1.5\u00b0C to 3\u00b0C.","reference_context":"Document 128: For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence). {WGII SPM B.4.1, WGII SPM B.4.2, \nWGII Figure SPM.3, WGII TS Appendix AII, WGII Appendix I Global to \nRegional Atlas Figure AI.46} (Figure 3.2, Figure 3.3)\nGlobal warming of 4\u00b0C and above is projected to lead to far-reaching \nimpacts on natural and human systems (high con\ufb01dence). Beyond \n4\u00b0C of warming, projected impacts on natural systems include local \nextinction of ~50% of tropical marine species (medium con\ufb01dence) \nand biome shifts across 35% of global land area (medium con\ufb01dence). \nAt this level of warming, approximately 10% of the global land area \nis projected to face both increasing high and decreasing low extreme \nstream\ufb02ow, affecting, without additional adaptation, over 2.1 billion people \n(medium con\ufb01dence) and about 4 billion people are projected to \nexperience water scarcity (medium con\ufb01dence). At 4\u00b0C of warming, the \nglobal burned area is projected to increase by 50 to 70% and the \nfire frequency by ~30% compared to today (medium confidence). \n{WGII SPM B.4.1, WGII SPM B.4.2, WGII TS.C.1.2, WGII TS.C.2.3, \nWGII TS.C.4.1, WGII TS.C.4.4} (Figure 3.2, Figure 3.3)\n\nDocument 124: Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence). At this GWL, many low-elevation \nand small glaciers around the world would lose most of their mass or \ndisappear within decades to centuries (high con\ufb01dence). Regions at \ndisproportionately higher risk include Arctic ecosystems, dryland regions, \nsmall island developing states and Least Developed Countries (high \ncon\ufb01dence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5 SPM A.3, \nSR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)\nAt 2\u00b0C of global warming, overall risk levels associated with the unequal \ndistribution of impacts (RFC3), global aggregate impacts (RFC4) and \nlarge-scale singular events (RFC5) would be transitioning to high (medium \ncon\ufb01dence), those associated with extreme weather events (RFC2) would \nbe transitioning to very high (medium con\ufb01dence), and those associated \nwith unique and threatened systems (RFC1) would be very high (high \ncon\ufb01dence) (Figure 3.3, panel a).\n\nDocument 127: For further explanations of global \nrisk levels and Reasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}\nchanges in food availability and diet quality are estimated to increase \nnutrition-related diseases and the number of undernourished people, \naffecting tens (under low vulnerability and low warming) to hundreds of \nmillions of people (under high vulnerability and high warming), particularly \namong low-income households in low- and middle-income countries in \nsub-Saharan Africa, South Asia and Central America (high con\ufb01dence). \nFor example, snowmelt water availability for irrigation is projected \nto decline in some snowmelt dependent river basins by up to 20% \n(medium con\ufb01dence). Climate change risks to cities, settlements \nand key infrastructure will rise sharply in the mid and long term with \nfurther global warming, especially in places already exposed to high \ntemperatures, along coastlines, or with high vulnerabilities (high \ncon\ufb01dence). {WGII SPM B.3.3, WGII SPM B.4.2, WGII SPM B.4.5, WGII TS C.3.3, \nWGII TS.C.12.2} (Figure 3.3)\nAt global warming of 3\u00b0C, additional risks in many sectors and regions \nreach high or very high levels, implying widespread systemic impacts, \nirreversible change and many additional adaptation limits (see Section 3.2) \n(high con\ufb01dence). For example, very high extinction risk for endemic \nspecies in biodiversity hotspots is projected to increase at least tenfold \nif warming rises from 1.5\u00b0C to 3\u00b0C (medium con\ufb01dence). Projected \nincreases in direct \ufb02ood damages are higher by 1.4 to 2 times at 2\u00b0C \nand 2.5 to 3.9 times at 3\u00b0C, compared to 1.5\u00b0C global warming without \nadaptation (medium con\ufb01dence).\n\nDocument 123: 71\nLong-Term Climate and Development Futures\nSection 3\n3.1.2 Impacts and Related Risks\nFor a given level of warming, many climate-related risks are \nassessed to be higher than in AR5 (high con\ufb01dence). Levels of \nrisk120 for all Reasons for Concern121 (RFCs) are assessed to become high \nto very high at lower global warming levels compared to what was \nassessed in AR5 (high con\ufb01dence). This is based upon recent evidence \nof observed impacts, improved process understanding, and new \nknowledge on exposure and vulnerability of human and natural \nsystems, including limits to adaptation. Depending on the level \nof global warming, the assessed long-term impacts will be up to \nmultiple times higher than currently observed (high confidence) for \n127 identi\ufb01ed key risks, e.g., in terms of the number of affected people \nand species. Risks, including cascading risks (see 3.1.3) and risks from \novershoot (see 3.3.4), are projected to become increasingly severe \nwith every increment of global warming (very high confidence). \n{WGII SPM B.3.3, WGII SPM B.4, WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} \n(Figure 3.2, Figure 3.3)\nClimate-related risks for natural and human systems are higher for \nglobal warming of 1.5\u00b0C than at present (1.1\u00b0C) but lower than at 2\u00b0C \n(high con\ufb01dence) (see Section 2.1.2). Climate-related risks to health, \nlivelihoods, food security, water supply, human security, and economic \ngrowth are projected to increase with global warming of 1.5\u00b0C. In \nterrestrial ecosystems, 3 to 14% of the tens of thousands of species \nassessed will likely face a very high risk of extinction at a GWL of 1.5\u00b0C. \nCoral reefs are projected to decline by a further 70\u201390% at 1.5\u00b0C of \nglobal warming (high con\ufb01dence).","conversation_history":[{"role":"user","content":"I'm interested in the projected increase in extinction risk for endemic species in biodiversity hotspots due to a rise in global warming from 1.5\u00b0C to 3\u00b0C."},{"role":"assistant","content":"How can I help you with that?"}],"metadata":{"question_type":"conversational","seed_document_id":128,"topic":"Climate Change Risks"}}