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35 Climate Change 2023 Synthesis Report IPCC, 2023: Sections. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 35-115, doi: 10.59327/IPCC/AR6-9789291691647 These Sections should be cited as:

37 Section 1 Introduction
38 Section 1 Section 1 This Synthesis Report (SYR) of the IPCC Sixth Assessment Report (AR6) summarises the state of knowledge of climate change, its widespread impacts and risks, and climate change mitigation and adaptation, based on the peer-reviewed scientiﬁc, technical and socio-economic literature since the publication of the IPCC’s Fifth Assessment Report (AR5) in 2014. The assessment is undertaken within the context of the evolving international landscape, in particular, developments in the UN Framework Convention on Climate Change (UNFCCC) process, including the outcomes of the Kyoto Protocol and the adoption of the Paris Agreement. It reﬂects the increasing diversity of those involved in climate action. This report integrates the main ﬁndings of the AR6 Working Group reports58 and the three AR6 Special Reports59. It recognizes the interdependence of climate, ecosystems and biodiversity, and human societies; the value of diverse forms of knowledge; and the close linkages between climate change adaptation, mitigation, ecosystem health, human well-being and sustainable development. Building on multiple analytical frameworks, including those from the physical and social sciences, this report identiﬁes opportunities for transformative action which are effective, feasible, just and equitable using concepts of systems transitions and resilient development pathways60. Different regional classiﬁcation schemes61 are used for physical, social and economic aspects, reﬂecting the underlying literature. After this introduction, Section 2, ‘Current Status and Trends’, opens with the assessment of observational evidence for our changing climate, historical and current drivers of human-induced climate change, and its impacts. It assesses the current implementation of adaptation and mitigation response options. Section 3, ‘Long-Term Climate and Development Futures’, provides a long-term assessment of climate change to 2100 and beyond in a broad range of socio-economic 58 The three Working Group contributions to AR6 are: Climate Change 2021: The Physical Science Basis; Climate Change 2022: Impacts, Adaptation and Vulnerability; and Climate Change 2022: Mitigation of Climate Change, respectively.
Different regional classiﬁcation schemes61 are used for physical, social and economic aspects, reﬂecting the underlying literature. After this introduction, Section 2, ‘Current Status and Trends’, opens with the assessment of observational evidence for our changing climate, historical and current drivers of human-induced climate change, and its impacts. It assesses the current implementation of adaptation and mitigation response options. Section 3, ‘Long-Term Climate and Development Futures’, provides a long-term assessment of climate change to 2100 and beyond in a broad range of socio-economic 58 The three Working Group contributions to AR6 are: Climate Change 2021: The Physical Science Basis; Climate Change 2022: Impacts, Adaptation and Vulnerability; and Climate Change 2022: Mitigation of Climate Change, respectively. Their assessments cover scientiﬁc literature accepted for publication respectively by 31 January 2021, 1 September 2021 and 11 October 2021. 59 The three Special Reports are : Global Warming of 1.5°C (2018): an IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty (SR1.5); Climate Change and Land (2019): an IPCC Special Report on climate change, desertiﬁcation, land degradation, sustainable land management, food security, and greenhouse gas ﬂuxes in terrestrial ecosystems (SRCCL); and The Ocean and Cryosphere in a Changing Climate (2019) (SROCC). The Special Reports cover scientiﬁc literature accepted for publication respectively by 15 May 2018, 7 April 2019 and 15 May 2019. 60 The Glossary (Annex I) includes deﬁnitions of these, and other terms and concepts used in this report drawn from the AR6 joint Working Group Glossary.
The Special Reports cover scientiﬁc literature accepted for publication respectively by 15 May 2018, 7 April 2019 and 15 May 2019. 60 The Glossary (Annex I) includes deﬁnitions of these, and other terms and concepts used in this report drawn from the AR6 joint Working Group Glossary. 61 Depending on the climate information context, geographical regions in AR6 may refer to larger areas, such as sub-continents and oceanic regions, or to typological regions, such as monsoon regions, coastlines, mountain ranges or cities. A new set of standard AR6 WGI reference land and ocean regions have been deﬁned. WGIII allocates countries to geographical regions, based on the UN Statistics Division Classiﬁcation {WGI 1.4.5, WGI 10.1, WGI 11.9, WGI 12.1–12.4, WGI Atlas.1.3.3–1.3.4}. 62 Each ﬁnding is grounded in an evaluation of underlying evidence and agreement. A level of conﬁdence is expressed using ﬁve qualiﬁers: very low, low, medium, high and very high, and typeset in italics, for example, medium conﬁdence. The following terms have been used to indicate the assessed likelihood of an outcome or result: virtually certain 99–100% probability; very likely 90–100%; likely 66–100%; more likely than not >50-100%; about as likely as not 33–66%; unlikely 0–33%; very unlikely 0–10%; and exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100% and extremely unlikely 0–5%) are also used when appropriate. Assessed likelihood also is typeset in italics: for example, very likely. This is consistent with AR5. In this Report, unless stated otherwise, square brackets [x to y] are used to provide the assessed very likely range, or 90% interval. futures.
The following terms have been used to indicate the assessed likelihood of an outcome or result: virtually certain 99–100% probability; very likely 90–100%; likely 66–100%; more likely than not >50-100%; about as likely as not 33–66%; unlikely 0–33%; very unlikely 0–10%; and exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100% and extremely unlikely 0–5%) are also used when appropriate. Assessed likelihood also is typeset in italics: for example, very likely. This is consistent with AR5. In this Report, unless stated otherwise, square brackets [x to y] are used to provide the assessed very likely range, or 90% interval. futures. It considers long-term characteristics, impacts, risks and costs in adaptation and mitigation pathways in the context of sustainable development. Section 4, ‘Near- Term Responses in a Changing Climate’, assesses opportunities for scaling up effective action in the period up to 2040, in the context of climate pledges, and commitments, and the pursuit of sustainable development. Based on scientiﬁc understanding, key ﬁndings can be formulated as statements of fact or associated with an assessed level of conﬁdence using the IPCC calibrated language62. The scientiﬁc ﬁndings are drawn from the underlying reports and arise from their Summary for Policymakers (hereafter SPM), Technical Summary (hereafter TS), and underlying chapters and are indicated by {} brackets. Figure 1.1 shows the Synthesis Report Figures Key, a guide to visual icons that are used across multiple ﬁgures within this report. 1. Introduction
39 Introduction Section 1 Figure 1.1: The Synthesis Report ﬁgures key. Italicized ‘annotations’ Simple explanations written in non-technical language Axis labels Synthesis Report ﬁgures key these help non-experts navigate complex content GHG emissions Temperature Cost or budget Net zero °C net zero
40
41 Section 2 Current Status and Trends
42 Section 2 Section 1 Section 2 2.1 Observed Changes, Impacts and Attribution Human activities, principally through emissions of greenhouse gases, have unequivocally caused global warming, with global surface temperature reaching 1.1°C above 1850–1900 in 2011–2020. Global greenhouse gas emissions have continued to increase over 2010–2019, with unequal historical and ongoing contributions arising from unsustainable energy use, land use and land-use change, lifestyles and patterns of consumption and production across regions, between and within countries, and between individuals (high conﬁdence). Human-caused climate change is already affecting many weather and climate extremes in every region across the globe. This has led to widespread adverse impacts on food and water security, human health and on economies and society and related losses and damages63 to nature and people (high conﬁdence). Vulnerable communities who have historically contributed the least to current climate change are disproportionately affected (high conﬁdence). 63 In this report, the term ‘losses and damages’ refers to adverse observed impacts and/or projected risks and can be economic and/or non-economic. (See Annex I: Glossary) Section 2: Current Status and Trends 2.1.1. Observed Warming and its Causes Global surface temperature was around 1.1°C above 1850–1900 in 2011–2020 (1.09 [0.95 to 1.20]°C)64, with larger increases over land (1.59 [1.34 to 1.83]°C) than over the ocean (0.88 [0.68 to 1.01]°C)65. Observed warming is human-caused, with warming from greenhouse gases (GHG), dominated by CO2 and methane (CH4), partly masked by aerosol cooling (Figure 2.1). Global surface temperature in the ﬁrst two decades of the 21st century (2001–2020) was 0.99 [0.84 to 1.10]°C higher than 1850–1900.
Observed Warming and its Causes Global surface temperature was around 1.1°C above 1850–1900 in 2011–2020 (1.09 [0.95 to 1.20]°C)64, with larger increases over land (1.59 [1.34 to 1.83]°C) than over the ocean (0.88 [0.68 to 1.01]°C)65. Observed warming is human-caused, with warming from greenhouse gases (GHG), dominated by CO2 and methane (CH4), partly masked by aerosol cooling (Figure 2.1). Global surface temperature in the ﬁrst two decades of the 21st century (2001–2020) was 0.99 [0.84 to 1.10]°C higher than 1850–1900. Global surface temperature has increased faster since 1970 than in any other 50-year period over at least the last 2000 years (high conﬁdence). The likely range of total human-caused global surface temperature increase from 1850–1900 to 2010–201966 is 0.8°C to 1.3°C, with a best estimate of 1.07°C. It is likely that well-mixed GHGs67 contributed a warming of 1.0°C to 2.0°C, and other human drivers (principally aerosols) contributed a cooling of 0.0°C to 0.8°C, natural (solar and volcanic) drivers changed global surface temperature by ±0.1°C and internal variability changed it by ±0.2°C. {WGI SPM A.1, WGI SPM A.1.2, WGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2} Observed increases in well-mixed GHG concentrations since around 1750 are unequivocally caused by GHG emissions from human activities.
It is likely that well-mixed GHGs67 contributed a warming of 1.0°C to 2.0°C, and other human drivers (principally aerosols) contributed a cooling of 0.0°C to 0.8°C, natural (solar and volcanic) drivers changed global surface temperature by ±0.1°C and internal variability changed it by ±0.2°C. {WGI SPM A.1, WGI SPM A.1.2, WGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2} Observed increases in well-mixed GHG concentrations since around 1750 are unequivocally caused by GHG emissions from human activities. Land and ocean sinks have taken up a near-constant proportion (globally about 56% per year) of CO2 emissions from human activities over 63 In this report, the term ‘losses and damages’ refers to adverse observed impacts and/or projected risks and can be economic and/or non-economic. (See Annex I: Glossary) 64 The estimated increase in global surface temperature since AR5 is principally due to further warming since 2003–2012 (+0.19 [0.16 to 0.22]°C). Additionally, methodological advances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements have also increased the estimate of global surface temperature change by approximately 0.1°C, but this increase does not represent additional physical warming since AR5 {WGI SPM A1.2 and footnote 10} 65 For 1850–1900 to 2013–2022 the updated calculations are 1.15 [1.00 to 1.25]°C for global surface temperature, 1.65 [1.36 to 1.90]°C for land temperatures and 0.93 [0.73 to 1.04]°C for ocean temperatures above 1850–1900 using the exact same datasets (updated by 2 years) and methods as employed in WGI.
Additionally, methodological advances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements have also increased the estimate of global surface temperature change by approximately 0.1°C, but this increase does not represent additional physical warming since AR5 {WGI SPM A1.2 and footnote 10} 65 For 1850–1900 to 2013–2022 the updated calculations are 1.15 [1.00 to 1.25]°C for global surface temperature, 1.65 [1.36 to 1.90]°C for land temperatures and 0.93 [0.73 to 1.04]°C for ocean temperatures above 1850–1900 using the exact same datasets (updated by 2 years) and methods as employed in WGI. 66 The period distinction with the observed assessment arises because the attribution studies consider this slightly earlier period. The observed warming to 2010–2019 is 1.06 [0.88 to 1.21]°C. {WGI SPM footnote 11} 67 Contributions from emissions to the 2010–2019 warming relative to 1850–1900 assessed from radiative forcing studies are: CO2 0.8 [0.5 to 1.2]°C; methane 0.5 [0.3 to 0.8]°C; nitrous oxide 0.1 [0.0 to 0.2]°C and ﬂuorinated gases 0.1 [0.0 to 0.2]°C. 68 For 2021 (the most recent year for which ﬁnal numbers are available) concentrations using the same observational products and methods as in AR6 WGI are: 415 ppm CO2; 1896 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 updated to use the WMO-CO2-X2019 scale. the past six decades, with regional differences (high conﬁdence).
68 For 2021 (the most recent year for which ﬁnal numbers are available) concentrations using the same observational products and methods as in AR6 WGI are: 415 ppm CO2; 1896 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 updated to use the WMO-CO2-X2019 scale. the past six decades, with regional differences (high conﬁdence). In 2019, atmospheric CO2 concentrations reached 410 parts per million (ppm), CH4 reached 1866 parts per billion (ppb) and nitrous oxide (N2O) reached 332 ppb68. Other major contributors to warming are tropospheric ozone (O3) and halogenated gases. Concentrations of CH4 and N2O have increased to levels unprecedented in at least 800,000 years (very high conﬁdence), and there is high conﬁdence that current CO2 concentrations are higher than at any time over at least the past two million years. Since 1750, increases in CO2 (47%) and CH4 (156%) concentrations far exceed – and increases in N2O (23%) are similar to – the natural multi-millennial changes between glacial and interglacial periods over at least the past 800,000 years (very high conﬁdence). The net cooling effect which arises from anthropogenic aerosols peaked in the late 20th century (high conﬁdence). {WGI SPM A1.1, WGI SPM A1.3, WGI SPM A.2.1, WGI Figure SPM.2, WGI TS 2.2, WGI 2ES, WGI Figure 6.1}
43 Current Status and Trends Section 2 Increased concentrations of GHGs in the atmosphere Increased emissions of greenhouse gases (GHGs) b) a) c) Changes in global surface temperature Carbon dioxide Methane d) Humans are responsible 0 15 30 45 60 400 350 300 1000 1500 500 –0.5 –1.0 0.0 0.5 1.0 1.5 2.0 Observed –0.5 –1.0 0.0 0.5 1.0 1.5 2.0 Total human inﬂuence Observed warming Well-mixed GHG Other human drivers* Solar and volcanic drivers Internal variability Observed warming is driven by emissions from human activities with GHG warming partly masked by aerosol cooling 2010–2019 (change from 1850–1900) 1.0 0.2 Global surface temperature has increased by 1.1°C by 2011-2020 compared to 1850-1900 Concentrations of GHGs have increased rapidly since 1850 (scaled to match their assessed contributions to warming over 1850–1900 to 2010–2019) Greenhouse gas (GHG) emissions resulting from human activities continue to increase Human activities are responsible for global warming 1850 1900 1950 2000 2020 1850 1900 1950 2000 2019 Non-CO2 emissions CO2 from fossil fuels and industry Parts per million (ppm) GHG Emissions (GtCO2-eq/yr) Parts per billion (ppb) °C 1850 1900 1950 2000 2019 °C CO2 from Land Use, Land-Use Change and Forestry (LULUCF) warmest multi-century period in more than 100,
Land-Use Change and Forestry (LULUCF) warmest multi-century period in more than 100,000 years 410 ppm CO2 1866 ppb CH4 332 ppb N2O 200 400 Parts per billion (ppb) Nitrous oxide °C 0 0.5 1 1.5 Key *Other human drivers are predominantly cooling aerosols, but also warming aerosols, land-use change (land-use reﬂectance) and ozone. Figure 2.1: The causal chain from emissions to resulting warming of the climate system. Emissions of GHG have increased rapidly over recent decades (panel (a)). Global net anthropogenic GHG emissions include CO2 from fossil fuel combustion and industrial processes (CO2-FFI) (dark green); net CO2 from land use, land-use change and forestry (CO2-LULUCF) (green); CH4; N2O; and ﬂuorinated gases (HFCs, PFCs, SF6, NF3) (light blue). These emissions have led to increases in the atmospheric concentrations of several GHGs including the three major well-mixed GHGs CO2, CH4 and N2O (panel (b), annual values). To indicate their relative importance each subpanel’s vertical extent for CO2, CH4 and N2O is scaled to match the assessed individual direct effect (and, in the case of CH4 indirect effect via atmospheric chemistry impacts on tropospheric ozone) of historical emissions on temperature change from 1850–1900 to 2010–2019. This estimate arises from an assessment of effective radiative forcing and climate sensitivity. The global surface temperature (shown as annual anomalies from a 1850–1900 baseline) has increased by around 1.1°C since 1850–1900 (panel (c)).
These emissions have led to increases in the atmospheric concentrations of several GHGs including the three major well-mixed GHGs CO2, CH4 and N2O (panel (b), annual values). To indicate their relative importance each subpanel’s vertical extent for CO2, CH4 and N2O is scaled to match the assessed individual direct effect (and, in the case of CH4 indirect effect via atmospheric chemistry impacts on tropospheric ozone) of historical emissions on temperature change from 1850–1900 to 2010–2019. This estimate arises from an assessment of effective radiative forcing and climate sensitivity. The global surface temperature (shown as annual anomalies from a 1850–1900 baseline) has increased by around 1.1°C since 1850–1900 (panel (c)). The vertical bar on the right shows the estimated temperature (very likely range) during the warmest multi-century period in at least the last 100,000 years, which occurred around 6500 years ago during the current interglacial period (Holocene). Prior to that, the next most recent warm period was about 125,000 years ago, when the assessed multi-century temperature range [0.5°C to 1.5°C] overlaps the observations of the most recent decade. These past warm periods were caused by slow (multi-millennial) orbital variations. Formal detection and attribution studies synthesise information from climate models and observations and show that the best estimate is that all the warming observed between 1850–1900 and 2010–2019 is caused by humans (panel (d)). The panel shows temperature change attributed to: total human inﬂuence; its decomposition into changes in GHG concentrations and other human drivers (aerosols, ozone and land-use change (land-use reﬂectance)); solar and volcanic drivers; and internal climate variability. Whiskers show likely ranges.
Prior to that, the next most recent warm period was about 125,000 years ago, when the assessed multi-century temperature range [0.5°C to 1.5°C] overlaps the observations of the most recent decade. These past warm periods were caused by slow (multi-millennial) orbital variations. Formal detection and attribution studies synthesise information from climate models and observations and show that the best estimate is that all the warming observed between 1850–1900 and 2010–2019 is caused by humans (panel (d)). The panel shows temperature change attributed to: total human inﬂuence; its decomposition into changes in GHG concentrations and other human drivers (aerosols, ozone and land-use change (land-use reﬂectance)); solar and volcanic drivers; and internal climate variability. Whiskers show likely ranges. {WGI SPM A.2.2, WGI Figure SPM.1, WGI Figure SPM.2, WGI TS2.2, WGI 2.1; WGIII Figure SPM.1, WGIII A.III.II.2.5.1}
44 Section 2 Section 1 Section 2 Average annual GHG emissions during 2010–2019 were higher than in any previous decade, but the rate of growth between 2010 and 2019 (1.3% yr-1) was lower than that between 2000 and 2009 (2.1% yr-1)69. Historical cumulative net CO2 emissions from 1850 to 2019 were 2400 ±240 GtCO2. Of these, more than half (58%) occurred between 1850 and 1989 [1400 ±195 GtCO2], and about 42% between 1990 and 2019 [1000 ±90 GtCO2]. Global net anthropogenic GHG emissions have been estimated to be 59±6.6 GtCO2-eq in 2019, about 12% (6.5 GtCO2-eq) higher than in 2010 and 54% (21 GtCO2-eq) higher than in 1990. By 2019, the largest growth in gross emissions occurred in CO2 from fossil fuels and industry (CO2-FFI) followed by CH4, whereas the highest relative growth occurred in fluorinated gases (F-gases), starting from low levels in 1990. (high confidence) {WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, WGIII Figure SPM.2} Regional contributions to global human-caused GHG emissions continue to differ widely. Historical contributions of CO2 emissions vary substantially across regions in terms of total magnitude, but also in terms of contributions to CO2-FFI (1650 ± 73 GtCO2-eq) and net CO2-LULUCF (760 ± 220 GtCO2-eq) emissions (Figure 2.2). Variations in regional and national per capita emissions partly reﬂect different development stages, but they also vary widely at similar income levels.
(high confidence) {WGIII SPM B1.1, WGIII SPM B.1.2, WGIII SPM B.1.3, WGIII Figure SPM.1, WGIII Figure SPM.2} Regional contributions to global human-caused GHG emissions continue to differ widely. Historical contributions of CO2 emissions vary substantially across regions in terms of total magnitude, but also in terms of contributions to CO2-FFI (1650 ± 73 GtCO2-eq) and net CO2-LULUCF (760 ± 220 GtCO2-eq) emissions (Figure 2.2). Variations in regional and national per capita emissions partly reﬂect different development stages, but they also vary widely at similar income levels. Average per capita net anthropogenic GHG emissions in 2019 ranged from 2.6 tCO2-eq to 19 tCO2-eq across regions (Figure 2.2). Least Developed Countries (LDCs) and Small Island Developing States (SIDS) have much lower per capita emissions (1.7 tCO2-eq and 4.6 tCO2-eq, respectively) than the global average (6.9 tCO2-eq), excluding CO2-LULUCF. Around 48% of the global population in 2019 lives in countries emitting on average more than 6 tCO2-eq per capita, 35% of the global population live in countries emitting more than 9 tCO2-eq per capita70 (excluding CO2-LULUCF) while another 41% live in countries emitting less than 3 tCO2-eq per capita. A substantial share of the population in these low-emitting countries lack access to modern energy services. (high conﬁdence) {WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3} Net GHG emissions have increased since 2010 across all major sectors (high conﬁdence).
Around 48% of the global population in 2019 lives in countries emitting on average more than 6 tCO2-eq per capita, 35% of the global population live in countries emitting more than 9 tCO2-eq per capita70 (excluding CO2-LULUCF) while another 41% live in countries emitting less than 3 tCO2-eq per capita. A substantial share of the population in these low-emitting countries lack access to modern energy services. (high conﬁdence) {WGIII SPM B.3, WGIII SPM B3.1, WGIII SPM B.3.2, WGIII SPM B.3.3} Net GHG emissions have increased since 2010 across all major sectors (high conﬁdence). In 2019, approximately 34% (20 GtCO2-eq) of net global GHG emissions came from the energy sector, 24% (14 GtCO2-eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% (8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2-eq) from buildings71 (high conﬁdence). Average annual GHG emissions growth between 69 GHG 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 the 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 contain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of metric 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 system and its response to past and future GHG emissions.
Average annual GHG emissions growth between 69 GHG 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 the 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 contain updated emission metric values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice of metric 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 system 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) 70 Territorial emissions 71 GHG emission levels are rounded to two signiﬁcant digits; as a consequence, small differences in sums due to rounding may occur. {WGIII SPM footnote 8} 72 Comprising a gross sink of -12.5 (±3.2) GtCO2 yr-1 resulting from responses of all land to both anthropogenic environmental change and natural climate variability, and net anthropogenic CO2-LULUCF emissions +5.9 (±4.1) GtCO2 yr-1 based on book-keeping models. {WGIII SPM Footnote 14} 73 This estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirect emissions from outside urban areas related to the 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, land-use change, forestry and agriculture.
{WGIII SPM footnote 8} 72 Comprising a gross sink of -12.5 (±3.2) GtCO2 yr-1 resulting from responses of all land to both anthropogenic environmental change and natural climate variability, and net anthropogenic CO2-LULUCF emissions +5.9 (±4.1) GtCO2 yr-1 based on book-keeping models. {WGIII SPM Footnote 14} 73 This estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirect emissions from outside urban areas related to the 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, land-use change, forestry and agriculture. {WGIII SPM footnote 15} 2010 and 2019 slowed compared to the previous decade in energy supply (from 2.3% to 1.0%) and industry (from 3.4% to 1.4%) but remained roughly constant at about 2% yr–1 in the transport sector (high conﬁdence). About half of total net AFOLU emissions are from CO2 LULUCF, predominantly from deforestation (medium conﬁdence). Land overall constituted a net sink of –6.6 (±4.6) GtCO2 yr–1 for the period 2010–201972 (medium conﬁdence). {WGIII SPM B.2, WGIII SPM B.2.1, WGIII SPM B.2.2, WGIII TS 5.6.1} Human-caused climate change is a consequence of more than a century of net GHG emissions from energy use, land-use and land use change, lifestyle and patterns of consumption, and production. Emissions reductions in CO2 from fossil fuels and industrial processes (CO2-FFI), due to improvements in energy intensity of GDP and carbon intensity of energy, have been less than emissions increases from rising global activity levels in industry, energy supply, transport, agriculture and buildings.
Land overall constituted a net sink of –6.6 (±4.6) GtCO2 yr–1 for the period 2010–201972 (medium conﬁdence). {WGIII SPM B.2, WGIII SPM B.2.1, WGIII SPM B.2.2, WGIII TS 5.6.1} Human-caused climate change is a consequence of more than a century of net GHG emissions from energy use, land-use and land use change, lifestyle and patterns of consumption, and production. Emissions reductions in CO2 from fossil fuels and industrial processes (CO2-FFI), due to improvements in energy intensity of GDP and carbon intensity of energy, have been less than emissions increases from rising global activity levels in industry, energy supply, transport, agriculture and buildings. The 10% of households with the highest per capita emissions contribute 34–45% of global consumption-based household GHG emissions, while the middle 40% contribute 40–53%, and the bottom 50% contribute 13–15%. An increasing share of emissions can be attributed to urban areas (a rise from about 62% to 67–72% of the global share between 2015 and 2020). The drivers of urban GHG emissions73 are complex and include population size, income, state of urbanisation and urban form. (high conﬁdence) {WGIII SPM B.2, WGIII SPM B.2.3, WGIII SPM B.3.4, WGIII SPM D.1.1}
45 Current Status and Trends Section 2 Key Population (millions) 0 2000 4000 6000 8000 0 5 10 15 20 Middle East Africa Eastern Asia South-East Asia and Paciﬁc Latin America and Caribbean Europe Southern Asia North America Australia, Japan and New Zealand Eastern Europe and West-Central Asia Africa Australia, Japan and New Zealand Eastern Asia Eastern Europe and West-Central Asia Europe International shipping and aviation Latin America and Caribbean Middle East North America South-East Asia and Paciﬁc Southern Asia 0 200 400 600 50 60 30 20 10 0 4% 16% 4% 2% 8% 12% 11% 10% 7% 2% 23% CO2 GHG GHG 2019 1990 1850 Timeframes represented in these graphs d) Regional indicators (2019) and regional production vs consumption accounting (2018) Production-based emissions (tCO2FFI per person, based on 2018 data) 1.2 10 8.4 9.2 6.5 2.8 8.7 16 2.6 1.6 Consumption-based emissions (tCO2FFI per person, based on 2018 data) 0.84 11 6.7 6.2 7.8 2.8 7.6 17 2.5 1.5 Population (million persons, 2019) 1292 157 1471 291 620 646 252 366 674 1836 GHG per capita (tCO2-eq per person) 3.9 13 11 13 7.8 9.2 13 19 7.9 2.6 GDP per capita (USD1000PPP 2017 per person) 1 5.0 43 17 20 43 15 20 61 12 6.2 Net GHG 2019 2 (production basis) CO2FFI, 2018,
6 1.6 Consumption-based emissions (tCO2FFI per person, based on 2018 data) 0.84 11 6.7 6.2 7.8 2.8 7.6 17 2.5 1.5 Population (million persons, 2019) 1292 157 1471 291 620 646 252 366 674 1836 GHG per capita (tCO2-eq per person) 3.9 13 11 13 7.8 9.2 13 19 7.9 2.6 GDP per capita (USD1000PPP 2017 per person) 1 5.0 43 17 20 43 15 20 61 12 6.2 Net GHG 2019 2 (production basis) CO2FFI, 2018, per person GHG emissions intensity (tCO2-eq / USD1000PPP 2017) 0.78 0.30 0.62 0.64 0.18 0.61 0.64 0.31 0.65 0.42 Africa Australia, Japan, New Zealand Eastern Asia Eastern Europe, West- Central Asia Europe Latin America and Caribbean Middle East North America South-East Asia and Paciﬁc Southern Asia 1 GDP per capita in 2019 in USD2017 currency purchasing power basis. 2 Includes CO2FFI, CO2LULUCF and Other GHGs, excluding international aviation and shipping.
2 Net GHG 2019 2 (production basis) CO2FFI, 2018, per person GHG emissions intensity (tCO2-eq / USD1000PPP 2017) 0.78 0.30 0.62 0.64 0.18 0.61 0.64 0.31 0.65 0.42 Africa Australia, Japan, New Zealand Eastern Asia Eastern Europe, West- Central Asia Europe Latin America and Caribbean Middle East North America South-East Asia and Paciﬁc Southern Asia 1 GDP per capita in 2019 in USD2017 currency purchasing power basis. 2 Includes CO2FFI, CO2LULUCF and Other GHGs, excluding international aviation and shipping. The regional groupings used in this ﬁgure are for statistical purposes only and are described in WGIII Annex II, Part I. c) Global net anthropogenic GHG emissions by region (1990–2019) 2000 1990 2010 2019 Eastern Asia North America Latin America and Caribbean South-East Asia and Paciﬁc Africa Southern Asia Europe Eastern Europe and West-Central Asia Middle East Australia, Japan and New Zealand International shipping and aviation 13% 18% 10% 7% 7% 7% 16% 14% 3% 5% 2% 16% 19% 11% 7% 8% 8% 2% 5% 8% 4% 13% 27% 24% 12% 14% 10% 11% 9% 7% 9% 8% 8% 8% 2% 2% 7% 5% 4% 5% 3% 6% 10% 8% Total: 38 GtCO2-eq 42 GtCO2-eq 53 GtCO2-eq 59 GtCO2-eq Emissions have grown in most regions but are distributed unevenly, both in the present day and cumulatively since 1850 b) Net anthropogenic GHG emissions per capita and for total population, per region (2019) a) Historical cumulative net anthropogenic CO2 emissions per region (1850–2019) GHG emissions (tCO2-eq per capita) / CO2 emissions (GtCO2) Net CO2 from land use, land use change, forestry (CO2LULUCF) Other GHG emissions Fossil fuel and industry (CO2FFI) All GHG emissions GHG emissions per year (GtCO2-eq/yr)
46 Section 2 Section 1 Section 2 Figure 2.2: Regional GHG emissions, and the regional proportion of total cumulative production-based CO2 emissions from 1850 to 2019. Panel (a) shows the share 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. CO2-LULUCF emissions are subject to high uncertainties, reﬂected by a global uncertainty estimate of ±70% (90% conﬁdence interval). Panel (b) shows the distribution of regional GHG 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, ﬂuorinated gases, expressed 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 refers 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 axis, indicating net CO2 removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr–1 (GWP100-AR6)) for the time period 1990–2019. 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 higher CO2-LULUCF emissions from a forest and peat ﬁre event in South East Asia. Regions are as grouped in Annex II of WGIII.
The height of each rectangle shows per capita emissions, the width shows the population of the region, so that the area of the rectangles refers 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 axis, indicating net CO2 removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr–1 (GWP100-AR6)) for the time period 1990–2019. 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 higher CO2-LULUCF emissions from a forest and peat ﬁre event in South East Asia. Regions are as grouped in Annex II of WGIII. Panel (d) shows population, gross domestic product (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, which 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 certain entity (e.g., region). Emissions from international aviation and shipping are not included. {WGIII Figure SPM.2} 2.1.2. Observed Climate System Changes and Impacts to Date It is unequivocal that human inﬂuence has warmed the atmosphere, ocean and land. Widespread and rapid changes in the atmosphere, ocean, cryosphere and biosphere have occurred (Table 2.1). The scale of recent changes across the climate system as a whole and the present state of many aspects of the climate system are unprecedented over many centuries to many thousands of years. It is very likely that GHG emissions were the main driver74 of tropospheric warming and extremely likely that human-caused stratospheric ozone depletion was the main driver of stratospheric cooling between 1979 and the mid-1990s.
Emissions from international aviation and shipping are not included. {WGIII Figure SPM.2} 2.1.2. Observed Climate System Changes and Impacts to Date It is unequivocal that human inﬂuence has warmed the atmosphere, ocean and land. Widespread and rapid changes in the atmosphere, ocean, cryosphere and biosphere have occurred (Table 2.1). The scale of recent changes across the climate system as a whole and the present state of many aspects of the climate system are unprecedented over many centuries to many thousands of years. It is very likely that GHG emissions were the main driver74 of tropospheric warming and extremely likely that human-caused stratospheric ozone depletion was the main driver of stratospheric cooling between 1979 and the mid-1990s. It is virtually certain that the global upper ocean (0-700m) has warmed since the 1970s and extremely likely that human inﬂuence is the main driver. Ocean warming accounted for 91% of the heating in the climate system, with land warming, ice loss and atmospheric warming accounting for about 5%, 3% and 1%, respectively (high conﬁdence). Global mean sea level increased by 0.20 [0.15 to 0.25] m between 1901 and 2018. The average rate of sea level rise was 1.3 [0.6 to 2.1]mm yr-1 between 1901 and 1971, increasing to 1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and further increasing to 3.7 [3.2 to –4.2] mm yr-1 between 2006 and 2018 (high conﬁdence). Human inﬂuence was very likely the main driver of these increases since at least 1971 (Figure 3.4).
Global mean sea level increased by 0.20 [0.15 to 0.25] m between 1901 and 2018. The average rate of sea level rise was 1.3 [0.6 to 2.1]mm yr-1 between 1901 and 1971, increasing to 1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and further increasing to 3.7 [3.2 to –4.2] mm yr-1 between 2006 and 2018 (high conﬁdence). Human inﬂuence was very likely the main driver of these increases since at least 1971 (Figure 3.4). Human inﬂuence is very likely the main driver of the global retreat of glaciers since the 1990s and the decrease in Arctic sea ice area between 1979–1988 and 2010–2019. Human inﬂuence has also very likely contributed to decreased Northern Hemisphere spring snow cover and surface melting of the Greenland ice sheet. It is virtually certain that human-caused CO2 emissions are the main driver of current global acidiﬁcation of the surface open ocean. {WGI SPM A.1, WGI SPM A.1.3, WGI SPM A.1.5, WGI SPM A.1.6, WG1 SPM A1.7, WGI SPM A.2, WG1.SPM A.4.2; SROCC SPM.A.1, SROCC SPM A.2} Human-caused climate change is already affecting many weather and climate extremes in every region across the globe. Evidence of observed changes in extremes such as heatwaves, heavy precipitation, droughts, and tropical cyclones, and, in particular, their attribution to human inﬂuence, has strengthened since AR5 (Figure 2.3).
It is virtually certain that human-caused CO2 emissions are the main driver of current global acidiﬁcation of the surface open ocean. {WGI SPM A.1, WGI SPM A.1.3, WGI SPM A.1.5, WGI SPM A.1.6, WG1 SPM A1.7, WGI SPM A.2, WG1.SPM A.4.2; SROCC SPM.A.1, SROCC SPM A.2} Human-caused climate change is already affecting many weather and climate extremes in every region across the globe. Evidence of observed changes in extremes such as heatwaves, heavy precipitation, droughts, and tropical cyclones, and, in particular, their attribution to human inﬂuence, has strengthened since AR5 (Figure 2.3). It is virtually certain that hot extremes (including heatwaves) have become more frequent and more intense across most land regions since the 1950s (Figure 2.3), while cold extremes (including cold waves) have become less frequent and less severe, with high conﬁdence that human-caused climate change is the main driver of these changes. Marine heatwaves have approximately doubled 74 ‘Main driver’ means responsible for more than 50% of the change. {WGI SPM footnote 12} 75 See Annex I: Glossary. in frequency since the 1980s (high conﬁdence), and human inﬂuence has very likely contributed to most of them since at least 2006. The frequency and intensity of heavy precipitation events have increased since the 1950s over most land areas for which observational data are sufﬁcient for trend analysis (high conﬁdence), and human-caused climate change is likely the main driver (Figure 2.3). Human-caused climate change has contributed to increases in agricultural and ecological droughts in some regions due to increased land evapotranspiration (medium conﬁdence) (Figure 2.3).
Marine heatwaves have approximately doubled 74 ‘Main driver’ means responsible for more than 50% of the change. {WGI SPM footnote 12} 75 See Annex I: Glossary. in frequency since the 1980s (high conﬁdence), and human inﬂuence has very likely contributed to most of them since at least 2006. The frequency and intensity of heavy precipitation events have increased since the 1950s over most land areas for which observational data are sufﬁcient for trend analysis (high conﬁdence), and human-caused climate change is likely the main driver (Figure 2.3). Human-caused climate change has contributed to increases in agricultural and ecological droughts in some regions due to increased land evapotranspiration (medium conﬁdence) (Figure 2.3). It is likely that the global proportion of major (Category 3–5) tropical cyclone occurrence has increased over the last four decades. {WGI SPM A.3, WGI SPM A3.1, WGI SPM A3.2; WGI SPM A3.4; SRCCL SPM.A.2.2; SROCC SPM. A.2} Climate change has caused substantial damages, and increasingly irreversible75 losses, in terrestrial, freshwater, cryospheric and coastal and open ocean ecosystems (high conﬁdence). The extent and magnitude of climate change impacts are larger than estimated in previous assessments (high conﬁdence). Approximately half of the species assessed globally have shifted polewards or, on land, also to higher elevations (very high conﬁdence). Biological responses including changes in geographic placement and shifting seasonal timing are often not sufﬁcient to cope with recent climate change (very high conﬁdence). Hundreds of local losses of species have been driven by increases in the magnitude of heat extremes (high conﬁdence) and mass mortality events on land and in the ocean (very high conﬁdence).
A.2} Climate change has caused substantial damages, and increasingly irreversible75 losses, in terrestrial, freshwater, cryospheric and coastal and open ocean ecosystems (high conﬁdence). The extent and magnitude of climate change impacts are larger than estimated in previous assessments (high conﬁdence). Approximately half of the species assessed globally have shifted polewards or, on land, also to higher elevations (very high conﬁdence). Biological responses including changes in geographic placement and shifting seasonal timing are often not sufﬁcient to cope with recent climate change (very high conﬁdence). Hundreds of local losses of species have been driven by increases in the magnitude of heat extremes (high conﬁdence) and mass mortality events on land and in the ocean (very high conﬁdence). Impacts on some ecosystems are approaching irreversibility such as the impacts of hydrological changes resulting from the retreat of glaciers, or the changes in some mountain (medium conﬁdence) and Arctic ecosystems driven by permafrost thaw (high conﬁdence). Impacts in ecosystems from slow-onset processes such as ocean acidiﬁcation, sea level rise or regional decreases in precipitation have also been attributed to human-caused climate change (high conﬁdence). Climate change has contributed to desertiﬁcation and exacerbated land degradation, particularly in low lying coastal areas, river deltas, drylands and in permafrost areas (high conﬁdence). Nearly 50% of coastal wetlands have been lost over the last 100 years, as a result of the combined effects of localised human pressures, sea level rise, warming and extreme climate events (high confidence).
Impacts in ecosystems from slow-onset processes such as ocean acidiﬁcation, sea level rise or regional decreases in precipitation have also been attributed to human-caused climate change (high conﬁdence). Climate change has contributed to desertiﬁcation and exacerbated land degradation, particularly in low lying coastal areas, river deltas, drylands and in permafrost areas (high conﬁdence). Nearly 50% of coastal wetlands have been lost over the last 100 years, as a result of the combined effects of localised human pressures, sea level rise, warming and extreme climate events (high confidence). {WGII SPM B.1.1, WGII SPM B.1.2, WGII Figure SPM.2.A, WGII TS.B.1; SRCCL SPM A.1.5, SRCCL SPM A.2, SRCCL SPM A.2.6, SRCCL Figure SPM.1; SROCC SPM A.6.1, SROCC SPM, A.6.4, SROCC SPM A.7}
47 Current Status and Trends Section 2 Table 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate system components, and their attribution to human inﬂuence. The colour coding indicates the assessed conﬁdence in / likelihood76 of the observed change and the human contribution as a driver or main driver (speciﬁed in that case) where available (see colour key). Otherwise, explanatory text is provided. {WGI Table TS.1} 76 Based on scientiﬁc understanding, key ﬁndings can be formulated as statements of fact or associated with an assessed level of conﬁdence indicated using the IPCC calibrated language.
47 Current Status and Trends Section 2 Table 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate system components, and their attribution to human inﬂuence. The colour coding indicates the assessed conﬁdence in / likelihood76 of the observed change and the human contribution as a driver or main driver (speciﬁed in that case) where available (see colour key). Otherwise, explanatory text is provided. {WGI Table TS.1} 76 Based on scientiﬁc understanding, key ﬁndings can be formulated as statements of fact or associated with an assessed level of conﬁdence indicated using the IPCC calibrated language. likely range of human contribution ([0.8-1.3°C]) encompasses the very likely range of observed warming ([0.9-1.2°C]) Observed change assessment Human contribution assessment Main driver Main driver 1979 - mid-1990s Southern Hemisphere Main driver Main driver Main driver Limited evidence & medium agreement Main driver Main driver Main driver Main driver Change in indicator Warming of global mean surface air temperature since 1850-1900 Warming of the troposphere since 1979 Cooling of the lower stratosphere since the mid-20th century Large-scale precipitation and upper troposphere humidity changes since 1979 Expansion of the zonal mean Hadley Circulation since the 1980s Ocean heat content increase since the 1970s Salinity changes since the mid-20th century Global mean sea level rise since 1970 Arctic sea ice loss since 1979 Reduction in Northern Hemisphere springtime snow cover since 1950 Greenland ice sheet mass loss since 1990s Antarctic ice sheet mass loss since 1990s Retreat of glaciers Increased amplitude of the seasonal cycle of atmospheric CO2 since the early 1960s Acidiﬁcation of the global surface ocean Mean surface air temperature over land (about 40% larger than global mean warming) Warming of the global climate system since preindustrial times medium conﬁdence likely / high conﬁdence very likely extremely likely virtually certain fact Atmosphere and water cycle Ocean Cryosphere Carbon cycle Land climate Synthesis Key
48 Section 2 Section 1 Section 2 Climate change has impacted human and natural systems across the world with those who have generally least contributed to climate change being most vulnerable a) Synthesis of assessment of observed change in hot extremes, heavy precipitation and drought, and conﬁdence in human contribution to the observed changes in the world’s regions Increase Decrease Limited data and/or literature Low agreement in the type of change Key Type of observed change since the 1950s High Medium Low due to limited agreement Low due to limited evidence Conﬁdence in human contribution to the observed change NWN Each hexagon corresponds to a region North-Western North America IPCC AR6 WGI reference regions: North America: NWN (North-Western North America, NEN (North-Eastern North America), WNA (Western North America), CNA (Central North America), ENA (Eastern North America), Central America: NCA (Northern Central America), SCA (Southern Central America), CAR (Caribbean), South America: NWS (North-Western South America), NSA (Northern South America), NES (North-Eastern South America), SAM (South American Monsoon), SWS (South-Western South America), SES (South-Eastern South America), SSA (Southern South America), Europe: GIC (Greenland/Iceland), NEU (Northern Europe), WCE (Western and Central Europe), EEU (Eastern Europe), MED (Mediterranean), Africa: MED (Mediterranean), SAH (Sahara), WAF (Western Africa), CAF (Central Africa), NEAF (North Eastern Africa), SEAF (South Eastern Africa), WSAF (West Southern Africa), ESAF (East Southern Africa), MDG (Madagascar), Asia: RAR (Russian Arctic), WSB (West Siberia), ESB (East Siberia), RFE (Russian Far East), WCA (West Central Asia), ECA (East Central Asia), TIB (Tibetan Plateau), EAS (East Asia), ARP (Arabian Peninsula),
SES (South-Eastern South America), SSA (Southern South America), Europe: GIC (Greenland/Iceland), NEU (Northern Europe), WCE (Western and Central Europe), EEU (Eastern Europe), MED (Mediterranean), Africa: MED (Mediterranean), SAH (Sahara), WAF (Western Africa), CAF (Central Africa), NEAF (North Eastern Africa), SEAF (South Eastern Africa), WSAF (West Southern Africa), ESAF (East Southern Africa), MDG (Madagascar), Asia: RAR (Russian Arctic), WSB (West Siberia), ESB (East Siberia), RFE (Russian Far East), WCA (West Central Asia), ECA (East Central Asia), TIB (Tibetan Plateau), EAS (East Asia), ARP (Arabian Peninsula), SAS (South Asia), SEA (South East Asia), Australasia: NAU (Northern Australia), CAU (Central Australia), EAU (Eastern Australia), SAU (Southern Australia), NZ (New Zealand), Small Islands: CAR (Caribbean), PAC (Paciﬁc Small Islands) NWN NEN GIC NEU RAR WNA CNA ENA WCE EEU WSB ESB RFE NCA MED WCA ECA TIB EAS SCA CAR SAH ARP SAS SEA NWS NSA WAF CAF NEAF NAU SAM NES WSAF
WCA (West Central Asia), ECA (East Central Asia), TIB (Tibetan Plateau), EAS (East Asia), ARP (Arabian Peninsula), SAS (South Asia), SEA (South East Asia), Australasia: NAU (Northern Australia), CAU (Central Australia), EAU (Eastern Australia), SAU (Southern Australia), NZ (New Zealand), Small Islands: CAR (Caribbean), PAC (Paciﬁc Small Islands) NWN NEN GIC NEU RAR WNA CNA ENA WCE EEU WSB ESB RFE NCA MED WCA ECA TIB EAS SCA CAR SAH ARP SAS SEA NWS NSA WAF CAF NEAF NAU SAM NES WSAF SEAF CAU EAU SWS SES ESAF SAU NZ SSA MDG PAC Africa Asia Australasia North America Central America South America Europe Small Islands Small Islands NWN NEN GIC NEU RAR WNA CNA ENA WCE EEU WSB ESB RFE NCA MED WCA ECA TIB EAS SCA CAR SAH ARP SAS SEA NWS NSA WAF CAF NEAF NAU SAM NES WSAF
SEAF CAU EAU SWS SES ESAF SAU NZ SSA MDG PAC Africa Asia Australasia North America Central America South America Europe Small Islands Small Islands NWN NEN GIC NEU RAR WNA CNA ENA WCE EEU WSB ESB RFE NCA MED WCA ECA TIB EAS SCA CAR SAH ARP SAS SEA NWS NSA WAF CAF NEAF NAU SAM NES WSAF SEAF CAU EAU SWS SES ESAF SAU NZ SSA MDG PAC Africa Asia Australasia North America Central America South America Europe Small Islands Small Islands NWN NEN GIC NEU RAR WNA CNA ENA WCE EEU WSB ESB RFE NCA MED WCA ECA TIB EAS SCA CAR SAH ARP SAS SEA NWS NSA WAF CAF NEAF NAU SAM NES WSAF SEAF CAU EAU SWS SES ESAF SAU NZ SSA MDG PAC Africa Asia Australasia North America Central America South America Europe Small Islands Small Islands Hot extremes Heavy precipitation Agricultural and ecological drought including heatwaves Hazard Dimension of Risk:
49 Current Status and Trends Section 2 Terrestrial Freshwater Ocean Changes in ecosystem structure Terrestrial Freshwater Ocean Species range shifts Terrestrial Freshwater Ocean Changes in seasonal timing (phenology) Water availability and food production Health and wellbeing Cities, settlements and infrastructure Asia Africa Global Australasia Europe Central & South America North America Small Islands Physical water availability Agriculture/crop production Fisheries yields and aquaculture production Animal and livestock health and productivity Infectious diseases Displacement Mental health Heat, malnutrition and harm from wildﬁre Inland ﬂooding and associated damages Flood/storm induced damages in coastal areas Damages to key economic sectors Damages to infrastructure c) Observed impacts and related losses and damages of climate change 2019 emissions per capita of 180 nations in tons of CO2 b) Vulnerability of population & per capita emissions per country in 2019 more vulnerable countries generally have lower emissions per capita Increased climate impacts HUMAN SYSTEMS ECOSYSTEMS Adverse impacts Adverse and positive impacts Climate-driven changes observed, no assessment of impact direction / 10 20 0 30 40 50 60 70 80 90 100 10 0 30 20 40 70 80 high low ECOSYSTEMS HUMAN SYSTEMS Key Conﬁdence in attribution to climate change High or very high Medium Low Evidence limited, insufﬁcient Not assessed Vulnerability Dimension of Risk: Impact Dimension of Risk: Vulnerability assessed on national data. Vulnerability differs between and within countries and is exacerbated by inequity and marginalisation. Relative average national vulnerability per capita by global indices INFORM and WRI (2019)
50 Section 2 Section 1 Section 2 Climate change has reduced food security and affected water security due to warming, changing precipitation patterns, reduction and loss of cryospheric elements, and greater frequency and intensity of climatic extremes, thereby hindering efforts to meet Sustainable Development Goals (high conﬁdence). Although overall agricultural productivity has increased, climate change has slowed this growth in agricultural productivity over the past 50 years globally (medium conﬁdence), with related negative crop yield impacts mainly recorded in mid- and low latitude regions, and some positive impacts in some high latitude regions (high conﬁdence). Ocean warming in the 20th century and beyond has contributed to an overall decrease in maximum catch potential (medium conﬁdence), compounding the impacts from overﬁshing for some ﬁsh stocks (high conﬁdence). Ocean warming and ocean acidiﬁcation have adversely affected food production from shellﬁsh aquaculture and ﬁsheries in some oceanic regions (high conﬁdence). Current levels of global warming are associated with moderate risks from increased dryland water scarcity (high conﬁdence). Roughly half of the world’s population currently experiences severe water scarcity for at least some part of the year due to a combination of climatic and non-climatic drivers (medium conﬁdence) (Figure 2.3). Unsustainable agricultural expansion, driven in part by unbalanced diets77, increases ecosystem and human vulnerability and leads to competition for land and/or water resources (high conﬁdence). Increasing weather and climate extreme events have exposed millions of people to acute food insecurity78 and reduced water security, with the largest impacts observed in many locations and/or communities in Africa, Asia, Central and South America, LDCs, Small Islands and the Arctic, and for small-scale food producers, low-income households and Indigenous Peoples globally (high conﬁdence).
Roughly half of the world’s population currently experiences severe water scarcity for at least some part of the year due to a combination of climatic and non-climatic drivers (medium conﬁdence) (Figure 2.3). Unsustainable agricultural expansion, driven in part by unbalanced diets77, increases ecosystem and human vulnerability and leads to competition for land and/or water resources (high conﬁdence). Increasing weather and climate extreme events have exposed millions of people to acute food insecurity78 and reduced water security, with the largest impacts observed in many locations and/or communities in Africa, Asia, Central and South America, LDCs, Small Islands and the Arctic, and for small-scale food producers, low-income households and Indigenous Peoples globally (high conﬁdence). {WGII SPM B.1.3, WGII SPM.B.2.3, WGII Figure SPM.2, WGII TS B.2.3, WGII TS Figure TS. 6; SRCCL SPM A.2.8, SRCCL SPM A.5.3; SROCC SPM A.5.4., SROCC SPM A.7.1, SROCC SPM A.8.1, SROCC Figure SPM.2} 77 Balanced 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, sustainable and low-GHG emissions systems, as described in SRCCL. {WGII SPM Footnote 32} 78 Acute 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 determinants of food security and nutrition, and is used to assess the need for humanitarian action.
6; SRCCL SPM A.2.8, SRCCL SPM A.5.3; SROCC SPM A.5.4., SROCC SPM A.7.1, SROCC SPM A.8.1, SROCC Figure SPM.2} 77 Balanced 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, sustainable and low-GHG emissions systems, as described in SRCCL. {WGII SPM Footnote 32} 78 Acute 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 determinants of food security and nutrition, and is used to assess the need for humanitarian action. {WGII SPM, footnote 30} 79 Slow-onset events are described among the climatic-impact drivers of the AR6 WGI and refer to the risks and impacts associated with e.g., increasing temperature means, desertiﬁcation, decreasing precipitation, loss of biodiversity, land and forest degradation, glacial retreat and related impacts, ocean acidiﬁcation, sea level rise and salinization. {WGII SPM footnote 29} In urban settings, climate change has caused adverse impacts on human health, livelihoods and key infrastructure (high conﬁdence). Hot extremes including heatwaves have intensiﬁed in cities (high conﬁdence), where they have also worsened air pollution events (medium conﬁdence) and limited functioning of key infrastructure (high conﬁdence). Urban infrastructure, including transportation, water, sanitation and energy systems have been compromised by extreme and slow-onset events79, with resulting economic losses, disruptions of services and impacts to well-being (high conﬁdence). Observed impacts are concentrated amongst economically and socially marginalised urban residents, e.g., those living in informal settlements (high conﬁdence).
{WGII SPM footnote 29} In urban settings, climate change has caused adverse impacts on human health, livelihoods and key infrastructure (high conﬁdence). Hot extremes including heatwaves have intensiﬁed in cities (high conﬁdence), where they have also worsened air pollution events (medium conﬁdence) and limited functioning of key infrastructure (high conﬁdence). Urban infrastructure, including transportation, water, sanitation and energy systems have been compromised by extreme and slow-onset events79, with resulting economic losses, disruptions of services and impacts to well-being (high conﬁdence). Observed impacts are concentrated amongst economically and socially marginalised urban residents, e.g., those living in informal settlements (high conﬁdence). Cities intensify human-caused warming locally (very high conﬁdence), while urbanisation also increases mean and heavy precipitation over and/or downwind of cities (medium conﬁdence) and resulting runoff intensity (high conﬁdence). {WGI SPM C.2.6; WGII SPM B.1.5, WGII Figure TS.9, WGII 6 ES} Climate change has adversely affected human physical health globally and mental health in assessed regions (very high conﬁdence), and is contributing to humanitarian crises where climate hazards interact with high vulnerability (high conﬁdence). In all regions increases in extreme heat events have resulted in human mortality and morbidity (very high conﬁdence). The occurrence of climate-related food-borne and water-borne diseases has increased (very high conﬁdence). The incidence of vector-borne diseases has increased from range expansion and/or increased reproduction of disease vectors (high conﬁdence). Animal and human diseases, including zoonoses, are emerging in new areas (high conﬁdence).
{WGI SPM C.2.6; WGII SPM B.1.5, WGII Figure TS.9, WGII 6 ES} Climate change has adversely affected human physical health globally and mental health in assessed regions (very high conﬁdence), and is contributing to humanitarian crises where climate hazards interact with high vulnerability (high conﬁdence). In all regions increases in extreme heat events have resulted in human mortality and morbidity (very high conﬁdence). The occurrence of climate-related food-borne and water-borne diseases has increased (very high conﬁdence). The incidence of vector-borne diseases has increased from range expansion and/or increased reproduction of disease vectors (high conﬁdence). Animal and human diseases, including zoonoses, are emerging in new areas (high conﬁdence). In assessed regions, some mental health challenges are associated with increasing temperatures (high conﬁdence), trauma from extreme events (very high conﬁdence), and loss of livelihoods and culture Figure 2.3: Both vulnerability to current climate extremes and historical contribution to climate change are highly heterogeneous with many of those who have least 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 in 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 on different time scales or more local spatial scales might differ from what is shown in the ﬁgure. The colours in each panel represent the four outcomes of the assessment on observed changes. 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 data and/or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium conﬁdence in the observed change.
Panel (a) The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size in 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 on different time scales or more local spatial scales might differ from what is shown in the ﬁgure. The colours in each panel represent the four outcomes of the assessment on observed changes. 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 data and/or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium conﬁdence in the observed change. The conﬁdence level for the human inﬂuence 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 high conﬁdence, two dots for medium conﬁdence and one dot for low conﬁdence (single, ﬁlled dot: limited agreement; single, empty dot: limited evidence). For hot extremes, the evidence is 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 heavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or ﬁve-day precipitation amounts using global and regional studies. Agricultural and ecological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence on changes in surface soil moisture, water balance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. Panel (b) shows the average level of vulnerability amongst a country’s 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 global indicator systems, namely INFORM and World Risk Index.
For hot extremes, the evidence is 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 heavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or ﬁve-day precipitation amounts using global and regional studies. Agricultural and ecological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence on changes in surface soil moisture, water balance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. Panel (b) shows the average level of vulnerability amongst a country’s 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 global 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 vice versa. The underlying data includes, for example, information on poverty, inequality, health care infrastructure or insurance coverage. Panel (c) Observed impacts on ecosystems and 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 assessments 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 adverse 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 methodology see WGII SMTS.1). Physical water availability includes balance of water available from various sources including ground water, water quality and demand for water. Global mental health and displacement assessments reﬂect only assessed regions. Conﬁdence levels reﬂect the assessment of attribution of the observed impact to climate change.
Panel (c) Observed impacts on ecosystems and 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 assessments 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 adverse 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 methodology see WGII SMTS.1). Physical water availability includes balance of water available from various sources including ground water, water quality and demand for water. Global mental health and displacement assessments reﬂect only assessed regions. Conﬁdence levels reﬂect the assessment of attribution of the observed impact to climate change. {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}
51 Current Status and Trends Section 2 (high conﬁdence) (Figure 2.3). Climate change impacts on health are mediated through natural and human systems, including economic and social conditions and disruptions (high conﬁdence). Climate and weather extremes are increasingly driving displacement in Africa, Asia, North America (high conﬁdence), and Central and South America (medium conﬁdence) (Figure 2.3), with small island states in the Caribbean and South Paciﬁc being disproportionately affected relative to their small population size (high conﬁdence). Through displacement and involuntary migration from extreme weather and climate events, climate change has generated and perpetuated vulnerability (medium conﬁdence). {WGII SPM B.1.4, WGII SPM B.1.7} Human inﬂuence has likely increased the chance of compound extreme events80 since the 1950s. Concurrent and repeated climate hazards have occurred in all regions, increasing impacts and risks to health, ecosystems, infrastructure, livelihoods and food (high conﬁdence). Compound extreme events include increases in the frequency of concurrent heatwaves and droughts (high conﬁdence); ﬁre weather in some regions (medium conﬁdence); and compound ﬂooding in some locations (medium conﬁdence). Multiple risks interact, generating new sources of vulnerability to climate hazards, and compounding overall risk (high conﬁdence). Compound climate hazards can overwhelm adaptive capacity and substantially increase damage (high conﬁdence)). {WGI SPM A.3.5; WGII SPM. B.5.1, WGII TS.C.11.3} Economic impacts attributable to climate change are increasingly affecting peoples’ livelihoods and are causing economic and societal impacts across national boundaries (high conﬁdence).
Compound extreme events include increases in the frequency of concurrent heatwaves and droughts (high conﬁdence); ﬁre weather in some regions (medium conﬁdence); and compound ﬂooding in some locations (medium conﬁdence). Multiple risks interact, generating new sources of vulnerability to climate hazards, and compounding overall risk (high conﬁdence). Compound climate hazards can overwhelm adaptive capacity and substantially increase damage (high conﬁdence)). {WGI SPM A.3.5; WGII SPM. B.5.1, WGII TS.C.11.3} Economic impacts attributable to climate change are increasingly affecting peoples’ livelihoods and are causing economic and societal impacts across national boundaries (high conﬁdence). Economic damages from climate change have been detected in climate-exposed sectors, with regional effects to agriculture, forestry, ﬁshery, energy, and tourism, and through outdoor labour productivity (high conﬁdence) with some exceptions of positive impacts in regions with low energy demand and comparative advantages in agricultural markets and tourism (high conﬁdence). Individual livelihoods have been affected through changes in agricultural productivity, impacts on human health and food security, destruction of homes and infrastructure, and loss of property and income, with adverse effects on gender and social equity (high conﬁdence). Tropical cyclones have reduced economic growth in the short-term (high conﬁdence). Event attribution studies and physical understanding indicate that human-caused climate change increases heavy precipitation associated with tropical cyclones (high conﬁdence). Wildﬁres in many regions have affected built assets, economic activity, and health (medium to high conﬁdence). In cities and settlements, climate impacts to key infrastructure are leading to losses and damages across water and food systems, and affect economic activity, with impacts extending beyond the area directly impacted by the climate hazard (high conﬁdence).
Individual livelihoods have been affected through changes in agricultural productivity, impacts on human health and food security, destruction of homes and infrastructure, and loss of property and income, with adverse effects on gender and social equity (high conﬁdence). Tropical cyclones have reduced economic growth in the short-term (high conﬁdence). Event attribution studies and physical understanding indicate that human-caused climate change increases heavy precipitation associated with tropical cyclones (high conﬁdence). Wildﬁres in many regions have affected built assets, economic activity, and health (medium to high conﬁdence). In cities and settlements, climate impacts to key infrastructure are leading to losses and damages across water and food systems, and affect economic activity, with impacts extending beyond the area directly impacted by the climate hazard (high conﬁdence). {WGI SPM A.3.4; WGII SPM B.1.6, WGII SPM B.5.2, WGII SPM B.5.3} Climate change has caused widespread adverse impacts and related losses and damages to nature and people (high conﬁdence). Losses and damages are unequally distributed across systems, regions and sectors (high conﬁdence). Cultural losses, related 80 See Annex 1: Glossary. 81 Governance: The structures, processes and actions through which private and public actors interact to address societal goals. This includes formal and informal institutions and the associated norms, rules, laws and procedures for deciding, managing, implementing and monitoring policies and measures at any geographic or political scale, from global to local. {WGII SPM Footnote 31} to tangible and intangible heritage, threaten adaptive capacity and may result in irrevocable losses of sense of belonging, valued cultural practices, identity and home, particularly for Indigenous Peoples and those more directly reliant on the environment for subsistence (medium conﬁdence). For example, changes in snow cover, lake and river ice, and permafrost in many Arctic regions, are harming the livelihoods and cultural identity of Arctic residents including Indigenous populations (high conﬁdence).
Cultural losses, related 80 See Annex 1: Glossary. 81 Governance: The structures, processes and actions through which private and public actors interact to address societal goals. This includes formal and informal institutions and the associated norms, rules, laws and procedures for deciding, managing, implementing and monitoring policies and measures at any geographic or political scale, from global to local. {WGII SPM Footnote 31} to tangible and intangible heritage, threaten adaptive capacity and may result in irrevocable losses of sense of belonging, valued cultural practices, identity and home, particularly for Indigenous Peoples and those more directly reliant on the environment for subsistence (medium conﬁdence). For example, changes in snow cover, lake and river ice, and permafrost in many Arctic regions, are harming the livelihoods and cultural identity of Arctic residents including Indigenous populations (high conﬁdence). Infrastructure, including transportation, water, sanitation and energy systems have been compromised by extreme and slow-onset events, with resulting economic losses, disruptions of services and impacts to well-being (high conﬁdence). {WGII SPM B.1, WGII SPM B.1.2, WGII SPM.B.1.5, WGII SPM C.3.5, WGII TS.B.1.6; SROCC SPM A.7.1} Across sectors and regions, the most vulnerable people and systems have been disproportionately affected by the impacts of climate change (high conﬁdence). LDCs and SIDS who have much lower per capita emissions (1.7 tCO2-eq, 4.6 tCO2-eq, respectively) than the global average (6.9 tCO2-eq) excluding CO2-LULUCF, also have high vulnerability to climatic hazards, with global hotspots of high human vulnerability observed in West-, Central- and East Africa, South Asia, Central and South America, SIDS and the Arctic (high conﬁdence). Regions and people with considerable development constraints have high vulnerability to climatic hazards (high conﬁdence).
LDCs and SIDS who have much lower per capita emissions (1.7 tCO2-eq, 4.6 tCO2-eq, respectively) than the global average (6.9 tCO2-eq) excluding CO2-LULUCF, also have high vulnerability to climatic hazards, with global hotspots of high human vulnerability observed in West-, Central- and East Africa, South Asia, Central and South America, SIDS and the Arctic (high conﬁdence). Regions and people with considerable development constraints have high vulnerability to climatic hazards (high conﬁdence). Vulnerability is higher in locations with poverty, governance challenges and limited access to basic services and resources, violent conﬂict and high levels of climate-sensitive livelihoods (e.g., smallholder farmers, pastoralists, ﬁshing communities) (high conﬁdence). Vulnerability at different spatial levels is exacerbated by inequity and marginalisation linked to gender, ethnicity, low income or combinations thereof (high conﬁdence), especially for many Indigenous Peoples and local communities (high conﬁdence). Approximately 3.3 to 3.6 billion people live in contexts that are highly vulnerable to climate change (high conﬁdence). Between 2010 and 2020, human mortality from ﬂoods, droughts and storms was 15 times higher in highly vulnerable regions, compared to regions with very low vulnerability (high conﬁdence). In the Arctic and in some high mountain regions, negative impacts of cryosphere change have been especially felt among Indigenous Peoples (high conﬁdence). Human and ecosystem vulnerability are interdependent (high conﬁdence). Vulnerability of ecosystems and people to climate change differs substantially among and within regions (very high conﬁdence), driven by patterns of intersecting socio-economic development, unsustainable ocean and land use, inequity, marginalisation, historical and ongoing patterns of inequity such as colonialism, and governance81 (high conﬁdence).
Between 2010 and 2020, human mortality from ﬂoods, droughts and storms was 15 times higher in highly vulnerable regions, compared to regions with very low vulnerability (high conﬁdence). In the Arctic and in some high mountain regions, negative impacts of cryosphere change have been especially felt among Indigenous Peoples (high conﬁdence). Human and ecosystem vulnerability are interdependent (high conﬁdence). Vulnerability of ecosystems and people to climate change differs substantially among and within regions (very high conﬁdence), driven by patterns of intersecting socio-economic development, unsustainable ocean and land use, inequity, marginalisation, historical and ongoing patterns of inequity such as colonialism, and governance81 (high conﬁdence). {WGII SPM B.1, WGII SPM B.2, WGII SPM B.2.4; WGIII SPM B.3.1; SROCC SPM A.7.1, SROCC SPM A.7.2}
52 Section 2 Section 1 Section 2 International climate agreements, rising national ambitions for climate action, along with rising public awareness are accelerating efforts to address climate change at multiple levels of governance. Mitigation policies have contributed to a decrease in global energy and carbon intensity, with several countries achieving GHG emission reductions for over a decade. Low-emission technologies are becoming more affordable, with many low or zero emissions options now available for energy, buildings, transport, and industry. Adaptation planning and implementation progress has generated multiple beneﬁts, with effective adaptation options having the potential to reduce climate risks and contribute to sustainable development. Global tracked ﬁnance for mitigation and adaptation has seen an upward trend since AR5, but falls short of needs. (high conﬁdence) 2.2.1. Global Policy Setting The United Nations Framework Convention on Climate Change (UNFCCC), Kyoto Protocol, and Paris Agreement are supporting rising levels of national ambition and encouraging the development and implementation of climate policies at multiple levels of governance (high conﬁdence). The Kyoto Protocol led to reduced emissions in some countries and was instrumental in building national and international capacity for GHG reporting, accounting and emissions markets (high confidence). The Paris Agreement, adopted under the UNFCCC, with near universal participation, has led to policy development and target-setting at national and sub-national levels, particularly in relation to mitigation but also for adaptation, as well as enhanced transparency of climate action and support (medium confidence). Nationally Determined Contributions (NDCs), required under the Paris Agreement, have required countries to articulate their priorities and ambition with respect to climate action. {WGII 17.4, WGII TS D.1.1; WGIII SPM B.5.1, WGIII SPM E.6} Loss & Damage82 was formally recognized in 2013 through establishment of the Warsaw International Mechanism on Loss and Damage (WIM), and in 2015, Article 8 of the Paris Agreement provided a legal basis for the WIM.
The Paris Agreement, adopted under the UNFCCC, with near universal participation, has led to policy development and target-setting at national and sub-national levels, particularly in relation to mitigation but also for adaptation, as well as enhanced transparency of climate action and support (medium confidence). Nationally Determined Contributions (NDCs), required under the Paris Agreement, have required countries to articulate their priorities and ambition with respect to climate action. {WGII 17.4, WGII TS D.1.1; WGIII SPM B.5.1, WGIII SPM E.6} Loss & Damage82 was formally recognized in 2013 through establishment of the Warsaw International Mechanism on Loss and Damage (WIM), and in 2015, Article 8 of the Paris Agreement provided a legal basis for the WIM. There is improved understanding of both economic and non-economic losses and damages, which is informing international climate policy and which has highlighted that losses and damages are not comprehensively addressed by current ﬁnancial, governance and institutional arrangements, particularly in vulnerable developing countries (high conﬁdence). {WGII SPM C.3.5, WGII Cross-Chapter Box LOSS} Other recent global agreements that inﬂuence responses to climate change include the Sendai Framework for Disaster Risk Reduction (2015-2030), the ﬁnance-oriented Addis Ababa Action Agenda (2015) and the New Urban Agenda (2016), and the Kigali Amendment to the Montreal Protocol on Substances that Deplete the Ozone Layer (2016), among others. In addition, the 2030 Agenda for Sustainable Development, adopted in 2015 by UN member states, sets out 17 Sustainable Development Goals (SDGs) and seeks to align efforts globally to prioritise ending extreme poverty, protect the planet and promote more peaceful, prosperous and inclusive societies. If achieved, these agreements would reduce climate change, and the impacts on health, well-being, migration, and conﬂict, among others (very high conﬁdence).
In addition, the 2030 Agenda for Sustainable Development, adopted in 2015 by UN member states, sets out 17 Sustainable Development Goals (SDGs) and seeks to align efforts globally to prioritise ending extreme poverty, protect the planet and promote more peaceful, prosperous and inclusive societies. If achieved, these agreements would reduce climate change, and the impacts on health, well-being, migration, and conﬂict, among others (very high conﬁdence). {WGII TS.A.1, WGII 7 ES} Since AR5, rising public awareness and an increasing diversity of actors, have overall helped accelerate political commitment and global efforts to address climate change (medium 82 See Annex I: Glossary. conﬁdence). Mass social movements have emerged as catalysing agents in some regions, often building on prior movements including Indigenous Peoples-led movements, youth movements, human rights movements, gender activism, and climate litigation, which is raising awareness and, in some cases, has inﬂuenced the outcome and ambition of climate governance (medium conﬁdence). 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). The media helps shape the public discourse about climate change. This can usefully build public support to accelerate climate action (medium evidence, high agreement). In some instances, public discourses of media and organised counter movements have impeded climate action, exacerbating helplessness and disinformation and fuelling polarisation, with negative implications for climate action (medium conﬁdence).
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). The media helps shape the public discourse about climate change. This can usefully build public support to accelerate climate action (medium evidence, high agreement). In some instances, public discourses of media and organised counter movements have impeded climate action, exacerbating helplessness and disinformation and fuelling polarisation, with negative implications for climate action (medium conﬁdence). {WGII SPM C.5.1, WGII SPM D.2, WGII TS.D.9, WGII TS.D.9.7, WGII TS.E.2.1, WGII 18.4; WGIII SPM D.3.3, WGIII SPM E.3.3, WGIII TS.6.1, WGIII 6.7, WGIII 13 ES, WGIII Box.13.7} 2.2.2. Mitigation Actions to Date There has been a consistent expansion of policies and laws addressing mitigation since AR5 (high conﬁdence). Climate governance supports mitigation by providing frameworks through which diverse actors interact, and a basis for policy development and implementation (medium conﬁdence). Many regulatory and economic instruments have already been deployed successfully (high conﬁdence). By 2020, laws primarily focussed on reducing GHG emissions existed in 56 countries covering 53% of global emissions (medium conﬁdence). The application of diverse policy instruments for mitigation at the national and sub-national levels has grown consistently across a range of sectors (high conﬁdence). Policy coverage is uneven across sectors and remains limited for emissions from agriculture, and from industrial materials and feedstocks (high conﬁdence).
Mitigation Actions to Date There has been a consistent expansion of policies and laws addressing mitigation since AR5 (high conﬁdence). Climate governance supports mitigation by providing frameworks through which diverse actors interact, and a basis for policy development and implementation (medium conﬁdence). Many regulatory and economic instruments have already been deployed successfully (high conﬁdence). By 2020, laws primarily focussed on reducing GHG emissions existed in 56 countries covering 53% of global emissions (medium conﬁdence). The application of diverse policy instruments for mitigation at the national and sub-national levels has grown consistently across a range of sectors (high conﬁdence). Policy coverage is uneven across sectors and remains limited for emissions from agriculture, and from industrial materials and feedstocks (high conﬁdence). {WGIII SPM B.5, WGIII SPM B.5.2, WGIII SPM E.3, WGIII SPM E.4} Practical experience has informed economic instrument design and helped to improve predictability, environmental effectiveness, economic efﬁciency, alignment with distributional goals, and social acceptance (high conﬁdence). Low-emission technological innovation is strengthened through the combination of technology-push policies, together with policies that create incentives for behaviour change and market opportunities (high conﬁdence) (Section 4.8.3). Comprehensive and consistent policy packages have been found to be more effective 2.2 Responses Undertaken to Date
53 Current Status and Trends Section 2 than single policies (high conﬁdence). Combining mitigation with policies to shift development pathways, policies that induce lifestyle or behaviour changes, for example, measures promoting walkable urban areas combined with electriﬁcation and renewable energy can create health co-beneﬁts from cleaner air and enhanced active mobility (high conﬁdence). Climate governance enables mitigation by providing an overall direction, setting targets, mainstreaming climate action across policy domains and levels, based on national circumstances and in the context of international cooperation. Effective governance enhances regulatory certainty, creating specialised organisations and creating the context to mobilise ﬁnance (medium conﬁdence). These functions can be promoted by climate-relevant laws, which are growing in number, or climate strategies, among others, based on national and sub-national context (medium conﬁdence). Effective and equitable climate governance builds on engagement with civil society actors, political actors, businesses, youth, labour, media, Indigenous Peoples and local communities (medium conﬁdence). {WGIII SPM E.2.2, WGIII SPM E.3, WGIII SPM E.3.1, WGIII SPM E.4.2, WGIII SPM E.4.3, WGIII SPM E.4.4} The unit costs of several low-emission technologies, including solar, wind and lithium-ion batteries, have fallen consistently since 2010 (Figure 2.4). Design and process innovations in combination with the use of digital technologies have led to near-commercial availability of many low or zero emissions options in buildings, transport and industry. 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%), and large increases in their deployment, e.g., >10× for solar and >100× for electric vehicles (EVs), albeit varying widely across regions (Figure 2.4).
Design and process innovations in combination with the use of digital technologies have led to near-commercial availability of many low or zero emissions options in buildings, transport and industry. 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%), and large increases in their deployment, e.g., >10× for solar and >100× for electric vehicles (EVs), albeit varying widely across regions (Figure 2.4). Electricity from PV and wind is now cheaper than electricity from fossil sources in many regions, electric vehicles are increasingly competitive with internal combustion engines, and large-scale battery storage on electricity grids is increasingly viable. In comparison to modular small-unit size technologies, the empirical record shows that multiple large-scale mitigation technologies, with fewer opportunities for learning, have seen minimal cost reductions and their adoption has grown slowly. Maintaining emission-intensive systems may, in some regions and sectors, be more expensive than transitioning to low emission systems. (high conﬁdence) {WGIII SPM B.4, WGIII SPM B.4.1, WGIII SPM C.4.2, WGIII SPM C.5.2, WGIII SPM C.7.2, WGIII SPM C.8, WGIII Figure SPM.3, WGIII Figure SPM.3} For almost all basic materials – primary metals, building materials and chemicals – many low- to zero-GHG intensity production processes are at the pilot to near-commercial and in some cases commercial stage but they are not yet established industrial practice. Integrated design in construction and retroﬁt of buildings has led to increasing examples of zero energy or zero carbon buildings. Technological innovation made possible the widespread adoption of LED lighting. Digital technologies including sensors, the internet of things, robotics, and artiﬁcial intelligence can improve energy management in all sectors; they can increase energy efﬁciency, and promote the adoption of many low-emission technologies, including decentralised renewable energy, while creating economic opportunities.
Integrated design in construction and retroﬁt of buildings has led to increasing examples of zero energy or zero carbon buildings. Technological innovation made possible the widespread adoption of LED lighting. Digital technologies including sensors, the internet of things, robotics, and artiﬁcial intelligence can improve energy management in all sectors; they can increase energy efﬁciency, and promote the adoption of many low-emission technologies, including decentralised renewable energy, while creating economic opportunities. However, some of these climate change mitigation gains can be reduced or counterbalanced by growth in demand for goods and services due to the use of digital devices. Several mitigation options, notably solar energy, wind energy, electriﬁcation of urban systems, urban green infrastructure, energy efﬁciency, demand side management, improved forest- and crop/grassland management, and reduced food waste and loss, are technically viable, are becoming increasingly cost effective and are generally supported by the public, and this enables expanded deployment in many regions. (high conﬁdence) {WGIII SPM B.4.3, WGIII SPM C.5.2, WGIII SPM C.7.2, WGIII SPM E.1.1, WGIII TS.6.5} The magnitude of global climate ﬁnance ﬂows has increased and ﬁnancing channels have broadened (high conﬁdence). Annual tracked total ﬁnancial ﬂows for climate mitigation and adaptation increased by up to 60% between 2013/14 and 2019/20, but average growth has slowed since 2018 (medium conﬁdence) and most climate ﬁnance stays within national borders (high conﬁdence). Markets for green bonds, environmental, social and governance and sustainable ﬁnance products have expanded signiﬁcantly since AR5 (high conﬁdence). Investors, central banks, and ﬁnancial regulators are driving increased awareness of climate risk to support climate policy development and implementation (high conﬁdence).
Annual tracked total ﬁnancial ﬂows for climate mitigation and adaptation increased by up to 60% between 2013/14 and 2019/20, but average growth has slowed since 2018 (medium conﬁdence) and most climate ﬁnance stays within national borders (high conﬁdence). Markets for green bonds, environmental, social and governance and sustainable ﬁnance products have expanded signiﬁcantly since AR5 (high conﬁdence). Investors, central banks, and ﬁnancial regulators are driving increased awareness of climate risk to support climate policy development and implementation (high conﬁdence). Accelerated international ﬁnancial cooperation is a critical enabler of low-GHG and just transitions (high conﬁdence). {WGIII SPM B.5.4, WGIII SPM E.5, WGIII TS.6.3, WGIII TS.6.4} Economic instruments have been effective in reducing emissions, complemented by regulatory instruments mainly at the national and also sub-national and regional level (high conﬁdence). By 2020, over 20% of global GHG emissions were covered by carbon taxes or emissions trading systems, although coverage and prices have been insufﬁcient to achieve deep reductions (medium conﬁdence). Equity and distributional impacts of carbon pricing instruments can be addressed by using revenue from carbon taxes or emissions trading to support low-income households, among other approaches (high conﬁdence). The mix of policy instruments which reduced costs and stimulated adoption of solar energy, wind energy and lithium-ion batteries includes public R&D, funding for demonstration and pilot projects, and demand-pull instruments such as deployment subsidies to attain scale (high conﬁdence) (Figure 2.4).
By 2020, over 20% of global GHG emissions were covered by carbon taxes or emissions trading systems, although coverage and prices have been insufﬁcient to achieve deep reductions (medium conﬁdence). Equity and distributional impacts of carbon pricing instruments can be addressed by using revenue from carbon taxes or emissions trading to support low-income households, among other approaches (high conﬁdence). The mix of policy instruments which reduced costs and stimulated adoption of solar energy, wind energy and lithium-ion batteries includes public R&D, funding for demonstration and pilot projects, and demand-pull instruments such as deployment subsidies to attain scale (high conﬁdence) (Figure 2.4). {WGIII SPM B.4.1, WGIII SPM B.5.2, WGIII SPM E.4.2, WG III TS.3} Mitigation actions, supported by policies, have contributed to a decrease in global energy and carbon intensity between 2010 and 2019, with a growing number of countries achieving absolute GHG emission reductions for more than a decade (high conﬁdence). While global net GHG emissions have increased since 2010, global energy intensity (total primary energy per unit GDP) decreased by 2% yr–1 between 2010 and 2019. Global carbon intensity (CO2-FFI per unit primary energy) also decreased by 0.3% yr–1, mainly due to fuel switching from coal to gas, reduced expansion of coal capacity, and increased use of renewables, and with large regional variations over the same period. In many countries, policies have enhanced energy efﬁciency, reduced rates of deforestation and accelerated technology deployment, leading to avoided and in some cases reduced or removed emissions (high conﬁdence).
While global net GHG emissions have increased since 2010, global energy intensity (total primary energy per unit GDP) decreased by 2% yr–1 between 2010 and 2019. Global carbon intensity (CO2-FFI per unit primary energy) also decreased by 0.3% yr–1, mainly due to fuel switching from coal to gas, reduced expansion of coal capacity, and increased use of renewables, and with large regional variations over the same period. In many countries, policies have enhanced energy efﬁciency, reduced rates of deforestation and accelerated technology deployment, leading to avoided and in some cases reduced or removed emissions (high conﬁdence). At least 18 countries have sustained production-based CO2 and GHG and consumption-based CO2 absolute emission reductions for longer than 10 years since 2005 through energy supply decarbonization, energy efﬁciency gains, and energy demand reduction, which resulted from both policies and changes in economic structure (high conﬁdence). Some countries have reduced production-based GHG emissions by a third or more since peaking, and some have achieved reduction rates of around 4% yr–1 for several years consecutively (high conﬁdence). Multiple lines of evidence suggest that mitigation policies have led to avoided global emissions of several GtCO2-eq yr–1 (medium conﬁdence).
54 Section 2 Section 1 Section 2 Market cost, with range Adoption (note different scales) Fossil fuel cost (2020) Passenger electric vehicle Photovoltaics (PV) Onshore wind Offshore wind Key a) Market Cost b) Market Adoption Renewable electricity generation is increasingly price-competitive and some sectors are electrifying Since AR5, the unit costs of some forms of renewable energy and of batteries for passenger EVs have fallen. Since AR5, the installed capacity of renewable energies has increased multiple times. 2000 2020 2010 2010 2010 2010 2010 2010 2010 2010 2010 Cost ($2020/MWh) 1200 1600 Li-ion battery packs 800 400 0 150 300 450 600 0 Cost ($2020/kWh) Adoption (millions of EVs) 0 2 4 6 8 Adoption (GW) -note differnt scales 0 200 400 600 800 0 10 20 30 40 Fossil fuel cost (2020) below this point, costs can be less than fossil fuels Figure 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) for 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 percentiles 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). In 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 of battery storage capacity; for the others, costs are LCOE, which includes installation, capital, operations, and maintenance costs per MWh of electricity produced.
The top panel (a) shows global costs per unit of energy (USD per MWh) for 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 percentiles 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). In 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 of 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 LCOE 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 or 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 technologies and alter their deployment. The bottom panel (b) shows cumulative global adoption for each technology, in GW of installed capacity for renewable energy and in 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 reﬂects different 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 technologies were selected as illustrative examples because they have recently shown rapid changes in costs and adoption, and because consistent data are available. Other mitigation 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}
55 Current Status and Trends Section 2 At least 1.8 GtCO2-eq yr–1 of avoided emissions can be accounted for by aggregating separate estimates for the effects of economic and regulatory instruments (medium conﬁdence). Growing numbers of laws and executive orders have impacted global emissions and are estimated to have resulted in 5.9 GtCO2-eq yr–1 of avoided emissions in 2016 (medium conﬁdence). These reductions have only partly offset global emissions growth (high confidence). {WGIII SPM B.1, WGIII SPM B.2.4, WGIII SPM B.3.5, WGIII SPM B.5.1, WGIII SPM B.5.3, WGIII 1.3.2, WGIII 2.2.3} 2.2.3. Adaptation Actions to Date Progress in adaptation planning and implementation has been observed across all sectors and regions, generating multiple beneﬁts (very high conﬁdence). The ambition, scope and progress on adaptation have risen among governments at the local, national and international levels, along with businesses, communities and civil society (high conﬁdence). Various tools, measures and processes are available that can enable, accelerate and sustain adaptation implementation (high conﬁdence). Growing public and political awareness of climate impacts and risks has resulted in at least 170 countries and many cities including adaptation in their climate policies and planning processes (high conﬁdence). Decision support tools and climate services are increasingly being used (very high conﬁdence) and pilot projects and local experiments are being implemented in different sectors (high conﬁdence). {WGII SPM C.1, WGII SPM.C.1.1, WGII TS.D.1.3, WGII TS.D.10} Adaptation to water-related risks and impacts make up the majority (~60%) of all documented83 adaptation (high conﬁdence).
Various tools, measures and processes are available that can enable, accelerate and sustain adaptation implementation (high conﬁdence). Growing public and political awareness of climate impacts and risks has resulted in at least 170 countries and many cities including adaptation in their climate policies and planning processes (high conﬁdence). Decision support tools and climate services are increasingly being used (very high conﬁdence) and pilot projects and local experiments are being implemented in different sectors (high conﬁdence). {WGII SPM C.1, WGII SPM.C.1.1, WGII TS.D.1.3, WGII TS.D.10} Adaptation to water-related risks and impacts make up the majority (~60%) of all documented83 adaptation (high conﬁdence). A large number of these adaptation responses are in the agriculture sector and these include on-farm water management, water storage, soil moisture conservation, and irrigation. Other adaptations in agriculture include cultivar improvements, agroforestry, community-based adaptation and farm and landscape diversiﬁcation among others (high conﬁdence). For inland ﬂooding, combinations of non-structural measures like early warning systems, enhancing natural water retention such as by restoring wetlands and rivers, and land use planning such as no build zones or upstream forest management, can reduce ﬂood risk (medium conﬁdence). Some land-related adaptation actions such as 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 are being undertaken, and can have mitigation co-beneﬁts (high conﬁdence). Adaptation actions that increase the resilience of biodiversity and ecosystem services to climate change include responses like minimising additional stresses or disturbances, reducing fragmentation, increasing natural habitat extent, connectivity and heterogeneity, and protecting small-scale refugia where microclimate conditions can allow species to persist (high conﬁdence).
Some land-related adaptation actions such as 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 are being undertaken, and can have mitigation co-beneﬁts (high conﬁdence). Adaptation actions that increase the resilience of biodiversity and ecosystem services to climate change include responses like minimising additional stresses or disturbances, reducing fragmentation, increasing natural habitat extent, connectivity and heterogeneity, and protecting small-scale refugia where microclimate conditions can allow species to persist (high conﬁdence). Most innovations in urban adaptation have occurred through advances 83 Documented adaptation refers to published literature on adaptation policies, measures and actions that has been implemented and documented in peer reviewed literature, as opposed to adaptation that may have been planned, but not implemented. 84 Effectiveness refers here to the extent to which an adaptation option is anticipated or observed to reduce climate-related risk. 85 See Annex I: Glossary. 86 Irrigation is effective in reducing drought risk and climate impacts in many regions and has several livelihood beneﬁts, but needs appropriate management to avoid potential adverse outcomes, which can include accelerated depletion of groundwater and other water sources and increased soil salinization (medium conﬁdence). 87 EbA is recognised internationally under the Convention on Biological Diversity (CBD14/5). A related concept is Nature-based Solutions (NbS), see Annex I: Glossary. in disaster risk management, social safety nets and green/blue infrastructure (medium conﬁdence). Many adaptation measures that beneﬁt health and well-being are found in other sectors (e.g., food, livelihoods, social protection, water and sanitation, infrastructure) (high conﬁdence).
85 See Annex I: Glossary. 86 Irrigation is effective in reducing drought risk and climate impacts in many regions and has several livelihood beneﬁts, but needs appropriate management to avoid potential adverse outcomes, which can include accelerated depletion of groundwater and other water sources and increased soil salinization (medium conﬁdence). 87 EbA is recognised internationally under the Convention on Biological Diversity (CBD14/5). A related concept is Nature-based Solutions (NbS), see Annex I: Glossary. in disaster risk management, social safety nets and green/blue infrastructure (medium conﬁdence). Many adaptation measures that beneﬁt health and well-being are found in other sectors (e.g., food, livelihoods, social protection, water and sanitation, infrastructure) (high conﬁdence). {WGII SPM C.2.1, WGII SPM C.2.2, WGII TS.D.1.2, WGII TS.D.1.4, WGII TS.D.4.2, WGII TS.D.8.3, WGII 4 ES; SRCCL SPM B.1.1} Adaptation can generate multiple additional beneﬁts such as improving agricultural productivity, innovation, health and well-being, food security, livelihood, and biodiversity conservation as well as reduction of risks and damages (very high conﬁdence). {WGII SPM C1.1} Globally tracked adaptation ﬁnance has shown an upward trend since AR5, but represents only a small portion of total climate ﬁnance, is uneven and has developed heterogeneously across regions and sectors (high conﬁdence). Adaptation ﬁnance has come predominantly from public sources, largely through grants, concessional and non-concessional instruments (very high conﬁdence). Globally, private-sector ﬁnancing of adaptation from a variety of sources such as commercial ﬁnancial institutions, institutional investors, other private equity, non-ﬁnancial corporations, as well as communities and households has been limited, especially in developing countries (high conﬁdence).
{WGII SPM C1.1} Globally tracked adaptation ﬁnance has shown an upward trend since AR5, but represents only a small portion of total climate ﬁnance, is uneven and has developed heterogeneously across regions and sectors (high conﬁdence). Adaptation ﬁnance has come predominantly from public sources, largely through grants, concessional and non-concessional instruments (very high conﬁdence). Globally, private-sector ﬁnancing of adaptation from a variety of sources such as commercial ﬁnancial institutions, institutional investors, other private equity, non-ﬁnancial corporations, as well as communities and households has been limited, especially in developing countries (high conﬁdence). Public mechanisms and ﬁnance can leverage private sector ﬁnance for adaptation by addressing real and perceived regulatory, cost and market barriers, for example via public-private partnerships (high conﬁdence). Innovations in adaptation and resilience ﬁnance, such as forecast-based/anticipatory ﬁnancing systems and regional risk insurance pools, have been piloted and are growing in scale (high conﬁdence). {WGII SPM C.3.2, WGII SPM C.5.4; WGII TS.D.1.6, WGII Cross-Chapter Box FINANCE; WGIII SPM E.5.4} There are adaptation options which are effective84 in reducing climate risks85 for speciﬁc contexts, sectors and regions and contribute positively to sustainable development and other societal goals. In the agriculture sector, cultivar improvements, on-farm water management and storage, soil moisture conservation, irrigation86, agroforestry, community-based adaptation, and farm and landscape level diversiﬁcation, and sustainable land management approaches, provide multiple beneﬁts and reduce climate risks. Reduction of food loss and waste, and adaptation measures in support of balanced diets contribute to nutrition, health, and biodiversity beneﬁts.
{WGII SPM C.3.2, WGII SPM C.5.4; WGII TS.D.1.6, WGII Cross-Chapter Box FINANCE; WGIII SPM E.5.4} There are adaptation options which are effective84 in reducing climate risks85 for speciﬁc contexts, sectors and regions and contribute positively to sustainable development and other societal goals. In the agriculture sector, cultivar improvements, on-farm water management and storage, soil moisture conservation, irrigation86, agroforestry, community-based adaptation, and farm and landscape level diversiﬁcation, and sustainable land management approaches, provide multiple beneﬁts and reduce climate risks. Reduction of food loss and waste, and adaptation measures in support of balanced diets contribute to nutrition, health, and biodiversity beneﬁts. (high conﬁdence) {WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.2; SRCCL B.2, SRCCL SPM C.2.1} Ecosystem-based Adaptation87 approaches such as urban greening, restoration of wetlands and upstream forest ecosystems reduce a range of climate change risks, including ﬂood risks, urban heat and provide multiple co-beneﬁts. Some land-based adaptation options provide immediate beneﬁts (e.g., conservation of peatlands,
56 Section 2 Section 1 Section 2 wetlands, rangelands, mangroves and forests); while afforestation and reforestation, restoration of high-carbon ecosystems, agroforestry, and the reclamation of degraded soils take more time to deliver measurable results. Signiﬁcant synergies exist between adaptation and mitigation, for example through sustainable land management approaches. Agroecological principles and practices and other approaches that work with natural processes support food security, nutrition, health and well-being, livelihoods and biodiversity, sustainability and ecosystem services. (high conﬁdence) {WGII SPM C.2.1, WGII SPM C.2.2, WGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; SROCC SPM C.2} Combinations of non-structural measures like early warning systems and structural measures like levees have reduced loss of lives in case of inland ﬂooding (medium conﬁdence) and early warning systems along with ﬂood-prooﬁng of buildings have proven to be cost-effective in the context of coastal ﬂooding under current sea level rise (high conﬁdence). Heat Health Action Plans that include early warning and response systems are effective adaptation options for extreme heat (high conﬁdence). 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, and improved early warning systems, surveillance, and vaccine development (very high conﬁdence). Adaptation options such as disaster risk management, early warning systems, climate services and social safety nets have broad applicability across multiple sectors (high conﬁdence).
Heat Health Action Plans that include early warning and response systems are effective adaptation options for extreme heat (high conﬁdence). 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, and improved early warning systems, surveillance, and vaccine development (very high conﬁdence). Adaptation options such as disaster risk management, early warning systems, climate services and social safety nets have broad applicability across multiple sectors (high conﬁdence). {WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.9, WGII SPM C.2.11, WGII SPM C.2.13; SROCC SPM C.3.2} Integrated, multi-sectoral solutions that address social inequities, differentiate responses based on climate risk and cut across systems, increase the feasibility and effectiveness of adaptation in multiple sectors (high conﬁdence). {WGII SPM C.2}
57 Current Status and Trends Section 2 2.3 Current Mitigation and Adaptation Actions and Policies are not Sufﬁcient At the time of the present assessment88 there are gaps between global ambitions and the sum of declared national ambitions. These are further compounded by gaps between declared national ambitions and current implementation for all aspects of climate action. For mitigation, global GHG emissions in 2030 implied by NDCs announced by October 2021 would make it likely that warming will exceed 1.5°C during the 21st century and would make it harder to limit warming below 2°C.89 Despite progress, adaptation gaps90 persist, with many initiatives prioritising short-term risk reduction, hindering transformational adaptation. Hard and soft limits to adaptation are being reached in some sectors and regions, while maladaptation is also increasing and disproportionately affecting vulnerable groups. Systemic barriers such as funding, knowledge, and practice gaps, including lack of climate literacy and data hinders adaptation progress. Insufﬁcient ﬁnancing, especially for adaptation, constraints climate action in particular in developing countries. (high conﬁdence) 88 The timing of various cut-offs for assessment differs by WG report and the aspect assessed. See footnote 1 in Section 1. 89 See CSB.2 for a discussion of scenarios and pathways. 90 See Annex I: Glossary. 2.3.1. The Gap Between Mitigation Policies, Pledges and Pathways that Limit Warming to 1.5°C or Below 2°C Global GHG emissions in 2030 associated with the implementation of NDCs announced prior to COP2691 would make it likely that warming will exceed 1.5°C during the 21st century and would make it harder to limit warming below 2°C – if no additional commitments are made or actions taken (Figure 2.5, Table 2.2).
(high conﬁdence) 88 The timing of various cut-offs for assessment differs by WG report and the aspect assessed. See footnote 1 in Section 1. 89 See CSB.2 for a discussion of scenarios and pathways. 90 See Annex I: Glossary. 2.3.1. The Gap Between Mitigation Policies, Pledges and Pathways that Limit Warming to 1.5°C or Below 2°C Global GHG emissions in 2030 associated with the implementation of NDCs announced prior to COP2691 would make it likely that warming will exceed 1.5°C during the 21st century and would make it harder to limit warming below 2°C – if no additional commitments are made or actions taken (Figure 2.5, Table 2.2). A substantial ‘emissions gap’ exists as global GHG emissions in 2030 associated with the implementation of NDCs announced prior to COP26 would be similar to or only slightly below 2019 emission levels and higher than those associated with modelled mitigation pathways that limit warming to 1.5°C (>50%) with no or limited overshoot or to 2°C (>67%), assuming immediate action, which implies deep, rapid, and sustained global GHG emission reductions this decade (high conﬁdence) (Table 2.2, Table 3.1, 4.1).92 The magnitude of the emissions gap depends on the global warming level considered and whether only unconditional or also conditional elements of NDCs93 are considered (high conﬁdence) (Table 2.2). Modelled pathways that are consistent with NDCs announced prior to COP26 until 2030 and assume no increase in ambition thereafter have higher emissions, leading 88 The timing of various cut-offs for assessment differs by WG report and the aspect assessed. See footnote 58 in Section 1. 89 See CSB.2 for a discussion of scenarios and pathways. 90 See Annex I: Glossary.
Modelled pathways that are consistent with NDCs announced prior to COP26 until 2030 and assume no increase in ambition thereafter have higher emissions, leading 88 The timing of various cut-offs for assessment differs by WG report and the aspect assessed. See footnote 58 in Section 1. 89 See CSB.2 for a discussion of scenarios and pathways. 90 See Annex I: Glossary. 91 NDCs announced prior to COP26 refer to the most recent NDCs submitted to the UNFCCC up to the literature cut-off date of the WGIII report, 11 October 2021, and revised NDCs announced by China, Japan and the Republic of Korea prior to October 2021 but only submitted thereafter. 25 NDC updates were submitted between 12 October 2021 and the start of COP26. {WGIII SPM footnote 24} 92 Immediate action in modelled global pathways refers to the adoption between 2020 and at latest before 2025 of climate policies intended to limit global warming to a given level. Modelled pathways that limit warming to 2°C (>67%) based on immediate action are summarised in category C3a in Table 3.1. All assessed modelled global pathways that limit warming to 1.5°C (>50%) with no or limited overshoot assume immediate action as deﬁned here (Category C1 in Table 3.1). {WGIII SPM footnote 26} 93 In this report, ‘unconditional’ elements of NDCs refer to mitigation efforts put forward without any conditions. ‘Conditional’ elements refer to mitigation efforts that are contingent on international cooperation, for example bilateral and multilateral agreements, ﬁnancing or monetary and/or technological transfers. This terminology is used in the literature and the UNFCCC’s NDC Synthesis Reports, not by the Paris Agreement. {WGIII SPM footnote 27} 94 Implementation gaps refer to how far currently enacted policies and actions fall short of reaching the pledges. The policy cut-off date in studies used to project GHG emissions of ‘policies implemented by the end of 2020’ varies between July 2019 and November 2020.
{WGIII SPM footnote 26} 93 In this report, ‘unconditional’ elements of NDCs refer to mitigation efforts put forward without any conditions. ‘Conditional’ elements refer to mitigation efforts that are contingent on international cooperation, for example bilateral and multilateral agreements, ﬁnancing or monetary and/or technological transfers. This terminology is used in the literature and the UNFCCC’s NDC Synthesis Reports, not by the Paris Agreement. {WGIII SPM footnote 27} 94 Implementation gaps refer to how far currently enacted policies and actions fall short of reaching the pledges. The policy cut-off date in studies used to project GHG emissions of ‘policies implemented by the end of 2020’ varies between July 2019 and November 2020. {WGIII Table 4.2, WGIII SPM footnote 25} to a median global warming of 2.8 [2.1 to 3.4]°C by 2100 (medium conﬁdence). If the ‘emission gap’ is not reduced, global GHG emissions in 2030 consistent with NDCs announced prior to COP26 make it likely that warming will exceed 1.5°C during the 21st century, while limiting warming to 2°C (>67%) would imply an unprecedented acceleration of mitigation efforts during 2030–2050 (medium conﬁdence) (see Section 4.1, Cross-Section Box.2). {WGIII SPM B.6, WGIII SPM B.6.1, WGIII SPM B.6.3, WGIII SPM B.6.4, WGIII SPM C.1.1} Policies implemented by the end of 2020 are projected to result in higher global GHG emissions in 2030 than those implied by NDCs, indicating an ‘implementation gap94’ (high conﬁdence) (Table 2.2, Figure 2.5). Projected global emissions implied by policies implemented by the end of 2020 are 57 (52–60) GtCO2-eq in 2030 (Table 2.2).
{WGIII SPM B.6, WGIII SPM B.6.1, WGIII SPM B.6.3, WGIII SPM B.6.4, WGIII SPM C.1.1} Policies implemented by the end of 2020 are projected to result in higher global GHG emissions in 2030 than those implied by NDCs, indicating an ‘implementation gap94’ (high conﬁdence) (Table 2.2, Figure 2.5). Projected global emissions implied by policies implemented by the end of 2020 are 57 (52–60) GtCO2-eq in 2030 (Table 2.2). This points to an implementation gap compared with the NDCs of 4 to 7 GtCO2-eq in 2030 (Table 2.2); without a strengthening of policies, emissions are projected to rise, leading to a median global warming of 2.2°C to 3.5°C (very likely range) by 2100 (medium confidence) (see Section 3.1.1). {WGIII SPM B.6.1, WGIII SPM C.1}
58 Section 2 Section 1 Section 2 Projected cumulative future CO2 emissions over the lifetime of existing fossil fuel infrastructure without additional abatement95 exceed the total cumulative net CO2 emissions in pathways that limit warming to 1.5°C (>50%) with no or limited overshoot. They are approximately equal to total cumulative net CO2 emissions in pathways that limit warming to 2°C with a likelihood of 83%96 (see Figure 3.5). Limiting warming to 2°C (>67%) or lower will result in stranded assets. About 80% of coal, 50% of gas, and 30% of oil reserves cannot be burned and emitted if warming is limited to 2°C. Signiﬁcantly more reserves are expected to remain unburned if warming is limited to 1.5°C. (high conﬁdence) {WGIII SPM B.7, WGIII Box 6.3} 95 Abatement 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} 96 WGI 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} Table 2.2 Projected global emissions in 2030 associated with policies implemented by the end of 2020 and NDCs announced prior to COP26, and associated emissions gaps. Emissions projections for 2030 and gross differences in emissions are based on emissions of 52–56 GtCO2-eq yr–1 in 2019 as assumed in underlying model studies97. (medium conﬁdence) {WGIII Table SPM.1} (Table 3.1, Cross-Section Box.2) 95 Abatement here refers to human interventions that reduce the amount of GHGs that are released from fossil fuel infrastructure to the atmosphere.
{WGI Table SPM.2} Table 2.2 Projected global emissions in 2030 associated with policies implemented by the end of 2020 and NDCs announced prior to COP26, and associated emissions gaps. Emissions projections for 2030 and gross differences in emissions are based on emissions of 52–56 GtCO2-eq yr–1 in 2019 as assumed in underlying model studies97. (medium conﬁdence) {WGIII Table SPM.1} (Table 3.1, Cross-Section Box.2) 95 Abatement 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} 96 WGI 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} 97 The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO2-eq] is within the uncertainty ranges of 2019 emissions assessed in WGIII Chapter 2 [53–66 GtCO2-eq].
(medium conﬁdence) {WGIII Table SPM.1} (Table 3.1, Cross-Section Box.2) 95 Abatement 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} 96 WGI 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} 97 The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO2-eq] is within the uncertainty ranges of 2019 emissions assessed in WGIII Chapter 2 [53–66 GtCO2-eq]. Emission and implementation gaps associated with projected global emissions in 2030 under Nationally Determined Contributions (NDCs) and implemented policies Implied by policies implemented by the end of 2020 (GtCO2-eq/yr) Implied by Nationally Determined Contributions (NDCs) announced prior to COP26 Unconditional elements (GtCO2-eq/yr) Including conditional elements (GtCO2-eq/yr) Median projected global emissions (min–max)* Implementation gap between implemented policies and NDCs (median) Emissions gap between NDCs and pathways that limit warming to 2°C (>67%) with immediate action Emissions gap between NDCs and pathways that limit warming to 1.5°C (>50%) with no or limited overshoot with immediate action 57 [52–60] – – – 4 7 53 [50–57] 50 [47–55] 10–16 6–14 19–26 16–23 *Emissions projections for 2030 and gross differences in emissions are based on emissions of 52–56 GtCO2-eq/yr in 2019 as assumed in underlying model studies. (medium conﬁdence)
59 Current Status and Trends Section 2 a) Global GHG emissions b) 2030 10 20 30 0 40 50 60 70 10 20 30 0 40 50 60 70 GHG emissions (GtCO2-eq/yr) 2020 2025 2015 2010 2030 2035 2040 2045 2050 Limit warming to 2ºC (>67%) or 1.5 (>50%) after high overshoot with NDCs until 2030 Trend from implemented policies 2019 Limit warming to 1.5ºC (>50%) with no or limited overshoot Limit warming to 2ºC (>67%) to be on-track to limit warming to 1.5°C, we need much more reduction by 2030 -4% +5% -26% -43% Projected global GHG emissions from NDCs announced prior to COP26 would make it likely that warming will exceed 1.5°C and also make it harder after 2030 to limit warming to below 2°C Past GHG emissions and uncertainty for 2015 and 2019 (dot indicates the median) Past GHG emissions and uncertainty for 2015 and 2019 (dot indicates the median) Figure 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). Panel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways: - 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 ambition levels beyond 2030 (29 scenarios across categories C5–C7, WGIII Table SPM.2).
Panel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways: - 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 ambition levels beyond 2030 (29 scenarios across categories C5–C7, WGIII Table SPM.2). - Limit to 2°C (>67%) or return warming to 1.5°C (>50%) after a high overshoot, NDCs until 2030: Pathways with GHG emissions until 2030 associated with the implementation of NDCs announced prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2°C (C3b, WGIII Table SPM.2) or to return warming to 1.5°C with a probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, WGIII Table SPM.2). - Limit to 2°C (>67%) with immediate action: Pathways that limit warming to 2°C (>67%) with immediate action after 2020 (C3a, WGIII Table SPM.2). - Limit to 1.5°C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5°C with no or limited overshoot (C1, WGIII Table SPM.2 C1). All 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 black 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 from WGIII Chapter 4.2 (Tables 4.2 and 4.3; median and full range). GHG emissions are CO2-equivalent using GWP100 from AR6 WGI.
- Limit to 1.5°C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5°C with no or limited overshoot (C1, WGIII Table SPM.2 C1). All 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 black 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 from 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, Table 4.3, Cross-Chapter Box 4 in Chapter 4} (Table 3.1, Cross-Section Box.2)
60 Section 2 Section 1 Section 2 Cross-Section Box.1: Understanding Net Zero CO2 and Net Zero GHG Emissions Limiting human-caused global warming to a speciﬁc level requires limiting cumulative CO2 emissions, reaching net zero or net negative CO2 emissions, along with strong reductions in other GHG emissions (see 3.3.2). Future additional warming will depend on future emissions, with 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} Reaching net zero CO2 emissions is different from reaching net zero GHG emissions. The timing of net zero for a basket of GHGs depends on the emissions metric, such as global warming potential over a 100-year period, chosen to convert non-CO2 emissions into CO2-equivalent (high conﬁdence). However, for a given emissions pathway, the physical climate response is independent of the metric chosen (high conﬁdence). {WGI SPM D.1.8; WGIII Box TS.6, WGIII Cross-Chapter Box 2} Achieving global net zero GHG emissions requires all remaining CO2 and metric-weighted98 non-CO2 GHG emissions to be counterbalanced by durably stored CO2 removals (high conﬁdence). Some non-CO2 emissions, such as CH4 and N2O from agriculture, cannot be fully eliminated using existing and anticipated technical measures. {WGIII SPM C.2.4, WGIII SPM C.11.4, WGIII Cross-Chapter Box 3} Global net zero CO2 or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that others reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions vary by sector and region.
{WGI SPM D.1.8; WGIII Box TS.6, WGIII Cross-Chapter Box 2} Achieving global net zero GHG emissions requires all remaining CO2 and metric-weighted98 non-CO2 GHG emissions to be counterbalanced by durably stored CO2 removals (high conﬁdence). Some non-CO2 emissions, such as CH4 and N2O from agriculture, cannot be fully eliminated using existing and anticipated technical measures. {WGIII SPM C.2.4, WGIII SPM C.11.4, WGIII Cross-Chapter Box 3} Global net zero CO2 or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that others reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions vary by sector and region. If and when net zero emissions for a given sector or region are reached depends on multiple factors, including the potential to reduce GHG emissions and undertake carbon dioxide removal, the associated costs, and the availability of policy mechanisms to balance emissions and removals between sectors and countries. (high conﬁdence) {WGIII Box TS.6, WGIII Cross-Chapter Box 3} The adoption and implementation of net zero emission targets by countries and regions also depend on equity and capacity considerations (high conﬁdence). The formulation of net zero pathways by countries will beneﬁt from clarity on scope, plans-of-action, and fairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global modelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the country-level timing of net zero (high conﬁdence). The Paris Agreement also recognizes that peaking of emissions will occur later in developing countries than developed countries (Article 4.1).
(high conﬁdence) {WGIII Box TS.6, WGIII Cross-Chapter Box 3} The adoption and implementation of net zero emission targets by countries and regions also depend on equity and capacity considerations (high conﬁdence). The formulation of net zero pathways by countries will beneﬁt from clarity on scope, plans-of-action, and fairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global modelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the country-level timing of net zero (high conﬁdence). The Paris Agreement also recognizes that peaking of emissions will occur later in developing countries than developed countries (Article 4.1). {WGIII Box TS.6, WGIII Cross-Chapter Box 3, WGIII 14.3} More 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 on sectoral aspects of net zero in Section 4.1. 98 See footnote 12 above.
61 Current Status and Trends Section 2 Many countries have signalled an intention to achieve net zero GHG or net zero CO2 emissions by around mid-century (Cross-Section Box.1). More than 100 countries have either adopted, announced or are discussing net zero GHG or net zero CO2 emissions commitments, covering more than two-thirds of global GHG emissions. A growing number of cities are setting climate targets, including net zero GHG targets. Many companies and institutions have also announced net zero emissions targets in recent years. The various net zero emission pledges differ across countries in terms of scope and speciﬁcity, and limited policies are to date in place to deliver on them. {WGIII SPM C.6.4, WGIII TS.4.1, WGIII Table TS.1, WGIII 13.9, WGIII 14.3, WGIII 14.5} All mitigation strategies face implementation challenges, including technology risks, scaling, and costs (high conﬁdence). Almost all mitigation options also face institutional barriers that need to be addressed to enable their application at scale (medium conﬁdence). Current development pathways may create behavioural, spatial, economic and social barriers to accelerated mitigation at all scales (high conﬁdence). Choices made by policymakers, citizens, the private sector and other stakeholders inﬂuence societies’ development pathways (high conﬁdence). Structural factors of national circumstances and capabilities (e.g., economic and natural endowments, political systems and cultural factors and gender considerations) affect the breadth and depth of climate governance (medium conﬁdence). The extent to which civil society actors, political actors, businesses, youth, labour, media, Indigenous Peoples, and local communities are engaged inﬂuences political support for climate change mitigation and eventual policy outcomes (medium conﬁdence).
Current development pathways may create behavioural, spatial, economic and social barriers to accelerated mitigation at all scales (high conﬁdence). Choices made by policymakers, citizens, the private sector and other stakeholders inﬂuence societies’ development pathways (high conﬁdence). Structural factors of national circumstances and capabilities (e.g., economic and natural endowments, political systems and cultural factors and gender considerations) affect the breadth and depth of climate governance (medium conﬁdence). The extent to which civil society actors, political actors, businesses, youth, labour, media, Indigenous Peoples, and local communities are engaged inﬂuences political support for climate change mitigation and eventual policy outcomes (medium conﬁdence). {WGIII SPM C.3.6, WGIII SPM E.1.1, WGIII SPM E.2.1, WGIII SPM E.3.3} The 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 (medium conﬁdence). In many countries, especially those with limited institutional capacity, several adverse side-effects have been observed as a result of diffusion of low-emission technology, e.g., low-value employment, and dependency on foreign knowledge and suppliers (medium conﬁdence). Low-emission innovation along with strengthened enabling conditions can reinforce development beneﬁts, which can, in turn, create feedbacks towards greater public support for policy (medium conﬁdence). Persistent and region-speciﬁc barriers also continue to hamper the economic and political feasibility of deploying AFOLU mitigation options (medium conﬁdence). 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 (high conﬁdence).
Low-emission innovation along with strengthened enabling conditions can reinforce development beneﬁts, which can, in turn, create feedbacks towards greater public support for policy (medium conﬁdence). Persistent and region-speciﬁc barriers also continue to hamper the economic and political feasibility of deploying AFOLU mitigation options (medium conﬁdence). 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 (high conﬁdence). {WGIII SPM B.4.2, WGIII SPM C.9.1, WGIII SPM C.9.3} 99 See Annex I: Glossary. 100 Adaptation limit: The point at which an actor’s objectives (or system needs) cannot be secured from intolerable risks through adaptive actions. Hard adaptation limit - No adaptive actions are possible to avoid intolerable risks. Soft adaptation limit - Options are currently not available to avoid intolerable risks through adaptive action. 101 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 to climate change, more inequitable outcomes, or diminished welfare, now or in the future. Most often, maladaptation is an unintended consequence. See Annex I: Glossary. 2.3.2. Adaptation Gaps and Barriers Despite progress, adaptation gaps exist between current levels of adaptation and levels needed to respond to impacts and reduce climate risks (high conﬁdence). While progress in adaptation implementation is observed across all sectors and regions (very high conﬁdence), many adaptation initiatives prioritise immediate and near-term climate risk reduction, e.g., through hard ﬂood protection, which reduces the opportunity for transformational adaptation99 (high conﬁdence).
101 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 to climate change, more inequitable outcomes, or diminished welfare, now or in the future. Most often, maladaptation is an unintended consequence. See Annex I: Glossary. 2.3.2. Adaptation Gaps and Barriers Despite progress, adaptation gaps exist between current levels of adaptation and levels needed to respond to impacts and reduce climate risks (high conﬁdence). While progress in adaptation implementation is observed across all sectors and regions (very high conﬁdence), many adaptation initiatives prioritise immediate and near-term climate risk reduction, e.g., through hard ﬂood protection, which reduces the opportunity for transformational adaptation99 (high conﬁdence). Most observed adaptation is fragmented, small in scale, incremental, sector-speciﬁc, and focused more on planning rather than implementation (high conﬁdence). Further, observed adaptation is unequally distributed across regions and the largest adaptation gaps exist among lower population income groups (high conﬁdence). In the urban context, the largest adaptation gaps exist in projects that manage complex risks, for example in the food–energy–water–health nexus or the inter-relationships of air quality and climate risk (high conﬁdence). Many funding, knowledge and practice gaps remain for effective implementation, monitoring and evaluation and current adaptation efforts are not expected to meet existing goals (high conﬁdence). At current rates of adaptation planning and implementation the adaptation gap will continue to grow (high conﬁdence). {WGII SPM C.1, WGII SPM C.1.2, WGII SPM C.4.1, WGII TS.D.1.3, WGII TS.D.1.4} Soft and hard adaptation limits100 have already been reached in some sectors and regions, in spite of adaptation having buffered some climate impacts (high conﬁdence).
Many funding, knowledge and practice gaps remain for effective implementation, monitoring and evaluation and current adaptation efforts are not expected to meet existing goals (high conﬁdence). At current rates of adaptation planning and implementation the adaptation gap will continue to grow (high conﬁdence). {WGII SPM C.1, WGII SPM C.1.2, WGII SPM C.4.1, WGII TS.D.1.3, WGII TS.D.1.4} Soft and hard adaptation limits100 have already been reached in some sectors and regions, in spite of adaptation having buffered some climate impacts (high conﬁdence). Ecosystems already reaching hard adaptation limits include some warm water coral reefs, some coastal wetlands, some rainforests, and some polar and mountain ecosystems (high conﬁdence). Individuals and households in low lying coastal areas in Australasia and Small Islands and smallholder farmers in Central and South America, Africa, Europe and Asia have reached soft limits (medium conﬁdence), resulting from ﬁnancial, governance, institutional and policy constraints and can be overcome by addressing these constraints (high conﬁdence). Transitioning from incremental to transformational adaptation can help overcome soft adaptation limits (high conﬁdence). {WGII SPM C.3, WGII SPM C.3.1, WGII SPM C.3.2, WGII SPM C.3.3, WGII SPM.C.3.4, WGII 16 ES} Adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits. 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. (high conﬁdence) {WGII SPM.C.3.5} There is increased evidence of maladaptation101 in various sectors and regions.
Transitioning from incremental to transformational adaptation can help overcome soft adaptation limits (high conﬁdence). {WGII SPM C.3, WGII SPM C.3.1, WGII SPM C.3.2, WGII SPM C.3.3, WGII SPM.C.3.4, WGII 16 ES} Adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits. 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. (high conﬁdence) {WGII SPM.C.3.5} There is increased evidence of maladaptation101 in various sectors and regions. Examples of maladaptation are observed in urban areas (e.g., new urban infrastructure that cannot be adjusted easily or affordably), agriculture (e.g., using high-cost irrigation in areas projected to have more intense drought conditions), ecosystems (e.g. ﬁre suppression in naturally
62 Section 2 Section 1 Section 2 ﬁre-adapted ecosystems, or hard defences against ﬂooding) and human settlements (e.g. stranded assets and vulnerable communities that cannot afford to shift away or adapt and require an increase in social safety nets). Maladaptation especially affects marginalised and vulnerable groups adversely (e.g., Indigenous Peoples, ethnic minorities, low-income households, people living in informal settlements), reinforcing and entrenching existing inequities. Maladaptation can be avoided by ﬂexible, multi-sectoral, inclusive and long-term planning and implementation of adaptation actions with beneﬁts to many sectors and systems. (high conﬁdence) {WGII SPM C.4, WGII SPM C.4.3, WGII TS.D.3.1} Systemic barriers constrain the implementation of adaptation options in vulnerable sectors, regions and social groups (high conﬁdence). Key barriers include limited resources, lack of private-sector and civic engagement, insufﬁcient mobilisation of ﬁnance, lack of political commitment, limited research and/or slow and low uptake of adaptation science and a low sense of urgency. Inequity and poverty also constrain adaptation, leading to soft limits and resulting in disproportionate exposure and impacts for most vulnerable groups (high conﬁdence). The largest adaptation gaps exist among lower income population groups (high conﬁdence). As adaptation options often have long implementation times, long-term planning and accelerated implementation, particularly in this decade, is important to close adaptation gaps, recognising that constraints remain for some regions (high conﬁdence). Prioritisation of options and transitions from incremental to transformational adaptation are limited due to vested interests, economic lock-ins, institutional path dependencies and prevalent practices, cultures, norms and belief systems (high conﬁdence).
Inequity and poverty also constrain adaptation, leading to soft limits and resulting in disproportionate exposure and impacts for most vulnerable groups (high conﬁdence). The largest adaptation gaps exist among lower income population groups (high conﬁdence). As adaptation options often have long implementation times, long-term planning and accelerated implementation, particularly in this decade, is important to close adaptation gaps, recognising that constraints remain for some regions (high conﬁdence). Prioritisation of options and transitions from incremental to transformational adaptation are limited due to vested interests, economic lock-ins, institutional path dependencies and prevalent practices, cultures, norms and belief systems (high conﬁdence). Many funding, knowledge and practice gaps remain for effective implementation, monitoring and evaluation of adaptation (high conﬁdence), including, lack of climate literacy at all levels and limited availability of data and information (medium conﬁdence); for example for Africa, severe climate data constraints and inequities in research funding and leadership reduce adaptive capacity (very high conﬁdence). {WGII SPM C.1.2, WGII SPM C.3.1, WGII TS.D.1.3, WGII TS.D.1.5, WGII TS.D.2.4} 2.3.3. Lack of Finance as a Barrier to Climate Action Insufﬁcient ﬁnancing, and a lack of political frameworks and incentives for ﬁnance, are key causes of the implementation gaps for both mitigation and adaptation (high conﬁdence). Financial ﬂows remained heavily focused on mitigation, are uneven, and have developed heterogeneously across regions and sectors (high conﬁdence). In 2018, public and publicly mobilised private climate ﬁnance ﬂows from developed to developing countries were below the collective goal under the UNFCCC and Paris Agreement to mobilise USD 100 billion per year by 2020 in the context of meaningful mitigation action and transparency on implementation (medium conﬁdence).

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Dataset Card for GTimothee/my-knowledge-base

This repository was created using the giskard library, an open-source Python framework designed to evaluate and test AI systems.

This dataset comprises a giskard's KnowledgeBase containing 310 documents. If embeddings were generated before the saving process, they are included and will be automatically loaded into a vector store when required.

Usage

You can load this knowledge base using the following code:

from giskard.rag import KnowledgeBase
kb = KnowledgeBase.load_from_hf_hub("GTimothee/my-knowledge-base")

Configuration

The configuration details for this Knowledge Base (can also be found in the config.json file):

{
    "columns": null,
    "chunk_size": 2048,
    "min_topic_size": 8,
    "language": "en",
    "seed": null,
    "embedding_model": null
}

Built with

Giskard helps identify performance, bias, and security issues in AI applications, supporting both LLM-based systems like RAG agents and traditional machine learning models for tabular data.

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