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IPCC AR6 SYRSYNTHESIS REPORTOF THE IPCC SIXTH ASSESSMENT REPORT (AR6)Longer Report
Core Writing Team: Hoesung Lee (Chair), Katherine Calvin (USA), Dipak Dasgupta (India/USA), Gerhard
Krinner (France/Germany), Aditi Mukherji (India), Peter Thorne (Ireland/United Kingdom), Christopher
Trisos (South Africa), José Romero (Switzerland), Paulina Aldunce (Chile), Ko Barrett (USA), Gabriel Blanco(Argentina), William W. L. Cheung (Canada), Sarah L. Connors (France/United Kingdom), Fatima Denton(The Gambia), Aïda Diongue-Niang (Senegal), David Dodman (Jamaica/United Kingdom/Netherlands),
Matthias Garschagen (Germany), Oliver Geden (Germany), Bronwyn Hayward (New Zealand), Christopher
Jones (United Kingdom), Frank Jotzo (Australia), Thelma Krug (Brazil), Rodel Lasco (Philippines), June-Yi
Lee (Republic of Korea), Valérie Masson-Delmotte (France), Malte Meinshausen (Australia/Germany), Katja
Mintenbeck (Germany), Abdalah Mokssit (Morocco), Friederike E. L. Otto (United Kingdom/Germany),
Minal Pathak (India), Anna Pirani (Italy), Elvira Poloczanska (UK/Australia), Hans-Otto Pörtner (Germany),
Aromar Revi (India), Debra C. Roberts (South Africa), Joyashree Roy (India/Thailand), Alex C. Ruane (USA),
Jim Skea (United Kingdom), Priyadarshi R. Shukla (India), Raphael Slade (United Kingdom), Aimée Slangen(The Netherlands), Youba Sokona (Mali), Anna A. Sörensson (Argentina), Melinda Tignor (USA/Germany),
Detlef van Vuuren (The Netherlands), Yi-Ming Wei (China), Harald Winkler (South Africa), Panmao Zhai
(China), Zinta Zommers (Latvia)
Extended Writing Team: Jean-Charles Hourcade (France), Francis X. Johnson (Thailand/Sweden), Shonali
Pachauri (Austria/India), Nicholas P. Simpson (South Africa/Zimbabwe), Chandni Singh (India), Adelle
Thomas (Bahamas), Edmond Totin (Benin)
Contributing Authors: Andrés Alegría (Germany/Honduras), Kyle Armour (USA), Birgit Bednar-Friedl(Austria), Kornelis Blok (The Netherlands) Guéladio Cissé (Switzerland/Mauritania/France), Frank Dentener(EU/Netherlands), Siri Eriksen (Norway), Erich Fischer (Switzerland), Gregory Garner (USA), Céline
Guivarch (France), Marjolijn Haasnoot (The Netherlands), Gerrit Hansen (Germany), Matthias Hauser(Switzerland), Ed Hawkins (UK), Tim Hermans (The Netherlands), Robert Kopp (USA), Noëmie LeprinceRinguet (France), Debora Ley (Mexico/Guatemala), Jared Lewis (Australia/New Zealand), Chloé Ludden(Germany/France), Zebedee Nicholls (Australia), Leila Niamir (Iran/The Netherlands/Austria), Shreya Some
(India/Thailand), Sophie Szopa (France), Blair Trewin (Australia), Kaj-Ivar van der Wijst (The Netherlands),
Gundula Winter (The Netherlands/Germany), Maximilian Witting (Germany)
Review Editors: Paola Arias (Colombia), Mercedes Bustamante (Brazil), Ismail Elgizouli (Sudan), Gregory
Flato (Canada), Mark Howden (Australia), Carlos Méndez (Venezuela), Joy Pereira (Malaysia), Ramón PichsMadruga (Cuba), Steven K Rose (USA), Yamina Saheb (Algeria/France), Roberto Sánchez (Mexico), Diana
Ürge-Vorsatz (Hungary), Cunde Xiao (China), Noureddine Yassaa (Algeria)
Scientific Steering Committee: Hoesung Lee (Chair, IPCC), Amjad Abdulla (Maldives), Edvin Aldrian(Indonesia), Ko Barrett (United States of America), Eduardo Calvo (Peru), Carlo Carraro (Italy), Fatima
Driouech (Morocco), Andreas Fischlin (Switzerland), Jan Fuglestvedt (Norway), Diriba Korecha Dadi
(Ethiopia), Thelma Krug (Brazil), Nagmeldin G.E. Mahmoud (Sudan), Valérie Masson-Delmotte (France),
Carlos Méndez (Venezuela), Joy Jacqueline Pereira (Malaysia), Ramón Pichs-Madruga (Cuba), Hans-Otto
Pörtner (Germany), Andy Reisinger (New Zealand), Debra Roberts (South Africa), Sergey Semenov (RussianFederation), Priyadarshi Shukla (India), Jim Skea (United Kingdom), Youba Sokona (Mali), Kiyoto Tanabe(Japan), Muhammad IrfanTariq (Pakistan), Diana Ürge-Vorsatz (Hungary), Carolina Vera (Argentina), Pius
Yanda (United Republic of Tanzania), Noureddine Yassaa (Algeria), Taha M. Zatari (Saudi Arabia), Panmao
Zhai (China)
Visual Conception and Information Design: Arlene Birt (USA), Meeyoung Ha (Republic of Korea)

Notes: SFs Compiled Version
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Table of Contents
Section 1: Introduction

4

Section 2: Current Status and Trends

6

2.1

Observed Changes, Impacts and Attribution

6

2.1.1

Observed Warming and its Causes

6

2.1.2

Observed Climate System Changes and Impacts to Date

11

2.2

Responses Undertaken to Date

18

2.2.1

Global Policy Setting

18

2.2.2

Mitigation Actions to Date

19

2.2.3

Adaptation Actions to Date

21

2.3

Current Mitigation and Adaptation Actions and Policies are not Sufficient

23

2.3.1
The Gap Between Mitigation Policies, Pledges and Pathways that Limit Warming to 1.5 or
Below 2°C
23
Cross-Section Box.1: Understanding Net Zero CO2 and Net Zero GHG Emissions

26

2.3.2

Adaptation Gaps and Barriers

27

2.3.3

Lack of Finance as a Barrier to Climate Action

28

Cross-Section Box.2: Scenarios, Global Warming Levels, and Risks

29

Section 3: Long-Term Climate and Development Futures
3.1

33

Long-Term Climate Change, Impacts and Related Risks

33

3.1.1

Long-term Climate Change

33

3.1.2

Impacts and Related Risks

36

3.1.3

The Likelihood and Risks of Abrupt and Irreversible Change

42

3.2

Long-term Adaptation Options and Limits

43

3.3

Mitigation Pathways

46

3.3.1

Remaining Carbon Budgets

46

3.3.2

Net Zero Emissions: Timing and Implications

50

3.3.3

Sectoral Contributions to Mitigation

51

3.3.4

Overshoot Pathways: Increased Risks and Other Implications

53

3.4

Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development

53

3.4.1

Synergies and trade-offs, costs and benefits

53

3.4.2

Advancing Integrated Climate Action for Sustainable Development

55

Section 4: Near-Term Responses in a Changing Climate

56

4.1

The Timing and Urgency of Climate Action

56

4.2

Benefits of Strengthening Near-Term Action

59

4.3

Near-Term Risks

62

4.4

Equity and Inclusion in Climate Change Action

66

4.5

Near-Term Mitigation and Adaptation Actions

68

4.5.1

Energy Systems

70

4.5.2

Industry

71

4.5.3

Cities, Settlements and Infrastructure

72

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4.5.4

Land, Ocean, Food, and Water

73

4.5.5

Health and Nutrition

74

4.5.6

Society, Livelihoods, and Economies

74

4.6

Co-Benefits of Adaptation and Mitigation for Sustainable Development Goals

75

4.7

Governance and Policy for Near-Term Climate Change Action

78

4.8

Strengthening the Response: Finance, International Cooperation and Technology

80

4.8.1

Finance for Mitigation and Adaptation Actions

80

4.8.2

International Cooperation and Coordination

82

4.8.3

Technology Innovation, Adoption, Diffusion and Transfer

83

Integration of Near-Term Actions Across Sectors and Systems

84

4.9

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IPCC AR6 SYRSection 1: Introduction
1. Introduction
This Synthesis Report (SYR) of the IPCC Sixth Assessment Report (AR6) summarises the state of knowledgeof 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 theoutcomes 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 reports1 and the three AR6 Special
Reports2. It recognizes the interdependence of climate, ecosystems and biodiversity, and human societies; thevalue 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 analyticalframeworks, including those from the physical and social sciences, this report identifies opportunities fortransformative action which are effective, feasible, just and equitable using concepts of systems transitions andresilient development pathways3. Different regional classification schemes4 are used for physical, social andeconomic 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 futures. It considers long-term characteristics, impacts, risks
and costs in adaptation and mitigation pathways in the context of sustainable development. Section 4, ‘NearTerm 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 anassessed level of confidence using the IPCC calibrated language5. The scientific findings are drawn from theunderlying 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

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.
2 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 responseto 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, andgreenhouse 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.
3 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.
4 Depending on the climate information context, geographical regions in AR6 may refer to larger areas, such as sub-continents andoceanic 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 {1.4.5, 10.1, 11.9, 12.1–12.4, Atlas.1.3.3–1.3.4}. WGIII allocates countries
to geographical regions, based on the UN Statistics Division Classification {Annex II, WG III}.
5 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using fivequalifiers: 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%; andexceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%; more likely than not >50–100%; 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.
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IPCC AR6 SYRFigure 1.1: The Synthesis Report figures key.

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IPCC AR6 SYRSection 2: Current Status and Trends
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 historicaland 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 damages6 to nature and people (high confidence). Vulnerable communities who have historicallycontributed the least to current climate change are disproportionately affected (high confidence).

2.1.1

Observed Warming and its Causes

Global surface temperature was around 1.1°C above 1850–1900 in 2011–2020 (1.09°C [0.95°C–
1.20°C])7, with larger increases over land (1.59 [1.34 to 1.83]°C) than over the ocean (0.88°C [0.68°C–
1.01°C])8. 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 overat least the last 2000 years (high confidence). The likely range of total human-caused global surface
temperature increase from 1850–1900 to 2010–20199 is 0.8°C to 1.3°C, with a best estimate of 1.07°C. It is
likely that well-mixed GHGs10 contributed a warming of 1.0°C–2.0°C, and other human drivers (principally
aerosols) contributed a cooling of 0.0°C–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, WGISPM 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 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 ppb11. 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 thatcurrent 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
6

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)
7 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}
8 For 1850–1900 to 2013–2022 the updated calculations are 1.15°C [1.00°C–1.25°C] for global surface temperature, 1.65°C [1.36°C–
1.90°C] for land temperatures and 0.93°C [0.73°C–1.04°C] for ocean temperatures above 1850–1900 using the exact same datasets(updated by 2 years) and methods as employed in WGI.
9 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°C [0.88°C–1.21°C]. {WGI SPM footnote 11}
10 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.
11 For 2021 (the most recent year for which final numbers are available) concentrations using the same observational products andmethods as in AR6 WGI are: 415 ppm CO2; 1896 ppb CH4; and 335 ppb N2O. Note that the CO2 is reported here using the WMOCO2-X2007 scale to be consistent with WGI. Operational CO2 reporting has since been updated to use the WMO-CO2-X2019 scale.
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years (very high confidence). The net cooling effect which arises from anthropogenic aerosols peaked in thelate 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}
[START FIGURE 2.1 HERE]

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IPCC AR6 SYRFigure 2.1: The causal chain from emissions to resulting warming of the climate system. Emissions of GHG haveincreased rapidly over recent decades (panel (a)). Global net anthropogenic GHG emissions include CO2 from fossil fuelcombustion and industrial processes (CO2-FFI) (dark green); net CO2 from land use, land-use change and forestry (CO2LULUCF) (green); CH4; N2O; and fluorinated gases (HFCs, PFCs, SF6, NF3) (light blue). These emissions have led toincreases in the atmospheric concentrations of several GHGs including the three major well-mixed GHGs CO2, CH4 andN2O (panel (b), annual values). To indicate their relative importance each subpanel’s vertical extent for CO 2, CH4 andN2O is scaled to match the assessed individual direct effect (and, in the case of CH4 indirect effect via atmosphericchemistry 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 multicentury 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 multicentury temperature range [0.5°C–1.5℃] 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 informationfrom 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}[END FIGURE 2.1 HERE]

Average annual GHG emissions12 during 2010–2019 were higher than in any previous decade, but therate of growth between 2010 and 2019 (1.3% yr-1) was lower than that between 2000 and 2009 (2.1% yr1). Historical cumulative net CO2 emissions from 1850 to 2019 were 2400 ±240 GtCO2. Of these, more thanhalf (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}[START FIGURE 2.2 HERE]

12 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)
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IPCC AR6 SYRFigure 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 CO 2 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%
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confidence interval). Panel (b) shows the distribution of regional GHG emissions in tonnes CO 2-eq per capita by regionin 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 CO 2-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 thecontribution 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 asgrouped in Annex II of WGIII. Panel (d) shows population, GDP per person, emission indicators by region in 2019 fortotal GHG per person, and total GHG emissions intensity, together with production-based and consumption-based CO2FFI data, which is assessed in this report up to 2018. Consumption-based emissions are emissions released to theatmosphere in order to generate the goods and services consumed by a certain entity (e.g., region). Emissions frominternational aviation and shipping are not included. {WGIII Figure SPM.2}[END FIGURE 2.2 HERE]

Regional contributions to global human-caused GHG emissions continue to differ widely. Historicalcontributions of CO2 emissions vary substantially across regions in terms of total magnitude, but also in termsof 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 tCO2eq 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 capita13 (excluding CO2LULUCF) 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 GtCO2eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% (8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2eq) from buildings14 (high confidence). Average annual GHG emissions growth between 2010 and 2019
slowed compared to the previous decade in energy supply (from 2.3% to 1.0%) and industry (from 3.4% to1.4%) but remained roughly constant at about 2% yr–1 in the transport sector (high confidence). About half oftotal 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 2010–201915 (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 fromenergy 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 inenergy 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 householdswith 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 sharebetween 2015 and 2020). The drivers of urban GHG emissions16 are complex and include population size,

13

Territorial emissions

14 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}
15 Comprising a gross sink of -12.5 (±3.2) GtCO yr-1 resulting from responses of all land to both anthropogenic environmental change
2and 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}.
16 This estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirectemissions from outside urban areas related to the production of electricity, goods and services consumed in cities. These estimates
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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}

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 andrapid changes in the atmosphere, ocean, cryosphere and biosphere have occurred (Table 2.1). The scaleof 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 driver17 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 certainthat the global upper ocean (0-700m) has warmed since the 1970s and extremely likely that human influenceis 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 [0.15–0.25] 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 and2006, 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 influenceis 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 certainthat 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}
[START TABLE 2.1 HERE]
Table 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate systemcomponents, and their attribution to human influence. The colour coding indicates the assessed confidence in /likelihood18 of the observed change and the human contribution as a driver or main driver (specified in that case) whereavailable (see colour key). Otherwise, explanatory text is provided. {WGI Table TS.1}

include all CO2 and CH4 emission categories except for aviation and marine bunker fuels, land-use change, forestry and agriculture{WGIII SPM footnote 15}
17 ‘Main driver’ means responsible for more than 50% of the change {WGI SPM footnote 12}.
18 Based on scientific understanding, key findings can be formulated as statements of fact or associated with an assessed level ofconfidence indicated using the IPCC calibrated language.
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IPCC AR6 SYR[END TABLE 2.1 HERE]

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) havebecome 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 humancaused climate change is the main driver of these changes. Marine heatwaves have approximately doubled infrequency since the 1980s (high confidence), and human influence has very likely contributed to most of themsince 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), andhuman-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 landevapotranspiration (medium confidence) (Figure 2.3). It is likely that the global proportion of major (Category3–5) 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}

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IPCC AR6 SYR[START FIGURE 2.3 HERE]

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IPCC AR6 SYRFigure 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 toits impacts. Panel (a) The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size in theirapproximate geographical location (see legend for regional acronyms). All assessments are made for each region as awhole 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 anassessment 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
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IPCC AR6 SYRusing global and regional studies. Agricultural and ecological droughts are assessed based on observed and simulatedchanges 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 CO 2-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, forexample, 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 mayoccur with positive impacts in another area or food item (for more details and methodology see WGII SMTS.1). Physicalwater availability includes balance of water available from various sources including ground water, water quality anddemand 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}[END FIGURE 2.3 HERE]
Climate change has caused substantial damages, and increasingly irreversible19 losses, in terrestrial,
freshwater, cryospheric and coastal and open ocean ecosystems (high confidence). The extent andmagnitude of climate change impacts are larger than estimated in previous assessments (highconfidence). Approximately half of the species assessed globally have shifted polewards or, on land, also tohigher elevations (very high confidence). Biological responses including changes in geographic placement andshifting 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 (highconfidence) and mass mortality events on land and in the ocean (very high confidence). Impacts on someecosystems are approaching irreversibility such as the impacts of hydrological changes resulting from theretreat of glaciers, or the changes in some mountain (medium confidence) and Arctic ecosystems driven bypermafrost 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 landdegradation, particularly in low lying coastal areas, river deltas, drylands and in permafrost areas (highconfidence). 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, SRCCLSPM 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}
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 intensityof climatic extremes, thereby hindering efforts to meet Sustainable Development Goals (highconfidence). Although overall agricultural productivity has increased, climate change has slowed this growthin 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 highlatitude 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 forsome fish stocks (high confidence). Ocean warming and ocean acidification have adversely affected foodproduction from shellfish aquaculture and fisheries in some oceanic regions (high confidence). Current levelsof 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 theyear due to a combination of climatic and non-climatic drivers (medium confidence) (Figure 2.3).
Unsustainable agricultural expansion, driven in part by unbalanced diets20, increases ecosystem and human
19 See Annex I: Glossary.
20 Balanced diets feature plant-based foods, such as those based on coarse grains, legumes fruits and vegetables, nuts and seeds, andanimal-source foods produced in resilient, sustainable and low-GHG emissions systems, as described in SRCCL. {WGII SPM Footnote
32}
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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 insecurity21 and reduced water
security, with the largest impacts observed in many locations and/or communities in Africa, Asia, Central andSouth 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}
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 (highconfidence), where they have also worsened air pollution events (medium confidence) and limited functioningof key infrastructure (high confidence). Urban infrastructure, including transportation, water, sanitation andenergy systems have been compromised by extreme and slow-onset events22, 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 assessedregions (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 inhuman mortality and morbidity (very high confidence). The occurrence of climate-related food-borne andwater-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). Animaland 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 fromextreme events (very high confidence), and loss of livelihoods and culture (high confidence) (Figure 2.3).
Climate change impacts on health are mediated through natural and human systems, including economic andsocial 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 perpetuatedvulnerability (medium confidence). {WGII SPM B.1.4, WGII SPM B.1.7}
Human influence has likely increased the chance of compound extreme events23 since the 1950s.
Concurrent and repeated climate hazards have occurred in all regions, increasing impacts and risks tohealth, ecosystems, infrastructure, livelihoods and food (high confidence). Compound extreme events
include increases in the frequency of concurrent heatwaves and droughts (high confidence); fire weather insome 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 (highconfidence). 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
21 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}.
22 Slow-onset events are described among the climatic-impact drivers of the WGI AR6 and refer to the risks and impacts associatedwith 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}
23 See Annex 1: Glossary.
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IPCC AR6 SYRmarkets and tourism (high confidence). Individual livelihoods have been affected through changes inagricultural 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 andphysical understanding indicate that human-caused climate change increases heavy precipitation associatedwith 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, WGIISPM 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 andpeople (high confidence). Losses and damages are unequally distributed across systems, regions and sectors(high confidence). Cultural losses, related to tangible and intangible heritage, threaten adaptive capacity andmay 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 (highconfidence). Infrastructure, including transportation, water, sanitation and energy systems have been
compromised by extreme and slow-onset events, with resulting economic losses, disruptions of services andimpacts to wellbeing (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 CO2LULUCF, 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 climatechange (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 especiallyfelt among Indigenous Peoples (high confidence). Human and ecosystem vulnerability are interdependent(high confidence). Vulnerability of ecosystems and people to climate change differs substantially among andwithin 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 suchas colonialism, and governance24 (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}

24 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}
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IPCC AR6 SYRResponses Undertaken to Date

International climate agreements, rising national ambitions for climate action, along with rising publicawareness 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 andcontribute 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 andimplementation 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 capacityfor 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 nationaland 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, WGIII SPM B.5.1, WGIII SPM E.6, WGII TS D.1.1}
Loss & Damage25 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 notcomprehensively addressed by current financial, governance and institutional arrangements, particularly invulnerable 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 in2015 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 andinclusive societies. If achieved, these agreements would reduce climate change, and the impacts on health,wellbeing, 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 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 decisionmaking 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 aboutclimate change. This can usefully build public support to accelerate climate action (medium evidence, highagreement). In some instances, public discourses of media and organised counter movements have impededclimate 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
25 See Annex I: Glossary.

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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 (highconfidence). Climate governance supports mitigation by providing frameworks through which diverse actors
interact, and a basis for policy development and implementation (medium confidence). Many regulatory andeconomic 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 (highconfidence). {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 oftechnology-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 beenfound to be more effective than single policies (high confidence). Combining mitigation with policies to shiftdevelopment 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 fromcleaner 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 governanceenhances 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, havefallen consistently since 2010 (Figure 2.4). Design and process innovations in combination with the useof digital technologies have led to near-commercial availability of many low or zero emissions options
in buildings, transport and industry. From 2010 to 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 acrossregions (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-scalebattery 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 thantransitioning 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 toincreasing examples of zero energy or zero carbon buildings. Technological innovation made possible thewidespread 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
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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}[START FIGURE 2.4 HERE]

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 ineach year. Yellow shading indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020 (corresponding
to USD55–148 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; forthe 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 nonmonetary) costs of technologies and alter their deployment. The bottom panel (b) shows cumulative global adoption foreach 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 sharereflects different capacity factors; for example, for the same amount of installed capacity, wind produces about twice as
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IPCC AR6 SYRmuch electricity as solar PV {WGIII 2.5, 6.4}. 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}[END FIGURE 2.4 HERE]

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) andmost 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 (highconfidence). 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 ofcarbon pricing instruments can be addressed by using revenue from carbon taxes or emissions trading tosupport 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 since2010, global energy intensity (total primary energy per unit GDP) decreased by 2% yr –1 between 2010 and2019. Global carbon intensity (CO2-FFI per unit primary energy) also decreased by 0.3% yr–1, mainly due tofuel switching from coal to gas, reduced expansion of coal capacity, and increased use of renewables, and withlarge 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 thatmitigation policies have led to avoided global emissions of several GtCO2-eq yr–1 (medium confidence). At
least 1.8 GtCO2-eq yr–1 of avoided emissions can be accounted for by aggregating separate estimates for theeffects 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 haverisen 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,
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of climate impacts and risks has resulted in at least 170 countries and many cities including adaptation in theirclimate 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 documented26 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 inagriculture include cultivar improvements, agroforestry, community-based adaptation and farm and landscapediversification 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, andland 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 andsustainable 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 havemitigation co-benefits (high confidence). Adaptation actions that increase the resilience of biodiversity andecosystem 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 in disaster risk management, social safety
nets and green/blue infrastructure (medium confidence). Many adaptation measures that benefit health andwellbeing 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 ofadaptation from a variety of sources such as commercial financial institutions, institutional investors, otherprivate equity, non-financial corporations, as well as communities and households has been limited, especiallyin developing countries (high confidence). Public mechanisms and finance can leverage private sector financefor adaptation by addressing real and perceived regulatory, cost and market barriers, for example via publicprivate partnerships (high confidence). Innovations in adaptation and resilience finance, such as forecastbased/anticipatory financing systems and regional risk insurance pools, have been piloted and are growing inscale (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 effective27 in reducing climate risks28 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,
irrigation29, agroforestry, community-based adaptation, and farm and landscape level diversification, andsustainable land management approaches, provide multiple benefits and reduce climate risks. Reduction offood loss and waste, and adaptation measures in support of balanced diets contribute to nutrition, health, andbiodiversity 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}
26 Documented adaptation refers to published literature on adaptation policies, measures and actions that has been implemented anddocumented in peer reviewed literature, as opposed to adaptation that may have been planned, but not implemented.
27 Effectiveness refers here to the extent to which an adaptation option is anticipated or observed to reduce climate-related risk.
28 See Annex I: Glossary.
29 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).
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IPCC AR6 SYREcosystem-based Adaptation30 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 cobenefits. Some land-based adaptation options provide immediate benefits (e.g., conservation of peatlands,
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 naturalprocesses 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 withflood-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, foodand vector-borne diseases include improving access to potable water, reducing exposure of water andsanitation 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 (highconfidence). {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 (highconfidence). {WGII SPM C.2}

2.3

Current Mitigation and Adaptation Actions and Policies are not Sufficient

At the time of the present assessment31 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. 32
Despite progress, adaptation gaps33 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. (highconfidence)

2.3.1

The Gap Between Mitigation Policies, Pledges and Pathways that Limit Warming to 1.5 or Below
2°C

Global GHG emissions in 2030 associated with the implementation of NDCs announced prior to
COP2634 would make it likely that warming will exceed 1.5°C during the 21st century and would make30

EbA is recognised internationally under the Convention on Biological Diversity (CBD14/5). A related concept is Nature-based
Solutions (NbS), see Annex I: Glossary
31 The timing of various cut-offs for assessment differs by WG report and the aspect assessed. See footnote 1 in Section 1.
32 See CSB.2 for a discussion of scenarios and pathways.
33 See Annex I: Glossary.
34 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
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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 theimplementation 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 andsustained global GHG emission reductions this decade (high confidence) (Table 2.2, Table 3.1, 4.1).35 The
magnitude of the emissions gap depends on the global warming level considered and whether only
unconditional or also conditional elements of NDCs36 are considered (high confidence) (Table 2.2). Modelled
pathways that are consistent with NDCs announced prior to COP26 until 2030 and assume no increase inambition thereafter have higher emissions, leading to a median global warming of 2.8 [2.1–3.4]°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, CSB2). {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 gap’37 (high confidence) (Table 2.2, Figure2.5). Projected global emissions implied by policies implemented by the end of 2020 are 57 (52–60) GtCO2eq in 2030 (Table 2.2). This points to an implementation gap compared with the NDCs of 4–7 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–3.5°C (very likely range) by 2100 (medium confidence) (see Section 3.1.1). {WGIII
SPM B.6.1, WGIII SPM C.1}
Projected cumulative future CO2 emissions over the lifetime of existing fossil fuel infrastructure without
additional abatement38 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 inpathways that limit warming to 2°C with a likelihood of 83%39 (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. 6.13}[START TABLE 2.2 HERE]
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 inemissions are based on emissions of 52–56 GtCO2-eq yr–1 in 2019 as assumed in underlying model studies40. (medium
confidence) {WGIII Table SPM.1} (Table 3.1, CSB.2)

only submitted thereafter. 25 NDC updates were submitted between 12 October 2021 and the start of COP26. {WGIII SPM footnote
24}
35 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)
36 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}
37 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}
38 Abatement here refers to human interventions that reduce the amount of GHGs that are released from fossil fuel infrastructure to theatmosphere. {WGIII SPM footnote 34}
39 WGI provides carbon budgets that are in line with limiting global warming to temperature limits with different likelihoods, such as50%, 67% or 83% {WGI Table SPM.2}.
40 The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO -eq] is within the uncertainty ranges of 20192
emissions assessed in WGIII Chapter 2 [53–66 GtCO2-eq]
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Figure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), and projected emission outcomesfrom near-term policy assessments for 2030 (Panel b). Panel a shows global GHG emissions over 2015–2050 for fourtypes 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
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IPCC AR6 SYRemissions reductions likely to limit warming to 2°C (C3b, WGIII Table SPM.2) or to return warming to 1.5°C with aprobability 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 after2020 (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 CO 2-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, CSB.2)[END FIGURE 2.5 HERE][START CROSS-SECTION BOX.1 HERE]

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 CO 2 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 pastand 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 CO 2 and metric-weighted41 non-CO2
GHG emissions to be counterbalanced by durably stored CO2 removals (high confidence). Some nonCO2 emissions, such as CH4 and N2O from agriculture, cannot be fully eliminated using existing andanticipated technical measures {WGIII SPM C.2.4, WGIII SPM C.11.4, 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 andundertake carbon dioxide removal, the associated costs, and the availability of policy mechanisms to balanceemissions and removals between sectors and countries. (high confidence) {WGIII Box TS.6, WGIII CrossChapter 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 onpolicies, 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 couldchange the country-level timing of net zero (high confidence). The Paris Agreement also recognizes thatpeaking of emissions will occur later in developing countries than developed countries (Article 4.1) {WGIIIBox TS.6, WGIII Cross-Chapter Box 3, WGIII 14.3}.
More information on country-level net zero pledges is provided in S2.3.1, on the timing of global net zero
emissions in S3.3.2, and on sectoral aspects of net zero in S4.1.

41 See footnote 12 above.

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Many countries have signalled an intention to achieve net-zero GHG or net-zero CO2 emissions byaround 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. Manycompanies 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 datein 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 toenable 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 madeby 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 ofclimate 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 forclimate 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 withlimited institutional capacity, several adverse side-effects have been observed as a result of diffusion of lowemission 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 politicalfeasibility 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 accessto 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}

2.3.2

Adaptation Gaps and Barriers

Despite progress, adaptation gaps exist between current levels of adaptation and levels needed torespond 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 initiativesprioritise immediate and near-term climate risk reduction, e.g., through hard flood protection, which reduces
the opportunity for transformational adaptation42 (high confidence). Most observed adaptation is fragmented,
small in scale, incremental, sector-specific, and focused more on planning rather than implementation (highconfidence). 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–healthnexus 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 andimplementation 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}

42 See Annex I: Glossary.

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IPCC AR6 SYRSoft and hard adaptation limits43 have already been reached in some sectors and regions, in spite ofadaptation 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 somepolar and mountain ecosystems (high confidence). Individuals and households in low lying coastal areas inAustralasia 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 fromincremental 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 softand hard limits. Losses and damages are unequally distributed across systems, regions and sectors and are notcomprehensively addressed by current financial, governance and institutional arrangements, particularly invulnerable developing countries. (high confidence) {WGII SPM.C.3.5}
There is increased evidence of maladaptation44 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 fire-adapted ecosystems, or hard defences against flooding) andhuman 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 byflexible, 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 andsocial 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 (highconfidence). 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 totransformational adaptation are limited due to vested interests, economic lock-ins, institutional pathdependencies 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 andinformation (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, WGIISPM C.3.1, WGII TS.D.1.3, WGII TS.D.1.5, 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 andsectors (high confidence). In 2018, public and publicly mobilised private climate finance flows fromdeveloped to developing countries were below the collective goal under the UNFCCC and Paris Agreement to
43 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.
44 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.
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mobilise USD 100 billion per year by 2020 in the context of meaningful mitigation action and transparency
on implementation (medium confidence). Public and private finance flows for fossil fuels are still greater thanthose for climate adaptation and mitigation (high confidence). The overwhelming majority of tracked climate
finance is directed towards mitigation (very high confidence). Nevertheless, average annual modelled
investment requirements for 2020 to 2030 in scenarios that limit warming to 2°C or 1.5°C are a factor of three
to six greater than current levels, and total mitigation investments (public, private, domestic and international)
would need to increase across all sectors and regions (medium confidence). Challenges remain for green bonds
and similar products, in particular around integrity and additionality, as well as the limited applicability ofthese markets to many developing countries (high confidence). {WGII SPM C.3.2, WGII SPM C.5.4; WGIII
SPM B.5.4, WGIII SPM E5.1}
Current global financial flows for adaptation including from public and private finance sources, are insufficient
for and constrain implementation of adaptation options, especially in developing countries (high confidence).
There are widening disparities between the estimated costs of adaptation and the documented finance allocatedto adaptation (high confidence). Adaptation finance needs are estimated to be higher than those assessed in
AR5, and the enhanced mobilisation of and access to financial resources are essential for implementation ofadaptation and to reduce adaptation gaps (high confidence). Annual finance flows targeting adaptation for
Africa, for example, are billions of USD less than the lowest adaptation cost estimates for near-term climatechange (high confidence). Adverse climate impacts can further reduce the availability of financial resources
by causing losses and damages and impeding national economic growth, thereby further increasing financial
constraints for adaptation particularly for developing countries and LDCs (medium confidence). {WGII SPM
C.1.2, WGII SPM C.3.2, WGII SPM C.5.4, WGII TS.D.1.6}
Without effective mitigation and adaptation, losses and damages will continue to disproportionately affect thepoorest and most vulnerable populations. Accelerated financial support for developing countries fromdeveloped countries and other sources is a critical enabler to enhance mitigation action {WGIII SPM. E.5.3}.
Many developing countries lack comprehensive data at the scale needed and lack adequate financial resources
needed for adaptation for reducing associated economic and non-economic losses and damages. (highconfidence) {WGII Cross-Chapter Box LOSS, WGII SPM C.3.1, WGII SPM C.3.2, WGII TS.D.1.3, WGII
TS.D.1.5; WGIII SPM E.5.3}
There are barriers to redirecting capital towards climate action both within and outside the global
financial sector. These barriers include: the inadequate assessment of climate-related risks and investment
opportunities, regional mismatch between available capital and investment needs, home bias factors, country
indebtedness levels, economic vulnerability, and limited institutional capacities. Challenges from outside thefinancial sector include: limited local capital markets; unattractive risk-return profiles, in particular due tomissing or weak regulatory environments that are inconsistent with ambition levels; limited institutional
capacity to ensure safeguards; standardisation, aggregation, scalability and replicability of investment
opportunities and financing models; and, a pipeline ready for commercial investments. (high confidence){WGII SPM C.5.4; WGIII SPM E.5.2; SR15 SPM D.5.2}[START CROSS-SECTION BOX.2 HERE]

Cross-Section Box.2: Scenarios, Global Warming Levels, and Risks
Modelled scenarios and pathways45 are used to explore future emissions, climate change, related impacts andrisks, and possible mitigation and adaptation strategies and are based on a range of assumptions, including
socio-economic variables and mitigation options. These are quantitative projections and are neither predictions
nor forecasts. Global modelled emission pathways, including those based on cost effective approaches containregionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition ofthese assumptions. Most do not make explicit assumptions about global equity, environmental justice or intraregional income distribution. IPCC is neutral with regard to the assumptions underlying the scenarios in the
45 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation toclimate goals. WGI primarily used the term scenarios and WGIII mostly used the term modelled emissions and mitigation pathways.
The SYR primarily uses scenarios when referring to WGI and modelled emissions and mitigation pathways when referring to WGIII.
{WGI Box SPM.1; WGIII footnote 44}
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literature assessed in this report, which do not cover all possible futures.46{SROCC Box SPM.1; SRCCL Box
SPM.1; WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1}.
Socio-economic Development, Scenarios, and Pathways
The five Shared Socio-economic Pathways (SSP1 to SSP5) were designed to span a range of challenges toclimate change mitigation and adaptation. For the assessment of climate impacts, risk and adaptation, the SSPs
are used for future exposure, vulnerability and challenges to adaptation. Depending on levels of GHG
mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming
levels47. There are many different mitigation strategies that could be consistent with different levels of global
warming in 2100 (see Figure 4.1). {WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1, WGIII Box
TS.5, WGIII Annex III; SRCCL Box SPM.1, Figure SPM.2}
WGI assessed the climate response to five illustrative scenarios based on SSPs48 that cover the range ofpossible future development of anthropogenic drivers of climate change found in the literature. These scenarios
combine socio-economic assumptions, levels of climate mitigation, land use and air pollution controls foraerosols and non-CH4 ozone precursors. The high and very high GHG emissions scenarios (SSP3-7.0 and
SSP5-8.5) have CO2 emissions that roughly double from current levels by 2100 and 2050, respectively49. Theintermediate GHG emissions scenario (SSP2-4.5) has CO2 emissions remaining around current levels until the
middle of the century. The very low and low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6) have CO2
emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative
CO2 emissions. In addition, Representative Concentration Pathways (RCPs)50 were used by WGI and WGII toassess regional climate changes, impacts and risks. {WGI Box SPM.1} (Cross-Section Box.2, Figure 1)
In WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways
were categorised based on their projected global warming over the 21st century, with categories ranging from
pathways that limit warming to 1.5°C with more than 50% likelihood51 with no or limited overshoot (C1) topathways that exceed 4°C (C8). Methods to project global warming associated with the modelled pathways
were updated to ensure consistency with the AR6 WGI assessment of the climate system response52. {WGIIIBox SPM.1, WGIII Table 3.1} (Table 3.1, Cross-Section Box.2, Figure 1)
Global Warming Levels (GWLs)
For many climate and risk variables, the geographical patterns of changes in climatic impact-drivers53 andclimate impacts for a level of global warming54 are common to all scenarios considered and independent oftiming when that level is reached. This motivates the use of GWLs as a dimension of integration. {WGI Box
SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2)
46 Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation/abatement

options globally. The other half look at existing policies and regionally and sectorally differentiated actions. The underlying population
assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion in 2100 (5–95th percentile) starting from 7.6 billion in 2019.
The underlying assumptions on global GDP growth range from 2.5 to 3.5% per year in the 2019–2050 period and 1.3 to 2.1% per year
in the 2050–2100 (5–95th percentile). {WGIII Box SPM.1}.
47 High mitigation challenges, for example, due to assumptions of slow technological change, high levels of global population growth,and high fragmentation as in the Shared Socio-economic Pathway SSP3, may render modelled pathways that limit warming to 2°C (>67%) or lower infeasible (medium confidence) {SRCCL Box SPM.1; WGIII SPM C.1.4}.
48 SSP-based scenarios are referred to as SSPx-y, where ‘SSPx’ refers to the Shared Socioeconomic Pathway describing thesocioeconomic trends underlying the scenarios, and ‘y’ refers to the level of radiative forcing (in watts per square metre, or Wm-2)
resulting from the scenario in the year 2100. {WGI SPM footnote 22}
49 Very high emission scenarios have become less likely but cannot be ruled out. Temperature levels > 4C may result from very highemission scenarios, but can also occur from lower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher thanthe best estimate.
50 RCP-based scenarios are referred to as RCPy, where ‘y’ refers to the approximate level of radiative forcing (in watts per square
metre, or Wm-2) resulting from the scenario in the year 2100. {WGII SPM footnote 21}
51 Denoted ‘>50%’ in this report.
52 The climate response to emissions is investigated with climate models, paleoclimatic insights and other lines of evidence. The
assessment outcomes are used to categorise thousands of scenarios via simple physically-based climate models (emulators) {WGI
TS.1.2.2}.
53 See Annex I: Glossary
54 See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850–1900. The assessed
time of when a certain global warming level is reached under a particular scenario is defined here as the mid-point of the first 20-year
running average period during which the assessed average global surface temperature change exceeds the level of global warming.
{WGI SPM footnote 26, Cross-Section Box TS.1}
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Risks
Dynamic interactions between climate-related hazards, exposure and vulnerability of the affected humansociety, species, or ecosystems result in risks arising from climate change. AR6 assesses key risks acrosssectors and regions as well as providing an updated assessment of the Reasons for Concern (RFCs) – fiveglobally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature.
Risks can also arise from climate change mitigation or adaptation responses when the response does notachieve its intended objective, or when it results in adverse effects for other societal objectives. {WGII SPM
A, WGII Figure SPM.3, WGII Box TS.1, WGII Figure TS.4; SR1.5 Figure SPM.2; SRCCL Figure SPM.2;
SROCC Errata Figure SPM.3} (3.1.2, Cross-Section Box.2, Figure 1; Figure 3.3)
[START CROSS-SECTION BOX.2, FIGURE 1 HERE]* The terminology SSPx-y is used, where ‘SSPx’ refers to the Shared Socio-economic Pathway or ‘SSP’ describing the socio-economic
trends underlying the scenario, and ‘y’ refers to the approximate level of radiative forcing (in watts per square metre, or W m –2)
resulting from the scenario in the year 2100.
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IPCC AR6 SYR** The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate
2100 radiative forcing levels (in Wm-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs.
They are similar but not identical, with differences in concentration trajectories for different GHGs. The overall radiative forcing tends
to be higher for the SSPs compared to the RCPs with the same label (medium confidence). {WGI TS.1.3.1}*** Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C, high overshoot by 0.1°C-0.3°C, in both cases
for up to several decades.

Cross-Section Box.2, Figure 1: Schematic of the AR6 framework for assessing future greenhouse gas emissions,climate change, risks, impacts and mitigation. Panel (a) The integrated framework encompasses socio-economic
development and policy, emissions pathways and global surface temperature responses to the five scenarios considered
by WGI (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and eight global mean temperature change
categorisations (C1–C8) assessed by WGIII, and the WGII risk assessment. The dashed arrow indicates that the influence
from impacts/risks to socio-economic changes is not yet considered in the scenarios assessed in the AR6. Emissions
include GHGs, aerosols, and ozone precursors. CO2 emissions are shown as an example on the left. The assessed global
surface temperature changes across the 21st century relative to 1850–1900 for the five GHG emissions scenarios areshown as an example in the centre. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0. Projected temperature
outcomes at 2100 relative to 1850–1900 are shown for C1 to C8 categories with median (line) and the combined very
likely range across scenarios (bar). On the right, future risks due to increasing warming are represented by an example‘burning ember’ figure (see 3.1.2 for the definition of RFC1). Panel (b) Description and relationship of scenarios
considered across AR6 Working Group reports. Panel (c) Illustration of risk arising from the interaction of hazard (driven
by changes in climatic impact-drivers) with vulnerability, exposure and response to climate change. {WGI TS1.4, Figure
4.11; WGII Figure 1.5, WGII Figure 14.8; WGIII Table SPM.2, Figure 3.11}[END CROSS-SECTION BOX.2 FIGURE 1 HERE][END CROSS-SECTION BOX.2 HERE]

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IPCC AR6 SYRSection 3: Long-Term Climate and Development Futures
3.1

Long-Term Climate Change, Impacts and Related Risks

Future warming will be driven by future emissions and will affect all major climate system components,
with every region experiencing multiple and co-occurring changes. Many climate-related risks areassessed to be higher than in previous assessments, and projected long-term impacts are up to multiple
times higher than currently observed. Multiple climatic and non-climatic risks will interact, resulting incompounding and cascading risks across sectors and regions. Sea level rise, as well as other irreversible
changes, will continue for thousands of years, at rates depending on future emissions. (high confidence)
3.1.1

Long-term Climate Change

The uncertainty range on assessed future changes in global surface temperature is narrower than in theAR5. For the first time in an IPCC assessment cycle, multi-model projections of global surface temperature,
ocean warming and sea level are constrained using observations and the assessed climate sensitivity. The likely
range of equilibrium climate sensitivity has been narrowed to 2.5°C–4.0°C (with a best estimate of 3.0°C)
based on multiple lines of evidence55, including improved understanding of cloud feedbacks. For related
emissions scenarios, this leads to narrower uncertainty ranges for long-term projected global temperaturechange than in AR5. {WGI A.4, WGI Box SPM.1, WGI TS.3.2, WGI 4.3}
Future warming depends on future greenhouse gas (GHG) emissions, with cumulative net CO2
dominating. The assessed best estimates and very likely ranges of warming for 2081–2100 with respect to1850–1900 vary from 1.4°C [1.0-1.8°C] in the very low GHG emissions scenario (SSP1-1.9) to 2.7°C [2.1°C–
3.5°C] in the intermediate GHG emissions scenario (SSP2-4.5) and 4.4°C [3.3°C–5.7°C] in the very high GHG
emissions scenario (SSP5-8.5)56. {WGI SPM B.1.1, WGI Table SPM.1, WGI Figure SPM.4} (Cross-Section
Box.2, Figure 1)
Modelled pathways consistent with the continuation of policies implemented by the end of 2020 lead to
global warming of 3.2 [2.2-3.5]°C (5–95% range) by 2100 (medium confidence) (see also Section 2.3.1).
Pathways of >4°C (≥50%) by 2100 would imply a reversal of current technology and/or mitigation policy
trends (medium confidence). However, such warming could occur in emissions pathways consistent with
policies implemented by the end of 2020 if climate sensitivity or carbon cycle feedbacks are higher than thebest estimate (high confidence). {WGIII SPM C.1.3}
Global warming will continue to increase in the near term in nearly all considered scenarios andmodelled pathways. Deep, rapid and sustained GHG emissions reductions, reaching net zero CO 2
emissions and including strong emissions reductions of other GHGs, in particular CH4, are necessary tolimit warming to 1.5°C (>50%) or less than 2°C (>67%) by the end of century (high confidence). The
best estimate of reaching 1.5°C of global warming lies in the first half of the 2030s in most of the consideredscenarios and modelled pathways57. In the very low GHG emissions scenario (SSP1-1.9), CO2 emissions reachnet zero around 2050 and the best-estimate end-of-century warming is 1.4°C, after a temporary overshoot (seeSection 3.3.4) of no more than 0.1°C above 1.5°C global warming. Global warming of 2°C will be exceeded
during the 21st century unless deep reductions in CO2 and other GHG emissions occur in the coming decades.
55 Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (see Annex I:

Glossary). {WGI SPM footnote 21}
56 The best estimates [and very likely ranges] for the different scenarios are: 1.4°C [1.0°C–1.8°C] (SSP1-1.9); 1.8°C [1.3°C–2.4°C](SSP1-2.6); 2.7°C [2.1°C–3.5°C] (SSP2-4.5); 3.6°C [2.8°C–4.6°C] (SSP3-7.0); and 4.4°C [3.3°C–5.7°C] (SSP5-8.5). {WGI Table
SPM.1} (CSB.2)
57 In the near term (2021–2040), the 1.5°C global warming level is very likely to be exceeded under the very high GHG emissions
scenario (SSP5-8.5), likely to be exceeded under the intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely
than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely than not to be reached under the very low
GHG emissions scenario (SSP1-1.9). In all scenarios considered by WGI except the very high emissions scenario, the midpoint of thefirst 20-year running average period during which the assessed global warming reaches 1.5°C lies in the first half of the 2030s. In thevery high GHG emissions scenario, this mid-point is in the late 2020s. Median five-year interval at which a 1.5°C global warming
level is reached (50% probability) in categories of modelled pathways considered in WGIII is 2030-2035. {WGI SPM B.1.3, WGI
Cross-Section Box TS.1, WGIII Table 3.2} (Cross-Section Box.2)
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Deep, rapid and sustained reductions in GHG emissions would lead to improvements in air quality within a
few years, to reductions in trends of global surface temperature discernible after around 20 years, and overlonger time periods for many other climate impact-drivers58 (high confidence). Targeted reductions of air
pollutant emissions lead to more rapid improvements in air quality compared to reductions in GHG emissions
only, but in the long term, further improvements are projected in scenarios that combine efforts to reduce air
pollutants as well as GHG emissions (high confidence)59. {WGI SPM B.1, WGI SPM B.1.3, WGI SPM D.1,
WGI SPM D.2, WGI Figure SPM.4, WGI Table SPM.1, WGI Cross-Section Box TS.1; WGIII SPM C.3,
WGIII Table SPM.2, WGIII Figure SPM.5, WGIII Box SPM.1 Figure 1, WGIII Table 3.2} (Table 3.1, CrossSection Box 2, Figure 1)
Changes in short-lived climate forcers (SLCF) resulting from the five considered scenarios lead to an
additional net global warming in the near and long term (high confidence). Simultaneous stringent
climate change mitigation and air pollution control policies limit this additional warming and lead tostrong benefits for air quality (high confidence). In high and very high GHG emissions scenarios (SSP3-7.0
and SSP5-8.5), combined changes in SLCF emissions, such as CH4, aerosol and ozone precursors, lead to a
net global warming by 2100 of likely 0.4°C–0.9°C relative to 2019. This is due to projected increases inatmospheric concentration of CH4, tropospheric ozone, hydrofluorocarbons and, when strong air pollution
control is considered, reductions of cooling aerosols. In low and very low GHG emissions scenarios (SSP11.9 and SSP1-2.6), air pollution control policies, reductions in CH4 and other ozone precursors lead to a net
cooling, whereas reductions in anthropogenic cooling aerosols lead to a net warming (high confidence).
Altogether, this causes a likely net warming of 0.0°C–0.3°C due to SLCF changes in 2100 relative to 2019 andstrong reductions in global surface ozone and particulate matter (high confidence). {WGI SPM D.1.7, WGIBox TS.7} (CSB.2)
Continued GHG emissions will further affect all major climate system components, and many changes
will be irreversible on centennial to millennial time scales. Many changes in the climate system becomelarger in direct relation to increasing global warming. With every additional increment of global warming,changes in extremes continue to become larger. Additional warming will lead to more frequent and intense
marine heatwaves and is projected to further amplify permafrost thawing and loss of seasonal snow cover,glaciers, land ice and Arctic sea ice (high confidence). Continued global warming is projected to further
intensify the global water cycle, including its variability, global monsoon precipitation60, and very wet andvery dry weather and climate events and seasons (high confidence). The portion of global land experiencing
detectable changes in seasonal mean precipitation is projected to increase (medium confidence) with morevariable precipitation and surface water flows over most land regions within seasons (high confidence) andfrom year to year (medium confidence). Many changes due to past and future GHG emissions are irreversible61
on centennial to millennial time scales, especially in the ocean, ice sheets and global sea level (see 3.1.3).
Ocean acidification (virtually certain), ocean deoxygenation (high confidence) and global mean sea level(virtually certain) will continue to increase in the 21st century, at rates dependent on future emissions. {WGISPM B.2, WGI SPM B.2.2, WGI SPM B.2.3, WGI SPM B.2.5, WGI SPM B.3, WGI SPM B.3.1, WGI SPM
B.3.2, WGI SPM B.4, WGI SPM B.5, WGI SPM B.5.1, WGI SPM B.5.3, WGI Figure SPM.8} (Figure 3.1)
With further global warming, every region is projected to increasingly experience concurrent andmultiple changes in climatic impact-drivers. Increases in hot and decreases in cold climatic impact-drivers,
such as temperature extremes, are projected in all regions (high confidence). At 1.5°C global warming, heavy
precipitation and flooding events are projected to intensify and become more frequent in most regions in
Africa, Asia (high confidence), North America (medium to high confidence) and Europe (medium confidence).
At 2°C or above, these changes expand to more regions and/or become more significant (high confidence),
and more frequent and/or severe agricultural and ecological droughts are projected in Europe, Africa,
Australasia and North, Central and South America (medium to high confidence). Other projected regionalchanges include intensification of tropical cyclones and/or extratropical storms (medium confidence), andincreases in aridity and fire weather62 (medium to high confidence). Compound heatwaves and droughts

58 See Cross-Section Box.2.
59 Based on additional scenarios.
60 Particularly over South and South East Asia, East Asia and West Africa apart from the far west Sahel {WGI SPM B.3.3}
61 See Annex I: Glossary.
62 See Annex I: Glossary.

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become likely more frequent, including concurrently at multiple locations (high confidence). {WGI SPM C.2,
WGI SPM C.2.1, WGI SPM C.2.2, WGI SPM C.2.3, WGI SPM C.2.4, WGI SPM C.2.7}[START FIGURE 3.1 HERE]

Figure 3.1: Projected changes of annual maximum daily temperature, annual mean total column soil moisture
CMIPand annual maximum daily precipitation at global warming levels of 1.5°C, 2°C, 3°C, and 4°C relative to1850–1900. Simulated (a) annual maximum temperature change (°C), (b) annual mean total column soil moisture(standard deviation), (c) annual maximum daily precipitation change (%). Changes correspond to CMIP6 multi-model
median changes. In panels (b) and (c), large positive relative changes in dry regions may correspond to small absolutechanges. In panel (b), the unit is the standard deviation of interannual variability in soil moisture during 1850–1900.
Standard deviation is a widely used metric in characterising drought severity. A projected reduction in mean soil moisture
by one standard deviation corresponds to soil moisture conditions typical of droughts that occurred about once every six
years during 1850–1900. The WGI Interactive Atlas (https://interactive-atlas.ipcc.ch/) can be used to explore additionalchanges in the climate system across the range of global warming levels presented in this figure.{WGI Figure SPM.5,
WGI Figure TS.5, WGI Figure 11.11, WGI Figure 11.16, WGI Figure 11.19} (CSB.2)

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3.1.2

Impacts and Related Risks

For a given level of warming, many climate-related risks are assessed to be higher than in AR5 (highconfidence). Levels of risk63 for all Reasons for Concern64 (RFCs) are assessed to become high to very highat lower global warming levels compared to what was assessed in AR5 (high confidence). This is based uponrecent evidence of observed impacts, improved process understanding, and new knowledge on exposure andvulnerability of human and natural systems, including limits to adaptation. Depending on the level of global
warming, the assessed long-term impacts will be up to multiple times higher than currently observed (highconfidence) for 127 identified key risks, e.g., in terms of the number of affected people and species. Risks,
including cascading risks (see 3.1.3) and risks from overshoot (see 3.3.4), are projected to become increasingly
severe with every increment of global warming (very high confidence). {WGII SPM B.3.3, WGII SPM B.4,
WGII SPM B.5, WGII 16.6.3; SRCCL SPM A5.3} (Figure 3.2, Figure 3.3)
Climate-related risks for natural and human systems are higher for global warming of 1.5°C than at present(1.1°C) but lower than at 2°C (high confidence) (see Section 2.1.2). Climate-related risks to health, livelihoods,
food security, water supply, human security, and economic growth are projected to increase with global
warming of 1.5°C. In terrestrial ecosystems, 3–14% of the tens of thousands of species assessed will likely
face a very high risk of extinction at a GWL of 1.5°C. Coral reefs are projected to decline by a further 70–90%
at 1.5°C of global warming (high confidence). At this GWL, many low-elevation and small glaciers aroundthe world would lose most of their mass or disappear within decades to centuries (high confidence). Regions
at disproportionately higher risk include Arctic ecosystems, dryland regions, small island development statesand Least Developed Countries (high confidence). {WGII SPM B.3, WGII SPM B.4.1, WGII TS.C.4.2; SR1.5
SPM A.3, SR1.5 SPM B.4.2, SR1.5 SPM B.5, SR1.5 SPM B.5.1} (Figure 3.3)
At 2°C of global warming, overall risk levels associated with the unequal distribution of impacts (RFC3),
global aggregate impacts (RFC4) and large-scale singular events (RFC5) would be transitioning to high(medium confidence), those associated with extreme weather events (RFC2) would be transitioning to very
high (medium confidence), and those associated with unique and threatened systems (RFC1) would be very
high (high confidence) (Figure 3.3, panel a). With about 2°C warming, climate-related changes in foodavailability and diet quality are estimated to increase nutrition-related diseases and the number ofundernourished people, affecting tens (under low vulnerability and low warming) to hundreds of millions ofpeople (under high vulnerability and high warming), particularly among low-income households in low- andmiddle-income countries in sub-Saharan Africa, South Asia and Central America (high confidence). For
example, snowmelt water availability for irrigation is projected to decline in some snowmelt dependent river
basins by up to 20% (medium confidence). Climate change risks to cities, settlements and key infrastructure
will rise sharply in the mid- and long-term with further global warming, especially in places already exposed
to high temperatures, along coastlines, or with high vulnerabilities (high confidence). {WGII SPM B.3.3, WGIISPM B.4.2, WGII SPM B.4.5, WGII TS C.3.3, WGII TS.C.12.2} (Figure 3.3)
63 Undetectable risk level indicates no associated impacts are detectable and attributable to climate change; moderate risk indicatesassociated impacts are both detectable and attributable to climate change with at least medium confidence, also accounting for the otherspecific criteria for key risks; high risk indicates severe and widespread impacts that are judged to be high on one or more criteria forassessing key risks; and very high risk level indicates very high risk of severe impacts and the presence of significant irreversibility or
the persistence of climate-related hazards, combined with limited ability to adapt due to the nature of the hazard or impacts/risks.
{WGII Figure SPM.3}
64 The Reasons for Concern (RFC) framework communicates scientific understanding about accrual of risk for five broad categories{WGII Figure SPM.3}. RFC1: Unique and threatened systems: ecological and human systems that have restricted geographic ranges
constrained by climate-related conditions and have high endemism or other distinctive properties. Examples include coral reefs, theArctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme weather events: risks/impacts to humanhealth, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associatedwildfires, and coastal flooding. RFC3: Distribution of impacts: risks/impacts that disproportionately affect particular groups due touneven distribution of physical climate change hazards, exposure or vulnerability. RFC4: Global aggregate impacts: impacts to socioecological systems that can be aggregated globally into a single metric, such as monetary damages, lives affected, species lost or
ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes
in systems caused by global warming, such as ice sheet instability or thermohaline circulation slowing. Assessment methods include astructured expert elicitation based on the literature described in WGII SM16.6 and are identical to AR5 but are enhanced by a structured
approach to improve robustness and facilitate comparison between AR5 and AR6. For further explanations of global risk levels andReasons for Concern, see WGII TS.AII. {WGII Figure SPM.3}
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IPCC AR6 SYRAt global warming of 3°C, additional risks in many sectors and regions reach high or very high levels, implying
widespread systemic impacts, irreversible change and many additional adaptation limits (see Section 3.2) (highconfidence). For example, very high extinction risk for endemic species in biodiversity hotspots is projected
to increase at least tenfold if warming rises from 1.5°C to 3°C (medium confidence). Projected increases in
direct flood damages are higher by 1.4–2 times at 2°C and 2.5–3.9 times at 3°C, compared to 1.5°C global
warming without adaptation (medium confidence). {WGII SPM B.4.1, WGII SPM B.4.2, WGII Figure SPM.3,
WGII TS Appendix AII, WGII Atlas Fig.AI.46} (Figure 3.2, Figure 3.3)
Global warming of 4°C and above is projected to lead to far-reaching impacts on natural and human systems(high confidence). Beyond 4°C of warming, projected impacts on natural systems include local extinction of~50% of tropical marine species (medium confidence) and biome shifts across 35% of global land area (medium
confidence). At this level of warming, approximately 10% of the global land area is projected to face bothincreasing high and decreasing low extreme streamflow, affecting, without additional adaptation, over 2.1
billion people (medium confidence) and about 4 billion people are projected to experience water scarcity(medium confidence). At 4°C of warming, the global burned area is projected to increase by 50–70% and thefire frequency by ~30% compared to today (medium confidence). {WGII SPM B.4.1, WGII SPM B.4.2, WGII
TS.C.1.2, WGII TS.C.2.3, WGII TS.C.4.1, WGII TS.C.4.4} (Figure 3.2, Figure 3.3)
Projected adverse impacts and related losses and damages from climate change escalate with every
increment of global warming (very high confidence), but they will also strongly depend on socioeconomic development trajectories and adaptation actions to reduce vulnerability and exposure (highconfidence). For example, development pathways with higher demand for food, animal feed, and water, moreresource-intensive consumption and production, and limited technological improvements result in higher risks
from water scarcity in drylands, land degradation and food insecurity (high confidence). Changes in, forexample, demography or investments in health systems have effect on a variety of health-related outcomes
including heat-related morbidity and mortality (Figure 3.3 Panel d). {WGII SPM B.3, WGII SPM B.4, WGII
Figure SPM.3; SRCCL SPM A.6}
With every increment of warming, climate change impacts and risks will become increasingly complex
and more difficult to manage. Many regions are projected to experience an increase in the probability ofcompound events with higher global warming, such as concurrent heatwaves and droughts, compound flooding
and fire weather. In addition, multiple climatic and non-climatic risk drivers such as biodiversity loss or violent
conflict will interact, resulting in compounding overall risk and risks cascading across sectors and regions.
Furthermore, risks can arise from some responses that are intended to reduce the risks of climate change, e.g.,
adverse side effects of some emission reduction and carbon dioxide removal (CDR) measures (see 3.4.1). (highconfidence) {WGI SPM C.2.7, WGI Figure SPM.6, WGI TS.4.3; WGII SPM B.1.7, WGII B.2.2, WGII SPM
B.5, WGII SPM B.5.4, WGII SPM C.4.2, WGII SPM B.5, WGII CCB2}
Solar Radiation Modification (SRM) approaches, if they were to be implemented, introduce awidespread range of new risks to people and ecosystems, which are not well understood. SRM has thepotential to offset warming within one or two decades and ameliorate some climate hazards but would notrestore climate to a previous state, and substantial residual or overcompensating climate change would occur
at regional and seasonal scales (high confidence). Effects of SRM would depend on the specific approach
used65, and a sudden and sustained termination of SRM in a high CO2 emissions scenario would cause rapid
climate change (high confidence). SRM would not stop atmospheric CO2 concentrations from increasing nor
reduce resulting ocean acidification under continued anthropogenic emissions (high confidence). Large
uncertainties and knowledge gaps are associated with the potential of SRM approaches to reduce climatechange risks. Lack of robust and formal SRM governance poses risks as deployment by a limited number ofstates could create international tensions. {WGI 4.6; WGII SPM B.5.5; WGIII 14.4.5.1; Cross-WG box SRM;
SR1.5 SPM C.1.4}[START FIGURE 3.2 HERE]

65 Several SRM approaches have been proposed, including stratospheric aerosol injection, marine cloud brightening, ground-based

albedo modifications, and ocean albedo change. See Annex I: Glossary.
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IPCC AR6 SYRFigure 3.2: Projected risks and impacts of climate change on natural and human systems at different global
warming levels (GWLs) relative to 1850–1900 levels. Projected risks and impacts shown on the maps are based on
outputs from different subsets of Earth system models that were used to project each impact indicator without additional
adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections andadditional lines of evidence. (a) Risks of species losses as indicated by the percentage of assessed species exposed topotentially dangerous temperature conditions, as defined by conditions beyond the estimated historical (1850-2005)
maximum mean annual temperature experienced by each species, at GWLs of 1.5°C, 2°C, 3°C and 4°C. Underpinning
projections of temperature are from 21 Earth system models and do not consider extreme events impacting ecosystems
such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure to hypothermic
conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (19912005) and at GWLs of 1.7°C–2.3°C (mean = 1.9°C; 13 climate models), 2.4°C–3.1°C (2.7°C; 16 climate models) and
4.2°C–5.4°C (4.7°C; 15 climate models). Interquartile ranges of WGLs by 2081-2100 under RCP2.6, RCP4.5 andSubject to Copyedit

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RCP8.5. The presented index is consistent with common features found in many indices included within WGI and WGII
assessments. (c) Impacts on food production: (c1) Changes in maize yield at projected GWLs of 1.6°C–2.4oC (2.0°C),
3.3°C–4.8oC (4.1°C) and 3.9°C–6.0oC (4.9°C). Median yield changes from an ensemble of 12 crop models, each driven
by bias-adjusted outputs from 5 Earth system models from the Agricultural Model Intercomparison and Improvement
Project (AgMIP) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Maps depict 2080–2099
compared to 1986–2005 for current growing regions (>10 ha), with the corresponding range of future global warming
levels shown under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively. Hatching indicates areas where <70% of the climatecrop model combinations agree on the sign of impact. (c2) Changes in maximum fisheries catch potential by 2081–2099
relative to 1986–2005 at projected GWLs of 0.9°C–2.0°C (1.5°C) and 3.4°C–5.2°C (4.3°C). GWLs by 2081–2100 under
RCP2.6 and RCP8.5. Hatching indicates where the two climate-fisheries models disagree in the direction of change. Large
relative changes in low yielding regions may correspond to small absolute changes. Biodiversity and fisheries in
Antarctica were not analysed due to data limitations. Food security is also affected by crop and fishery failures notpresented here {WGII Fig. TS.5, WGII Fig TS.9, WGII Annex I: Global to Regional Atlas Figure AI.15, Figure AI.22,
Figure AI.23, Figure AI.29; WGII 7.3.1.2, 7.2.4.1, SROCC Figure SPM.3} (3.1.2, Cross-Section Box.2)[END FIGURE 3.2 HERE][START FIGURE 3.3 HERE]

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IPCC AR6 SYRFigure 3.3: Synthetic risk diagrams of global and sectoral assessments and examples of regional key risks. The
burning embers result from a literature based expert elicitation. Panel (a): Left - Global surface temperature changes in°C relative to 1850–1900. These changes were obtained by combining CMIP6 model simulations with observational
constraints based on past simulated warming, as well as an updated assessment of equilibrium climate sensitivity. Verylikely ranges are shown for the low and high GHG emissions scenarios (SSP1-2.6 and SSP3-7.0); Right - Global Reasonsfor Concern, comparing AR6 (thick embers) and AR5 (thin embers) assessments. Diagrams are shown for each RFC,
assuming low to no adaptation (i.e., adaptation is fragmented, localised and comprises incremental adjustments to existing
practices). However, the transition to a very high risk level has an emphasis on irreversibility and adaptation limits. The
horizontal line denotes the present global warming of 1.1°C which is used to separate the observed, past impacts below
the line from the future projected risks above it. Lines connect the midpoints of the transition from moderate to high risk
across AR5 and AR6. Panel (b): Risks for land-based systems and ocean/coastal ecosystems. Diagrams shown for each
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IPCC AR6 SYRrisk assume low to no adaptation. Text bubbles indicate examples of impacts at a given warming level. Panel (c): Left Global mean sea level change in centimetres, relative to 1900. The historical changes (black) are observed by tide gauges
before 1992 and altimeters afterwards. The future changes to 2100 (coloured lines and shading) are assessed consistently
with observational constraints based on emulation of CMIP, ice-sheet, and glacier models, and likely ranges are shown
for SSP1-2.6 and SSP3-7.0. Right - Assessment of the combined risk of coastal flooding, erosion and salinization for
four illustrative coastal geographies in 2100, due to changing mean and extreme sea levels, under two response scenarios,with respect to the SROCC baseline period (1986–2005) and indicating the IPCC AR6 baseline period (1995–2014). The
assessment does not account for changes in extreme sea level beyond those directly induced by mean sea level rise; risk
levels could increase if other changes in extreme sea levels were considered (e.g., due to changes in cyclone intensity).
“No-to-moderate response” describes efforts as of today (i.e., no further significant action or new types of actions).
“Maximum potential response” represents a combination of responses implemented to their full extent and thus significant
additional efforts compared to today, assuming minimal financial, social and political barriers. The assessment criteria
include exposure and vulnerability (density of assets, level of degradation of terrestrial and marine buffer ecosystems),
coastal hazards (flooding, shoreline erosion, salinization), in-situ responses (hard engineered coastal defences, ecosystem
restoration or creation of new natural buffers areas, and subsidence management) and planned relocation. Planned
relocation refers to managed retreat or resettlement. Forced displacement is not considered in this assessment. The term
response is used here instead of adaptation because some responses, such as retreat, may or may not be considered to beadaptation. Panel (d): Left - Heat-sensitive human health outcomes under three scenarios of adaptation effectiveness.
The diagrams are truncated at the nearest whole ºC within the range of temperature change in 2100 under three SSP
scenarios. Right - Risks associated with food security due to climate change and patterns of socio-economic development.
Risks to food security include availability and access to food, including population at risk of hunger, food price increases
and increases in disability adjusted life years attributable to childhood underweight. Risks are assessed for two contrasted
socio-economic pathways (SSP1 and SSP3) excluding the effects of targeted mitigation and adaptation policies. Panel(e): Examples of regional key risks. Risks identified are of at least medium confidence level. Key risks are identified basedon the magnitude of adverse consequences (pervasiveness of the consequences, degree of change, irreversibility ofconsequences, potential for impact thresholds or tipping points, potential for cascading effects beyond systemboundaries); likelihood of adverse consequences; temporal characteristics of the risk; and ability to respond to the risk,e.g., by adaptation. {WGI Figure SPM.8; WGII SPM B.3.3, WGII Figure SPM.3, WGII SM 16.6, WGII SM 16.7.4;
SRCCL Figure SPM.2; SROCC Figure SPM.3d; SROCC SPM.5a; SROCC 4SM; SRCCL 7.3.1; SRCCL 7SM} (CSB.2)[END FIGURE 3.3 HERE]

3.1.3

The Likelihood and Risks of Abrupt and Irreversible Change

The likelihood of abrupt and irreversible changes and their impacts increase with higher global
warming levels (high confidence). As warming levels increase, so do the risks of species extinction or
irreversible loss of biodiversity in ecosystems such as forests (medium confidence), coral reefs (very highconfidence) and in Arctic regions (high confidence). Risks associated with large-scale singular events or
tipping points, such as ice sheet instability or ecosystem loss from tropical forests, transition to high risk
between 1.5°C–2.5°C (medium confidence) and to very high risk between 2.5°C–4°C (low confidence). The
response of biogeochemical cycles to anthropogenic perturbations can be abrupt at regional scales andirreversible on decadal to century time scales (high confidence). The probability of crossing uncertain regional
thresholds increases with further warming (high confidence). {WGI SPM C.3.2, WGI Box TS.9, WGI TS.2.6;
WGII Figure SPM.3, WGII SPM B.3.1, WGII SPM B.4.1, WGII SPM B.5.2, WGII Table TS.1, WGII TS.C.1,
WGII TS.C.13.3; SROCC SPM B.4}
Sea level rise is unavoidable for centuries to millennia due to continuing deep ocean warming and ice
sheet melt, and sea levels will remain elevated for thousands of years (high confidence). Global mean sea
level rise will continue in the 21st century (virtually certain), with projected regional relative sea level rise
within 20% of the global mean along two-thirds of the global coastline (medium confidence). The magnitude,
the rate, the timing of threshold exceedances, and the long-term commitment of sea level rise depend on
emissions, with higher emissions leading to greater and faster rates of sea level rise. Due to relative sea levelrise, extreme sea level events that occurred once per century in the recent past are projected to occur at least
annually at more than half of all tide gauge locations by 2100 and risks for coastal ecosystems, people andinfrastructure will continue to increase beyond 2100 (high confidence). At sustained warming levels between
2°C and 3°C, the Greenland and West Antarctic ice sheets will be lost almost completely and irreversibly overmultiple millennia (limited evidence). The probability and rate of ice mass loss increase with higher global
surface temperatures (high confidence). Over the next 2000 years, global mean sea level will rise by about 2–
3 m if warming is limited to 1.5°C and 2–6 m if limited to 2°C (low confidence). Projections of multi-millennial
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global mean sea level rise are consistent with reconstructed levels during past warm climate periods: global
mean sea level was very likely 5–25 m higher than today roughly 3 million years ago, when global temperatures
were 2.5°C–4°C higher than 1850–1900 (medium confidence). Further examples of unavoidable changes in
the climate system due to multi-decadal or longer response timescales include continued glacier melt (veryhigh confidence) and permafrost carbon loss (high confidence). {WGI SPM B.5.2, WGI SPM B.5.3, WGISPM B.5.4, WGI SPM C.2.5, WGI Box TS.4, WGI Box TS.9, WGI 9.5.1; WGII TS C.5; SROCC SPM B.3,
SROCC SPM B.6, SROCC SPM B.9} (Figure 3.4)
The probability of low-likelihood outcomes associated with potentially very large impacts increases withhigher global warming levels (high confidence). Warming substantially above the assessed very likely range
for a given scenario cannot be ruled out, and there is high confidence this would lead to regional changes
greater than assessed in many aspects of the climate system. Low-likelihood, high-impact outcomes could
occur at regional scales even for global warming within the very likely assessed range for a given GHG
emissions scenario. Global mean sea level rise above the likely range – approaching 2 m by 2100 and in excess
of 15 m by 2300 under a very high GHG emissions scenario (SSP5-8.5) (low confidence) – cannot be ruledout due to deep uncertainty in ice-sheet processes66 and would have severe impacts on populations in low
elevation coastal zones. If global warming increases, some compound extreme events67 will become more
frequent, with higher likelihood of unprecedented intensities, durations or spatial extent (high confidence). The
Atlantic Meridional Overturning Circulation is very likely to weaken over the 21st century for all consideredscenarios (high confidence), however an abrupt collapse is not expected before 2100 (medium confidence). If
such a low probability event were to occur, it would very likely cause abrupt shifts in regional weather patterns
and water cycle, such as a southward shift in the tropical rain belt, and large impacts on ecosystems and humanactivities. A sequence of large explosive volcanic eruptions within decades, as have occurred in the past, is a
low-likelihood high-impact event that would lead to substantial cooling globally and regional climate
perturbations over several decades {WGI SPM B.5.3, WGI SPM C.3, WGI SPM C.3.1, WGI SPM C.3.2, WGISPM C.3.3, WGI SPM C.3.4, WGI SPM C.3.5, WGI Figure SPM.8, WGI Box TS.3, WGI Figure TS.6, WGI
Box 9.4; WGII SPM B.4.5, WGII SPM C.2.8; SROCC SPM B.2.7}. (Figure 3.4, Cross-Section Box.2)

3.2

Long-term Adaptation Options and Limits

With increasing warming, adaptation options will become more constrained and less effective. At higher
levels of warming, losses and damages will increase, and additional human and natural systems willreach adaptation limits. Integrated, cross-cutting multi-sectoral solutions increase the effectiveness ofadaptation. Maladaptation can create lock-ins of vulnerability, exposure and risks but can be avoided
by long-term planning and the implementation of adaptation actions that are flexible, multi-sectoral
and inclusive. (high confidence)
The effectiveness of adaptation to reduce climate risk is documented for specific contexts, sectors andregions (high confidence) and will decrease with increasing warming (high confidence)68. For example,
common adaptation responses in agriculture – adopting improved cultivars and agronomic practices, andchanges in cropping patterns and crop systems – will become less effective from 2°C to higher levels ofwarming (high confidence). The effectiveness of most water-related adaptation options to reduce projectedrisks declines with increasing warming (high confidence). Adaptations for hydropower and thermo-electric
power generation are effective in most regions up to 1.5°C–2°C, with decreasing effectiveness at higher levelsof warming (medium confidence). Ecosystem-based Adaptation is vulnerable to climate change impacts, witheffectiveness declining with increasing global warming (high confidence). Globally, adaptation options related
to agroforestry and forestry have a sharp decline in effectiveness at 3°C, with a substantial increase in residual
risk (medium confidence). {WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.10, WGII
Figure TS.6 Panel (e), 4.7.2}
66 This outcome is characterised by deep uncertainty: Its likelihood defies quantitative assessment but is considered due to its highpotential impact. {WGI Box TS.1; WGII Cross-Chapter Box DEEP}67 See Annex I: Glossary. Examples of compound extreme events are concurrent heatwaves and droughts or compound flooding. {WGISPM Footnote 18}
68 There are limitations to assessing the full scope of adaptation options available in the future since not all possible future adaptation
responses can be incorporated in climate impact models, and projections of future adaptation depend on currently available technologies
or approaches. {WGII 4.7.2}
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IPCC AR6 SYRWith increasing global warming, more limits to adaptation will be reached (high confidence) and losses
and damages, strongly concentrated among the poorest vulnerable populations, will increase (highconfidence). Already below 1.5°C, autonomous and evolutionary adaptation responses by terrestrial andaquatic ecosystems will increasingly face hard limits (high confidence) (Section 2.1.2). Above 1.5°C, someecosystem-based adaptation measures will lose their effectiveness in providing benefits to people as theseecosystems will reach hard adaptation limits (high confidence). Adaptation to address the risks of heat stress,
heat mortality and reduced capacities for outdoor work for humans face soft and hard limits across regions that
become significantly more severe at 1.5°C, and are particularly relevant for regions with warm climates (highconfidence). Above 1.5°C global warming level, limited freshwater resources pose potential hard limits for
Small Islands and for regions dependent on glacier and snow melt (medium confidence). By 2°C, soft limits
are projected for multiple staple crops, particularly in tropical regions (high confidence). By 3°C, soft limits
are projected for some water management measures for many regions, with hard limits projected for parts ofEurope (medium confidence). {WGII SPM C.3, WGII SPM C.3.3, WGII SPM C.3.4, WGII SPM C.3.5, WGII
TS.D.2.2, WGII TS.D.2.3; SR1.5 SPM B.6; SROCC SPM C.1}
Integrated, cross-cutting multi-sectoral solutions increase the effectiveness of adaptation. For example,
inclusive, integrated and long-term planning at local, municipal, sub-national and national scales, together witheffective regulation and monitoring systems and financial and technological resources and capabilities foster
urban and rural system transition. There are a range of cross-cutting adaptation options, such as disaster risk
management, early warning systems, climate services and risk spreading and sharing that have broad
applicability across sectors and provide greater benefits to other adaptation options when combined.
Transitioning from incremental to transformational adaptation, and addressing a range of constraints, primarily
in the financial, governance, institutional and policy domains, can help overcome soft adaptation limits.
However, adaptation does not prevent all losses and damages, even with effective adaptation and before
reaching soft and hard limits. (high confidence) {WGII SPM C.2, WGII SPM C.2.6, WGII SPM.C.2.13, WGIISPM C.3.1, WGII SPM.C.3.4, WGII SPM C.3.5, WGII Figure TS.6 Panel (e)}Maladaptive responses to climate change can create lock-ins of vulnerability, exposure and risks thatare difficult and expensive to change and exacerbate existing inequalities. Actions that focus on sectors
and risks in isolation and on short-term gains often lead to maladaptation. Adaptation options can become
maladaptive due to their environmental impacts that constrain ecosystem services and decrease biodiversity
and ecosystem resilience to climate change or by causing adverse outcomes for different groups, exacerbating
inequity. Maladaptation can be avoided by flexible, multi-sectoral, inclusive and long-term planning andimplementation of adaptation actions with benefits to many sectors and systems. (high confidence) {WGII
SPM C.4, WGII SPM.C.4.1, WGII SPM C.4.2, WGII SPM C.4.3}
Sea level rise poses a distinctive and severe adaptation challenge as it implies both dealing with slow
onset changes and increases in the frequency and magnitude of extreme sea level events (highconfidence). Such adaptation challenges would occur much earlier under high rates of sea level rise (highconfidence). Responses to ongoing sea level rise and land subsidence include protection, accommodation,
advance and planned relocation (high confidence). These responses are more effective if combined and/or
sequenced, planned well ahead, aligned with sociocultural values and underpinned by inclusive community
engagement processes (high confidence). Ecosystem-based solutions such as wetlands provide co-benefits forthe environment and climate mitigation, and reduce costs for flood defences (medium confidence), but havesite-specific physical limits, at least above 1.5ºC of global warming (high confidence) and lose effectivenessat high rates of sea level rise beyond 0.5–1 cm/yr (medium confidence). Seawalls can be maladaptive as theyeffectively reduce impacts in the short term but can also result in lock-ins and increase exposure to climate
risks in the long term unless they are integrated into a long-term adaptive plan (high confidence). {WGI SPM
C.2.5; WGII SPM C.2.8, WGII SPM C.4.1; WGII 13.10, WGII Cross-Chapter Box SLR; SROCC SPM B.9,
SROCC SPM C.3.2, SROCC Figure SPM.4, SROCC Figure SPM.5c} (Figure 3.4)
[START FIGURE 3.4 HERE]

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IPCC AR6 SYRFigure 3.4: Observed and projected global mean sea level change and its impacts, and time scales of coastal risk
management. Panel (a): Global mean sea level change in metres relative to 1900. The historical changes (black) are
observed by tide gauges before 1992 and altimeters afterwards. The future changes to 2100 and for 2150 (coloured lines
and shading) are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glaciermodels, and median values and likely ranges are shown for the considered scenarios. Relative to 1995–2014, the likely
global mean sea level rise by 2050 is between 0.15–0.23 m in the very low GHG emissions scenario (SSP1-1.9) and 0.20–
0.29 m in the very high GHG emissions scenario (SSP5-8.5); by 2100 between 0.28–0.55 m under SSP1-1.9 and 0.63–
1.01 m under SSP5-8.5; and by 2150 between 0.37–0.86 m under SSP1-1.9 and 0.98–1.88 m under SSP5-8.5 (medium
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confidence). Changes relative to 1900 are calculated by adding 0.158 m (observed global mean sea level rise from 1900
to 1995–2014) to simulated changes relative to 1995–2014. The future changes to 2300 (bars) are based on literatureassessment, representing the 17th–83rd percentile range for SSP1-2.6 (0.3–3.1 m) and SSP5-8.5 (1.7–6.8 m). Red dashedlines: Low-likelihood, high-impact storyline, including ice sheet instability processes. These indicate the potential impact
of deeply uncertain processes, and show the 83rd percentile of SSP5-8.5 projections that include low-likelihood, highimpact processes that cannot be ruled out; because of low confidence in projections of these processes, this is not part ofa likely range. IPCC AR6 global and regional sea level projections are hosted at https://sealevel.nasa.gov/ipcc-ar6-sealevel-projection-tool. The low-lying coastal zone is currently home to around 896 million people (nearly 11% of the 2020
global population), projected to reach more than one billion by 2050 across all five SSPs. Panel (b): Typical time scales
for the planning, implementation (dashed bars) and operational lifetime of current coastal risk-management measures(blue bars). Higher rates of sea level rise demand earlier and stronger responses and reduce the lifetime of measures(inset). As the scale and pace of sea level rise accelerates beyond 2050, long-term adjustments may in some locations bebeyond the limits of current adaptation options and for some small islands and low-lying coasts could be an existential
risk. {WGI SPM B.5, C.2.5, Figure SPM.8, 9.6; WGII SPM B.4.5, B.5.2, C.2.8, D.3.3, TS.D.7, Cross-Chapter Box SLR}
(CSB.2)[END FIGURE 3.4 HERE]

3.3

Mitigation Pathways

Limiting human-caused global warming requires net zero anthropogenic CO2 emissions. Pathways
consistent with 1.5°C and 2°C carbon budgets imply rapid, deep, and in most cases immediate GHG
emission reductions in all sectors (high confidence). Exceeding a warming level and returning (i.e.
overshoot) implies increased risks and potential irreversible impacts; achieving and sustaining global
net negative CO2 emissions would reduce warming (high confidence).
3.3.1

Remaining Carbon Budgets

Limiting global temperature increase to a specific level requires limiting cumulative net CO 2 emissions
to within a finite carbon budget69, along with strong reductions in other GHGs. For every 1000 GtCO2
emitted by human activity, global mean temperature rises by likely 0.27°C–0.63°C (best estimate of 0.45°C).
This relationship implies that there is a finite carbon budget that cannot be exceeded in order to limit warming
to any given level. {WGI SPM D.1, WGI SPM D.1.1; SR1.5 SPM C.1.3} (Figure 3.5)
The best estimates of the remaining carbon budget (RCB) from the beginning of 2020 for limiting
warming to 1.5°C with a 50% likelihood70 is estimated to be 500 GtCO2; for 2°C (67% likelihood) thisis 1150 GtCO2.71 Remaining carbon budgets have been quantified based on the assessed value of TCRE and
its uncertainty, estimates of historical warming, climate system feedbacks such as emissions from thawing
permafrost, and the global surface temperature change after global anthropogenic CO2 emissions reach net
zero, as well as variations in projected warming from non-CO2 emissions due in part to mitigation action. The
stronger the reductions in non-CO2 emissions the lower the resulting temperatures are for a given RCB or thelarger RCB for the same level of temperature change. For instance, the RCB for limiting warming to 1.5°C
with a 50% likelihood could vary between 300 to 600 GtCO2 depending on non-CO2 warming72. Limiting
warming to 2°C with a 67% (or 83%) likelihood would imply a RCB of 1150 (900) GtCO2 from the beginning

69 See Annex 1: Glossary.
70 This likelihood is based on the uncertainty in transient climate response to cumulative net CO

2 emissions and additional Earth system
feedbacks and provides the probability that global warming will not exceed the temperature levels specified. {WGI Table SPM.1}
71 Global databases make different choices about which emissions and removals occurring on land are considered anthropogenic. Most
countries report their anthropogenic land CO2 fluxes including fluxes due to human-caused environmental change (e.g., CO2
fertilisation) on ‘managed’ land in their National GHG inventories. Using emissions estimates based on these inventories, the remaining
carbon budgets must be correspondingly reduced. {WGIII SPM Footnote 9, WGIII TS.3, WGIII Cross-Chapter Box 6}
72 The central case RCB assumes future non-CO warming (the net additional contribution of aerosols and non-CO GHG) of around2
2
0.1°C above 2010–2019 in line with stringent mitigation scenarios. If additional non-CO2 warming is higher, the RCB for limiting
warming to 1.5°C with a 50% likelihood shrinks to around 300 GtCO2. If, however, additional non-CO2 warming is limited to only
0.05°C (via stronger reductions of CH4 and N2O through a combination of deep structural and behavioural changes, e.g., dietarychanges), the RCB could be around 600 GtCO2 for 1.5°C warming. {WGI Table SPM.2, WGI Box TS.7; WGIII Box 3.4}
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of 2020. To stay below 2°C with a 50% likelihood, the RCB is higher, i.e., 1350 GtCO273. {WGI SPM D.1.2,
WGI Table SPM.2; WGIII Box SPM.1, WGIII Box 3.4; SR1.5 SPM C.1.3}
If the annual CO2 emissions between 2020-2030 stayed, on average, at the same level as 2019, the resulting
cumulative emissions would almost exhaust the remaining carbon budget for 1.5°C (50%), and exhaust morethan a third of the remaining carbon budget for 2°C (67%) (Figure 3.5). Based on central estimates only,
historical cumulative net CO2 emissions between 1850 and 2019 (2400 ±240 GtCO2) amount to about fourfifths74 of the total carbon budget for a 50% probability of limiting global warming to 1.5°C (central estimate
about 2900 GtCO2) and to about two-thirds75 of the total carbon budget for a 67% probability to limit global
warming to 2°C (central estimate about 3550 GtCO2). {WGI Table SPM.2; WGIII SPM B.1.3, WGIII Table
2.1}
In scenarios with increasing CO2 emissions, the land and ocean carbon sinks are projected to be lesseffective at slowing the accumulation of CO2 in the atmosphere (high confidence). While natural land andocean carbon sinks are projected to take up, in absolute terms, a progressively larger amount of CO 2 underhigher compared to lower CO2 emissions scenarios, they become less effective, that is, the proportion ofemissions taken up by land and ocean decreases with increasing cumulative net CO 2 emissions (highconfidence). Additional ecosystem responses to warming not yet fully included in climate models, such as
GHG fluxes from wetlands, permafrost thaw, and wildfires, would further increase concentrations of thesegases in the atmosphere (high confidence). In scenarios where CO2 concentrations peak and decline during the
21st century, the land and ocean begin to take up less carbon in response to declining atmospheric CO 2
concentrations (high confidence) and turn into a weak net source by 2100 in the very low GHG emissions
scenario (medium confidence)76. {WGI SPM B.4, WGI SPM B.4.1, WGI SPM B.4.2, WGI SPM B.4.3}[START FIGURE 3.5 HERE]

73 When adjusted for emissions since previous reports, these RCB estimates are similar to SR1.5 but larger than AR5 values due tomethodological improvements. {WGI SPM D.1.3}
74 Uncertainties for total carbon budgets have not been assessed and could affect the specific calculated fractions.
75 See footnote 77.
76 These projected adjustments of carbon sinks to stabilisation or decline of atmospheric CO concentrations are accounted for in
2
calculations of remaining carbon budgets. {WGI SPM footnote 32}
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IPCC AR6 SYRFigure 3.5: Cumulative past, projected, and committed emissions, and associated global temperature changes.
Panel (a) Assessed remaining carbon budgets to limit warming more likely than not to 1.5°C, below 2°C with a 83% and
67% likelihood, compared to cumulative emissions corresponding to constant 2019 emissions until 2030, existing andplanned fossil fuel infrastructures (in GtCO2). For remaining carbon budgets, thin lines indicate the uncertainty due to thecontribution of non-CO2 warming. For lifetime emissions from fossil fuel infrastructure, thin lines indicate the assessedsensitivity range. Panel (b) Relationship between cumulative CO2 emissions and the increase in global surface
temperature. Historical data (thin black line) shows historical CO 2 emissions versus observed global surface temperature
increase relative to the period 1850–1900. The grey range with its central line shows a corresponding estimate of thehuman-caused share of historical warming. Coloured areas show the assessed very likely range of global surface
temperature projections, and thick coloured central lines show the median estimate as a function of cumulative CO2
emissions for the selected scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Projections until 2050 use
the cumulative CO2 emissions of each respective scenario, and the projected global warming includes the contribution
from all anthropogenic forcers. {WGI SPM D.1, WGI Figure SPM.10, WGI Table SPM.2; WGIII SPM B.1, WGIII SPM
B.7, WGIII 2.7; SR1.5 SPM C.1.3}
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IPCC AR6 SYR[END FIGURE 3.5 HERE][START TABLE 3.1 HERE]
Table 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG
emissions, projected net-zero timings and the resulting global warming outcomes. Pathways are categorised (columns),
according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before2100) and 2100 warming levels. Values shown are for the median [p50] and 5th–95th percentiles [p5–p95], noting that
not all pathways achieve net-zero CO2 or GHGs. {WGIII Table SPM.2}

1 Detailed explanations on the Table are provided in WGIII Box SPM.1 and WGIII Table SPM.2. The relationship between the temperature categories and
SSP/RCPs is discussed in Cross-Section Box 2. Values in the table refer to the 50th and [5th–95th] percentile values across the pathways falling within a given
category as defined in WGIII Box SPM.1. The three dots (…) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net-zero is
not reached). Based on the assessment of climate emulators in AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment

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IPCC AR6 SYRof the resulting warming of the pathways. For the ‘Temperature Change’ and ‘Likelihood’ columns, the non-bracketed values represent the 50th percentile acrossthe pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model emulator. For thebracketed ranges in the “likelihood” column, the median warming for every pathway in that category is calculated for each of the two climate model emulators(MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate emulators’ uncertainty. All global warming levels
are relative to 1850–1900.
2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4.
3 Global emission reductions in mitigation pathways are reported on a pathway-by-pathway basis relative to harmonised modelled global emissions in 2019 rather
than the global emissions reported in WGIII SPM Section B and WGIII Chapter 2; this ensures internal consistency in assumptions about emission sources andactivities, as well as consistency with temperature projections based on the physical climate science assessment by WGI (see WGIII SPM Footnote 49). Negativevalues (e.g., in C5, C6) represent an increase in emissions. The modelled GHG emissions in 2019 are 55 [53–58] GtCO2-eq, thus within the uncertainty ranges of
estimates for 2019 emissions [53-66] GtCO2-eq (see 2.1.1).
4 Emissions milestones are provided for 5-year intervals in order to be consistent with the underlying 5-year time-step data of the modelled pathways. Ranges insquare brackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile 5-year interval and the upper bound of the95th percentile 5-year interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones over the 21st century. Percentiles
reported
acrossallpathwaysinthat
category
include
those
that
do
not
reach
net
zero
before2100.
5 For cases where models do not report all GHGs, missing GHG species are infilled and aggregated into a Kyoto basket of GHG emissions in CO2-eq defined by
the 100-year global warming potential. For each pathway, reporting of CO2, CH4, and N2O emissions was the minimum required for the assessment of the climate
response and the assignment to a climate category. Emissions pathways without climate assessment are not included in the ranges presented here. See WGIII
Annex III.II.5.
6 Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively. They are based on harmonised net CO 2 emissions,ensuring consistency with the WG I assessment of the remaining carbon budget. {WGIII Box 3.4, WGIII SPM Footnote 50}[END TABLE 3.1 HERE]

3.3.2

Net Zero Emissions: Timing and Implications

From a physical science perspective, 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 of other GHG emissions (see Cross-Section Box 1). Global modelled pathways that reach andsustain net zero GHG emissions are projected to result in a gradual decline in surface temperature (highconfidence). Reaching net zero GHG emissions primarily requires deep reductions in CO2, methane, and other
GHG emissions, and implies net-negative CO2 emissions77. Carbon dioxide removal (CDR) will be necessary
to achieve net-negative CO2 emissions78. Achieving global net zero CO2 emissions, with remaining
anthropogenic CO2 emissions balanced by durably stored CO2 from anthropogenic removal, is a requirement
to stabilise CO2-induced global surface temperature increase (see 3.3.3) (high confidence). This is different
from achieving net zero GHG emissions, where metric-weighted anthropogenic GHG emissions (see CrossSection Box 1) equal CO2 removal (high confidence). Emissions pathways that reach and sustain net zero GHG
emissions defined by the 100-year global warming potential imply net-negative CO2 emissions and areprojected to result in a gradual decline in surface temperature after an earlier peak (high confidence). Whilereaching net-zero CO2 or net-zero GHG emissions requires deep and rapid reductions in gross emissions, thedeployment of CDR to counterbalance hard-to-abate residual emissions (e.g., some emissions from agriculture,aviation, shipping, and industrial processes) is unavoidable (high confidence). {WGI SPM D.1, WGI SPM
D.1.1, WGI SPM D.1.8; WGIII SPM C.2, WGIII SPM C.3, WGIII SPM C.11, WGIII Box TS.6; SR1.5 SPM
A.2.2}
In modelled pathways, the timing of net-zero CO2 emissions, followed by net-zero GHG emissions,depends on several variables, including the desired climate outcome, the mitigation strategy and thegases covered (high confidence). Global net zero CO2 emissions are reached in the early 2050s in pathways
that limit warming to 1.5°C (>50%) with no or limited overshoot, and around the early 2070s in pathways that
limit warming to 2°C (>67%). While non-CO2 GHG emissions are strongly reduced in all pathways that limit
warming to 2°C (>67%) or lower, residual emissions of CH4 and N2O and F-gases of about 8 [5–11] GtCO2eq/yr remain at the time of net zero GHG, counterbalanced by net negative CO 2 emissions. As a result, net
zero CO2 would be reached before net zero GHGs (high confidence). {WGIII SPM C.2, WGIII SPM C.2.3,
WGIII SPM C.2.4, WGIII Table SPM.2, WGIII 3.3} (Figure 3.6)

77 Net zero GHG emissions defined by the 100-year global warming potential. See footnote 12.
78 See section 3.3.3 and 3.4.1

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IPCC AR6 SYR[START FIGURE 3.6 HERE]

Figure 3.6: Total GHG, CO2 and CH4 emissions and timing of reaching net-zero in different mitigation pathways.
Top row: GHG, CO2 and CH4 emissions over time (in GtCO2eq) with historical emissions, projected emissions in linewith policies implemented until the end of 2020 (grey), and pathways consistent with temperature goals in colour (blue,
purple, and brown, respectively); Panel (a) (left) shows pathways that limit warming to 1.5°C (>50%) with no or limited
overshoot (C1) and Panel (b) (right) shows pathways that limit warming to 2°C (>66%) (C3). Bottom row: Panel (c)shows median (vertical line), likely (bar) and very likely (thin lines) timing of reaching net-zero GHG and CO2 emissions
for global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot (C1) (left) or 2°C (>67%)(C3) (right). {WGIII Figure SPM.5}[END FIGURE 3.6 HERE]

3.3.3

Sectoral Contributions to Mitigation

All global modelled pathways that limit warming to 2°C (>67%) or lower by 2100 involve rapid anddeep and in most cases immediate GHG emissions reductions in all sectors (see also 4.1, 4.5). Reductionsin GHG emissions in industry, transport, buildings, and urban areas can be achieved through a combination ofenergy efficiency and conservation and a transition to low-GHG technologies and energy carriers (see also
4.5, Figure 4.4). Socio-cultural options and behavioural change can reduce global GHG emissions of end-use
sectors, with most of the potential in developed countries, if combined with improved infrastructure design
and access. (high confidence) {WGIII SPM C.3, WGIII SPM C.5, WGIII SPM C.6, WGIII SPM C.7.3, WGIII
SPM C.8, WGIII SPM C.10.2}

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IPCC AR6 SYRGlobal modelled mitigation pathways reaching net zero CO2 and GHG emissions include transitioning
from fossil fuels without carbon capture and storage (CCS) to very low- or zero-carbon energy sources,
such as renewables or fossil fuels with CCS, demand-side measures and improving efficiency, reducing
non-CO2 GHG emissions, and CDR.79. In global modelled pathways that limit warming to 2°C or below,
almost all electricity is supplied from zero or low-carbon sources in 2050, such as renewables or fossil fuelswith CO2 capture and storage, combined with increased electrification of energy demand. Such pathways meetenergy service demand with relatively low energy use, through e.g., enhanced energy efficiency andbehavioural changes and increased electrification of energy end use. Modelled global pathways limiting global
warming to 1.5°C (>50%) with no or limited overshoot generally implement such changes faster than pathways
limiting global warming to 2°C (>67%). (high confidence) {WGIII SPM C.3, WGIII SPM C.3.2, WGIII SPM
C.4, WGIII TS.4.2; SR1.5 SPM C.2.2}
AFOLU mitigation options, when sustainably implemented, can deliver large-scale GHG emission
reductions and enhanced CO2 removal; however, barriers to implementation and trade-offs may result
from the impacts of climate change, competing demands on land, conflicts with food security andlivelihoods, the complexity of land ownership and management systems, and cultural aspects (see 3.4.1).
All assessed modelled pathways that limit warming to 2°C (>67%) or lower by 2100 include land-based
mitigation and land-use change, with most including different combinations of reforestation, afforestation,
reduced deforestation, and bioenergy. However, accumulated carbon in vegetation and soils is at risk fromfuture loss (or sink reversal) triggered by climate change and disturbances such as flood, drought, fire, or pest
outbreaks, or future poor management. (high confidence) {WGI SPM B.4.3; WGII SPM B.2.3, WGII SPM
B.5.4; WGIII SPM C.9, WGIII SPM C.11.3, WGIII SPM D.2.3, WGIII TS.4.2, 3.4; SR1.5 SPM C.2.5; SRCCLSPM B.1.4, SRCCL SPM B.3, SRCCL SPM B.7}
In addition to deep, rapid, and sustained emission reductions, CDR can fulfil three complementaryroles: lowering net CO2 or net GHG emissions in the near term; counterbalancing ‘hard-to-abate’
residual emissions (e.g., some emissions from agriculture, aviation, shipping, industrial processes) tohelp reach net zero CO2 or GHG emissions, and achieving net negative CO2 or GHG emissions if
deployed at levels exceeding annual residual emissions (high confidence). CDR methods vary in terms of
their maturity, removal process, time scale of carbon storage, storage medium, mitigation potential, cost, cobenefits, impacts and risks, and governance requirements (high confidence). Specifically, maturity ranges fromlower maturity (e.g., ocean alkalinisation) to higher maturity (e.g., reforestation); removal and storage potential
ranges from lower potential (<1 Gt CO2/yr, e.g., blue carbon management) to higher potential (>3 Gt CO2/yr,e.g., agroforestry); costs range from lower cost (e.g., –45 to 100 USD/tCO2 for soil carbon sequestration) tohigher cost (e.g., 100–300 USD/tCO2 for direct air carbon dioxide capture and storage) (medium confidence).
Estimated storage timescales vary from decades to centuries for methods that store carbon in vegetation andthrough soil carbon management, to ten thousand years or more for methods that store carbon in geologicalformations (high confidence). Afforestation, reforestation, improved forest management, agroforestry and soil
carbon sequestration are currently the only widely practiced CDR methods (high confidence). Methods andlevels of CDR deployment in global modelled mitigation pathways vary depending on assumptions about
costs, availability and constraints (high confidence). {WGIII SPM C.3.5, WGIII SPM C.11.1, WGIII SPM
C.11.4}79 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage isavailable. When CO2 is captured directly from the atmosphere (DACCS), or from biomass (BECCS), CCS provides the storage
component of these CDR methods. CO2 capture and subsurface injection is a mature technology for gas processing and enhanced oil
recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production,
where it is a critical mitigation option. The technical geological storage capacity is estimated to be on the order of 1000 GtCO2, which
is more than the CO2 storage requirements through 2100 to limit global warming to 1.5°C, although the regional availability ofgeological storage could be a limiting factor. If the geological storage site is appropriately selected and managed, it is estimated that
the CO2 can be permanently isolated from the atmosphere. Implementation of CCS currently faces technological, economic,
institutional, ecological environmental and socio-cultural barriers. Currently, global rates of CCS deployment are far below those inmodelled pathways limiting global warming to 1.5°C to 2°C. Enabling conditions such as policy instruments, greater public support
and technological innovation could reduce these barriers. (high confidence) {WGIII SPM C.4.6}
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3.3.4

Longer Report

IPCC AR6 SYROvershoot Pathways: Increased Risks and Other Implications

Exceeding a specific remaining carbon budget results in higher global warming. Achieving andsustaining net negative global CO2 emissions could reverse the resulting temperature exceedance (highconfidence). Continued reductions in emissions of short-lived climate forcers, particularly methane, after peaktemperature has been reached, would also further reduce warming (high confidence). Only a small number ofthe most ambitious global modelled pathways limit global warming to 1.5°C (>50%) without overshoot. {WGI
SPM D.1.1, WGI SPM D.1.6, WGI SPM D.1.7; WGIII TS.4.2}
Overshoot of a warming level results in more adverse impacts, some irreversible, and additional risks forhuman and natural systems compared to staying below that warming level, with risks growing with themagnitude and duration of overshoot (high confidence). Compared to pathways without overshoot, societies
and ecosystems would be exposed to greater and more widespread changes in climatic impact-drivers, such as
extreme heat and extreme precipitation, with increasing risks to infrastructure, low-lying coastal settlements,
and associated livelihoods (high confidence). Overshooting 1.5°C will result in irreversible adverse impacts
on certain ecosystems with low resilience, such as polar, mountain, and coastal ecosystems, impacted by icesheet glacier melt, or by accelerating and higher committed sea level rise (high confidence). Overshootincreases the risks of severe impacts, such as increased wildfires, mass mortality of trees, drying of peatlands,
thawing of permafrost and weakening natural land carbon sinks; such impacts could increase releases of GHGs
making temperature reversal more challenging (medium confidence). {WGI SPM C.2, WGI SPM C.2.1, WGISPM C.2.3; WGII SPM B.6, WGII SPM B.6.1, WGII SPM B.6.2; SR1.5 3.6}
The larger the overshoot, the more net negative CO2 emissions needed to return to a given warming level (highconfidence). Reducing global temperature by removing CO2 would require net negative emissions of 220
GtCO2 (best estimate, with a likely range 160-370 GtCO2) for every tenth of a degree (medium confidence).
Modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot reach median values ofcumulative net-negative emissions of 220 GtCO2 by 2100, pathways that return warming to 1.5°C (>50%)
after high overshoot reach median values of 360 GtCO2 (high confidence).80 More rapid reduction in CO2 andnon-CO2 emissions, particularly methane, limits peak warming levels and reduces the requirement for net
negative CO2 emissions and CDR, thereby reducing feasibility and sustainability concerns, and social andenvironmental risks (high confidence). {WGI SPM D.1.1; WGIII SPM B.6.4, WGIII SPM C.2, WGIII SPM
C.2.2, WGIII Table SPM.2}

3.4

Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development

Mitigation and adaptation can lead to synergies and trade-offs with sustainable development (highconfidence). Accelerated and equitable mitigation and adaptation bring benefits from avoiding
damages from climate change and are critical to achieving sustainable development (high confidence).
Climate resilient development81 pathways are progressively constrained by every increment offurther warming (very high confidence). There is a rapidly closing window of opportunity to secure a
liveable and sustainable future for all (very high confidence).

3.4.1

Synergies and trade-offs, costs and benefits

Mitigation and adaptation options can lead to synergies and trade-offs with other aspects of sustainable
development (see also Section 4.6, Figure 4.4). Synergies and trade-offs depend on the pace and magnitudeof changes and the development context including inequalities, with consideration of climate justice. The
potential or effectiveness of some adaptation and mitigation options decreases as climate change intensifies(see also Sections 3.2, 3.3.3, 4.5). (high confidence) {WGII SPM C.2, WGII Figure SPM.4b; WGIII SPM D.1,
WGIII SPM D.1.2, WGIII TS.5.1, WGIII Figure SPM.8; SR1.5 SPM D.3, SR1.5 SPM D.4; SRCCL SPM B.2,
SRCCL SPM B.3, SRCCL SPM D.3.2, SRCCL Figure SPM.3}
80 Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C, high overshoot by 0.1°C-0.3°C, in both cases for

up to several decades. {WGIII Box SPM.1}
81 See Annex I: Glossary.
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In the energy sector, transitions to low-emission systems will have multiple co-benefits, including
improvements in air quality and health. There are potential synergies between sustainable development and,for instance, energy efficiency and renewable energy. (high confidence) {WGIII SPM C.4.2, WGIII SPM
D.1.3}For agriculture, land, and food systems, many land management options and demand-side response options(e.g., dietary choices, reduced post-harvest losses, reduced food waste) can contribute to eradicating poverty
and eliminating hunger while promoting good health and wellbeing, clean water and sanitation, and life onland (medium confidence). In contrast, certain adaptation options that promote intensification of production,such as irrigation, may have negative effects on sustainability (e.g., for biodiversity, ecosystem services,groundwater depletion, and water quality) (high confidence). {WGII TS.D.5.5; WGIII SPM D.10; SRCCLSPM B.2.3}
Reforestation, improved forest management, soil carbon sequestration, peatland restoration and coastal blue
carbon management are examples of CDR methods that can enhance biodiversity and ecosystem functions,employment and local livelihoods, depending on context.82 However, afforestation or production of biomass
crops for bioenergy with carbon dioxide capture and storage or biochar can have adverse socio-economic andenvironmental impacts, including on biodiversity, food and water security, local livelihoods and the rights ofIndigenous Peoples, especially if implemented at large scales and where land tenure is insecure. (highconfidence) {WGII SPM B.5.4, WGII SPM C.2.4; WGIII SPM C.11.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5;
SRCCL SPM B.3, SRCCL SPM B.7.3, SRCCL Figure SPM.3}
Modelled pathways that assume using resources more efficiently or shift global development towards
sustainability include fewer challenges, such as dependence on CDR and pressure on land and biodiversity,and have the most pronounced synergies with respect to sustainable development (high confidence). {WGIII
SPM C.3.6; SR1.5 SPM D.4.2}
Strengthening climate change mitigation action entails more rapid transitions and higher up-front
investments, but brings benefits from avoiding damages from climate change and reduced adaptation
costs. The aggregate effects of climate change mitigation on global GDP (excluding damages from climatechange and adaptation costs) are small compared to global projected GDP growth. Projected estimates ofglobal aggregate net economic damages and the costs of adaptation generally increase with global warming
level. (high confidence) {WGII SPM B.4.6, WGII TS.C.10; WGIII SPM C.12.2, WGIII SPM C.12.3}
Cost-benefit analysis remains limited in its ability to represent all damages from climate change, including
non-monetary damages, or to capture the heterogeneous nature of damages and the risk of catastrophic
damages (high confidence). Even without accounting for these factors or for the co-benefits of mitigation, theglobal benefits of limiting warming to 2°C exceed the cost of mitigation (medium confidence). This finding isrobust against a wide range of assumptions about social preferences on inequalities and discounting over time
(medium confidence). Limiting global warming to 1.5°C instead of 2°C would increase the costs of mitigation,
but also increase the benefits in terms of reduced impacts and related risks (see 3.1.1, 3.1.2) and reduced
adaptation needs (high confidence)83. {WGII SPM B.4, WGII SPM B.6; WGIII SPM C.12, WGIII SPM
C.12.2, WGIII SPM C.12.3 WGIII Box TS.7; SR1.5 SPM B.3, SR1.5 SPM B.5, SR1.5 SPM B.6}
Considering other sustainable development dimensions, such as the potentially strong economic benefits onhuman health from air quality improvement, may enhance the estimated benefits of mitigation (medium
confidence). The economic effects of strengthened mitigation action vary across regions and countries,
depending notably on economic structure, regional emissions reductions, policy design and level ofinternational cooperation (high confidence). Ambitious mitigation pathways imply large and sometimes
disruptive changes in economic structure, with implications for near-term actions (Section 4.2), equity (Section
4.4), sustainability (Section 4.6), and finance (Section 4.8) (high confidence). {WGIII SPM C.12.2, WGIIISPM D.3.2, WGIII TS.4.2}
82 The impacts, risks, and co-benefits of CDR deployment for ecosystems, biodiversity and people will be highly variable dependingon the method, site-specific context, implementation and scale (high confidence). {WGIII SPM C.11.2}
83 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5°C. {WGIII SPM FOOTNOTE 68}
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3.4.2

Longer Report

IPCC AR6 SYRAdvancing Integrated Climate Action for Sustainable Development

An inclusive, equitable approach to integrating adaptation, mitigation and development can advancesustainable development in the long term (high confidence). Integrated responses can harness synergies forsustainable development and reduce trade-offs (high confidence)}. Shifting development pathways towards
sustainability and advancing climate resilient development is enabled when governments, civil society and theprivate sector make development choices that prioritise risk reduction, equity and justice, and when decisionmaking processes, finance and actions are integrated across governance levels, sectors and timeframes (veryhigh confidence) (see also Figure 4.2). Inclusive processes involving local knowledge and Indigenous
Knowledge increase these prospects (high confidence). However, opportunities for action differ substantiallyamong and within regions, driven by historical and ongoing patterns of development (very high confidence).
Accelerated financial support for developing countries is critical to enhance mitigation and adaptation action(high confidence). {WGII SPM C.5.4, WGII SPM D.1, WGII SPM D.1.1, WGII SPM D.1.2, WGII SPM D.2,
WGII SPM D.3, WGII SPM D.5, WGII SPM D.5.1, WGII SPM D.5.2; WGIII SPM D.1, WGIII SPM D.2,
WGIII SPM D.2.4, WGIII SPM E.2.2, WGIII SPM E.2.3, WGIII SPM E.5.3, WGIII Cross-Chapter Box 5}
Policies that shift development pathways towards sustainability can broaden the portfolio of available
mitigation and adaptation responses (medium confidence). Combining mitigation with action to shiftdevelopment pathways, such as broader sectoral policies, approaches that induce lifestyle or behaviourchanges, financial regulation, or macroeconomic policies can overcome barriers and open up a broader rangeof mitigation options (high confidence). Integrated, inclusive planning and investment in everyday decisionmaking about urban infrastructure can significantly increase the adaptive capacity of urban and rural
settlements. Coastal cities and settlements play an important role in advancing climate resilient development
due to the high number of people living in the Low Elevation Coastal Zone, the escalating and climate
compounded risk that they face, and their vital role in national economies and beyond (high confidence).
{WGII SPM.D.3, WGII SPM D.3.3; WGIII SPM E.2, WGIII SPM E.2.2; SR1.5 SPM D.6}
Observed adverse impacts and related losses and damages, projected risks, trends in vulnerability, andadaptation limits demonstrate that transformation for sustainability and climate resilient development
action is more urgent than previously assessed (very high confidence). Climate resilient development
integrates adaptation and GHG mitigation to advance sustainable development for all. Climate resilient
development pathways have been constrained by past development, emissions and climate change and areprogressively constrained by every increment of warming, in particular beyond 1.5°C (very high confidence).
Climate resilient development will not be possible in some regions and sub-regions if global warming exceeds
2°C (medium confidence). Safeguarding biodiversity and ecosystems is fundamental to climate resilient
development, but biodiversity and ecosystem services have limited capacity to adapt to increasing global
warming levels, making climate resilient development progressively harder to achieve beyond 1.5°C
warming (very high confidence). {WGII SPM D.1, WGII SPM D.1.1, WGII SPM D.4, WGII SPM D.4.3,
WGII SPM D.5.1; WGIII SPM D.1.1}
The cumulative scientific evidence is unequivocal: climate change is a threat to human well-being andplanetary health (very high confidence). Any further delay in concerted anticipatory global action on
adaptation and mitigation will miss a brief and rapidly closing window of opportunity to secure a
liveable and sustainable future for all (very high confidence). Opportunities for near-term action areassessed in the following section. {WGII SPM D.5.3; WGIII SPM D.1.1}

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IPCC AR6 SYRSection 4: Near-Term Responses in a Changing Climate
4.1

The Timing and Urgency of Climate Action

Deep, rapid and sustained mitigation and accelerated implementation of adaptation reduces the risksof climate change for humans and ecosystems. In modelled pathways that limit warming to 1.5°C(>50%) with no or limited overshoot and in those that limit warming to 2°C (>67%) and assume
immediate action, global GHG emissions are projected to peak in the early 2020s followed by rapidand deep reductions. As adaptation options often have long implementation times, accelerated
implementation of adaptation, particularly in this decade, is important to close adaptation gaps. (highconfidence)
The magnitude and rate of climate change and associated risks depend strongly on near-term mitigation
and adaptation actions (very high confidence). Global warming is more likely than not to reach 1.5°C
between 2021 and 2040 even under the very low GHG emission scenarios (SSP1-1.9), and likely or very likely
to exceed 1.5°C under higher emissions scenarios84. Many adaptation options have medium or high feasibility
up to 1.5°C (medium to high confidence, depending on option), but hard limits to adaptation have already beenreached in some ecosystems and the effectiveness of adaptation to reduce climate risk will decrease withincreasing warming (high confidence). Societal choices and actions implemented in this decade determine theextent to which medium- and long-term pathways will deliver higher or lower climate resilient development(high confidence). Climate resilient development prospects are increasingly limited if current greenhouse gas
emissions do not rapidly decline, especially if 1.5°C global warming is exceeded in the near-term (highconfidence). Without urgent, effective and equitable adaptation and mitigation actions, climate change
increasingly threatens the health and livelihoods of people around the globe, ecosystem health, andbiodiversity, with severe adverse consequences for current and future generations (high confidence). {WGISPM B.1.3, WGI SPM B.5.1, WGI SPM B.5.2; WGII SPM A, WGII SPM B.4, WGII SPM C.2, WGII SPM
C.3.3, WGII Figure SPM.4, WGII SPM D.1, WGII SPM D.5, WGIII SPM D.1.1 SR1.5 SPM D.2.2}. (CrossSection Box.2, Figure 2.1, Figure 2.3)
In modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot and in thosethat limit warming to 2°C (>67%), assuming immediate actions, global GHG emissions are projected topeak in the early 2020s followed by rapid and deep GHG emissions reductions (high confidence) 85. In
pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, net global GHG emissions areprojected to fall by 43% [34–60%]86 below 2019 levels by 2030,60% [49–77%] by 2035, 69% [58-90%] by2040 and 84% [73-98%] (high confidence) (Section 2.3.1, Table 2.2, Figure 2.5, Table 3.1)87. Global modelled
pathways that limit warming to 2°C (>67%) have reductions in GHG emissions below 2019 levels of 21% [1–42]% by 2030, 35% [22–55%] by 2035, 46% [34-63%] by 2040 and 64% [53-77%] by 2050 88(highconfidence). Global GHG emissions associated with NDCs announced prior to COP26 would make it likelythat warming would exceed 1.5°C (high confidence) and limiting warming to 2°C (>67%) would then imply arapid acceleration of emission reductions during 2030–2050, around 70% faster than in pathways where
immediate action is taken to limit warming to 2°C (>67%) (medium confidence) (Section 2.3.1) Continued
investments in unabated high-emitting infrastructure89 and limited development and deployment of lowemitting alternatives prior to 2030 would act as barriers to this acceleration and increase feasibility risks (highconfidence). {WGIII SPM B.6.3, WGIII Chapter 3.5.2, WGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1,
WGIII SPM C1.1, Table SPM.2} (Cross-Section Box.2)
84In the near term (2021–2040), the 1.5°C global warming level is very likely to be exceeded under the very high GHG emissions

scenario (SSP5-8.5), likely to be exceeded under the intermediate and high GHG emissions scenarios (SSP2-4.5, SSP3-7.0), more likely
than not to be exceeded under the low GHG emissions scenario (SSP1-2.6) and more likely than not to be reached under the very low
GHG emissions scenario (SSP1-1.9). The best estimates [and very likely ranges] of global warming for the different scenarios in thenear-term are: 1.5°C [1.2°C–1.7°C] (SSP1-1.9); 1.5°C [1.2°C–1.8°C] (SSP1-2.6); 1.5°C [1.2°C–1.8°C] (SSP2-4.5); 1.5°C [1.2°C–
1.8°C] (SSP3-7.0); and 1.6°C [1.3°C–1.9°C] (SSP5-8.5). {WGI SPM B.1.3, WGI Table SPM.1} (Cross-Section Box.2)
85 Values in parentheses indicate the likelihood of limiting warming to the level specified (see Cross-Section Box.2).
86 Median and very likely range [5th to 95th percentile] {WGIII SPM footnote 30}.
87 These numbers for CO2 are 48% [36-69] in 2030, 65% [50-96%] in 2035, 80% [61-109%] in 2040 and 99 [79-119%] in 2050.
88 These numbers for CO2 are 22% [1-44] in 2030, 37% [21-59%] in 2035, 51% [36-70%] in 2040 and 73 [55-90%] in 2050
89 In this context, ‘unabated fossil fuels’ refers to fossil fuels produced and used without interventions that substantially reduce theamount of GHG emitted throughout the life cycle; for example, capturing 90% or more CO2 from power plants, or 50–80% of fugitive
methane emissions from energy supply {WGIII SPM footnote 54}.
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All global modelled pathways that limit warming to 2°C (>67%) or lower by 2100 involve reductions inboth net CO2 emissions and non-CO2 emissions (see Figure 3.6) (high confidence). For example, inpathways that limit warming to 1.5°C (>50%) with no or limited overshoot, global CH4 (methane) emissions
are reduced by 34% [21–57%] below 2019 levels by 2030 and by 44% [31–63%] in 2040 (high confidence).
Global CH4 emissions are reduced by 24% [9–53%] below 2019 levels by 2030 and by 37% [20–60%] in 2040
in modelled pathways that limit warming to 2°C with action starting in 2020 (>67%) (high confidence).
{WGIII SPM C1.2, WGIII Table SPM.2, WGIII Chapter 3.3; SR1.5 SPM C.1, SR1.5 SPM C.1.2} (CrossSection Box.2)
All global modelled pathways that limit warming to 2°C (>67%) or lower by 2100 involve GHG emission
reductions in all sectors (high confidence). The contributions of different sectors vary across modelled
mitigation pathways. In most global modelled mitigation pathways, emissions from land-use, land-use change
and forestry, via reforestation and reduced deforestation, and from the energy supply sector reach net zero CO2emissions earlier than the buildings, industry and transport sectors (Figure 4.1). Strategies can rely on
combinations of different options (Figure 4.1, Section 4.5), but doing less in one sector needs to becompensated by further reductions in other sectors if warming is to be limited. (high confidence) {WGIII SPM
C.3, WGIII SPM C.3.1, WGIII SPM 3.2, WGIII SPM C.3.3} (Cross-Section Box.2)
Without rapid, deep and sustained mitigation and accelerated adaptation actions, losses and damages
will continue to increase, including projected adverse impacts in Africa, LDCs, SIDS, Central and SouthAmerica90, Asia and the Arctic, and will disproportionately affect the most vulnerable populations (highconfidence). {WGII SPM C.3.5; WGII SPM B.2.4; WGII Global to Regional Atlas Annex A1.15, A1.27;
WGII 12.2; WGII 10. Box 10.6; WGII TS D.7.5; WGII CCB6 ES; SR1.5 SPM B.5.3; SR 1.5 SPM B.5.7;
SRCCL A.5.6} (Figure 3.2; Figure 3.3)

[START FIGURE 4.1 HERE]

90 The southern part of Mexico is included in the climatic subregion South Central America (SCA) for WGI. Mexico is assessed as partof North America for WGII. The climate change literature for the SCA region occasionally includes Mexico, and in those cases WGII
assessment makes reference to Latin America. Mexico is considered part of Latin America and the Caribbean for WGIII. {WGII 12.1.1,
WGIII AII.1.1}
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IPCC AR6 SYRFigure 4.1: Sectoral emissions in pathways that limit warming to 1.5°C. Panel (a) shows sectoral CO2 and non-CO2
emissions in global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot. The horizontal
lines illustrate halving 2015 emissions (base year of the pathways) (dashed) and reaching net-zero emissions (solid line).
The range shows the 5–95th percentile of the emissions across the pathways. The timing strongly differs by sector, with
the CO2 emissions from the electricity/fossil fuel industries sector and land-use change generally reaching net zero
earlier. Non-CO2 emissions from agriculture are also substantially reduced compared to pathways without climate policy
but do not typically reach zero. Panel (b) Although all pathways include strongly reduced emissions, there are different
pathways as indicated by the illustrative mitigation pathways used in IPCC WGIII. The pathways emphasise routes
consistent with limiting warming to 1.5°C with a high reliance on net negative emissions (IMP-Neg), high resource
efficiency (IMP-LD), a focus on sustainable development (IMP-SP) or renewables (IMP-Ren) and consistent with 2°C
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based on a less rapid introduction of mitigation measures followed by a subsequent gradual strengthening (IMP-GS).
Positive (solid filled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways arecompared to GHG emissions from the year 2019. The category “energy supply (including electricity)” includes bioenergy
with carbon capture and storage and direct air carbon capture and storage. {WGIII Box TS.5, 3.3, 3.4, 6.6, 10.3, 11.3}(Cross-Section Box 2)[END FIGURE 4.1 HERE]

4.2

Benefits of Strengthening Near-Term Action

Accelerated implementation of adaptation will improve well-being by reducing losses and damages,
especially for vulnerable populations. Deep, rapid and sustained mitigation actions would reduce
future adaptation costs and losses and damages, enhance sustainable development co-benefits, avoid
locking-in emission sources, and reduce stranded assets and irreversible climate changes. These nearterm actions involve higher up-front investments and disruptive changes, which can be moderated bya range of enabling conditions and removal or reduction of barriers to feasibility. (high confidence)
Accelerated implementation of adaptation responses will bring benefits to human well-being (highconfidence) (Section 4.3). As adaptation options often have long implementation times, long-term planningand accelerated implementation, particularly in this decade, is important to close adaptation gaps, recognisingthat constraints remain for some regions. The benefits to vulnerable populations would be high (see Section
4.4). (high confidence) {WGI SPM B.1, WGI SPM B.1.3, WGI SPM B.2.2, WGI SPM B.3; WGII SPM C.1.1,
WGII SPM C.1.2, WGII SPM C.2, WGII SPM C.3.1, WGII SPM Figure SPM.4b; SROCC SPM C.3.4,
SROCC Figure 3.4, SROCC SPM Figure 5}
Near-term actions that limit global warming to close to 1.5°C would substantially reduce projected losses
and damages related to climate change in human systems and ecosystems, compared to higher warming
levels, but cannot eliminate them all (very high confidence). The magnitude and rate of climate change andassociated risks depend strongly on near-term mitigation and adaptation actions, and projected adverse impacts
and related losses and damages escalate with every increment of global warming (very high confidence).
Delayed mitigation action will further increase global warming which will decrease the effectiveness of many
adaptation options, including Ecosystem-based Adaptation and many water-related options, as well as
increasing mitigation feasibility risks, such as for options based on ecosystems (high confidence).
Comprehensive, effective, and innovative responses integrating adaptation and mitigation can harness
synergies and reduce trade-offs between adaptation and mitigation, as well as in meeting requirements forfinancing (very high confidence) (see Section 4.5, 4.6, 4.8 and 4.9) {WGII SPM B.3, WGII SPM B.4, WGIISPM B.6.2, WGII SPM C.2, WGII SPM C.3, WGII SPM D.1, WGII SPM D.4.3, WGII SPM D.5, WG II TS
D.1.4, WG II TS.D.5, WGII TS D.7.5, WGIII SPM B.6.3,WGIII SPM B.6.4, WGIII SPM C.9, WGIII SPM
D.2, WGIII SPM E.13, SR1.5 SPM C.2.7, SR1.5 D.1.3, SR1.5 D.5.2}.
Mitigation actions will have other sustainable development co-benefits (high confidence). Mitigation will
improve air quality and human health in the near-term notably because many air pollutants are co-emitted by
GHG emitting sectors and because methane emissions leads to surface ozone formation (high confidence) The
benefits from air quality improvement include prevention of air pollution-related premature deaths, chronic
diseases and damages to ecosystems and crops. The economic benefits for human health from air quality
improvement arising from mitigation action can be of the same order of magnitude as mitigation costs, andpotentially even larger (medium confidence). As methane has a short lifetime but is a potent GHG, strong,
rapid and sustained reductions in methane emissions can limit near-term warming and improve air quality by
reducing global surface ozone (high confidence). {WGI SPM D.1.7, WGI SPM D.2.2, WGI Chapter 6.7, WGITS Box TS.7, WGI Chapter 6 Box 6.2, WGI Figures 6.3, 6.16, 6.17, WGII TS.D.8.3, WGII Cross-Chapter
Box HEALTH, WGII Chapter 5 ES, WGII Chapter 7 ES; WGII Chapter 7.3.1.2; WGIII Figure SPM.8, WGIII
SPM C.2.3, WGIII SPM C.4.2, WGIII TS.4.2}

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IPCC AR6 SYRChallenges from delayed adaptation and mitigation actions include the risk of cost escalation, lock-in of
infrastructure, stranded assets, and reduced feasibility and effectiveness of adaptation and mitigation
options (high confidence). The continued installation of unabated fossil fuel91 infrastructure will ‘lockin’ GHG emissions (high confidence). Limiting global warming to 2°C or below will leave a substantial
amount of fossil fuels unburned and could strand considerable fossil fuel infrastructure (high confidence), with
globally discounted value projected to be around USD1–4 trillion from 2015 to 2050 (medium confidence).
Early actions would limit the size of these stranded assets, whereas delayed actions with continued investments
in unabated high-emitting infrastructure and limited development and deployment of low-emitting alternativesprior to 2030 would raise future stranded assets to the higher end of the range – acting as barriers and increase
political economy feasibility risks that may jeopardise efforts to limit global warming (high confidence).
{WGIII SPM B.6.3, WGIII SPM C.4, WGIII Box TS.8}.
Scaling-up near-term climate actions (Section 4.1) will mobilise a mix of low-cost and high-cost options.
High-cost options, as in energy and infrastructure, are needed to avoid future lock-ins, foster innovation andinitiate transformational changes (Figure 4.4). Climate resilient development pathways in support ofsustainable development for all are shaped by equity, and social and climate justice (very high confidence).
Embedding effective and equitable adaptation and mitigation in development planning can reduce
vulnerability, conserve and restore ecosystems, and enable climate resilient development. This is especiallychallenging in localities with persistent development gaps and limited resources. (high confidence) {WGII
SPM C.5, WGII SPM D1; WGIII TS.5.2, WGIII Section 8.3.1, WGIII Section 8.3.4, WGIII Section 8.4.1,
WGIII Section 8.6}.
Scaling-up climate action may generate disruptive changes in economic structure with distributional
consequences and need to reconcile divergent interests, values and worldviews, within and between
countries. Deeper fiscal, financial, institutional and regulatory reforms can offset such adverse effects andunlock mitigation potentials. Societal choices and actions implemented in this decade will determine the extent
to which medium and long-term development pathways will deliver higher or lower climate resilient
development outcomes. (high confidence) {WGII SPM D.2, WGII SPM D.5, WGII Box TS.8; WGIII SPM
D.3, WGIII SPM E.2, WGIII SPM E.3, WGIII SPM E.4, WGIII TS.2, WGIII TS.4.1, WGIII TS.6.4, WGIII
Chapter 15.2, WGIII Chapter 15.6,}
Enabling conditions would need to be strengthened in the near-term and barriers reduced or removed
to realise opportunities for deep and rapid adaptation and mitigation actions and climate resilient
development (high confidence) (Figure 4.2). These enabling conditions are differentiated by national,
regional and local circumstances and geographies, according to capabilities, and include: equity and andinclusion in climate action (see Section 4.4), rapid and far-reaching transitions in sectors and system (seeSection 4.5), measures to achieve synergies and reduce trade-offs with sustainable development goals (seeSection 4.6), governance and policy improvements (see Section 4.7), access to finance, improved international
cooperation and technology improvements (see Section 4.8), and integration of near-term actions acrosssectors, systems and regions (see Section 4.9). {WGII SPM D.2, WGIII SPM E.1, WGIII SPM E.2}
Barriers to feasibility would need to be reduced or removed to deploy mitigation and adaptation optionsat scale. Many limits to feasibility and effectiveness of responses can be overcome by addressing a range ofbarriers, including economic, technological, institutional, social, environmental and geophysical. The
feasibility and effectiveness of options increase with integrated, multi-sectoral solutions that differentiate
responses based on climate risk, cut across systems and address social inequities. Strengthened near-term
actions in modelled cost-effective pathways that limit global warming to 2°C or lower, reduce the overall risk
to the feasibility of the system transitions, compared to modelled pathways with delayed or uncoordinatedaction. (high confidence) {WGII SPM C.2, WGII SPM C.3, WGII SPM C.5; WGIII SPM E.1, WGIII SPM
E.1.3}.

91 In this context, ‘unabated fossil fuels’ refers to fossil fuels produced and used without interventions that substantially reduce theamount of GHG emitted throughout the life cycle; for example, capturing 90% or more CO2 from power plants, or 50–80% of fugitive
methane emissions from energy supply {WGIII SPM footnote 54}.
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Figure 4.2: The illustrative development pathways (red to green) and associated outcomes (right panel) show that there
is a rapidly narrowing window of opportunity to secure a liveable and sustainable future for all. Climate resilient
development is the process of implementing greenhouse gas mitigation and adaptation measures to support sustainable
development. Diverging pathways illustrate that interacting choices and actions made by diverse government, private
sector and civil society actors can advance climate resilient development, shift pathways towards sustainability, andenable lower emissions and adaptation. Diverse knowledges and values include cultural values, Indigenous Knowledge,
local knowledge, and scientific knowledge. Climatic and non-climatic events, such as droughts, floods or pandemics,
pose more severe shocks to pathways with lower climate resilient development (red to yellow) than to pathways withhigher climate resilient development (green). There are limits to adaptation and adaptive capacity for some human andnatural systems at global warming of 1.5°C, and with every increment of warming, losses and damages will increase. The
development pathways taken by countries at all stages of economic development impact GHG emissions and hence shape
mitigation challenges and opportunities, which vary across countries and regions. Pathways and opportunities for action
are shaped by previous actions (or inactions and opportunities missed, dashed pathway), and enabling and constraining
conditions (left panel), and take place in the context of climate risks, adaptation limits and development gaps. The longer
emissions reductions are delayed, the fewer effective adaptation options. {WGI SPM B.1, WGII SPM B.1-B.5, WGIISPM C.2-5, WGII SPM D.1-5, WGII Figure SPM.3; WGII Figure SPM.4, WGII Figure SPM.5; WGII TS.D.5, WGII
Chapter 3.1, WGII Chapter 3.2, WGII Chapter 3.4; WGII Chapter 4.2, WGII Figure 4.4, WGII Chapter 4.5, WGII Chapter
4.6, WGII Chapter 4.9, WGIII SPM A, WGIII SPM B1, WGIII SPM B.3, WGIII SPM B.6, WGIII SPM C.4, WGIII SPM
D1-3, WGIII SPM E.1, WGIII SPM E.2, WGIII SPM E.4, WGIII SPM E.5, WGIII FigureTS.1, TS.7, Box TS. 3, Box
TS.8, Cross-Working Group Box 1, WGIII Cross-Chapter Box 5 in Chapter 4, SR1.5 SPM D1-6, SRCCL SPM D.3}

[END FIGURE 4.2 HERE]

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IPCC AR6 SYRIntegrating ambitious climate actions with macroeconomic policies under global uncertainty would
provide benefits (high confidence). This encompasses three main directions: (a) economy-wide
mainstreaming packages supporting options to improved sustainable low-emission economic recovery,
development and job creation programs (Sections 4.4, 4.5, 4.6, 4.8, 4.9) (b) safety nets and social protectionin the transition (Section 4.4, 4.7); and (c) broadened access to finance, technology and capacity-building andcoordinated support to low-emission infrastructure (‘leap-frog’ potential), especially in developing regions,and under debt stress (high confidence). (Section 4.8) {WGII SPM C.2, WGII SPM C.4.1, WGII SPM D.1.3,
WGII SPM D.2, WGII SPM D.3.2, WGII SPM E.2.2, WGII SPM E.4, WGII SPM TS.2, WGII SPM TS.5.2,
WGII TS.6.4, WGII TS.15, WGII TS Box TS.3 WGIII SPM B.4.2, WGIII SPM C.5.4, WGIII SPM C.6.2,
WGIII SPM C.12.2, WGIII SPM D.3.4, WGIII SPM E.4.2, WGIII SPM E.4.5, WGIII SPM E.5.2, WGIII SPM
E.5.3, WGIII TS.1, WGIII Box TS.15, WGIII Chapter 15.2, WGIII Cross-Chapter Box 1 on COVID in Chapter
1}
4.3

Near-Term Risks

Many changes in the climate system, including extreme events, will become larger in the near termwith increasing global warming (high confidence). Multiple climatic and non-climatic risks willinteract, resulting in increased compounding and cascading impacts becoming more difficult tomanage (high confidence). Losses and damages will increase with increasing global warming (veryhigh confidence), while strongly concentrated among the poorest vulnerable populations (highconfidence). Continuing with current unsustainable development patterns would increase exposureand vulnerability of ecosystems and people to climate hazards (high confidence).
Global warming will continue to increase in the near term (2021–2040) mainly due to increased
cumulative CO2 emissions in nearly all considered scenarios and pathways. In the near term, every
region in the world is projected to face further increases in climate hazards (medium to high confidence,
depending on region and hazard), increasing multiple risks to ecosystems and humans (very highconfidence). In the near-term, natural variability92 will modulate human-caused changes, either attenuating or
amplifying projected changes, especially at regional scales, with little effect on centennial global warming.
Those modulations are important to consider in adaptation planning. Global surface temperature in any single
year can vary above or below the long-term human-induced trend, due to natural variability. By 2030, global
surface temperature in any individual year could exceed 1.5oC relative to 1850–1900 with a probability
between 40% and 60%, across the five scenarios assessed in WGI (medium confidence). The occurrence ofindividual years with global surface temperature change above a certain level does not imply that this global
warming level has been reached. If a large explosive volcanic eruption were to occur in the near-term93 , itwould temporarily and partially mask human-caused climate change by reducing global surface temperatureand precipitation, especially over land, for one to three years (medium confidence). {WGI SPM B.1.3, WGISPM B.1.4, WGI SPM C.1, WGI SPM C.2, WGI Cross-Section Box TS.1, WGI Cross-Chapter Box 4.1; WGIISPM B.3, WGII SPM B.3.1; WGIII Box SPM.1 Figure 1}.
The level of risk for humans and ecosystems will depend on near-term trends in vulnerability, exposure,level of socio-economic development and adaptation (high confidence). In the near-term, many climateassociated risks to natural and human systems depend more strongly on changes in these systems’ vulnerability
and exposure than on differences in climate hazards between emissions scenarios (high confidence). Future
exposure to climatic hazards is increasing globally due to socio-economic development trends including
growing inequality, and when urbanisation or migration increase exposure (high confidence). Urbanisation
increases hot extremes (very high confidence) and precipitation runoff intensity (high confidence). Increasing
urbanisation in low-lying and coastal zones will be a major driver of increasing exposure to extreme riverflow
events and sea level rise hazards, increasing risks (high confidence) (Figure 4.3). Vulnerability will also rise
rapidly in low-lying Small Island Developing States and atolls in the context of sea level rise (high confidence)(see Figure 3.4 and Figure 4.3). Human vulnerability will concentrate in informal settlements and rapidly
growing smaller settlements; and vulnerability in rural areas will be heightened by reduced habitability and
92 See Annex I: Glossary. The main internal variability phenomena include El Niño–Southern Oscillation, Pacific Decadal Variability

and Atlantic Multi-decadal Variability through their regional influence {WGI SPM footnote 37}. The internal variability of global
surface temperature in any single year is estimated to be about ±0.25°C (5–95% range, high confidence) {WGI SPM footnote 29}.
93 Based on 2500-year reconstructions, eruptions with a radiative forcing more negative than -1 Wm-2, related to the radiative effect of
volcanic stratospheric aerosols in the literature assessed in this report, occur on average twice per century. {WGI SPM footnote 38}
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IPCC AR6 SYRhigh reliance on climate-sensitive livelihoods (high confidence). Human and ecosystem vulnerability areinterdependent (high confidence). Vulnerability to climate change for ecosystems will be strongly influenced
by past, present, and future patterns of human development, including from unsustainable consumption andproduction, increasing demographic pressures, and persistent unsustainable use and management of land,
ocean, and water (high confidence). Several near-term risks can be moderated with adaptation (highconfidence). (see Section 4.5 and 3.2) {WGI SPM C.2.6; WGII SPM B.2, WGII SPM B.2.3, WGII SPM B.2.5,
WGII SPM B.3, WGII SPM B.3.2, WGII TS.C.5.2}
Principal hazards and associated risks expected in the near-term (at 1.5°C global warming) are:●

Increased intensity and frequency of hot extremes and dangerous heat-humidity conditions, withincreased human mortality, morbidity, and labour productivity loss (high confidence) {WGI SPM
B.2.2, WGI TS Figure TS.6; WGII SPM B.1.4, WGII SPM B.4.4, WGII SPM Figure SPM.2}.
● Increasing frequency of marine heatwaves will increase risks of biodiversity loss in the oceans,including from mass mortality events (high confidence) {WGI SPM B.2.3; WGII SPM B.1.2, WGIISPM Figure SPM.2; SROCC SPM B.5.1}● Near-term risks for biodiversity loss are moderate to high in forest ecosystems (medium confidence)and kelp and seagrass ecosystems (high to very high confidence) and are high to very high in Arctic
sea-ice and terrestrial ecosystems (high confidence) and warm-water coral reefs (very high confidence){WGII SPM B.3.1}.
● More intense and frequent extreme rainfall and associated flooding in many regions including coastaland other low-lying cities (medium to high confidence), and increased proportion of and peak windspeeds of intense tropical cyclones (high confidence) {WGI SPM B.2.4, WGI SPM C.2.2, WGI SPM
C.2.6, WGI Chapter 11.7}.
● High risks from dryland water scarcity, wildfire damage, and permafrost degradation (medium
confidence) {SRCCL SPM A.5.3.}.
● Continued sea level rise and increased frequency and magnitude of extreme sea level events
encroaching on coastal human settlements and damaging coastal infrastructure (high confidence),
committing low-lying coastal ecosystems to submergence and loss (medium confidence), expanding
land salinization (very high confidence), with cascading to risks to livelihoods, health, well-being,
cultural values, food and water security (high confidence) (Figure 3.4, 4.3). {WGI SPM C.2.5, WGISPM C.2.6; WGII SPM B.3.1, WGII SPM B.5.2; SRCCL SPM A.5.6; SROCC SPM B.3.4, SROCC
SPM 3.6, SROCC SPM B.9.1}.
● Climate change will significantly increase ill health and premature deaths from the near- to long-term(high confidence). Further warming will increase climate-sensitive food-borne, water-borne, andvector-borne disease risks (high confidence), and mental health challenges including anxiety and stress(very high confidence). {WGII SPM B.4.4}● Cryosphere-related changes in floods, landslides, and water availability have the potential to lead tosevere consequences for people, infrastructure and the economy in most mountain regions (highconfidence). {WGII TS C.4.2}● The projected increase in frequency and intensity of heavy precipitation (high confidence) will
increase rain-generated local flooding (medium confidence). {WGI Figure SPM.6; WGI SPM B.2.2;
WGII TS C.4.5}
Multiple climate change risks will increasingly compound and cascade in the near term (highconfidence). Many regions are projected to experience an increase in the probability of compound events withhigher global warming (high confidence) including concurrent heatwaves and drought. Risks to health andfood production will be made more severe from the interaction of sudden food production losses from heatand drought, exacerbated by heat-induced labour productivity losses (high confidence) (Figure 4.3). These
interacting impacts will increase food prices, reduce household incomes, and lead to health risks ofmalnutrition and climate-related mortality with no or low levels of adaptation, especially in tropical regions(high confidence). Concurrent and cascading risks from climate change to food systems, human settlements,
infrastructure and health will make these risks more severe and more difficult to manage, including wheninteracting with non-climatic risk drivers such as competition for land between urban expansion and foodproduction, and pandemics (high confidence). Loss of ecosystems and their services has cascading and longterm impacts on people globally, especially for Indigenous Peoples and local communities who are directly
dependent on ecosystems, to meet basic needs (high confidence). Increasing transboundary risks are projected
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across the food, energy and water sectors as impacts from weather and climate extremes propagate throughsupply-chains, markets, and natural resource flows (high confidence) and may interact with impacts from othercrises such as pandemics. Risks also arise from some responses intended to reduce the risks of climate change,
including risks from maladaptation and adverse side effects of some emissions reduction and carbon dioxide
removal measures, such as afforestation of naturally unforested land or poorly implemented bioenergy
compounding climate-related risks to biodiversity, food and water security, and livelihoods (high confidence).
(see Section 3.4.1 and 4.5) {WGI SPM.2.7; WGII SPM B.2.1, WGII SPM B.5, WGII SPM B.5.1, WGII SPM
B.5.2, WGII SPM B.5.3, WGII SPM B.5.4, WGII Cross-Chapter Box COVID in Chapter 7; WGIII SPM
C.11.2; SRCCL SPM A.5, SRCCL SPM A.6.5} (Figure 4.3)
With every increment of global warming losses and damages will increase (very high confidence), become
increasingly difficult to avoid and be strongly concentrated among the poorest vulnerable populations(high confidence). Adaptation does not prevent all losses and damages, even with effective adaptation andbefore reaching soft and hard limits. Losses and damages will be unequally distributed across systems, regions
and sectors and are not comprehensively addressed by current financial, governance and institutionalarrangements, particularly in vulnerable developing countries. (high confidence). {WGII SPM B.4, WGII SPM
C.3, WGII SPM C.3.5}[START FIGURE 4.3 HERE]

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IPCC AR6 SYRFigure 4.3: Every region faces more severe or frequent compound and/or cascading climate risks in the near term.
Changes in risk result from changes in the degree of the hazard, the population exposed, and the degree of vulnerabilityof people, assets, or ecosystems. Panel (a) Coastal flooding events affect many of the highly populated regions of theworld where large percentages of the population are exposed. The panel shows near-term projected increase of population
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population change), based on the intermediate GHG emissions scenario (SSP2-4.5) and current adaptation measures. Outmigration from coastal areas due to future sea level rise is not considered in the scenario. Panel (b) projected medianprobability in the year 2040 for extreme water levels resulting from a combination of mean sea level rise, tides and storm
surges, which have a historical 1% average annual probability. A peak-over-threshold (99.7%) method was applied to thehistorical tide gauge observations available in the Global Extreme Sea Level Analysis version 2 database, which is thesame information as WGI Figure 9.32, except here the panel uses relative sea level projections under SSP2-4.5 for theyear 2040 instead of 2050 The absence of a circle indicates an inability to perform an assessment due to a lack of data,
but does not indicate absence of increasing frequencies.
Panel (c) Climate hazards can initiate risk cascades that affect multiple sectors and propagate across regions following
complex natural and societal connections. This example of a compound heat wave and a drought event striking an
agricultural region shows how multiple risks are interconnected and lead to cascading biophysical, economic, and societal
impacts even in distant regions, with vulnerable groups such as smallholder farmers, children and pregnant womenparticularly impacted. {WGI Figure 9.32; WGII SPM B4.3, WGII SPM B1.3, WGII SPM B.5.1, WGII TS Figure TS.9,
WGII TS Figure TS.10 (c), WGII Fig 5.2, WGII TS.B.2.3, WGII TS.B.2.3, WGII TS.B.3.3, WGII 9.11.1.2}[END FIGURE 4.3 HERE]

4.4

Equity and Inclusion in Climate Change Action

Actions that prioritise equity, climate justice, social justice and inclusion lead to more sustainableoutcomes, co-benefits, reduce trade-offs, support transformative change and advance climate resilient
development. Adaptation responses are immediately needed to reduce rising climate risks, especiallyfor the most vulnerable. Equity, inclusion and just transitions are key to progress on adaptation anddeeper societal ambitions for accelerated mitigation. (high confidence)
Adaptation and mitigation actions, across scales, sectors and regions, that prioritise equity, climate
justice, rights-based approaches, social justice and inclusivity, lead to more sustainable outcomes,
reduce trade-offs, support transformative change and advance climate resilient development (highconfidence). Redistributive policies across sectors and regions that shield the poor and vulnerable,, social
safety nets, equity, inclusion and just transitions, at all scales can enable deeper societal ambitions and resolve
trade-offs with sustainable development goals.(SDGs), particularly education, hunger, poverty, gender andenergy access (high confidence). Mitigation efforts embedded within the wider development context canincrease the pace, depth and breadth of emission reductions (medium confidence). Equity, inclusion and justtransitions at all scales enable deeper societal ambitions for accelerated mitigation, and climate action more
broadly (high confidence). The complexity in risk of rising food prices, reduced household incomes, and healthand climate-related malnutrition (particularly maternal malnutrition and child undernutrition) and mortality
increases with little or low levels of adaptation (high confidence). {WGII SPM B.5.1, WGII SPM C.2.9, WGIISPM D.2.1, WGII TS Box TS.4; WGIII SPM D.3, WGIII SPM D.3.3, WGIII SPM WGIII SPM E.3, SR1.5
SPM D.4.5} (Figure 4.3c)
Regions and people with considerable development constraints have high vulnerability to climatic
hazards. Adaptation outcomes for the most vulnerable within and across countries and regions areenhanced through approaches focusing on equity, inclusivity, and rights-based approaches, including
3.3 to 3.6 billion people living in contexts that are highly vulnerable to climate change (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). Several risks can be moderated with adaptation (highconfidence). The largest adaptation gaps exist among lower income population groups (high confidence) andadaptation progress is unevenly distributed with observed adaptation gaps (high confidence). Present
development challenges causing high vulnerability are influenced by historical and ongoing patterns ofinequity such as colonialism, especially for many Indigenous Peoples and local communities (highconfidence). Vulnerability is exacerbated by inequity and marginalisation linked to gender, ethnicity, low
income or combinations thereof, especially for many Indigenous Peoples and local communities (highconfidence). {WGII SPM B.2, WGII SPM B.2.4, WGII SPM B.3.2, WGII SPM B.3.3, WGII SPM C.1, WGIISPM C.1.2, WGII SPM C.2.9}

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IPCC AR6 SYRMeaningful participation and inclusive planning, informed by cultural values, Indigenous Knowledge,
local knowledge, and scientific knowledge can help address adaptation gaps and avoid maladaptation(high confidence). Such actions with flexible pathways may encourage low-regret and timely actions (veryhigh confidence). Integrating climate adaptation into social protection programmes, including cash transfersand public works programmes, would increase resilience to climate change, especially when supported bybasic services and infrastructure (high confidence). {WGII SPM C.2.3, WGII SPM C.4.3, WGII SPM C.4.4,
WGII SPM C.2.9, WGII WPM D.3}
Equity, inclusion, just transitions, broad and meaningful participation of all relevant actors in decision
making at all scales enable deeper societal ambitions for accelerated mitigation, and climate action more
broadly, and build social trust, support transformative changes and an equitable sharing of benefits andburdens (high confidence). Equity remains a central element in the UN climate regime, notwithstanding
shifts in differentiation between states over time and challenges in assessing fair shares. Ambitious
mitigation pathways imply large and sometimes disruptive changes in economic structure, with significant
distributional consequences, within and between countries, including shifting of income and employment
during the transition from high to low emissions activities (high confidence). While some jobs may be lost,
low-emissions development can also open up opportunities to enhance skills and create jobs (high confidence).
Broadening equitable access to finance, technologies and governance that facilitate mitigation, andconsideration of climate justice can help equitable sharing of benefits and burdens, especially for vulnerable
countries and communities. {WGIII SPM D.3, WGIII SPM D.3.2, WGIII SPM D.3.3, WGIII SPM D.3.4,
WGIII TS Box TS.4}
Development priorities among countries also reflect different starting points and contexts, and enabling
conditions for shifting development pathways towards increased sustainability will therefore differ,giving rise to different needs (high confidence). Implementing just transition principles through collective
and participatory decision-making processes is an effective way of integrating equity principles into policies
at all scales depending on national circumstances, while in several countries just transition commissions, task
forces and national policies have been established (medium confidence). {WGIII SPM D.3.1, WGIII SPM
D.3.3}
Many economic and regulatory instruments have been effective in reducing emissions and practicalexperience has informed instrument design to improve them while addressing distributional goals andsocial acceptance (high confidence). The design of behavioural interventions, including the way that choices
are presented to consumers work synergistically with price signals, making the combination more effective(medium confidence). Individuals with high socio-economic status contribute disproportionately to emissions,and have the highest potential for emissions reductions, e.g., as citizens, investors, consumers, role models,and professionals (high confidence). There are options on design of instruments such as taxes, subsidies, prices,and consumption-based approaches, complemented by regulatory instruments to reduce high-emissions
consumption while improving equity and societal well-being (high confidence). Behaviour and lifestylechanges to help end-users adopt low-GHG-intensive options can be supported by policies, infrastructure andtechnology with multiple co-benefits for societal well-being (high confidence). Broadening equitable accessto domestic and international finance, technologies and capacity can also act as a catalyst for accelerating
mitigation and shifting development pathways in low-income contexts (high confidence). Eradicating extreme
poverty, energy poverty, and providing decent living standards to all in these regions in the context ofachieving sustainable development objectives, in the near-term, can be achieved without significant global
emissions growth (high confidence). Technology development, transfer, capacity building and financing can
support developing countries/ regions leapfrogging or transitioning to low-emissions transport systems thereby
providing multiple co-benefits (high confidence). Climate resilient development is advanced when actors workin equitable, just and enabling ways to reconcile divergent interests, values and worldviews, toward equitableand just outcomes (high confidence) {WGII D.2.1, WGIII SPM B.3.3, WGIII SPM.C.8.5, WGIII SPM C.10.2,
WGIII SPM C.10.4, WGIII SPM D.3.4, WGIII SPM E.4.2, WGIII TS.5.1, WGIII Chapter 5.4, WGIII Chapter
5.8, WGIII Chapter 15.2}

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Longer Report

IPCC AR6 SYRNear-Term Mitigation and Adaptation Actions

Rapid and far-reaching transitions across all sectors and systems are necessary to achieve deep andsustained emissions reductions and secure a liveable and sustainable future for all. These systemtransitions involve a significant upscaling of a wide portfolio of mitigation and adaptation options.
Feasible, effective and low-cost options for mitigation and adaptation are already available, withdifferences across systems and regions. (high confidence)
Rapid and far-reaching transitions across all sectors and systems are necessary to achieve deep
emissions reductions and secure a liveable and sustainable future for all (high confidence). Systemtransitions94 consistent with pathways that limit warming to 1.5°C (>50%) with no or limited overshoot are
more rapid and pronounced in the near-term than in those that limit warming to 2°C (>67%) (high confidence).
Such a systemic change is unprecedented in terms of scale, but not necessarily in terms of speed (medium
confidence). The system transitions make possible the transformative adaptation required for high levels ofhuman health and well-being, economic and social resilience, ecosystem health, and planetary health. {WGII
SPM A, WGII SPM Figure SPM.1; WGIII SPM C.3; SR1.5 SPM C.2, SR1.5 SPM C.2.1, SR1.5 SPM C.2,
SR1.5 SPM C.5}
Feasible, effective and low-cost options for mitigation and adaptation are already available (highconfidence) (Figure 4.4). Mitigation options costing USD100 per tCO2-eq or less could reduce global GHG
emissions by at least half the 2019 level by 2030 (options costing less than USD20 tCO2-eq–1 are estimated tomake up more than half of this potential) (high confidence) (Figure 4.4). The availability, feasibility95 andpotential of mitigation or effectiveness of adaptation options in the near-term differ across systems and regions(very high confidence). {WGII SPM C.2; WGIII SPM C.12, WGIII SPM E.1.1; SR1.5 SPM B.6}
Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in
end-use sectors by 40–70% by 2050 compared to baseline scenarios, while some regions andsocioeconomic groups require additional energy and resources. Demand-side mitigation encompasseschanges in infrastructure use, end-use technology adoption, and socio-cultural and behavioural change. (highconfidence) (Figure 4.4) {WGIII SPM C.10}[START FIGURE 4.4 HERE]

94

System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions andtransformative adaptation in all sectors. This report has a particular focus on the following system transitions: energy; industry; cities,
settlements and infrastructure; land, ocean, food and water; health and nutrition; and society, livelihood and economies { WGII SPM
A., WGII SPM Figure SPM.1, WGII SPM Figure SPM.4; SR1.5 SPM C.2,}
95 See Annex I: Glossary.
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IPCC AR6 SYRFigure 4.4: Multiple Opportunities for scaling up climate action. Panel (a) presents selected mitigation and adaptation
options across different systems. The left hand side of panel (a) shows climate responses and adaptation options assessed
for their multidimensional feasibility at global scale, in the near term and up to 1.5°C global warming. As literature above
1.5°C is limited, feasibility at higher levels of warming may change, which is currently not possible to assess robustly.
The term response is used here in addition to adaptation because some responses, such as migration, relocation andresettlement may or may not be considered to be adaptation. Migration, when voluntary, safe and orderly, allows reductionof risks to climatic and non-climatic stressors. Forest based adaptation includes sustainable forest management, forest
conservation and restoration, reforestation and afforestation. WASH refers to water, sanitation and hygiene. Six feasibility
dimensions (economic, technological, institutional, social, environmental and geophysical) were used to calculate thepotential feasibility of climate responses and adaptation options, along with their synergies with mitigation. For potential
feasibility and feasibility dimensions, the figure shows high, medium, or low feasibility. Synergies with mitigation are
identified as high, medium, and low. The right hand side of panel (a) provides an overview of selected mitigation options
and their estimated costs and potentials in 2030. Relative potentials and costs will vary by place, context and time and in
the longer term compared to 2030. Costs are net lifetime discounted monetary costs of avoided greenhouse gas emissions
calculated relative to a reference technology. The potential (horizontal axis) is the quantity of net GHG emission reductionthat can be achieved by a given mitigation option relative to a specified emission baseline. Net GHG emission reductions
are the sum of reduced emissions and/or enhanced sinks. The baseline used consists of current policy (around 2019)reference scenarios from the AR6 scenarios database (25/75 percentile values). The mitigation potentials are assessedindependently for each option and are not necessarily additive. Health system mitigation options are included mostly insettlement and infrastructure (e.g., efficient healthcare buildings) and cannot be identified separately. Fuel switching inindustry refers to switching to electricity, hydrogen, bioenergy and natural gas. The length of the solid bars represents the
mitigation potential of an option. Potentials are broken down into cost categories, indicated by different colours (seelegend). Only discounted lifetime monetary costs are considered. Where a gradual colour transition is shown, thebreakdown of the potential into cost categories is not well known or depends heavily on factors such as geographicallocation, resource availability, and regional circumstances, and the colours indicate the range of estimates. The uncertainty
in the total potential is typically 25–50%. When interpreting this figure, the following should be taken into account: (1)The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) being displaced, therate of new technology adoption, and several other factors; (2) Different options have different feasibilities beyond thecost aspects, which are not reflected in the figure; and (3) Costs for accommodating the integration of variable renewableenergy sources in electricity systems are expected to be modest until 2030, and are not included.
Panel (b) displays the indicative potential of demand-side mitigation options for 2050. Potentials are estimated based on
approximately 500 bottom-up studies representing all global regions. The baseline (white bar) is provided by the sectoralmean GHG emissions in 2050 of the two scenarios (IEA-STEPS and IP_ModAct) consistent with policies announced bynational governments until 2020. The green arrow represents the demand-side emissions reductions potentials. The range
in potential is shown by a line connecting dots displaying the highest and the lowest potentials reported in the literature.
Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns
enabled by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global
GHG emissions in end-use sectors (buildings, land transport, food) by 40–70% by 2050 compared to baseline scenarios,
while some regions and socioeconomic groups require additional energy and resources. The last row shows how demandside mitigation options in other sectors can influence overall electricity demand. The dark grey bar shows the projected
increase in electricity demand above the 2050 baseline due to increasing electrification in the other sectors. Based on abottom-up assessment, this projected increase in electricity demand can be avoided through demand-side mitigation
options in the domains of infrastructure use and socio-cultural factors that influence electricity usage in industry, landtransport, and buildings (green arrow).
{WGII SPM Figure SPM 4, WGII Cross-Chapter Box FEASIB in Chapter 18; WGIII SPM C.10, WGIII Chapter 12.2.1,
WGIII Chapter 12.2.2, WGIII Figure SPM 6, WGIII SPM Figure SPM 7}[END FIGURE 4.4 HERE]

4.5.1

Energy Systems

Rapid and deep reductions in GHG emissions require major energy system transitions (highconfidence). Adaptation options can help reduce climate-related risks to the energy system (very highconfidence). Net zero CO2 energy systems entail: a substantial reduction in overall fossil fuel use, minimaluse of unabated fossil fuels96, and use of Carbon Capture and Storage in the remaining fossil fuel systems;
96 In this context, ‘unabated fossil fuels’ refers to fossil fuels produced and used without interventions that substantially reduce theamount of GHG emitted throughout the life cycle; for example, capturing 90% or more CO2 from power plants, or 50–80% of fugitive
methane emissions from energy supply {WGIII SPM footnote 54}.
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IPCC AR6 SYRelectricity systems that emit no net CO2; widespread electrification; alternative energy carriers in applications
less amenable to electrification; energy conservation and efficiency; and greater integration across the energy
system (high confidence). Large contributions to emissions reductions can come from options costing less than
USD20 tCO2-eq–1, including solar and wind energy, energy efficiency improvements, and CH4 (methane)emissions reductions (from coal mining, oil and gas, and waste) (medium confidence).97 Many of these
response options are technically viable and are supported by the public (high confidence). Maintaining
emission-intensive systems may, in some regions and sectors, be more expensive than transitioning to low
emission systems (high confidence) {WGII SPM C.2.10; WGIII SPM C.4.1, WGIII SPM C.4.2, WGIII SPM
C.12.1, WGIII SPM E.1.1, WGIII TS.5.1}.
Climate change and related extreme events will affect future energy systems, including hydropower
production, bioenergy yields, thermal power plant efficiencies, and demands for heating and cooling (highconfidence). The most feasible energy system adaptation options support infrastructure resilience, reliable
power systems and efficient water use for existing and new energy generation systems (very high confidence).
Adaptations for hydropower and thermo-electric power generation are effective in most regions up to 1.5°C to
2°C, with decreasing effectiveness at higher levels of warming (medium confidence). Energy generation
diversification (e.g., wind, solar, small-scale hydroelectric) and demand side management (e.g., storage andenergy efficiency improvements) can increase energy reliability and reduce vulnerabilities to climate change,
especially in rural populations (high confidence). Climate responsive energy markets, updated design standards
on energy assets according to current and projected climate change, smart-grid technologies, robusttransmission systems and improved capacity to respond to supply deficits have high feasibility in the mediumto long-term, with mitigation co-benefits (very high confidence). {WGII SPM B.5.3, WGII SPM C.2.10;
WGIII TS.5.1}

4.5.2

Industry

There are several options to reduce industrial emissions that differ by type of industry; many industries
are disrupted by climate change, especially from extreme events (high confidence). Reducing industry
emissions will entail coordinated action throughout value chains to promote all mitigation options, including
demand management, energy and materials efficiency, circular material flows, as well as abatement
technologies and transformational changes in production processes (high confidence). Light industry andmanufacturing can be largely decarbonized through available abatement technologies (e.g., material efficiency,
circularity), electrification (e.g., electrothermal heating, heat pumps), and switching to low- and zero-GHG
emitting fuels (e.g., hydrogen, ammonia, and bio-based and other synthetic fuels) (high confidence), while
deep reduction of cement process emissions will rely on cementitious material substitution and the availabilityof Carbon Capture and Storage (CCS) until new chemistries are mastered (high confidence). Reducing
emissions from the production and use of chemicals would need to rely on a life cycle approach, including
increased plastics recycling, fuel and feedstock switching, and carbon sourced through biogenic sources, and,depending on availability, Carbon Capture and Utilisation (CCU), direct air CO2 capture, as well as CCS (highconfidence). Action to reduce industry sector emissions may change the location of GHG-intensive industries
and the organisation of value chains, with distributional effects on employment and economic structure(medium confidence). {WGII TS.B.9.1, WGII Chapter 16.5.2 WGIII SPM C.5, WGIII SPM C.5.2, WGIII
SPM C.5.3, WGIII TS.5.5}
Many industrial and service sectors are negatively affected by climate change through supply and operational
disruptions, especially from extreme events (high confidence), and will require adaptation efforts. Water
intensive industries (e.g., mining) can undertake measures to reduce water stress, such as water recycling andreuse, using brackish or saline sources, working to improve water use efficiency. However, residual risks willremain, especially at higher levels of warming (medium confidence). (Section 3.2) {WGII TS.B.9.1, WGII
Chapter 16.5.2, WGII Chapter 4.6.3}

97 The mitigation potentials and mitigation costs of individual technologies in a specific context or region may differ greatly from theprovided estimates (medium confidence) {WGIII SPM C.12.1}.
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4.5.3

Longer Report

IPCC AR6 SYRCities, Settlements and Infrastructure

Urban systems are critical for achieving deep emissions reductions and advancing climate resilient
development, particularly when this involves integrated planning that incorporates physical, naturaland social infrastructure (high confidence). Deep emissions reductions and integrated adaptation actions areadvanced by: integrated, inclusive land use planning and decision-making; compact urban form by co-locatingjobs and housing; reducing or changing urban energy and material consumption; electrification in combination
with low emissions sources; improved water and waste management infrastructure; and enhancing carbon
uptake and storage in the urban environment (e.g. bio-based building materials, permeable surfaces and urban
green and blue infrastructure). Cities can achieve net-zero emissions if emissions are reduced within andoutside of their administrative boundaries through supply chains, creating beneficial cascading effects acrossother sectors. (high confidence). {WGII SPM C.5.6, WGII SPM D.1.3, WGII SPM D.3; WGIII SPM C.6,
WGIII SPM C.6.2, WGIII TS 5.4, SR1.5 SPM C.2.4}
Considering climate change impacts and risks (e.g., through climate services) in the design and planning ofurban and rural settlements and infrastructure is critical for resilience and enhancing human well-being.
Effective mitigation can be advanced at each of the design, construction, retrofit, use and disposal stages forbuildings. Mitigation interventions for buildings include: at the construction phase, low-emission construction
materials, highly efficient building envelope and the integration of renewable energy solutions; at the usephase, highly efficient appliances/equipment, the optimisation of the use of buildings and their supply with
low-emission energy sources; and at the disposal phase, recycling and re-using construction materials.
Sufficiency98 measures can limit the demand for energy and materials over the lifecycle of buildings andappliances. (high confidence) {WGII SPM C.2.5; WGIII SPM C.7.2}.
Transport-related GHG emissions can be reduced by demand-side options and low-GHG emissions
technologies. Changes in urban form, reallocation of street space for cycling and walking, digitalisation (e.g.,
teleworking) and programs that encourage changes in consumer behaviour (e.g. transport, pricing) can reducedemand for transport services and support the shift to more energy efficient transport modes (high confidence).
Electric vehicles powered by low-emissions electricity offer the largest decarbonisation potential for landbased transport, on a life cycle basis (high confidence). Costs of electrified vehicles are decreasing and theiradoption is accelerating, but they require continued investments in supporting infrastructure to increase scaleof deployment (high confidence). The environmental footprint of battery production and growing concerns
about critical minerals can be addressed by material and supply diversification strategies, energy and material
efficiency improvements, and circular material flows (medium confidence). Advances in battery technologies
could facilitate the electrification of heavy-duty trucks and compliment conventional electric rail systems(medium confidence). Sustainable biofuels can offer additional mitigation benefits in land-based transport in
the short and medium term (medium confidence). Sustainable biofuels, low-emissions hydrogen, andderivatives (including synthetic fuels) can support mitigation of CO2 emissions from shipping, aviation, andheavy-duty land transport but require production process improvements and cost reductions (medium
confidence). Key infrastructure systems including sanitation, water, health, transport, communications andenergy will be increasingly vulnerable if design standards do not account for changing climate conditions (highconfidence) {WGII SPM B.2.5; WGIII SPM C.6.2, WGIII SPM C.8, WGIII SPM C.8.1, WGIII SPM C.8.2,
WGIII SPM C.10.2, WGIII SPM C.10.3, WGIII SPM C.10.4}.
Green/natural and blue infrastructure such as urban forestry, green roofs, ponds and lakes, and river restoration
can mitigate climate change through carbon uptake and storage, avoided emissions, and reduced energy use
while reducing risk from extreme events such as heatwaves, heavy precipitation and droughts, and advancing
co-benefits for health, wellbeing and livelihoods (medium confidence). Urban greening can provide local
cooling (very high confidence). Combining green/natural and grey/physical infrastructure adaptation responses
has potential to reduce adaptation costs and contribute to flood control, sanitation, water resourcesmanagement, landslide prevention and coastal protection (medium confidence). Globally, more financing isdirected at grey/physical infrastructure than green/natural infrastructure and social infrastructure (medium
confidence), and there is limited evidence of investment in informal settlements (medium to high confidence).
The greatest gains in well-being in urban areas can be achieved by prioritising finance to reduce climate risk
98 A set of measures and daily practices that avoid demand for energy, materials, land and water while delivering human well-being

for all within planetary boundaries {WGIII Annex I}
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for low-income and marginalised communities including people living in informal settlements (highconfidence). {WGII SPM C.2.5, WGII SPM C.2.6, WGII SPM C.2.7, WGII SPM D.3.2, WGII TS.E.1.4, WGII
Cross-Chapter Box FEAS; WGIII SPM C.6, WGIII SPM C.6.2, WGIII SPM D.1.3, WGIII SPM D.2.1}
Responses to ongoing sea level rise and land subsidence in low-lying coastal cities and settlements and small
islands include protection, accommodation, advance and planned relocation. These responses are more
effective if combined and/or sequenced, planned well ahead, aligned with sociocultural values anddevelopment priorities, and underpinned by inclusive community engagement processes. (high confidence){WGII SPM C.2.8}
4.5.4

Land, Ocean, Food, and Water

There is substantial mitigation and adaptation potential from options in agriculture, forestry and otherland use, and in the oceans, that could be upscaled in the near term across most regions (high confidence)(Figure 4.5). Conservation, improved management, and restoration of forests and other ecosystems offer thelargest share of economic mitigation potential, with reduced deforestation in tropical regions having the highest
total mitigation potential. Ecosystem restoration, reforestation, and afforestation can lead to trade-offs due tocompeting demands on land. Minimizing trade-offs required integrated approaches to meet multiple objectives
including food security. Demand-side measures (shifting to sustainable healthy diets and reducing foodloss/waste) and sustainable agricultural intensification can reduce ecosystem conversion and CH4 and N2Oemissions, and free up land for reforestation and ecosystem restoration. Sustainably sourced agriculture andforest products, including long-lived wood products, can be used instead of more GHG-intensive products inother sectors. Effective adaptation options include cultivar improvements, agroforestry, community-based
adaptation, farm and landscape diversification, and urban agriculture. These AFOLU response options require
integration of biophysical, socioeconomic and other enabling factors. The effectiveness of ecosystem-based
adaptation and most water-related adaptation options declines with increasing warming (see 3.2). (highconfidence). {WGII SPM C.2.1, WGII SPM C.2.2, WGII SPM C.2.5 WGIII SPM C.9.1; SRCCL SPM B.1.1,
SRCCL SPM B.5.4, SRCCL SPM D.1; SROCC SPM C}
Some options, such as conservation of high-carbon ecosystems (e.g., peatlands, wetlands, rangelands,
mangroves and forests), have immediate impacts while others, such as restoration of high-carbon ecosystems,
reclamation of degraded soils or afforestation, take decades to deliver measurable results (high confidence).
Many sustainable land management technologies and practices are financially profitable in three to ten years(medium confidence). {SRCCL SPM B.1.2, SRCCL SPM D.2.2}
Maintaining the resilience of biodiversity and ecosystem services at a global scale depends on effective
and equitable conservation of approximately 30–50% of Earth’s land, freshwater and ocean areas,
including currently near-natural ecosystems (high confidence). The services and options provided byterrestrial, freshwater, coastal and ocean ecosystems can be supported by protection, restoration, precautionary
ecosystem-based management of renewable resource use, and the reduction of pollution and other stressors(high confidence). {WGII SPM C.2.4, WGII SPM D.4; SROCC SPM C.2}
Large-scale land conversion for bioenergy, biochar, or afforestation can increase risks to biodiversity, waterand food security. In contrast, restoring natural forests and drained peatlands, and improving sustainability ofmanaged forests enhances the resilience of carbon stocks and sinks and reduces ecosystem vulnerability to
climate change. Cooperation, and inclusive decision making, with local communities and Indigenous Peoples,
as well as recognition of inherent rights of Indigenous Peoples, is integral to successful adaptation acrossforests and other ecosystems. (high confidence). {WGII SPM B.5.4, WGII SPM C.2.3, WGII SPM C.2.4;
WGIII SPM D.2.3; SRCCL B.7.3, SRCCL SPM C.4.3, SRCCL TS.7}
Natural rivers, wetlands and upstream forests reduce flood risk in most circumstances (high confidence).
Enhancing natural water retention such as by restoring wetlands and rivers, land use planning such as no build
zones or upstream forest management, can further reduce flood risk (medium confidence). For inland flooding,combinations of non-structural measures like early warning systems and structural measures like levees have
reduced loss of lives (medium confidence), but hard defences against flooding or sea level rise can also be
maladaptive (high confidence). {WGII SPM C.2.1, WGII SPM C.4.1, WGII SPM C.4.2, WGII SPM C.2.5}
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Protection and restoration of coastal ‘blue carbon’ ecosystems (e.g., mangroves, tidal marshes and seagrassmeadows) could reduce emissions and/or increase carbon uptake and storage (medium confidence). Coastal
wetlands protect against coastal erosion and flooding (very high confidence). Strengthening precautionary
approaches, such as rebuilding overexploited or depleted fisheries, and responsiveness of existing fisheries
management strategies reduces negative climate change impacts on fisheries, with benefits for regional
economies and livelihoods (medium confidence). Ecosystem-based management in fisheries and aquaculture
supports food security, biodiversity, human health and well-being (high confidence). {WGII SPM C.2.2, WGIISPM C.2; SROCC SPM C2.3, SROCC SPM C.2.4}
4.5.5

Health and Nutrition

Human health will benefit from integrated mitigation and adaptation options that mainstream healthinto food, infrastructure, social protection, and water policies (very high confidence). Balanced andsustainable healthy diets99 and reduced food loss and waste present important opportunities for adaptation andmitigation while generating significant co-benefits in terms of biodiversity and human health (highconfidence). Public health policies to improve nutrition, such as increasing the diversity of food sources inpublic procurement, health insurance, financial incentives, and awareness-raising campaigns, can potentiallyinfluence food demand, reduce food waste, reduce healthcare costs, contribute to lower GHG emissions andenhance adaptive capacity (high confidence). Improved access to clean energy sources and technologies, andshifts to active mobility (e.g., walking and cycling) and public transport can deliver socioeconomic, air quality
and health benefits, especially for women and children (high confidence). {WGII SPM C.2.2, WGII SPM
C.2.11, WGII Cross-Chapter Box HEALTH; WGIII SPM C.2.2, WGIII SPM C.4.2, WGIII SPM C.9.1, WGIII
SPM C.10.4, WGIII SPM D.1.3, WGIII SPM Figure SPM6, WGIII SPM Figure SPM.8; SRCCL SPM B.6.2,
SRCCL SPM B.6.3, SRCCL B.4.6, SRCCL SPM C.2.4}
Effective adaptation options exist to help protect human health and wellbeing (high confidence). Health
Action Plans that include early warning and response systems are effective for extreme heat (high confidence).
Effective options for water-borne and food-borne diseases include improving access to potable water, reducing
exposure of water and sanitation systems to flooding and extreme weather events, and improved early warning
systems (very high confidence). For vector-borne diseases, effective adaptation options include surveillance,
early warning systems, and vaccine development (very high confidence). Effective adaptation options for
reducing mental health risks under climate change include improving surveillance and access to mental healthcare, and monitoring of psychosocial impacts from extreme weather events (high confidence). A key pathway
to climate resilience in the health sector is universal access to healthcare (high confidence) {WGII SPM C.2.11,
WGII Chapter 7.4.6}

4.5.6

Society, Livelihoods, and Economies

Enhancing knowledge on risks and available adaptation options promotes societal responses, andbehaviour and lifestyle changes supported by policies, infrastructure and technology can help reduce
global GHG emissions (high confidence). Climate literacy and information provided through climate services
and community approaches, including those that are informed by Indigenous Knowledge and local knowledge,
can accelerate behavioural changes and planning (high confidence). Educational and information programmes,
using the arts, participatory modelling and citizen science can facilitate awareness, heighten risk perception,and influence behaviours (high confidence). The way choices are presented can enable adoption of low GHG
intensive socio-cultural options, such as shifts to balanced, sustainable healthy diets, reduced food waste, andactive mobility (high confidence). Judicious labelling, framing, and communication of social norms canincrease the effect of mandates, subsidies, or taxes (medium confidence) {WGII SPM C.5.3, WGII TS.D.10.1;
WGIII SPM C.10, WGIII SPM C.10.2, WGIII SPM C.10.3, WGIII SPM E.2.2, WGIII Figure SPM.6, WGIII
TS.6.1, 5.4; SR1.5 SPM D.5.6; SROCC SPM C.4}.

99 Balanced diets refer to diets that feature plant-based foods, such as those based on coarse grains, legumes, fruits and vegetables, nuts

and seeds, and animal-sourced food produced in resilient, sustainable and low-GHG emission systems, as described in SRCCL.
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A range of adaptation options, such as disaster risk management, early warning systems, climate
services and risk spreading and sharing approaches, have broad applicability across sectors and provide
greater risk reduction benefits when combined (high confidence). Climate services that are demand-driven
and inclusive of different users and providers can improve agricultural practices, inform better water use andefficiency, and enable resilient infrastructure planning (high confidence). Policy mixes that include weather
and health insurance, social protection and adaptive safety nets, contingent finance and reserve funds, anduniversal access to early warning systems combined with effective contingency plans, can reduce vulnerability
and exposure of human systems (high confidence). Integrating climate adaptation into social protection
programs, including cash transfers and public works programs, is highly feasible and increases resilience toclimate change, especially when supported by basic services and infrastructure (high confidence). Social safety
nets can build adaptive capacities, reduce socioeconomic vulnerability, and reduce risk linked to hazards(robust evidence, medium agreement). {WGII SPM C.2.9, WGII SPM C.2.13, WGII Cross-Chapter Box
FEASIB in Chapter 18; SRCCL SPM C.1.4, SRCCL SPM D.1.2}.
Reducing future risks of involuntary migration and displacement due to climate change is possible
through cooperative, international efforts to enhance institutional adaptive capacity and sustainable
development (high confidence). Increasing adaptive capacity minimises risk associated with involuntary
migration and immobility and improves the degree of choice under which migration decisions are made, while
policy interventions can remove barriers and expand the alternatives for safe, orderly and regular migrationthat allows vulnerable people to adapt to climate change (high confidence). {WGII SPM C.2.12, WGII
TS.D.8.6, WGII Cross-Chapter Box MIGRATE in Chapter 7}
Accelerating commitment and follow-through by the private sector is promoted for instance by building
business cases for adaptation, accountability and transparency mechanisms, and monitoring andevaluation of adaptation progress (medium confidence). Integrated pathways for managing climate risks
will be most suitable when so-called ‘low-regret’ anticipatory options are established jointly across sectors ina timely manner and are feasible and effective in their local context, and when path dependencies andmaladaptations across sectors are avoided (high confidence). Sustained adaptation actions are strengthened bymainstreaming adaptation into institutional budget and policy planning cycles, statutory planning, monitoringand evaluation frameworks and into recovery efforts from disaster events (high confidence). Instruments thatincorporate adaptation such as policy and legal frameworks, behavioural incentives, and economic instrumentsthat address market failures, such as climate risk disclosure, inclusive and deliberative processes strengthen
adaptation actions by public and private actors (medium confidence). {WGII SPM C.5.1, WGII SPM C.5.2,
WGII TS.D.10.4}

4.6

Co-Benefits of Adaptation and Mitigation for Sustainable Development Goals

Mitigation and adaptation actions have more synergies than trade-offs with Sustainable Development
Goals (SDGs). Synergies and trade-offs depend on context and scale of implementation. Potential
trade-offs can be compensated or avoided with additional policies, investments and financial
partnerships. (high confidence)
Many mitigation and adaptation actions have multiple synergies with Sustainable Development Goals(SDGs), but some actions can also have trade-offs. Potential synergies with SDGs exceed potential tradeoffs. Synergies and trade-offs are context specific and depend on: means and scale of implementation, intraand inter-sectoral interactions, cooperation between countries and regions, the sequencing, timing andstringency of actions, governance, and policy design. Eradicating extreme poverty, energy poverty, andproviding decent living standards to all, consistent with near-term sustainable development objectives, can beachieved without significant global emissions growth. (high confidence) (Figure 4.5) {WGII SPM C.2.3, WGIISPM Figure SPM.4b; WGIII SPM B.3.3, WGIII SPM C.9.2, WGIII SPM D.1.2, WGIII SPM D.1.4, WGIII
SPM Figure SPM.8}
Several mitigation and adaptation options can harness near-term synergies and reduce trade-offs toadvance sustainable development in energy, urban and land systems (Figure 4.5) (high confidence).
Clean energy supply systems have multiple co-benefits, including improvements in air quality and health. Heat
Health Action Plans that include early warning and response systems, approaches that mainstream health into
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food, livelihoods, social protection, water and sanitation benefit health and well-being. There are potential
synergies between multiple Sustainable Development Goals and sustainable land use and urban planning withmore green spaces, reduced air pollution, and demand-side mitigation including shifts to balanced, sustainable
healthy diets. Electrification combined with low-GHG energy, and shifts to public transport can enhance
health, employment, and can contribute to energy security and deliver equity. Conservation, protection andrestoration of terrestrial, freshwater, coastal and ocean ecosystems, together with targeted management to adapt
to unavoidable impacts of climate change can generate multiple additional benefits, such as agricultural
productivity, food security, and biodiversity conservation. (high confidence). {WGII SPM C.1.1, WGII C.2.4,
WGII SPM D.1, WGII SPM Figure SPM.4, WGII Cross-Chapter Box HEALTH in Chapter 17, WGII CrossChapter Box FEASIB in Chapter 18; WGIII SPM C.4.2, WGIII SPM D.1.3, WGIII SPM D.2, WGIII SPM
Figure SPM.8; SRCCL SPM B.4.6}
When implementing mitigation and adaptation together, and taking trade-offs into account, multiple
co-benefits and synergies for human well-being as well as ecosystem and planetary health can be realised(high confidence). There is a strong link between sustainable development, vulnerability and climate risks.
Social safety nets that support climate change adaptation have strong co-benefits with development goals suchas education, poverty alleviation, gender inclusion and food security. Land restoration contributes to mitigation
and adaptation with synergies via enhanced ecosystem services and with economically positive returns andco-benefits for poverty reduction and improved livelihoods. Trade-offs can be evaluated and minimised bygiving emphasis to capacity building, finance, technology transfer, investments; governance, development,
context specific gender-based and other social equity considerations with meaningful participation ofIndigenous Peoples, local communities and vulnerable populations. (high confidence). {WGII SPM C.2.9,
WGII SPM C.5.6, WGII SPM D.5.2, WGII Cross-Chapter Box on Gender in Chapter 18; WGIII SPM C.9.2,
WGIII SPM D.1.2, WGIII SPM D.1.4, WGIII SPM D.2; SRCCL SPM D.2.2, SRCCL TS.4}
Context relevant design and implementation requires considering people’s needs, biodiversity, andother sustainable development dimensions (very high confidence). Countries at all stages of economic
development seek to improve the well-being of people, and their development priorities reflect different
starting points and contexts. Different contexts include but are not limited to social, economic, environmental,
cultural, or political circumstances, resource endowment, capabilities, international environment, and priordevelopment. n regions with high dependency on fossil fuels for, among other things, revenue and employment
generation, mitigating risks for sustainable development requires policies that promote economic and energy
sector diversification and considerations of just transitions principles, processes and practices (highconfidence). For individuals and households in low-lying coastal areas, in Small Islands, and smallholder
farmers transitioning from incremental to transformational adaptation can help overcome soft adaptation limits(high confidence). Effective governance is needed to limit trade-offs of some mitigation options such as large
scale afforestation and bioenergy options due to risks from their deployment for food systems, biodiversity,
other ecosystem functions and services, and livelihoods (high confidence). Effective governance requires
adequate institutional capacity at all levels (high confidence) {WGII SPM B.5.4, WGII SPM C.3.1, WGII SPM
C.3.4; WGIII SPM D.1.3, WGIII SPM E.4.2; SR1.5 SPM C.3.4, SR1.5 SPM C.3.5, SR1.5 SPM Figure SPM.4,
SR1.5 SPM D.4.3, SR1.5 SPM D.4.4}[START FIGURE 4.5]

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IPCC AR6 SYRFigure 4.5: Potential synergies and trade-offs between the portfolio of climate change mitigation and adaptation
options and the Sustainable Development Goals (SDGs). This figure presents a high-level summary of potential
synergies and trade-offs assessed in WGII Figure SPM.4b and WGIII Figure SPM.8, based on the qualitative andquantitative assessment of each individual mitigation or option. The SDGs serve as an analytical framework for theassessment of different sustainable development dimensions, which extend beyond the time frame of 2030 SDG targets.
Synergies and trade-offs across all individual options within a sector/system are aggregated into sector/system potentials
for the whole mitigation or adaptation portfolio.
The length of each bar represents the total number of mitigation or adaptation options under each system/sector. The
number of adaptation and mitigation options vary across system/sector, and have been normalised to 100% so that bars
are comparable across mitigation, adaptation, system/sector, and SDGs. Positive links shown in WGII Figure SPM 4b
and WGIII Figure SPM 8 are counted and aggregated to generate the percentage share of synergies, represented here by
the blue proportion within the bars. Negative links shown in WGII Figure SPM 4b and WGIII Figure SPM 8 are counted
and aggregated to generate the percentage share of trade-offs and is represented by orange proportion within the bars.
‘Both synergies and trade-offs’ shown in WGII Figure SPM 4b WGIII Figure SPM 8 are counted and aggregated to
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generate the percentage share of ‘both synergies and trade-off’, represented by the striped proportion within the bars. The‘white’ proportion within the bar indicates limited evidence/ no evidence/ not assessed.
Energy systems comprise all mitigation options listed in WGIII Figure SPM.8 and WGII Figure SPM.4b for adaptation.
Urban and infrastructure comprises all mitigation options listed in WGIII Figure SPM.8 under Urban systems, under
Buildings and under Transport and adaptation options listed in WGII Figure SPM.4b under Urban and infrastructure
systems. Land system comprises mitigation options listed in WGIII Figure SPM.8 under AFOLU and adaptation options
listed in WGII Figure SPM.4b under Land and ocean systems: forest-based adaptation, agroforestry, biodiversity
management and ecosystem connectivity, improved cropland management, efficient livestock management, water use
efficiency and water resource management. Ocean ecosystems comprises adaptation options listed in WGII Figure
SPM.4b under Land and ocean systems: coastal defence and hardening, integrated coastal zone management andsustainable aquaculture and fisheries. Society, livelihood and economies comprises adaptation options listed in WGII
Figure SPM.4b under Cross-sectoral; Industry comprises all those mitigation options listed in WGIII Figure SPM.8 underIndustry.
SDG 13 (Climate Action) is not listed because mitigation/ adaptation is being considered in terms of interaction with
SDGs and not vice versa (SPM SR1.5 Figure SPM.4 caption). The bars denote the strength of the connection and do notconsider the strength of the impact on the SDGs. The synergies and trade-offs differ depending on the context and thescale of implementation. Scale of implementation particularly matters when there is competition for scarce resources. For
the sake of uniformity, we are not reporting the confidence levels because there is knowledge gap in adaptation option
wise relation with SDGs and their confidence level which is evident from WGII fig SPM 4b. {WGII Figure SPM.4b;
WGIII Figure SPM.8}[END FIGURE 4.5 HERE]

4.7

Governance and Policy for Near-Term Climate Change Action

Effective climate action requires political commitment, well-aligned multi-level governance andinstitutional frameworks, laws, policies and strategies. It needs clear goals, adequate finance andfinancing tools, coordination across multiple policy domains, and inclusive governance processes.
Many mitigation and adaptation policy instruments have been deployed successfully, and could
support deep emissions reductions and climate resilience if scaled up and applied widely, dependingon national circumstances. Adaptation and mitigation action benefits from drawing on diverse
knowledge. (high confidence)
Effective climate governance enables mitigation and adaptation by providing overall direction based onnational circumstances, setting targets and priorities, mainstreaming climate action across policy
domains and levels, based on national circumstances and in the context of international cooperation.
Effective governance enhances monitoring and evaluation and regulatory certainty, prioritising
inclusive, transparent and equitable decision-making, and improves access to finance and technology(high confidence). These functions can be promoted by climate-relevant laws and plans, which are growing
in number across sectors and regions, advancing mitigation outcomes and adaptation benefits (highconfidence). Climate laws have been growing in number and have helped deliver mitigation and adaptation
outcomes (medium confidence). {WGII SPM C.5, WGII SPM C.5.1, WGII SPM C5.4, WGII SPM C.5.6;
WGIII SPM B.5.2, WGIII SPM E.3.1}
Effective municipal, national and sub-national climate institutions, such as expert and co-ordinating
bodies, enable co-produced, multi-scale decision-processes, build consensus for action among diverse
interests, and inform strategy settings (high confidence). This requires adequate institutional capacity at alllevels (high confidence). Vulnerabilities and climate risks are often reduced through carefully designed andimplemented laws, policies, participatory processes, and interventions that address context specific inequities
such as based on gender, ethnicity, disability, age, location and income (high confidence). Policy support is
influenced by Indigenous Peoples, businesses, and actors in civil society, including, youth, labour, media, andlocal communities, and effectiveness is enhanced by partnerships between many different groups in society(high confidence).Climate-related litigation is growing, with a large number of cases in some developed
countries and with a much smaller number in some developing countries, and in some cases has influenced the
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IPCC AR6 SYRoutcome and ambition of climate governance (medium confidence). {WGII SPM C2.6, WGII SPM C.5.2,
WGII SPM C.5.5, WGII SPM C.5.6, WGII SPM D.3.1; WGIII SPM E3.2, WGIII SPM E.3.3}
Effective climate governance is enabled by inclusive decision processes, allocation of appropriate
resources, and institutional review, monitoring and evaluation (high confidence). Multi-level, hybrid andcross-sector governance facilitates appropriate consideration for co-benefits and trade-offs, particularly in land
sectors where decision processes range from farm level to national scale (high confidence). Consideration ofclimate justice can help to facilitate shifting development pathways towards sustainability. {WGII SPM C.5.5,
WGII SPM C.5.6, WGII SPM D.1.1, WGII SPM D.2, WGII SPM D.3.2; SRCCL SPM C.3, SRCCL TS.1}
Drawing on diverse knowledge and partnerships, including with women, youth, Indigenous Peoples,
local communities, and ethnic minorities can facilitate climate resilient development and has allowed
locally appropriate and socially acceptable solutions (high confidence). {WGII SPM D.2, D.2.1}
Many regulatory and economic instruments have already been deployed successfully. These instruments
could support deep emissions reductions if scaled up and applied more widely. Practical experience has
informed instrument design and helped to improve predictability, environmental effectiveness, economic
efficiency, and equity. (high confidence) {WGII SPM E.4; WGIII SPM E.4.2}.
Scaling up and enhancing the use of regulatory instruments, consistent with national circumstances, canimprove mitigation outcomes in sectoral applications (high confidence), and regulatory instruments that
include flexibility mechanisms can reduce costs of cutting emissions (medium confidence). {WGII SPM
C.5.4; WGIII SPM E.4.1}
Where implemented, carbon pricing instruments have incentivized low-cost emissions reduction
measures, but have been less effective, on their own and at prevailing prices during the assessment
period, to promote higher-cost measures necessary for further reductions (medium confidence). Revenue
from carbon taxes or emissions trading can be used for equity and distributional goals, for example to support
low-income households, among other approaches (high confidence). There is no consistent evidence thatcurrent emission trading systems have led to significant emissions leakage (medium confidence). {WGIII SPM
E4.2, WGIII SPM E.4.6}
Removing fossil fuel subsidies would reduce emissions, improve public revenue and macroeconomic
performance, and yield other environmental and sustainable development benefits such as improved
public revenue, macroeconomic and sustainability performance; subsidy removal can have adverse
distributional impacts especially on the most economically vulnerable groups which, in some cases, canbe mitigated by measures such as re-distributing revenue saved, and depend on national circumstances(high confidence). Fossil fuel subsidy removal is projected by various studies to reduce global CO2 emissions
by 1–4%, and GHG emissions by up to 10% by 2030, varying across regions (medium confidence). {WGIII
SPM E.4.2}
National policies to support technology development, and participation in international markets foremission reduction, can bring positive spillover effects for other countries (medium confidence), although
reduced demand for fossil fuels as a result of climate policy could result in costs to exporting countries (highconfidence). Economy-wide packages can meet short-term economic goals while reducing emissions andshifting development pathways towards sustainability (medium confidence). Examples are public spending
commitments; pricing reforms; and investment in education and training, R&D and infrastructure (highconfidence). Effective policy packages would be comprehensive in coverage, harnessed to a clear vision forchange, balanced across objectives, aligned with specific technology and system needs, consistent in terms ofdesign and tailored to national circumstances (high confidence). {WGIII SPM E4.4, WGIII SPM 4.5, WGIII
SPM 4.6}

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IPCC AR6 SYRStrengthening the Response: Finance, International Cooperation and Technology

Finance, international cooperation and technology are critical enablers for accelerated climate action.
If climate goals are to be achieved, both adaptation and mitigation financing would have to increase
many-fold. There is sufficient global capital to close the global investment gaps but there are barriers
to redirect capital to climate action. Barriers include institutional, regulatory and market accessbarriers, are reduced and address the needs and opportunities, economic vulnerability andindebtedness in many developing countries. Enhancing international cooperation is possible throughmultiple channels. Enhancing technology innovation systems is key to accelerate the widespread
adoption of technologies and practices. (high confidence)

4.8.1

Finance for Mitigation and Adaptation Actions

Improved availability and access to finance100 will enable accelerated climate action (very highconfidence). Addressing needs and gaps and broadening equitable access to domestic and international
finance, when combined with other supportive actions, can act as a catalyst for accelerating mitigation andshifting development pathways (high confidence). Climate resilient development is enabled by increased
international cooperation including improved access to financial resources, particularly for vulnerable regions,sectors and groups, and inclusive governance and coordinated policies (high confidence). Accelerated
international financial cooperation is a critical enabler of low-GHG and just transitions, and can address
inequities in access to finance and the costs of, and vulnerability to, the impacts of climate change (highconfidence). {WGII SPM C.1.2, WGII SPM C.3.2, WGII SPM C.5, WGII SPM C.5.4, WGII SPM D.2, WGIISPM D.3.2, WGII SPM D.5, WGII SPM D.5.2; WGIII SPM B.4.2,WGIII SPM B.5, WGIII SPM B.5.4, WGIII
SPM C.4.2, WGIII SPM C.7.3, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.2.4, WGIII SPM D.3.4,
WGIII SPM E.2.3, WGIII SPM E.3.1, WGIII SPM E.5, WGIII SPM E.5.1, WGIII SPM E.5.2, WGIII SPM
E.5.3, WGIII SPM E.5.4, WGIII SPM E.6.2}
Both adaptation and mitigation finance need to increase many-fold, to address rising climate risks andto accelerate investments in emissions reduction (high confidence). Increased finance would address soft
limits to adaptation and rising climate risks while also averting some related losses and damages, particularly
in vulnerable developing countries (high confidence). Enhanced mobilisation of and access to finance, together
with building capacity, are essential for implementation of adaptation actions and to reduce adaptation gaps
given rising risks and costs, especially for the most vulnerable groups, regions and sectors (high confidence).
Public finance is an important enabler of adaptation and mitigation, and can also leverage private finance (highconfidence). Adaptation funding predominately comes from public sources, and public mechanisms andfinance can leverage private sector finance by addressing real and perceived regulatory, cost and market
barriers, for instance via public-private partnerships (high confidence). Financial and technological resources
enable effective and ongoing implementation of adaptation, especially when supported by institutions with astrong understanding of adaptation needs and capacity (high confidence). Average annual modelled mitigation
investment requirements for 2020 to 2030 in scenarios that limit warming to 2°C or 1.5°C are a factor of three
to six greater than current levels, and total mitigation investments (public, private, domestic and international)
would need to increase across all sectors and regions (medium confidence). Even if extensive global mitigation
efforts are implemented, there will be a large need for financial, technical, and human resources for adaptation(high confidence) (Section 2.3.2, 2.3.3, 4.4, Figure 4.6) {WGII SPM C.1.2, WGII SPM C2.11, WGII SPM
C.3, WGII SPM C.3.2, WGII SPM C3.5, WGII SPM C.5, WGII SPM C.5.4, WGII SPM D.1, WGII SPM
D.1.1, WGII SPM D.1.2, WGII SPM C.5.4; WGIII SPM D.2.4,WGIII SPM E.5, WGIII SPM E.5.1,WGIII
Chapter 15.2}
There is sufficient global capital and liquidity to close global investment gaps, given the size of the global
financial system, but there are barriers to redirect capital to climate action both within and outside theglobal financial sector and in the context of economic vulnerabilities and indebtedness facing many
100 Finance can originate from diverse sources, singly or in combination: public or private, local, national or international, bilateral or

multilateral, and alternative sources (e.g., philanthropic, carbon offsets). It can be in the form of grants, technical assistance, loans(concessional and non-concessional), bonds, equity, risk insurance and financial guarantees (of various types).
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IPCC AR6 SYRdeveloping countries (high confidence). For shifts in private finance, options include better assessment ofclimate-related risks and investment opportunities within the financial system, reducing sectoral and regional
mismatches between available capital and investment needs, improving the risk-return profiles of climate
investments, and developing institutional capacities and local capital markets. Macroeconomic barriers
include, amongst others, indebtedness and economic vulnerability of developing regions. (high confidence).
{WGII SPM C.5.4; WGIII SPM E.4.2, WGIII SPM E.5, WGIII SPM E.5.2, WGIII SPM E.5.3}
Scaling up financial flows requires clear signalling from governments and the international community.
Tracked financial flows fall short of the levels needed for adaptation and to achieve mitigation goals
across all sectors and regions. These gaps create many opportunities and the challenge of closing gaps
is largest in developing countries. This includes a stronger alignment of public finance, lowering real andperceived regulatory, cost and market barriers, and higher levels of public finance to lower the risks associatedwith low-emission investments. Up-front risks deter economically sound low carbon projects, and developing
local capital markets are an option. Investors, financial intermediaries, central banks and financial regulators
can shift the systemic underpricing of climate-related risks. A robust labelling of bonds and transparency isneeded to attract savers. (high confidence). {WGII SPM C.5.4; WGIII SPM B.5.4, WGIII SPM E.4, WGIII
SPM E.5.4, WGIII Section 15.2, 15.6.1, 15.6.2, 15.6.7}[START FIGURE 4.6 HERE]

Figure 4.6: Breakdown of average mitigation investment flows and investment needs until 2030 (USD billion).
Mitigation investment flows and investment needs by sector (energy efficiency, transport, electricity, and agriculture,
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forestry and other land use), by type of economy, and by region (see WGIII Annex II Part I Section 1 for the classification
schemes for countries and areas).
The blue bars display data on mitigation investment flows for four years: 2017, 2018, 2019 and 2020 by sector and by
type of economy. For the regional breakdown, the annual average mitigation investment flows for 2017 –2019 are shown.
The grey bars show the minimum and maximum level of global annual mitigation investment needs in the assessed
scenarios. This has been averaged until 2030. The multiplication factors show the ratio of global average early mitigation
investment needs (averaged until 2030) and current yearly mitigation flows (averaged for 2017/18–2020). The lower
multiplication factor refers to the lower end of the range of investment needs. The upper multiplication factor refers to
the upper range of investment needs.
Given the multiple sources and lack of harmonised methodologies, the data can be considered only if indicative of thesize and pattern of investment needs. {WGIII Figure TS.25, WGIII Sections 15.3, 15.4, 15.5, Table 15.2, Table 15.3,
Table 15.4}[END FIGURE 4.6 HERE]

The largest climate finance gaps and opportunities are in developing countries (high confidence).
Accelerated support from developed countries and multilateral institutions is a critical enabler to enhance
mitigation and adaptation action and can address inequities in finance, including its costs, terms and conditions,and economic vulnerability to climate change. Scaled-up public grants for mitigation and adaptation fundingfor vulnerable regions, e.g., in Sub-Saharan Africa, would be cost-effective and have high social returns interms of access to basic energy. Options for scaling up mitigation and adaptation in developing regions include:
increased levels of public finance and publicly mobilised private finance flows from developed to developing
countries in the context of the USD 100 billion-a-year goal of the Paris Agreement; increase the use of publicguarantees to reduce risks and leverage private flows at lower cost; local capital markets development; andbuilding greater trust in international cooperation processes. A coordinated effort to make the post-pandemic
recovery sustainable over the long term through increased flows of financing over this decade can accelerate
climate action, including in developing regions facing high debt costs, debt distress and macroeconomic
uncertainty. (high confidence) {WGII SPM C.5.2, WGII SPM C.5.4, WGII SPM C.6.5, WGII SPM D.2, WGII
TS.D.10.2; WGIII SPM E.5, WGIII SPM E.5.3, WGIII TS.6.4, WGIII Box TS.1, WGIII Chapter 15.2, WGIII
Chapter 15.6}

4.8.2

International Cooperation and Coordination

International cooperation is a critical enabler for achieving ambitious climate change mitigation goals
and climate resilient development (high confidence). Climate resilient development is enabled by increased
international cooperation including mobilising and enhancing access to finance, particularly for developing
countries, vulnerable regions, sectors and groups and aligning finance flows for climate action to be consistent
with ambition levels and funding needs (high confidence). While agreed processes and goals, such as those in
the UNFCCC, Kyoto Protocol and Paris Agreement, are helping (Section 2.2.1), international financial,technology and capacity building support to developing countries will enable greater implementation and more
ambitious actions (medium confidence). By integrating equity and climate justice, national and international
policies can help to facilitate shifting development pathways towards sustainability, especially by mobilisingand enhancing access to finance for vulnerable regions, sectors and communities (high confidence).
International cooperation and coordination, including combined policy packages, may be particularly
important for sustainability transitions in emissions-intensive and highly traded basic materials industries thatare exposed to international competition (high confidence). The large majority of emission modelling studies
assume significant international cooperation to secure financial flows and address inequality and poverty issues
in pathways limiting global warming. There are large variations in the modelled effects of mitigation on GDP
across regions, depending notably on economic structure, regional emissions reductions, policy design andlevel of international cooperation (high confidence). Delayed global cooperation increases policy costs acrossregions (high confidence). {WGII SPM D.2, WGII SPM D.3.1, WGII SPM D.5.2; WGIII SPM D.3.4, WGIII
SPM C5.4, WGIII SPM C.12.2, WGIII SPM E.6, WGIII SPM E.6.1, WGIII E.5.4, WGIII TS.4.2, WGIII
TS.6.2; SR1.5 SPM D.6.3, SR1.5 SPM D.7, SR1.5 SPM D.7.3}.

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The transboundary nature of many climate change risks (e.g., for supply chains, markets and natural
resource flows in food, fisheries, energy and water, and potential for conflict) increases the need forclimate-informed transboundary management, cooperation, responses and solutions through multinational or regional governance processes (high confidence). Multilateral governance efforts can help
reconcile contested interests, world views and values about how to address climate change. International
environment and sectoral agreements, and initiatives in some cases, may help to stimulate low GHG
investment and reduce emissions (such as ozone depletion, transboundary air pollution and atmosphericemissions of mercury). Improvements to national and international governance structures would further enable
the decarbonisation of shipping and aviation through deployment of low-emissions fuels, for example throughstricter efficiency and carbon intensity standards. Transnational partnerships can also stimulate policy
development, low-emissions technology diffusion, emission reductions and adaptation, by linking sub-nationaland other actors, including cities, regions, non-governmental organisations and private sector entities, and byenhancing interactions between state and non-state actors, though uncertainties remain over their costs,
feasibility, and effectiveness. International environmental and sectoral agreements, institutions, and initiatives
are helping, and in some cases may help, to stimulate low GHG emissions investment and reduce emissions.
(medium confidence) {WGII SPM B.5.3, WGII SPM C.5.6, WGII TS.E.5.4, WGII TS.E.5.5, WGIII SPM
C.8.4, WGIII SPM E.6.3, WGIII SPM E.6.4, WGIII SPM E.6.4, WGIII TS.5.3}

4.8.3

Technology Innovation, Adoption, Diffusion and Transfer

Enhancing technology innovation systems can provide opportunities to lower emissions growth andcreate social and environmental co-benefits. Policy packages tailored to national contexts andtechnological characteristics have been effective in supporting low-emission innovation and technology
diffusion. Support for successful low-carbon technological innovation includes public policies such as training
and R&D, complemented by regulatory and market-based instruments that create incentives and market
opportunities such as appliance performance standards and building codes. (high confidence) {WGIII SPM
B.4, WGIII SPM B.4.4, WGIII SPM E.4.3, WGIII SPM E4.4}.
International cooperation on innovation systems and technology development and transfer,accompanied by capacity building, knowledge sharing, and technical and financial support canaccelerate the global diffusion of mitigation technologies, practices and policies and align these withother development objectives (high confidence). Choice architecture can help end-users adopt technology
and low-GHG-intensive options (high confidence). Adoption of low-emission technologies lags in mostdeveloping countries, particularly least developed ones, due in part to weaker enabling conditions, including
limited finance, technology development and transfer, and capacity building (medium confidence). {WGIII
SPM B.4.2, WGIII SPM E.6.2, WGIII SPM C.10.4, WGIII Chapter 16.5}
International cooperation on innovation works best when tailored to and beneficial for local value chains,when partners collaborate on an equal footing, and when capacity building is an integral part of the effort(medium confidence). {WGIII SPM E.4.4, WGIII SPM E.6.2}.
Technological innovation can have trade-offs that include externalities such as new and greater
environmental impacts and social inequalities; rebound effects leading to lower net emission reductions
or even emission increases; and overdependence on foreign knowledge and providers (high confidence).
Appropriately designed policies and governance have helped address distributional impacts and reboundeffects (high confidence). For example, digital technologies can promote large increases in energy efficiency
through coordination and an economic shift to services (high confidence). However, societal digitalization can
induce greater consumption of goods and energy and increased electronic waste as well as negatively
impacting labour markets and worsening inequalities between and within countries (medium confidence).
Digitalisation requires appropriate governance and policies in order to enhance mitigation potential (highconfidence) . Effective policy packages can help to realise synergies, avoid trade-offs and/or reduce reboundeffects: these might include a mix of efficiency targets, performance standards, information provision, carbon
pricing, finance and technical assistance (high confidence). {WGIII SPM B.4.2, WGIII SPM B.4.3, WGIII
SPM E.4.4, WGIII TS 6.5, WGIII Cross-Chapter Box 11 on Digitalization in Chapter 16}

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IPCC AR6 SYRTechnology transfer to expand use of digital technologies for land use monitoring, sustainable land
management, and improved agricultural productivity supports reduced emissions from deforestation and land
use change while also improving GHG accounting and standardisation (medium confidence) {SRCCL SPM
C.2.1, SRCCL SPM D.1.2, SRCCL SPM D.1.4, SRCCL Chapter 7.4.4, SRCCL Chapter 7.4.6}.
4.9

Integration of Near-Term Actions Across Sectors and Systems

The feasibility, effectiveness and benefits of mitigation and adaptation actions are increased when
multi-sectoral solutions are undertaken that cut across systems. When such options are combinedwith broader sustainable development objectives, they can yield greater benefits for human wellbeing, social equity and justice, and ecosystem and planetary health. (high confidence)
Climate resilient development strategies that treat climate, ecosystems and biodiversity, and humansociety as parts of an integrated system are the most effective (high confidence). Human and ecosystemvulnerability are interdependent (high confidence). Climate resilient development is enabled when decisionmaking processes and actions are integrated across sectors (very high confidence). Synergies with and progress
towards the Sustainable Development Goals enhance prospects for climate resilient development. Choices andactions that treat humans and ecosystems as an integrated system build on diverse knowledge about climate
risk, equitable, just and inclusive approaches, and ecosystem stewardship. {WGII SPM B.2, WGII Figure
SPM.5, WGII SPM D.2, WGII SPM D2.1, WGII SPM 2.2, WGII SPM D4, WGII SPM D4.1, WGII SPM
D4.2, WGII SPM D5.2, WGII SPM Figure SPM.5}.
Approaches that align goals and actions across sectors provide opportunities for multiple and largescale benefits and avoided damages in the near-term. Such measures can also achieve greater benefits
through cascading effects across sectors (medium confidence). For example, the feasibility of using landfor both agriculture and centralised solar production can increase when such options are combined (highconfidence). Similarly, integrated transport and energy infrastructure planning and operations can together
reduce the environmental, social, and economic impacts of decarbonising the transport and energy sectors(high confidence). The implementation of packages of multiple city-scale mitigation strategies can havecascading effects across sectors and reduce GHG emissions both within and outside a city’s administrative
boundaries (very high confidence). Integrated design approaches to the construction and retrofit of buildings
provide increasing examples of zero energy or zero carbon buildings in several regions. To minimise
maladaptation, multi-sectoral, multi-actor and inclusive planning with flexible pathways encourages lowregret and timely actions that keep options open, ensure benefits in multiple sectors and systems and suggest
the available solution space for adapting to long-term climate change (very high confidence). Trade-offs interms of employment, water use, land-use competition and biodiversity, as well as access to, and theaffordability of, energy, food, and water can be avoided by well-implemented land-based mitigation options,especially those that do not threaten existing sustainable land uses and land rights, with frameworks for
integrated policy implementation (high confidence){WGII SPM C.2, WGII SPM C.2.1–2.13, WGII SPM
C.4.4; WGIII SPM C.6.3, WGIII SPM C.6, WGIII SPM C.7.2, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIIISPM D.1.5, WGIII SPM E.1.2}
Mitigation and adaptation when implemented together, and combined with broader sustainable
development objectives, would yield multiple benefits for human well-being as well as ecosystem andplanetary health (high confidence). The range of such positive interactions is significant in the landscape ofnear-term climate policies across regions, sectors and systems. For example, AFOLU mitigation actions inland-use change and forestry, when sustainably implemented, can provide large-scale GHG emission
reductions and removals that simultaneously benefit biodiversity, food security, wood supply and otherecosystem services but cannot fully compensate for delayed mitigation action in other sectors. Adaptation
measures in land, ocean and ecosystems similarly can have widespread benefits for food security, nutrition,
health and well-being, ecosystems and biodiversity. Equally, urban systems are critical, interconnected sites
for climate resilient development; urban policies that implement multiple interventions can yield adaptation or
mitigation gains with equity and human well-being. Integrated policy packages can improve the ability tointegrate considerations of equity, gender equality and justice. Coordinated cross-sectoral policies andplanning can maximise synergies and avoid or reduce trade-offs between mitigation and adaptation. Effective
action in all of the above areas will require near-term political commitment and follow-through, social
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cooperation, finance, and more integrated cross-sectoral policies and support and actions. (high confidence).
(3.4, 4.4) {WGII SPM C.1, WG II SPM C.2, WGII SPM C.2, WGII SPM C.5, WGII SPM D.2, WGII SPM
D.3.2, WGII SPM D.3.3, WGII SPM Figure SPM.4; WGIII SPM C.6.3, WGIII SPM C.8.2, WGIII SPM C.9,
WGIII SPM C.9.1, WGIII SPM C.9.2, WGIII SPM D.2, WGIII SPM D.2.4, WGIII SPM D.3.2, WGIII SPM
E.1, WGIII SPM E.2.4, WGIII SPM Figure SPM.8, WGIII TS.7, WGIII TS Figure TS.29: SRCCL ES Section
7.4.8, SRCCL SPM B.6}

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