Editing IPCC:AR6/SYR/Longer-Report (section)

== Section 2: Current Status and Trends ==

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=== 2.1 Observed Changes, Impacts and Attribution ===

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'''Human activities, principally through emissions of greenhouse gases, have unequivocally caused global warming, with global surface temperature reaching 1.1°C above 1850 – 1900 in 2011 – 2020. Global greenhouse gas emissions have continued to increase over 2010 – 2019, with unequal historical and ongoing contributions arising from unsustainable energy use, land use and land-use change, lifestyles and patterns of consumption and production across regions, between and within countries, and between individuals ( '''''high confidence''''' ) . Human-caused climate change is already affecting many weather and climate extremes in every region across the globe. This has led to widespread adverse impacts on food and water security, human health and on economies and society and related losses and damages '''[[#footnote-094|63]]''' to nature and people ( '''''high confidence''''' ) . Vulnerable communities who have historically contributed the least to current climate change are disproportionately affected ( '''''high confidence''''' ) .'''
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==== 2.1.1. Observed Warming and its Causes ====

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'''Global surface temperature was around 1.1°C above 1850–1900 in 2011–2020 (1.09 [0.95 to 1.20]°C)''' '''[[#footnote-093|64]] , with larger increases over land (1.59 [1.34 to 1.83]°C) than over the ocean (0.88 [0.68 to 1.01]°C)''' '''[[#footnote-092|65]] . Observed warming is human- caused, with warming from greenhouse gases (GHG), dominated by CO''' '''2 and methane (CH''' '''4), partly masked by aerosol cooling (Figure 2.1)''' . Global surface temperature in the first two decades of the 21st century (2001–2020) was 0.99 [0.84 to 1.10]°C higher than 1850–1900. Global surface temperature has increased faster since 1970 than in any other 50-year period over at least the last 2000 years ( ''high confidence'' ). The ''likely'' range of total human-caused global surface temperature increase from 1850–1900 to 2010–2019 '''[[#footnote-091|66]]''' is 0.8°C to 1.3°C, with a best estimate of 1.07°C. It is ''likely'' that well-mixed GHGs '''[[#footnote-090|67]]''' contributed a warming of 1.0°C to 2.0°C, and other human drivers (principally aerosols) contributed a cooling of 0.0°C to 0.8°C, natural (solar and volcanic) drivers changed global surface temperature by ±0.1°C and internal variability changed it by ±0.2°C. { ''WGI SPM A.1, WGI SPM A.1.2, WGI SPM A.1.3, WGI SPM A.2.2, WGI Figure SPM.2; SRCCL TS.2'' }

Observed increases in well-mixed GHG concentrations since around 1750 are unequivocally caused by GHG emissions from human activities. Land and ocean sinks have taken up a near-constant proportion (globally about 56% per year) of CO 2 emissions from human activities over the past six decades, with regional differences ( high confidence ) . In 2019, atmospheric CO 2 concentrations reached 410 parts per million (ppm), CH 4 reached 1866 parts per billion (ppb) and nitrous oxide ( N 2 O ) reached 332 ppb [[#footnote-089|68]] . Other major contributors to warming are tropospheric ozone (O 3 ) and halogenated gases. Concentrations of CH 4 and N 2 O have increased to levels unprecedented in at least 800,000 years ( very high confidence ) , and there is high confidence that current CO 2 concentrations are higher than at any time over at least the past two million years. Since 1750, increases in CO 2 (47%) and CH 4 (156%) concentrations far exceed – and increases in N 2 O (23%) are similar to – the natural multi-millennial changes between glacial and interglacial periods over at least the past 800,000 years ( very high confidence ) . The net cooling effect which arises from anthropogenic aerosols peaked in the late 20th century ( high confidence ) . { WGI SPM A1.1, WGI SPM A1.3, WGI SPM A.2.1, WGI Figure SPM.2, WGI TS 2.2, WGI 2ES, WGI Figure 6.1 }

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[[File:091ec207e6eb5e141653abb239b1a8a8 IPCC_AR6_SYR_Figure_2_1.png]]
'''Figure 2.1: The causal chain from emissions to resulting warming of the climate system.''' Emissions of GHG have increased rapidly over recent decades '''(panel (a))''' . Global net anthropogenic GHG emissions include CO 2 from fossil fuel combustion and industrial processes (CO 2 -FFI) (dark green); net CO 2 from land use, land-use change and forestry (CO 2 -LULUCF) (green); CH 4 ; N 2 O; and fluorinated gases (HFCs, PFCs, SF 6 , NF 3 ) (light blue). These emissions have led to increases in the atmospheric concentrations of several GHGs including the three major well-mixed GHGs CO 2 , CH 4 and N 2 O '''(panel (b)''' , annual values). To indicate their relative importance each subpanel’s vertical extent for CO 2 , CH 4 and N 2 O is scaled to match the assessed individual direct effect (and, in the case of CH 4 indirect effect via atmospheric chemistry impacts on tropospheric ozone) of historical emissions on temperature change from 1850–1900 to 2010–2019. This estimate arises from an assessment of effective radiative forcing and climate sensitivity. The global surface temperature (shown as annual anomalies from a 1850–1900 baseline) has increased by around 1.1°C since 1850–1900 '''(panel (c))''' . The vertical bar on the right shows the estimated temperature ''(very likely range)'' during the warmest multi-century period in at least the last 100,000 years, which occurred around 6500 years ago during the current interglacial period (Holocene). Prior to that, the next most recent warm period was about 125,000 years ago, when the assessed multi-century temperature range [0.5°C to 1.5°C] overlaps the observations of the most recent decade. These past warm periods were caused by slow (multi-millennial) orbital variations. Formal detection and attribution studies synthesise information from climate models and observations and show that the best estimate is that all the warming observed between 1850–1900 and 2010–2019 is caused by humans '''(panel (d))''' . The panel shows temperature change attributed to: total human influence; its decomposition into changes in GHG concentrations and other human drivers (aerosols, ozone and land-use change (land-use reflectance)); solar and volcanic drivers; and internal climate variability. Whiskers show ''likely'' ranges. ''{ 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 }''

[https://www.ipcc.ch/figures/figure-2-1 ]

'''Average annual GHG emissions during 2010 –2019 were higher than in any previous decade, but the rate of growth between 2010 and 2019 (1.3% yr''' -1 ) was lower than that between 2000 and 2009 (2.1% yr -1 ) '''[[#footnote-088|69]] .''' Historical cumulative net CO 2 emissions from 1850 to 2019 were 2400 ±240 GtCO 2 . Of these, more than half (58%) occurred between 1850 and 1989 [1400 ±195 GtCO 2 ], and about 42% between 1990 and 2019 [1000 ±90 GtCO 2 ]. Global net anthropogenic GHG emissions have been estimated to be 59±6.6 GtCO 2 -eq in 2019, about 12% (6.5 GtCO 2 -eq) higher than in 2010 and 54% (21 GtCO 2 -eq) higher than in 1990. By 2019, the largest growth in gross emissions occurred in CO 2 from fossil fuels and industry (CO 2 -FFI) followed by CH 4 , 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'' }

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[[File:94a7f0eb0d41f519dc02f8fdd48dfc77 IPCC_AR6_SYR_Figure_2_2.png]]
'''Figure 2.2: Regional GHG emissions, and the regional proportion of total cumulative production-based CO''' '''2''' 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 GtCO 2 . This includes CO 2 -FFI and CO 2 -LULUCF. Other GHG emissions are not included. CO 2 -LULUCF emissions are subject to high uncertainties, reflected by a global uncertainty estimate of ±70% (90% confidence interval). '''Panel (b)''' shows the distribution of regional GHG emissions in tonnes CO 2 -eq per capita by region in 2019. GHG emissions are categorised into: CO 2 -FFI; net CO 2 -LULUCF; and other GHG emissions (CH 4 , N 2 O, fluorinated gases, expressed in CO 2 -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 CO 2 removals rather than emissions. '''Panel (c)''' shows global net anthropogenic GHG emissions by region (in GtCO 2 -eq yr ''–1'' (GWP100-AR6)) for the time period 1990–2019. Percentage values refer to the contribution of each region to total GHG emissions in each respective time period. The single-year peak of emissions in 1997 was due to higher CO 2 -LULUCF emissions from a forest and peat fire event in South East Asia. Regions are as grouped in Annex II of WGIII. '''Panel (d)''' shows population, gross domestic product (GDP) per person, emission indicators by region in 2019 for total GHG per person, and total GHG emissions intensity, together with production-based and consumption-based CO 2 -FFI data, which is assessed in this report up to 2018. Consumption-based emissions are emissions released to the atmosphere in order to generate the goods and services consumed by a certain entity (e.g., region). Emissions from international aviation and shipping are not included. ''{ WGIII Figure SPM.2 }''

[https://www.ipcc.ch/figures/figure-2-2 ]

'''Regional contributions to global human-caused GHG emissions continue to differ widely.''' Historical contributions of CO 2 emissions vary substantially across regions in terms of total magnitude, but also in terms of contributions to CO 2 -FFI (1650 ± 73 GtCO 2 -eq) and net CO 2 -LULUCF (760 ± 220 GtCO 2 -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 tCO 2 -eq to 19 tCO 2 -eq across regions (Figure 2.2). Least Developed Countries (LDCs) and Small Island Developing States (SIDS) have much lower per capita emissions (1.7 tCO 2 -eq and 4.6 tCO 2 -eq, respectively) than the global average (6.9 tCO 2 -eq), excluding CO 2 -LULUCF. Around 48% of the global population in 2019 lives in countries emitting on average more than 6 tCO 2 -eq per capita, 35% of the global population live in countries emitting more than 9 tCO 2 -eq per capita '''[[#footnote-087|70]]''' (excluding CO 2 -LULUCF) while another 41% live in countries emitting less than 3 tCO 2 -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 GtCO 2 -eq) of net global GHG emissions came from the energy sector, 24% (14 GtCO 2 -eq) from industry, 22% (13 GtCO 2 -eq) from AFOLU, 15% (8.7 GtCO 2 -eq) from transport and 6% (3.3 GtCO 2 -eq) from buildings '''[[#footnote-086|71]]''' ( ''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% to 1.4%) but remained roughly constant at about 2% yr ''–1'' in the transport sector ( ''high confidence'' ). About half of total net AFOLU emissions are from CO 2 LULUCF, predominantly from deforestation ( ''medium confidence'' ). Land overall constituted a net sink of –6.6 (±4.6) GtCO 2 yr ''–1'' for the period 2010–2019 '''[[#footnote-085|72]]''' ( ''medium confidence'' ). { ''WGIII SPM B.2, WGIII SPM B.2.1, WGIII SPM B.2.2, WGIII TS 5.6.1'' } .

'''Human-caused climate change is a consequence of more than a century of net GHG emissions from energy use, land-use and land use change, lifestyle and patterns of consumption, and production.''' Emissions reductions in CO 2 from fossil fuels and industrial processes (CO 2 -FFI), due to improvements in energy intensity of GDP and carbon intensity of energy, have been less than emissions increases from rising global activity levels in industry, energy supply, transport, agriculture and buildings. The 10% of households with the highest per capita emissions contribute 34–45% of global consumption-based household GHG emissions, while the middle 40% contribute 40–53%, and the bottom 50% contribute 13–15%. An increasing share of emissions can be attributed to urban areas (a rise from about 62% to 67–72% of the global share between 2015 and 2020). The drivers of urban GHG emissions '''[[#footnote-084|73]]''' are complex and include population size, income, state of urbanisation and urban form. ( ''high confidence'' ) { ''WGIII SPM B.2, WGIII SPM B.2.3, WGIII SPM B.3.4, WGIII SPM D.1.1'' }

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==== 2.1.2. Observed Climate System Changes and Impacts to Date ====

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'''It is unequivocal that human influence has warmed the atmosphere, ocean and land. Widespread and rapid changes in the atmosphere, ocean, cryosphere and biosphere have occurred (Table 2.1).''' The scale of recent changes across the climate system as a whole and the present state of many aspects of the climate system are unprecedented over many centuries to many thousands of years. It is ''very likely'' that GHG emissions were the main driver '''[[#footnote-083|74]]''' of tropospheric warming and ''extremely likely'' that human-caused stratospheric ozone depletion was the main driver of stratospheric cooling between 1979 and the mid-1990s. It is ''virtually certain'' that the global upper ocean (0-700m) has warmed since the 1970s and ''extremely likely'' that human influence is the main driver. Ocean warming accounted for 91% of the heating in the climate system, with land warming, ice loss and atmospheric warming accounting for about 5%, 3% and 1%, respectively ( ''high confidence'' ). Global mean sea level increased by 0.20 [0.15 to 0.25] m between 1901 and 2018. The average rate of sea level rise was 1.3 [0.6 to 2.1]mm yr ''-1'' between 1901 and 1971, increasing to 1.9 [0.8 to 2.9] mm yr ''-1'' between 1971 and 2006, and further increasing to 3.7 [3.2 to –4.2] mm yr ''-1'' between 2006 and 2018 ( ''high confidence'' ). Human influence was ''very likely'' the main driver of these increases since at least 1971 (Figure 3.4). Human influence is ''very likely'' the main driver of the global retreat of glaciers since the 1990s and the decrease in Arctic sea ice area between 1979–1988 and 2010–2019. Human influence has also ''very likely'' contributed to decreased Northern Hemisphere spring snow cover and surface melting of the Greenland ice sheet. It is ''virtually'' certain that human-caused CO 2 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'' }

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'''Table 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate system components, and their attribution to human influence.''' The colour coding indicates the assessed confidence in / likelihood '''[[#footnote-081|76]]''' of the observed change and the human contribution as a driver or main driver (specified in that case) where available (see colour key). Otherwise, explanatory text is provided. { ''WGI Table TS.1'' }

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'''Human-caused climate change is already affecting many weather and climate extremes in every region across the globe. Evidence of observed changes in extremes such as heatwaves, heavy precipitation, droughts, and tropical cyclones, and, in particular, their attribution to human influence, has strengthened since AR5 (Figure 2.3).''' It is ''virtually'' certain that hot extremes (including heatwaves) have become more frequent and more intense across most land regions since the 1950s (Figure 2.3), while cold extremes (including cold waves) have become less frequent and less severe, with ''high confidence'' that human-caused climate change is the main driver of these changes. Marine heatwaves have approximately doubled in frequency since the 1980s ( ''high confidence'' ), and human influence has ''very likely'' contributed to most of them since at least 2006. The frequency and intensity of heavy precipitation events have increased since the 1950s over most land areas for which observational data are sufficient for trend analysis ( ''high confidence'' ), and human-caused climate change is ''likely'' the main driver (Figure 2.3). Human-caused climate change has contributed to increases in agricultural and ecological droughts in some regions due to increased land evapotranspiration ( ''medium confidence'' ) (Figure 2.3). It is ''likely'' that the global proportion of major (Category 3–5) tropical cyclone occurrence has increased over the last four decades. { ''WGI SPM A.3, WGI SPM A3.1, WGI SPM A3.2; WGI SPM A3.4; SRCCL SPM.A.2.2; SROCC SPM. A.2'' }

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[[File:5655d3e46294b1b81ac919bd67dd20e7 IPCC_AR6_SYR_Figure_2_3_1.png]] [[File:bae15f91425cf0fb7884c48589495a0e IPCC_AR6_SYR_Figure_2_3_2.png]]
'''Figure 2.3: Both vulnerability to current climate extremes and historical contribution to climate change are highly heterogeneous with many of those who have least contributed to climate change to date being most vulnerable to its impacts. Panel (a)''' The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size in their approximate geographical location (see legend for regional acronyms). All assessments are made for each region as a whole and for the 1950s to the present. Assessments made on different time scales or more local spatial scales might differ from what is shown in the figure. The colours in each panel represent the four outcomes of the assessment on observed changes. Striped hexagons (white and light-grey) are used where there is ''low agreement'' in the type of change for the region as a whole, and grey hexagons are used when there is limited data and/or literature that prevents an assessment of the region as a whole. Other colours indicate at least ''medium confidence'' in the observed change. 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 agreemen'' t; single, empty dot: ''limited evidence'' ). For hot extremes, the evidence is mostly drawn from changes in metrics based on daily maximum temperatures; regional studies using other indices (heatwave duration, frequency and intensity) are used in addition. For heavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or five-day precipitation amounts using global and regional studies. Agricultural and ecological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence on changes in surface soil moisture, water balance ( precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. '''Panel (b)''' shows the average level of vulnerability amongst a country’s population against 2019 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, for example, information on poverty, inequality, health care infrastructure or insurance coverage. '''Panel (c)''' Observed impacts on ecosystems and human systems attributed to climate change at global and regional scales. Global assessments focus on large studies, multi-species, meta-analyses and large reviews. Regional assessments consider evidence on impacts across an entire region and do not focus on any country in particular. For human systems, the direction of impacts is assessed and both adverse and positive impacts have been observed e.g., adverse impacts in one area or food item may occur with positive impacts in another area or food item (for more details and methodology see WGII SMTS.1). Physical water availability includes balance of water available from various sources including ground water, water quality and demand for water. Global mental health and displacement assessments reflect only assessed regions. Confidence levels reflect the assessment of attribution of the observed impact to climate change. ''{ 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 }''

[https://www.ipcc.ch/figures/figure-2-3 ]

'''Climate change has caused substantial damages, and increasingly irreversible''' '''[[#footnote-082|75]] losses, in terrestrial, freshwater, cryospheric and coastal and open ocean ecosystems''' '''''(''''' '''''high confidence). The extent and magnitude of climate change impacts are larger than estimated in previous assessments (''''' '''''high confidence)''''' . Approximately half of the species assessed globally have shifted polewards or, on land, also to higher elevations ( ''very high confidence'' ). Biological responses including changes in geographic placement and shifting seasonal timing are often not sufficient to cope with recent climate change. ( ''very high confidence'' ). Hundreds of local losses of species have been driven by increases in the magnitude of heat extremes ( ''high confidence'' ) and mass mortality events on land and in the ocean ( ''very high confidence'' ). Impacts on some ecosystems are approaching irreversibility such as the impacts of hydrological changes resulting from the retreat of glaciers, or the changes in some mountain ( ''medium confidence'' ) and Arctic ecosystems driven by permafrost thaw ( ''high confidence'' ). Impacts in ecosystems from slow-onset processes such as ocean acidification, sea level rise or regional decreases in precipitation have also been attributed to human-caused climate change ( ''high confidence'' ). Climate change has contributed to desertification and exacerbated land degradation, particularly in low lying coastal areas, river deltas, drylands and in permafrost areas ( ''high confidence'' ). Nearly 50% of coastal wetlands have been lost over the last 100 years, as a result of the combined effects of localised human pressures, sea level rise, warming and extreme climate events ( ''high confidence'' ). { ''WGII SPM B.1.1, WGII SPM B.1.2, WGII Figure SPM.2.A, WGII TS.B.1; SRCCL SPM A.1.5, SRCCL SPM A.2, SRCCL SPM A.2.6, SRCCL Figure SPM.1; SROCC SPM A.6.1, SROCC SPM, A.6.4, SROCC SPM A.7'' } .

'''Climate change has reduced food security and affected water security due to warming, changing precipitation patterns, reduction and loss of cryospheric elements, and greater frequency and intensity of climatic extremes, thereby hindering efforts to meet Sustainable Development Goals (''' '''''high confidence).''''' Although overall agricultural productivity has increased, climate change has slowed this growth in agricultural productivity over the past 50 years globally ( ''medium confidence'' ), with related negative crop yield impacts mainly recorded in mid- and low latitude regions, and some positive impacts in some high latitude regions ( ''high confidence'' ). Ocean warming in the 20th century and beyond has contributed to an overall decrease in maximum catch potential ( ''medium confidence'' ), compounding the impacts from overfishing for some fish stocks ( ''high confidence'' ). Ocean warming and ocean acidification have adversely affected food production from shellfish aquaculture and fisheries in some oceanic regions ( ''high confidence'' ). Current levels of global warming are associated with moderate risks from increased dryland water scarcity ( ''high confidence'' ). Roughly half of the world’s population currently experiences severe water scarcity for at least some part of the year due to a combination of climatic and non-climatic drivers ( ''medium confidence'' ) (Figure 2.3). Unsustainable agricultural expansion, driven in part by unbalanced diets '''[[#footnote-080|77]]''' , increases ecosystem and human vulnerability and leads to competition for land and/or water resources ( ''high confidence'' ). Increasing weather and climate extreme events have exposed millions of people to acute food insecurity '''[[#footnote-079|78]]''' and reduced water security, with the largest impacts observed in many locations and/or communities in Africa, Asia, Central and South America, LDCs, Small Islands and the Arctic, and for small-scale food producers, low-income households and Indigenous Peoples globally ( ''high confidence'' ). { ''WGII SPM B.1.3, WGII SPM.B.2.3, WGII Figure SPM.2, WGII TS B.2.3, WGII TS Figure TS. 6; SRCCL SPM A.2.8, SRCCL SPM A.5.3; SROCC SPM A.5.4., SROCC SPMA.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 ( ''high confidence'' ), where they have also worsened air pollution events. ( ''medium confidence'' ) and limited functioning of key infrastructure ( ''high confidence'' ). Urban infrastructure, including transportation, water, sanitation and energy systems have been compromised by extreme and slow-onset events '''[[#footnote-078|79]]''' , with resulting economic losses, disruptions of services and impacts to well-being ( ''high confidence'' ). Observed impacts are concentrated amongst economically and socially marginalised urban residents, e.g., those living in informal settlements. ( ''high confidence'' ). Cities intensify human-caused warming locally ( ''very high confidence'' ), while urbanisation also increases mean and heavy precipitation over and/or downwind of cities ( ''medium confidence'' ) and resulting runoff intensity ( ''high confidence'' ). { ''WGI SPM C.2.6; WGII SPM B.1.5, WGII Figure TS.9, WGII 6 ES'' }

'''Climate change has adversely affected human physical health globally and mental health in assessed regions (''' '''''very high confidence), and is contributing to humanitarian crises where climate hazards interact with high vulnerability (''''' '''''high confidence).''''' In all regions increases in extreme heat events have resulted in human mortality and morbidity ( ''very high confidence'' ). The occurrence of climate-related food-borne and water-borne diseases has increased ( ''very high confidence'' ). The incidence of vector-borne diseases has increased from range expansion and/or increased reproduction of disease vectors ( ''high confidence'' ). Animal and human diseases, including zoonoses, are emerging in new areas ( ''high confidence'' ). In assessed regions, some mental health challenges are associated with increasing temperatures ( ''high confidence'' ), trauma from extreme events ( ''very high confidence'' ), and loss of livelihoods and culture ( ''high confidence'' ). (Figure 2.3). Climate change impacts on health are mediated through natural and human systems, including economic and social conditions and disruptions ( ''high confidence'' ). Climate and weather extremes are increasingly driving displacement in Africa, Asia, North America ( ''high confidence'' ), and Central and South America. ( ''medium confidence'' ). (Figure 2.3), with small island states in the Caribbean and South Pacific being disproportionately affected relative to their small population size ( ''high confidence'' ). Through displacement and involuntary migration from extreme weather and climate events, climate change has generated and perpetuated vulnerability ( ''medium confidence'' ). { ''WGII SPM B.1.4, WGII SPM B.1.7'' }

'''Human influence has''' '''''likely increased the chance of compound extreme events''''' '''[[#footnote-077|80]] since the 1950s. Concurrent and repeated climate hazards have occurred in all regions, increasing impacts and risks to health, ecosystems, infrastructure, livelihoods and food (''' '''''high confidence).''''' Compound extreme events include increases in the frequency of concurrent heatwaves and droughts ( ''high confidence'' ); fire weather in some regions ( ''medium confidence'' ); and compound flooding in some locations ( ''medium confidence'' ). Multiple risks interact, generating new sources of vulnerability to climate hazards, and compounding overall risk ( ''high confidence'' ). Compound climate hazards can overwhelm adaptive capacity and substantially increase damage ( ''high confidence'' ). { ''WGI SPM A.3.5; WGII SPM. B.5.1, WGII TS.C.11.3'' }

'''Economic impacts attributable to climate change are increasingly affecting peoples’ livelihoods and are causing economic and societal impacts across national boundaries (''' '''''high confidence)''''' '''.''' Economic damages from climate change have been detected in climate-exposed sectors, with regional effects to agriculture, forestry, fishery, energy, and tourism, and through outdoor labour productivity ( ''high confidence'' ) with some exceptions of positive impacts in regions with low energy demand and comparative advantages in agricultural markets and tourism. ( ''high confidence'' ). Individual livelihoods have been affected through changes in agricultural productivity, impacts on human health and food security, destruction of homes and infrastructure, and loss of property and income, with adverse effects on gender and social equity ( ''high confidence'' ). Tropical cyclones have reduced economic growth in the short-term ( ''high confidence'' ). Event attribution studies and physical understanding indicate that human-caused climate change increases heavy precipitation associated with tropical cyclones ( ''high confidence'' ). Wildfires in many regions have affected built assets, economic activity, and health ( ''medium'' to ''high confidence'' ). In cities and settlements, climate impacts to key infrastructure are leading to losses and damages across water and food systems, and affect economic activity, with impacts extending beyond the area directly impacted by the climate hazard. ( ''high confidence'' ). { ''WGI SPM A.3.4; WGII SPM B.1.6, WGII SPM B.5.2, WGII SPM B.5.3'' } .

'''Climate change has caused widespread adverse impacts and related losses and damages to nature and people (''' '''''high confidence).''''' Losses and damages are unequally distributed across systems, regions and sectors ( ''high confidence'' ). Cultural losses, related to tangible and intangible heritage, threaten adaptive capacity and may result in irrevocable losses of sense of belonging, valued cultural practices, identity and home, particularly for Indigenous Peoples and those more directly reliant on the environment for subsistence. ( ''medium confidence'' ). For example, changes in snow cover, lake and river ice, and permafrost in many Arctic regions, are harming the livelihoods and cultural identity of Arctic residents including Indigenous populations ( ''high confidence'' ). Infrastructure, including transportation, water, sanitation and energy systems have been compromised by extreme and slow-onset events, with resulting economic losses, disruptions of services and impacts to well-being ( ''high confidence'' ). { ''WGII SPM B.1, WGII SPM B.1.2, WGII SPM.B.1.5, WGII SPM C.3.5, WGII TS.B.1.6; SROCC SPM A.7.1'' }

'''Across sectors and regions, the most vulnerable people and systems have been disproportionately affected by the impacts of climate change''' '''''(''''' '''''high confidence).''''' LDCs and SIDS who have much lower per capita emissions (1.7 tCO 2 -eq, 4.6 tCO 2 -eq, respectively) than the global average (6.9 tCO 2 -eq) excluding CO 2 -LULUCF, also have high vulnerability to climatic hazards, with global hotspots of high human vulnerability observed in West-, Central- and East Africa, South Asia, Central and South America, SIDS and the Arctic ( ''high confidence'' ). Regions and people with considerable development constraints have high vulnerability to climatic hazards ( ''high confidence'' ). Vulnerability is higher in locations with poverty, governance challenges and limited access to basic services and resources, violent conflict and high levels of climate-sensitive livelihoods (e.g., smallholder farmers, pastoralists, fishing communities) ( ''high confidence'' ). Vulnerability at different spatial levels is exacerbated by inequity and marginalisation linked to gender, ethnicity, low income or combinations thereof ( ''high confidence'' ), especially for many Indigenous Peoples and local communities ( ''high confidence'' ). Approximately 3.3 to 3.6 billion people live in contexts that are highly vulnerable to climate change ( ''high confidence'' ). Between 2010 and 2020, human mortality from floods, droughts and storms was 15 times higher in highly vulnerable regions, compared to regions with very low vulnerability ( ''high confidence'' ). In the Arctic and in some high mountain regions, negative impacts of cryosphere change have been especially felt among Indigenous Peoples ( ''high confidence'' ). Human and ecosystem vulnerability are interdependent ( ''high confidence'' ). Vulnerability of ecosystems and people to climate change differs substantially among and within regions ( ''very high confidence'' ), driven by patterns of intersecting socio-economic development, unsustainable ocean and land use, inequity, marginalisation, historical and ongoing patterns of inequity such as colonialism, and governance '''[[#footnote-076|81]]''' ( ''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'' }

<div id="2.2" class="h2-container"></div>

<span id="responses-undertaken-to-date"></span>
=== 2.2 Responses Undertaken to Date ===

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'''International climate agreements, rising national ambitions for climate action, along with rising public awareness are accelerating efforts to address climate change at multiple levels of governance. Mitigation policies have contributed to a decrease in global energy and carbon intensity, with several countries achieving GHG emission reductions for over a decade. Low-emission technologies are becoming more affordable, with many low or zero emissions options now available for energy, buildings, transport, and industry. Adaptation planning and implementation progress has generated multiple benefits, with effective adaptation options having the potential to reduce climate risks and contribute to sustainable development. Global tracked finance for mitigation and adaptation has seen an upward trend since AR5, but falls short of needs. ( '''''high confidence''''' )'''
<div id="2.2.1" class="h3-container"></div>

<span id="global-policy-setting"></span>
==== 2.2.1. Global Policy Setting ====

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'''The United Nations Framework Convention on Climate Change ( UNFCCC), Kyoto Protocol, and Paris Agreement are supporting rising levels of national ambition and encouraging the development and implementation of climate policies at multiple levels of governance (''' '''''high confidence).''''' The Kyoto Protocol led to reduced emissions in some countries and was instrumental in building national and international capacity for GHG reporting, accounting and emissions markets ( ''high confidence'' ). The Paris Agreement, adopted under the UNFCCC, with near universal participation, has led to policy development and target-setting at national and sub-national levels, particularly in relation to mitigation but also for adaptation, as well as enhanced transparency of climate action and support ( ''medium confidence'' ). Nationally Determined Contributions (NDCs), required under the Paris Agreement, have required countries to articulate their priorities and ambition with respect to climate action. { ''WGII 17.4, WGII TS D.1.1; WGIII SPM B.5.1, WGIII SPM E.6'' }

Loss &amp; Damage '''[[#footnote-075|82]]''' was formally recognized in 2013 through establishment of the Warsaw International Mechanism on Loss and Damage (WIM), and in 2015, Article 8 of the Paris Agreement provided a legal basis for the WIM. There is improved understanding of both economic and non-economic losses and damages, which is informing international climate policy and which has highlighted that losses and damages are not comprehensively addressed by current financial, governance and institutional arrangements, particularly in vulnerable developing countries ( ''high confidence'' ). { ''WGII SPM C.3.5, WGII Cross-Chapter Box LOSS'' }

Other recent global agreements that influence responses to climate change include the Sendai Framework for Disaster Risk Reduction (2015-2030), the finance-oriented Addis Ababa Action Agenda (2015) and the New Urban Agenda (2016), and the Kigali Amendment to the Montreal Protocol on Substances that Deplete the Ozone Layer (2016), among others. In addition, the 2030 Agenda for Sustainable Development, adopted in 2015 by UN member states, sets out 17 Sustainable Development Goals (SDGs) and seeks to align efforts globally to prioritise ending extreme poverty, protect the planet and promote more peaceful, prosperous and inclusive societies. If achieved, these agreements would reduce climate change, and the impacts on health, well-being, migration, and conflict, among others ( ''very high confidence'' ). { ''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 decision-making processes has enabled deeper ambition and accelerated action in different ways, and at all scales, depending on national circumstances ( ''medium confidence'' ). The media helps shape the public discourse about climate change. This can usefully build public support to accelerate climate action ( ''medium evidence, high agreement'' ). In some instances, public discourses of media and organised counter movements have impeded climate action, exacerbating helplessness and disinformation and fuelling polarisation, with negative implications for climate action ( ''medium confidence'' ). { ''WGII SPM C.5.1, WGII SPM D.2, WGII TS.D.9, WGII TS.D.9.7, WGII TS.E.2.1, WGII 18.4; WGIII SPM D.3.3, WGIII SPM E.3.3, WGIII TS.6.1, WGIII 6.7, WGIII 13 ES, WGIII Box.13.7'' }

<div id="2.2.2" class="h3-container"></div>

<span id="mitigation-actions-to-date"></span>
==== 2.2.2. Mitigation Actions to Date ====

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'''There has been a consistent expansion of policies and laws addressing mitigation since AR5''' '''''(''''' '''''high confidence).''''' Climate governance supports mitigation by providing frameworks through which diverse actors interact, and a basis for policy development and implementation ( ''medium confidence'' ). Many regulatory and economic instruments have already been deployed successfully ( ''high confidence'' ). By 2020, laws primarily focussed on reducing GHG emissions existed in 56 countries covering 53% of global emissions ( ''medium confidence'' ). The application of diverse policy instruments for mitigation at the national and sub-national levels has grown consistently across a range of sectors. ( ''high confidence'' ). Policy coverage is uneven across sectors and remains limited for emissions from agriculture, and from industrial materials and feedstocks ( ''high confidence'' ). { ''WGIII SPM B.5, WGIII SPM B.5.2, WGIII SPM E.3, WGIII SPM E.4'' }

Practical experience has informed economic instrument design and helped to improve predictability, environmental effectiveness, economic efficiency, alignment with distributional goals, and social acceptance ( ''high confidence'' ). Low-emission technological innovation is strengthened through the combination of technology-push policies, together with policies that create incentives for behaviour change and market opportunities. ( ''high confidence'' ). (Section 4.8.3). Comprehensive and consistent policy packages have been found to be more effective than single policies ( ''high confidence'' ). Combining mitigation with policies to shift development pathways, policies that induce lifestyle or behaviour changes, for example, measures promoting walkable urban areas combined with electrification and renewable energy can create health co-benefits from cleaner air and enhanced active mobility ( ''high confidence'' ). Climate governance enables mitigation by providing an overall direction, setting targets, mainstreaming climate action across policy domains and levels, based on national circumstances and in the context of international cooperation. Effective governance enhances regulatory certainty, creating specialised organisations and creating the context to mobilise finance ( ''medium confidence'' ). These functions can be promoted by climate-relevant laws, which are growing in number, or climate strategies, among others, based on national and sub-national context ( ''medium confidence'' ). Effective and equitable climate governance builds on engagement with civil society actors, political actors, businesses, youth, labour, media, Indigenous Peoples and local communities ( ''medium confidence'' ). { ''WGIII SPM E.2.2, WGIII SPM E.3, WGIII SPM E.3.1, WGIII SPM E.4.2, WGIII SPM E.4.3, WGIII SPM E.4.4'' }

'''The unit costs of several low-emission technologies, including solar, wind and lithium-ion batteries, have fallen consistently since 2010 (Figure 2.4). Design and process innovations in combination with the use of digital technologies have led to near-commercial availability of many low or zero emissions options in buildings, transport and industry.''' From 2010-2019, there have been sustained decreases in the unit costs of solar energy (by 85%), wind energy (by 55%), and lithium-ion batteries (by 85%), and large increases in their deployment, e.g., &gt;10× for solar and &gt;100× for electric vehicles (EVs), albeit varying widely across regions (Figure 2.4). Electricity from PV and wind is now cheaper than electricity from fossil sources in many regions, electric vehicles are increasingly competitive with internal combustion engines, and large-scale battery storage on electricity grids is increasingly viable. In comparison to modular small-unit size technologies, the empirical record shows that multiple large-scale mitigation technologies, with fewer opportunities for learning, have seen minimal cost reductions and their adoption has grown slowly. Maintaining emission-intensive systems may, in some regions and sectors, be more expensive than transitioning to low emission systems. ( ''high confidence'' ) { ''WGIII SPM B.4, WGIII SPM B.4.1, WGIII SPM C.4.2, WGIII SPM C.5.2, WGIII SPM C.7.2, WGIII SPM C.8, WGIII Figure SPM.3, WGIII Figure SPM.3'' }

For almost all basic materials – primary metals, building materials and chemicals – many low- to zero-GHG intensity production processes are at the pilot to near-commercial and in some cases commercial stage but they are not yet established industrial practice. Integrated design in construction and retrofit of buildings has led to increasing examples of zero energy or zero carbon buildings. Technological innovation made possible the widespread adoption of LED lighting. Digital technologies including sensors, the internet of things, robotics, and artificial intelligence can improve energy management in all sectors; they can increase energy efficiency, and promote the adoption of many low-emission technologies, including decentralised renewable energy, while creating economic opportunities. However, some of these climate change mitigation gains can be reduced or counterbalanced by growth in demand for goods and services due to the use of digital devices. Several mitigation options, notably solar energy, wind energy, electrification of urban systems, urban green infrastructure, energy efficiency, demand side management, improved forest- and crop/grassland management, and reduced food waste and loss, are technically viable, are becoming increasingly cost effective and are generally supported by the public, and this enables expanded deployment in many regions. ( ''high confidence'' ) { ''WGIII SPM B.4.3, WGIII SPM C.5.2, WGIII SPM C.7.2, WGIII SPM E.1.1, WGIII TS.6.5'' }

'''The magnitude of global climate finance flows has increased and financing channels have broadened (''' '''''high confidence).''''' Annual tracked total financial flows for climate mitigation and adaptation increased by up to 60% between 2013/14 and 2019/20, but average growth has slowed since 2018 ( ''medium confidence'' ).and most climate finance stays within national borders ( ''high confidence'' ). Markets for green bonds, environmental, social and governance and sustainable finance products have expanded significantly since AR5 ( ''high confidence'' ). Investors, central banks, and financial regulators are driving increased awareness of climate risk to support climate policy development and implementation ( ''high confidence'' ). Accelerated international financial cooperation is a critical enabler of low-GHG and just transitions ( ''high confidence'' ). { ''WGIII SPM B.5.4, WGIII SPM E.5, WGIII TS.6.3, WGIII TS.6.4'' }

Economic instruments have been effective in reducing emissions, complemented by regulatory instruments mainly at the national and also sub-national and regional level ( ''high confidence'' ). By 2020, over 20% of global GHG emissions were covered by carbon taxes or emissions trading systems, although coverage and prices have been insufficient to achieve deep reductions ( ''medium confidence'' ). Equity and distributional impacts of carbon pricing instruments can be addressed by using revenue from carbon taxes or emissions trading to support low-income households, among other approaches. ( ''high confidence'' ). The mix of policy instruments which reduced costs and stimulated adoption of solar energy, wind energy and lithium-ion batteries includes public R&amp;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, WGIII TS.3'' }

<div id="figure-2-4" class="_idGenObjectStyleOverride-2 figure-cont"></div>

[[File:304c23eece1056631eb516392dc8af56 IPCC_AR6_SYR_Figure_2_4.png]]
'''Figure 2.4: Unit cost reductions and use in some rapidly changing mitigation technologies.''' The '''top panel (a)''' shows global costs per unit of energy (USD per MWh) for some rapidly changing mitigation technologies. Solid blue lines indicate average unit cost in each year. Light blue shaded areas show the range between the 5th and 95th percentiles in each year. Yellow shading indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020 (corresponding to USD 55 to 148 per MWh). In 2020, the levelised costs of energy (LCOE) of the three renewable energy technologies could compete with fossil fuels in many places. For batteries, costs shown are for 1 kWh of battery storage capacity; for the others, costs are LCOE, which includes installation, capital, operations, and maintenance costs per MWh of electricity produced. The literature uses LCOE because it allows consistent comparisons of cost trends across a diverse set of energy technologies to be made. However, it does not include the costs of grid integration or climate impacts. Further, LCOE does not take into account other environmental and social externalities that may modify the overall (monetary and non-monetary) costs of technologies and alter their deployment. The '''bottom panel (b)''' shows cumulative global adoption for each technology, in GW of installed capacity for renewable energy and in millions of vehicles for battery-electric vehicles. A vertical dashed line is placed in 2010 to indicate the change over the past decade. The electricity production share reflects different capacity factors; for example, for the same amount of installed capacity, wind produces about twice as much electricity as solar PV. Renewable energy and battery technologies were selected as illustrative examples because they have recently shown rapid changes in costs and adoption, and because consistent data are available. Other mitigation options assessed in the WGIII report are not included as they do not meet these criteria. { ''WGIII Figure SPM.3, WGIII 2.5, 6.4'' }

[https://www.ipcc.ch/figures/figure-2-4 ]

'''Mitigation actions, supported by policies, have contributed to a decrease in global energy and carbon intensity between 2010 and 2019, with a growing number of countries achieving absolute GHG emission reductions for more than a decade (''' '''''high confidence).''''' While global net GHG emissions have increased since 2010, global energy intensity (total primary energy per unit GDP) decreased by 2% yr ''–1'' between 2010 and 2019. Global carbon intensity (CO 2 -FFI per unit primary energy) also decreased by 0.3% yr ''–1'' , mainly due to fuel switching from coal to gas, reduced expansion of coal capacity, and increased use of renewables, and with large regional variations over the same period. In many countries, policies have enhanced energy efficiency, reduced rates of deforestation and accelerated technology deployment, leading to avoided and in some cases reduced or removed emissions ( ''high confidence'' ). At least 18 countries have sustained production-based CO 2 and GHG and consumption-based CO 2 absolute emission reductions for longer than 10 years since 2005 through energy supply decarbonization, energy efficiency gains, and energy demand reduction, which resulted from both policies and changes in economic structure. ( ''high confidence'' ). Some countries have reduced production-based GHG emissions by a third or more since peaking, and some have achieved reduction rates of around 4% yr ''–1'' for several years consecutively ( ''high confidence'' ). Multiple lines of evidence suggest that mitigation policies have led to avoided global emissions of several GtCO 2 -eq yr ''–1'' ( ''medium confidence'' ). At least 1.8 GtCO 2 -eq yr ''–1'' of avoided emissions can be accounted for by aggregating separate estimates for the effects of economic and regulatory instruments ( ''medium confidence'' ). Growing numbers of laws and executive orders have impacted global emissions and are estimated to have resulted in 5.9 GtCO 2 -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'' }

<div id="2.2.3" class="h3-container"></div>

<span id="adaptation-actions-to-date"></span>
==== 2.2.3. Adaptation Actions to Date ====

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'''Progress in adaptation planning and implementation has been observed across all sectors and regions, generating multiple benefits (''' '''''very high confidence).''''' The ambition, scope and progress on adaptation have risen among governments at the local, national and international levels, along with businesses, communities and civil society ( ''high confidence'' ). Various tools, measures and processes are available that can enable, accelerate and sustain adaptation implementation ( ''high confidence'' ). Growing public and political awareness of climate impacts and risks has resulted in at least 170 countries and many cities including adaptation in their climate policies and planning processes ( ''high confidence'' ). Decision support tools and climate services are increasingly being used ( ''very high confidence'' ) and pilot projects and local experiments are being implemented in different sectors ( ''high confidence'' ). { ''WGII SPM C.1, WGII SPM.C.1.1, WGII TS.D.1.3, WGII TS.D.10'' }

Adaptation to water-related risks and impacts make up the majority (~60%) of all documented '''[[#footnote-074|83]]''' adaptation. ( ''high confidence'' ). A large number of these adaptation responses are in the agriculture sector and these include on-farm water management, water storage, soil moisture conservation, and irrigation. Other adaptations in agriculture include cultivar improvements, agroforestry, community-based adaptation and farm and landscape diversification among others ( ''high confidence'' ). For inland flooding, combinations of non-structural measures like early warning systems, enhancing natural water retention such as by restoring wetlands and rivers, and land use planning such as no build zones or upstream forest management, can reduce flood risk ( ''medium confidence'' ). Some land-related adaptation actions such as sustainable food production, improved and sustainable forest management, soil organic carbon management, ecosystem conservation and land restoration, reduced deforestation and degradation, and reduced food loss and waste are being undertaken, and can have mitigation co-benefits ( ''high confidence'' ). Adaptation actions that increase the resilience of biodiversity and ecosystem services to climate change include responses like minimising additional stresses or disturbances, reducing fragmentation, increasing natural habitat extent, connectivity and heterogeneity, and protecting small-scale refugia where microclimate conditions can allow species to persist ( ''high confidence'' ). 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 and well-being are found in other sectors (e.g., food, livelihoods, social protection, water and sanitation, infrastructure) ( ''high confidence'' ). { ''WGII SPM C.2.1, WGII SPM C.2.2, WGII TS.D.1.2, WGII TS.D.1.4, WGII TS.D.4.2, WGII TS.D.8.3, WGII 4 ES; SRCCL SPM B.1.1'' }

Adaptation can generate multiple additional benefits such as improving agricultural productivity, innovation, health and well-being, food security, livelihood, and biodiversity conservation as well as reduction of risks and damages ( ''very high confidence'' ). { ''WGII SPM C1.1'' } .

'''Globally tracked adaptation finance has shown an upward trend since AR5, but represents only a small portion of total climate finance, is uneven and has developed heterogeneously across regions and sectors (''' '''''high confidence).''''' Adaptation finance has come predominantly from public sources, largely through grants, concessional and non-concessional instruments ( ''very high confidence'' ). Globally, private-sector financing of adaptation from a variety of sources such as commercial financial institutions, institutional investors, other private equity, non-financial corporations, as well as communities and households has been limited, especially in developing countries ( ''high confidence'' ). Public mechanisms and finance can leverage private sector finance for adaptation by addressing real and perceived regulatory, cost and market barriers, for example via public-private partnerships ( ''high confidence'' ). Innovations in adaptation and resilience finance, such as forecast-based/anticipatory financing systems and regional risk insurance pools, have been piloted and are growing in scale ( ''high confidence'' ). { ''WGII SPM C.3.2, WGII SPM C.5.4; WGII TS.D.1.6, WGII Cross-Chapter Box FINANCE; WGIII SPM E.5.4'' }

'''There are adaptation options which are effective''' '''[[#footnote-073|84]] in reducing climate risks''' '''[[#footnote-072|85]] 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, irrigation '''[[#footnote-071|86]]''' , agroforestry, community-based adaptation, and farm and landscape level diversification, and sustainable land management approaches, provide multiple benefits and reduce climate risks. Reduction of food loss and waste, and adaptation measures in support of balanced diets contribute to nutrition, health, and biodiversity benefits. ( ''high confidence'' ). { ''WGII SPM C.2, WGII SPM C.2.1, WGII SPM C.2.2; SRCCL B.2, SRCCL SPM C.2.1'' }

Ecosystem-based Adaptation '''[[#footnote-070|87]]''' approaches such as urban greening, restoration of wetlands and upstream forest ecosystems reduce a range of climate change risks, including flood risks, urban heat and provide multiple co-benefits. Some land-based adaptation options provide immediate benefits (e.g., conservation of peatlands, wetlands, rangelands, mangroves and forests); while afforestation and reforestation, restoration of high-carbon ecosystems, agroforestry, and the reclamation of degraded soils take more time to deliver measurable results. Significant synergies exist between adaptation and mitigation, for example through sustainable land management approaches. Agroecological principles and practices and other approaches that work with natural processes support food security, nutrition, health and well-being, livelihoods and biodiversity, sustainability and ecosystem services.. ( ''high confidence'' ). { ''WGII SPM C.2.1, WGII SPM C.2.2, WGII SPM C.2.5, WGII TS.D.4.1; SRCCL SPM B.1.2, SRCCL SPM.B.6.1; SROCC SPM C.2'' }

Combinations of non-structural measures like early warning systems and structural measures like levees have reduced loss of lives in case of inland flooding ( ''medium confidence'' ) and early warning systems along with flood-proofing of buildings have proven to be cost-effective in the context of coastal flooding under current sea level rise ( ''high confidence'' ). Heat Health Action Plans that include early warning and response systems are effective adaptation options for extreme heat ( ''high confidence'' ). Effective adaptation options for water, food and vector-borne diseases include improving access to potable water, reducing exposure of water and sanitation systems to extreme weather events, and improved early warning systems, surveillance, and vaccine development ( ''very high confidence'' ). Adaptation options such as disaster risk management, early warning systems, climate services and social safety nets have broad applicability across multiple sectors ( ''high confidence'' ). { ''WGII SPM C.2.1, WGII SPM C.2.5, WGII SPM C.2.9, WGII SPM C.2.11, WGII SPM C.2.13; SROCC SPM C.3.2'' }

Integrated, multi-sectoral solutions that address social inequities, differentiate responses based on climate risk and cut across systems, increase the feasibility and effectiveness of adaptation in multiple sectors. ( ''high confidence'' ). { ''WGII SPM C.2'' }

<div id="2.3" class="h2-container"></div>

<span id="current-mitigation-and-adaptation-actions-and-policies-are-not-sufficient"></span>
=== 2.3 Current Mitigation and Adaptation Actions and Policies are not Sufficient ===

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'''At the time of the present assessment '''[[#footnote-069|88]]''' 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. '''[[#footnote-068|89]]''' Despite progress, adaptation gaps '''[[#footnote-067|90]]''' persist, with many initiatives prioritising short-term risk reduction, hindering transformational adaptation. Hard and soft limits to adaptation are being reached in some sectors and regions, while maladaptation is also increasing and disproportionately affecting vulnerable groups. Systemic barriers such as funding, knowledge, and practice gaps, including lack of climate literacy and data hinders adaptation progress. Insufficient financing, especially for adaptation, constraints climate action in particular in developing countries. ( '''''high confidence''''' )'''
<div id="2.3.1" class="h3-container"></div>

<span id="the-gap-between-mitigation-policies-pledges-and-pathways-that-limit-warming-to-1.5c-or-below-2c"></span>
==== 2.3.1. The Gap Between Mitigation Policies, Pledges and Pathways that Limit Warming to 1.5°C or Below 2°C ====

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'''Global GHG emissions in 2030 associated with the implementation of NDCs announced prior to COP26''' '''[[#footnote-066|91]] would make it''' '''''likely''''' '''that warming will exceed 1. 5°C during the 21st century and would make it harder to limit warming below 2°C – if no additional commitments are made or actions taken (Figure 2.5, Table 2.2).''' A substantial ‘emissions gap’ exists as global GHG emissions in 2030 associated with the implementation of NDCs announced prior to COP26 would be similar to or only slightly below 2019 emission levels and higher than those associated with modelled mitigation pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot or to 2°C (&gt;67%), assuming immediate action, which implies deep, rapid, and sustained global GHG emission reductions this decade ( ''high confidence'' ). (Table 2.2, Table 3.1, 4.1). '''[[#footnote-065|92]]''' The magnitude of the emissions gap depends on the global warming level considered and whether only unconditional or also conditional elements of NDCs '''[[#footnote-064|93]]''' are considered ( ''high confidence'' ) (Table 2.2). Modelled pathways that are consistent with NDCs announced prior to COP26 until 2030 and assume no increase in ambition thereafter have higher emissions, leading to a median global warming of 2.8 [2.1 to 3.4]°C by 2100 ( ''medium confidence'' ). If the ‘emission gap’ is not reduced, global GHG emissions in 2030 consistent with NDCs announced prior to COP26 make it ''likely'' that warming will exceed 1.5°C during the 21st century, while limiting warming to 2°C (&gt;67%) would imply an unprecedented acceleration of mitigation efforts during 2030–2050 ( ''medium confidence'' ) (see Section 4.1, Cross-Section Box.2). { ''WGIII SPM B.6, WGIII SPM B.6.1, WGIII SPM B.6.3, WGIII SPM B.6.4, WGIII SPM C.1.1'' }

'''Policies implemented by the end of 2020 are projected to result in higher global GHG emissions in 2030 than those implied by NDCs, i ndicating an ‘implementation gap''' '''[[#footnote-063|94]] ’ (''' '''''high confidence)''''' '''''( Table 2.2, Figure 2.5).''''' Projected global emissions implied by policies implemented by the end of 2020 are 57 (52–60) GtCO 2 -eq in 2030 (Table 2.2). This points to an implementation gap compared with the NDCs of 4 to 7 GtCO 2 -eq in 2030 (Table 2.2); without a strengthening of policies, emissions are projected to rise, leading to a median global warming of 2.2°C to 3.5°C ( ''very likely range'' ) by 2100 ( ''medium confidence'' )(see [[#3.1.1|Section 3.1.1]] ). { ''WGIII SPM B.6.1, WGIII SPM C.1'' }

Projected cumulative future CO 2 emissions over the lifetime of existing fossil fuel infrastructure without additional abatement '''[[#footnote-062|95]]''' exceed the total cumulative net CO 2 emissions in pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot. They are approximately equal to total cumulative net CO 2 emissions in pathways that limit warming to 2°C with a likelihood of 83% '''[[#footnote-061|96]]''' (see Figure 3.5). Limiting warming to 2°C (&gt;67%) or lower will result in stranded assets. About 80% of coal, 50% of gas, and 30% of oil reserves cannot be burned and emitted if warming is limited to 2°C. Significantly more reserves are expected to remain unburned if warming is limited to 1.5°C. ( ''high confidence'' ). { ''WGIII SPM B.7, WGIII Box 6.3'' }

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'''Table 2.2 Projected global emissions in 2030 associated with policies implemented by the end of 2020 and NDCs announced prior to COP26, and associated emissions gaps.''' Emissions projections for 2030 and gross differences in emissions are based on emissions of 52–56 GtCO 2 -eq yr–1 in 2019 as assumed in underlying model studies '''[[#footnote-060|97]]''' . ( ''medium confidence'' ) { ''WGIII Table SPM.1'' } ( ''Table 3.1, Cross-Section Box.2'' ).

[[File:044d161a2fafbae99655aaaa0e5a957f IPCC_AR6_SYR_Table_2_2.png]]

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[[File:e748b9ca133a36e4a9f58ea8219a52df IPCC_AR6_SYR_Table_Figure_2_5.png]]
'''Figure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), and projected emission outcomes from near-term policy assessments for 2030 (Panel b). Panel a''' shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:

* Trend from implemented policies: Pathways with projected near-term GHG emissions in line with po licies 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 (&gt;67%) or return warming to 1.5°C (&gt;50%) after a high overshoot, NDCs until 2030: Pathways with GHG emissions until 2030 associated with the implementation of NDCs announced prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2°C (C3b, WGIII Table SPM.2) or to return warming to 1.5°C with a probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, WGIII Table SPM.2).
* Limit to 2°C (&gt;67%) with immediate action: Pathways that limit warming to 2°C (&gt;67%) with immediate action after 2020 (C3a, WGIII Table SPM.2).
* Limit to 1.5°C (&gt;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, Cross-Section Box.2'' )

[https://www.ipcc.ch/figures/figure-2-5 ]

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'''Cross-Section Box.1: Understanding Net Zero CO''' '''2''' 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 CO '''2''' emissions, along with strong reductions in other GHG emissions (see 3.3.2). Future additional warming will depend on future emissions, with total warming dominated by past and future cumulative CO 2 emissions. { ''WGI SPM D.1.1, WGIFigure SPM.4; SR1.5 SPM A.2.2'' } .

'''Reaching net zero CO''' '''2''' 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-CO 2 emissions into CO 2 -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-weighted '''[[#footnote-059|98]] non-CO''' '''2''' GHG emissions to be counterbalanced by durably stored CO '''2''' removals ( '''''high confidence).''''' Some non-CO 2 emissions, such as CH 4 and N 2 O from agriculture, cannot be fully eliminated using existing and anticipated technical measures. { ''WGIII SPM C.2.4, WGIII SPM C.11.4, WGIII Cross-Chapter Box 3'' }

'''Global net zero CO''' '''2''' or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that others reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions vary by sector and region. If and when net zero emissions for a given sector or region are reached depends on multiple factors, including the potential to reduce GHG emissions and undertake carbon dioxide removal, the associated costs, and the availability of policy mechanisms to balance emissions and removals between sectors and countries. ( ''high confidence'' ). { ''WGIII Box TS.6, WGIII Cross-Chapter Box 3'' }

'''The adoption and implementation of net zero emission targets by countries and regions also depend on equity and capacity considerations (''' '''''high confidence).''''' The formulation of net zero pathways by countries will benefit from clarity on scope, plans-of-action, and fairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global modelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the country-level timing of net zero ( ''high confidence'' ). The Paris Agreement also recognizes that peaking of emissions will occur later in developing countries than developed countries (Article 4.1). { ''WGIII Box TS.6, WGIII Cross-Chapter Box 3, WGIII 14.3'' }

More information on country-level net zero pledges is provided in [[#2.3.1|Section 2.3.1]] , on the timing of global net zero emissions in [[#3.3.2|Section 3.3.2]] , and on sectoral aspects of net zero in Section 4.1.

'''Many countries have signalled an intention to achieve net zero GHG or net zero CO''' '''2''' emissions by around mid-century (Cross-Section Box.1). More than 100 countries have either adopted, announced or are discussing net zero GHG or net zero CO 2 emissions commitments, covering more than two-thirds of global GHG emissions. A growing number of cities are setting climate targets, including net zero GHG targets. Many companies and institutions have also announced net zero emissions targets in recent years. The various net zero emission pledges differ across countries in terms of scope and specificity, and limited policies are to date in place to deliver on them. { ''WGIII SPM C.6.4, WGIII TS.4.1, WGIII Table TS.1, WGIII 13.9, WGIII 14.3, WGIII 14.5'' } .

'''All mitigation strategies face implementation challenges, including technology risks, scaling, and costs (''' '''''high confidence).''''' Almost all mitigation options also face institutional barriers that need to be addressed to enable their application at scale ( ''medium confidence'' ). Current development pathways may create behavioural, spatial, economic and social barriers to accelerated mitigation at all scales ( ''high confidence'' ). Choices made by policymakers, citizens, the private sector and other stakeholders influence societies’ development pathways ( ''high confidence'' ). Structural factors of national circumstances and capabilities (e.g., economic and natural endowments, political systems and cultural factors and gender considerations) affect the breadth and depth of climate governance ( ''medium confidence'' ). The extent to which civil society actors, political actors, businesses, youth, labour, media, Indigenous Peoples, and local communities are engaged influences political support for climate change mitigation and eventual policy outcomes ( ''medium confidence'' ). { ''WGIII SPM C.3.6, WGIII SPM E.1.1, WGIII SPM E.2.1, WGIII SPM E.3.3'' }

'''The adoption of low-emission technologies lags in most developing countries, particularly least developed ones, due in part to weaker enabling conditions, including limited finance, technology development and transfer, and capacity (''' '''''medium confidence).''''' In many countries, especially those with limited institutional capacity, several adverse side-effects have been observed as a result of diffusion of low-emission technology, e.g., low-value employment, and dependency on foreign knowledge and suppliers ( ''medium confidence'' ). Low-emission innovation along with strengthened enabling conditions can reinforce development benefits, which can, in turn, create feedbacks towards greater public support for policy. ( ''medium confidence)'' . Persistent and region-specific barriers also continue to hamper the economic and political feasibility of deploying AFOLU mitigation options ( ''medium confidence'' ). Barriers to implementation of AFOLU mitigation include insufficient institutional and financial support, uncertainty over long-term additionality and trade-offs, weak governance, insecure land ownership, low incomes and the lack of access to alternative sources of income, and the risk of reversal ( ''high confidence'' ). { ''WGIII SPM B.4.2, WGIII SPM C.9.1, WGIII SPM C.9.3'' } .

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<span id="adaptation-gaps-and-barriers"></span>
==== 2.3.2. Adaptation Gaps and Barriers ====

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'''Despite progress, adaptation gaps exist between current levels of adaptation and levels needed to respond to impacts and reduce climate risks (''' '''''high confidence)''''' '''.''' While progress in adaptation implementation is observed across all sectors and regions . ''very high confidence)'' , many adaptation initiatives prioritise immediate and near-term climate risk reduction, e.g., through hard flood protection, which reduces the opportunity for transformational adaptation '''[[#footnote-058|99]]''' ( ''high confidence'' ). Most observed adaptation is fragmented, small in scale, incremental, sector-specific, and focused more on planning rather than implementation. ( ''high confidence'' ). Further, observed adaptation is unequally distributed across regions and the largest adaptation gaps exist among lower population income groups ( ''high confidence'' ). In the urban context, the largest adaptation gaps exist in projects that manage complex risks, for example in the food–energy–water–health nexus or the inter-relationships of air quality and climate risk ( ''high'' . ''confidence'' ). Many funding, knowledge and practice gaps remain for effective implementation, monitoring and evaluation and current adaptation efforts are not expected to meet existing goals ( ''high confidence'' ). At current rates of adaptation planning and implementation the adaptation gap will continue to grow ( ''high confidence'' ). { ''WGII SPM C.1, WGII SPM C.1.2, WGII SPM C.4.1, WGII TS.D.1.3, WGII TS.D.1.4'' } .

'''Soft and hard adaptation limits''' '''[[#footnote-057|100]] have already been reached in some sectors and regions, in spite of adaptation having buffered some climate impacts (''' '''''high confidence)''''' '''.''' Ecosystems already reaching hard adaptation limits include some warm water coral reefs, some coastal wetlands, some rainforests, and some polar and mountain ecosystems ( ''high confidence'' ). Individuals and households in low lying coastal areas in Australasia and Small Islands and smallholder farmers in Central and South America, Africa, Europe and Asia have reached soft limits. ( ''medium confidence'' ), resulting from financial, governance, institutional and policy constraints and can be overcome by addressing these constraints ( ''high confidence'' ). Transitioning from incremental to transformational adaptation can help overcome soft adaptation limits ( ''high confidence'' ). { ''WGII SPM C.3, WGII SPM C.3.1, WGII SPM C.3.2, WGII SPM C.3.3, WGII SPM.C.3.4, WGII 16 ES'' }

Adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits. Losses and damages are unequally distributed across systems, regions and sectors and are not comprehensively addressed by current financial, governance and institutional arrangements, particularly in vulnerable developing countries.. ( ''high confidence'' ). { ''WGII SPM.C.3.5'' }

'''There is increased evidence of maladaptation''' '''[[#footnote-056|101]] 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) and human settlements (e.g. stranded assets and vulnerable communities that cannot afford to shift away or adapt and require an increase in social safety nets). Maladaptation especially affects marginalised and vulnerable groups adversely (e.g., Indigenous Peoples, ethnic minorities, low-income households, people living in informal settlements), reinforcing and entrenching existing inequities. Maladaptation can be avoided by flexible, multi-sectoral, inclusive and long-term planning and implementation of adaptation actions with benefits to many sectors and systems. ( ''high confidence'' ). { ''WGII SPM C.4, WGII SPM C.4.3, WGII TS.D.3.1'' }

'''Systemic barriers constrain the implementation of adaptation options in vulnerable sectors, regions and social groups (''' '''''high confidence).''''' Key barriers include limited resources, lack of private-sector and civic engagement, insufficient mobilisation of finance, lack of political commitment, limited research and/or slow and low uptake of adaptation science and a low sense of urgency. Inequity and poverty also constrain adaptation, leading to soft limits and resulting in disproportionate exposure and impacts for most vulnerable groups ( ''high confidence'' ). The largest adaptation gaps exist among lower income population groups ( ''high confidence'' ). As adaptation options often have long implementation times, long-term planning and accelerated implementation, particularly in this decade, is important to close adaptation gaps, recognising that constraints remain for some regions ( ''high confidence'' ). Prioritisation of options and transitions from incremental to transformational adaptation are limited due to vested interests, economic lock-ins, institutional path dependencies and prevalent practices, cultures, norms and belief systems ( ''high confidence'' ). Many funding, knowledge and practice gaps remain for effective implementation, monitoring and evaluation of adaptation ( ''high confidence'' ), including, lack of climate literacy at all levels and limited availability of data and information ( ''medium confidence'' ); for example for Africa, severe climate data constraints and inequities in research funding and leadership reduce adaptive capacity ( ''very high confidence'' ). { ''WGII SPM C.1.2, WGII SPM C.3.1, WGII TS.D.1.3, WGII TS.D.1.5, WGII TS.D.2.4'' }

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<span id="lack-of-finance-as-a-barrier-to-climate-action"></span>
==== 2.3.3. Lack of Finance as a Barrier to Climate Action ====

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'''Insufficient financing, and a lack of political frameworks and incentives for finance, are key causes of the implementation gaps for both mitigation and adaptation (''' '''''high confidence). Financial flows remained heavily focused on mitigation, are uneven, and have developed heterogeneously across regions and sectors (''''' '''''high confidence).''''' In 2018, public and publicly mobilised private climate finance flows from developed to developing countries were below the collective goal under the UNFCCC and Paris Agreement to mobilise USD 100 billion per year by 2020 in the context of meaningful mitigation action and transparency on implementation ( ''medium confidence'' ). Public and private finance flows for fossil fuels are still greater than those 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 of these markets to many developing countries ( ''high confidence'' ). { ''WGII SPM C.3.2, WGII SPM C.5.4; WGIII SPM B.5.4, WGIII SPM E.5.1'' }

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 allocated to 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 of adaptation 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 climate change ( ''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 the poorest and most vulnerable populations. Accelerated financial support for developing countries from developed 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. ( ''high confidence'' ). { ''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 the financial sector include: limited local capital markets; unattractive risk-return profiles, in particular due to missing 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; SR1.5 SPM D.5.2'' }

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

Modelled scenarios and pathways '''[[#footnote-055|102]]''' are used to explore future emissions, climate change, related impacts and risks, 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 contain regionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition of these assumptions. Most do not make explicit assumptions about global equity, environmental justice or intra-regional income distribution. IPCC is neutral with regard to the assumptions underlying the scenarios in the literature assessed in this report, which do not cover all possible futures '''[[#footnote-054|103]]''' . { ''WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1; SROCC Box SPM.1; SRCCL 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 to climate 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 levels '''[[#footnote-053|104]]''' . 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, SRCCL Figure SPM.2'' }

WGI assessed the climate response to five illustrative scenarios based on SSPs '''[[#footnote-052|105]]''' that cover the range of possible 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 for aerosols and non- CH 4 ozone precursors. The high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5) have CO 2 emissions that roughly double from current levels by 2100 and 2050, respectively '''[[#footnote-051|106]]''' . The intermediate GHG emissions scenario (SSP2-4.5) has CO 2 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 CO 2 emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO 2 emissions. In addition, Representative Concentration Pathways (RCPs) '''[[#footnote-050|107]]''' were used by WGI and WGII to assess regional climate changes, impacts and risks. { ''WGI BoxSPM.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% likelihood '''[[#footnote-049|108]]''' with no or limited overshoot (C1) to pathways 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 response '''[[#footnote-048|109]]''' . { ''WGIII Box 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-drivers '''[[#footnote-047|110]]''' and climate impacts for a level of global warming '''[[#footnote-046|111]]''' are common to all scenarios considered and independent of timing 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'' )

'''Risks'''

Dynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result in risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the Reasons for Concern (RFCs) – five globally 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 not achieve 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; SROCC Errata Figure SPM.3; SRCCL Figure SPM.2'' } ( ''3.1.2, Cross-Section Box.2 Figure 1, Figure 3.3'' )

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[[File:cd5731fe0df129fa508da850d6fdcb4c IPCC_AR6_SYR_CSB_2_Figure_1.png]]
\* 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 Wm ''–2'' ) resulting from the scenario in the year 2100.

\** 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 W m ''-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. CO 2 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 are shown 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, WGIII Figure 3.11'' }

[https://www.ipcc.ch/figures/csb-2-figure-1 ]

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<span id="section-3-long-term-climate-and-development-futures"></span>