APPROVED Summary for Policymakers IPCC AR6 WG III
A. Introduction and framing
The Working Group III (WG III) contribution to the IPCC’s Sixth Assessment Report (AR6) assesses
literature on the scientific, technological, environmental, economic and social aspects of mitigation of
climate change. [FOOTNOTE 1] Levels of confidence [FOOTNOTE 2] are given in () brackets.
Numerical ranges are presented in square [] brackets. References to Chapters, Sections, Figures and
Boxes in the underlying report and Technical Summary (TS) are given in {} brackets.
FOOTNOTE 1: The Report covers literature accepted for publication by 11 October 2021.
FOOTNOTE 2: Each finding is grounded in an evaluation of underlying evidence and agreement. A
level of confidence is expressed using five qualifiers, typeset in italics: very low, low, medium, high and
very high. The assessed likelihood of an outcome or a result is described as: virtually certain 99–100%
probability, very likely 90–100%, likely 66–100%, more likely than not 50–100%, about as likely as
not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms
may also be used when appropriate, consistent with the IPCC uncertainty guidance:
https://www.ipcc.ch/site/assets/uploads/2018/05/uncertainty-guidance-note.pdf.
The report reflects new findings in the relevant literature and builds on previous IPCC reports, including
the WG III contribution to the IPCC’s Fifth Assessment Report (AR5), the WG I and WG II
contributions to AR6 and the three Special Reports in the Sixth Assessment cycle, [FOOTNOTE 3] as
well as other UN assessments. Some of the main developments relevant for this report include {TS.1,
TS.2}:
FOOTNOTE 3: The three Special Reports are: Global Warming of 1.5°C: an IPCC Special Report on
the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas
emission pathways, in the context of strengthening the global response to the threat of climate change,
sustainable development, and efforts to eradicate poverty (2018); Climate Change and Land: an IPCC
Special Report on climate change, desertification, land degradation, sustainable land management, food
security, and greenhouse gas fluxes in terrestrial ecosystems (2019); IPCC Special Report on the Ocean
and Cryosphere in a Changing Climate (2019).
• An evolving international landscape. The literature reflects, among other factors: developments
in the UN Framework Convention on Climate Change (UNFCCC) process, including the outcomes
of the Kyoto Protocol and the adoption of the Paris Agreement {13, 14, 15, 16}; the UN 2030
Agenda for Sustainable Development including the Sustainable Development Goals (SDGs) {1, 3,
4, 17}; and the evolving roles of international cooperation {14}, finance {15} and innovation {16}.
• Increasing diversity of actors and approaches to mitigation. Recent literature highlights the
growing role of non-state and sub-national actors including cities, businesses, Indigenous Peoples,
citizens including local communities and youth, transnational initiatives, and public-private entities
in the global effort to address climate change {5, 13, 14, 15, 16, 17}. Literature documents the
global spread of climate policies and cost declines of existing and emerging low emission
technologies, along with varied types and levels of mitigation efforts, and sustained reductions in
greenhouse gas (GHG) emissions in some countries {2, 5, 6, 8, 12, 13, 16}, and the impacts of,
and some lessons from, the COVID-19 pandemic. {1, 2, 3, 5, 13, 15, Box TS.1, Cross-Chapter Box
1 in Chapter 1}
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• Close linkages between climate change mitigation, adaptation and development pathways.
The development pathways taken by countries at all stages of economic development impact GHG
emissions and hence shape mitigation challenges and opportunities, which vary across countries
and regions. Literature explores how development choices and the establishment of enabling
conditions for action and support influence the feasibility and the cost of limiting emissions {1, 3,
4, 5, 13, 15, 16}. Literature highlights that climate change mitigation action designed and
conducted in the context of sustainable development, equity, and poverty eradication, and rooted
in the development aspirations of the societies within which they take place, will be more
acceptable, durable and effective {1, 3, 4, 5}. This report covers mitigation from both targeted
measures, and from policies and governance with other primary objectives.
• New approaches in the assessment. In addition to the sectoral and systems chapters {3, 6, 7, 8,
9, 10, 11, 12}, the report includes, for the first time in a WG III report, chapters dedicated to
demand for services, and social aspects of mitigation {5, Box TS.11}, and to innovation,
technology development and transfer {16}. The assessment of future pathways in this report covers
near term (to 2030), medium term (up to 2050), and long term (to 2100) timescales, combining
assessment of existing pledges and actions {4, 5}, with an assessment of emissions reductions, and
their implications, associated with long-term temperature outcomes up to the year 2100
{3}.[FOOTNOTE 4] The assessment of modelled global pathways addresses ways of shifting
development pathways towards sustainability. Strengthened collaboration between IPCC Working
Groups is reflected in Cross-Working Group boxes that integrate physical science, climate risks
and adaptation, and the mitigation of climate change. [FOOTNOTE 5]
FOOTNOTE 4: The term ‘temperature’ is used in reference to “global surface temperatures”
throughout this SPM as defined in footnote 8 of WG I SPM. See FOOTNOTE 14 of Table SPM.1.
Emission pathways and associated temperature changes are calculated using various forms of
models, as summarised in Box SPM.1 and Chapter 3 and discussed in Annex III.
FOOTNOTE 5: Namely: Economic Benefits from Avoided Climate Impacts along Long-Term
Mitigation Pathways {Cross-Working Group Box 1 in Chapter 3}; Urban: Cities and Climate
Change {Cross-Working Group Box 2 in Chapter 8}; and Mitigation and Adaptation via the
Bioeconomy {Cross-Working Group Box 3 in Chapter 12}.
• Increasing diversity of analytic frameworks from multiple disciplines including social
sciences. This report identifies multiple analytic frameworks to assess the drivers of, barriers to
and options for, mitigation action. These include: economic efficiency including the benefits of
avoided impacts; ethics and equity; interlinked technological and social transition processes; and
socio-political frameworks, including institutions and governance {1, 3, 13, Cross-Chapter Box 12
in Chapter 16}. These help to identify risks and opportunities for action including co-benefits and
just and equitable transitions at local, national and global scales. {1, 3, 4, 5, 13, 14, 16, 17}
Section B of this Summary for Policymakers (SPM) assesses Recent developments and current trends,
including data uncertainties and gaps. Section C, System transformations to limit global warming,
identifies emission pathways and alternative mitigation portfolios consistent with limiting global
warming to different levels, and assesses specific mitigation options at the sectoral and system level.
Section D addresses Linkages between mitigation, adaptation, and sustainable development. Section E,
Strengthening the response, assesses knowledge of how enabling conditions of institutional design,
policy, finance, innovation and governance arrangements can contribute to climate change mitigation
in the context of sustainable development.
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B. Recent developments and current trends
B.1 Total net anthropogenic GHG emissions [FOOTNOTE 6] have continued to rise during
the period 2010–2019, as have cumulative net CO2 emissions since 1850. Average annual GHG
emissions during 2010-2019 were higher than in any previous decade, but the rate of growth
between 2010 and 2019 was lower than that between 2000 and 2009. (high confidence) (Figure
SPM.1) {Figure 2.2, Figure 2.5, Table 2.1, 2.2, Figure TS.2}
FOOTNOTE 6: Net GHG emissions in this report refer to releases of greenhouse gases from
anthropogenic sources minus removals by anthropogenic sinks, for those species of gases that are
reported under the common reporting format of the United Nations Framework Convention on Climate
Change (UNFCCC): CO2 from fossil fuel combustion and industrial processes (CO2-FFI); net CO2
emissions from land use, land use change and forestry (CO2-LULUCF); methane (CH4); nitrous oxide
(N2O); and fluorinated gases (F-gases) comprising hydrofluorocarbons (HFCs), perfluorocarbons
(PFCs), sulphur hexafluoride (SF6) as well as nitrogen trifluoride (NF3). Different datasets for GHG
emissions exist, with varying time horizons and coverage of sectors and gases, including some that go
back to 1850. In this report, GHG emissions are assessed from 1990, and CO2 sometimes also from
1850. Reasons for this include data availability and robustness, scope of the assessed literature, and the
differing warming impacts of non-CO2 gases over time.
B.1.1 Global net anthropogenic GHG emissions were 59±6.6 GtCO2-eq [FOOTNOTE 7, 8] in 2019,
about 12% (6.5 GtCO2-eq) higher than in 2010 and 54% (21 GtCO2-eq) higher than in 1990. The annual
average during the decade 2010–2019 was 56±6.0 GtCO2-eq, 9.1 GtCO2-eq yr-1 higher than in 2000-
2009. This is the highest increase in average decadal emissions on record. The average annual rate of
growth slowed from 2.1% yr-1 between 2000 and 2009 to 1.3% yr-1 between 2010 and 2019. (high
confidence) (Figure SPM.1) {Figure 2.2, Figure 2.5, Table 2.1, 2.2, Figure TS.2}
FOOTNOTE 7: GHG emission metrics are used to express emissions of different greenhouse gases in
a common unit. Aggregated GHG emissions in this report are stated in CO2-equivalent (CO2-eq) using
the Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the
contribution of Working Group I to the AR6. The choice of metric depends on the purpose of the
analysis and all GHG emission metrics have limitations and uncertainties, given that they simplify the
complexity of the physical climate system and its response to past and future GHG emissions. {Chapter
2 SM 2.3, Cross-Chapter Box 2 in Chapter 2, Box TS.2, WG I Chapter 7 Supplementary Material}
FOOTNOTE 8: In this SPM, uncertainty in historic GHG emissions is reported using 90 % uncertainty
intervals unless stated otherwise. GHG emission levels are rounded to two significant digits; as a
consequence, small differences in sums due to rounding may occur.
B.1.2 Growth in anthropogenic emissions has persisted across all major groups of GHGs since 1990,
albeit at different rates. By 2019, the largest growth in absolute emissions occurred in CO2 from fossil
fuels and industry followed by CH4, whereas the highest relative growth occurred in fluorinated gases,
starting from low levels in 1990 (high confidence). Net anthropogenic CO2 emissions from land use,
land-use change and forestry (CO2-LULUCF) are subject to large uncertainties and high annual
variability, with low confidence even in the direction of the long-term trend [FOOTNOTE 9]. (Figure
SPM.1) {Figure 2.2, Figure 2.5, 2.2, Figure TS.2}
FOOTNOTE 9: Global databases make different choices about which emissions and removals
occurring on land are considered anthropogenic. Currently, net CO2 fluxes from land reported by global
book-keeping models used here are estimated to be about ~5.5 GtCO2 yr-1 higher than the aggregate
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global net emissions based on national GHG inventories. This difference, which has been considered in
the literature, mainly reflects differences in how anthropogenic forest sinks and areas of managed land
are defined. Other reasons for this difference, which are more difficult to quantify, can arise from the
limited representation of land management in global models and varying levels of accuracy and
completeness of estimated LULUCF fluxes in national GHG inventories. Neither method is inherently
preferable. Even when the same methodological approach is applied, the large uncertainty of CO2-
LULUCF emissions can lead to substantial revisions to estimated emissions. {Cross-Chapter Box 3 in
Chapter 3, 7.2, SRCCL SPM A.3.3}
B.1.3 Historical cumulative net CO2 emissions from 1850 to 2019 were 2400±240 GtCO2 (high
confidence). Of these, more than half (58%) occurred between 1850 and 1989 [1400±195 GtCO2], and
about 42% between 1990 and 2019 [1000±90 GtCO2]. About 17% of historical cumulative net CO2
emissions since 1850 occurred between 2010 and 2019 [410±30 GtCO2]. [FOOTNOTE 10] By
comparison, the current central estimate of the remaining carbon budget from 2020 onwards for limiting
warming to 1.5°C with a probability of 50% has been assessed as 500 Gt CO2, and as 1150 Gt CO2 for
a probability of 67% for limiting warming to 2°C. Remaining carbon budgets depend on the amount of
non-CO2 mitigation (±220 Gt CO2) and are further subject to geophysical uncertainties. Based on central
estimates only, cumulative net CO2 emissions between 2010-2019 compare to about four fifths of the
size of the remaining carbon budget from 2020 onwards for a 50% probability of limiting global
warming to 1.5°C, and about one third of the remaining carbon budget for a 67% probability to limit
global warming to 2°C. Even when taking uncertainties into account, historical emissions between 1850
and 2019 constitute a large share of total carbon budgets for these global warming levels [FOOTNOTE
11, 12]. Based on central estimates only, historical cumulative net CO2 emissions between 1850-2019
amount to about four fifths [FOOTNOTE 12] of the total carbon budget for a 50% probability of limiting
global warming to 1.5°C (central estimate about 2900 GtCO2), and to about two thirds [FOOTNOTE
12] of the total carbon budget for a 67% probability to limit global warming to 2°C (central estimate
about 3550 GtCO2). {Figure 2.7, 2.2, Figure TS.3, WG I Table SPM.2}
FOOTNOTE 10: For consistency with WGI, historical cumulative CO2 emissions from 1850-2019 are
reported using 68% confidence intervals.
FOOTNOTE 11: The carbon budget is the maximum amount of cumulative net global anthropogenic
CO2 emissions that would result in limiting global warming to a given level with a given likelihood,
taking into account the effect of other anthropogenic climate forcers. This is referred to as the total
carbon budget when expressed starting from the pre-industrial period, and as the remaining carbon
budget when expressed from a recent specified date. The total carbon budgets reported here are the sum
of historical emissions from 1850 to 2019 and the remaining carbon budgets from 2020 onwards, which
extend until global net zero CO2 emissions are reached. {Annex I: Glossary; WG I SPM}
FOOTNOTE 12: Uncertainties for total carbon budgets have not been assessed and could affect the
specific calculated fractions.
B.1.4 Emissions of CO2–FFI dropped temporarily in the first half of 2020 due to responses to the
COVID-19 pandemic (high confidence), but rebounded by the end of the year (medium confidence).
The annual average CO2-FFI emissions reduction in 2020 relative to 2019 was about 5.8% [5.1-6.3%],
or 2.2 [1.9-2.4] GtCO2 (high confidence). The full GHG emissions impact of the COVID-19 pandemic
could not be assessed due to a lack of data regarding non-CO2 GHG emissions in 2020. {Cross-Chapter
Box 1 in Chapter 1, Figure 2.6, 2.2, Box TS.1, Box TS.1 Figure 1}
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Figure SPM.1: Global net anthropogenic GHG emissions (GtCO2-eq yr-1) 1990–2019
Global net anthropogenic GHG emissions include CO2 from fossil fuel combustion and industrial processes (CO2-
FFI); net CO2 from land use, land use change and forestry (CO2-LULUCF) [FOOTNOTE 9]; methane (CH4);
nitrous oxide (N2O); fluorinated gases (HFCs; PFCs, SF6, NF3). [FOOTNOTE 6]
Panel a shows aggregate annual global net anthropogenic GHG emissions by groups of gases from 1990 to 2019
reported in GtCO2-eq converted based on global warming potentials with a 100-year time horizon (GWP100-
AR6) from the IPCC Sixth Assessment Report Working Group I (Chapter 7). The fraction of global emissions for
each gas is shown 1990, 2000, 2010, 2019; as well as the aggregate average annual growth rate between these
decades. At the right side of Panel a, GHG emissions in 2019 are broken down into individual components with
the associated uncertainties [90% confidence interval] indicated by the error bars: CO2 FFI ±8%, CO2-LULUCF
±70%, CH4 ±30%, N2O ±60%, F-gases ±30%, GHG ±11%. Uncertainties in GHG emissions are assessed in the
Supplementary Material to Chapter 2. The single year peak of emissions in 1997 was due to higher CO2-LULUCF
emissions from a forest and peat fire event in South East Asia.
Panel b shows global anthropogenic CO2-FFI, net CO2-LULUCF, CH4, N2O and fluorinated gas emissions
individually for the period 1990–2019, normalised relative to 100 in 1990. Note the different scale for the included
fluorinated gas emissions compared to other gases, highlighting its rapid growth from a low base. Shaded areas
indicate the uncertainty range. Uncertainty ranges as shown here are specific for individual groups of greenhouse
gases and cannot be compared. The table shows the central estimate for: absolute emissions in 2019, the absolute
change in emissions between 1990 and 2019, and emissions in 2019 expressed as a percentage of 1990 emissions.
{2.2, Figure 2.5, Figure TS.2, Chapter 2 SM}
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FOOTNOTE 9: Global databases make different choices about which emissions and removals occurring on land
are considered anthropogenic. Currently, net CO2 fluxes from land reported by global book-keeping models used
here are estimated to be about ~5.5 GtCO2 yr-1 higher than the aggregate global net emissions based on national
GHG inventories. This difference, which has been considered in the literature, mainly reflects differences in how
anthropogenic forest sinks and areas of managed land are defined. Other reasons for this difference, which are
more difficult to quantify, can arise from the limited representation of land management in global models and
varying levels of accuracy and completeness of estimated LULUCF fluxes in national GHG inventories. Neither
method is inherently preferable. Even when the same methodological approach is applied, the large uncertainty
of CO2-LULUCF emissions can lead to substantial revisions to estimated emissions. {Cross-Chapter Box 3 in
Chapter 3, 7.2, SRCCL SPM A.3.3}
FOOTNOTE 6: Net GHG emissions in this report refer to releases of greenhouse gases from anthropogenic
sources minus removals by anthropogenic sinks, for those species of gases that are reported under the common
reporting format of the United Nations Framework Convention on Climate Change (UNFCCC): CO2 from fossil
fuel combustion and industrial processes (CO2-FFI); net CO2 emissions from land use, land use change and
forestry (CO2-LULUCF); methane (CH4); nitrous oxide (N2O); and fluorinated gases (F-gases) comprising
hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) as well as nitrogen trifluoride
(NF3). Different datasets for GHG emissions exist, with varying time horizons and coverage of sectors and gases,
including some that go back to 1850. In this report, GHG emissions are assessed from 1990, and CO2 sometimes
also from 1850. Reasons for this include data availability and robustness, scope of the assessed literature, and the
differing warming impacts of non-CO2 gases over time.
B.2 Net anthropogenic GHG emissions have increased since 2010 across all major sectors
globally. An increasing share of emissions can be attributed to urban areas. Emissions reductions
in CO2 from fossil fuels and industrial processes, 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. (high confidence) {2.2, 2.4,
6.3, 7.2, 8.3, 9.3, 10.1, 11.2}
B.2.1 In 2019, approximately 34% [20 GtCO2-eq] of total net anthropogenic GHG emissions came
from the energy supply sector, 24% [14 GtCO2-eq] from industry, 22% [13 GtCO2-eq]from agriculture,
forestry and other land use (AFOLU), 15% [8.7 GtCO2-eq] from transport and 6% [3.3 GtCO2-eq] from
buildings.13 If emissions from electricity and heat production are attributed to the sectors that use the
final energy, 90% of these indirect emissions are allocated to the industry and buildings sectors,
increasing their relative GHG emissions shares from 24% to 34%, and from 6% to 16%, respectively.
After reallocating emissions from electricity and heat production, the energy supply sector accounts for
12% of global net anthropogenic GHG emissions. (high confidence) {Figure 2.12, 2.2, 6.3, 7.2, 9.3,
10.1, 11.2, Figure TS.6}
FOOTNOTE 13: Sector definitions can be found in Annex II 9.1.
B.2.2 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% per year in the transport sector (high confidence). Emissions growth in
AFOLU, comprising emissions from agriculture (mainly CH4 and N2O) and forestry and other land use
(mainly CO2) is more uncertain than in other sectors due to the high share and uncertainty of CO2-
LULUCF emissions (medium confidence). About half of total net AFOLU emissions are from CO2
LULUCF, predominantly from deforestation. [FOOTNOTE 14] (medium confidence). {Figure 2.13,
2.2, 6.3, 7.2, Figure 7.3, 9.3, 10.1, 11.2, TS.3}
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FOOTNOTE 14: Land overall constituted a net sink of -6.6 (±4.6) GtCO2 yr-1 for the period 2010-
2019, comprising a gross sink of -12.5 (±3.2) GtCO2 yr-1 resulting from responses of all land to both
anthropogenic environmental change and natural climate variability, and net anthropogenic CO2-
LULUCF emissions +5.9 (±4.1) GtCO2 yr-1 based on book-keeping models. {2.2, 7.2, Table 7.1}
B.2.3 The global share of emissions that can be attributed to urban areas is increasing. In 2015, urban
emissions were estimated to be 25 GtCO2-eq (about 62% of the global share) and in 2020, 29 GtCO2-
eq (67-72% of the global share).15 The drivers of urban GHG emission are complex and include
population size, income, state of urbanisation and urban form. (high confidence) {8.1, 8.3}
FOOTNOTE 15: This estimate is based on consumption-based accounting, including both direct
emissions from within urban areas, and indirect emissions from outside urban areas related to the
production of electricity, goods and services consumed in cities. These estimates include all CO2 and
CH4 emission categories except for aviation and marine bunker fuels, land-use change, forestry and
agriculture. {8.1, Annex I: Glossary}
B.2.4 Global energy intensity (total primary energy per unit GDP) decreased by 2% yr-1 between 2010
and 2019. Carbon intensity (CO2 from fossil fuel combustion and industrial processes (CO2 FFI) per
unit primary energy) decreased by 0.3% yr-1, with large regional variations, over the same period mainly
due to fuel switching from coal to gas, reduced expansion of coal capacity, and increased use of
renewables. This reversed the trend observed for 2000–2009. For comparison, the carbon intensity of
primary energy is projected to decrease globally by about 3.5% yr-1 between 2020 and 2050 in modelled
scenarios that limit warming to 2°C (>67%), and by about 7.7% yr-1 globally in scenarios that limit
warming to 1.5°C (>50%) with no or limited overshoot.16 (high confidence) {Figure 2.16, 2.2, 2.4, Table
3.4, 3.4, 6.3}
FOOTNOTE 16: See Box SPM.1 for the categorisation of modelled long-term emission scenarios
based on projected temperature outcomes and associated probabilities adopted in this report.
B.3 Regional contributions [FOOTNOTE 17] to global GHG emissions continue to differ
widely. Variations in regional, and national per capita emissions partly reflect different
development stages, but they also vary widely at similar income levels. The 10% of households
with the highest per capita emissions contribute a disproportionately large share of global
household GHG emissions. At least 18 countries have sustained GHG emission reductions for
longer than 10 years. (high confidence) (Figure SPM.2) {Figure 1.1, Figure 2.9, Figure 2.10, Figure
2.25, 2.2, 2.3, 2.4, 2.5, 2.6, Figure TS.4, Figure TS.5}
FOOTNOTE 17: See Working Group III Annex II, Part 1 for regional groupings adopted in this report.
B.3.1 GHG emissions trends over 1990-2019 vary widely across regions and over time, and across
different stages of development as shown in Figure SPM.2. Average global per capita net anthropogenic
GHG emissions increased from 7.7 to 7.8 tCO2-eq, ranging from 2.6 tCO2-eq to 19 tCO2-eq across
regions. Least Developed Countries (LDCs) and Small Island Developing States (SIDS) have much
lower per capita emissions (1.7 tCO2-eq, 4.6 tCO2-eq, respectively) than the global average (6.9 tCO2-
eq), excluding CO2-LULUCF [FOOTNOTE 18]. (high confidence) (Figure SPM.2) {Figure1.2, Figure
2.9, Figure 2.10, 2.2, Figure TS.4}
FOOTNOTE 18: In 2019, LDCs are estimated to have emitted 3.3% of global GHG emissions, and
SIDS are estimated to have emitted 0.60% of global GHG emissions, excluding CO2-LULUCF. These
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country groupings cut across geographic regions and are not depicted separately in Fig SPM2. {Figure
2.10}
B.3.2 Historical contributions to cumulative net anthropogenic CO2 emissions between 1850 and
2019 vary substantially across regions in terms of total magnitude, but also in terms of contributions to
CO2-FFI (1650 +/- 73 GtCO2-eq) and net CO2-LULUCF (760 +/- 220 GtCO2-eq)
emissions.[FOOTNOTE 19] Globally, the major share of cumulative CO2-FFI emissions is
concentrated in a few regions, while cumulative CO2-LULUCF [FOOTNOTE 9] emissions are
concentrated in other regions. LDCs contributed less than 0.4% of historical cumulative CO2-FFI
emissions between 1850 and 2019, while SIDS contributed 0.5%. (high confidence) (Figure SPM.2)
{Figure 2.10, 2.2, TS.3, Figure 2.7}
FOOTNOTE 9: Global databases make different choices about which emissions and removals
occurring on land are considered anthropogenic. Currently, net CO2 fluxes from land reported by global
book-keeping models used here are estimated to be about ~5.5 GtCO2 yr-1 higher than the aggregate
global net emissions based on national GHG inventories. This difference, which has been considered in
the literature, mainly reflects differences in how anthropogenic forest sinks and areas of managed land
are defined. Other reasons for this difference, which are more difficult to quantify, can arise from the
limited representation of land management in global models and varying levels of accuracy and
completeness of estimated LULUCF fluxes in national GHG inventories. Neither method is inherently
preferable. Even when the same methodological approach is applied, the large uncertainty of CO2-
LULUCF emissions can lead to substantial revisions to estimated emissions. {Cross-Chapter Box 3 in
Chapter 3, 7.2, SRCCL SPM A.3.3}
FOOTNOTE 19: For consistency with WGI, historical cumulative CO2 emissions from 1850-2019 are
reported using 68% confidence intervals.
B.3.3 In 2019, around 48% of the global population lives in countries emitting on average more than
6t CO2-eq per capita, excluding CO2-LULUCF. 35% live in countries emitting more than 9 tCO2-eq per
capita. Another 41% live in countries emitting less than 3 tCO2-eq per capita. A substantial share of the
population in these low emitting countries lack access to modern energy services (FOOTNOTE 20).
Eradicating extreme poverty, energy poverty, and providing decent living standards (FOOTNOTE 21)
to all in these regions in the context of achieving sustainable development objectives, in the near-term,
can be achieved without significant global emissions growth. (high confidence) (Figure SPM.2) {Figure
1.2, 2.2, 2.4, 2.6, 3.7, 4.2, 6.7, Figure TS.4, Figure TS.5}
FOOTNOTE 20: In this report, access to modern energy services is defined as access to clean, reliable
and affordable energy services for cooking and heating, lighting, communications, and productive uses
(See Annex I: Glossary)
FOOTNOTE 21: In this report, decent living standards are defined as a set of minimum material
requirements essential for achieving basic human well-being, including nutrition, shelter, basic living
conditions, clothing, health care, education, and mobility. (See 5.1)
B.3.4 Globally, the 10% of households with the highest per capita emissions contribute 34-45% of
global consumption-based household GHG emissions [FOOTNOTE 22], while the middle 40%
contribute 40-53%, and the bottom 50% contribute 13-15%. (high confidence) {2.6, Figure 2.25}
FOOTNOTE 22: Consumption-based emissions refer to emissions released to the atmosphere to
generate the goods and services consumed by a certain entity (e.g., a person, firm, country, or region).
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The bottom 50% of emitters spend less than USD3PPP per capita per day. The top 10% of emitters (an
open-ended category) spend more than USD23PPP per capita per day. The wide range of estimates for
the contribution of the top 10% result from the wide range of spending in this category and differing
methods in the assessed literature. {Annex I: Glossary; 2.6}
B.3.5 At least 18 countries have sustained production-based GHG and consumption-based CO2
emission reductions for longer than 10 years. Reductions were linked to energy supply decarbonisation,
energy efficiency gains, and energy demand reduction, which resulted from both policies and changes
in economic structure. Some countries have reduced production-based GHG emissions by a third or
more since peaking, and some have achieved several years of consecutive reduction rates of around 4
%/yr, comparable to global reductions in scenarios limiting warming to 2°C (>67%) or lower. These
reductions have only partly offset global emissions growth. (high confidence) (Figure SPM.2) {Figure
TS.4, 2.2, 1.3.2}
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Figure SPM.2: Regional GHG emissions, and the regional proportion of total cumulative production-
based CO2 emissions from 1850–2019
Panel a shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr-1 (GWP100 AR6)) for the
time period 1990–2019 [FOOTNOTE 6]. Percentage values refer to the contribution of each region to total GHG
emissions in each respective time period. The single year peak of emissions in 1997 was due to higher CO2-
LULUCF emissions from a forest and peat fire event in South East Asia. Regions are as grouped in Annex II.
Panel b shows the share of historical cumulative net anthropogenic CO2 emissions per region from 1850 to 2019
in GtCO2. This includes CO2 from fossil fuel combustion and industrial processes (CO2-FFI) and net CO2 Land
use, land use change, forestry (CO2-LULUCF). Other GHG emissions are not included [FOOTNOTE 6]. CO2-
LULUCF emissions are subject to high uncertainties, reflected by a global uncertainty estimate of ± 70% (90%
confidence interval).
Panel c shows the distribution of regional GHG emissions in tonnes CO2-eq per capita by region in 2019. GHG
emissions are categorised into: CO2-FFI, net CO2-LULUCF and other GHG emissions (methane, nitrous oxide,
fluorinated gases, expressed in CO2-eq using GWP100-AR6). The height of each rectangle shows per-capita
emissions, the width shows the population of the region, so that the area of the rectangles refers to the total
emissions for each region. Emissions from international aviation and shipping are not included. In the case of two
regions, the area for CO2-LULUCF is below the axis, indicating net CO2 removals rather than emissions. CO2-
LULUCF emissions are subject to high uncertainties, reflected by a global uncertainty estimate of ± 70% (90%
confidence interval).
Panel d shows population, GDP per person, emission indicators by region in 2019 for percentage GHG
contributions, total GHG per person, and total GHG emissions intensity, together with production-based and
consumption-based CO2-FFI data, which is assessed in this report up to 2018. Consumption-based emissions are
emissions released to the atmosphere in order to generate the goods and services consumed by a certain entity
(e.g., region). Emissions from international aviation and shipping are not included.
{1.3, Figure 1.2, 2.2, Figure 2.9, Figure 2.10, Figure 2.11, Annex II}
B.4 The unit costs of several low-emission technologies have fallen continuously since 2010.
Innovation policy packages have enabled these cost reductions and supported global adoption.
Both tailored policies and comprehensive policies addressing innovation systems have helped
overcome the distributional, environmental and social impacts potentially associated with global
diffusion of low-emission technologies. Innovation has lagged in developing countries due to
weaker enabling conditions. Digitalisation can enable emission reductions, but can have adverse
side-effects unless appropriately governed. (high confidence) (Figure SPM.3) {2.2, 6.3, 6.4, 7.2,
12.2, 16.2, 16.4, 16.5, Cross-Chapter Box 11 in Chapter 16}
B.4.1 From 2010–2019, there have been sustained decreases in the unit costs of solar energy (85%),
wind energy (55%), and lithium-ion batteries (85%), and large increases in their deployment, e.g., >10x
for solar and >100x for electric vehicles (EVs), varying widely across regions (Figure SPM.3). The mix
of policy instruments which reduced costs and stimulated adoption includes public R&D, funding for
demonstration and pilot projects, and demand pull instruments such as deployment subsidies to attain
scale. 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. (high confidence) {1.3, 1.5, Figure 2.5, 2.5, 6.3, 6.4,
7.2, 11.3, 12.2, 12.3, 12.6, 13.6, 16.3, 16.4, 16.6}
B.4.2 Policy packages tailored to national contexts and technological characteristics have been
effective in supporting low-emission innovation and technology diffusion. Appropriately designed
policies and governance have helped address distributional impacts and rebound effects. Innovation has
provided opportunities to lower emissions and reduce emission growth and created social and
environmental co-benefits. (high confidence) Adoption of low-emission technologies lags in most
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developing countries, particularly least developed ones, due in part to weaker enabling conditions,
including limited finance, technology development and transfer, and capacity. In many countries,
especially those with limited institutional capacities, 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. 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) {9.9, 13.6, 13.7, 16.3, 16.4, 16.5, 16.6, Cross-Chapter
Box 12 in Chapter 16, TS.3}
B.4.3 Digital technologies can contribute to mitigation of climate change and the achievement of
several SDGs (high confidence). For example, sensors, Internet of Things, robotics, and artificial
intelligence can improve energy management in all sectors, increase energy efficiency, and promote the
adoption of many low-emission technologies, including decentralised renewable energy, while creating
economic opportunities (high confidence). 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 (high confidence). Digitalisation can involve trade-offs across several SDGs, e.g., increasing
electronic waste, negative impacts on labour markets, and exacerbating the existing digital divide.
Digital technology supports decarbonisation only if appropriately governed (high confidence). {5.3, 10,
12.6, 16.2, Cross-Chapter Box 11 in Chapter 16, TS.5, Box TS.14}
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Figure SPM.3: Unit cost reductions and use in some rapidly changing mitigation technologies
The top panel shows global costs per unit of energy (USD/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. Grey shading indicates the range of unit costs for new fossil fuel
(coal and gas) power in 2020 (corresponding to USD55–148 per MWh). In 2020, the levelised costs of energy
(LCOE) of the four 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 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 since AR5. Shares of electricity produced and share of passenger vehicle fleet are indicated
in text for 2020 based on provisional data, i.e., percentage of total electricity production (for PV, onshore wind,
offshore wind, CSP) and of total stock of passenger vehicles (for electric vehicles). The electricity production
share reflects different capacity factors; e.g., for the same amount of installed capacity, wind produces about twice
as much electricity as solar PV. {2.5, 6.4}
Renewable energy and battery technologies were selected as illustrative examples because they have recently
shown rapid changes in costs and adoption, and because consistent data are available. Other mitigation options
assessed in the report are not included as they do not meet these criteria.
B.5 There has been a consistent expansion of policies and laws addressing mitigation since
AR5. This has led to the avoidance of emissions that would otherwise have occurred and increased
investment in low-GHG technologies and infrastructure. Policy coverage of emissions is uneven
across sectors. Progress on the alignment of financial flows towards the goals of the Paris
Agreement remains slow and tracked climate finance flows are distributed unevenly across
regions and sectors. (high confidence) {5.6, 13.2, 13.4, 13.5, 13.6, 13.9, 14.3, 14.4, 14.5, Cross-
Chapter Box 10 in Chapter 14, 15.3, 15.5}
B.5.1 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). At least 18 countries that had Kyoto targets for the first commitment period have had
sustained absolute emission reductions for at least a decade from 2005, of which two were countries
with economies in transition (very high confidence). The Paris Agreement, with near universal
participation, has led to policy development and target-setting at national and sub-national levels, in
particular in relation to mitigation, as well as enhanced transparency of climate action and support
(medium confidence). {14.3, 14.6}
B.5.2 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). 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). By 2020, there were
‘direct’ climate laws focused primarily on GHG reductions in 56 countries covering 53% of global
emissions (medium confidence). Policy coverage remains limited for emissions from agriculture and
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the production of industrial materials and feedstocks (high confidence). {5.6, 7.6, 11.5, 11.6, 13.2,
13.6}
B.5.3 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). Multiple lines of evidence suggest that mitigation policies have led to
avoided global emissions of several Gt CO2-eq yr-1 (medium confidence). At least 1.8 Gt CO2-eq yr-1
can be accounted for by aggregating separate estimates for the effects of economic and regulatory
instruments. Growing numbers of laws and executive orders have impacted global emissions and were
estimated to result in 5.9 Gt CO2-eq yr-1 less in 2016 than they otherwise would have been. (medium
confidence) (Figure SPM.3) {2.2, 2.8, 6.7, 7.6, 9.9, 10.8, 13.6, Cross-chapter Box 10 in Chapter 14}
B.5.4 Annual tracked total financial flows for climate mitigation and adaptation increased by up to
60% between 2013/14 and 2019/20 (in USD2015), but average growth has slowed since 201823
(medium confidence). These 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 mobilize 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). Markets for green bonds, ESG (environmental, social and
governance) and sustainable finance products have expanded significantly since AR5. Challenges
remain, in particular around integrity and additionality, as well as the limited applicability of these
markets to many developing countries. (high confidence) {Box 15.4, 15.3, 15.5, 15.6, Box 15.7}
FOOTNOTE 23: Estimates of financial flows (comprising both private and public, domestic and
international flows) are based on a single report which assembles data from multiple sources and which
has applied various changes to their methodology over the past years. Such data can suggest broad
trends but is subject to uncertainties.
B.6 Global GHG emissions in 2030 associated with the implementation of nationally
determined contributions (NDCs) announced prior to COP26 [FOOTNOTE 24] would make it
likely that warming will exceed 1.5°C during the 21st century.[FOOTNOTE 25] Likely limiting
warming to below 2°C would then rely on a rapid acceleration of mitigation efforts after 2030.
Policies implemented by the end of 2020 [FOOTNOTE 26] are projected to result in higher global
GHG emissions than those implied by NDCs. (high confidence) (Figure SPM.4) {3.3, 3.5, 4.2,
Cross-Chapter Box 4 in Chapter 4}
FOOTNOTE 24: NDCs announced prior to COP26 refer to the most recent nationally determined
contributions submitted to the UNFCCC up to the literature cut-off date of this report, 11 October 2021,
and revised NDCs announced by China, Japan and the Republic of Korea prior to October 2021 but
only submitted thereafter. 25 NDC updates were submitted between 12 October 2021 and prior to the
start of COP26.
FOOTNOTE 25: This implies that mitigation after 2030 can no longer establish a pathway with less
than 67% probability to exceed 1.5°C during the 21st century, a defining feature of the class of pathways
that limit warming to 1.5°C (>50%) with no or limited overshoot assessed in this report (Category C1
in Table SPM.1). These pathways limit warming to 1.6°C or lower throughout the 21st century with a
50% likelihood.
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FOOTNOTE 26: The policy cut-off date in studies used to project GHG emissions of “policies
implemented by the end of 2020” varies between July 2019 and November 2020. {Table 4.2}
B.6.1 Policies implemented by the end of 2020 are projected to result in higher global GHG emissions
than those implied by NDCs, indicating an implementation gap. A gap remains between global GHG
emissions in 2030 associated with the implementation of NDCs announced prior to COP26 and those
associated with modelled mitigation pathways assuming immediate action (for quantification see Table
SPM.X). [FOOTNOTE 27] The magnitude of the emission gap depends on the global warming level
considered and whether only unconditional or also conditional elements of NDCs [FOOTNOTE 28] are
considered.[FOOTNOTE 29] (high confidence) {3.5, 4.2, Cross-Chapter Box 4 in Chapter 4}
Table SPM.X: Projected global emissions in 2030 associated with policies implemented by the end of
2020 and NDCs announced prior to COP26, and associated emission gaps. *Emissions projections for
2030 and absolute differences in emissions are based on emissions of 52-56 GtCO2-eq yr-1 in 2019 as
assumed in underlying model studies. (medium confidence){4.2, Table 4.3, Cross-Chapter Box 4 in
Chapter 4}
GtCO2-eq yr-1 Implied by policies Implied by NDCs announced
implemented by the prior to COP26
end of 2020
Unconditional Inc.
elements conditional
elements
Median (Min–Max)* 57 (52–60) 53 (50–57) 50 (47–55)
Implementation gap between 4 7
implemented policies and NDCs
(Median)
Emission gap between NDCs and 10–16 6–14
pathways that limit warming to 2°C
(>67%) with immediate action
Emissions gap between NDCs and 19–26 16–23
pathways that limit warming to 1.5°C
(>50%) with no or limited overshoot
with immediate action
FOOTNOTE 27: Immediate action in modelled global pathways refers to the adoption between 2020
and at latest before 2025 of climate policies intended to limit global warming to a given level. Modelled
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pathways that limit warming to 2°C (>67%) based on immediate action are summarised in Category
C3a in Table SPM.1. All assessed modelled global pathways that limit warming to 1.5°C (>50%) with
no or limited overshoot assume immediate action as defined here (Category C1 in Table SPM.1).
FOOTNOTE 28: In this report, “unconditional” elements of NDCs refer to mitigation efforts put
forward without any conditions. “Conditional” elements refer to mitigation efforts that are contingent
on international cooperation, for example bilateral and multilateral agreements, financing or monetary
and/or technological transfers. This terminology is used in the literature and the UNFCCC’s NDC
Synthesis Reports, not by the Paris Agreement. {4.2.1, 14.3.2}
FOOTNOTE 29: Two types of gaps are assessed: The implementation gap is calculated as the
difference between the median of global emissions in 2030 implied by policies implemented by the end
of 2020 and those implied by NDCs announced prior to COP26. The emissions gap is calculated as the
difference between GHG emissions implied by the NDCs (minimum/maximum emissions in 2030) and
the median of global GHG emissions in modelled pathways limiting warming to specific levels based
on immediate action and with stated likelihoods as indicated (Table SPM.1).
B.6.2 Global emissions in 2030 associated with the implementation of NDCs announced prior to
COP26 are lower than the emissions implied by the original NDCs [FOOTNOTE 30] (high confidence).
The original emission gap has fallen by about 20% to one third relative to pathways that limit warming
to 2°C (>67%) with immediate action (Category C3a in Table SPM.1), and by about 15-20% relative
to pathways limiting warming to 1.5°C (>50%) with no or limited overshoot (Category C1 in Table
SPM.1) (medium confidence). (Figure SPM.4) {3.5, 4.2, Cross-Chapter Box 4 in Chapter 4}
FOOTNOTE 30: Original NDCs refer to those submitted to the UNFCCC in 2015 and 2016.
Unconditional elements of NDCs announced prior to COP26 imply global GHG emissions in 2030 that
are 3.8 [3.0–5.3] GtCO2-eq yr-1 lower than those from the original NDCs, and 4.5 [2.7–6.3] GtCO2-eq
yr-1 lower when conditional elements of NDCs are included. NDC updates at or after COP26 could
further change the implied emissions.
B.6.3 Modelled global emission pathways consistent with NDCs announced prior to COP26 that limit
warming to 2°C (>67%) (Category C3b in Table SPM.1) imply annual average global GHG emissions
reduction rates of 0–0.7 GtCO2-eq per year during the decade 2020-2030, with an unprecedented
acceleration to 1.4–2.0 GtCO2-eq per year during 2030-2050 (medium confidence). Continued
investments in unabated high emitting infrastructure and limited development and deployment of low
emitting alternatives prior to 2030 would act as barriers to this acceleration and increase feasibility risks
(high confidence). {3.3, 3.5, 3.8, Cross-Chapter Box 5 in Chapter 4}
B.6.4 Modelled global emission pathways consistent with NDCs announced prior to COP26 will
likely exceed 1.5°C during the 21st century. Those pathways that then return warming to 1.5°C by 2100
with a likelihood of 50% or greater imply a temperature overshoot of 0.15-0.3°C (42 pathways in
category C2 in Table SPM.1). In such pathways, global cumulative net-negative CO2 emissions are -
380 [-860 to -200] GtCO2 [FOOTNOTE 31] in the second half of the century, and there is a rapid
acceleration of other mitigation efforts across all sectors after 2030. Such overshoot pathways imply
increased climate-related risk, and are subject to increased feasibility concerns[FOOTNOTE 32], and
greater social and environmental risks, compared to pathways that limit warming to 1.5°C (>50%) with
no or limited overshoot. (high confidence) (Figure SPM.4, Table SPM.1) {3.3, 3.5, 3.8, 12.3; WG II
SPM.B.6}
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FOOTNOTE 31: Median and very likely range [5th to 95th percentile].
FOOTNOTE 32: Returning to below 1.5°C in 2100 from GHG emissions levels in 2030 associated
with the implementation of NDCs is infeasible for some models due to model-specific constraints on
the deployment of mitigation technologies and the availability of net negative CO2 emissions.
Figure SPM.4: Global GHG emissions of modelled pathways (funnels in Panel a. and associated bars in
Panels b, c, d) and projected emission outcomes from near-term policy assessments for 2030 (Panel b).
Panel a shows global GHG emissions over 2015-2050 for four types of assessed modelled global pathways:
● Trend from implemented policies: Pathways with projected near-term GHG emissions in line with
policies implemented until the end of 2020 and extended with comparable ambition levels beyond 2030
(29 scenarios across categories C5-C7, Table SPM.1)
● Limit to 2°C (>67%) or return warming to 1.5°C (>50%) after a high overshoot, NDCs until 2030:
Pathways with GHG emissions until 2030 associated with the implementation of NDCs announced
prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2°C (C3b,
Table SPM.1) or to return warming to 1.5°C with a probability of 50% or greater after high overshoot
(subset of 42 scenarios from C2, Table SPM.1).
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● Limit to 2°C (>67%) with immediate action: Pathways that limit warming to 2°C (>67%) with
immediate action after 202027 (C3a, Table SPM.1).
● Limit to 1.5°C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5°C with no or
limited overshoot (C1, Table SPM.1 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 [FOOTNOTE 33] and past global GHG emissions in 2015 and 2019 as assessed in
Chapter 2 are shown by whiskers.
FOOTNOTE 33: See the Box SPM.1 for a description of the approach to project global warming outcomes of
modelled pathways and its consistency between the climate assessment in AR6 WG I.
Panels b, c and d show snapshots of the GHG emission ranges of the modelled pathways in 2030, 2050, and
2100, respectively. Panel b also shows projected emissions outcomes from near-term policy assessments in 2030
from Chapter 4.2 (Tables 4.2 and 4.3; median and full range). GHG emissions are in CO2-equivalent using
GWP100 from AR6 WG I. {3.5, 4.2, Tables 4.2 and 4.3, Cross-Chapter Box 4 in Chapter 4}
B.7 Projected cumulative future CO2 emissions over the lifetime of existing and currently
planned fossil fuel infrastructure without additional abatement exceed the total cumulative net
CO2 emissions in pathways that limit warming to 1.5°C (>50%) with no or limited overshoot.
They are approximately equal to total cumulative net CO2 emissions in pathways that limit
warming to 2°C (>67%). (high confidence) {2.7, 3.3}
B.7.1 If historical operating patterns are maintained, [FOOTNOTE 34] and without additional
abatement [FOOTNOTE 35], estimated cumulative future CO2 emissions from existing fossil fuel
infrastructure, the majority of which is in the power sector, would, from 2018 until the end of its
lifetime, amount to 660 [460–890] GtCO2. They would amount to 850 [600–1100] GtCO2 when
unabated emissions from currently planned infrastructure in the power sector is included. These
estimates compare with cumulative global net CO2 emissions from all sectors of 510 [330–710] GtCO2
until the time of reaching net zero CO2 emissions [FOOTNOTE 36] in pathways that limit warming to
1.5°C (>50%) with no or limited overshoot, and 890 [640–1160] GtCO2 in pathways that limit warming
to 2°C (>67%). (Table SPM.1) (high confidence) {2.7, Figure 2.26, Figure TS.8}
FOOTNOTE 34: Historical operating patterns are described by load factors and lifetimes of fossil fuel
installations as observed in the past (average and range).
FOOTNOTE 35: Abatement here refers to human interventions that reduce the amount of greenhouse
gases that are released from fossil fuel infrastructure to the atmosphere.
FOOTNOTE 36: Total cumulative CO2 emissions up to the time of global net zero CO2 emissions are
similar but not identical to the remaining carbon budget for a given temperature limit assessed by
Working Group I. This is because the modelled emission scenarios assessed by Working Group III
cover a range of temperature levels up to a specific limit, and exhibit a variety of reductions in non-CO2
emissions that also contribute to overall warming. {Box 3.4}
B.7.2 In modelled global pathways that limit warming to 2°C (>67%) or lower, most remaining fossil
fuel CO2 emissions until the time of global net zero CO2 emissions are projected to occur outside the
power sector, mainly in industry and transport. Decommissioning and reduced utilisation of existing
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fossil fuel based power sector infrastructure, retrofitting existing installations with CCS [FOOTNOTE
37] switches to low carbon fuels, and cancellation of new coal installations without CCS are major
options that can contribute to aligning future CO2 emissions from the power sector with emissions in
the assessed global modelled least-cost pathways. The most appropriate strategies will depend on
national and regional circumstances, including enabling conditions and technology availability. (high
confidence) {Table 2.7, 2.7, 3.4, 6.3, 6.5, 6.7, Box SPM.1}
FOOTNOTE 37: In this context, capture rates of new installations with CCS are assumed to be 90-
95% + {11.3.5}. Capture rates for retrofit installations can be comparable, if plants are specifically
designed for CCS retrofits {11.3.6}.
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C. System transformations to limit global warming
C.1 Global GHG emissions are projected to peak between 2020 and at the latest before 2025
in global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot
and in those that limit warming to 2°C (>67%) and assume immediate action. [ Table SPM footnote [#9],
FOOTNOTE 38]
In both types of modelled pathways, rapid and deep GHG emissions reductions
follow throughout 2030, 2040 and 2050 (high confidence). Without a strengthening of policies
beyond those that are implemented by the end of 2020, GHG emissions are projected to rise
beyond 2025, leading to a median global warming of 3.2 [2.2 to 3.5] °C by 2100 [FOOTNOTE
39, 40] (medium confidence). (Table SPM.1, Figure SPM.4, Figure SPM.5) {3.3, 3.4}
FOOTNOTE 38: All reported warming levels are relative to the period 1850–1900. If not otherwise
specified, ‘pathways’ always refer to pathways computed with a model. Immediate action in the
pathways refers to the adoption of climate policies between 2020 and at latest 2025 intended to limit
global warming at a given level.
FOOTNOTE 39: Long-term warming is calculated from all modelled pathways assuming mitigation
efforts consistent with national policies that were implemented by the end of 2020 (scenarios that fall
into policy category P1b of Chapter 3) and that pass through the 2030 GHG emissions ranges of such
pathways assessed in Chapter 4 (See FOOTNOTE 25) {3.2, Table 4.2}
FOOTNOTE 40: Warming estimates refer to the 50th and [5th–95th] percentile across the modelled
pathways and the median temperature change estimate of the probabilistic WG I climate model
emulators[Footnote 1] (Table SPM1).
C.1.1 Net global GHG emissions are projected to fall from 2019 levels by 27% [13–45%] by 2030
and 63% [52-76%] [FOOTNOTE 41] by 2050 in global modelled pathways that limit warming to 2°C
(>67%) and assuming immediate action (category C3a, Table SPM.1). This compares with reductions
of 43% [34–60%] by 2030 and 84% [73–98%] by 2050 in pathways that limit warming to 1.5°C
(>50%) with no or limited overshoot (C1, Table SPM.1) (high confidence).[ [FOOTNOTE 42] In
modelled pathways that return warming to 1.5°C (>50%) after a high overshoot [FOOTNOTE 43],
GHG emissions are reduced by 23 [0-44%] in 2030 and by 75 [62-91%] in 2050 (C2, Table SPM.1)
(high confidence). 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°C [2.1-3.4°C] by 2100 (medium confidence). [FOOTNOTE 24] (Figure SPM .4).
{3.3}
FOOTNOTE 41: In this report, emissions reductions are reported relative to 2019 modelled emission
levels, while in SR1.5 emissions reductions were calculated relative to 2010. Between 2010 and 2019
global GHG and global CO2 emissions have grown by 12% (6.5 GtCO2eq) and 13% (5.0 Gt CO2)
respectively. In global modelled pathways assessed in this report that limit warming to 1.5°C (>50%)
with no or limited overshoot, GHG emissions are projected to be reduced by 37% [28-57%] in 2030
relative to 2010. In the same type of pathways assessed in SR1.5, GHG emissions are reduced by 45%
(40-60% interquartile range) relative to 2010. In absolute terms, the 2030 GHG emissions levels of
pathways that limit warming to 1.5°C (>50%) with no or limited overshoot are higher in AR6 (31 [21-
36] GtCO2eq) than in SR1.5 (28 (26-31 interquartile range) GtCO2eq). (Figure SPM. 1, Table SPM.1)
{3.3, SR1.5}
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FOOTNOTE 42: Scenarios in this category limit peak warming to 2°C throughout the 21st century
with close to, or more than, 90% likelihood.
FOOTNOTE 43: This category contains 91 scenarios with immediate action and 42 scenarios that
are consistent with the NDCs until 2030.
C.1.2 In modelled pathways that limit warming to 2°C (>67%) assuming immediate action, global
net CO2 emissions are reduced compared to modelled 2019 emissions by 27% [11–46%] in 2030 and
by 52% [36-70%] in 2040; and global CH4 emissions are reduced by 24% [9–53%] in 2030 and by
37% [20–60%] in 2040. In pathways that limit warming to 1.5°C (>50%) with no or limited overshoot
global net CO2 emissions are reduced compared to modelled 2019 emissions by 48% [36–69%] in
2030 and by 80% [61-109%] in 2040; and global CH4 emissions are reduced by 34% [21–57%] in
2030 and 44% [31-63%] in 2040. There are similar reductions of non-CO2 emissions by 2050 in both
types of pathways: CH4 is reduced by 45% [25–70%]; N2O is reduced by 20% [-5 – 55%]; and F-
Gases are reduced by 85% [20–90%]. [FOOTNOTE 44] Across most modelled pathways, this is the
maximum technical potential for anthropogenic CH4 reductions in the underlying models (high
confidence). Further emissions reductions, as illustrated by the IMP-SP pathway, may be achieved
through changes in activity levels and/or technological innovations beyond those represented in the
majority of the pathways (medium confidence). Higher emissions reductions of CH4 could further
reduce peak warming. (high confidence) (Figure SPM.5) {3.3}
FOOTNOTE 44: These numbers for CH4, N2O, and F-gases are rounded to the nearest 5% except
numbers below 5%.
C.1.3 In modelled pathways consistent with the continuation of policies implemented by the end of
2020, GHG emissions continue to rise, leading to global warming of 3.2 [2.2–3.5]°C by 2100 (within
C5-C7, Table SPM 1) (medium confidence). Pathways that exceed warming of >4°C (≥50%) (C8,
SSP5-8.5, Table SPM.1) would imply a reversal of current technology and/or mitigation policy trends
(medium confidence). Such warming could occur in emission pathways consistent with policies
implemented by the end of 2020 if climate sensitivity is higher than central estimates (high
confidence). (Table SPM.1, Figure SPM.4) {3.3, Box 3.3}
C.1.4 Global modelled pathways falling into the lowest temperature category of the assessed literature
(C1, Table SPM.1) are on average associated with a higher median peak warming in AR6 compared
to pathways in the same category in SR1.5. In the modelled pathways in AR6, the likelihood of
limiting warming to 1.5°C has on average declined compared to SR1.5. This is because GHG
emissions have risen since 2017, and many recent pathways have higher projected emissions by 2030,
higher cumulative net CO2 emissions and slightly later dates for reaching net zero CO2 or net zero
GHG emissions. High mitigation challenges, for example, due to assumptions of slow technological
change, high levels of global population growth, and high fragmentation as in the Shared
Socioeconomic Pathway SSP3, may render modelled pathways that limit warming to 2°C (> 67%) or
lower infeasible. (medium confidence) (Table SPM.1, Box SPM.1) {3.3, 3.8, Annex III Figure II.1,
Annex III Figure II.3}
Table SPM.1 | Key characteristics of the modelled global emissions pathways: Summary of
projected CO2 and GHG emissions, projected net zero timings and the resulting global warming
outcomes. Pathways are categorised (rows), according to their likelihood of limiting warming to
different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels.
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Values shown are for the median [p50] and 5th-95th percentiles [p5-p95], noting that not all pathways
achieve net zero CO2 or GHGs.
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1 Values in the table refer to the 50th and [5th–95th] percentile values across the pathways falling within a given
category as defined in Box SPM.1. For emissions-related columns these values relate to the distribution of all
the pathways in that category. Harmonized emissions values are given for consistency with projected global
warming outcomes using climate emulators. Based on the assessment of climate emulators in AR6 WG I
(Chapter 7, Box 7.1), two climate emulators are used for the probabilistic assessment of the resulting warming
of the pathways. For the ‘Temperature Change’ and ‘Likelihood’ columns, the single upper row values
represent the 50th percentile across the pathways in that category and the median [50th percentile] across the
warming estimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges, the median
warming for every pathway in that category is calculated for each of the two climate model emulators
(MAGICC and FaIR). Subsequently, the 5th and 95th percentile values across all pathways for each emulator
are calculated. The coolest and warmest outcomes (i.e. the lowest p5 of two emulators, and the highest p95,
respectively) are shown in square brackets. These ranges therefore cover both the uncertainty of the emissions
pathways as well as the climate emulators’ uncertainty.
2 For a description of pathways categories see Box SPM.1.
3 All global warming levels are relative to 1850–1900. See Table SPM 1 Footnote 13 below and SPM Scenarios
Box FOOTNOTE 46 for more details.
4 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in
Figure SPM.4. Two pathways derived from a cost-benefit analysis have been added to C3a, whilst 10 pathways
with specifically designed near-term action until 2030, whose emissions fall below those implied by NDCs
announced prior to COP26, are not included in either of the two subsets.
5 Alignment with the categories of the illustrative SSP scenarios considered in AR6 WG I, and the Illustrative
(Mitigation) Pathways (IPs/IMPs) of WG III. The IMPs have common features such as deep and rapid emissions
reductions, but also different combinations of sectoral mitigation strategies. See SPM Box 1 for an introduction
of the IPs and IMPs and Chapter 3 for full descriptions. {3.2, 3.3, Annex III.II.4}
6 The Illustrative Mitigation Pathway ‘Neg’ has extensive use of carbon dioxide removal (CDR) in the AFOLU,
energy and the industry sectors to achieve net negative emissions. Warming peaks around 2060 and declines to
below 1.5°C (50% likelihood) shortly after 2100. Whilst technically classified as C3, it strongly exhibits the
characteristics of C2 high overshoot pathways, hence it has been placed in the C2 category. See SPM C3.1 for
an introduction of the IPs and IMPs.
7 The 2019 range of harmonized GHG emissions across the pathways [53-58 GtCO2eq] is within the uncertainty
ranges of 2019 emissions assessed in Chapter 2 [53-66 GtCO2-eq]. {Fig SPM 1, Fig SPM 2, Box SPM1
FOOTNOTE 50}
8 Rates of global emission reduction in mitigation pathways are reported on a pathway-by-pathway basis
relative to harmonized modelled global emissions in 2019 rather than the global emissions reported in SPM
Section B and Chapter 2; this ensures internal consistency in assumptions about emission sources and activities,
as well as consistency with temperature projections based on the physical climate science assessment by WG I.
{Annex III.II.2.5, FOOTNOTE 50} Negative values (e.g., in C7, C8) represent an increase in emissions.
9 Emissions milestones are provided for 5-year intervals in order to be consistent with the underlying 5-year
time-step data of the modelled pathways. Peak emissions (CO2 and GHGs) are assessed for 5 year reporting
intervals starting in 2020. The interval 2020-2025 signifies that projected emissions peak as soon as possible
between 2020 and at latest before 2025. The upper 5-year interval refers to the median interval within which the
emissions peak or reach net zero. Ranges in square brackets underneath refer to the range across the pathways,
comprising the lower bound of the 5th percentile 5-year interval and the upper bound of the 95th percentile 5-
year interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones.
10 Percentiles reported across all pathways in that category include those that do not reach net zero before 2100
(fraction of pathways reaching net zero is given in round brackets). If the fraction of pathways that reach net
zero before 2100 is lower than the fraction of pathways covered by a percentile (e.g., 0.95 for the 95th
percentile), the percentile is not defined and denoted with "…". The fraction of pathways reaching net zero
includes all with reported non-harmonised, and / or harmonised emissions profiles that reach net zero. Pathways
were counted when at least one of the two profiles fell below 100 MtCO2 yr-1 until 2100.
11 The timing of net zero is further discussed in SPM C2.4 and the Cross-Chapter Box 3 in Chapter 3 on net
zero CO2 and net zero GHG emissions.
12 For cases where models do not report all GHGs, missing GHG species are infilled and aggregated into a
Kyoto basket of GHG emissions in CO2-eq defined by the 100 year global warming potential. For each pathway,
reporting of CO2, CH4, and N2O emissions was the minimum required for the assessment of the climate
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response and the assignment to a climate category. Emissions pathways without climate assessment are not
included in the ranges presented here. See Annex III.II.5.
13 Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively.
They are based on harmonized net CO2 emissions, ensuring consistency with the WG I assessment of the
remaining carbon budget. {Box 3.4, FOOTNOTE 51 in SPM C.2}.
14 Global mean temperature change for category (at peak, if peak temperature occurs before 2100, and in 2100)
relative to 1850–1900, based on the median global warming for each pathway assessed using the probabilistic
climate model emulators calibrated to the AR6 WG I assessment, see also SPM Scenarios Box. {SPM
FOOTNOTE 12, WG I Cross Chapter Box 7.1, Annex III.II.2.5}.
15 Probability of staying below the temperature thresholds for the pathways in each category, taking into
consideration the range of uncertainty from the climate model emulators consistent with the AR6 WG I
assessment. The probabilities refer to the probability at peak temperature. Note that in the case of temperature
overshoot (e.g., category C2 and some pathways in C1), the probabilities of staying below at the end of the
century are higher than the probabilities at peak temperature.
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Box SPM.1: Assessment of modelled global emission scenarios
A wide range of modelled global emission pathways and scenarios from the literature is assessed in this
report, including pathways and scenarios with and without mitigation.[FOOTNOTE 45] Emissions
pathways and scenarios project the evolution of GHG emissions based on a set of internally consistent
assumptions about future socio-economic conditions and related mitigation measures.[FOOTNOTE 46]
These are quantitative projections and are neither predictions nor forecasts. Around half of all modelled
global emission scenarios assume cost-effective approaches that rely on least-cost emission abatement
options globally. The other half looks at existing policies and regionally and sectorally differentiated
actions. Most do not make explicit assumptions about global equity, environmental justice or intra-
regional income distribution. Global 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. This assessment focuses on their global characteristics.
The majority of the assessed scenarios (about 80%) have become available since the SR1.5, but some
were assessed in that report. Scenarios with and without mitigation were categorised based on their
projected global warming over the 21st century, following the same scheme as in the SR1.5 for warming
up to and including 2°C. {1.5, 3.2, 3.3, Annex III.II.2, Annex III.II.3}
FOOTNOTE 45: In the literature, the terms pathways and scenarios are used interchangeably, with the
former more frequently used in relation to climate goals. For this reason, this SPM uses mostly the term
(emissions and mitigation) pathways. {Annex III.II.1.1}
FOOTNOTE 46: Key assumptions relate to technology development in agriculture and energy systems
and socio-economic development, including demographic and economic projections. 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. Additional scenarios may be developed. The underlying population
assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion in 2100 (5-95th percentile)
starting from 7.6 billion in 2019. The underlying assumptions on global GDP growth (ppp) range from
2.5 to 3.5% per year in the 2019-2050 period and 1.3 to 2.1% per year in the 2050-2100 (5-95th
percentile). Many underlying assumptions are regionally differentiated. {1.5; 3.2; 3.3; Figure 3.9;
Annex III.II.1.4; Annex III.II.3}
Scenario categories are defined by their likelihood of exceeding global warming levels (at peak and in
2100) and referred to in this report as follows [FOOTNOTE 47, 48]:
• Category C1 comprises modelled scenarios that limit warming to 1.5°C in 2100 with a
likelihood of greater than 50%, and reach or exceed warming of 1.5°C during the 21st century
with a likelihood of 67% or less. In this report, these scenarios are referred to as scenarios that
limit warming to 1.5°C (>50%) with no or limited overshoot. Limited overshoot refers to
exceeding 1.5°C global warming by up to about 0.1°C and for up to several decades.
[FOOTNOTE 49]
• Category C2 comprises modelled scenarios that limit warming to 1.5°C in 2100 with a
likelihood of greater than 50%, and exceed warming of 1.5°C during the 21st century with a
likelihood of greater than 67%. In this report, these scenarios are also referred to as scenarios
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that return warming to 1.5°C (>50%) after a high overshoot. High overshoot refers to
temporarily exceeding 1.5°C global warming by 0.1-0.3°C for up to several decades.
• Category C3 comprises modelled scenarios that limit peak warming to 2°C throughout the 21st
century with a likelihood of greater than 67%. In this report, these scenarios are also referred
to as scenarios that limit warming to 2°C (>67%).
• Categories C4-C7 comprise modelled scenarios that limit warming to 2°C, 2.5°C, 3°C, 4°C,
respectively, throughout the 21st century with a likelihood of greater than 50%. In some
scenarios in C4 and many scenarios in C5-C7, warming continues beyond the 21st century.
• Category C8 comprises modelled scenarios that exceed warming of 4°C during the 21st century
with a likelihood of 50% or greater. In these scenarios warming continues to rise beyond the
21st century.
Categories of modelled scenarios are distinct and do not overlap; they do not contain categories
consistent with lower levels of global warming, e.g., the category of C3 scenarios that limit warming to
2°C (>67%) does not include the C1 and C2 scenarios that limit or return warming to 1.5°C (>50%).
Where relevant, scenarios belonging to the group of categories C1-C3 are referred to in this report as
scenarios that limit warming to 2°C (>67%) or lower.
FOOTNOTE 47: The future scenario projections presented here are consistent with the total observed
increase in global surface temperature between 1850-1900 and 1995-2014 as well as to 2011-2020 (with
best estimates of 0.85 and 1.09°C, respectively) assessed in WGI. The largest contributor to historical
human-induced warming is CO2, with historical cumulative CO2 emissions from 1850 to 2019 being
2400 ± 240 (GtCO2). {WGI SPM A.1.2,WGI Table SPM.2, WGI Table 5.1, Section B}
FOOTNOTE 48: In case no explicit likelihood is provided, the reported warming levels are associated
with a likelihood of >50%.
FOOTNOTE 49: Scenarios in this category are found to have simultaneous likelihood to limit peak
global warming to 2°C throughout the 21st century of close to and more than 90%.
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Box SPM.1, Figure 1
Projected global mean warming of the ensemble of modelled scenarios included in the climate categories C1-C8
and IMPs (based on emulators calibrated to the WGI assessment), as well as five illustrative scenarios (SSPx-y)
as considered by AR6 WG I. The left panel shows the p5-p95 range of projected median warming across global
modelled pathways within a category, with the category medians (line). The right panel shows the peak and 2100
emulated temperature outcomes for the categories C1 to C8 and for IMPs, and the five illustrative scenarios (SSPx-
y) as considered by AR6 WG I. The boxes show the p5-p95 range within each scenario category as in panel-a.
The combined p5-p95 range across scenarios and the climate uncertainty for each category C1- C8 is also shown
for 2100 warming (thin vertical lines). {Table SPM.1, Figure 3.11, WGI Figure SPM.8}
Methods to project global warming associated with the scenarios were updated to ensure consistency
with the AR6 WG1 assessment of physical climate science [FOOTNOTE 50]. {3.2, Annex III.II.2.5,
WG I Cross-chapter box 7.1}
FOOTNOTE 50: This involved improved methodologies to use climate emulators (MAGICC7 and
FAIR v1.6), which were evaluated and calibrated to closely match the global warming response to
emissions as assessed in AR6 WGI. It included harmonisation of global GHG emissions in 2015 in
modelled scenarios (51-56 GtCO2-eq; 5th to 95th percentiles) with the corresponding emission value
underlying the CMIP6 projected climate response assessed by WG I (54 GtCO2-eq), based on similar
data sources of historical emissions that are updated over time. The assessment of past GHG emissions
in Chapter 2 of the report is based on a more recent dataset providing emissions of 57 [±6.3] GtCO2-eq
in 2015 (B.1). Differences are well within the assessed uncertainty range, and arise mainly from
differences in estimated CO2-LULUCF emissions, which are subject to large uncertainties, high annual
variability and revisions over time. Projected rates of global emission reduction in mitigation scenarios
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are reported relative to modelled global emissions in 2019 rather than the global emissions reported in
Chapter 2; this ensures internal consistency in assumptions about emission sources and activities, as
well as consistency with temperature projections based on the physical climate science assessment by
WG I. {Annex III.II.2.5}
These updated methods affect the categorisation of some scenarios. On average across scenarios, peak
global warming is projected to be lower by up to about 0.05[±0.1]°C than if the same scenarios were
evaluated using the SR1.5 methodology, and global warming in 2100 is projected to be lower by about
0.1[±0.1]°C. {Annex III.II.2.5.1, Annex III, Figure II.3}
Resulting changes to the emission characteristics of scenario categories described in Table SPM.1
interact with changes in the characteristics of the wider range of emission scenarios published since the
SR1.5. Proportionally more scenarios assessed in AR6 are designed to limit temperature overshoot and
more scenarios limit large-scale net negative CO2 emissions than in SR1.5. As a result, AR6 scenarios
in the lowest temperature category (C1) generally reach net zero GHG emissions later in the 21st
century than scenarios in the same category assessed in SR1.5, and about half do not reach net zero
GHG by 2100. The rate of decline of GHG emissions in the near term by 2030 in category C1 scenarios
is very similar to the assessed rate in SR1.5, but absolute GHG emissions of category C1 scenarios in
AR6 are slightly higher in 2030 than in SR1.5, since the reductions start from a higher emissions level
in 2020. (Table SPM.1) {Annex III 2.5, 3.2, 3.3}
The large number of global emissions scenarios assessed, including 1202 scenarios with projected
global warming outcomes using climate emulators, come from a wide range of modelling approaches.
They include the five illustrative scenarios (Shared Socioeconomic Pathways; SSPs) assessed by WG I
for their climate outcomes but cover a wider and more varied set in terms of assumptions and modelled
outcomes. For this assessment, Illustrative Mitigation Pathways (IMPs) were selected from this larger
set to illustrate a range of different mitigation strategies that would be consistent with different warming
levels. The IMPs illustrate pathways that achieve deep and rapid emissions reductions through different
combinations of mitigation strategies. The IMPs are not intended to be comprehensive and do not
address all possible themes in the underlying report. They differ in terms of their focus, for example,
placing greater emphasis on renewables (IMP-Ren), deployment of carbon dioxide removal that result
in net negative global GHG emissions (IMP-Neg) and efficient resource use as well as shifts in
consumption patterns globally, leading to low demand for resources, while ensuring a high level of
services and satisfying basic needs (IMP-LD) (Figure SPM.5). Other IMPs illustrate the implications
of a less rapid introduction of mitigation measures followed by a subsequent gradual strengthening
(IMP-GS), and how shifting global pathways towards sustainable development, including by reducing
inequality, can lead to mitigation (IMP-SP). The IMPs reach different climate goals as indicated in
Table SPM.1 and Figure Box SPM.1.{1.5, 3.1, 3.2, 3.3, 3.6, Figure 3.7, Figure 3.8, Box 3.4, Annex
III.II.2.4}
C.2 Global net zero CO2 emissions are reached in the early 2050s in modelled pathways that
limit warming to 1.5°C (>50%) with no or limited overshoot, and around the early 2070s in
modelled pathways that limit warming to 2°C (>67%). Many of these pathways continue to net
negative CO2 emissions after the point of net zero. These pathways also include deep reductions
in other GHG emissions. The level of peak warming depends on cumulative CO2 emissions until
the time of net zero CO2 and the change in non-CO2 climate forcers by the time of peaking. Deep
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GHG emissions reductions by 2030 and 2040, particularly reductions of methane emissions, lower
peak warming, reduce the likelihood of overshooting warming limits and lead to less reliance on
net negative CO2 emissions that reverse warming in the latter half of the century. Reaching and
sustaining global net zero GHG emissions results in a gradual decline in warming. (high
confidence) (Table SPM.1) {3.3, 3.5, Box 3.4, Cross-Chapter Box 3 in Chapter 3, AR6 WG I SPM
D1.8}
C.2.1 Modelled global pathways limiting warming to 1.5°C (>50%) with no or limited overshoot are
associated with projected cumulative net CO2 emissions [FOOTNOTE 51] until the time of net zero
CO2 of 510 [330–710] GtCO2. Pathways limiting warming to 2°C (>67%) are associated with 890 [640–
1160] GtCO2 (Table SPM.1) . (high confidence). {3.3, Box 3.4}
FOOTNOTE 51: Cumulative net CO2 emissions from the beginning of the year 2020 until the time of
net zero CO2 in assessed pathways are consistent with the remaining carbon budgets assessed by WG
I, taking account of the ranges in the WG III temperature categories and warming from non-CO2 gases.
{Box 3.4}
C.2.2 Modelled global pathways that limit warming to 1.5°C (>50%) with no or limited overshoot
involve more rapid and deeper near-term GHG emissions reductions through to 2030, and are projected
to have less net negative CO2 emissions and less carbon dioxide removal (CDR) in the longer term, than
pathways that return warming to 1.5°C (>50%) after a high overshoot (C2 category). Modelled
pathways that limit warming to 2°C (>67%) have on average lower net negative CO2 emissions
compared to pathways that limit warming to 1.5°C (>50%) with no or limited overshoot and pathways
that return warming to 1.5°C (>50%) after a high overshoot (C1 and C2 categories respectively).
Modelled pathways that return warming to 1.5°C (>50%) after a high overshoot (C2 category) show
near-term GHG emissions reductions similar to pathways that limit warming to 2°C (>67%) (C3
category). For a given peak global warming level, greater and more rapid near-term GHG emissions
reductions are associated with later net zero CO2 dates. (high confidence) (Table SPM.1) {3.3, Table
3.5, Cross-Chapter Box 3 in Chapter 3, Annex I: Glossary}
C.2.3 Future non-CO2 warming depends on reductions in non-CO2 GHG, aerosol and their precursor,
and ozone precursor emissions. In modelled global low emission pathways, the projected reduction of
cooling and warming aerosol emissions over time leads to net warming in the near- to mid-term. In
these mitigation pathways, the projected reductions of cooling aerosols are mostly due to reduced fossil
fuel combustion that was not equipped with effective air pollution controls. Non-CO2 GHG emissions
at the time of net zero CO2 are projected to be of similar magnitude in modelled pathways that limit
warming to 2°C (>67%) or lower. These non-CO2 GHG emissions are about 8 [5–11] GtCO2-eq per
year, with the largest fraction from CH4 (60% [55–80%]), followed by N2O (30% [20–35%]) and F-
gases (3% [2–20%]). [FOOTNOTE 52] Due to the short lifetime of CH4 in the atmosphere, projected
deep reduction of CH4 emissions up until the time of net zero CO2 in modelled mitigation pathways
effectively reduces peak global warming. (high confidence) {3.3, AR6 WG I SPM D1.7}
FOOTNOTE 52: All numbers here rounded to the closest 5%, except values below 5% (for F-gases).
C.2.4 At the time of global net zero GHG emissions, net negative CO2 emissions counterbalance
metric-weighted non-CO2 GHG emissions. Typical emissions pathways that reach and sustain global
net zero GHG emissions based on the 100 year global warming potential (GWP100) [FOOTNOTE 7]
are projected to result in a gradual decline of global warming. About half of the assessed pathways that
limit warming to 1.5°C (>50%) with no or limited overshoot (C1 category) reach net zero GHG
emissions during the second half of the 21st century. These pathways show greater reduction in global
warming after the peak to 1.2 [1.1-1.4]°C by 2100 than modelled pathways in the same category that
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do not reach net zero GHG emissions before 2100 and that result in warming of 1.4 [1.3–1.5]°C by
2100. In modelled pathways that limit warming to 2°C (>67%) (C3 category), there is no significant
difference in warming by 2100 between those pathways that reach net zero GHGs (around 30%) and
those that do not (high confidence). In pathways that limit warming to 2°C (>67%) or lower and that
do reach net zero GHG, net zero GHG occurs around 10–40 years later than net zero CO2 emissions
(medium confidence). {3.3, Cross-Chapter Box 3 in Chapter 3, Cross-Chapter Box 2 in Chapter 2; AR6
WG I SPM D1.8}
C.3 All global modelled pathways that limit warming to 1.5°C (>50%) with no or limited
overshoot, and those that limit warming to 2°C (>67%) involve rapid and deep and in most cases
immediate GHG emission reductions in all sectors. Modelled mitigation strategies to achieve these
reductions include transitioning from fossil fuels without CCS to very low- or zero-carbon energy
sources, such as renewables or fossil fuels with CCS, demand side measures and improving
efficiency, reducing non-CO2 emissions, and deploying carbon dioxide removal (CDR) methods
to counterbalance residual GHG emissions. Illustrative Mitigation Pathways (IMPs) show
different combinations of sectoral mitigation strategies consistent with a given warming level.
(high confidence) (Figure SPM.5) {3.2, 3.3, 3.4, 6.4, 6.6}
C.3.1 There is a variation in the contributions of different sectors in modelled mitigation pathways,
as illustrated by the Illustrative Mitigation Pathways. However, modelled pathways that limit warming
to 2°C (>67%) or lower share common characteristics, including rapid and deep GHG emission
reductions. Doing less in one sector needs to be compensated by further reductions in other sectors if
warming is to be limited. (high confidence) (Figure SPM.5) {3.2, 3.3, 3.4}
C.3.2 In modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, the
global use of coal, oil and gas in 2050 is projected to decline with median values of about 95%, 60%
and 45% compared to 2019. The interquartile ranges are (80 to 100%), (40 to 75%) and (20 to 60%)
and the p5-p95 ranges are [60 to 100%], [25 to 90%] and [-30 to 85%], respectively. In modelled
pathways that limit warming to 2°C (>67%), these projected declines have a median value and
interquartile range of 85% (65 to 95%), 30% (15 to 50%) and 15% (-10 to 40%) respectively by 2050.
The use of coal, oil and gas without CCS in modelled pathways that limit warming to 1.5°C (>50%)
with no or limited overshoot is projected to be reduced to a greater degree, with median values of about
100%, 60% and 70% in 2050 compared to 2019. The interquartile ranges are (95 to 100%), (45 to 75%)
and (60 to 80%) and the p5-p95 range of about [85 to 100%], [25 to 90%], and [35 to 90%] for coal, oil
and gas respectively. In these global modelled pathways, in 2050 almost all electricity is supplied from
zero or low-carbon sources, such as renewables or fossil fuels with CCS, combined with increased
electrification of energy demand. As indicated by the ranges, choices in one sector can be compensated
for by choices in another while being consistent with assessed warming levels. [FOOTNOTE 53] (high
confidence) {3.4, 3.5, Table 3.6, Figure 3.22, Figure 6.35}
FOOTNOTE 53: Most but not all models include the use of fossil fuels for feedstock with varying
underlying standards.
C.3.3 In modelled pathways that reach global net zero CO2 emissions, at the point they reach net
zero, 5-16 GtCO2 of emissions from some sectors are compensated for by net negative CO2 emissions
in other sectors. In most global modelled pathways that limit warming to 2°C (>67%) or lower, the
AFOLU sector, via reforestation and reduced deforestation, and the energy supply sector reach net zero
CO2 emissions earlier than the buildings, industry and transport sectors. (high confidence) (Figure
SPM.5, panel e and f) {3.4}
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C.3.4 In modelled pathways that reach global net zero GHG emissions, at the point they reach net
zero GHG, around 74% [54 to 90%] of global emissions reductions are achieved by CO2 reductions in
energy supply and demand, 13% [4 to20%] by CO2 mitigation options in the AFOLU sector, and 13%
[10 to18%] through the reduction of non-CO2 emissions from land-use, energy and industry (medium
confidence). (Figure SPM.5f) {3.3, 3.4}
C.3.5 Methods and levels of CDR deployment in global modelled mitigation pathways vary
depending on assumptions about costs, availability and constraints. [FOOTNOTE 54] In modelled
pathways that report CDR and that limit warming to 1.5°C (>50%) with no or limited overshoot, global
cumulative CDR during 2020-2100 from Bioenergy with Carbon Dioxide Capture and Storage
(BECCS) and Direct Air Carbon Dioxide Capture and Storage (DACCS) is 30-780 GtCO2 and 0-310
GtCO2, respectively. In these modelled pathways, the AFOLU sector contributes 20-400 GtCO2 net
negative emissions. Total cumulative net negative CO2 emissions including CDR deployment across all
options represented in these modelled pathways are 20–660 GtCO2. In modelled pathways that limit
warming to 2°C (>67%), global cumulative CDR during 2020–2100 from BECCS and DACCS is 170–
650 and 0–250 GtCO2 respectively, the AFOLU sector contributes 10–250 GtCO2 net negative
emissions, and total cumulative net negative CO2 emissions are around 40 [0–290] GtCO2. (Table
SPM.1) (high confidence) {Table 3.2, 3.3, 3.4}
FOOTNOTE 54: Aggregate levels of CDR deployment are higher than total net negative CO2
emissions given that some of the deployed CDR is used to counterbalance remaining gross emissions.
Total net negative CO2 emissions in modelled pathways might not match the aggregated net negative
CO2 emissions attributed to individual CDR methods. Ranges refer to the 5-95th percentile across
modelled pathways that include the specific CDR method. Cumulative levels of CDR from AFOLU
cannot be quantified precisely given that: a) some pathways assess CDR deployment relative to a
baseline; and b) different models use different reporting methodologies that in some cases combine
gross emissions and removals in AFOLU. Total CDR from AFOLU equals or exceeds the net negative
emissions mentioned.
C.3.6 All mitigation strategies face implementation challenges, including technology risks, scaling,
and costs. Many challenges, such as dependence on CDR, pressure on land and biodiversity (e.g.,
bioenergy) and reliance on technologies with high upfront investments (e.g., nuclear), are significantly
reduced in modelled pathways that assume using resources more efficiently (e.g., IMP-LD) or shift
global development towards sustainability (e.g., IMP-SP). (high confidence) (Figure SPM 5) {3.2, 3.4,
3.7, 3.8, 4.3, 5.1}
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Figure SPM.5: Illustrative Mitigation Emissions Pathways (IMPs) and net zero CO2 and GHG
emissions strategies
Panel a and b show the development of global GHG and CO2 emissions in modelled global pathways (upper sub-
panels) and the associated timing of when GHG and CO2 emissions reach net zero (lower sub-panels). Panels c
and d show the development of global CH4 and N2O emissions, respectively. Coloured ranges denote the 5th to
95th percentile across pathways. The red ranges depict emissions pathways assuming policies that were
implemented by the end of 2020 and pathways assuming implementation of NDCs (announced prior to COP26).
Ranges of modelled pathways that limit warming to 1.5oC (>50%) with no or limited overshoot are shown in light
blue (category C1) and pathways that limit warming to 2oC (>67%) are shown in light purple (category C3). The
grey range comprises all assessed pathways (C1-C8) from the 5th percentile of the lowest warming category (C1)
to the 95th percentile of the highest warming category (C8). The modelled pathway ranges are compared to the
emissions from two pathways illustrative of high emissions (CurPol and ModAct) and five Illustrative Mitigation
Pathways (IMPs): IMP-LD, IMP-Ren, IMP-SP, IMP-Neg and IMP-GS. Emissions are harmonised to the same
2015 base year. The vertical error bars in 2015 show the 5-95th percentile uncertainty range of the non-harmonised
emissions across the pathways, and the uncertainty range, and median value, in emission estimates for 2015 and
2019. The vertical error bars in 2030 (panel a) depict the assessed range of the NDCs,as announced prior to COP26
(see Figure SPM.4, FOOTNOTE 24) .
Panel e shows the sectoral contributions of CO2 and non-CO2 emissions sources and sinks at the time when net
zero CO2 emissions are reached in the IMPs. Positive and negative emissions for different IMPs are compared to
the GHG emissions from the year 2019. Energy supply (neg.) includes BECCS and DACCS. DACCS features in
only two of the five IMPs (IMP-REN, IMP-GS) and contributes <1 % and 64%, respectively, to the net negative
emissions in Energy Supply (neg.).
Panel f shows the contribution of different sectors and sources to the emissions reductions from a 2019 baseline
for reaching net zero GHG emissions. Bars denote the median emissions reductions for all pathways that reach
net zero GHG emissions. The whiskers indicate the p5-p95 range. The contributions of the service sectors
(transport, buildings, industry) are split into direct (demand-side) as well as indirect (supply-side) CO2 emissions
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reductions. Direct emissions represent demand-side emissions due to the fuel use in the respective demand sector.
Indirect emissions represent upstream emissions due to industrial processes and energy conversion, transmission
and distribution. In addition, the contributions from the LULUCF sector and reductions from non-CO2 emissions
sources (green and grey bars) are displayed.
{3.3, 3.4}
C.4 Reducing GHG emissions across the full energy sector requires major transitions,
including a substantial reduction in overall fossil fuel use, the deployment of low-emission energy
sources, switching to alternative energy carriers, and energy efficiency and conservation. The
continued installation of unabated fossil fuel [FOOTNOTE 55] infrastructure will ‘lock-in’ GHG
emissions. (high confidence) {2.7, 6.6, 6.7, 16.4}
C.4.1 Net-zero CO2 energy systems entail: a substantial reduction in overall fossil fuel use, minimal
use of unabated fossil fuels, and use of CCS in the remaining fossil system [FOOTNOTE 55]; electricity
systems that emit no net CO2; widespread electrification of the energy system including end uses;
energy carriers such as sustainable biofuels, low-emissions hydrogen, and derivatives in applications
less amenable to electrification; energy conservation and efficiency; and greater physical, institutional,
and operational integration across the energy system. CDR will be needed to counter-balance residual
emissions in the energy sector. The most appropriate strategies depend on national and regional
circumstances, including enabling conditions and technology availability. (high confidence) {3.4, 6.6,
11.3, 16.4}
FOOTNOTE 55: In this context, ‘unabated fossil fuels’ refers to fossil fuels produced and used without
interventions that substantially reduce the amount of GHG emitted throughout the life-cycle; for
example, capturing 90% or more from power plants, or 50-80% of fugitive methane emissions from
energy supply. {Box 6.5, 11.3}
C.4.2 Unit cost reductions in key technologies, notably wind power, solar power, and storage, have
increased the economic attractiveness of low-emission energy sector transitions through 2030.
Maintaining emission-intensive systems may, in some regions and sectors, be more expensive than
transitioning to low emission systems. Low-emission energy sector transitions will have multiple co-
benefits, including improvements in air quality and health. The long-term economic attractiveness of
deploying energy system mitigation options depends, inter alia, on policy design and implementation,
technology availability and performance, institutional capacity, equity, access to finance, and public
and political support. (high confidence) {Figure SPM3, 3.4, 6.4, 6.6, 6.7, 13.7}
C.4.3 Electricity systems powered predominantly by renewables are becoming increasingly viable.
Electricity systems in some countries and regions are already predominantly powered by renewables. It
will be more challenging to supply the entire energy system with renewable energy. Even though
operational, technological, economic, regulatory, and social challenges remain, a variety of systemic
solutions to accommodate large shares of renewables in the energy system have emerged. A broad
portfolio of options such as, integrating systems, coupling sectors, energy storage, smart grids, demand-
side management, sustainable biofuels, electrolytic hydrogen and derivatives, and others will ultimately
be needed to accommodate large shares of renewables in energy systems. (high confidence) {Box 6.8,
6.4, 6.6}
C.4.4 Limiting global warming to 2⁰C or below will leave a substantial amount of fossil fuels
unburned and could strand considerable fossil fuel infrastructure (high confidence). Depending on its
availability, CCS could allow fossil fuels to be used longer, reducing stranded assets (high confidence).
The combined global discounted value of the unburned fossil fuels and stranded fossil fuel infrastructure
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has been projected to be around 1–4 trillion dollars from 2015 to 2050 to limit global warming to
approximately 2⁰C, and it will be higher if global warming is limited to approximately 1.5⁰C (medium
confidence). In this context, coal assets are projected to be at risk of being stranded before 2030, while
oil and gas assets are projected to be more at risk of being stranded toward mid-century. A low-emission
energy sector transition is projected to reduce international trade in fossil fuels. (high confidence) {6.7,
Figure 6.35}
C.4.5 Global methane emissions from energy supply, primarily fugitive emissions from production
and transport of fossil fuels, accounted for about 18% [13%-23%] of global GHG emissions from
energy supply, 32% [22%-42%] of global methane emissions, and 6% [4%-8%] of global GHG
emissions in 2019 (high confidence). About 50–80% of CH4 emissions from these fossil fuels could be
avoided with currently available technologies at less than USD50 tCO2-eq-1 (medium confidence). {6.3,
6.4.2, Box 6.5, 11.3, 2.2.2, Table 2.1, Figure 2.5; Annex1 Glossary}
C.4.6 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources,
provided geological storage is available. When CO2 is captured directly from the atmosphere (DACCS),
or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO2 capture
and subsurface injection is a mature technology for gas processing and enhanced oil recovery. In
contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and
chemicals production, where it is a critical mitigation option. The technical geological CO2 storage
capacity is estimated to be on the order of 1000 gigatonnes of CO2, which is more than the CO2 storage
requirements through 2100 to limit global warming to 1.5°C, although the regional availability of
geological storage could be a limiting factor. If the geological storage site is appropriately selected and
managed, it is estimated that the CO2 can be permanently isolated from the atmosphere. Implementation
of CCS currently faces technological, economic, institutional, ecological-environmental and socio-
cultural barriers. Currently, global rates of CCS deployment are far below those in modelled pathways
limiting global warming to 1.5°C or 2°C. Enabling conditions such as policy instruments, greater public
support and technological innovation could reduce these barriers. (high confidence) {2.5, 6.3, 6.4, 6.7,
11.3, 11.4, Cross-Chapter Box 8 in Chapter 12, Figure TS.31, SRCCS Chapter 5}
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C.5 Net-zero CO2 emissions from the industrial sector are challenging but possible. Reducing
industry emissions will entail coordinated action throughout value chains to promote all
mitigation options, including demand management, energy and materials efficiency, circular
material flows, as well as abatement technologies and transformational changes in production
processes. Progressing towards net zero GHG emissions from industry will be enabled by the
adoption of new production processes using low and zero GHG electricity, hydrogen, fuels, and
carbon management. (high confidence) {11.2, 11.3, 11.4, Box TS.4}
C.5.1 The use of steel, cement, plastics, and other materials is increasing globally, and in most
regions. There are many sustainable options for demand management, materials efficiency, and circular
material flows that can contribute to reduced emissions, but how these can be applied will vary across
regions and different materials. These options have a potential for being more used in industrial practice
and would need more attention from industrial policy. These options, as well as new production
technologies, are generally not considered in recent global scenarios nor in national economy-wide
scenarios due to relative newness. As a consequence, the mitigation potential in some scenarios is
underestimated compared to bottom-up industry-specific models. (high confidence) {3.4, 5.3, Figure
5.7, 11.2, Box 11.2, 11.3, 11.4, 11.5.2, 11.6}
C.5.2 For almost all basic materials ‒ primary metals [FOOTNOTE 56], 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 not yet established industrial practice. Introducing new
sustainable basic materials production processes could increase production costs but, given the small
fraction of consumer cost based on materials, are expected to translate into minimal cost increases for
final consumers. Hydrogen direct reduction for primary steelmaking is near-commercial in some
regions. Until new chemistries are mastered, deep reduction of cement process emissions will rely on
already commercialised cementitious material substitution and the availability of CCS. Reducing
emissions from the production and use of chemicals would need to rely on a life cycle approach,
including increased plastics recycling, fuel and feedstock switching, and carbon sourced through
biogenic sources, and, depending on availability, CCU, direct air CO2 capture, as well as CCS. Light
industry, mining and manufacturing have the potential to be decarbonised through available abatement
technologies (e.g., material efficiency, circularity), electrification (e.g., electrothermal heating, heat
pumps) and low- or zero- GHG emitting fuels (e.g., hydrogen, ammonia, and bio-based & other
synthetic fuels). (high confidence) {Table 11.4, Box 11.2, 11.3, 11.4}
FOOTNOTE 56: Primary metals refers to virgin metals produced from ore.
C.5.3 Action to reduce industry sector emissions may change the location of GHG intensive industries
and the organisation of value chains. Regions with abundant low GHG energy and feedstocks have the
potential to become exporters of hydrogen-based chemicals and materials processed using low-carbon
electricity and hydrogen. Such reallocation will have global distributional effects on employment and
economic structure. (medium confidence) {Box 11.1}
C.5.4 Emissions intensive and highly traded basic materials industries are exposed to international
competition, and international cooperation and coordination may be particularly important in enabling
change. For sustainable industrial transitions, broad and sequential national and sub-national policy
strategies reflecting regional contexts will be required. These may combine policy packages including:
transparent GHG accounting and standards; demand management; materials and energy efficiency
policies; R&D and niche markets for commercialisation of low emission materials and products;
economic and regulatory instruments to drive market uptake; high quality recycling, low-emissions
energy and other abatement infrastructure (e.g., for CCS); and socially inclusive phase-out plans of
emissions intensive facilities within the context of just transitions. The coverage of mitigation policies
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could be expanded nationally and sub-nationally to include all industrial emission sources, and both
available and emerging mitigation options. (high confidence) {11.6}
C.6 Urban areas can create opportunities to increase resource efficiency and significantly
reduce GHG emissions through the systemic transition of infrastructure and urban form through
low-emission development pathways towards net-zero emissions. Ambitious mitigation efforts for
established, rapidly growing and emerging cities will encompass 1) reducing or changing energy
and material consumption, 2) electrification, and 3) enhancing carbon uptake and storage in the
urban environment. Cities can achieve net-zero emissions, but only if emissions are reduced
within and outside of their administrative boundaries through supply chains, which will have
beneficial cascading effects across other sectors. (very high confidence) {8.2, 8.3, 8.4, 8.5, 8.6,
Figure 8.21, 13.2}
C.6.1 In modelled scenarios, global consumption-based urban CO2 and CH4 emissions [FOOTNOTE
15] are projected to rise from 29 GtCO2-eq in 2020 to 34 GtCO2-eq in 2050 with moderate mitigation
efforts (intermediate GHG emissions, SSP2-4.5), and up to 40 GtCO2-eq in 2050 with low mitigation
efforts (high GHG emissions, SSP 3-7.0). With ambitious and immediate mitigation efforts, including
high levels of electrification and improved energy and material efficiency, global consumption-based
urban CO2 and CH4 emissions could be reduced to 3 GtCO2-eq in 2050 in the modelled scenario with
very low GHG emissions (SSP1-1.9). [FOOTNOTE 57] (medium confidence) {8.3}
FOOTNOTE 15: This estimate is based on consumption-based accounting, including both direct
emissions from within urban areas, and indirect emissions from outside urban areas related to the
production of electricity, goods and services consumed in cities. These estimates include all CO2 and
CH4 emission categories except for aviation and marine bunker fuels, land-use change, forestry and
agriculture. {8.1, Annex I: Glossary}
FOOTNOTE 57: These scenarios have been assessed by WGI to correspond to intermediate, high and
very low GHG emissions.
C.6.2 The potential and sequencing of mitigation strategies to reduce GHG emissions will vary
depending on a city’s land use, spatial form, development level, and state of urbanisation (high
confidence). Strategies for established cities to achieve large GHG emissions savings include efficiently
improving, repurposing or retrofitting the building stock, targeted infilling, and supporting non-
motorised (e.g., walking, bicycling) and public transport. Rapidly growing cities can avoid future
emissions by co-locating jobs and housing to achieve compact urban form, and by leapfrogging or
transitioning to low-emissions technologies. New and emerging cities will have significant
infrastructure development needs to achieve high quality of life, which can be met through energy
efficient infrastructures and services, and people-centred urban design. (high confidence). For cities,
three broad mitigation strategies have been found to be effective when implemented concurrently: i)
reducing or changing energy and material use towards more sustainable production and consumption;
ii) electrification in combination with switching to low-emission energy sources; and iii) enhancing
carbon uptake and storage in the urban environment, for example through bio-based building materials,
permeable surfaces, green roofs, trees, green spaces, rivers, ponds and lakes [FOOTNOTE 58]. (very
high confidence) {5.3, Figure 5.7, Table SM5.2, 8.2, 8.4, 8.6, Figure 8.21, 9.4, 9.6, 10.2}
FOOTNOTE 58: These examples are considered to be a subset of nature-based solutions or ecosystem-
based approaches.
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C.6.3 The implementation of packages of multiple city-scale mitigation strategies can have cascading
effects across sectors and reduce GHG emissions both within and outside a city’s administrative
boundaries. The capacity of cities to develop and implement mitigation strategies varies with the
broader regulatory and institutional settings, as well as enabling conditions, including access to financial
and technological resources, local governance capacity, engagement of civil society, and municipal
budgetary powers. (very high confidence). {Figure 5.7, Table SM5.2, 8.4, 8.5, 8.6, 13.2, 13.3, 13.5,
13.7, Cross-Chapter Box 9}
C.6.4 A growing number of cities are setting climate targets, including net-zero GHG targets. Given
the regional and global reach of urban consumption patterns and supply chains, the full potential for
reducing consumption-based urban emissions to net-zero GHG can be met only when emissions beyond
cities’ administrative boundaries are also addressed. The effectiveness of these strategies depends on
cooperation and coordination with national and sub-national governments, industry, and civil society,
and whether cities have adequate capacity to plan and implement mitigation strategies. Cities can play
a positive role in reducing emissions across supply chains that extend beyond cities’ administrative
boundaries, for example through building codes and the choice of construction materials. (very high
confidence) {8.4, Box 8.4, 8.5, 9.6, 9.9, 13.5, 13.9}
C.7. In modelled global scenarios, existing buildings, if retrofitted, and buildings yet to be
built, are projected to approach net zero GHG emissions in 2050 if policy packages, which
combine ambitious sufficiency, efficiency, and renewable energy measures, are effectively
implemented and barriers to decarbonisation are removed. Low ambitious policies increase the
risk of lock-in buildings in carbon for decades while well-designed and effectively implemented
mitigation interventions, in both new buildings and existing ones if retrofitted, have significant
potential to contribute to achieving SDGs in all regions while adapting buildings to future climate.
(high confidence) {9.1, 9.3, 9.4, 9.5, 9.6, 9.9}
C.7.1 In 2019, global direct and indirect GHG emissions from buildings and emissions from cement
and steel use for building construction and renovation were 12 GtCO2-eq. These emissions include
indirect emissions from offsite generation of electricity and heat, direct emissions produced onsite and
emissions from cement and steel used for building construction and renovation. In 2019, global direct
and indirect emissions from non-residential buildings increased by about 55% and those from
residential buildings increased by about 50% compared to 1990. The latter increase, according to the
decomposition analysis, was mainly driven by the increase of the floor area per capita, population
growth and the increased use of emission-intensive electricity and heat while efficiency improvements
have partly decreased emissions. There are great differences in the contribution of each of these drivers
to regional emissions. (high confidence) {9.3}
C.7.2 Integrated design approaches to the construction and retrofit of buildings have led to increasing
examples of zero energy or zero carbon buildings in several regions. However, the low renovation rates
and low ambition of retrofitted buildings have hindered the decrease of emissions. Mitigation
interventions at the design stage include buildings typology, form, and multi-functionality to allow for
adjusting the size of buildings to the evolving needs of their users and repurposing unused existing
buildings to avoid using GHG-intensive materials and additional land. Mitigation interventions include:
at the construction phase, low-emission construction materials, highly efficient building envelope and
the integration of renewable energy solutions[FOOTNOTE 59]; at the use phase, highly efficient
appliances/ equipment, the optimisation of the use of buildings and the supply with low-emission energy
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sources; and at the disposal phase, recycling and re-using construction materials. (high confidence) {9.4,
9.5, 9.6, 9.7}
FOOTNOTE 59: Integration of renewable energy solutions refers to the integration of solutions such
as solar photovoltaics, small wind turbines, solar thermal collectors, and biomass boilers.
C.7.3 By 2050, bottom-up studies show that up to 61% (8.2 GtCO2) of global building emissions
could be mitigated. Sufficiency policies [FOOTNOTE 60] that avoid the demand for energy and
materials contribute 10% to this potential, energy efficiency policies contribute 42%, and renewable
energy policies 9%. The largest share of the mitigation potential of new buildings is available in
developing countries while in developed countries the highest mitigation potential is within the retrofit
of existing buildings. The 2020-2030 decade is critical for accelerating the learning of know-how,
building the technical and institutional capacity, setting the appropriate governance structures, ensuring
the flow of finance, and in developing the skills needed to fully capture the mitigation potential of
buildings. (high confidence) {9.3, 9.4, 9.5, 9.6, 9.7, 9.9}
FOOTNOTE 60: Sufficiency policies are a set of measures and daily practices that avoid demand for
energy , materials, land and water while delivering human wellbeing for all within planetary
boundaries.
C.8 Demand-side options and low-GHG emissions technologies can reduce transport sector
emissions in developed countries and limit emissions growth in developing countries (high
confidence). Demand-focused interventions can reduce demand for all transport services and
support the shift to more energy efficient transport modes (medium confidence). Electric vehicles
powered by low emissions electricity offer the largest decarbonisation potential for land-based
transport, on a life cycle basis (high confidence). Sustainable biofuels can offer additional
mitigation benefits in land-based transport in the short and medium term (medium confidence).
Sustainable biofuels, low emissions hydrogen, and derivatives (including synthetic fuels) can
support mitigation of CO2 emissions from shipping, aviation, and heavy-duty land transport but
require production process improvements and cost reductions (medium confidence). Many
mitigation strategies in the transport sector would have various co-benefits, including air quality
improvements, health benefits, equitable access to transportation services, reduced congestion,
and reduced material demand (high confidence). {10.2, 10.4, 10.5, 10.6, 10.7}
C.8.1 In scenarios that limit warming to 1.5°C (>50%) with no or limited overshoot, global transport-
related CO2 emissions fall by 59% [42–68% interquartile range] by 2050 relative to modelled 2020
emissions, but with regionally differentiated trends (high confidence). In global modelled scenarios that
limit warming to 2°C (>67%), transport related CO2 emissions are projected to decrease by 29% [14-
44% interquartile range] by 2050 compared to modelled 2020 emissions. In both categories of scenarios,
the transport sector likely does not reach zero CO2 emissions by 2100 so negative emissions are likely
needed to counterbalance residual CO2 emissions from the sector (high confidence). {3.4, 10.7}
C.8.2 Changes in urban form (e.g., density, land use mix, connectivity, and accessibility) in
combination with programmes that encourage changes in consumer behaviour (e.g., transport pricing)
could reduce transport related greenhouse gas emissions in developed countries and slow growth in
emissions in developing countries (high confidence). Investments in public inter- and intra-city
transport and active transport infrastructure (e.g., bike and pedestrian pathways) can further support the
shift to less GHG-intensive transport modes (high confidence). Combinations of systemic changes
including, teleworking, digitalisation, dematerialisation, supply chain management, and smart and
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shared mobility may reduce demand for passenger and freight services across land, air, and sea (high
confidence). Some of these changes could lead to induced demand for transport and energy services,
which may decrease their GHG emissions reduction potential (medium confidence). {5.3, 10.2, 10.8}
C.8.3 Electric vehicles powered by low-GHG emissions electricity have large potential to reduce
land-based transport GHG emissions, on a life cycle basis (high confidence). Costs of electrified
vehicles, including automobiles, two and three wheelers, and buses are decreasing and their adoption is
accelerating, but they require continued investments in supporting infrastructure to increase scale of
deployment (high confidence). Advances in battery technologies could facilitate the electrification of
heavy-duty trucks and complement conventional electric rail systems (medium confidence). There are
growing concerns about critical minerals needed for batteries. Material and supply diversification
strategies, energy and material efficiency improvements, and circular material flows can reduce the
environmental footprint and material supply risks for battery production (medium confidence). Sourced
sustainably and with low-GHG emissions feedstocks, bio-based fuels, blended or unblended with fossil
fuels, can provide mitigation benefits, particularly in the short- and medium-term (medium confidence).
Low-GHG emissions hydrogen and hydrogen derivatives, including synthetic fuels, can offer mitigation
potential in some contexts and land-based transport segments (medium confidence). {3.4, 6.3, 10.3,
10.4, 10.7, 10.8, Box 10.6}
C.8.4 While efficiency improvements (e.g., optimised aircraft and vessel designs, mass reduction,
and propulsion system improvements) can provide some mitigation potential, additional CO2 emissions
mitigation technologies for aviation and shipping will be required (high confidence). For aviation, such
technologies include high energy density biofuels (high confidence), and low-emission hydrogen and
synthetic fuels (medium confidence). Alternative fuels for shipping include low-emission hydrogen,
ammonia, biofuels, and other synthetic fuels (medium confidence). Electrification could play a niche
role for aviation and shipping for short trips (medium confidence) and can reduce emissions from port
and airport operations (high confidence). Improvements to national and international governance
structures would further enable the decarbonisation of shipping and aviation (medium confidence). Such
improvements could include, for example, the implementation of stricter efficiency and carbon intensity
standards for the sectors (medium confidence). {10.3. 10.5, 10.6, 10.7, 10.8, Box 10.5}
C.8.5 Substantial potential for GHG reductions, both direct and indirect, for the transport sector
largely depends on power sector decarbonisation, and low emissions feedstocks and production chains
(high confidence). Integrated transport and energy infrastructure planning and operations can enable
sectoral synergies and reduce the environmental, social, and economic impacts of decarbonising the
transport and energy sectors (high confidence). Technology transfer and financing can support
developing countries leapfrogging or transitioning to low emissions transport systems thereby providing
multiple co-benefits (high confidence). {10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8}
C.9 AFOLU mitigation options, when sustainably implemented, can deliver large-scale GHG
emission reductions and enhanced removals, but cannot fully compensate for delayed action in
other sectors. In addition, sustainably sourced agricultural and forest products can be used
instead of more GHG intensive products in other sectors. Barriers to implementation and trade-
offs may result from the impacts of climate change, competing demands on land, conflicts with
food security and livelihoods, the complexity of land ownership and management systems, and
cultural aspects. There are many country-specific opportunities to provide co-benefits (such as
biodiversity conservation, ecosystem services, and livelihoods) and avoid risks (for example,
through adaptation to climate change). (high confidence) {7.4, 7.6, 7.7, 12.5, 12.6}
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C.9.1 The projected economic mitigation potential of AFOLU options between 2020 and 2050, at
costs below USD100 tCO2-eq-1, is 8-14 GtCO2-eq yr-1 [FOOTNOTE 61] (high confidence). 30-50% of
this potential is available at less than USD20/tCO2-eq and could be upscaled in the near term across
most regions (high confidence). The largest share of this economic potential [4.2-7.4 GtCO2-eq yr-1]
comes from the conservation, improved management, and restoration of forests and other ecosystems
(coastal wetlands, peatlands, savannas and grasslands), with reduced deforestation in tropical regions
having the highest total mitigation. Improved and sustainable crop and livestock management, and
carbon sequestration in agriculture, the latter includes soil carbon management in croplands and
grasslands, agroforestry and biochar, can contribute 1.8-4.1 GtCO2-eq yr-1 reduction. Demand-side and
material substitution measures, such as shifting to balanced, sustainable healthy diets [FOOTNOTE
62], reducing food loss and waste, and using bio-materials, can contribute 2.1 [1.1-3.6]GtCO2-eq yr-1
reduction. In addition, demand-side measures together with the sustainable intensification of agriculture
can reduce ecosystem conversion and CH4 and N2O emissions, and free-up land for reforestation and
restoration, and the producing of renewable energy. The improved and expanded use of wood products
sourced from sustainably managed forests also has potential through the allocation of harvested wood
to longer-lived products, increasing recycling or material substitution. AFOLU mitigation measures
cannot compensate for delayed emission reductions in other sectors. Persistent and region-specific
barriers continue to hamper the economic and political feasibility of deploying AFOLU mitigation
options. Assisting countries to overcome barriers will help to achieve significant mitigation (medium
confidence). (Figure SPM.6) {7.1, 7.4, 7.5, 7.6}
FOOTNOTE 61: The global top-down estimates and sectoral bottom-up estimates described here do
not include the substitution of emissions from fossil fuels and GHG-intensive materials. 8-14 GtCO2-
eq yr-1 represents the mean of the AFOLU economic mitigation potential estimates from top-down
estimates (lower bound of range) and global sectoral bottom-up estimates (upper bound of range). The
full range from top-down estimates is 4.1-17.3 GtCO2-eq yr-1 using a “no policy” baseline. The full
range from global sectoral studies is 6.7-23.4 GtCO2-eq yr-1 using a variety of baselines. (high
confidence)
FOOTNOTE 62: ‘Sustainable healthy diets’ promote all dimensions of individuals’ health and
wellbeing; have low environmental pressure and impact; are accessible, affordable, safe and equitable;
and are culturally acceptable, as described in FAO and WHO. The related concept of balanced diets
refers to diets that feature plant-based foods, such as those based on coarse grains, legumes, fruits and
vegetables, nuts and seeds, and animal-sourced food produced in resilient, sustainable and low-GHG
emission systems, as described in SRCCL.
C.9.2 AFOLU carbon sequestration and GHG emission reduction options have both co-benefits and
risks in terms of biodiversity and ecosystem conservation, food and water security, wood supply,
livelihoods and land tenure and land-use rights of Indigenous Peoples, local communities and small
land owners. Many options have co-benefits but those that compete for land and land-based resources
can pose risks. The scale of benefit or risk largely depends on the type of activity undertaken,
deployment strategy (e.g., scale, method), and context (e.g., soil, biome, climate, food system, land
ownership) that vary geographically and over time. Risks can be avoided when AFOLU mitigation is
pursued in response to the needs and perspectives of multiple stakeholders to achieve outcomes that
maximize co-benefits while limiting trade-offs. (high confidence) {7.4, 7.6, 12.3}
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C.9.3 Realising the AFOLU potential entails overcoming institutional, economic and policy
constraints and managing potential trade-offs (high confidence). Land-use decisions are often spread
across a wide range of landowners; demand-side measures depend on billions of consumers in diverse
contexts. Barriers to the implementation of AFOLU mitigation include insufficient institutional and
financial support, uncertainty over long-term additionality and trade-offs, weak governance, insecure
land ownership, the low incomes and the lack of access to alternative sources of income, and the risk
of reversal. Limited access to technology, data, and know-how is a barrier to implementation. Research
and development are key for all measures. For example, measures for the mitigation of agricultural CH4
and N2O emissions with emerging technologies show promising results. However the mitigation of
agricultural CH4 and N2O emissions is still constrained by cost, the diversity and complexity of
agricultural systems, and by increasing demands to raise agricultural yields, and increasing demand for
livestock products. (high confidence) {7.4, 7.6}
C.9.4 Net costs of delivering 5-6 Gt CO2 yr-1 of forest related carbon sequestration and emission
reduction as assessed with sectoral models are estimated to reach to ~USD400 billion yr-1 by 2050. The
costs of other AFOLU mitigation measures are highly context specific. Financing needs in AFOLU,
and in particular in forestry, include both the direct effects of any changes in activities as well as the
opportunity costs associated with land use change. Enhanced monitoring, reporting and verification
capacity and the rule of law are crucial for land-based mitigation, in combination with policies also
recognising interactions with wider ecosystem services, could enable engagement by a wider array of
actors, including private businesses, NGOs, and Indigenous Peoples and local communities. (medium
confidence) {7.6, 7.7}
C.9.5 Context specific policies and measures have been effective in demonstrating the delivery of
AFOLU carbon sequestration and GHG emission reduction options but the above-mentioned
constraints hinder large scale implementation (medium confidence). Deploying land-based mitigation
can draw on lessons from experience with regulations, policies, economic incentives, payments (e.g.,
for biofuels, control of nutrient pollution, water regulations, conservation and forest carbon, ecosystem
services, and rural livelihoods), and from diverse forms of knowledge such as Indigenous knowledge,
local knowledge and scientific knowledge. Indigenous Peoples, private forest owners, local farmers and
communities manage a significant share of global forests and agricultural land and play a central role
in land-based mitigation options. Scaling successful policies and measures relies on governance that
emphasises integrated land use planning and management framed by SDGs, with support for
implementation. (high confidence) {7.4, Box 7.2, 7.6}
C.10 Demand-side mitigation encompasses changes in infrastructure use, end-use technology
adoption, and socio-cultural and behavioural change. Demand-side measures and new ways of
end-use service provision can reduce global GHG emissions in end use sectors by 40-70% by 2050
compared to baseline scenarios, while some regions and socioeconomic groups require additional
energy and resources. Demand side mitigation response options are consistent with improving
basic wellbeing for all. (high confidence) (Figure SPM.6) {5.3, 5.4, Figure 5.6, Figure 5.14, 8.2, 9.4,
10.2, 11.3, 11.4, 12.4, Figure TS.22}
C.10.1 Infrastructure design and access, and technology access and adoption, including information
and communication technologies, influence patterns of demand and ways of providing services, such
as mobility, shelter, water, sanitation, and nutrition. Illustrative global low demand scenarios,
accounting for regional differences, indicate that more efficient end-use energy conversion can improve
services while reducing the need for upstream energy by 45% by 2050 compared to 2020. Demand-side
mitigation potential differs between and within regions, and some regions and populations require
additional energy, capacity, and resources for human wellbeing. The lowest population quartile by
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income worldwide faces shortfalls in shelter, mobility, and nutrition. (high confidence) {5.2, 5.3, 5.4,
5.5, Figure 5.6, Figure 5.10, Figure TS.20, Figure TS.22, Table 5.2}
C.10.2 By 2050, comprehensive demand-side strategies across all sectors could reduce CO2 and non-
CO2 GHG emissions globally by 40–70% compared to the 2050 emissions projection of two scenarios
consistent with policies announced by national governments until 2020. With policy support, socio-
cultural options, and behavioural change can reduce global GHG emissions of end-use sectors by at
least 5% rapidly, with most of the potential in developed countries, and more until 2050, if combined
with improved infrastructure design and access. Individuals with high socio-economic status contribute
disproportionately to emissions and have the highest potential for emissions reductions, e.g., as citizens,
investors, consumers, role models, and professionals. (high confidence) (Figure SPM.6){5.2, 5.3, 5.4,
5.5, 5.6, Table SM5.2, 8.4, 9.9, 13.2, 13.5, 13.8, Figure TS.20}
C.10.3 A range of 5-30% of global annual GHG emissions from end-use sectors are avoidable by
2050, compared to 2050 emissions projection of two scenarios consistent with policies announced by
national governments until 2020, through changes in the built environment, new and repurposed
infrastructures and service provision through compact cities, co-location of jobs and housing, more
efficient use of floor space and energy in buildings, and reallocation of street space for active mobility
(high confidence). (Figure SPM.6) {5.3.1, 5.3.3, 5.4, Figure 5.7, Figure 5.13, Table 5.1, Table 5.5, Table
SM5.2, 8.4, 9.5, 10.2, 11.3, 11.4, Table 11.6, Box TS.12}
C.10.4 Choice architecture [FOOTNOTE 63] can help end-users adopt, as relevant to consumers,
culture and country contexts, low GHG intensive options such as balanced, sustainable healthy
diets[FOOTNOTE 62] acknowledging nutritional needs; food waste reduction; adaptive heating and
cooling choices for thermal comfort; integrated building renewable energy; and electric light-duty
vehicles, and shifts to walking, cycling, shared pooled and public transit; sustainable consumption by
intensive use of longer-lived repairable products (high confidence). Addressing inequality and many
forms of status consumption [FOOTNOTE 64] and focusing on wellbeing supports climate change
mitigation efforts (high confidence). (Figure SPM.6) {2.4.3, 2.6.2, 4.2.5, 5.1, 5.2, 5.3, 5.4, Figure 5.4,
Figure 5.10, Table 5.2, Table SM5.2, 7.4.5, 8.2, 8.4, 9.4, 10.2, 12.4, Figure TS.20}
FOOTNOTE 63: Choice architecture describes the presentation of choices to consumers, and the
impact that presentation has on consumer decision-making.
FOOTNOTE 64: Status consumption refers to the consumption of goods and services which publicly
demonstrates social prestige.
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Figure SPM.6 Indicative potential of demand-side mitigation options by 2050
Figure SPM.6 covers the indicative potential of demand-side options for the year 2050. Figure SPM.7 covers cost
and potentials for the year 2030. Demand-side mitigation response options are categorised into three broad
domains: ‘socio-cultural factors’, associated with individual choices, behaviour; and lifestyle changes, social
norms and culture; ‘infrastructure use’, related to the design and use of supporting hard and soft infrastructure that
enables changes in individual choices and behaviour; and ‘end-use technology adoption’, refers to the uptake of
technologies by end-users. Demand side mitigation is a central element of the IMP-LD and IMP-SP scenarios
(Figure SPM.5).
Panel (a) (Nutrition) demand-side potentials in 2050 assessment is based on bottom-up studies and estimated
following the 2050 baseline for the food sector presented in peer-reviewed literature (more information in
Supplementary Material 5.II, and 7.4.5). Panel (b) (Manufactured products, mobility, shelter) assessment of
potentials for total emissions in 2050 are estimated based on approximately 500 bottom up studies representing
all global regions (detailed list is in Table SM5.2). Baseline is provided by the sectoral mean GHG emissions in
2050 of the two scenarios consistent with policies announced by national governments until 2020. The heights of
the coloured columns represent the potentials represented by the median value. These are based on a range of
values available in the case studies from literature shown in Chapter 5 Supplementary Material II. The range is
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shown by the dots connected by dotted lines representing the highest and the lowest potentials reported in the
literature.
Panel (a) shows the demand side potential of socio-cultural factors and infrastructure use. The median value of
direct emissions (mostly non-CO2) reduction through socio-cultural factors is 1.9 GtCO2-eq without considering
land-use change through reforestation of freed up land. If changes in land use pattern enabled by this change in
food demand are considered, the indicative potential could reach 7 GtCO2-eq. Panel (b) illustrates mitigation
potential in industry, land transport and buildings end-use sectors through demand-side options. Key options are
presented in the summary table below the figure and the details are in Table SM5.2.
Panel (c) visualizes how sectoral demand-side mitigation options (presented in Panel (b)) change demand on the
electricity distribution system. Electricity accounts for an increasing proportion of final energy demand in 2050
(additional electricity bar) in line with multiple bottom-up studies (detailed list is in Table SM5.3), and Chapters
6 (6.6). These studies are used to compute the impact of end-use electrification which increases overall electricity
demand. Some of the projected increase in electricity demand can be avoided through demand-side mitigation
options in the domains of socio-cultural factors and infrastructure use in end-use electricity use in buildings,
industry, and land transport found in literature based on bottom-up assessments. Dark grey columns show the
emissions that cannot be avoided through demand-side mitigation options.
{5.3, Figure 5.7, Supplementary Material 5.II}
C.11 The deployment of CDR to counterbalance hard-to-abate residual emissions is
unavoidable if net zero CO2 or GHG emissions are to be achieved. The scale and timing of
deployment will depend on the trajectories of gross emission reductions in different sectors.
Upscaling the deployment of CDR depends on developing effective approaches to address
feasibility and sustainability constraints especially at large scales. (high confidence) {3.4, 7.4, 12.3,
Cross-Chapter Box 8 in Chapter 12}
C.11.1 CDR refers to anthropogenic activities that remove CO2 from the atmosphere and store it
durably in geological, terrestrial, or ocean reservoirs, or in products. CDR methods vary in terms of
their maturity, removal process, timescale of carbon storage, storage medium, mitigation potential, cost,
co-benefits, impacts and risks, and governance requirements (high confidence). Specifically, maturity
ranges from lower maturity (e.g., ocean alkalinisation) to higher maturity (e.g., reforestation); removal
and storage potential ranges from lower potential (<1 Gt CO2 yr-1, e.g., blue carbon management) to
higher potential (>3 Gt CO2 yr-1, e.g., agroforestry); costs range from lower cost (e.g., 45-100 USD/tCO2
for soil carbon sequestration) to higher cost (e.g., 100-300 USD/tCO2 for DACCS) (medium
confidence). Estimated storage timescales vary from decades to centuries for methods that store carbon
in vegetation and through soil carbon management, to ten thousand years or more for methods that
store carbon in geological formations (high confidence). The processes by which CO2 is removed from
the atmosphere are categorised as biological, geochemical or chemical. Afforestation, reforestation,
improved forest management, agroforestry and soil carbon sequestration are currently the only widely
practiced CDR methods (high confidence). {7.4, 7.6, 12.3, Table 12.6, Table TS.7, Cross-Chapter Box
8 in Chapter 12, WG I 5.6}
C.11.2 The impacts, risks and co-benefits of CDR deployment for ecosystems, biodiversity and people
will be highly variable depending on the method, site-specific context, implementation and scale (high
confidence). Reforestation, improved forest management, soil carbon sequestration, peatland
restoration and blue carbon management are examples of methods that can enhance biodiversity and
ecosystem functions, employment and local livelihoods, depending on context (high confidence). In
contrast, afforestation or production of biomass crops for BECCS or biochar, when poorly implemented,
can have adverse socio-economic and environmental impacts, including on biodiversity, food and water
security, local livelihoods and on the rights of Indigenous Peoples, especially if implemented at large
scales and where land tenure is insecure (high confidence). Ocean fertilisation, if implemented, could
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lead to nutrient redistribution, restructuring of ecosystems, enhanced oxygen consumption and
acidification in deeper waters (medium confidence). {7.4, 7.6, 12.3, 12.5}
C.11.3 The removal and storage of CO2 through vegetation and soil management can be reversed by
human or natural disturbances; it is also prone to climate change impacts. In comparison, CO2 stored in
geological and ocean reservoirs (via BECCS, DACCS, ocean alkalinisation) and as carbon in biochar
is less prone to reversal. (high confidence) {6.4, 7.4, 12.3}
C11.4 In addition to deep, rapid, and sustained emission reductions CDR can fulfil three different
complementary roles globally or at country level: lowering net CO2 or net GHG emissions in the near-
term; counterbalancing ‘hard-to-abate’ residual emissions (e.g., emissions from agriculture, aviation,
shipping, industrial processes) in order to help reach net zero CO2 or net zero GHG emissions in the
mid-term; achieving net negative CO2 or GHG emissions in the long-term if deployed at levels
exceeding annual residual emissions (high confidence) {3.3, 7.4, 11.3, 12.3, Cross-Chapter Box 8 in
Chapter 12}
C.11.5 Rapid emission reductions in all sectors interact with future scale of deployment of CDR
methods, and their associated risks, impacts and co-benefits. Upscaling the deployment of CDR
methods depends on developing effective approaches to address sustainability and feasibility
constraints, potential impacts, co-benefits and risks. Enablers of CDR include accelerated research,
development and demonstration, improved tools for risk assessment and management, targeted
incentives and development of agreed methods for measurement, reporting and verification of carbon
flows. (high confidence) {3.4, 7.6, 12.3}
C.12 Mitigation options costing USD100 tCO2-eq-1 or less could reduce global GHG emissions
by at least half the 2019 level by 2030 (high confidence). Global GDP continues to grow in
modelled pathways [FOOTNOTE 65] but, without accounting for the economic benefits of
mitigation action from avoided damages from climate change nor from reduced adaptation costs,
it is a few percent lower in 2050 compared to pathways without mitigation beyond current
policies. The global economic benefit of limiting warming to 2°C is reported to exceed the cost of
mitigation in most of the assessed literature. (medium confidence) (Figure SPM.7) {3.6, 3.8, Cross-
Working Group Box 1 in Chapter 3, 12.2, Box TS.7}
FOOTNOTE 65: In modelled pathways that limit warming to 2°C (>67%) or lower.
C.12.1 Based on a detailed sectoral assessment of mitigation options, it is estimated that mitigation
options costing USD100 tCO2-eq-1 or less could reduce global GHG emissions by at least half of the
2019 level by 2030 (options costing less than USD20 tCO2-eq-1 are estimated to make up more than half
of this potential) [FOOTNOTE 66]. For a smaller part of the potential, deployment leads to net cost
savings. Large contributions with costs less than USD20 tCO2-eq-1 come from solar and wind energy,
energy efficiency improvements, reduced conversion of natural ecosystems, and CH4 emissions
reductions (coal mining, oil and gas, waste). The mitigation potentials and mitigation costs of individual
technologies in a specific context or region may differ greatly from the provided estimates. The
assessment of the underlying literature suggests that the relative contribution of the various options
could change beyond 2030. (medium confidence) (Figure SPM.7) {12.2}
FOOTNOTE 66. The methodology underlying the assessment is described in the caption to Figure
SPM.7.
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C.12.2 The aggregate effects of climate change mitigation on global GDP are small compared to global
projected GDP growth in assessed modelled global scenarios that quantify the macroeconomic
implications of climate change mitigation, but that do not account for damages from climate change nor
adaptation costs (high confidence). For example, compared to pathways that assume the continuation
of policies implemented by the end of 2020, assessed global GDP reached in 2050 is reduced by 1.3–
2.7% in modelled pathways assuming coordinated global action starting between now and 2025 at the
latest to limit warming to 2°C (>67%). The corresponding average reduction in annual global GDP
growth over 2020-2050 is 0.04–0.09 percentage points. In assessed modelled pathways, regardless of
the level of mitigation action, global GDP is projected to at least double (increase by at least 100%)
over 2020-2050. For modelled global pathways in other temperature categories, the reductions in global
GDP in 2050 compared to pathways that assume the continuation of policies implemented by the end
of 2020 are as follows: 2.6 - 4.2% (C1), 1.6 - 2.8% (C2), 0.8 - 2.1% (C4), 0.5 - 1.2% (C5). The
corresponding reductions in average annual global GDP growth over 2020-2050, in percentage points,
are as follows: 0.09 - 0.14 (C1), 0.05 - 0.09 (C2), 0.03 - 0.07 (C4), 0.02 - 0.04 (C5) [FOOTNOTE 67].
There are large variations in the modelled effects of mitigation on GDP across regions, depending
notably on economic structure, regional emissions reductions, policy design and level of international
cooperation [FOOTNOTE 68] (high confidence). Country level studies also show large variations in
the effect of mitigation on GDP depending notably on the level of mitigation and on the way it is
achieved (high confidence). Macroeconomic implications of mitigation co-benefits and trade-offs are
not quantified comprehensively across the above scenarios and depend strongly on mitigation strategies
(high confidence). {3.6, 4.2, Box TS.7, Annex III I.2, I.9, I.10 and II.3}
FOOTNOTE 67: These estimates are based on 311 pathways that report effects of mitigation on GDP
and that could be classified in temperature categories, but that do not account for damages from climate
change nor adaptation costs and that mostly do not reflect the economic impacts of mitigation co-
benefits and trade-offs. The ranges given are interquartile ranges. The macroeconomic implications
quantified vary largely depending on technology assumptions, climate/emissions target formulation,
model structure and assumptions, and the extent to which pre-existing inefficiencies are considered.
Models that produced the pathways classified in temperature categories do not represent the full
diversity of existing modelling paradigms, and there are in the literature models that find higher
mitigation costs, or conversely lower mitigation costs and even gains. {1.7, 3.2, 3.6, Annex III I.2 I.9
I.10 and II.3}
FOOTNOTE 68: In modelled cost-effective pathways with a globally uniform carbon price, without
international financial transfers or complementary policies, carbon intensive and energy exporting
countries are projected to bear relatively higher mitigation costs because of a deeper transformation of
their economies and changes in international energy markets. {3.6}
C.12.3 Estimates of aggregate economic benefits from avoiding damages from climate change, and
from reduced adaptation costs, increase with the stringency of mitigation (high confidence). Models
that incorporate the economic damages from climate change find that the global cost of limiting
warming to 2°C over the 21st century is lower than the global economic benefits of reducing warming,
unless: i) climate damages are towards the low end of the range; or, ii) future damages are discounted
at high rates (medium confidence) [FOOTNOTE 69]. Modelled pathways with a peak in global
emissions between now and 2025 at the latest, compared to modelled pathways with a later peak in
global emissions, entail more rapid near-term transitions and higher up-front investments, but bring
long-term gains for the economy, as well as earlier benefits of avoided climate change impacts (high
confidence). The precise magnitude of these gains and benefits is difficult to quantify. {1.7, 3.6, Cross-
Working Group Box 1 in Chapter 3 Box TS.7, WGII SPM B.4}
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FOOTNOTE 69: The evidence is too limited to make a similar robust conclusion for limiting warming
to 1.5°C.
Figure SPM.7: Overview of mitigation options and their estimated ranges of costs and potentials in 2030.
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Costs shown are net lifetime costs of avoided greenhouse gas emissions. Costs are calculated relative to a reference
technology. The assessments per sector were carried out using a common methodology, including definition of
potentials, target year, reference scenarios, and cost definitions. The mitigation potential (shown in the horizontal
axis) is the quantity of net greenhouse gas emission reductions that can be achieved by a given mitigation option
relative to a specified emission baseline. Net greenhouse gas emission reductions are the sum of reduced emissions
and/or enhanced sinks. The baseline used consists of current policy (~ 2019) reference scenarios from the AR6
scenarios database (25/75 percentile values). The assessment relies on approximately 175 underlying sources, that
together give a fair representation of emission reduction potentials across all regions. The mitigation potentials
are assessed independently for each option and are not necessarily additive. {12.2.1, 12.2.2}
The length of the solid bars represents the mitigation potential of an option. The error bars display the full ranges
of the estimates for the total mitigation potentials. Sources of uncertainty for the cost estimates include
assumptions on the rate of technological advancement, regional differences, and economies of scale, among
others. Those uncertainties are not displayed in the figure.
Potentials are broken down into cost categories, indicated by different colours (see legend). Only discounted
lifetime monetary costs are considered. Where a gradual colour transition is shown, the breakdown of the potential
into cost categories is not well known or depends heavily on factors such as geographical location, resource
availability, and regional circumstances, and the colours indicate the range of estimates. Costs were taken directly
from the underlying studies (mostly in the period 2015-2020) or recent datasets. No correction for inflation was
applied, given the wide cost ranges used. The cost of the reference technologies were also taken from the
underlying studies and recent datasets. Cost reductions through technological learning are taken into account
(FOOTNOTE 70).
When interpreting this figure, the following should be taken into account:
− The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) being
displaced, the rate of new technology adoption, and several other factors.
− Cost and mitigation potential estimates were extrapolated from available sectoral studies. Actual costs
and potentials would vary by place, context and time.
− Beyond 2030, the relative importance of the assessed mitigation options is expected to change, in
particular while pursuing long-term mitigation goals, recognising also that the emphasis for particular
options will vary across regions (for specific mitigation options see sections C4.1, C5.2, C7.3, C8.3 and
C9.1).
− Different options have different feasibilities beyond the cost aspects, which are not reflected in the figure
(cf. section E.1).
− The potentials in the cost range 100 to 200 USD tCO2-eq-1 may be underestimated for some options.
− Costs for accommodating the integration of variable renewable energy sources in electricity systems are
expected to be modest until 2030, and are not included because of complexities in attributing such costs
to individual technology options.
− Cost range categories are ordered from low to high. This order does not imply any sequence of
implementation.
− Externalities are not taken into account.
{12.2, Table 12.3, 6.4, Table 7.3, Supplementary Material Table 9.2, Supplementary Material Table 9.3, 10.6,
11.4, Fig 11.13, Supplementary Material 12.A.2.3}
FOOTNOTE 70: For nuclear energy, modelled costs for long-term storage of radio-active waste are included.
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D. Linkages between mitigation, adaptation, and sustainable
development
D.1 Accelerated and equitable climate action in mitigating, and adapting to, climate change
impacts is critical to sustainable development. Climate change actions can also result in some
trade-offs. The trade-offs of individual options could be managed through policy design. The
Sustainable Development Goals (SDGs) adopted under the UN 2030 Agenda for Sustainable
Development can be used as a basis for evaluating climate action in the context of sustainable
development. (high confidence) (Figure SPM.8) {1.6, 3.7, 17.3, Figure TS.29}
D.1.1 Human-induced climate change is a consequence of more than a century of net GHG emissions
from unsustainable energy use, land-use and land use change, lifestyle and patterns of consumption and
production. Without urgent, effective and equitable mitigation actions, climate change increasingly
threatens the health and livelihoods of people around the globe, ecosystem health and biodiversity.
There are both synergies and trade-offs between climate action and the pursuit of other SDGs.
Accelerated and equitable climate action in mitigating, and adapting to, climate change impacts is
critical to sustainable development. (high confidence) {1.6, Cross-Chapter Box 5 in Chapter 4, 7.2, 7.3,
17.3, WGI, WGII}
D.1.2 Synergies and trade-offs depend on the development context including inequalities, with
consideration of climate justice. They also depend on means of implementation, intra- and inter-sectoral
interactions, cooperation between countries and regions, the sequencing, timing and stringency of
mitigation actions, governance, and policy design. Maximising synergies and avoiding trade-offs pose
particular challenges for developing countries, vulnerable populations, and Indigenous Peoples with
limited institutional, technological and financial capacity, and with constrained social, human, and
economic capital. Trade-offs can be evaluated and minimized by giving emphasis to capacity building,
finance, governance, technology transfer, investments, and development and social equity
considerations with meaningful participation of Indigenous Peoples and vulnerable populations. (high
confidence) {1.6, 1.7, 3.7, 5.2, 5.6, 7.4, 7.6, 17.4}
D.1.3 There are potential synergies between sustainable development and energy efficiency and
renewable energy, urban planning with more green spaces, reduced air pollution, and demand side
mitigation including shifts to balanced, sustainable healthy diets (high confidence). Electrification
combined with low GHG energy, and shifts to public transport can enhance health, employment, and
can elicit energy security and deliver equity (high confidence). In industry, electrification and circular
material flows contribute to reduced environmental pressures and increased economic activity and
employment. However, some industrial options could impose high costs (medium confidence). (Figure
SPM.8) {5.2, 8.2, 11.3, 11.5, 17.3, Figure TS.29}
D.1.4 Land-based options such as reforestation and forest conservation, avoided deforestation and
restoration and conservation of natural ecosystems and biodiversity, improved sustainable forest
management, agroforestry, soil carbon management and options that reduce CH4 and N2O emissions in
agriculture from livestock and soil, can have multiple synergies with the SDGs. These include
enhancing sustainable agricultural productivity and resilience, food security, providing additional
biomass for human use, and addressing land degradation. Maximising synergies and managing trade-
offs depend on specific practices, scale of implementation, governance, capacity building, integration
with existing land-use, and the involvement of local communities and Indigenous Peoples and through
benefit sharing supported by frameworks such as Land Degradation Neutrality within the UNCCD.
(high confidence) {3.7, 7.4, 12.5, 17.3}
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D.1.5 Trade-offs in terms of employment, water use, land use competition and biodiversity, as well as
access to, and the affordability of, energy, food, and water can be avoided by well-implemented land-
based mitigation options, especially those that do not threaten existing sustainable land uses and land
rights, though more frameworks for integrated policy implementation are required. The sustainability
of bioenergy and other biobased products is influenced by feedstock, land management practice,
climatic region, the context of existing land management, and the timing, scale and speed of
deployment. (medium confidence) {3.5, 3.7, 7.4, 12.4, 12.5, 17.1}
D.1.6 CDR methods such as soil carbon sequestration and biochar [FOOTNOTE 71] can improve
soil quality and food production capacity. Ecosystem restoration and reforestation sequester carbon in
plants and soil, and can enhance biodiversity and provide additional biomass, but can displace food
production and livelihoods, which calls for integrated approaches to land use planning, to meet multiple
objectives including food security. However, due to limited application of some of the options today,
there are some uncertainties about potential benefits (high confidence) {3.7, 7.4, 7.6, 12.5, 17.3, Table
TS.7}
FOOTNOTE 71: Potential risks, knowledge gaps due to the relative immaturity of use of biochar as
soil amendment and unknown impacts of widespread application, and co-benefits of biochar are
reviewed in 7.4.3.2.
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Figure SPM.8 Synergies and trade-offs between sectoral and system mitigation options and the SDGs
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The sectoral chapters (Chapters 6–11) include qualitative assessments of synergies and trade-offs between sectoral
mitigation options and the SDGs. Figure SPM.8 presents a summary of the chapter-level assessment for selected
mitigation options (see Supplementary Material Table 17.1 for the underlying assessment). The last column
provides a line of sight to the sectoral chapters, which provide details on context specificity and dependence of
interactions on the scale of implementation. Blank cells indicate that interactions have not been assessed due to
limited literature. They do not indicate the absence of interactions between mitigation options and the SDGs.
Confidence levels depend on the quality of evidence and level of agreement in the underlying literature assessed
by the sectoral chapters. Where both synergies and trade-offs exist, the lower of the confidence levels for these
interactions is used.
Some mitigation options may have applications in more than one sector or system. The interactions between
mitigation options and the SDGs might differ depending on the sector or system, and also on the context and the
scale of implementation. Scale of implementation particularly matters when there is competition for scarce
resources.
{6.3, 6.4, 6.7, 7.3, 7.4, 7.5, 7.6, 8.2, 8.4, 8.6, Figure 8.4, Table SM8.1, Table SM8.2, 9.4, 9.5, 9.8, Table 9.5, 10.3,
10.4, 10.5, 10.6, 10.8, Table 10.3, 11.5, 12.5, 17.3, Figure 17.1, Table SM17.1, Annex II Part IV Section 12}
D.2 There is a strong link between sustainable development, vulnerability and climate risks.
Limited economic, social and institutional resources often result in high vulnerability and low
adaptive capacity, especially in developing countries (medium confidence). Several response
options deliver both mitigation and adaptation outcomes, especially in human settlements , land
management, and in relation to ecosystems. However, land and aquatic ecosystems can be
adversely affected by some mitigation actions, depending on their implementation (medium
confidence). Coordinated cross-sectoral policies and planning can maximise synergies and avoid
or reduce trade-offs between mitigation and adaptation (high confidence). {3.7, 4.4, 13.8, 17.3,
WG II}
D.2.1 Sustainable urban planning and infrastructure design including green roofs and facades,
networks of parks and open spaces, management of urban forests and wetlands, urban agriculture, and
water-sensitive design can deliver both mitigation and adaptation benefits in settlements (medium
confidence). These options can also reduce flood risks, pressure on urban sewer systems, urban heat
island effects, and can deliver health benefits from reduced air pollution (high confidence). There could
also be trade-offs. For example, increasing urban density to reduce travel demand, could imply high
vulnerability to heat waves and flooding (high confidence). (Figure SPM.8) {3.7, 8.2, 8.4, 12.5, 13.8,
17.3}
D.2.2 Land-related mitigation options with potential co-benefits for adaptation include agroforestry,
cover crops, intercropping, and perennial plants, thus restoring natural vegetation and rehabilitating
degraded land. These can enhance resilience by maintaining land productivity and protecting and
diversifying livelihoods. Restoration of mangroves and coastal wetlands sequester carbon, while also
reducing coastal erosion and protecting against storm surges, thus, reduce the risks from sea level rise
and extreme weather. (high confidence) {4.4, 7.4, 7.6, 12.5, 13.8}
D.2.3 Some mitigation options can increase competition for scarce resources including land, water
and biomass. Consequently, these can also reduce adaptive capacity, especially if deployed at larger
scale and with high expansion rates thus exacerbating existing risks in particular where land and water
resources are very limited. Examples include the large-scale or poorly planned deployment of
bioenergy, biochar, and afforestation of naturally unforested land. (high confidence) {12.5, 17.3}
D.2.4 Coordinated policies, equitable partnerships and integration of adaptation and mitigation within
and across sectors can maximise synergies and minimise trade-offs and thereby enhance the support for
climate action (medium confidence). Even if extensive global mitigation efforts are implemented, there
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will be a large need for financial, technical, and human resources for adaptation. Absence or limited
resources in social and institutional systems can lead to poorly coordinated responses, thus reducing the
potential for maximising mitigation and adaptation benefits, and increasing risk (high confidence).
{12.6, 13.8, 17.1, 17.3}
D.3 Enhanced mitigation and broader action to shift development pathways towards
sustainability will have distributional consequences within and between countries. Attention to
equity and broad and meaningful participation of all relevant actors in decision-making at all
scales can build social trust, and deepen and widen support for transformative changes. (high
confidence) {3.6, 4.2, 4.5, 5.2, 13.2, 17.3, 17.4}
D.3.1 Countries at all stages of economic development seek to improve the well-being of people, and
their development priorities reflect different starting points and contexts. Different contexts include
social, economic, environmental, cultural, or political conditions, resource endowment, capabilities,
international environment, and history. The enabling conditions for shifting development pathways
towards increased sustainability will therefore also differ, giving rise to different needs. (high
confidence) (Figure SPM.2) {1.6, 1.7, 2.4, 2.6, Cross-Chapter Box 5 in Chapter 4, 4.3.2, 17.4}
D.3.2 Ambitious mitigation pathways imply large and sometimes disruptive changes in economic
structure, with significant distributional consequences, within and between countries. Equity remains a
central element in the UN climate regime, notwithstanding shifts in differentiation between states over
time and challenges in assessing fair shares. Distributional consequences within and between countries
include shifting of income and employment during the transition from high to low emissions activities.
While some jobs may be lost, low-emissions development can also open more opportunities to enhance
skills and create more jobs that last, with differences across countries and sectors. Integrated policy
packages can improve the ability to integrate considerations of equity, gender equality and justice. (high
confidence). {1.4, 1.6, 3.6, 4.2, 5.2, Box 11.1, 14.3, 15.2, 15.5, 15.6}
D.3.3 Inequalities in the distribution of emissions and in the impacts of mitigation policies within
countries affect social cohesion and the acceptability of mitigation and other environmental policies.
Equity and just transitions can enable deeper ambitions for accelerated mitigation. Applying just
transition principles and implementing them through collective and participatory decision-making
processes is an effective way of integrating equity principles into policies at all scales, in different ways
depending on national circumstances. (medium confidence) This is already taking place in many
countries and regions, as national just transition commissions or task forces, and related national
policies, have been established in several countries. A multitude of actors, networks, and movements
are engaged. (high confidence) {1.6, 1.7, 2.4, 2.6, 4.5, 13.2, 13.9, 14.3, 14.5}
D.3.4 Broadening equitable access to domestic and international finance, technologies that facilitate
mitigation, and capacity, while explicitly addressing needs can further integrate equity and justice into
national and international policies and act as a catalyst for accelerating mitigation and shifting
development pathways (medium confidence). The consideration of ethics and equity can help address
the uneven distribution of adverse impacts associated with 1.5°C and higher levels of global warming,
in all societies (high confidence). Consideration of climate justice can help to facilitate shifting
development pathways towards sustainability, including through equitable sharing of benefits and
burdens of mitigation, increasing resilience to the impacts of climate change, especially for vulnerable
countries and communities, and equitably supporting those in need (high confidence). {1.4, 1.6, 1.7,
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3.6, 4.2, 4.5, Box 5.10, 13.4, 13.8, 13.9, 14.3, 14.5, 15.2, 15.5, 15.6, 16.5, 17.3, 17.4, SR1.5 SPM, WGII
CH18}
E. Strengthening the response
E.1 There are mitigation options which are feasible [FOOTNOTE 72] to deploy at scale in the
near term. Feasibility differs across sectors and regions, and according to capacities and the speed
and scale of implementation. Barriers to feasibility would need to be reduced or removed, and
enabling conditions [FOOTNOTE 73] strengthened to deploy mitigation options at scale. These
barriers and enablers include geophysical, environmental-ecological, technological, and economic
factors, and especially institutional and socio-cultural factors. Strengthened near-term action
beyond the NDCs (announced prior to UNFCCC COP26) can reduce and/or avoid long-term
feasibility challenges of global modelled pathways that limit warming to 1.5 °C (>50%) with no
or limited overshoot. (high confidence) {3.8, 6.4, 8.5, 9.9, 10.8, 12.3, Figure TS.31, Annex II Part
IV Section 11}
FOOTNOTE 72: In this report, the term ‘feasibility’ refers to the potential for a mitigation or adaptation
option to be implemented. Factors influencing feasibility are context-dependent and may change over
time. Feasibility depends on geophysical, environmental-ecological, technological, economic, socio-
cultural and institutional factors that enable or constrain the implementation of an option. The feasibility
of options may change when different options are combined and increase when enabling conditions are
strengthened.
FOOTNOTE 73: In this report, the term ‘enabling conditions’ refers to conditions that enhance the
feasibility of adaptation and mitigation options. Enabling conditions include finance, technological
innovation, strengthening policy instruments, institutional capacity, multi-level governance and
changes in human behaviour and lifestyles.
E.1.1 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. This enables deployment in many
regions. (high confidence) While many mitigation options have environmental co-benefits, including
improved air quality and reducing toxic waste, many also have adverse environmental impacts, such as
reduced biodiversity, when applied at very large scale, for example very large scale bioenergy or large
scale use of battery storage, that would have to be managed (medium confidence). Almost all mitigation
options face institutional barriers that need to be addressed to enable their application at scale (medium
confidence). {6.4, Figure 6.19, 7.4, 8.5, Figure 8.19, 9.9, Figure 9.20, 10.8, Figure 10.23, 12.3, Figure
12.4, Figure TS.31}
E.1.2 The feasibility of mitigation options varies according to context and time. For example, the
institutional capacity to support deployment varies across countries; the feasibility of options that
involve large-scale land use changes varies across regions; spatial planning has a higher potential at
early stages of urban development; the potential of geothermal is site specific; and capacities, cultural
and local conditions can either inhibit or enable demand-side responses. The deployment of solar and
wind energy has been assessed to become increasingly feasible over time. The feasibility of some
options can increase when combined or integrated, such as using land for both agriculture and
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centralised solar production. (high confidence) {6.4, 6.6, 7.4, 8.5, 9.9, 10.8, 12.3, Appendix 10.3, Table
SM6, Table SM8.2, Table SM9.1, Table SM12.B}
E.1.3 Feasibility depends on the scale and speed of implementation. Most options face barriers when
they are implemented rapidly at a large scale, but the scale at which barriers manifest themselves varies.
Strengthened and coordinated near-term actions in cost-effective modelled global pathways that limit
warming to 2°C (>67%) or lower, reduce the overall risks to the feasibility of the system transitions,
compared to modelled pathways with relatively delayed or uncoordinated action.[FOOTNOTE 74]
(high confidence) {3.8, 6.4, 10.8, 12.3}
FOOTNOTE 74: The future feasibility challenges described in the modelled pathways may differ from
the real-world feasibility experiences of the past.
E.2 In all countries, mitigation efforts embedded within the wider development context can
increase the pace, depth and breadth of emissions reductions (medium confidence). Policies that
shift development pathways towards sustainability can broaden the portfolio of available
mitigation responses, and enable the pursuit of synergies with development objectives (medium
confidence). Actions can be taken now to shift development pathways and accelerate mitigation
and transitions across systems (high confidence). {4.3, 4.4, Cross-Chapter Box 5 in Chapter 4, 5.2,
5.4, 13.9, 14.5, 15.6, 16.3, 16.4, 16.5}
E.2.1 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).
Actions that steer, for example, energy and land systems transitions, economy-wide structural change,
and behaviour change, can shift development pathways towards sustainability [FOOTNOTE 75]
(medium confidence). {4.3, Cross-Chapter Box 5 in Chapter 4, 5.4, 13.9}
FOOTNOTE 75: Sustainability may be interpreted differently in various contexts as societies pursue
a variety of sustainable development objectives.
E.2.2 Combining mitigation with policies to shift development pathways, such as broader sectoral
policies, policies that induce lifestyle or behaviour changes, financial regulation, or macroeconomic
policies can overcome barriers and open up a broader range of mitigation options (high confidence). It
can also facilitate the combination of mitigation and other development goals (high confidence). For
example, measures promoting walkable urban areas combined with electrification and renewable
energy can create health co-benefits from cleaner air and benefits from enhanced mobility (high
confidence). Coordinated housing policies that broaden relocation options can make mitigation
measures in transport more effective (medium confidence). {3.2, 4.3, 4.4, Cross-Chapter Box 5 in
Chapter 4, 5.3, 8.2, 8.4}
E.2.3 Institutional and regulatory capacity, innovation, finance, improved governance and
collaboration across scales, and multi-objective policies enable enhanced mitigation and shifts in
development pathways. Such interventions can be mutually reinforcing and establish positive feedback
mechanisms, resulting in accelerated mitigation. (high confidence) {4.4, 5.4, Figure 5.14, 5.6, 9.9, 13.9,
14.5, 15.6, 16.3, 16.4, 16.5, Cross-Chapter Box 12 in Chapter 16}
E.2.4 Enhanced action on all the above enabling conditions can be taken now (high confidence). In
some situations, such as with innovation in technology at an early stage of development and some
changes in behaviour towards low-emissions, because the enabling conditions may take time to be
established, action in the near-term can yield accelerated mitigation in the mid-term (medium
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confidence). In other situations, the enabling conditions can be put in place and yield results in a
relatively short time frame, for example the provision of energy related information, advice and
feedback to promote energy saving behaviour (high confidence). {4.4, 5.4, Figure 5.14, 5.6, 6.7, 9.9,
13.9, 14.5, 15.6, 16.3, 16.4, 16.5, Cross-Chapter Box 12 in Chapter 16}
E.3 Climate governance, acting through laws, strategies and institutions, based on national
circumstances, supports mitigation by providing frameworks through which diverse actors
interact, and a basis for policy development and implementation (medium confidence). Climate
governance is most effective when it integrates across multiple policy domains, helps realise
synergies and minimize trade-offs, and connects national and sub-national policy-making levels
(high 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). {5.4, 5.6, 8.5, 9.9, 13.2, 13.7, 13.9}
E.3.1 Climate governance enables mitigation by providing an overall direction, setting targets,
mainstreaming climate action across policy domains, enhancing 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). Framework laws set an
overarching legal basis, either operating through a target and implementation approach, or a sectoral
mainstreaming approach, or both, depending on national circumstance (medium confidence). Direct
national and sub-national laws that explicitly target mitigation and indirect laws that impact emissions
through mitigation related policy domains have both been shown to be relevant to mitigation outcomes
(medium confidence). {13.2}
E.3.2 Effective national climate institutions address coordination across sectors, scales and actors,
build consensus for action among diverse interests, and inform strategy setting (medium confidence).
These functions are often accomplished through independent national expert bodies, and high-level
coordinating bodies that transcend departmental mandates. Complementary sub-national institutions
tailor mitigation actions to local context and enable experimentation but can be limited by inequities
and resource and capacity constraints (high confidence). Effective governance requires adequate
institutional capacity at all levels (high confidence). {4.4, 8.5, 9.9, 11.3, 11.5, 11.6, 13.2, 13.5, 13.7,
13.9}
E.3.3 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. 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. Mitigation options that align with
prevalent ideas, values and beliefs are more easily adopted and implemented. Climate-related litigation,
for example by governments, private sector, civil society and individuals is growing, with a large
number of cases in some developed countries, and with a much smaller number in some developing
countries, and in some cases, has influenced the outcome and ambition of climate governance. (medium
confidence) {5.2, 5.4, 5.5, 5.6, 9.9, 13.3, 13.4}
E.4 Many regulatory and economic instruments have already been deployed successfully.
Instrument design can help address equity and other objectives. These instruments could support
deep emissions reductions and stimulate innovation if scaled up and applied more widely (high
confidence). Policy packages that enable innovation and build capacity are better able to support
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a shift towards equitable low-emission futures than are individual policies (high confidence).
Economy-wide packages, consistent with national circumstances, can meet short-term economic
goals while reducing emissions and shifting development pathways towards sustainability
(medium confidence). {13.6, 13.7, 13.9, 16.3, 16.4, 16.6, Cross-Chapter Box 5 in Chapter 4}
E.4.1 A wide range of regulatory instruments at the sectoral level have proven effective in reducing
emissions. These instruments, and broad-based approaches including relevant economic
instruments[FOOTNOTE 76], are complementary. (high confidence) Regulatory instruments that are
designed to be implemented with flexibility mechanisms can reduce costs (medium confidence).
Scaling up and enhancing the use of regulatory instruments, consistent with national circumstances,
could improve mitigation outcomes in sectoral applications, including but not limited to renewable
energy, land-use and zoning, building codes, vehicle and energy efficiency, fuel standards, and low-
emissions industrial processes and materials (high confidence). {6.7, 7.6, 8.4, 9.9, 10.4, 11.5, 11.6,
13.6}
FOOTNOTE 76: Economic instruments are structured to provide a financial incentive to reduce
emissions and include, among others, market- and price-based instruments.
E.4.2 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). Where
implemented, carbon pricing instruments have incentivized low-cost emissions reduction measures, but
have been less effective, on their own and at prevailing prices during the assessment period, to promote
higher-cost measures necessary for further reductions (medium confidence). Equity and distributional
impacts of such 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).
Practical experience has informed instrument design and helped to improve predictability,
environmental effectiveness, economic efficiency, distributional goals and social acceptance (high
confidence). Removing fossil fuel subsidies would reduce emissions, improve public revenue and
macroeconomic performance, and yield other environmental and sustainable development benefits;
subsidy removal may have adverse distributional impacts especially on the most economically
vulnerable groups which, in some cases can be mitigated by measures such as re-distributing revenue
saved, all of which depend on national circumstances (high confidence); fossil fuel subsidy removal is
projected by various studies to reduce global CO2 emissions by 1-4%, and GHG emissions by up to
10% by 2030, varying across regions (medium confidence). {6.3, 13.6}
E.4.3 Low-emission technological innovation is strengthened through the combination of dedicated
technology-push policies and investments (e.g., for scientific training, R&D, demonstration), with
tailored demand-pull policies (e.g., standards, feed-in tariffs, taxes), which create incentives and market
opportunities. Developing countries’ abilities to deploy low-emission technologies, seize socio-
economic benefits and manage trade-offs would be enhanced with increased financial resources and
capacity for innovation which are currently concentrated in developed countries, alongside technology
transfer. (high confidence) {16.2, 16.3, 16.4, 16.5}
E.4.4 Effective policy packages would be comprehensive in coverage, harnessed to a clear vision for
change, balanced across objectives, aligned with specific technology and system needs, consistent in
terms of design and tailored to national circumstances. They are better able to realise synergies and
avoid trade-offs across climate and development objectives. Examples include: emissions reductions
from buildings through a mix of efficiency targets, building codes, appliance performance standards,
information provision, carbon pricing, finance and technical assistance; and industrial GHG emissions
reductions through innovation support, market creation and capacity building. (high confidence) {4.4,
6.7, 9.9, 11.6, 13.7, 13.9, 16.3, 16.4}
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E.4.5 Economy-wide packages that support mitigation and avoid negative environmental outcomes
include: long-term public spending commitments, pricing reform; and investment in education and
training, natural capital, R&D and infrastructure (high confidence). They can meet short-term economic
goals while reducing emissions and shifting development pathways towards sustainability (medium
confidence). Infrastructure investments can be designed to promote low-emissions futures that meet
development needs (medium confidence). {Cross Chapter Box 7 in Chapter 4, 5.4, 5.6, 8.5, 13.6, 13.9,
16.3, 16.5, 16.6}
E.4.6 National policies to support technology development and diffusion, and participation in
international markets for emission reduction, can bring positive spill-over effects for other countries
(medium confidence), although reduced demand for fossil fuels could result in costs to exporting
countries (high confidence). There is no consistent evidence that current emission trading systems have
led to significant emissions leakage, which can be attributed to design features aimed at minimising
competitiveness effects among other reasons (medium confidence). {13.6, 13.7, 13.8, 16.2, 16.3, 16.4}
E.5 Tracked financial flows fall short of the levels needed to achieve mitigation goals across
all sectors and regions. The challenge of closing gaps is largest in developing countries as a whole.
Scaling up mitigation financial flows can be supported by clear policy choices and signals from
governments and the international community. (high confidence) Accelerated international
financial cooperation is a critical enabler of low-GHG and just transitions, and can address
inequities in access to finance and the costs of, and vulnerability to, the impacts of climate change
(high confidence). {15.2, 15.3, 15.4, 15.5, 15.6}
E.5.1 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). Mitigation investment gaps are wide for all sectors, and widest for the
AFOLU sector in relative terms and for developing countries [FOOTNOTE 77] (high confidence).
Financing and investment requirements for adaptation, reduction of losses and damages, general
infrastructure, regulatory environment and capacity building, and climate-responsive social protection
further exacerbate the magnitude of the challenges for developing countries to attract financing (high
confidence). {3.2, 14.4, 15.1, 15.2, 15.3, 15.4, 15.5}
FOOTNOTE 77: In modelled pathways, regional investments are projected to occur when and where
they are most cost-effective to limit global warming. The model quantifications help to identify high-
priority areas for cost-effective investments, but do not provide any indication on who would finance
the regional investments.
E.5.2 There is sufficient global capital and liquidity to close global investment gaps, given the size
of the global financial system, but there are barriers to redirect capital to climate action both within and
outside the global financial sector, and in the macroeconomic headwinds facing developing regions.
Barriers to the deployment of commercial finance from within the financial sector as well as
macroeconomic considerations include: 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 (high
confidence). Challenges from outside the financial sector include: limited local capital markets;
unattractive risk-return profiles, in particular due to missing or weak regulatory environments consistent
with ambition levels; limited institutional capacity to ensure safeguards; standardization, aggregation,
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scalability and replicability of investment opportunities and financing models; and, a pipeline ready for
commercial investments. (high confidence) {15.2, 15.3, 15.5, 15.6}
E.5.3 Accelerated financial support for developing countries from developed countries and other
sources is a critical enabler to enhance mitigation action and address inequities in access to finance,
including its costs, terms and conditions and economic vulnerability to climate change for developing
countries (high confidence). Scaled-up public grants for mitigation and adaptation funding for
vulnerable regions, especially in Sub-Saharan Africa, would be cost-effective and have high social
returns in terms of access to basic energy (high confidence). Options for scaling up mitigation in
developing regions include: increased levels of public finance and publicly mobilised private finance
flows from developed to developing countries in the context of the USD100 billion-a-year goal; increase
the use of public guarantees to reduce risks and leverage private flows at lower cost; local capital
markets development; and building greater trust in international cooperation processes (high
confidence). A coordinated effort to make the post-pandemic recovery sustainable and increased flows
of financing over the next decade can accelerate climate action, including in developing regions and
countries facing high debt costs, debt distress and macro-economic uncertainty (high confidence).
{15.2, 15.3, 15.4, 15.5, 15.6, Box 15.6}
E.5.4 Clear signalling by governments and the international community, including a stronger
alignment of public sector finance and policy, and higher levels of public sector climate finance, reduces
uncertainty and transition risks for the private sector. Depending on national contexts, investors and
financial intermediaries, central banks, and financial regulators can support climate action and can shift
the systemic underpricing of climate climate-related risk by increasing awareness, transparency and
consideration of climate-related risk, and investment opportunities. Financial flows can also be aligned
with funding needs through: greater support for technology development; a continued role for
multilateral and national climate funds and development banks; lowering financing costs for
underserved groups through entities such as green banks existing in some countries, funds and risk-
sharing mechanisms; economic instruments which consider economic and social equity and
distributional impacts; gender-responsive and women-empowerment programs as well as enhanced
access to finance for local communities and Indigenous Peoples and small landowners; and greater
public-private cooperation. (high confidence) {15.2, 15.5, 15.6}
E.6 International cooperation is a critical enabler for achieving ambitious climate change
mitigation goals. The UNFCCC, Kyoto Protocol, and Paris Agreement are supporting rising
levels of national ambition and encouraging development and implementation of climate policies,
although gaps remain. Partnerships, agreements, institutions and initiatives operating at the sub-
global and sectoral levels and engaging multiple actors are emerging, with mixed levels of
effectiveness. (high confidence) {8.5, 14.2, 14.3, 14.5, 14.6, 15.6, 16.5}
E.6.1 Internationally agreed processes and goals, such as those in the UNFCCC, Kyoto Protocol, and
Paris Agreement, including transparency requirements for national reporting on emissions, actions and
support, and tracking progress towards the achievement of nationally determined contributions, are
enhancing international cooperation, national ambition and policy development. International financial,
technology and capacity building support to developing countries will enable greater implementation
and encourage ambitious nationally determined contributions over time. (medium confidence) {14.3}
E.6.2 International cooperation on technology development and transfer accompanied by capacity
building, knowledge sharing, and technical and financial support can accelerate the global diffusion of
mitigation technologies, practices and policies at national and sub-national levels, and align these with
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other development objectives (high confidence). Challenges in and opportunities to enhance innovation
cooperation exist, including in the implementation of elements of the UNFCCC and the Paris
Agreement as per the literature assessed, such as in relation to technology development and transfer,
and finance (high confidence). International cooperation on innovation works best when tailored to
specific institutional and capability contexts, when it benefits local value chains, when partners
collaborate equitably and on voluntary and mutually agreed terms, when all relevant voices are heard,
and when capacity building is an integral part of the effort (medium confidence). Support to strengthen
technological innovation systems and innovation capabilities, including through financial support in
developing countries would enhance engagement in and improve international cooperation on
innovation (high confidence). {4.4, 14.2, 14.4, 16.3, 16.5, 16.6}
E.6.3 Transnational partnerships can stimulate policy development, low-emissions technology
diffusion and emission reductions by linking sub-national and other actors, including cities, regions,
non-governmental organisations and private sector entities, and by enhancing interactions between state
and non-state actors. While this potential of transnational partnerships is evident, uncertainties remain
over their costs, feasibility, and effectiveness. Transnational networks of city governments are leading
to enhanced ambition and policy development and a growing exchange of experience and best practices
(medium confidence). {8.5, 11.6, 14.5, 16.5, Cross-Chapter Box 12 in Chapter 16}
E.6.4 International environmental and sectoral agreements, institutions, and initiatives are helping,
and in some cases may help, to stimulate low GHG emissions investment and reduce emissions.
Agreements addressing ozone depletion and transboundary air pollution are contributing to mitigation,
and in other areas, such as atmospheric emissions of mercury, may contribute to mitigation (high
confidence). Trade rules have the potential to stimulate international adoption of mitigation
technologies and policies, but may also limit countries’ ability to adopt trade-related climate policies
(medium confidence). Current sectoral levels of ambition vary, with emission reduction aspirations in
international aviation and shipping lower than in many other sectors (medium confidence). {14.5, 14.6}
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