Editing IPCC:AR6/WGIII/TS (section)

== TS.3 Emission Trends and Drivers ==

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'''Global net anthropogenic GHG emissions during the decade 2010–2019 were higher than any previous time in human history (''' '''''high confidence''''' ''').''' Since 2010, GHG emissions have continued to grow reaching 59 ± 6.6 GtCO 2 -eq in 2019, [[#footnote-029|4]] but the average annual growth in the last decade (1.3%, 2010–2019) was lower than in the previous decade (2.1%, 2000–2009) ( ''high confidence'' ). Average annual GHG emissions were 56 GtCO 2 -eq yr –1 for 2010–2019 (the highest decadal average on record) growing by about 9.1 GtCO 2 -eq yr –1 from the previous decade (2000–2009) ( ''high confidence'' ). (Figure TS.2) {2.2.2, Table 2.1, Figure 2.5}

'''Emissions growth has varied, but has persisted, across all groups of greenhouse gases (''' '''''high confidence''''' ''').''' The average annual emission levels of the last decade (2010–2019) were higher than in any previous decade for each group of greenhouse gases ( ''high confidence'' ). In 2019, CO 2 emissions were 45 ± 5.5 GtCO ''2'' , [[#footnote-028|5]] methane (CH 4 ) 11 ± 3.2 GtCO 2 -eq, nitrous oxide (N 2 O) 2.7 ± 1.6 GtCO 2 -eq and fluorinated gases (F-gases [[#footnote-027|6]] ) 1.4 ± 0.41 GtCO 2 -eq. Compared to 1990, the magnitude and speed of these increases differed across gases: CO 2 from fossil fuel and industry (FFI) grew by 15 GtCO 2 -eq yr –1 (67%), CH 4 by 2.4 GtCO 2 -eq yr –1 (29%), F-gases by 0.97 GtCO ''2'' -eq yr –1 (250%), N 2 O by 0.65 GtCO 2 -eq yr –1 (33%). CO 2 emissions from net land use, land-use change and forestry (LULUCF) have shown little long-term change, with large uncertainties preventing the detection of statistically significant trends. F-gases excluded from GHG emissions inventories such as ''chlorofluorocarbons'' and ''hydrochlorofluorocarbons'' are about the same size as those included ( ''high confidence'' ). (Figure TS.2) {2.2.1, 2.2.2, Table 2.1, Figures 2.2, 2.3 and 2.5}

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'''Figure TS.2 | Global net anthropogenic GHG emissions (''' '''GtCO''' ''2'' '''-eq''' '''y''' '''r''' –1 ''') 1990–2019.''' Global net anthropogenic GHG emissions include CO 2 from fossil fuel combustion and industrial processes (CO 2 -FFI); net CO 2 from land use, land-use change and forestry (CO 2 -LULUCF) 5 ; methane (CH 4 ); nitrous oxide (N 2 O); and fluorinated gases (HFCs, PFCs, SF 6 , NF 3 ). 6 '''Panel a''' shows aggregate annual global net anthropogenic GHG emissions by groups of gases from 1990 to 2019 reported in GtCO ''2'' -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 for 1990, 2000, 2010 and 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: CO 2 -FFI ±8%; CO 2 -LULUCF ±70%; CH 4 ±30%; N 2 O ±60%; F-gases ±30%; GHG ±11%. Uncertainties in GHG emissions are assessed in Supplementary Material 2.2. The single-year peak of emissions in 1997 was due to higher CO 2 -LULUCF emissions from a forest and peat fire event in South East Asia. '''Panel b''' shows global anthropogenic CO 2 -FFI, net CO 2 -LULUCF, CH 4 , N 2 O and F-gas emissions individually for the period 1990–2019, normalised relative to 100 in 1990. Note the different scale for the included F-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, Supplementary Material 2.2, Figure TS.2}

'''Globally, gross domestic product (GDP) per capita and population growth remained the strongest drivers of CO''' 2 '''emissions from fossil fuel combustion in the last decade (''' '''''high confidence''''' ''').''' Trends since 1990 continued in the years 2010 to 2019 with GDP per capita and population growth increasing emissions by 2.3% yr –1 and 1.2% yr –1 , respectively. This growth outpaced the reduction in the use of energy per unit of GDP (–2% yr –1 , globally) as well as improvements in the carbon intensity of energy (–0.3% yr –1 ). {2.4.1, Figure 2.19}

'''Box TS.1 |''' '''The COVID-19 Pandemic: Impact on Emissions and Opportunities for Mitigation'''

The COVID-19 pandemic triggered the deepest global economic contraction as well as CO 2 emission reductions since the Second World War {2.2.2} . While emissions and most economies rebounded in 2020, some impacts of the pandemic could last well beyond this. Owing to the very recent nature of this event, it remains unclear what the exact short- and long-term impacts on global emissions drivers, trends, macroeconomics and finance will be.

Starting in the spring of 2020 a major break in global emissions trends was observed due to lockdown policies implemented in response to the pandemic. Overall, global CO 2 -FFI emissions are estimated to have declined by 5.8% (5.1–6.3%) in 2020, or about 2.2 (1.9–2.4%) GtCO 2 in total. This exceeds any previous global emissions decline since 1970 both in relative and absolute terms (Box TS.1, Figure 1). During periods of economic lockdown, daily emissions, estimated based on activity and power-generation data, declined substantially compared to 2019, particularly in April 2020 – as shown in Box TS.1, Figure 1 – but rebounded by the end of 2020. Impacts were differentiated by sector, with road transport and aviation particularly affected. Different databases estimate the total power-sector CO 2 reduction from 2019 to 2020 at 3% (IEA [[#footnote-026|7]] ) and 4.5% (EDGAR [[#footnote-025|8]] ). Approaches that predict near real-time estimates of the power-sector reduction are more uncertain and estimates range more widely between 1.8%, 4.1% and 6.8%, the latter taking into account the over-proportional reduction of coal generation due to low gas prices and merit order effects.

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'''Box TS.1, Figure''' '''1 |''' '''Global carbon emissions in 2020 and the impact of COVID-19. Panel (a)''' depicts carbon emissions from fossil fuel and industry over the past five decades. The single-year declines in emissions following major economic and geopolitical events are shown, as well as the decline recorded in five different datasets for emissions in 2020 compared to 2019. '''Panel (b)''' depicts the perturbation of daily carbon emissions in 2020 compared to 2019, showing the impact of COVID-19 lockdown policies. {Figure 2.6}

The lockdowns implemented in many countries accelerated some specific trends, such as the uptake in urban cycling. The acceptability of collective social change over a longer term towards less resource-intensive lifestyles, however, depends on the social mandate for change. This mandate can be built through public participation, discussion and debate, to produce recommendations that inform policymaking. {Box 5.2}

Most countries were forced to undertake unprecedented levels of short-term public expenditures in 2021. This is expected to slow economic growth and may squeeze financial resources for mitigation and relevant investments in the near future. Pandemic responses have increased sovereign debt across countries in all income bands and the sharp increase in most developing economies and regions has caused debt distress, widening the gap in developing countries’ access to capital. {15.6.3}

The wider overall reduction in energy investment has prompted a relative shift towards low-carbon investment particularly for major future investment decisions by the private sector {15.2.1, 15.3.1, 15.6.1} . Some countries and regions have prioritised green stimulus expenditures, for example, as part of a ‘Green New Deal’ {Box 13.1} . This is motivated by assessments that investing in new growth industries can boost the macroeconomic effectiveness (‘multipliers’) of public spending, crowd-in and revive private investment, whilst also delivering on mitigation commitments. {15.2.3}

The impacts of COVID-19 may have temporarily set back development and the delivery of many SDGs. It also distracts political and financial capacity away from efforts to accelerate climate change mitigation and shift development pathways to increased sustainability. Yet, studies of previous post-shock periods suggest that waves of innovation that are ready to emerge can be accelerated by crises, which may prompt new behaviours, weaken incumbent systems, and initiate rapid reform. {1.6.5}

Institutional change can be slow but major economic dislocation can create significant opportunities for new ways of financing and enabling ‘leapfrogging’ investment {10.8} . Given the unambiguous risks of climate change, and consequent stranded asset risks from new fossil fuel investments {Box 6.11} , the most robust recoveries may well be those which align with lower carbon and resilient development pathways.

'''Cumulative net CO''' 2 '''emissions over the last decade (2''' '''010–201''' '''9) are about the same size as the remaining carbon budget to limit warming to 1.5°C (&gt;67%) (''' '''''medium confidence''''' ''').''' 62% of total cumulative CO 2 emissions from 1850 to 2019 occurred since 1970 (1500 ± 140 GtCO 2 ), about 43% since 1990 (1000 ± 90 GtCO 2 ), and about 17% since 2010 (410 ± 30 GtCO 2 ). For comparison, the remaining carbon budget for keeping warming to 1.5°C with a 67% (50%) probability is about 400 (500) ± 220 GtCO 2 (Figure TS.3). {2.2.2, Figure 2.7, AR6 WGI Chapter 5.5, AR6 WGI Chapter 5, Table 5.8}

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'''Figure TS.''' '''3 |''' '''Historic anthropogenic CO''' 2 '''emission and cumulative CO''' 2 '''emissions (1850–2019) as well as remaining carbon budgets for limiting warming to 1.5°C (&gt;67%) and 2°C (&gt;67%). Panel (a)''' shows historic annual anthropogenic CO 2 emissions (GtCO 2 yr –1 ) by fuel type and process. '''Panel (b)''' shows historic cumulative anthropogenic CO 2 emissions for the periods 1850–1989, 1990–2009, and 2010–2019 as well as remaining future carbon budgets as of 1 January 2020 to limit warming to 1.5°C and 2°C at the 67th percentile of the transient climate response to cumulative CO 2 emissions. The whiskers indicate a budget uncertainty of ±220 GtCO 2 -eq for each budget and the aggregate uncertainty range at one standard deviation for historical cumulative CO 2 emissions, consistent with WGI. {Figure 2.7}

'''A growing number of countries have achieved GHG emission reductions over periods longer than 10 years – a few at rates that are broadly consistent with the global rates described in climate change mitigation scenarios that limit warming to 2°C (&gt;67%) (''' '''''high confidence''''' ''').''' At least 18 countries have reduced CO 2 and GHG emissions for longer than 10 years. Reduction rates in a few countries have reached 4% in some years, in line with global rates observed in pathways that limit warming to 2°C (&gt;67%). However, the total reduction in annual GHG emissions of these countries is small (about 3.2 GtCO 2 -eq yr –1 ) compared to global emissions growth observed over the last decades. Complementary evidence suggests that countries have decoupled territorial CO 2 emissions from GDP, but fewer have decoupled consumption-based emissions from GDP. Decoupling has mostly occurred in countries with high per-capita GDP and high per-capita CO 2 emissions. (Figure TS.4, Box TS.2) {2.2.3, 2.3.3, Figure 2.11, Tables 2.3 and 2.4}

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'''Figure TS.4 |''' '''Emissions have grown in most regions, although some countries have achieved sustained emission reductions in line with 2°C scenarios. Emissions have grown in most regions, although some countries have achieved sustained emission reductions in line with 2°C scenarios.''' Change in regional GHG emissions and rates of change compatible with warming targets. '''Panel (a):''' Regional GHG emission trends (in GtCO 2 -eq yr –1 (GWP100; AR6) for the time period 1990–2019. '''Panel (b):''' Historical GHG emissions change by region (2010–2019). Circles depict countries, scaled by total emissions in 2019, short horizontal lines depict the average change by region. Also shown are global rates of reduction over the period 2020–2040 in scenarios assessed in AR6 that limit global warming to 1.5°C and 2°C with different probabilities. The 5–95th percentile range of emissions changes for scenarios below 1.5°C with no or limited overshoot (scenario category C1) and scenarios below 2°C (&gt;67%) with immediate action (scenario category C3a) are shown as a shaded area with a horizontal line at the mean value. Panel b excludes CO 2 LULUCF due to a lack of consistent historical national data, and International Shipping and Aviation, which cannot be allocated to regions. Global rates of reduction in scenarios are shown for illustrative purposes only and do not suggest rates of reduction at the regional or national level. {Figures 2.9 and 2.11}

'''Box TS.2 | Greenhouse Gas (GHG) Emission Metrics Provide Simplified Information About the Effects of Different Greenhouse Gases'''

Comprehensive mitigation policy relies on consideration of all anthropogenic forcing agents, which differ widely in their atmospheric lifetimes and impacts on the climate system. GHG emission metrics provide simplified information about the effect that emissions of different gases have on global temperature or other aspects of climate, usually expressed relative to the effect of emitting CO 2 . [[#footnote-024|9]] This information can support choices about priorities, trade-offs and synergies in mitigation policies and emission targets for non-CO 2 gases relative to CO 2 as well as baskets of gases expressed in CO 2 -eq.

The choice of metric can affect the timing and emphasis placed on reducing emissions of short-lived climate forcers (SLCFs) relative to CO 2 within multi-gas abatement strategies as well as the costs of such strategies. Different metric choices can also alter the time at which net zero GHG emissions are calculated to be reached for any given emissions scenario. A wide range of GHG emission metrics has been published in the scientific literature, which differ in terms of: (i) the key measure of climate change they consider, (ii) whether they consider climate outcomes for a specified point in time or integrated over a specified time horizon, (iii) the time horizon over which the metric is applied, (iv) whether they apply to a single emission pulse, to emissions sustained over a period of time, or to a combination of both, and (v) whether they consider the climate effect from an emission compared to the absence of that emission, or compared to a reference emissions level or climate state. {Annex II}

Parties to the Paris Agreement decided to report aggregated emissions and removals (expressed as CO ''2'' -eq) based on the Global Warming Potential (GWP) with a time horizon of 100 years (GWP100) using values from IPCC AR5 or from a subsequent IPCC report as agreed upon by the CMA, [[#footnote-023|10]] and to account for future Nationally Determined Contributions (NDCs) in accordance with this approach. Parties may also report supplemental information on aggregate emissions and removals, expressed as CO ''2'' -eq, using other GHG emission metrics assessed by the IPCC.

The WGIII contribution to AR6 uses updated GWP100 values from AR6 WGI to report aggregate emissions and removals unless stated otherwise. These reflect updated scientific understanding of the response of the climate system to emissions of different gases and include a methodological update to incorporate climate-carbon cycle feedbacks associated with the emission of non-CO 2 gases (see Annex II.II.8 for a list of GWP100 metric values). The choice of GWP100 was made ''inter alia'' for consistency with decisions under the Rulebook for the Paris Agreement and because it is the dominant metric used in the literature assessed by WGIII. Furthermore, for mitigation pathways that limit global warming to 2°C (&gt;67%) or lower, using GWP100 to inform cost-effective abatement choices between gases would achieve such long-term temperature goals at close to least global cost within a few percent ( ''high confidence'' ).

However, GWP100 is not well-suited to estimate the cumulative effect on climate from sustained SLCF emissions and the resulting warming at specific points in time. This is because the warming caused by an individual SLCF emission pulse is not permanent, and hence, unlike CO 2 , the warming from successive SLCF emission pulses over multiple decades or centuries depends mostly on their ongoing rate of emissions rather than cumulative emissions. Recently developed step/pulse metrics such as the CGTP (combined global temperature change potential) and GWP* (referred to as GWP-star and indicated by an asterisk) recognise that a sustained increase/decrease in the rate of SLCF emissions has indeed a similar effect on global surface temperature as one-off emission/removal of CO 2 . These metrics use this relationship to calculate the CO 2 emissions or removals that would result in roughly the same temperature change as a sustained change in the rate of SLCF emissions (CGTP) over a given time period, or as a varying time series of CH 4 emissions (GWP*). IFrom a mitigation perspective, this makes these metrics well-suited in principle to estimate the effect on the remaining carbon budget from more, or less, ambitious SLCF mitigation over multiple decades compared to a given reference scenario ( ''high confidence'' ). However, potential application in wider climate policy (e.g., to inform equitable and ambitious emission targets or to support sector-specific mitigation policies) is contested and relevant literature still limited.

All 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. For this reason, the WGIII contribution to the AR6 reports emissions and mitigation options for individual gases where possible; CO 2 -equivalent emissions are reported in addition to individual gas emissions where this is judged to be policy-relevant. This approach aims to reduce the ambiguity regarding actual climate outcomes over time arising from the use of any specific GHG emission metric. {Cross-Chapter Box 2 in Chapter 2, SM.2.3, Annex II.II.8; AR6 WGI Chapter 7.6}

'''Consumption-based CO''' 2 '''emissions in Developed Countries and the Asia and Pacific region are higher than in other regions (''' '''''high confidence''''' ''').''' In Developed Countries, consumption-based CO 2 emissions peaked at 15 GtCO 2 in 2007, declining to about 13 GtCO 2 in 2018. The Asia and Developing Pacific region, with 52% of the current global population, has become a major contributor to consumption-based CO 2 emission growth since 2000 (5.5% yr –1 for 2000–2018); in 2015 it exceeded the Developed Countries region, with 16% of global population, as the largest emitter of consumption-based CO 2 . {2.3.2, Figure 2.14}

'''Carbon-intensity improvements in the production of traded products has led to a net reduction in CO''' ''2'' '''emissions embodied in international trade (''' '''''high confidence''''' ''').''' A decrease in the carbon intensity of traded products has offset increased trade volumes between 2006 and 2016. Emissions embodied in internationally traded products depend on the composition of the global supply chain across sectors and countries and the respective carbon intensity of production processes (emissions per unit of economic output). {2.3, 2.4}

'''Developed Countries tend to be net CO''' 2 '''emission importers, whereas developing countries tend to be net emission exporters (''' '''''high confidence''''' ''').''' Net CO 2 emission transfers from developing to Developed Countries via global supply chains have decreased between 2006 and 2016. Between 2004 and 2011, CO 2 emissions embodied in trade between developing countries have more than doubled (from 0.47 to 1.1 Gt) with the centre of trade activities shifting from Europe to Asia. {2.3.4, Figure 2.15}

'''Territorial emissions from developing country regions continue to grow, mostly driven by increased consumption and investment, albeit starting from a low base of per-capita emissions and with a lower historic contribution to cumulative emissions than developed countries (''' '''''high confidence''''' ''').''' Average 2019 per-capita CO 2 -FFI emissions in three developing regions, Africa (1.2 tCO 2 ), Asia and Pacific (4.4 tCO 2 ), and Latin America and Caribbean (2.7 tCO 2 ), remained less than half of Developed Countries’ 2019 CO 2 -FFI emissions (9.5 tCO 2 ). In these three developing regions together, CO 2 -FFI emissions grew by 26% between 2010 and 2019 (compared to 260% between 1990 and 2010). In contrast, in Developed Countries emissions contracted by 9.9% between 2010 and 2019 and by 9.6% between 1990 and 2010. Historically, these three developing regions together contributed 28% to cumulative CO 2 -FFI emissions between 1850 and 2019, whereas Developed Countries contributed 57%, and least developed countries contributed 0.4%. (Figure TS.5) {2.2, Figures 2.9 and 2.10}

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'''Figure TS.5 |''' '''Global emissions are distributed unevenly, both in the present day and cumulatively since 1850. Panel (a)''' shows the distribution of regional GHG emissions in tonnes CO 2 -eq per capita by region in 2019. GHG emissions are categorised into: CO 2 fossil fuel and industry (CO 2 -FFI); CO 2 land use, land-use change and forestry (CO 2 -LULUCF); and other GHG emissions (CH 4 , nitrous oxide, F-gas, expressed in CO 2 -eq using GWP100). 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 regional. Percentages refer to overall GHG contributions to total global emissions in 2019. Emissions from international aviation and shipping are not included. '''Panel (b)''' shows the share of historical net CO 2 emissions per region from 1850 to 2019. This includes CO 2 -FFI and CO 2 -LULUCF (GtCO 2 ). Other GHG emissions are not included. Emissions from international aviation and shipping are included. '''Panel (c)''' 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 CO 2 -FFI data, which is assessed in this report up to 2018. Consumption-based emissions are emissions released to the atmosphere in order to generate the goods and services consumed by a certain entity (e.g., region). Emissions from international aviation and shipping are not included. {1.3, Figure 1.2a, 2.2, Figure 2.10}

'''Globally, households with income in the top 10% contribute about 36–45% of global GHG emissions (''' '''''robust evidence, medium agreement''''' ''').''' About two thirds of the top 10% live in Developed Countries and one third in other economies. The lifestyle consumption emissions of the middle income and poorest citizens in emerging economies are between five and 50 times below their counterparts in high-income countries ( ''medium confidence'' ). Increasing inequality within a country can exacerbate dilemmas of redistribution and social cohesion, and affect the willingness of the rich and poor to accept policies to protect the environment, and to accept and afford lifestyle changes that favour mitigation ( ''medium confidence'' ). {2.6.1, 2.6.2, Figure 2.29}

'''Globally, GHG emissions continued to rise across all sectors and subsectors, and most rapidly in transport and industry (''' '''''high confidence''''' ''').''' In 2019, 34% (20 GtCO ''2'' -eq) of global GHG emissions came from the energy sector, 24% (14 GtCO ''2'' -eq) from industry, 22% (13 GtCO ''2'' -eq) from agriculture, forestry and other land use (AFOLU), 15% (8.7 GtCO ''2'' -eq) from transport, and 5.6% (3.3 GtCO ''2'' -eq) from buildings. Once indirect emissions from energy use are considered, the relative shares of industry and buildings emissions rise to 34% and 16%, respectively. Average annual GHG emissions growth during 2010–2019 slowed compared to the previous decade in energy supply (from 2.3% to 1.0%) and industry (from 3.4% to 1.4%, direct emissions only), but remained roughly constant at about 2% yr ''–1'' in the transport sector ( ''high confidence'' ). Emission growth in AFOLU is more uncertain due to the high share of CO ''2'' -LULUCF emissions ( ''medium confidence'' ). (Figure TS.8) {2.2.4, Figure 2.13 and Figures 2.16–2.21}

'''There is a discrepancy, equating to 5.5 GtCO''' 2 '''yr''' –1 ''', between alternative methods of accounting for anthropogenic land CO''' 2 '''fluxes. Accounting for this discrepancy would assist in assessing collective progress in a global stocktake (''' '''''high confidence''''' ''').''' The principal accounting approaches are national GHG inventories (NGHGI) and global modelling [[#footnote-022|11]] approaches. NGHGI, based on IPCC guidelines, consider a much larger area of forest to be under human management than global models. NGHGI consider the fluxes due to human-induced environmental change on this area to be anthropogenic and are thus reported. Global models, in contrast, consider these fluxes to be natural and are excluded from the total reported anthropogenic land CO 2 flux. The accounting method used will affect the assessment of collective progress in a global stocktake ( ''medium confidence'' ) {Cross-Chapter Box 6 in Chapter 7} . In the absence of these adjustments, allowing a like-with-like comparison, collective progress would appear better than it is. {7.2}

'''This accounting discrepancy also applies to Integrated Assessment Models (IAMs), with the consequence that anthropogenic land CO''' 2 '''fluxes reported in IAM pathways cannot be compared directly with those reported in national GHG inventories (''' '''''high confidence''''' ''').''' Methodologies enabling a more like-for-like comparison between models’ and countries’ approaches would support more accurate assessment of the collective progress achieved under the Paris Agreement. {3.4, 7.2.2}

'''Average annual growth in GHG emissions from energy supply decreased from 2.3% for 2000–2009 to 1.0% for 2010–2019 (''' '''''high confidence''''' ''').''' This slowing of growth is attributable to further improvements in energy efficiency and reductions in the carbon intensity of energy supply driven by fuel switching from coal to gas, reduced expansion of coal capacity, particularly in Eastern Asia, and the increased use of renewables ( ''medium confidence'' ). (Figure TS.6) {2.2.4, 2.4.2.1, Figure 2.17}

'''The industry, buildings and transport sectors make up 44% of global GHG emissions, or 66% when the emissions from electricity and heat production are reallocated as''' '''''indirect emissions''''' '''(''' '''''high confidence''''' ''').''' This reallocation makes a substantial difference to overall industry and buildings emissions as shown in Figure TS.6. Industry, buildings, and transport emissions are driven, respectively, by the large rise in demand for basic materials and manufactured products, a global trend of increasing floor space per capita, building energy service use, travel distances, and vehicle size and weight. Between 2010 and 2019, aviation grew particularly fast on average at about 3.3% per annum. Globally, energy efficiency has improved in all three demand sectors, but carbon intensities have not. (Figure TS.6) {2.2.4, Figures 2.18, 2.19 and 2.20}

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'''Figure TS''' '''.6 |''' '''Total anthropogenic direct and indirect GHG emissions for the year 2019 (in GtCO''' 2 '''-eq) by sector and subsector.''' Direct emissions estimates assign emissions to the sector in which they arise (scope 1 reporting). Indirect emissions – as used here – refer to the reallocation of emissions from electricity and heat to the sector of final use (scope 2 reporting). Note that cement refers to process emissions only, as a lack of data prevents the full reallocation of indirect emissions to this sector. More comprehensive conceptualisations of indirect emissions including all products and services (scope 3 reporting) are discussed in [https://www.ipcc.ch/chapters/chapter-2#2.3 Section 2.3] . Emissions are converted into CO ''2'' -equivalents based on global warming potentials with a 100-year time horizon (GWP100) from the IPCC Sixth Assessment Report. Percentages may not add up to 100 across categories due to rounding at the second significant digit. {Figure 2.12, 2.3}

'''Providing access to modern energy services universally would increase global GHG emissions by a few percent at most (''' '''''high confidence''''' ''').''' The additional energy demand needed to support ''decent living standards'' [[#footnote-021|12]] for all is estimated to be well below current average energy consumption ( ''medium evidence'' , ''high agreement'' ). More equitable income distribution could also reduce carbon emissions, but the nature of this relationship can vary by level of income and development ( ''limited evidence'' , ''medium agreement'' ). {2.4.3}

'''Evidence of rapid energy transitions exists in some case studies (''' '''''medium confidence''''' ''').''' Emerging evidence since AR5 on past energy transitions identifies a growing number of cases of accelerated technology diffusion at sub-global scales and describes mechanisms by which future energy transitions may occur more quickly than those in the past. Important drivers include technology transfer and cooperation, international policy and financial support, and harnessing synergies among technologies within a sustainable energy system perspective ( ''medium confidence'' ). A fast global low-carbon energy transition enabled by finance to facilitate low-carbon technology adoption in developing and particularly in least developed countries can facilitate achieving climate stabilisation targets ( ''high confidence'' ). {2.5.2, Table 2.5}

'''Multiple low-carbon technologies have shown rapid progress since AR5 – in cost, performance, and adoption – enhancing the feasibility of rapid energy transitions (''' '''''high confidence''''' ''').''' The rapid deployment and unit cost decrease of modular technologies like solar, wind, and batteries have occurred much faster than anticipated by experts and modelled in previous mitigation scenarios, as shown in Figure TS.7 ( ''high confidence'' ). The political, economic, social, and technical feasibility of solar energy, wind energy and electricity storage technologies has improved dramatically over the past few years. In contrast, the adoption of nuclear energy and CO 2 capture and storage (CCS) in the electricity sector has been slower than the growth rates anticipated in stabilisation scenarios. Emerging evidence since AR5 indicates that small-scale technologies (e.g., solar, batteries) tend to improve faster and be adopted more quickly than large-scale technologies (nuclear, CCS) ( ''medium confidence'' ). (Figure TS.7, Box TS.15) {2.5.3, 2.5.4, Figures 2.22 and 2.23}

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'''Figure TS.7 |''' '''The unit costs of batteries and some forms of renewable energy have fallen significantly, and their adoption continues to increase.''' The '''top panel''' shows global costs per unit of energy (USD per MWh) for some rapidly changing mitigation technologies. Solid blue lines indicate average unit cost in each year. Light blue shaded areas show the range between the 5th and 95th percentiles in each year. 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 EVs). The electricity production share reflects different capacity factors; for example, for the same amount of installed capacity, wind produces about twice as much electricity as solar PV. {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.

'''Robust incentives for investment in innovation, especially incentives reinforced by national policy and international agreements, are central to accelerating low-carbon technological change (''' '''''robust evidence, medium agreement''''' ''').''' Policies have driven innovation, including instruments for technology push (e.g., scientific training, research and development (R&amp;D)) and demand pull (e.g., carbon pricing, adoption subsidies), as well as those promoting knowledge flows and especially technology transfer. The magnitude of the scale-up challenge elevates the importance of rapid technology development and adoption. This includes ensuring participation of developing countries in an enhanced global flow of knowledge, skills, experience, equipment, and technology; which in turn requires strong financial, institutional, and capacity-building support. {16.4, 16.5}

'''Estimates of future CO''' 2 '''emissions from existing fossil fuel infrastructures already exceed remaining cumulative net CO''' 2 '''emissions in pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot (''' '''''high confidence''''' ''').''' Assuming variations in historic patterns of use and decommissioning, estimated future CO 2 emissions from existing fossil fuel infrastructure alone are 660 (460–890) GtCO 2 and from existing and currently planned infrastructure 850 (600–1100) GtCO 2 . This compares to overall cumulative net CO 2 emissions until reaching net zero CO 2 of 510 (330–710) GtCO 2 in pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot, and 890 (640–1160) GtCO 2 in pathways that limit warming to 2°C (&gt;67%) ( ''high confidence'' ). While most future CO 2 emissions from existing and currently planned fossil fuel infrastructure are situated in the power sector, most remaining fossil fuel CO 2 emissions in pathways that limit warming to 2°C (&gt;67%) and below are from non-electric energy – most importantly from the industry and transportation sectors ( ''high confidence'' ). Decommissioning and reduced utilisation of existing fossil fuel installations in the power sector as well as cancellation of new installations are required to align future CO 2 emissions from the power sector with projections in these pathways ( ''high confidence'' ). (Figure TS.8) {2.7.2, 2.7.3, Figure 2.26, Tables 2.6 and 2.7}

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'''Figure TS.''' '''8 |''' '''Future CO''' 2 '''emissions from existing and currently planned fossil fuel infrastructure in the context of the Paris Agreement carbon budgets in GtCO''' 2 '''based on historic patterns of infrastructure lifetimes''' and Future CO 2 emissions estimates of existing infrastructure for the electricity sector as well as all other sectors (industry, transport, buildings, other fossil fuel infrastructures) and of proposed infrastructures for coal power as well as gas and oil power. Grey bars on the right depict the range (5–95th percentile) in overall cumulative net CO 2 emissions until reaching net zero CO 2 in pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot (1.5°C scenarios), and in pathways that limit warming to 2°C (&gt;67%) (2°C scenarios). {Figure 2.26}

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