Editing IPCC:AR6/WGIII/Chapter-3 (section)

== 3.3 Emission Pathways, Including Socio-economic, Carbon Budget and Climate Responses Uncertainties ==

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=== 3.3.1 Socio-economic Drivers of Emissions Scenarios ===

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Greenhouse gas (GHG) emissions mainly originate from the use and transformation of energy, agriculture, land use (change) and industrial activities. The future development of these sources is influenced by trends in socio-economic development, including population, economic activity, technology, politics, lifestyles, and climate policy. Trends for these factors are not independent, and scenarios provide a consistent outlook for these factors together ( [[#3.2|Section 3.2]] ). [[#Marangoni--2017|Marangoni et al. (2017)]] show that in projections, assumptions influencing energy intensity (e.g., structural change, lifestyle and efficiency) and economic growth are the most important determinants of future CO 2 emissions from energy combustion. Other critical factors include technology assumptions, preferences, resource assumptions and policy ( [[#van%20Vuuren--2008|van Vuuren et al. 2008]] ). As many of the factors are represented differently in specific models, the model itself is also an important factor – providing a reason for the importance of model diversity ( [[#Sognnaes--2021|Sognnaes et al. 2021]] ). For land use, [[#Stehfest--2019|Stehfest et al. (2019)]] show that assumptions on population growth are more dominant given that variations in per capita consumption of food are smaller than for energy. Here, we only provide a brief overview of some key drivers. We focus first on so-called reference scenarios (without stringent climate policy) and look at mitigation scenarios in detail later. We use the SSPs to discuss trends in more detail. The SSPs were published in 2017, and by now, some elements will have to be updated ( [[#O’Neill--2020b|O’Neill et al. 2020b]] ). Still, the ranges represent the full literature relatively well.

Historically, population and GDP have been growing over time. Scenario studies agree that further global population growth is likely up to 2050, leading to a range of possible outcomes of around 8.5–11 billion people (Figure 3.9a). After 2050, projections show a much wider range. If fertility drops below replacement levels, a decline in the global population is possible (as illustrated by SSP1 and SSP5). This typically includes scenarios with rapid development and investment in education. However, median projections mostly show a stabilisation of the world population (e.g., SSP2), while high-end projections show a continued growth (e.g., SSP3). The UN Population Prospects include considerably higher values for both the medium projection and the high end of the range than the SSP scenarios ( [[#KC--2017|KC and Lutz 2017]] ; [[#UN--2019|UN 2019]] ). The most recent median UN projection reaches almost 11 billion people in 2100. The key differences are in Africa and China: here, the population projections are strongly influenced by the rate of fertility change (faster drop in SSPs). Underlying these differences, the UN approach is more based on current demographic trends while the SSPs assume a broader range of factors (including education) driving future fertility.

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[[File:a4bb55a425ddb788edb059d090be1575 IPCC_AR6_WGIII_Figure_3_9.png]]

'''Figure 3.9 | Trends in key scenario characteristics and driving forces as included in the SSP scenarios (showing 5–95th percentiles of the reference scenarios as included in the database in grey shading).''' Reference (dotted lines) refers to the UN low-, medium- and high-population scenarios ( [[#UN--2019|UN 2019]] ), the OECD long-term economic growth scenario ( [[#OECD--2021|OECD 2021]] ), the scenarios from the IEA’s World Energy Outlook ( [[#IEA--2019|IEA 2019]] ), and the scenarios in the FAO assessment ( [[#FAO--2018|FAO 2018]] ).

Economic growth is even more uncertain than the population projections (Figure 3.9c). The average growth rate of GDP was about 2.8% per year (constant USD) in the 1990–2019 period ( [[#The%20World%20Bank--2021|The World Bank 2021]] ). In 2020, the COVID-19 crisis resulted in a considerable drop in GDP (estimated around 4–5%) ( [[#IMF--2021|IMF 2021]] ). After a recovery period, most economic projections assume growth rates to converge back to previous projections, although at a lower level ( [[#IMF--2021|IMF 2021]] ; [[#OECD--2021|OECD 2021]] ) (see also Box 3.2). In the long term, assumptions on future growth relate to political stability, the role of the progress of the technology frontier and the degree to which countries can catch up ( [[#Johansson--2013|Johansson et al. 2013]] ). The SSP scenarios cover an extensive range, with low per-capita growth in SSP3 and SSP4 (mostly in developing countries) and rapid growth in SSP1 and SSP5. At the same, however, also scenarios outside the range have some plausibility – including the option of economic decline ( [[#Kallis--2012|Kallis et al. 2012]] ) or much faster economic development ( [[#Christensen--2018|Christensen et al. 2018]] ). The OECD long-term projection is at the global level reasonably consistent with SSP2. Equally important economic parameters include income distribution (inequity) and the type of growth (structural change, i.e., services vs manufacturing industries). Some projections (like SSP1) show a considerable convergence of income levels within and across countries, while in other projections, this does not occur (e.g., SSP3). Most scenarios reflect the suggested inverse relationship between the assumed growth rate for income and population growth (Figure 3.9e). SSP1 and SSP5 represent examples of scenarios with relatively low population increase and relatively high-income increase over the century. SSP3 represents an example of the opposite – while SSP2 and SSP4 are placed more in the middle. Nearly all scenarios assessed here do not account for climate impacts on growth (mostly for methodological reasons). As discussed in [[#3.5|Section 3.5]] these impacts can be considerable. An emerging area of literature emphasises the possibility of stabilisation (or even decline) of income levels in developed countries, arguing that such a trend would be preferred or even needed for environmental reasons ( [[#Anderson--2013|Anderson and Larkin 2013]] ; [[#Hickel--2020|Hickel and Kallis 2020]] ; [[#Kallis--2020|Kallis et al. 2020]] ; [[#Hickel--2021|Hickel et al. 2021]] ; [[#Keyßer--2021|Keyßer and Lenzen 2021]] ) (see also Chapter 5). Such scenarios are not common among IAM outcomes, that are more commonly based on the idea that decarbonisation can be combined with economic growth by a combination of technology, lifestyle and structural economic changes. Still, such scenarios could result in a dramatic reduction of energy and resource consumption.

Scenarios show a range of possible energy projections. In the absence of climate policy, most scenarios project the final energy demand to continue to grow to around 650–800 EJ yr –1 in 2100 (based on the AR6 Scenarios Database, Figure 3.9b). Some projections show a very high energy demand up to 1000 EJ yr –1 (comparable to SSP5). The scenario of the IEA lies within the SSP range but near the SSP1 projection. However, it should be noted that the IEA scenario includes current policies (most reference scenarios do not) and many scenarios published before 2021 did not account for the COVID-19 crisis. Several researchers discuss the possibility of decoupling material and energy demand from economic growth in the literature, mainly in developed countries ( [[#Kemp-Benedict--2018|Kemp-Benedict 2018]] ) (decoupling here refers to either a much slower increase in demand or even a decrease). In the scenario literature, this is reflected by scenarios with very low demand for final energy based on increased energy efficiency and less energy-intensive lifestyles (e.g., SSP1 and the LED scenario) ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#van%20Vuuren--2018|van Vuuren et al. 2018]] ). While these studies show the feasibility of such pathways, their energy efficiency improvement rates are considerably above the historic range of around 2% ( [[#Gütschow--2018|Gütschow et al. 2018]] ; [[#Jeffery--2018|Jeffery et al. 2018]] ; [[#Vrontisi--2018|Vrontisi et al. 2018]] ; [[#Haberl--2020|Haberl et al. 2020]] ; [[#Roelfsema--2020|Roelfsema et al. 2020]] ; [[#Giarola--2021|Giarola et al. 2021]] ; [[#Höhne--2021|Höhne et al. 2021]] ; [[#IEA--2021a|]] [[#IEA--2021|IEA 2021]] a ; [[#Höhne--2021|Höhne et al. 2021]] ; [[#Sognnaes--2021|Sognnaes et al. 2021]] ). These scenarios also show clear differences in food consumption and the amount of land used for agriculture. Food demand in terms of per-capita caloric intake is projected to increase in most scenarios (Figure 3.9d). However, it should be noted that there are large differences in dietary composition across the scenarios (from more meat-intensive in scenarios such as SSP5 to a decrease in meat consumptions in other scenarios such as SSP1). Land-use projections also depend on assumed changes in yield and the population scenarios (Figure 3.9f). Typically, changes in land use are less drastic than some other parameters (in fact, the 5–95th percentile database range is almost stable). Agriculture land is projected to increase in SSP3, SSP2, and SSP4 – it is more-or-less stable in SSP5 and is projected to decline in SSP1.

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<span id="emission-pathways-and-temperature-outcomes"></span>
=== 3.3.2 Emission Pathways and Temperature Outcomes ===

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<span id="overall-mitigation-profiles-and-temperature-consequences"></span>
==== 3.3.2.1 Overall Mitigation Profiles and Temperature Consequences ====

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Figure 3.10 shows the GHG and CO 2 emission trajectories for different temperature categories as defined in [[#3.2|Section 3.2]] (the temperature levels are calculated using simple climate models, consistent with the outcomes of the recent WGI assessment, Cross-Chapter Box 7.1). It should be noted that most scenarios currently in the literature do not account for the impact of COVID-19 (Box 3.2). The higher categories (C6 and C7) mostly included scenarios with no or modest climate policy. Because of the progression of climate policy, it is becoming more common that reference scenarios incorporate implemented climate policies. Modelling studies typically implement current or pledged policies up until 2030 ( [[#Vrontisi--2018|Vrontisi et al. 2018]] ; [[#Roelfsema--2020|Roelfsema et al. 2020]] ; [[#Sognnaes--2021|Sognnaes et al. 2021]] ) with some studies focusing also on the policy development in the long term ( [[#Höhne--2021|Höhne et al. 2021]] ; [[#IEA--2021a|]] [[#IEA--2021|IEA 2021]] a ; [[#Jeffery--2018|Jeffery et al. 2018]] ; [[#Gütschow--2018|Gütschow et al. 2018]] ). Based on the assessment in Chapter 4, reference pathways consistent with the implementation and trend from implemented policies until the end of 2020 are associated with increased GHG emissions from 59 (53–65) GtCO 2 -eq yr –1 in 2019 to 54–60 GtCO 2 -eq yr –1 by 2030 and to 47–67 GtCO 2 -eq yr –1 by 2050 (Figure 3.6). Pathways with these near-term emissions characteristics lead to a median global warming of 2.2°C to 3.5°C by 2100 (see also further in this section). These pathways consider policies at the time that they were developed. A recent model comparison that harmonised socio-economic, technological, and policy assumptions ( [[#Giarola--2021|Giarola et al. 2021]] ) found a 2.2°C–2.9°C median temperature rise in 2100 for current and stated policies, with the results sensitive to the model used and the method of implementing policies ( [[#Sognnaes--2021|Sognnaes et al. 2021]] ). Scenario inference and construction methods using similar policy assumptions lead to a median range of 2.9°C–3.2°C in 2100 for current policies and 2.4°C–2.9°C in 2100 for 2030 pledges ( [[#Höhne--2021|Höhne et al. 2021]] ). The median spread of 1°C across these studies (2.2°C–3.2°C) indicates the deep uncertainties involved with modelling temperature outcomes of 2030 policies through to 2100 ( [[#Höhne--2021|Höhne et al. 2021]] ).

The lower categories include increasingly stringent assumed climate policies. For all scenario categories, except the highest category, emissions peak in the 21st century. For the lowest categories, the emissions peak is mostly before 2030. In fact, for scenarios in the category that avoids temperature overshoot for the 1.5°C scenario (C1 category), GHG emissions are reduced already to almost zero around the middle of the century. Typically, CO 2 emissions reach net zero about 10 to 40 years before total GHG emissions reach net zero. The main reason is that scenarios reduce non-CO 2 greenhouse gas emissions less than CO 2 due to a limited mitigation potential ( [[#3.3.2.2|Section 3.3.2.2]] ). Figure 3.10 also shows that many scenarios in the literature with a temperature outcome below 2°C show net negative emissions. There are, however, also exceptions in which more immediate emission reductions limits the need for CDR. The IMPs illustrate alternative pathways to reach the C1–C3 temperature levels.

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[[File:8eb0e7468597cfb14004b5f3f327efeb IPCC_AR6_WGIII_Figure_3_10.png]]

'''Figure 3.10 | Total emissions profiles in the scenarios based on climate category for GHGs (AR6''' '''GWP-100''' ''') and CO''' 2. The Illustrative mitigation pathways (IMPs) are also indicated.

Figure 3.11 shows the possible consequences of the different scenario categories for global mean temperature calculated using a reduced complexity model (RCM) calibrated to the IPCC AR6 WGI assessment (see Annex III.II.2.5 of this report and Cross-Chapter Box 7.1 in AR6 WGI report). For the C5–C7 categories (containing most of the reference and current policy scenarios), the global mean temperature is expected to increase throughout the century (and further increase will happen after 2100 for C6 and C7). While warming would ''more likely than not'' be in the range from 2.2°C to 3.5°C, warming up to 5°C cannot be excluded. The highest emissions scenarios in the literature combine assumptions about rapid long-term economic growth and pervasive climate policy failures, leading to a reversal of some recent trends (Box 3.3). For the categories C1–C4, a peak in global mean temperature is reached mid-century for most scenarios in the database, followed by a small (C3/C4) or more considerable decline (C1/C2). There is a clear distinction between the scenarios with no or limited overshoot (typically &lt;0.1°C, C1) compared to those with high overshoot (C2): in emissions, the C1 category is characterised by steep early reductions and a relatively small contribution of net negative emissions (like ''IMP-LD'' and ''IMP-Ren'' ) (Figure 3.10). In addition to the temperature caused by the range of scenarios in each category (main panel), climate uncertainties also contribute to a range of temperature outcomes (including uncertainties regarding the carbon cycle, climate sensitivity, and the rate of change, see AR6 WGI). The bars on the right of Figure 3.11 show the uncertainty range for each category (combining scenario and climate uncertainty). While the C1 category ''more likely than not'' limits warming to 1.5°C (&gt;50%) by the end of the century, even with such a scenario, warming above 2°C cannot be excluded (95th percentile). The uncertainty range for the highest emission categories (C7) implies that these scenarios could lead to a warming above 6°C.

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[[File:ce7bf6b11a1edb5ff7bd2a93970cc700 IPCC_AR6_WGIII_Figure_3_11.png]]

'''Figure 3.11 | Global mean temperature outcome of the ensemble of scenarios included in the climate categories C1–C8 (based on a reduced complexity model – RCM – calibrated to the WGI assessment, both in terms of future and historic warming).''' The left panel shows the ranges of scenario uncertainty (shaded area) with the P50 RCM probability (line). The right panel shows the P5 to P95 range of combined RCM climate uncertainty (C1–C8 is explained in Table 3.1) and scenario uncertainty, and the P50 (line).

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<span id="the-role-of-carbon-dioxide-and-other-greenhouse-gases"></span>
==== 3.3.2.2 The Role of Carbon Dioxide and Other Greenhouse Gases ====

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The trajectory of future CO 2 emissions plays a critical role in mitigation, given CO 2 long-term impact and dominance in total greenhouse gas forcing. As shown in Figure 3.12, CO 2 dominates total greenhouse gas emissions in the high-emissions scenarios but is also reduced most, going from scenarios in the highest to lower categories. In C4 and below, most scenarios exhibit net negative CO 2 emissions in the second half of the century compensating for some of the residual emissions of non-CO 2 gases as well as reducing overall warming from an intermediate peak. Still, early emission reductions and further reductions in non-CO 2 emissions can also lead to scenarios without net negative emissions in 2100, even in C1 and C3 (shown for the 85–95th percentile). In C1, avoidance of significant overshoot implies that immediate gross reductions are more relevant than long-term net negative emissions (explaining the lower number than in C2) but carbon dioxide removal (CDR) is still playing a role in compensating for remaining positive emissions in hard-to-abate sectors.

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[[File:d1dd6a4272e18776d6d7b9812527cc38 IPCC_AR6_WGIII_Figure_3_12.png]]

'''Figure 3.12 |''' '''(a) The role of CO''' 2 '''and other greenhouse gases.''' Emission in CO 2 -eq in 2100 (using AR6 GWP-100) (other = halogenated gases) and '''(b)''' cumulative CO 2 emissions in the 2020–2100 period. Panels '''(c)''' and '''(d)''' show the development of CH 4 and N 2 O emissions over time. Energy emissions include the contribution of BECCS. For both energy and AFOLU sectors, the positive and negative values represent the cumulated annual balances. In both panels, the three bars per scenario category represent the lowest 5–15th percentile, the average value and the highest 5–15th percentile. These illustrate the range of scenarios in each category. The definition of C1–C7 can be found in Table 3.1.

CH 4 and N 2 O emissions are also reduced from C7 to C1, but this mostly occurs between C7 and C5. The main reason is the characteristics of abatement potential: technical measures can significantly reduce CH 4 and N 2 O emissions at relatively low costs to about 50% of the current levels (e.g., by reducing CH 4 leaks from fossil fuel production and transport, reducing landfill emissions gazing, land management and introducing measures related to manure management, see also [[IPCC:Wg3:Chapter:Chapter-7|Chapter 7]] and 11). However, technical potential estimates become exhausted even if the stringency of mitigation is increased ( [[#Harmsen--2019a|Harmsen et al. 2019a]] ,b; [[#Höglund-Isaksson--2020|Höglund-Isaksson et al. 2020]] ). Therefore, further reduction may come from changes in activity levels, such as switching to a less meat-intensive diet, therefore reducing livestock ( [[#Stehfest--2009|Stehfest et al. 2009]] ; [[#Willett--2019|Willett et al. 2019]] ; [[#Ivanova--2020|Ivanova et al. 2020]] ) (Chapter 7). Other non-CO 2 GHG emissions (halogenated gases) are reduced to low levels for scenarios below 2.5°C.

Short-lived climate forcers (SLCFs) also play an important role in climate change, certainly for short-term changes (AR6 WGI, Figure SPM.2) ( [[#Shindell--2012|Shindell et al. 2012]] ). These forcers consist of (i) substances contributing to warming, such as methane, black carbon and tropospheric ozone, and (ii) substances contributing to cooling (other aerosols, such as related to sulphur emissions). Most SLCFs are also air pollutants, and reducing their emissions provides additional co-benefits ( [[#Shindell--2017a|Shindell et al. 2017a]] ,b; [[#Hanaoka--2020|Hanaoka and Masui 2020]] ). In the case of the first group, emission reduction thus leads to both air pollution and climate benefits. For the second, group there is a possible trade-off ( [[#Shindell--2019|Shindell and Smith 2019]] ; [[#Lund--2020|Lund et al. 2020]] ). As aerosol emissions are mostly associated with fossil fuel combustion, the benefits of reducing CO 2 could, in the short term, be reduced as a result of lower aerosol cooling. There has been an active discussion on the exact climate contribution of SLCF-focused policies in the literature. This discussion partly emerged from different assumptions on possible reductions in the absence of ambitious climate policy and the uncertain global climate benefit from aerosol (black carbon) ( [[#Rogelj--2014|Rogelj et al. 2014]] ). The latter is now assessed to be smaller than originally thought ( [[#Takemura--2019|Takemura and Suzuki 2019]] ; [[#Smith--2020b|Smith et al. 2020b]] ) (see also AR6 WGI [[IPCC:Wg3:Chapter:Chapter-6#6.4|Section 6.4]] ). Reducing SLCF emissions is critical to meet long-term climate goals and might help reduce the rate of climate change in the short term. Deep SLCF emission reductions also increase the remaining carbon budget for a specific temperature goal ( [[#Rogelj--2015a|Rogelj et al. 2015a]] ; [[#Reisinger--2021|Reisinger et al. 2021]] ) (Box 3.4). A more detailed discussion can be found in AR6 WGI Chapters 5 and 6.

For accounting of emissions and the substitution of different gases as part of a mitigation strategy, typically, emission metrics are used to compare the climate impact of different gases. Most policies currently use Global Warming Potentials (GWPs) with a 100-year time horizon as this is also mandated for emissions reporting in the Paris Rulebook (for a wider discussion of GHG metrics, see Box 2.1 in [[IPCC:Wg3:Chapter:Chapter-2|Chapter 2]] of this report, and AR6 WGI, Chapter 7, [[IPCC:Wg3:Chapter:Chapter-7#7.6|Section 7.6]] ). Alternative metrics have also been proposed, such as those using a shorter or longer time horizon, or those that focus directly on the consequences of reaching a certain temperature target (Global Temperature Change Potential – GTP), allowing a more direct comparison with cumulative CO 2 emissions ( [[#Allen--2016|Allen et al. 2016]] ; [[#Lynch--2020|Lynch et al. 2020]] ) or focusing on damages (Global Damage Potential) (an overview is given in Chapter 2, and Cross-Chapter Box 3 in Chapter 3). Depending on the metric, the value attributed to reducing short-lived forcers such as methane can be lower in the near term (e.g., in the case of GTP) or higher (GWP with a short reference period). For most metrics, however, the impact on mitigation strategies is relatively small, among others, due to the marginal abatement cost curve of methane (low costs for low-to-medium mitigation levels; expensive for high levels). The timing of reductions across different gases impacts warming and the co-benefits ( [[#Harmsen--2016|Harmsen et al. 2016]] ; [[#Cain--2019|Cain et al. 2019]] ). Nearly all scenarios in the literature use GWP-100 in cost-optimisation, reflecting the existing policy approach; the use of GWP-100 deviates from cost-optimal mitigation pathways by at most a few percent for temperature goals that limit warming to 2°C (&gt;67%) or lower (Box 2.1).

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<span id="cumulative-co-2-emissions-and-temperature-goals"></span>
===== Cumulative CO 2 emissions and temperature goals =====

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The dominating role of CO 2 and its long lifetime in the atmosphere and some critical characteristics of the Earth System implies that there is a strong relationship between cumulative CO 2 emissions and temperature outcomes (Allen et al. 2009; [[#Matthews--2009|Matthews et al. 2009]] ; [[#Meinshausen--2009|Meinshausen et al. 2009]] ; [[#MacDougall--2015|MacDougall and Friedlingstein 2015]] ). This is illustrated in Figure 3.13, which plots the cumulative CO 2 emissions against the projected outcome for global mean temperature, both until peak temperature and through to end of century (or 2100). The deviations from a linear relationship in Figure 3.13 are mostly caused by different non-CO 2 emission and forcing levels (see also [[#Rogelj--2015b|Rogelj et al. 2015b]] ). This means that reducing non-CO 2 emissions can play an important role in limiting peak warming: the smaller the residual non-CO 2 warming, the larger the carbon budget. This impact on carbon budgets can be substantial for stringent warming limits. For 1.5°C pathways, variations in non-CO 2 warming across different emission scenarios have been found to vary the remaining carbon budget by approximately 220 GtCO 2 (AR6 WGI Chapter 5, [[IPCC:Wg3:Chapter:Chapter-5#5.5.2|Section 5.5.2]] .2). In addition to reaching net zero CO 2 emissions, a strong reduction in methane emissions is the most critical component in non-CO 2 mitigation to keep the Paris climate goals in reach ( [[#Collins--2018|Collins et al. 2018]] ; [[#van%20Vuuren--2018|van Vuuren et al. 2018]] ) (see also AR6 WGI, Chapters 5, 6 and 7). It should be noted that the temperature categories (C1–C7) generally aligned with the horizontal axis, except for the end-of-century values for C1 and C2 that coincide.

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[[File:097905b7b2683f470fa3f94df52d7591 IPCC_AR6_WGIII_Figure_3_13.png]]

'''Figure 3.13 | The near-linear relationship between cumulative CO''' 2 '''emissions and temperature.''' The left panel shows cumulative emissions until net zero emission is reached. The right panel shows cumulative emissions until the end of the century, plotted against peak and end-of-century temperature, respectively. Both are shown as a function of non-CO 2 forcing and cumulative net negative CO 2 emissions. Position temperature categories (circles) and IPs are also indicated, including two 2°C sensitivity cases for ''Neg'' (Neg-2.0) and ''Ren'' (Ren-2.0).

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<span id="the-timing-of-net-zero-emissions"></span>
==== 3.3.2.3 The Timing of Net Zero Emissions ====

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In addition to the constraints on change in global mean temperature, the Paris Agreement also calls for reaching a balance of sources and sinks of GHG emissions (Art. 4). Different interpretations of the concept related to balance have been published ( [[#Rogelj--2015c|Rogelj et al. 2015c]] ; [[#Fuglestvedt--2018|Fuglestvedt et al. 2018]] ). Key concepts include that of net zero CO 2 emissions (anthropogenic CO 2 sources and sinks equal zero) and net zero greenhouse gas emissions (see Annex I: Glossary, and Box 3.3). The same notion can be used for all GHG emissions, but here ranges also depend on the use of equivalence metrics (Box 2.1). Moreover, it should be noted that while reaching net zero CO 2 emissions typically coincides with the peak in temperature increase; net zero GHG emissions (based on GWP-100) imply a decrease in global temperature ( [[#Riahi--2021|Riahi et al. 2021]] ) and net zero GHG emissions typically require negative CO 2 emissions to compensate for the remaining emissions from other GHGs. Many countries have started to formulate climate policy in the year that net zero emissions (either CO 2 or all greenhouse gases) are reached – although, at the moment, formulations are often still vague ( [[#Rogelj--2021|Rogelj et al. 2021]] ). There has been increased attention on the timing of net zero emissions in the scientific literature and ways to achieve it.

Figure 3.14 shows that there is a relationship between the temperature target, the cumulative CO 2 emissions budget, and the net zero year for CO 2 emissions (panel a) and the sum of greenhouse gases (panel b) for the scenarios published in the literature. In other words, the temperature targets from the Paris Agreement can, to some degree, be translated into a net-zero emission year (Tanaka and O’Neill 2018). There is, however, a considerable spread. In addition to the factors influencing the emission budget (AR6 WGI and [[#3.3.2.2|Section 3.3.2.2]] ), this is influenced by the emission trajectory until net zero is reached, decisions related to temperature overshoot and non-CO 2 emissions (especially for the moment CO 2 reaches net zero emissions). Scenarios with limited or no net negative emissions and rapid near-term emission reductions can allow small positive emissions (e.g., in hard-to-abate-sectors). They may therefore have a later year that net zero CO 2 emissions are achieved. High emissions in the short term, in contrast, require an early net zero year.

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[[File:2b9f3422963bd2eb571a5eb82c56550b IPCC_AR6_WGIII_Figure_3_14.png]]

'''Figure 3.14 | Net zero year for CO''' 2 '''and all GHGs (based on AR6''' '''GWP100''' ''') as a function of remaining carbon budget and temperature outcomes (note that scenarios that stabilise (near) zero are also included in determining the net zero year).'''

For the scenarios in the C1 category (limit warming to 1.5°C (&gt;50% with no or limited overshoot, the net zero year for CO 2 emissions is typically around 2035–2070. For scenarios in C3 (limiting warming to 2°C (&gt;67%)), CO 2 emissions reach net zero around after 2050. Similarly, also the years for net zero GHG emissions can be calculated (see Fig 3.14b. The GHG net zero emissions year is typically around 10–40 years later than the carbon neutrality. Residual non-CO 2 emissions at the time of reaching net zero CO 2 range between 5–11 GtCO 2 -eq in pathways that limit warming to 2°C (&gt;67%) or lower. In pathways limiting warming to 2°C (&gt;67%), methane is reduced by around 19% (3–46%) in 2030 and 46% (29–64%) in 2050, and in pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot by around 34% (21–57%) in 2030 and a similar 51% (35–70%) in 2050. Emissions-reduction potentials assumed in the pathways become largely exhausted when limiting warming to 2°C (&gt;50%). N 2 O emissions are reduced too, but similar to CH 4 , emission reductions saturate for stringent climate goals. In the mitigation pathways, the emissions of cooling aerosols are reduced due to reduced use of fossil fuels. The overall impact on non-CO 2 -related warming combines these factors.

In cost-optimal scenarios, regions will mostly achieve net zero emissions as a function of options for emission reduction, CDR, and expected baseline emission growth ( [[#van%20Soest--2021b|van Soest et al. 2021b]] ). This typically implies relatively early net zero emission years in scenarios for the Latin America region and relatively late net zero years for Asia and Africa (and average values for OECD countries). However, an allocation based on equity principles (such as responsibility, capability and equality) might result in different net zero years, based on the principles applied – with often earlier net zero years for the OECD ( [[#Fyson--2020|Fyson et al. 2020]] ; [[#van%20Soest--2021b|van Soest et al. 2021b]] ). Therefore, the emission trajectory until net zero emissions is a critical determinant of future warming ( [[#3.5|Section 3.5]] ). The more CO 2 is emitted until 2030, the less CO 2 can be emitted after that to stay below a warming limit ( [[#Riahi--2015|Riahi et al. 2015]] ). As discussed before, also non-CO 2 forcing plays a key role in the short term.

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==== 3.3.2.4 Mitigation Strategies ====

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Detailed sectoral implications are discussed in [[#3.4|Section 3.4]] and Chapters 5–11 (see also Table 3.3). The stringency of climate policy has clear implications for mitigation action (Figure 3.15). There are a number of important commonalities of pathways limiting warming to 2°C (&gt;67%) or lower: for instance, they all rely on significant improvement of energy efficiency, rapid decarbonisation of supply and, many of them, CDR (in energy supply or AFOLU), either in terms of net negative emissions or to compensate residual emissions. Still, there are also important differences and the (IMPs) show how different choices can steer the system into alternative directions with different combinations of response options. For decarbonisation of energy supply many options exist, including CCS, nuclear power, and renewables (Chapter 6). In the majority of the scenarios reaching low GHG targets, a considerable amount of CCS is applied (Figure 3.15d). The share of renewables is around 30–70% in the scenarios that limit warming to 2°C (&gt;67%) and clearly above 40% for scenarios that limit warming 1.5°C (&gt;50%) (panel c). Scenarios have been published with 100% renewable energy systems even at a global scale, partly reflecting the rapid progress made for these technologies in the last decade ( [[#Creutzig--2017|Creutzig et al. 2017]] ; [[#Jacobson--2018|Jacobson et al. 2018]] ; [[#Breyer--2020|Breyer and Jefferson 2020]] ). These scenarios do not show in the graph due to a lack of information from non-energy sources. There is a debate in the literature on whether it is possible to achieve a 100% renewable energy system by 2050 ( [[#Brook--2018|Brook et al. 2018]] ). This critically depends on assumptions made on future system integration, system flexibility, storage options, consequences for material demand and the ability to supply high-temperature functions and specific mobility functions with renewable energy. The range of studies published showing 100% renewable energy systems show that it is possible to design such systems in the context of energy system models ( [[#Hong--2014a|Hong et al. 2014a]] ,b; [[#Lehtveer--2015a|Lehtveer and Hedenus 2015a]] ,b; [[#Pfenninger--2015|Pfenninger and Keirstead 2015]] ; [[#Sepulveda--2018|Sepulveda et al. 2018]] ; [[#Zappa--2019|Zappa et al. 2019]] ; [[#IEA--2021b|]] [[#IEA--2021|IEA 2021]] b ) (see also Box 6.6 on 100% renewables in net zero CO 2 systems). Panels e and f, finally, show the contribution of CDR – both in terms of net negative emissions and gross CDR. The contribution of total CDR obviously exceeds the net negative emissions. It should be noted that while a majority of scenarios rely on net negative emissions to reach stringent mitigation goals – this is not the case for all of them.

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[[File:b29202f6f1bb94302ce2f6aa8c80b128 IPCC_AR6_WGIII_Figure_3_15.png]]

'''Figure 3.15 | Characteristics of scenarios as a function of the remaining carbon budget (mean decarbonisation rate is shown as the average reduction in the period 2010–2050 divided by 2010 emissions).''' The categories C1–C7 are explained in Table 3.1.

The spread shown in Figure 3.15 implies different mitigation strategies that could all lead to emissions levels consistent with the Paris Agreement (and reach zero emissions). The IMPs illustrate some options for different decarbonisation pathways with heavy reliance on renewables ( ''IMP-Ren'' ), strong emphasis on energy-demand reductions ( ''IMP-LD'' ), widespread deployment of CDR methods coupled with CCS (BECCS and DACCS) ( ''IMP-Neg'' ), mitigation in the context of sustainable development ( ''IMP-SP'' ) (Figure 3.16). For example, in some scenarios, a small part of the energy system is still based on fossil fuels in 2100 ( ''IMP-Neg'' ), while in others, fossil fuels are almost or completely phased out ( ''IMP-Ren'' ). Nevertheless, in all scenarios, fossil fuel use is greatly reduced and unabated coal use is completely phased out by 2050. Also, nuclear power can be part of a mitigation strategy (however, the literature only includes some scenarios with high-nuclear contributions, such as [[#Berger--2017|Berger et al. 2017]] ). This is explored further in [[#3.5|Section 3.5]] . The different strategies are also clearly apparent in the way they scenarios reach net zero emissions. While ''IMP-GS'' and ''IMP-Neg'' rely significantly on BECCS and DACCS, their use is far more restricted in the other IMPs. Consistently, in these IMPs residual emissions are also significantly lower.

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[[File:f32648216ceab34d32ed0ce0e4820373 IPCC_AR6_WGIII_Figure_3_16.png]]

'''Figure 3.16 | Primary energy use and net emissions at net zero year for the different IMPS.''' Source: AR6 Scenarios Database.

Mitigation pathways also have a regional dimension. In 2010, about 40% of emissions originated from the Developed Countries and Eastern Europe and West Central Asia regions. According to the projections shown in Figure 3.17, the share of the latter regions will further increase to about 70% by 2050. In the scenarios in the literature, emissions are typically almost equally reduced across the regions.

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[[File:9cb143a622c7e8ef7e162f886b473979 IPCC_AR6_WGIII_Figure_3_17.png]]

'''Figure 3.17''' 11 '''| Emissions by region (including 5–95th percentile range).''' Source: AR6 Scenarios Database.

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=== Box 3.2 | Impact of COVID-19 on Long-term Emissions ===

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The reduction in CO 2 emissions of the COVID-19 pandemic in 2020 was estimated to be about 6% (Section 4.2.2.4 and Table 4.SM.2) lower than 2019 levels ( [[#Forster--2020|Forster et al. 2020]] ; [[#Friedlingstein--2020|Friedlingstein et al. 2020]] ; [[#Liu--2020c|Liu et al. 2020c]] ; [[#BP--2021|BP 2021]] ; [[#Crippa--2021|Crippa et al. 2021]] ; [[#IEA--2021|IEA 2021]] ; [[#Le%20Quéré--2021|Le Quéré et al. 2021]] ). Near-real-time monitoring estimates show a rebound in emissions levels, meaning 2021 emissions levels are expected to be higher than 2020 ( [[#Le%20Quéré--2021|Le Quéré et al. 2021]] ). The longer-term effects are uncertain but so far do not indicate a clear structural change for climate policy related to the pandemic. The increase in renewable shares in 2020 could stimulate a further transition, but slow economic growth can also slow down (renewable) energy investments. Also, lifestyle changes during the crisis can still develop in different directions (working from home, but maybe also living further away from work). Without a major intervention, most long-term scenarios project that emissions will start to follow a similar pathway as earlier projections (although at a reduced level) ( [[#IEA--2020b|IEA 2020b]] ; [[#Kikstra--2021a|Kikstra et al. 2021a]] ; [[#Rochedo--2021|Rochedo et al. 2021]] ). If emissions reductions are limited to only a short time, the adjustment of pathways will lead to negligible outcomes in the order of 0.01K ( [[#Forster--2020|Forster et al. 2020]] ; [[#Jones--2021|Jones et al. 2021]] ). At the same time, however, the large amount of investments pledged in the recovery packages could provide a unique opportunity to determine the long-term development of infrastructure, energy systems and land use ( [[#Andrijevic--2020b|Andrijevic et al. 2020b]] ; [[#Hepburn--2020|Hepburn et al. 2020]] ; [[#Pianta--2021|Pianta et al. 2021]] ). Near-term alternative recovery pathways have been shown to have the potential to influence carbon-price pathways, and energy investments and electrification requirements under stringent mitigation targets ( [[#Bertram--2021|Bertram et al. 2021]] ; [[#Kikstra--2021a|Kikstra et al. 2021a]] ; [[#Pollitt--2021|Pollitt et al. 2021]] ; [[#Rochedo--2021|Rochedo et al. 2021]] ; Shan et al. 202). Most studies suggest a noticeable reduction in 2030 emissions. However, much further reductions would be needed to reach the emission levels consistent with mitigation scenarios that limit warming to 2°C (&gt;67%) or lower (see Chapter 4). At the moment, the share of investments in greenhouse gas reduction is relatively small in most recovery packages, and no structural shifts for climate policies are observed linked to the pandemic. Finally, most of the scenarios analysed in this Chapter do not include the 2020 emissions reduction related to the COVID-19 pandemic. The effect of the pandemic on the pathways will likely be very small. The assessment of climate mitigation pathways in this chapter should be interpreted as being almost exclusively based on the assumption of a fast recovery with limited persistent effects on emissions or structural changes.

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=== Box 3.3 | The Likelihood of High-end Emissions Scenarios ===

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At the time the Representative Concentration Pathways (RCPs) were published, they included three scenarios that could represent emission developments in the absence of climate policy: RCP4.5, RCP6 and RCP8.5, described as, respectively, low, medium and high-end scenarios in the absence of strong climate policy ( [[#van%20Vuuren--2011|van Vuuren et al. 2011]] ). RCP8.5 was described as representative of the top 5% scenarios in the literature. The SSPs-based set of scenarios covered the RCP forcing levels, adding a new low scenario (at 1.9 W m –2 ). [[#Hausfather--2020|Hausfather and Peters (2020)]] pointed out that since 2011, the rapid development of renewable energy technologies and emerging climate policy have made it considerably less likely that emissions could end up as high as RCP8.5. Still, emission trends in developing countries track RCP8.5 [[#Pedersen--2020|Pedersen et al. (2020)]] , and high land-use emissions could imply that emissions would continue to do so in the future, even at the global scale (Schwalm et al. 2020). Other factors resulting in high emissions include higher population or economic growth as included in the SSPs ( [[#3.3.1|Section 3.3.1]] ) or rapid development of new energy services. Climate projections of RCP8.5 can also result from strong feedbacks of climate change on (natural) emission sources and high climate sensitivity (AR6 WGI Chapter 7), and therefore their median climate impacts might also materialise while following a lower emission path (e.g., Hausfather and Betts 2020). The discussion also relates to a more fundamental discussion on assigning likelihoods to scenarios, which is extremely difficult given the deep uncertainty and direct relationship with human choice. However, it would help to appreciate certain projections (e.g., Ho et al. 2019). All in all, this means that high-end scenarios have become considerably less likely since AR5 but cannot be ruled out. It is important to realise that RCP8.5 and SSP5-8.5 do not represent a typical ‘business-as-usual’ projection but are only useful as high-end, high-risk scenarios. Reference emission scenarios (without additional climate policy) typically end up in the C5–C7 categories included in this assessment.

[[File:fe970aa2d2acab12da229b09df2aba98 IPCC_AR6_WGIII_Box_3_4_Figure_1.png]]

'''Box 3.4, Figure 1 | Cumulative CO 2 emissions from AR6 scenario categories (coloured dots), adjusted for distinct 0.''' '''1°C warming levels (black bars) in comparison to the WGI remaining carbon budgets (grey bars).''' The cumulative carbon emissions for the AR6 scenarios are shown for the median peak warming '''(a)''' , the 33rd-percentile peak warming '''(b)''' and the upper 67th-percentile peak warming '''(c)''' calculated with the WGI-calibrated emulator MAGICC7 (IPCC AR6 WGI, Cross-Chapter Box 7.1). The adjustment to the nearest 0.1°C intervals is made using AR6 WGI TCRE (at the relevant percentile, e.g., the 67th-percentile TCRE is used to adjust the 67th-percentile peak warming), with the 5–95% range of adjusted scenarios provided by the black bar. The AR6 WGI remaining carbon budget is shown, including the WGI estimate of at least a ±220 GtCO 2 uncertainty due to non-CO 2 emissions variations across scenarios (grey bars). For median peak warming (panel a) projections below 2°C relative to 1850–1900, the AR6 WGIII assessment of cumulative carbon emissions tends to be slightly smaller than the remaining carbon budgets provided by WGI but well within the uncertainties. Note that only a few scenarios in WGIII limit warming to below 1.5°C with a 50% chance, thus statistics for that specific threshold have low confidence.

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<span id="box-3.4-consistency-of-remaining-carbon-budgets-in-the-wgi-assessment-and-cumulative-co-2-emissions-in-wgiii-mitigation-pathways"></span>

=== Box 3.4 | Consistency of Remaining Carbon Budgets in the WGI Assessment and Cumulative CO 2 Emissions in WGIII Mitigation Pathways ===

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Introduction

The WGI assessment has shown that the increase in global mean temperature has a near-linear relationship with cumulative CO 2 emissions (Chapter 5, [[IPCC:Wg3:Chapter:Chapter-5#5.5|Section 5.5]] , Box 5.3 of AR6 WGI report). Consistently, WGI has confirmed that net zero CO 2 emissions are required to halt CO 2 -induced warming. This permits the estimation of carbon budgets consistent with specific temperature goals. In Chapter 3, we present the temperature outcomes and cumulative CO 2 emissions associated with different warming levels for around 1200 scenarios published in the literature and which were classified according to different warming levels ( [[#3.2|Section 3.2]] and Annex III.II.3.2). In this box, we discuss the consistency of the assessments presented here and in IPCC AR6 WGI. The box summarises how the remaining carbon budgets assessed by AR6 WGI relate to the remaining cumulative CO 2 emissions until the time of net zero CO 2 emissions in mitigation pathways (Tables 3.2 and SPM.1) assessed by AR6 WGIII.

In its assessment, AR6 WGI uses a framework in which the various components of the remaining carbon budget are informed by various lines of evidence and assessed climate system characteristics. The AR6 WGIII, instead, uses around 1200 emission scenarios with estimated warming levels that cover the scenario range presented in AR6 WGI but also contain many more intermediate projections with varying emission profiles and a combination of CO 2 emissions and other greenhouse gases. In order to assess their climate outcomes, climate model emulators are used. The emulators are reduced complexity climate models that are provided by AR6 WGI, and which are calibrated to the AR6 WGI assessment of future warming for various purposes (a detailed description of the use of climate model emulators in the AR6 WGI and WGIII assessments can be found in Cross-Chapter Box 7.1 in the AR6 WGI report, with the connection of WGI and WGIII discussed in Annex III.2.5.1).

'''Remaining carbon budgets estimated by AR6 WGI'''

The AR6 WGI estimated the remaining carbon budgets from their assessment of (i) the transient climate response to cumulative emissions of carbon dioxide (TCRE), and estimates of (ii) the historical human-induced warming, (iii) the temperature change after reaching net zero CO 2 emissions, (iv) the contribution of future non-CO 2 warming (derived from the emissions scenarios assessed in the Special Report on 1.5°C Warming using WGI-calibrated emulators), and (v) the Earth System feedbacks (AR6 WGI Chapter 5.5, Box 5.2). For a given warming level, AR6 WGI assessed the remaining carbon budget from the beginning of 2020 onwards. These are 650/500/400 GtCO 2 for limiting warming to 1.5°C with 33%/50%/ 67% chance and 1350/1150 GtCO 2 for limiting warming to 2°C with 50%/67% chance. The estimates are subject to considerable uncertainty related to historical warming, future non-CO 2 forcing, and poorly quantified climate feedbacks. For instance, variation in non-CO 2 emissions across scenarios are estimated to either increase or decrease the remaining carbon budget estimates by 220 GtCO 2 . The estimates of the remaining carbon budget assume that non-CO 2 emissions are reduced consistently with the tight temperature targets for which the budgets are estimated.

Cumulative CO 2 emissions until net zero estimated by AR6 WGIII

The AR6 WGIII provides estimates of cumulative net CO 2 emissions (from 2020 inclusive) until the time of reaching net zero CO 2 emissions (henceforth called ‘peak cumulative CO 2 emissions’) and until the end of the century for eight temperature classes that span a range of warming levels. The numbers can be found in Table 3.2 (330–710 GtCO 2 for C1; 530–930 for C2; and 640–1160 for C3).

Comparing the AR6 WGI remaining carbon budgets and remaining cumulative CO 2 emissions of the AR6 WGIII scenarios

A comparison between AR6 WGI and WGIII findings requires recognising that, unlike in WGI, cumulative emissions in WGIII are not provided for a specific peak-warming threshold or level but are instead provided for a set of scenarios in a category, representing a specific range of peak-temperature outcomes (for instance the C4 category contains scenarios with a median peak warming anywhere between approximately 1.8°C and up to 2°C). When accounting for this difference, the AR6 WGI and WGIII findings are very consistent for temperature levels below 2°C. Figure 1 compares the peak temperatures and associated cumulative CO 2 emissions (i.e., peak cumulative CO 2 emissions) for the WGIII scenarios to the remaining carbon budgets assessed by WGI. This shows only minor differences between the WGI and WGIII approaches.

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[[File:3cf307f6bcda7d4aa1cb8cce69661ddd IPCC_AR6_WGIII_Box_3_4_Figure_2.png]]

'''Box 3.4, Figure 2 | (a) Differences in regressions of the relationship between peak surface temperature and associated cumulative CO 2e missions from 2020 derived from scenarios of eight integrated assessment model frameworks.''' The coloured lines show the regression at median for scenarios of the eight modelling frameworks, each with more than 20 scenarios in the database and a detailed land-use representation. The red dotted lines indicate the non-CO 2 uncertainty range of AR6 WGI [[IPCC:Wg3:Chapter:Chapter-5|Chapter 5]] (±220 GtCO 2 ), here visualised around the median of the eight model framework lines. Carbon budgets from 2020 until 1.5°C (0.43K above 2010–2019 levels) and 2.0°C (0.93K above 2010–2019 levels) are shown for minimum and maximum model estimates at the median, rounded to the nearest 10 GtCO 2 . Panel '''(b)''' shows the relationship between the estimated non-CO 2 warming in mitigation scenarios that reach net zero and the associated peak surface temperature outcomes. The coloured lines show the regression at median for scenarios of the eight modelling frameworks with more than 20 scenarios in the database and a detailed land-use representation. The black dashed line indicates the non-CO 2 relationship based on the scenarios and climate emulator setup as was assessed in AR6 WGI Chapter 5.

After correcting for the categorisation, some (small) differences between the AR6 WGI and WGIII numbers arise from remaining differences between the outcomes of the climate emulators and their set-up (IPCC AR6 WGI Cross-Chapter Box 7.1) and the differences in the underlying scenarios. Moreover, the WGI assessment estimated the non-CO 2 warming at the time of net zero CO 2 emissions based on a relationship derived from the SR1.5 scenario database with historical emission estimates as in [[#Meinshausen--2020|Meinshausen et al. (2020)]] (AR6 WGI Chapter 5). The WGIII assessment uses the same climate emulator with improved historical emissions estimates ( [[#Nicholls--2021|Nicholls et al. 2021]] ) (AR6 WGI Cross-Chapter Box 7.1). Annex III.II.2.5.1 further explores the effects of these factors on the relationship between non-CO 2 warming at peak cumulative CO 2 and peak surface temperature.

Estimates of the remaining carbon budgets thus vary with the assumed level of non-CO 2 emissions, which are a function of policies and technology development. The linear relationship used in the AR6 WGI assessment between peak temperature and the warming as a result of non-CO 2 emissions (based on the SR1.5 data) is shown in the right panel of Figure 2 (dashed line). In the AR6 WGIII approach, the non-CO 2 warming for each single scenario is based on the individual scenario characteristics. This is shown in the same figure by plotting the outcomes of scenario outcomes of a range of models (dots). The lines show the fitted data for individual models, emphasising the clear differences across models and the relationship with peak warming (policy level). In some scenarios, stringent non-CO 2 emission reductions provide an option to reach more stringent climate goals with the same carbon budget. This is especially the case for scenarios with a very low non-CO 2 warming, for instance, as a result of methane reductions through diet change. The left panel shows how these differences impact estimates of the remaining carbon budget. While the AR6 scenarios database includes a broad range of non-CO 2 emission projections the overall range is still very consistent with the WGI relationship and the estimated uncertainty with a ±220 GtCO 2 range (see also Figure 5 in Annex III.II.2.5.1).

Overall, the slight differences between the cumulative emissions in AR6 WGIII and the carbon budget in AR6 WGI are because the non-CO 2 warming in the WGIII scenarios is slightly lower than in the SR1.5 scenarios that are used for the budget estimates in WGI (Annex III.2.5.1). In addition, improved consistency with Cross-Chapter Box 7.1 in Chapter 7, AR6 WGI results in a non-CO 2 -induced temperature difference of about about 0.05K between the assessments. Recalculating the remaining carbon budget using the WGI methodology combined with the full AR6 WGIII scenario database results in a reduction of the estimated remaining 1.5°C carbon budget by about 100 GtCO 2 (–20%), and a reduction of about 40 GtCO 2 (–3%) for 2°C. Accounting also for the categorisation effect, the difference between the WGI and WGIII estimates is found to be small and well within the uncertainty range (Figure 1). This means that the cumulative CO 2 emissions presented in WGIII and the WGI carbon budgets are highly consistent.

A detailed comparison of the impact of different assessment steps (i.e., the new emulators, scenarios, and harmonisation methods), has been made and is presented in Figure 6 in Annex III.II.3.2 .

Policy implications

The concept of a finite carbon budget means that the world needs to get to net zero CO 2 , no matter whether global warming is limited to 1.5°C or well below 2°C (or any other level). Moreover, exceeding the remaining carbon budget will have consequences by overshooting temperature levels. Still, the relationship between the timing of net zero and temperature targets is a flexible one, as discussed further in Cross-Chapter Box 3 in this chapter. It should be noted that the national-level inventory as used by UNFCCC for the land use, land-use change and forestry sector is different from the overall concept of anthropogenic emissions employed by IPCC AR6 WGI. For emissions estimates based on these inventories, the remaining carbon budgets must be correspondingly reduced by approximately 15%, depending on the scenarios ( [[#Grassi--2021|Grassi et al., 2021]] ) (Chapter 7).

One of the uncertainties of the remaining carbon budget is the level of non-CO 2 emissions which is a function of policies and technology development. This represents a point of leverage for policies rather than an inherent geophysical uncertainty. Stringent non-CO 2 emission reductions hence can provide – to some degree – an option to reach more stringent climate goals with the same carbon budget.

The near-linear relationship implies that cumulative CO 2 emissions are critically important for climate outcomes ( [[#Collins--2013|Collins et al. 2013]] ). The maximum temperature increase is a direct function of the cumulative emissions until net zero CO 2 emissions is reached (the emission budget) (Figure 3.13, left side). The end-of-century temperature correlates well with cumulative emissions across the century (right panel). For long-term climate goals, positive emissions in the first half of the century can be offset by net removal of CO 2 from the atmosphere (net negative emissions) at the cost of a temporary overshoot of the target ( [[#Tokarska--2019|Tokarska et al. 2019]] ). The bottom panels of Figure 3.13 show the contribution of net negative CO 2 emissions.

Focusing on cumulative emissions, the right-hand panel of Figure 3.12b shows that for high-end scenarios (C6–C7), most emissions originate from fossil fuels, with a smaller contribution from net deforestation. For C5 and lower, there is also a negative contribution to emissions from both AFOLU emissions and energy systems. For the energy systems, these negative emissions originate from bioenergy with carbon capture and storage (BECCS), while for AFOLU, they originate from reforestation and afforestation. For C3–C5, reforestation has a larger CDR contribution than BECCS, mostly due to considerably lower costs ( [[#Rochedo--2018|Rochedo et al. 2018]] ). For C1 and C2, the tight carbon budgets imply in many scenarios more CDR use ( [[#Riahi--2021|Riahi et al. 2021]] ). Please note that net negative emissions are not so relevant for peak-temperature targets, and thus the C1 category, but CDR can still be used to offset the remaining positive emissions ( [[#Riahi--2021|Riahi et al. 2021]] ). While positive CO 2 emissions from fossil fuels are significantly reduced, inertia and hard-to-abate sectors imply that in many C1–C3 scenarios, around 800–1000 GtCO 2 of net positive cumulative CO 2 emissions remain. This is consistent with literature estimates that current infrastructure is associated with 650 GtCO 2 (best estimate) if operated until the end of its lifetime ( [[#Tong--2019|Tong et al. 2019]] ). These numbers are considerably above the estimated carbon budgets for 1.5°C estimated in AR6 WGI, hence explaining CDR reliance (either to offset emissions immediately or later in time).

Creating net negative emissions can thus be an important part of a mitigation strategy to offset remaining emissions or compensate for emissions earlier in time. As indicated above, there are different ways to potentially achieve this, including reforestation and afforestation and BECCS (as often covered in IAMs) but also soil carbon enhancement, direct air carbon capture and storage (DACCS) and ocean alkalinisation (Chapter 12). Except for reforestation, these options have not been tested at large scale and often require more R&amp;D. Moreover, the reliance on CDR in scenarios has been discussed given possible consequences of land use related to biodiversity loss and food security (BECCS and afforestation), the reliance on uncertain storage potentials (BECCS and DACCS), water use (BECCS), energy use (DACCS), the risks of possible temperature overshoot and the consequences for meeting Sustainable Development Goals (SDGs) ( [[#Anderson--2016|Anderson and Peters 2016]] ; [[#Smith--2016|Smith et al. 2016]] ; [[#Venton--2016|Venton 2016]] ; [[#Peters--2017|Peters and Geden 2017]] ; [[#van%20Vuuren--2017|van Vuuren et al. 2017]] ; [[#Honegger--2021|Honegger et al. 2021]] ). In the case of BECCS, it should be noted that bioenergy typically is associated with early-on positive CO 2 emissions and net negative effects are only achieved in time (carbon debt), and its potential is limited ( [[#Cherubini--2013|Cherubini et al. 2013]] ; [[#Hanssen--2020|Hanssen et al. 2020]] ); most IAMs have only a very limited representation of these time dynamics. Several scenarios have therefore explored how reliance on net negative CO 2 emissions can be reduced or even avoided by alternative emission strategies ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#van%20Vuuren--2018|van Vuuren et al. 2018]] ) or early reductions by more stringent emission reduction in the short term ( [[#Rogelj--2019b|Rogelj et al. 2019b]] ; [[#Riahi--2021|Riahi et al. 2021]] ). A more in-depth discussion of land-based mitigation options can be found in Chapter 7. It needs to be emphasised that even in strategies with net negative CO 2 emissions, the emission reduction via more conventional mitigation measures (efficiency improvement, decarbonisation of energy supply) is much larger than the CDR contribution ( [[#Tsutsui--2020|Tsutsui et al. 2020]] ).

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=== Cross-Chapter Box 3 | Understanding Net Zero CO 2 and Net Zero GHG Emissions ===

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'''Authors:''' Elmar Kriegler (Germany), Alaa Al Khourdajie (United Kingdom/Syria), Edward Byers (Austria/Ireland), Katherine Calvin (the United States of America), Leon Clarke (the United States of America), Annette Cowie (Australia), Navroz Dubash (India), Jae Edmonds (the United States of America), Jan S. Fuglestvedt (Norway), Oliver Geden (Germany), Giacomo Grassi (Italy/European Union), Anders Hammer Strømman (Norway), Frank Jotzo (Australia), Alexandre Köberle (Brazil/United Kingdom), Franck Lecocq (France), Yun Seng Lim (Malaysia), Eric Masanet (the United States of America), Toshihiko Masui (Japan), Catherine Mitchell (United Kingdom), Gert-Jan Nabuurs (the Netherlands), Anthony Patt (the United States of America/Switzerland), Glen P. Peters (Norway/Australia), Andy Reisinger (New Zealand), Keywan Riahi (Austria), Joeri Rogelj (United Kingdom/Belgium), Yamina Saheb (France/Algeria), Jim Skea (United Kingdom), Detlef P. van Vuuren (the Netherlands), Harald Winkler (Republic of South Africa)

This Cross-Chapter Box surveys scientific, technical and policy aspects of net zero carbon dioxide (CO 2 ) and net zero greenhouse gas (GHG) emissions, with a focus on timing, the relationship with warming levels, and sectoral and regional characteristics of net zero emissions. Assessment of net zero GHG emissions additionally requires consideration of non-CO 2 gases and choice of GHG emission metrics used to aggregate emissions and removals of different GHGs (Cross-Chapter Box 2 in [[IPCC:Wg3:Chapter:Chapter-2|Chapter 2]] and Cross-Chapter Box 7 in Chapter 10). The following considers net zero CO 2 and GHG emissions globally, followed by regional and sectoral dimensions.

'''Net zero CO''' 2 '''emissions'''

'''Reaching net zero CO''' 2 '''emissions globally is necessary for limiting global warming to any level.''' At the point of net zero CO 2 , the amount of CO 2 human activity is putting into the atmosphere equals the amount of CO 2 human activity is removing from the atmosphere (see Annex I: Glossary). Reaching and sustaining net zero CO 2 emissions globally stabilizes CO 2 -induced warming. Reaching net zero CO 2 emissions and then moving to net negative CO 2 emissions globally leads to a peak and decline in CO 2 -induced warming (AR6 WGI Sections 5.5 and 5.6).

'''Limiting warming to 1.5°C (&gt;50%) or to 2°C (&gt;67%) requires deep, rapid, and sustained reductions of other greenhouse gases including methane alongside rapid reductions of CO''' 2 '''emissions to net zero.''' This ensures that the warming contributions from non-CO 2 forcing agents as well as from CO 2 emissions are both limited at low levels. The AR6 WGI estimated remaining carbon budgets until the time of reaching net zero CO 2 emissions for a range of warming limits, taking into account historical CO 2 emissions and projections of the warming from non-CO 2 forcing agents (Box 3.4 in [[#3.3|Section 3.3]] , AR6 WGI [[IPCC:Wg3:Chapter:Chapter-5#5.5|Section 5.5]] ).

'''The earlier global net zero CO''' 2 '''emissions are reached, the lower the cumulative net amount of CO''' 2 '''emissions and human-induced global warming, all else being equal''' (Figure 1a in this Cross-Chapter Box). For a given net zero date, a variation in the shape of the CO 2 emissions profile can lead to a variation in the cumulative net amount of CO 2 emissions until the time of net zero CO 2 and as a result to different peak-warming levels. For example, cumulative net CO 2 emissions until the time of reaching net zero CO 2 will be smaller, and peak warming lower, if emissions are reduced steeply and then more slowly compared to reducing emissions slowly and then more steeply (Figure 1b in this Cross-Chapter Box).

'''Net zero CO''' 2 '''emissions are reached between 2050–2055 (2035–2070) in global emissions pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot, and between 2070–2075 (2055–…) in pathways limiting warming to 2°C (&gt;67%) as reported in the AR6 scenarios database''' (median five-year interval and 5–95th percentile ranges). [[#footnote-015|5]] The variation of non-CO 2 emissions in 1.5°C–2°C pathways varies the available remaining carbon budget which can move the time of reaching net zero CO 2 in these pathways forward or backward. [[#footnote-014|6]] The shape of the CO 2 emissions reduction profile also affects the time of reaching net zero CO 2 (Figure 1c in this Cross-Chapter Box). Global emission pathways that more than halve CO 2 emissions from 2020 to 2030 can follow this rapid reduction by a more gradual decline towards net zero CO 2 and still limit warming to 1.5°C with no or limited overshoot, reaching the point of net zero after 2050. The literature since SR1.5 included a larger fraction of such pathways than were available at the time of SR1.5. This is the primary reason for the small backward shift in the median estimate of reaching global net zero CO 2 emissions in 1.5°C pathways collected in the AR6 scenario database compared to SR1.5. This does not mean that the world is assessed to have more time to rapidly reduce current emissions levels compared to SR1.5. The assessment of emissions reductions by 2030 and 2040 in pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot has not changed substantially. It only means that the exact timing of reaching net zero CO 2 after a steep decline of CO 2 emissions until 2030 and 2040 can show some variation, and the SR1.5 median value of 2050 is still close to the middle of the current range (Figure 1c in this Cross-Chapter Box).

<div id="_idContainer040" class="_idGenObjectStyleOverride-2"></div>

[[File:5f3aa58eb3e450fb0bc2fbb9f2c3fc10 IPCC_AR6_WGIII_CCBox_3_Figure_1.png]]

'''Cross-Chapter Box 3, Figure 1 | Selected global CO 2 emissions trajectories with similar shape and different net zero CO 2 date (a), different shape and similar net zero CO 2 date (b), and similar peak warming, but varying shapes and net zero CO 2 dates (c). Funnels show pathways limiting warming to 1.''' 5 °C (&gt;50%) with no or limited overshoot (light blue) and limiting warming to 2°C (&gt;67%) (beige). Historic CO 2 emissions from [[IPCC:Wg3:Chapter:Chapter-2#2.2|Section 2.2]] (EDGAR v6).

'''Pathways following emissions levels projected from the implementation of Nationally Determined Contributions (NDCs) announced prior to COP26 until 2030 would result in substantially (&gt;0.1°C) exceeding 1.5°C.''' They would have to reach net zero CO 2 around 5–10 years later [[#footnote-013|7]] than in pathways with no or limited overshoot in order to reach the net negative emissions that would then be required to return warming to 1.5°C (&gt;50%) after a high overshoot by 2100. Those high overshoot pathways have higher transient warming and higher reliance on net negative CO 2 emissions towards the end of the 21st century. As they need to reach net zero CO 2 emissions in only limited amount of time but from much higher 2030 emissions levels, their post-2030 CO 2 emissions reduction rates are substantially higher (by around 30%) than in pathways limiting warming to 1.5°C with no or limited overshoot. ( [[#3.5|Section 3.5]] ).

'''Pathways following emissions levels projected from the implementation of NDCs announced prior to COP26 until 2030 would have to reach net zero CO''' 2 '''around 5 years earlier''' [[#footnote-012|8]] '''than cost-effective pathways that''' '''limit warming to 2°C (&gt;67%).''' While cost-effective pathways take around 50–55 years to reach net zero CO 2 emissions, those pathways would only have 35–40 years left for transitioning to net zero CO 2 from 2030 onwards, close to the transition times that 1.5°C pathways are faced with today. Current CO 2 emissions and 2030 emission levels projected under the NDCs announced prior to COP26 are in a similar range (Sections 3.5 and 4.2).

'''Net zero greenhouse gas (GHG) emissions'''

'''The amount of CO''' 2 '''-equivalent emissions and the point when net zero GHG emissions are reached in multi-GHG emissions pathways depends on the choice of GHG emissions metric.''' Various GHG emission metrics are available for this purpose. [[#footnote-011|9]] GWP-100 is the most commonly used metric for reporting CO 2 -equivalent emissions and is required for emissions reporting under the Rulebook of the Paris Agreement. (Cross-Chapter Box 2 in Chapter 2, Annex I and Annex II.9)

'''For most choices of GHG emissions metric, reaching net zero GHG emissions requires net negative CO''' 2 '''emissions in order to balance residual CH''' 4 ''', N''' 2 '''O and F-gas emissions.''' Under foreseen technology developments, some CH 4 , N 2 O and F-gas emissions from, for example, agriculture and industry, will remain over the course of this century. Net negative CO 2 emissions will therefore be needed to balance these remaining non-CO 2 GHG emissions to obtain net zero GHG emissions at a point in time after net zero CO 2 has been reached in emissions pathways. Both the amount of net negative CO 2 emissions and the time lag to reaching net zero GHG depend on the choice of GHG emission metric.

'''Reaching net zero GHG emissions globally in terms of''' '''GWP-100''' '''leads to a reduction in global warming from an earlier peak.''' This is due to net negative CO 2 emissions balancing the GWP-100-equivalent emissions of short-lived GHG emissions, which by themselves do not contribute to further warming if sufficiently declining ( [[#Fuglestvedt--2018|Fuglestvedt et al. 2018]] ; [[#Rogelj--2021|Rogelj et al. 2021]] ). Hence, 1.5°C–2°C emissions pathways in the AR6 scenario database that reach global net zero GHG emissions in the second half of the century show warming being halted at some peak value followed by a gradual decline towards the end of the century (AR6 WGI Chapter 1, Box 1.4).

'''Global net zero GHG emissions measured in terms of''' '''GWP-100''' '''are reached between 2095 and 2100 (2050–…)''' [[#footnote-010|10]] '''in emission pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot (median and 5–95th percentile).''' Around 50% of pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot and 70% of pathways limiting warming to 2°C (&gt;67%) do not reach net zero GHG emissions in terms of GWP-100 before 2100. These pathways tend to show less reduction in warming after the peak than pathways that reach net zero GHG emissions. For the subset of pathways that reach net zero GHG emissions before 2100, including around 90% of pathways that return warming to 1.5°C after a high overshoot (&gt;0.1°C) by 2100, the time lag between reaching net zero CO 2 and net zero GHG is 12–14 (7–39) years and the amount of net negative CO 2 emissions deployed to balance non-CO 2 emissions at the time of net zero GHG is around -7 (–10 to –4) GtCO 2 (range of medians and lowest 5th to highest 95 percentile across the four scenario classes that limit median warming to 2°C or lower) ( [[#3.3|Section 3.3]] and Table 3.2).

'''Sectoral and regional aspects of net zero'''

'''The timing of net zero CO''' 2 '''or GHG emissions may differ across regions and sectors. Achieving net zero emissions globally implies that some sectors and regions must reach net zero CO''' 2 '''or GHG ahead of the time of global net zero CO''' 2 '''or GHG if others reach it later.''' Similarly, some sectors and regions would need to achieve net negative CO 2 or GHG emissions to compensate for continued emissions by other sectors and regions after the global net zero year. Differences in the timing to reach net zero emissions between sectors and regions depend on multiple factors, including the potential of countries and sectors to reduce GHG emissions and undertake carbon dioxide removal (CDR), the associated costs, and the availability of policy mechanisms to balance emissions and removals between sectors and countries ( [[#Fyson--2020|Fyson et al. 2020]] ; [[#Strefler--2021a|Strefler et al. 2021a]] ; [[#van%20Soest--2021b|van Soest et al. 2021b]] ). A lack of such mechanisms could lead to higher global costs to reach net zero emissions globally, but less interdependencies and institutional needs ( [[#Fajardy--2020|Fajardy and Mac Dowell 2020]] ). Sectors will reach net zero CO 2 and GHG emissions at different times if they are aiming for such targets with sector-specific policies or as part of an economy-wide net zero emissions strategy integrating emissions reductions and removals across sectors. In the latter case, sectors with large potential for achieving net negative emissions would go beyond net zero to balance residual emissions from sectors with low potential, which in turn would take more time compared to the case of sector-specific action. Global pathways project global AFOLU emissions to reach global net zero CO 2 the earliest, around 2030 to 2035 in pathways to limit warming to 2°C (&gt;67%) or lower, by rapid reduction of deforestation and enhancing carbon sinks on land, although net zero GHG emissions from global AFOLU are typically reached 30 years later, if at all. The ability of global AFOLU CO 2 emissions to reach net zero as early as in the 2030s in modelled pathways hinges on optimistic assumptions about the ability to establish global cost-effective mechanisms to balance emissions reductions and removals across regions and sectors. These assumptions have been challenged in the literature and the ''Special Report on Climate Change and Land'' (IPCC SRCCL).

'''The adoption and implementation of net zero CO''' 2 '''or GHG emission targets by countries and regions also depends on equity and capacity criteria.''' The Paris Agreement recognises that peaking of emissions will occur later in developing countries (Art. 4.1). Just transitions to net zero CO 2 or GHG could be expected to follow multiple pathways, in different contexts. Regions may decide about net zero pathways based on their consideration of potential for rapid transition to low-carbon development pathways, the capacity to design and implement those changes, and perceptions of equity within and across countries. Cost-effective pathways from global models have been shown to distribute the mitigation effort unevenly and inequitably in the absence of financial support mechanisms and capacity building ( [[#Budolfson--2021|Budolfson et al. 2021]] ), and hence would require additional measures to become aligned with

equity considerations ( [[#Fyson--2020|Fyson et al. 2020]] ; [[#van%20Soest--2021b|van Soest et al. 2021b]] ). Formulation of net zero pathways by countries will benefit from clarity on scope, roadmaps and fairness ( [[#Rogelj--2021|Rogelj et al. 2021]] ; [[#Smith--2021|Smith 2021]] ). Achieving net zero emission targets relies on policies, institutions and milestones against which to track progress. Milestones can include emissions levels, as well as markers of technological diffusion.

'''The accounting of anthropogenic carbon dioxide removal on land matters for the evaluation of net zero CO''' 2 '''and net zero GHG strategies.''' Due to the use of different approaches between national inventories and global models, the current net CO 2 emissions are lower by 5.5 GtCO 2 , and cumulative net CO 2 emissions in modelled 1.5°C–2°C pathways would be lower by 104–170 GtCO 2 , if carbon dioxide removals on land are accounted based on national GHG inventories. National GHG inventories typically consider a much larger area of managed forest than global models, and on this area additionally consider the fluxes due to human-induced global environmental change (indirect effects) to be anthropogenic, while global models consider these fluxes to be natural. Both approaches capture the same land fluxes, only the accounting of anthropogenic vs natural emissions is different. Methods to convert estimates from global models to the accounting scheme of national GHG inventories will improve the use of emission pathways from global models as benchmarks against which collective progress is assessed. ( [[IPCC:Wg3:Chapter:Chapter-7#7.2.2|Section 7.2.2]] .5).

'''Net zero CO''' 2 '''and carbon neutrality have different meanings in this assessment, as is the case for net zero GHG and GHG neutrality.''' They apply to different boundaries in the emissions and removals being considered. Net zero (GHG or CO 2 ) refers to emissions and removals under the direct control or territorial responsibility of the reporting entity. In contrast, (GHG or carbon) neutrality includes anthropogenic emissions and anthropogenic removals within and also those beyond the direct control or territorial responsibility of the reporting entity. At the global scale, net zero CO 2 and carbon neutrality are equivalent, as is the case for net zero GHG and GHG neutrality. The term ‘climate neutrality’ is not used in this assessment because the concept of climate neutrality is diffuse, used differently by different communities, and not readily quantified.

Table 3.2 summarises the key characteristics for all temperature categories in terms of cumulative CO 2 emissions, near-term emission reductions, and the years of peak emission and net zero CO 2 and GHG emissions. The table shows again that many pathways in the literature limit global warming to 2 '''°''' C (&gt;67%) or limit warming to 1.5°C (&gt;50%) with no or limited overshoot compared to pre-industrial levels. Cumulative net CO 2 emissions from the year 2020 until the time of net zero CO 2 in pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot are 510 (330–710) GtCO 2 and in pathways that limit warming to 2°C (&gt;67%), 890 (640–1160) GtCO 2 (see also Cross-Chapter Box 3 in this chapter). Mitigation pathways that limit warming to 2°C (&gt;67%) compared to pre-industrial levels are associated with net global GHG emissions of 44 (32–55) GtCO 2 -eq yr –1 by 2030 and 20 (13–26) GtCO 2 -eq yr –1 in 2050. These correspond to GHG emissions reductions of 21% (1–42%) by 2030, and 64% (53–77%) by 2050 relative to 2019 emission levels. Pathways that limit global warming to 1.5°C (&gt;50%) with no or limited overshoot require a further acceleration in the pace of the transformation, with GHG emissions reductions of 43% (34–60%) by 2030 and 84% (73–98%) in 2050 relative to modelled 2019 emission levels. The likelihood of limiting warming to below 1.5°C (&gt;50%) with no or limited overshoot of the most stringent mitigation pathways in the literature (C1) has declined since SR1.5. This is because emissions have risen since 2010 by about 9 GtCO 2 yr –1 , resulting in relatively higher near-term emissions of the AR6 pathways by 2030 and slightly later dates for reaching net zero CO 2 emissions compared to SR1.5.

Given the larger contribution of scenarios in the literature that aim to reduce net negative emissions, emission reductions are somewhat larger in the short term compared to similar categories in the IPCC SR1.5. At the same time, the year of net zero emissions is somewhat later (but only if these rapid, short-term emission reductions are achieved). The scenarios in the literature in C1–C3 show a peak in global emissions before 2025. Not achieving this requires a more rapid reduction after 2025 to still meet the Paris goals ( [[#3.5|Section 3.5]] ).

'''Table 3.2 | GHG, CO''' 2 '''emissions and warming characteristics of different mitigation pathways submitted to the AR6 scenarios database and as categorised in the climate assessment.'''

{| class="wikitable"
|-
! colspan="3"| '''p50 [p5–p95]''' ''a''

! colspan="3"| '''GHG emissionsGt CO''' ''2'' '''-eq/yr''' ''g''

! colspan="3"| '''GHG emissions reductions from 2019%''' ''h''

! colspan="4"| '''Emissions milestones''' ''i,j''

! colspan="2"| '''Cumulative CO''' ''2'' '''emissionsGt CO''' ''2'' ''m''

! '''Cumulative net-negative CO''' ''2'' '''emissionsGt CO''' ''2''

! colspan="2"| '''Global mean temperature changes 50% probability''' ''n'' '''°C'''

! colspan="3"| '''Likelihood of peak global warming staying below (%)''' ''o''

! colspan="3"| '''Time when specific global warming levels are reached (with a 50% probability)'''

|-
! '''Category''' ''b, c, d'' '''[# path-ways]'''

! '''Category/ subset label'''

! '''WG I SSP &amp; WG III IPs/IMPs alignment''' ''e, f''

! '''2030'''

! '''2040'''

! '''2050'''

! '''2030'''

! '''2040'''

! '''2050'''

! '''Peak CO''' ''2'' '''emissions (% peak before 2100)'''

! '''Peak GHG emissions (% peak before 2100)'''

! '''Net-zero CO''' ''2'' '''(% net-zero pathways)'''

! '''Net-zero GHGs''' ''k, l'' '''(% net-zero pathways)'''

! '''2020 to net-zero CO''' ''2''

! '''2020–2100'''

! '''Year of net-zero CO''' ''2'' '''to 2100'''

! '''at peak warming'''

! '''2100'''

! '''&lt;1.5°C'''

! '''&lt;2°C'''

! '''&lt;3°C'''

! '''1.5°C'''

! '''2°C'''

! '''3°C'''

|-
! colspan="3"| Modelled global emissions pathways categorised by projected global warming levels (GWL). Detailed likelihood definitions are provided in SPM Box1.

The five illustrative scenarios (SSPx-yy) considered by AR6 WGI and the Illustrative (Mitigation) Pathways assessed in WGIII are aligned with the temperature categories and are indicated in a separate column. Global emission pathways contain regionally differentiated information. This assessment focuses on their global characteristics.

! colspan="3"| Projected median annual GHG emissions in the year across the scenarios, with the 5th–95th percentile in brackets.

Modelled GHG emissions in 2019: 55 [53–58] Gt CO 2 -eq.

! colspan="3"| Projected median GHG emissions reductions of pathways in the year across the scenarios compared to modelled 2019, with the 5th–95th percentile in brackets. Negative numbers indicate increase in emissions compared to 2019.

! colspan="2"| Median 5-year intervals at which projected CO 2 &amp; GHG emissions peak, with the 5th–95th percentile interval in square brackets. Percentage of peaking pathways is denoted in round brackets.

Three dots (…) denotes emissions peak in 2100 or beyond for that percentile.

! colspan="2"| Median 5-year intervals at which projected CO 2 &amp; GHG emissions of pathways in this category reach net-zero, with the 5th–95th percentile interval in square brackets. Percentage of net zero pathways is denoted in round brackets.

Three dots (…) denotes net zero not reached for that percentile.

! colspan="2"| Median cumulative net CO 2 emissions across the projected scenarios in this category until reaching net-zero or until 2100, with the 5th–95th percentile interval in square brackets.

! Median cumulative net-negative CO 2 emissions between the year of net-zero CO 2 and 2100. More net-negative results in greater temperature declines after peak.

! colspan="2"| Projected temperature change of pathways in this category (50% probability across the range of climate uncertainties), relative to 1850–1900, at peak warming and in 2100, for the median value across the scenarios and the 5th–95th percentile interval in square brackets.

! colspan="3"| Median likelihood that the projected pathways in this category stay below a given global warming level, with the 5th–95th percentile interval in square brackets.

! colspan="3"| Median 5-year intervals at which specific global warming levels are reached (50% probability), with the 5th–95th percentile interval in square brackets. Percentage of pathways is denoted in round brackets.

Three dots (…) denotes temperature does not exceed the GWL by 2100 for that percentile.

|-
| '''C1 [97]'''

| '''limit warming to 1.5°C (&gt;50%) with no or limited overshoot'''

|
| 31

[21–36]

| 17

[6–23]

| 9

[1–15]

| 43

[34–60]

| 69

[58–90]

| 84

[73–98]

| rowspan="4" colspan="2"| 2020–2025 (100%)

[2020–2025]

| rowspan="4"| 2050–2055 (100%)

[2035–2070]

| 2095–2100 (52%)

[2050–…]

| 510

[330–710]

| 320

[–210–570]

| –220

[–660-–20]

| 1.6

[1.4–1.6]

| 1.3

[1.1–1.5]

| 38

[33–58]

| 90

[86–97]

| 100

[99–100]

| 2030–2035 (91%)

[2030–…]

| …–… (0%)

[…–…]

| …–… (0%)

[…–…]

|-
| '''C1a [50]'''

| '''… with net-zero GHGs'''

| SSP1-1.9, IMP-SP

IMP-LD

| 33

[22–37]

| 18

[6–24]

| 8

[0–15]

| 41

[31–59]

| 66

[58–89]

| 85

[72–100]

| 2070–2075 (100%)

[2050–2090]

| 550

[340–760]

| 160

[–220–620]

| –360

[–680-–140]

| 1.6

[1.4–1.6]

| 1.2

[1.1–1.4]

| 38

[34–60]

| 90

[85–98]

| 100

[99–100]

| 2030–2035 (90%)

[2030–…]

| …–… (0%)

[…–…]

| …–… (0%)

[…–…]

|-
| rowspan="2"| '''C1b [47]'''

| rowspan="2"| '''… without net-zero GHGs'''

| IMP-Ren

| rowspan="2"| 29

[21–36]

| rowspan="2"| 16

[7–21]

| rowspan="2"| 9

[4–13]

| rowspan="2"| 48

[35–61]

| rowspan="2"| 70

[62–87]

| rowspan="2"| 84

[76–93]

| rowspan="2"| …–… (0%)

[…–…]

| rowspan="2"| 460

[320–590]

| rowspan="2"| 360

[10–540]

| rowspan="2"| –60

[–440–0]

| rowspan="2"| 1.6

[1.5–1.6]

| rowspan="2"| 1.4

[1.3–1.5]

| rowspan="2"| 37

[33–56]

| rowspan="2"| 89

[87–96]

| rowspan="2"| 100

[99–100]

| rowspan="2"| 2030–2035 (91%)

[2030–…]

| rowspan="2"| …–… (0%)

[…–…]

| rowspan="2"| …–… (0%)

[…–…]

|-
|
|-
| rowspan="2"| '''C2 [133]'''

| rowspan="2"| '''return warming to 1.5°C (&gt;50%) after a high overshoot'''

| '''IMP-Neg'''

| rowspan="2"| 42

[31–55]

| rowspan="2"| 25

[17–34]

| rowspan="2"| 14

[5–21]

| rowspan="2"| 23

[0–44]

| rowspan="2"| 55

[40–71]

| rowspan="2"| 75

[62–91]

| colspan="2"| 2020–2025 (100%)

| rowspan="2"| 2055–2060 (100%)

[2045–2070]

| rowspan="2"| 2070–2075 (87%)

[2055–…]

| rowspan="2"| 720

[530–930]

| rowspan="2"| 400

[–90–620]

| rowspan="2"| –360

[–680-–60]

| rowspan="2"| 1.7

[1.5–1.8]

| rowspan="2"| 1.4

[1.2–1.5]

| rowspan="2"| 24

[15–42]

| rowspan="2"| 82

[71–93]

| rowspan="2"| 100

[99–100]

| rowspan="2"| 2030–2035 (100%)

[…–…]

| rowspan="2"| …–… (0%)

[…–…]

| rowspan="2"| …–… (0%)

[…–…]

|-
|
| [2020–2030]

| [2020–2025]

|-
| rowspan="2"| '''C3 [311]'''

| rowspan="2"| limit warming to 2°C (&gt;67%)

|
| rowspan="2"| 44

[32–55]

| rowspan="2"| 29

[20–36]

| rowspan="2"| 20

[13–26]

| rowspan="2"| 21

[1–42]

| rowspan="2"| 46

[34–63]

| rowspan="2"| 64

[53–77]

| colspan="2"| 2020–2025 (100%)

| rowspan="2"| 2070–2075 (93%)

[2055–…]

| rowspan="2"| …–… (30%)

[2075–…]

| rowspan="2"| 890

[640–1160]

| rowspan="2"| 800

[510–1140]

| rowspan="2"| –40

[–290–0]

| rowspan="2"| 1.7

[1.6–1.8]

| rowspan="2"| 1.6

[1.5–1.8]

| rowspan="2"| 20

[13–41]

| rowspan="2"| 76

[68–91]

| rowspan="2"| 99

[98–100]

| rowspan="2"| 2030–2035 (100%)

[…–…]

| rowspan="2"| …–… (0%)

[…–…]

| rowspan="2"| …–… (0%)

[…–…]

|-
|
| [2020–2030]

| [2020–2025]

|-
| '''C3a [204]'''

| '''… with action starting in 2020'''

| SSP1-2.6

| 40

[30–49]

| 29

[21–36]

| 20

[14–27]

| 27

[13–45]

| 47

[35–63]

| 63

[52–76]

| colspan="2"| 2020–2025 (100%)

[2020–2025]

| 2070–2075 (91%)

[2055–…]

| …–… (24%)

[2080–…]

| 860

[640–1180]

| 790

[480–1150]

| –30

[–280–0]

| 1.7

[1.6–1.8]

| 1.6

[1.5–1.8]

| 21

[14–42]

| 78

[69–91]

| 100

[98–100]

| 2030–2035 (100%)

[2030–2040]

| …–… (0%)

[…–…]

| …–… (0%)

[…–…]

|-
| '''C3b [97]'''

| '''… NDCs until 2030'''

| IMP-GS

| 52

[47–56]

| 29

[20–36]

| 18

[10–25]

| 5

[0–14]

| 46

[34–63]

| 68

[56–82]

| rowspan="3" colspan="2"| 2020–2025 (100%)

[2020–2030]

| 2065–2070 (97%)

[2055–2090]

| …–… (41%)

[2075–…]

| 910

[720–1150]

| 800

[560–1050]

| –60

[–300–0]

| 1.8

[1.6–1.8]

| 1.6

[1.5–1.7]

| 17

[12–35]

| 73

[67–87]

| 99

[98–99]

| 2030–2035 (100%)

[2030–2035]

| …–… (0%)

[…–…]

| …–… (0%)

[…–…]

|-
| '''C4 [159]'''

| '''limit warming to 2°C (&gt;50%)'''

|
| 50

[41–56]

| 38

[28–44]

| 28

[19–35]

| 10

[0–27]

| 31

[20–50]

| 49

[35–65]

| 2080–2085 (86%)

[2065–…]

| …–… (31%)

[2075–…]

| 1210

[970–1490]

| 1160

[700–1490]

| –30

[–390–0]

| 1.9

[1.7–2.0]

| 1.8

[1.5–2.0]

| 11

[7–22]

| 59

[50–77]

| 98

[95–99]

| 2030–2035 (100%)

[2030–2035]

| …–… (0%)

[…–…]

| …–… (0%)

[…–…]

|-
| '''C5 [212]'''

| '''limit warming to 2.5°C (&gt;50%)'''

|
| 52

[46–56]

| 45

[37–53]

| 39

[30–49]

| 6

[–1–18]

| 18

[4–33]

| 29

[11–48]

| …–… (41%)

[2080–…]

| …–… (12%)

[2090–…]

| 1780

[1400–2360]

| 1780

[1260–2360]

| 0

[–160–0]

| 2.2

[1.9–2.5]

| 2.1

[1.9–2.5]

| 4

[0–10]

| 37

[18–59]

| 91

[83–98]

| 2030–2035 (100%)

[2030–2035]

| 2060–2065 (99%)

[2050–2095]

| …–… (0%)

[…–…]

|-
| rowspan="2"| '''C6 [97]'''

| rowspan="2"| '''limit warming to 3°C (&gt;50%)'''

| rowspan="2"| SSP2-4.5

Mod-Act

| rowspan="2"| 54

[50–62]

| rowspan="2"| 53

[48–61]

| rowspan="2"| 52

[45–57]

| rowspan="2"| 2

[–10–11]

| rowspan="2"| 3

[–14–14]

| rowspan="2"| 5

[–2–18]

| 2030–2035 (96%)

| 2020–2025 (97%)

| rowspan="5" colspan="2"| no net-zero

| rowspan="5"| no net-zero

| rowspan="2"| 2790

[2440–3520]

| rowspan="5"| no net-zero

| rowspan="5"| temperature does not peak by 2100

| rowspan="2"| 2.7

[2.4–2.9]

| rowspan="2"| 0

[0–0]

| rowspan="2"| 8

[2–18]

| rowspan="2"| 71

[53–88]

| rowspan="2"| 2030–2035 (100%)

[2030–2035]

| rowspan="2"| 2050–2055 (100%)

[2045–2060]

| rowspan="2"| …–… (0%)

[…–…]

|-
| colspan="2"| [2020–2090]

|-
| rowspan="2"| '''C7 [164]'''

| rowspan="2"| '''limit warming to 4°C (&gt;50%)'''

| rowspan="2"| SSP3-7.0

Cur-Pol

| rowspan="2"| 62

[53–69]

| rowspan="2"| 67

[56–76]

| rowspan="2"| 70

[58–83]

| rowspan="2"| –11

[–18–3]

| rowspan="2"| –19

[–31–1]

| rowspan="2"| –24

[–41––2]

| 2085–2090 (57%)

| 2090–2095 (56%)

| rowspan="2"| 4220

[3160–5000]

| rowspan="2"| 3.5

[2.8–3.9]

| rowspan="2"| 0

[0–0]

| rowspan="2"| 0

[0–2]

| rowspan="2"| 22

[7–60]

| rowspan="2"| 2030–2035 (100%)

[2030–2035]

| rowspan="2"| 2045–2050 (100%)

[2040–2055]

| rowspan="2"| 2080–2085 (100%)

[2070–2100]

|-
| colspan="2"| [2040–…]

|-
| '''C8 [29]'''

| '''exceed warming of 4°C (''' ≥ '''50%)'''

| SSP5-8.5

| 71

[69–81]

| 80

[78–96]

| 88

[82–112]

| –20

[–34-–17]

| –35

[–65-–29]

| –46

[–92-–36]

| colspan="2"| 2080–2085 (90%)

[2070–…]

| 5600

[4910–7450]

| 4.2

[3.7–5.0]

| 0

[0–0]

| 0

[0–0]

| 4

[0–11]

| 2030–2035 (100%)

[2030–2035]

| 2040–2045 (100%)

[2040–2050]

| 2065–2070 (100%)

[2060–2075]

|}

a 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. Harmonised emissions values are given for consistency with projected global warming outcomes using climate emulators. Based on the assessment of climate emulators in AR6 WGI (WG1 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.

b For a description of pathways categories see Box SPM.1 and Table 3.1.

c All global warming levels are relative to 1850–1900. (See footnote n below and Box SPM.1 45 for more details.)

d 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.

e Alignment with the categories of the illustrative SSP scenarios considered in AR6 WGI, and the Illustrative (Mitigation) Pathways (IPs/IMPs) of WGIII. The IMPs have common features such as deep and rapid emissions reductions, but also different combinations of sectoral mitigation strategies. See Box SPM.1 for an introduction of the IPs and IMPs, and [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-3 Chapter 3] for full descriptions. {3.2, 3.3, Annex III.II.2.4}

f 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 Box SPM.1 for an introduction of the IPs and IMPs.

g The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO 2 -eq] is within the uncertainty ranges of 2019 emissions assessed in [[IPCC:Wg3:Chapter:Chapter-2|Chapter 2]] [53–66 GtCO 2 -eq]. 49 (Figure SPM.1, Figure SPM.2, Box SPM.1)

h Rates of global emission reduction in mitigation pathways are reported on a pathway-by-pathway basis relative to harmonised modelled global emissions in 2019 rather than the global emissions reported in 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 WGI. 49 {Annex III.II.2.5} . Negative values (e.g., in C7, C8) represent an increase in emissions.

i Emissions milestones are provided for five-year intervals in order to be consistent with the underlying five-year time-step data of the modelled pathways. Peak emissions (CO 2 and GHGs) are assessed for five-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 five-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 five-year interval and the upper bound of the 95th percentile five-year interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones.

j 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 MtCO 2 yr –1 until 2100.

k The timing of net zero is further discussed in SPM C2.4 and Cross-Chapter Box 3 in [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-3 Chapter 3] on net zero CO 2 and net zero GHG emissions.

l For cases where models do not report all GHGs, missing GHG species are infilled and aggregated into a Kyoto basket of GHG emissions in CO 2 -eq defined by the 100-year global warming potential. For each pathway, reporting of CO 2 , CH 4 , and N 2 O emissions was the minimum required for the assessment of the climate response and the assignment to a climate category. Emissions pathways without climate assessment are not included in the ranges presented here. {See Annex III.II.2.5 }

m Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively. They are based on harmonised net CO 2 emissions, ensuring consistency with the WGI assessment of the remaining carbon budget. 50 {Box 3.4}

n 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 WGI assessment. 12 (See also Box SPM.1) {Annex III.II.2.5; WGI Cross-Chapter Box 7.1}

o 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 WGI 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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=== 3.3.3 Impacts on Mitigation Potential ''[[#footnote-009|11]]'' ===

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At the moment, climate change impact on mitigation potential is hardly considered in model-based scenarios. While a detailed overview of climate impacts is provided in IPCC AR6 WGII and [[#3.6|Section 3.6]] discusses the economic consequences, here we concentrate on the implications for mitigation potential. Climate change directly impacts the carbon budget via all kinds of feedbacks – which is included in the ranges provided for the carbon budget (e.g., 300–900 GtCO 2 for 17th–83rd percentile for not exceeding 1.5°C; see AR6 WGI Chapter 5, 2021). Climate change, however, alters the production and consumption of energy ( [[IPCC:Wg3:Chapter:Chapter-6#6.5|Section 6.5]] ). An overview of the literature is provided by [[#Yalew--2020|Yalew et al. (2020)]] . In terms of supply, impacts could influence the cooling capacity of thermal plants, the potential and predictability of renewable energy, and energy infrastructure ( [[#van%20Vliet--2016|van Vliet et al. 2016]] ; [[#Turner--2017|Turner et al. 2017]] ; [[#Cronin--2018a|Cronin et al. 2018a]] ; [[#Lucena--2018|Lucena et al. 2018]] ; [[#Yalew--2020|Yalew et al. 2020]] ; [[#Gernaat--2021|Gernaat et al. 2021]] ). Although the outcomes of these studies differ, they seem to suggest that although impacts might be relatively small at the global scale, they could be substantial at the regional scale (increasing or decreasing potential). Climate change can also impact energy demand, with rising temperatures resulting in decreases in heating demand and increases in cooling demand ( [[#Isaac--2009|Isaac and van Vuuren 2009]] ; [[#Zhou--2014|Zhou et al. 2014]] ; [[#Labriet--2015|Labriet et al. 2015]] ; [[#McFarland--2015|McFarland et al. 2015]] ; [[#Auffhammer--2017|Auffhammer et al. 2017]] ; [[#Clarke--2018|Clarke et al. 2018]] ; [[#van%20Ruijven--2019|van Ruijven et al. 2019]] ; [[#Yalew--2020|Yalew et al. 2020]] ). As expected, the increase in cooling demand dominates the impact in warm regions and decreases in heating demand in cold regions ( [[#Isaac--2009|Isaac and van Vuuren 2009]] ; [[#Zhou--2014|Zhou et al. 2014]] ; [[#Clarke--2018|Clarke et al. 2018]] ). Globally, most studies show a net increase in energy demand at the end of the century due to climate impacts ( [[#Isaac--2009|Isaac and van Vuuren 2009]] ; [[#Clarke--2018|Clarke et al. 2018]] ; [[#van%20Ruijven--2019|van Ruijven et al. 2019]] ); however, one study shows a net decrease ( [[#Labriet--2015|Labriet et al. 2015]] ). Only a few studies quantify the combined impacts of climate change on energy supply and energy demand ( [[#McFarland--2015|McFarland et al. 2015]] ; [[#Mima--2015|Mima and Criqui 2015]] ; [[#Emodi--2019|Emodi et al. 2019]] ; [[#Steinberg--2020|Steinberg et al. 2020]] ). These studies show increases in electricity generation in the USA ( [[#McFarland--2015|McFarland et al. 2015]] ; [[#Steinberg--2020|Steinberg et al. 2020]] ) and increases in CO 2 emissions in Australia ( [[#Emodi--2019|Emodi et al. 2019]] ) or the USA ( [[#McFarland--2015|McFarland et al. 2015]] ).

Climate change can impact the potential for AFOLU mitigation action by altering terrestrial carbon uptake, crop yields and bioenergy potential (Chapter 7). Carbon sequestration in forests may be positively or adversely affected by climate change and CO 2 fertilisation. On the one hand, elevated CO 2 levels and higher temperatures could enhance tree growth rates, carbon sequestration, and timber and biomass production ( [[#Beach--2015|Beach et al. 2015]] ; [[#Kim--2017|Kim et al. 2017]] ; [[#Anderegg--2020|Anderegg et al. 2020]] ). On the other hand, climate change could lead to greater frequency and intensity of disturbance events in forests, such as fires, prolonged droughts, storms, pests and diseases ( [[#Kim--2017|Kim et al. 2017]] ; [[#Anderegg--2020|Anderegg et al. 2020]] ). The impact of climate change on crop yields could also indirectly impact the availability of land for mitigation and AFOLU emissions ( [[#Calvin--2013|Calvin et al. 2013]] ; [[#Bajželj--2014|Bajželj and Richards 2014]] ; [[#Kyle--2014|Kyle et al. 2014]] ; [[#Beach--2015|Beach et al. 2015]] ; [[#Meijl--2018|Meijl et al. 2018]] ). The impact is, however, uncertain, as discussed in AR6 WGII Chapter 5. A few studies estimate the effect of climate impacts on AFOLU on mitigation, finding increases in carbon prices or mitigation costs by 1–6% in most scenarios ( [[#Calvin--2013|Calvin et al. 2013]] ; [[#Kyle--2014|Kyle et al. 2014]] ).

In summary, a limited number of studies quantify the impact of climate on emissions pathways. The most important impact in energy systems might be through the impact on demand, although climate change could also impact renewable mitigation potential – certainly at the local and regional scale. Climate change might be more important for land-use related mitigation measures, including afforestation, bioenergy and nature-based solutions. The net effect of changes in climate and CO 2 fertilisation are uncertain but could be substantial (Chapter 7).

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