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

=== 3.3.2 Emission Pathways and Temperature Outcomes ===

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==== 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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==== 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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===== 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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==== 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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