Editing IPCC:AR6/SR15/Chapter-2 (section)

== Box 2.1 Bioenergy and BECCS Deployment in Integrated Assessment Modelling ==

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Bioenergy can be used in various parts of the energy sector of IAMs, including for electricity, liquid fuel, biogas, and hydrogen production. It is this flexibility that makes bioenergy and bioenergy technologies valuable for the decarbonization of energy use (Klein et al., 2014; Krey et al., 2014a; Rose et al., 2014a; Bauer et al., 2017, 2018) <sup>[[#fn:r292|292]]</sup> . Most bioenergy technologies in IAMs are also available in combination with CCS (BECCS). Assumed capture rates differ between technologies, for example, about 90% for electricity and hydrogen production and about 40–50% for liquid fuel production. Decisions about bioenergy deployment in IAMs are based on economic considerations to stay within a carbon budget that is consistent with a long-term climate goal. IAMs consider both the value of bioenergy in the energy system and the value of BECCS in removing CO <sub>2</sub> from the atmosphere. Typically, if bioenergy is strongly limited, BECCS technologies with high capture rates are favoured. If bioenergy is plentiful IAMs tend to choose biofuel technologies with lower capture rates but high value for replacing fossil fuels in transport (Kriegler et al., 2013a; Bauer et al., 2018) <sup>[[#fn:r293|293]]</sup> . Most bioenergy use in IAMs is combined with CCS if available (Rose et al., 2014a) <sup>[[#fn:r294|294]]</sup> . If CCS is unavailable, bioenergy use remains largely unchanged or even increases due to the high value of bioenergy for the energy transformation (Bauer et al., 2018) <sup>[[#fn:r295|295]]</sup> . As land impacts are tied to bioenergy use, the exclusion of BECCS from the mitigation portfolio will not automatically remove the trade-offs with food, water and other sustainability objectives due to the continued and potentially increased use of bioenergy.

IAMs assume bioenergy to be supplied mostly from second generation biomass feedstocks such as dedicated cellulosic crops (for example ''Miscanthus'' or poplar) as well as agricultural and forest residues. Detailed process IAMs include land-use models that capture competition for land for different uses (food, feed, fiber, bioenergy, carbon storage, biodiversity protection) under a range of dynamic factors including socio-economic drivers, productivity increases in crop and livestock systems, food demand, and land, environmental, biodiversity, and carbon policies. Assumptions about these factors can vary widely between different scenarios (Calvin et al., 2014; Popp et al., 2017; van Vuuren et al., 2018) <sup>[[#fn:r296|296]]</sup> . IAMs capture a number of potential environmental impacts from bioenergy production, in particular indirect land-use change emissions from land conversion and nitrogen and water use for bioenergy production (Kraxner et al., 2013; Bodirsky et al., 2014; Bonsch et al., 2014; Obersteiner et al., 2016; Humpenöder et al., 2018) <sup>[[#fn:r297|297]]</sup> . The impact of bioenergy production on soil degradation is an area of active IAM development and was not comprehensively accounted for in the mitigation pathways assessed in this report (but is, for example, in Frank et al., 2017) <sup>[[#fn:r298|298]]</sup> . Whether bioenergy has large adverse impacts on environmental and societal goals depends in large parts on the governance of land use (Haberl et al., 2013; Erb et al., 2016b; Obersteiner et al., 2016; Humpenöder et al., 2018) <sup>[[#fn:r299|299]]</sup> . Here IAMs often make idealized assumptions about effective land management, such as full protection of the land carbon stock by conservation measures and a global carbon price, respectively, but variations on these assumptions have also been explored (Calvin et al., 2014; Popp et al., 2014a) <sup>[[#fn:r300|300]]</sup> .

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==== 2.3.4.2 Sustainability implications of CDR deployment in 1.5°C pathways ====

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Strong concerns about the sustainability implications of large-scale CDR deployment in deep mitigation pathways have been raised in the literature (Williamson and Bodle, 2016; Boysen et al., 2017b; Dooley and Kartha, 2018; Heck et al., 2018) <sup>[[#fn:r301|301]]</sup> , and a number of important knowledge gaps have been identified (Fuss et al., 2016) <sup>[[#fn:r302|302]]</sup> . An assessment of the literature on implementation constraints and sustainable development implications of CDR measures is provided in Chapter 4, Section 4.3.7 and the Cross-chapter Box 7 in Chapter 3. An initial discussion of potential environmental side effects of CDR deployment in 1.5°C-consistent pathways is provided in this section. Chapter 4, Section 4.3.7 then contrasts CDR deployment in 1.5°C-consistent pathways with other branches of literature on limitations of CDR. Integrated modelling aims to explore a range of developments compatible with specific climate goals and often does not include the full set of broader environmental and societal concerns beyond climate change. This has given rise to the concept of sustainable development pathways (Cross-Chapter Box 1 in Chapter 1) (van Vuuren et al., 2015) <sup>[[#fn:r303|303]]</sup> , and there is an increasing body of work to extend integrated modelling to cover a broader range of sustainable development goals (Section 2.6). However, only some of the available 1.5°C-consistent pathways were developed within a larger sustainable development context  (Bertram et al., 2018; Grubler et al., 2018; Rogelj et al., 2018; van Vuuren et al., 2018) <sup>[[#fn:r304|304]]</sup> . As discussed in Section 2.3.4.1, those pathways are characterized by low energy and/or food demand effectively limiting fossil-fuel substitution and alleviating land competition, respectively. They also include regulatory policies for deepening early action and ensuring environmental protection (Bertram et al., 2018) <sup>[[#fn:r305|305]]</sup> . Overall sustainability implications of 1.5°C-consistent pathways are assessed in Section 2.5.3 and Chapter 5, Section 5.4.

Individual CDR measures have different characteristics and therefore would carry different risks for their sustainable deployment at scale (Smith et al., 2015) <sup>[[#fn:r306|306]]</sup> . Terrestrial CDR measures, BECCS and enhanced weathering of rock powder distributed on agricultural lands require land. Those land-based measures could have substantial impacts on environmental services and ecosystems (Cross-Chapter Box 7 in Chapter 3) (Smith and Torn, 2013; Boysen et al., 2016; Heck et al., 2016; Krause et al., 2017) <sup>[[#fn:r307|307]]</sup> . Measures like afforestation and bioenergy with and without CCS that directly compete with other land uses could have significant impacts on agricultural and food systems (Creutzig et al., 2012, 2015; Calvin et al., 2014; Popp et al., 2014b, 2017; Kreidenweis et al., 2016; Boysen et al., 2017a; Frank et al., 2017; Stevanović et al., 2017; Strapasson et al., 2017; Humpenöder et al., 2018) <sup>[[#fn:r308|308]]</sup> . BECCS using dedicated bioenergy crops could substantially increase agricultural water demand (Bonsch et al., 2014; Séférian et al., 2018) <sup>[[#fn:r309|309]]</sup> and nitrogen fertilizer use (Bodirsky et al., 2014) <sup>[[#fn:r310|310]]</sup> . DACCS and BECCS rely on CCS and would require safe storage space in geological formations, including management of leakage risks (Pawar et al., 2015) <sup>[[#fn:r311|311]]</sup> and induced seismicity (Nicol et al., 2013) <sup>[[#fn:r312|312]]</sup> . Some approaches like DACCS have high energy demand (Socolow et al., 2011) <sup>[[#fn:r313|313]]</sup> . Most of the CDR measures currently discussed could have significant impacts on either land, energy, water, or nutrients if deployed at scale (Smith et al., 2015) <sup>[[#fn:r314|314]]</sup> . However, actual trade-offs depend on a multitude factors (Haberl et al., 2011; Erb et al., 2012; Humpenöder et al., 2018) <sup>[[#fn:r315|315]]</sup> , including the modalities of CDR deployment (e.g., on marginal vs. productive land) (Bauer et al., 2018) <sup>[[#fn:r316|316]]</sup> , socio-economic developments (Popp et al., 2017) <sup>[[#fn:r317|317]]</sup> , dietary choices (Stehfest et al., 2009; Popp et al., 2010; van Sluisveld et al., 2016; Weindl et al., 2017; van Vuuren et al., 2018) <sup>[[#fn:r318|318]]</sup> , yield increases, livestock productivity and other advances in agricultural technology (Havlik et al., 2013; Valin et al., 2013; Havlík et al., 2014; Weindl et al., 2015; Erb et al., 2016b) <sup>[[#fn:r319|319]]</sup> , land policies (Schmitz et al., 2012; Calvin et al., 2014; Popp et al., 2014a) <sup>[[#fn:r320|320]]</sup> , and governance of land use (Unruh, 2011; Buck, 2016; Honegger and Reiner, 2018) <sup>[[#fn:r321|321]]</sup> .

Figure 2.11 shows the land requirements for BECCS and afforestation in the selected 1.5°C-consistent pathway archetypes, including the LED (Grubler et al., 2018) <sup>[[#fn:r322|322]]</sup> and S1 pathways (Fujimori, 2017; Rogelj et al., 2018) <sup>[[#fn:r323|323]]</sup> following a sustainable development paradigm. As discussed, these land-use patterns are heavily influenced by assumptions about, among other things, future population levels, crop yields, livestock production systems, and food and livestock demand, which all vary between the pathways (Popp et al., 2017) <sup>[[#fn:r324|324]]</sup> (Section 2.3.1.1). In pathways that allow for large-scale afforestation in addition to BECCS, land demand for afforestation can be larger than for BECCS (Humpenöder et al., 2014) <sup>[[#fn:r325|325]]</sup> . This follows from the assumption in the modelled pathways that, unlike bioenergy crops, forests are not harvested to allow unabated carbon storage on the same patch of land. If wood harvest and subsequent processing or burial are taken into account, this finding can change. There are also synergies between the various uses of land, which are not reflected in the depicted pathways. Trees can grow on agricultural land (Zomer et al., 2016) <sup>[[#fn:r326|326]]</sup> , and harvested wood can be used with BECCS and pyrolysis systems (Werner et al., 2018) <sup>[[#fn:r327|327]]</sup> . The pathways show a very substantial land demand for the two CDR measures combined, up to the magnitude of the current global cropland area. This is achieved in IAMs in particular by a conversion of pasture land freed by intensification of livestock production systems, pasture intensification and/or demand changes (Weindl et al., 2017) <sup>[[#fn:r328|328]]</sup> , and to a more limited extent, cropland for food production, as well as expansion into natural land. However, pursuing such large-scale changes in land use would pose significant food supply, environmental and governance challenges, concerning both land management and tenure (Unruh, 2011; Erb et al., 2012, 2016b; Haberl et al., 2013; Haberl, 2015; Buck, 2016) <sup>[[#fn:r329|329]]</sup> , particularly if synergies between land uses, the relevance of dietary changes for reducing land demand, and co-benefits with other sustainable development objectives are not fully recognized. A general discussion of the land-use transformation in 1.5°C-consistent pathways is provided in Section 2.4.4.

An important consideration for CDR which moves carbon from the atmosphere to the geological, oceanic or terrestrial carbon pools is the permanence of carbon stored in these different pools (Matthews and Caldeira, 2008; NRC, 2015; Fuss et al., 2016; Jones et al., 2016) <sup>[[#fn:r330|330]]</sup> (see also Chapter 4, Section 4.3.7 for a discussion). Terrestrial carbon can be returned to the atmosphere on decadal time scales by a variety of mechanisms, such as soil degradation, forest pest outbreaks and forest fires, and therefore requires careful consideration of policy frameworks to manage carbon storage, for example, in forests (Gren and Aklilu, 2016) <sup>[[#fn:r331|331]]</sup> . There are similar concerns about outgassing of CO <sub>2</sub> from ocean storage (Herzog et al., 2003) <sup>[[#fn:r332|332]]</sup> , unless it is transformed to a substance that does not easily exchange with the atmosphere, for example, ocean alkalinity or buried marine biomass (Rau, 2011) <sup>[[#fn:r333|333]]</sup> . Understanding of the assessment and management of the potential risk of CO <sub>2</sub> release from geological storage of CO <sub>2</sub> has improved since the IPCC Special Report on Carbon Dioxide Capture and Storage (IPCC, 2005) <sup>[[#fn:r334|334]]</sup> with experience and the development of management practices in geological storage projects, including risk management to prevent sustentative leakage (Pawar et al., 2015) <sup>[[#fn:r335|335]]</sup> . Estimates of leakage risk have been updated to include scenarios of unregulated drilling and limited wellbore integrity (Choi et al., 2013) <sup>[[#fn:r336|336]]</sup> and find that about 70% of stored CO <sub>2</sub> would still be retained after 10,000 years in these circumstances (Alcalde et al., 2018) <sup>[[#fn:r337|337]]</sup> . The literature on the potential environmental impacts from the leakage of CO <sub>2</sub> – and approaches to minimize these impacts should a leak occur – has also grown and is reviewed by Jones et al. (2015) <sup>[[#fn:r338|338]]</sup> . To the extent that non-permanence of terrestrial and geological carbon storage is driven by socio-economic and political factors, there are parallels to questions of fossil-fuel reservoirs remaining in the ground (Scott et al., 2015) <sup>[[#fn:r339|339]]</sup> .

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'''Land-use changes in 2050 and 2100 in the illustrative 1.5°C-consistent pathway archetypes.'''
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[[File:8c674c48ea97cf8131c4724563a33782 Figure-2.11-1024x408.jpg]]

Land-use changes in 2050 and 2100 in the illustrative 1.5°C-consistent pathway archetypes (Fricko et al., 2017; Fujimori, 2017; Kriegler et al., 2017; Grubler et al., 2018; Rogelj et al., 2018) <sup>[[#fn:r340|340]]</sup> . Changes in land for food crops, energy crops, forest, pasture and other natural land are shown, compared to 2010.

Original Creation for this Report using IAMC 1.5°C Scenario Data hosted by IIASA

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=== 2.3.5 Implications of Near-Term Action in 1.5°C Pathways ===

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Less CO <sub>2</sub> emission reductions in the near term would require steeper and deeper reductions in the longer term in order to meet specific warming targets afterwards (Riahi et al., 2015; Luderer et al., 2016a) <sup>[[#fn:r341|341]]</sup> . This is a direct consequence of the quasi-linear relationship between the total cumulative amount of CO <sub>2</sub> emitted into the atmosphere and global mean temperature rise (Matthews et al., 2009; Zickfeld et al., 2009; Collins et al., 2013; Knutti and Rogelj, 2015) <sup>[[#fn:r342|342]]</sup> . Besides this clear geophysical trade-off over time, delaying GHG emissions reductions over the coming years also leads to economic and institutional lock-in into carbon-intensive infrastructure, that is, the continued investment in and use of carbon-intensive technologies that are difficult or costly to phase-out once deployed (Unruh and Carrillo-Hermosilla, 2006; Jakob et al., 2014; Erickson et al., 2015; Steckel et al., 2015; Seto et al., 2016; Michaelowa et al., 2018) <sup>[[#fn:r343|343]]</sup> . Studies show that to meet stringent climate targets despite near-term delays in emissions reductions, models prematurely retire carbon-intensive infrastructure, in particular coal without CCS (Bertram et al., 2015a; Johnson et al., 2015) <sup>[[#fn:r344|344]]</sup> . The AR5 reports that delaying mitigation action leads to substantially higher rates of emissions reductions afterwards, a larger reliance on CDR technologies in the long term, and higher transitional and long-term economic impacts (Clarke et al., 2014) <sup>[[#fn:r345|345]]</sup> . The literature mainly focuses on delayed action until 2030 in the context of meeting a 2°C goal (den Elzen et al., 2010; van Vuuren and Riahi, 2011; Kriegler et al., 2013b; Luderer et al., 2013, 2016a; Rogelj et al., 2013b; Riahi et al., 2015; OECD/IEA and IRENA, 2017) <sup>[[#fn:r346|346]]</sup> . However, because of the smaller carbon budget consistent with limiting warming to 1.5°C and the absence of a clearly declining long-term trend in global emissions to date, these general insights apply equally, or even more so, to the more stringent mitigation context of 1.5°C-consistent pathways. This is further supported by estimates of committed emissions due to fossil fuel-based infrastructure (Seto et al., 2016; Edenhofer et al., 2018) <sup>[[#fn:r347|347]]</sup> .

All available 1.5°C pathways that explore consistent mitigation action from 2020 onwards peak global Kyoto-GHG emissions in the next decade and already decline Kyoto-GHG emissions to below 2010 levels by 2030. The near-term emissions development in these pathways can be compared with estimated emissions in 2030 implied by the Nationally Determined Contributions (NDCs) submitted by Parties to the Paris Agreement (Figure 2.12). Altogether, the unconditional (conditional) NDCs are assessed to result in global Kyoto-GHG emissions on the order of 52–58 (50–54) GtCO <sub>2</sub> e yr <sup>−1</sup> in 2030 (e.g., den Elzen et al., 2016; Fujimori et al., 2016; UNFCCC, 2016; Rogelj et al., 2017; Rose et al., 2017b; Benveniste et al., 2018; Vrontisi et al., 2018 <sup>[[#fn:r348|348]]</sup> ; see Cross-Chapter Box 11 in Chapter 4 for detailed assessment). In contrast, 1.5°C pathways with limited overshoot available to this assessment show an interquartile range of about 26–31 (median 28) GtCO <sub>2</sub> e yr <sup>−1</sup> in 2030 <sup>[[#fn:5|5]]</sup> (Table 2.4, Section 2.3.3). Based on these ranges, this report assesses the emissions gap for a two-in-three chance of limiting warming to 1.5°C to be 26 (19–29) and 28 (22–33) GtCO <sub>2</sub> e (median and interquartile ranges) for conditional and unconditional NDCs, respectively (Cross-Chapter Box 11, applying GWP-100 values from the IPCC Second Assessment Report).

The later emissions peak and decline, the more CO <sub>2</sub> will have accumulated in the atmosphere. Peak cumulated CO <sub>2</sub> emissions – and consequently peak temperatures – increase with higher 2030 emissions levels (Figure 2.12). Current NDCs (Cross-Chapter Box 11 in Chapter 4) are estimated to lead to CO <sub>2</sub> emissions of about 400–560 GtCO <sub>2</sub> from 2018 to 2030 (Rogelj et al., 2016a) <sup>[[#fn:r349|349]]</sup> . Available 1.5°C- and 2°C-consistent pathways with 2030 emissions in the range estimated for the NDCs rely on an assumed swift and widespread deployment of CDR after 2030, and show peak cumulative CO <sub>2</sub> emissions from 2018 of about 800–1000 GtCO <sub>2</sub> , above the remaining carbon budget for a one-in-two chance of remaining below 1.5°C. These emissions reflect that no pathway is able to project a phase-out of CO <sub>2</sub> emissions starting from year-2030 NDC levels of about 40 GtCO <sub>2</sub> yr <sup>−1</sup> (Fawcett et al., 2015; Rogelj et al., 2016a) <sup>[[#fn:r350|350]]</sup> to net zero in less than about 15 years. Based on the implied emissions until 2030, the high challenges of the assumed post-2030 transition, and the assessment of carbon budgets in Section 2.2.2, global warming is assessed to exceed 1.5°C if emissions stay at the levels implied by the NDCs until 2030 (Figure 2.12). The chances of remaining below 1.5°C in these circumstances remain conditional upon geophysical properties that are uncertain, but these Earth system response uncertainties would have to serendipitously align beyond current median estimates in order for current NDCs to become consistent with limiting warming to 1.5°C.

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Median global warming estimated by MAGICC (panel a) and peak cumulative  CO <sub>2 </sub> emissions (panel b) in 1.5°C-consistent pathways in the SR1.5 scenario database, as a function of  CO <sub>2</sub> -equivalent emissions (based on AR4 GWP-100) of Kyoto-GHGs in 2030.
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[[File:5f6c3b2e205a2b1e9a5f1c12d1fd3c06 Figure-2.12-1024x515.jpg]]

Pathways that were forced to go through the NDCs or a similarly high emissions point in 2030 by design are highlighted by yellow marker edges (see caption of Figure 2.13 and text for further details on the design of these pathways). The combined range of global Kyoto-GHG emissions in 2030 for the conditional and unconditional NDCs assessed in Cross-Chapter Box 11 is shown by the grey shaded area (adjusted to AR4 GWPs for comparison). As a second line of evidence, peak cumulative CO <sub>2</sub> emissions derived from a 1.5°C pathway sensitivity analysis (Kriegler et al., 2018b) <sup>[[#fn:r351|351]]</sup> are shown by grey circles in the right-hand panel. Circles show gross fossil-fuel and industry emissions of the sensitivity cases, increased by assumptions about the contributions from AFOLU (5 GtCO <sub>2</sub> yr−1 until 2020, followed by a linear phase out until 2040) and non-CO <sub>2</sub> Kyoto-GHGs (median non-CO <sub>2</sub> contribution from 1.5°C-consistent pathways available in the database: 10 GtCO <sub>2</sub> e yr <sup>−1</sup> in 2030), and reduced by assumptions about CDR deployment until the time of net zero CO <sub>2</sub> emissions (limiting case for CDR deployment assumed in (Kriegler et al., 2018b) <sup>[[#fn:r352|352]]</sup> (logistic growth to 1, 4, 10 GtCO <sub>2</sub> yr <sup>−1</sup> in 2030, 2040, and 2050, respectively, leading to approximately 100 GtCO <sub>2</sub> of CDR by mid-century).

Original Creation for this Report using IAMC 1.5°C Scenario Data hosted by IIASA and Sensitivity cases from Kriegler et al. (2018), doi: 10.1098/rsta.2016.0457

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It is unclear whether following NDCs until 2030 would still allow global mean temperature to return to 1.5°C by 2100 after a temporary overshoot, due to the uncertainty associated with the Earth system response to net negative emissions after a peak (Section 2.2). Available IAM studies are working with reduced-form carbon cycle–climate models like MAGICC, which assume a largely symmetric Earth-system response to positive and net negative CO <sub>2</sub> emissions. The IAM findings on returning warming to 1.5°C from NDCs after a temporary temperature overshoot are hence all conditional on this assumption. Two types of pathways with 1.5°C-consistent action starting in 2030 have been considered in the literature (Luderer et al., 2018) <sup>[[#fn:r353|353]]</sup> (Figure 2.13): pathways aiming to obtain the same end-of-century carbon budget as 1.5°C-consistent pathways starting in 2020 despite higher emissions until 2030, and pathways assuming the same mitigation stringency after 2030 as in 1.5°C-consistent pathways starting in 2020 (approximated by using the same global price of emissions as found in least-cost pathways starting from 2020). An IAM comparison study found increasing challenges to implementing pathways with the same end-of-century carbon budgets after following NDCs until 2030 (Luderer et al., 2018) <sup>[[#fn:r354|354]]</sup> . The majority of model experiments (four out of seven) failed to produce NDC pathways that would return cumulative CO <sub>2</sub> emissions over the 2016–2100 period to 200 GtCO <sub>2</sub> , indicating limitations to the availability and timing of CDR. The few such pathways that were identified show highly disruptive features in 2030 (including abrupt transitions from moderate to very large emissions reduction and low carbon energy deployment rates) indicating a high risk that the required post-2030 transformations are too steep and abrupt to be achieved by the mitigation measures in the models ( ''high confidence'' ). NDC pathways aiming for a cumulative 2016–2100 CO <sub>2</sub> emissions budget of 800 GtCO <sub>2</sub> were more readily obtained (Luderer et al., 2018) <sup>[[#fn:r355|355]]</sup> , and some were classified as 1.5°C-high-OS pathways in this assessment (Section 2.1).

NDC pathways that apply a post-2030 price of emissions as found in least-cost pathways starting from 2020 show infrastructural carbon lock-in as a result of following NDCs instead of least-cost action until 2030. A key finding is that carbon lock-ins persist long after 2030, with the majority of additional CO <sub>2</sub> emissions occurring during the 2030–2050 period. Luderer et al. (2018) <sup>[[#fn:r356|356]]</sup> find 90 (80–120) GtCO <sub>2</sub> additional emissions until 2030, growing to 240 (190–260) GtCO <sub>2</sub> by 2050 and 290 (200–200) GtCO <sub>2</sub> by 2100. As a result, peak warming is about 0.2°C higher and not all of the modelled pathways return warming to 1.5°C by the end of the century. There is a four sided trade-off between (i) near-term ambition, (ii) degree of overshoot, (iii) transitional challenges during the 2030–2050 period, and (iv) the amount of CDR deployment required during the century (Figure 2.13) (Holz et al., 2018b; Strefler et al., 2018b) <sup>[[#fn:r357|357]]</sup> . Transition challenges, overshoot, and CDR requirements can be significantly reduced if global emissions peak before 2030 and fall below levels in line with current NDCs by 2030. For example, Strefler et al. (2018b) <sup>[[#fn:r358|358]]</sup> find that CDR deployment levels in the second half of the century can be halved in 1.5°C-consistent pathways with similar CO <sub>2</sub> emissions reductions rates during the 2030–2050 period if CO <sub>2</sub> emissions by 2030 are reduced by an additional 30% compared to NDC levels. Kriegler et al. (2018a) <sup>[[#fn:r359|359]]</sup> investigate a global rollout of selected regulatory policies and moderate carbon pricing policies. They show that additional reductions of about 10 GtCO <sub>2</sub> e yr <sup>−1</sup> can be achieved in 2030 compared to the current NDCs. Such a 20% reduction of year-2030 emissions compared to current NDCs would effectively lower the disruptiveness of post-2030 action. The strengthening of short-term policies in deep mitigation pathways has hence been identified as a way of bridging options to keep the Paris climate goals within reach (Bertram et al., 2015b; IEA, 2015a; Spencer et al., 2015; Kriegler et al., 2018a) <sup>[[#fn:r360|360]]</sup> .

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'''Figure 2.13'''

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Comparison of 1.5°C-consistent pathways starting action as of 2020 (A; light-blue diamonds) with pathways following the NDCs until 2030 and aiming to limit warming to 1.5°C thereafter.
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[[File:58d9874253b3e5eb1562ecd3fe2c88cc Figure-2.13-858x1024.jpg]]

The 1.5°C pathways that follow the NDCs until 2030 either aim for the same cumulative CO <sub>2</sub> emissions by 2100 as the pathways that start action as of 2020 (B; red diamonds) or assume the same mitigation stringency as reflected by the price of emissions in associated least-cost 1.5°C-consistent pathways starting from 2020 (P; black diamonds). Panels show (a) the underlying emissions pathways, (b) additional warming in the delay scenarios compared to 2020 action case, (c) cumulated CDR, (d) CDR ramp-up rates, (e) cumulated gross CO <sub>2</sub> emissions from fossil-fuel combustion and industrial (FFI) processes over the 2018–2100 period, and (f) gross FFI CO <sub>2</sub> emissions reductions rates. Scenario pairs or triplets (circles and diamonds) with 2020 and 2030 action variants were calculated by six (out of seven) models in the ADVANCE study symbols (Luderer et al., 2018) <sup>[[#fn:r361|361]]</sup> and five of them (passing near-term plausibility checks) are shown by symbols. Only two of five models could identify pathways with post-2030 action leading to a 2016–2100 carbon budget of about 200 GtCO <sub>2</sub> (red). The range of all 1.5°C pathways with no and low overshoot is shown by the boxplots.

Original Creation for this Report using IAMC 1.5°C Scenario Data hosted by IIASA

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