Editing IPCC:AR6/WGIII/Chapter-7 (section)

==== 7.4.1.3 Overview of Global and Regional Technical and Economic Potentials in AFOLU ====

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'''IPCC AR5 (2014).''' In the AR5, the economic mitigation potential of supply-side measures in the AFOLU sector was estimated at 7.18–10.60 GtCO 2 -eq yr –1 in 2030 with carbon prices up to USD100 tCO 2 -eq –1 , about a third of which could be achieved at &lt;USD20 tCO 2 -eq –1 ( ''medium evidence'' , ''medium agreement'' ) (Smith et al. 2014). The AR5 provided a summary table of individual AFOLU mitigation measures, but did not conduct a detailed assessment for each.

'''IPCC SRCCL (2019).''' The SRCCL assessed the full range of technical, economic and sustainability mitigation potentials in AFOLU for the period 2030–2050 and identified reduced deforestation and forest degradation to have greatest potential for reducing supply-side emissions (0.4 to 5.8 GtCO 2 -eq yr –1 ) ( ''high confidence'' ) followed by combined agriculture measures, 0.3 to 3.4 GtCO 2 -eq yr –1 ( ''medium confidence'' ) ( [[#Jia--2019|Jia et al. 2019]] ). For the demand-side estimates, shifting towards healthy, sustainable diets (0.7 to 8.0 GtCO 2 -eq yr –1 ) ( ''high confidence'' ) had the highest potential, followed by reduced food loss and waste (0.8 to 4.5 GtCO 2 -eq yr –1 ) ( ''high confidence'' ). Measures with greatest potential for CDR were afforestation/reforestation (0.5 to 10.1 GtCO 2 -eq yr –1 ) ( ''medium confidence'' ), soil carbon sequestration in croplands and grasslands (0.4 to 8.6 GtCO 2 -eq yr –1 ) ( ''medium confidence'' ) and BECCS (0.4 to 11.3 GtCO 2 -eq yr –1 ) ( ''medium confidence'' ). The SRCCL did not explore regional potential, associated feasibility nor provide detailed analysis of costs.

'''IPCC AR6.''' This assessment concludes the likely range of global land-based mitigation potential is approximately 8–14 GtCO 2 -eq yr –1 between 2020–2050 with carbon prices up to USD100 tCO 2 -eq –1 , about half of the technical potential ( ''medium evidence'' , ''medium agreement'' ). About 30–50% could be achieved &lt;USD20 tCO 2 -eq –1 (Table 7.3). The global economic potential estimates in this assessment are slightly higher than the AR5 range. Since AR5, there have been numerous new global assessments of sectoral land-based mitigation potential ( [[#Fuss--2018|Fuss et al. 2018]] ; [[#Griscom--2017|Griscom et al. 2017]] , 2020; [[#Roe--2019|Roe et al. 2019]] ; [[#Jia--2019|Jia et al. 2019]] ; [[#Griscom--2020|Griscom et al. 2020]] ; [[#Roe--2021|Roe et al. 2021]] ) as well as IAM estimates of mitigation potential ( [[#Riahi--2017|Riahi et al. 2017]] ; [[#Popp--2017|Popp et al. 2017]] ; [[#Rogelj--2018a|Rogelj et al. 2018a]] ; [[#Frank--2019|Frank et al. 2019]] ; [[#Johnston--2019|Johnston and Radeloff 2019]] ; [[#Baker--2019|Baker et al. 2019]] ), expanding the scope of AFOLU mitigation measures included and substantially improving the robustness and spatial resolution of mitigation estimates. A recent development is an assessment of country-level technical and economic (USD100 tCO 2 -eq –1 ) mitigation potential for 20 AFOLU measures, including for demand-side and soil organic carbon sequestration in croplands and grasslands, not estimated before ( [[#Roe--2021|Roe et al. 2021]] ). Estimates on costs, feasibility, sustainability, benefits, and risks have also been developed for some mitigation measures, and they continue to be active areas of research. Developing more refined sustainable potentials at a country-level will be an important next step. Although most mitigation estimates still do not consider the impact of future climate change, there are some emerging studies that do ( [[#Sonntag--2016|Sonntag et al. 2016]] ; Doelman et al. 2019). Given the IPCC WG1 finding that the land sink is continuing to increase although its efficiency is decreasing with climate change, it will be critical to better understand how future climate will affect mitigation potentials, particularly from CDR measures.

Across global sectoral studies, the economic mitigation potential (up to USD100 tCO 2 -eq –1 ) of supply-side measures in AFOLU for the period 2020–2050 is 11.4 mean (5.6–19.8 full range) GtCO 2 -eq yr –1 , about 50% of the technical potential of 24.2 (4.9–58) GtCO 2 -eq yr –1 (Table 7.3). Adding 2.1 GtCO 2 -eq yr –1 from demand-side measures (accounting only for diverted agricultural production to avoid double counting with land-use change effects), total land-based mitigation potential up to USD100 tCO 2 -eq –1 is 13.6 (6.7–23.4) GtCO 2 -eq yr –1 . This estimate aligns with the most recent regional assessment ( [[#Roe--2021|Roe et al. 2021]] ), which found the aggregate global mitigation potential of supply and demand-side measures to be 13.8 ± 3.1 GtCO 2 -eq yr –1 up to USD100 tCO 2 -eq –1 for the period 2020–2050. Across integrated assessment models (IAMs), the economic potential for land-based mitigation (Agriculture, LULUCF and BECCS) for USD100 tCO 2 -eq –1 is 7.9 mean (4.1–17.3 range) GtCO 2 -eq yr –1 in 2050 (Table 7.3). We add the estimate for BECCS here to provide the full land-based potential, as IAMs optimise land allocation based on costs, which displaces land-based CDR activities for BECCS. Combining both IAM and sectoral approaches, the likely range is therefore 7.9–13.6 (rounded to 8–14) GtCO 2 -eq yr –1 up to USD100 tCO 2 -eq –1 between 2020–2050. Considering both IAM and sectoral economic potential estimates, land-based mitigation could have the capacity to make the AFOLU sector net negative in GHG emissions from 2036 (Figure 7.12), although there are highly variable mitigation strategies for how AFOLU potential can be deployed for achieving climate targets (Illustrative Mitigation Pathways in [[#7.5.5|Section 7.5.5]] ). Economic potential estimates, which reflect a public willingness to pay, may be more relevant for policy making compared with technical potentials which reflect a theoretical maximum that may not be feasible or sustainable.

Among the mitigation options, the protection, improved management, and restoration of forests and other ecosystems (wetlands, savannas and grasslands) have the largest potential to reduce emissions and/or sequester carbon at 7.3 (3.9–13.1) GtCO 2 -eq yr –1 (up to USD100 tCO 2 -eq –1 ), with measures that ‘protect’ having the single highest total mitigation and mitigation densities (mitigation per area) in AFOLU (Table 7.3 and Figure 7.11). Agriculture provides the second largest share of mitigation, with 4.1 (1.7–6.7) GtCO 2 -eq yr –1 potential (up to USD100 tCO 2 -eq –1 ), from soil carbon management in croplands and grasslands, agroforestry, biochar, rice cultivation, and livestock and nutrient management (Table 7.3 and Figure 7.11). Demand-side measures including shifting to sustainable healthy diets, reducing food waste, and improving wood products can mitigate 2.2 (1.1–3.6) GtCO 2 -eq yr –1 when accounting only for diverted agricultural production from diets and food waste to avoid double counting with measures in forests and other ecosystems (Table 7.3 and Figure 7.11). The potential of demand-side measures increases three-fold, to 6.5 (4–9.5) GtCO 2 -eq yr –1 when accounting for the entire value chain including land-use effects, but would overlap with other measures and is therefore not additive.

Most mitigation options are available and ready to deploy. Emissions reductions can be unlocked relatively quickly, whereas CDR need upfront investment to generate sequestration over time. The protection of natural ecosystems, carbon sequestration in agriculture, sustainable healthy diets and reduced food waste have especially high co-benefits and cost efficiency. Avoiding the conversion of carbon-rich primary peatlands, coastal wetlands and forests is particularly important as most carbon lost from those ecosystems are irrecoverable through restoration by the 2050 timeline of achieving net zero carbon emissions ( [[#Goldstein--2020|Goldstein et al. 2020]] ). Sustainable intensification, shifting diets, reducing food waste could enhance efficiencies and reduce agricultural land needs, and are therefore critical for enabling supply-side measures such as reduced deforestation, restoration, as well as reducing N 2 O and CH 4 emissions from agricultural production – as seen in the Illustrative Mitigation Pathway (IMP-SP) ( [[#7.5|Section 7.5]] .6). Although agriculture measures that reduce non-CO 2 , particularly of CH 4 , are important for near-term emissions reductions, they have less economic potential due to costs. Demand-side measures may be able to deliver non-CO 2 emissions reductions more cost efficiently.

Regionally, economic mitigation potential up to USD100 tCO 2 -eq –1 is estimated to be greatest in tropical countries in Asia and Pacific (34%), Latin America and the Caribbean (24%), and Africa and the Middle East (18%) because of the large potential from reducing deforestation and sequestering carbon in forests and agriculture (Figure 7.11). However, there is also considerable potential in Developed Countries (18%) and more modest potential in Eastern Europe and West-Central Asia (5%). These results are in line with the IAM regional mitigation potentials (Figure 7.11). The protection of forests and other ecosystems is the dominant source of mitigation potential in tropical regions, whereas carbon sequestration in agricultural land and demand-side measures are important in Developed Countries and Asia and Pacific. The restoration and management of forests and other ecosystems is more geographically distributed, with all regions having significant potential. Regions with large livestock herds (Developed Countries, Latin America) and rice paddy fields (Asia and Pacific) have potential to reduce CH 4 . As expected, the highest total potential is associated with countries and regions with large land areas, however when considering mitigation density (total potential per hectare), many smaller countries, particularly those with wetlands have disproportionately high levels of mitigation for their size ( [[#Roe--2021|Roe et al. 2021]] ). As global commodity markets connect regions, AFOLU measures may create synergies and trade-offs across the world, which could make national demand-side measures for example, important in mitigating supply-side emissions elsewhere (Kallio et al. 2018).

Although economic potentials provide more realistic, near-term climate mitigation compared to technical potentials, they still do not account for feasibility barriers and enabling conditions that vary by region and country. For example, according to most models, including IAMs, avoided deforestation is the cheapest land-based mitigation option (Table 7.3, Sections 7.5.3 and 7.5.4), however implementing interventions aimed at reducing deforestation (including REDD+) often have higher transaction and implementation costs than expected due to various barriers and enabling conditions ( [[#Luttrell--2018|Luttrell et al. 2018]] ) ( [[#7.6|Section 7.6]] ). The feasibility of implementing AFOLU mitigation measures, including those with multiple co-benefits, depends on varying economic, technological, institutional, socio-cultural, environmental and geophysical barriers ( ''high confidence'' ) (L.G. [[#Smith--2019|Smith et al. 2019]] ). The section for each individual mitigation measure provides an overview of co-benefits and risks associated with the measure and [[#7.6|Section 7.6]] .6 outlines key enabling factors and barriers for implementation.

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