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

==== 7.4.1.1 Estimating Mitigation Potentials ====

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Mitigation potentials for AFOLU measures are estimated by calculating the scale of emissions reductions or carbon sequestration against a counterfactual scenario without mitigation activities. The types of mitigation potential estimates in recent literature include: (i) technical potential (the biophysical potential or amount possible with current technologies); (ii) economic potential (constrained by costs, usually by a given carbon price (Table 7.3); (iii) sustainable potential (constrained by environmental safeguards and/or natural resources, e.g., limiting natural forest conversion), and (iv) feasible potential (constrained by environmental, socio-cultural, and/or institutional barriers), however, there are no set definitions used in literature. In addition to types of mitigation estimates, there are two AFOLU mitigation categories often calculated: supply-side measures (land management interventions) and demand-side measures (interventions that require a change in consumer behaviour).

'''Table 7.3 | Estimated annual mitigation potential (GtCO''' 2 '''-eq y''' '''r''' –1 ''') in''' '''2020–2050''' '''of AFOLU mitigation options by carbon price.''' Estimates reflect sectoral studies based on a comprehensive literature review updating data from ( [[#Roe--2019|Roe et al. 2019]] ) and integrated assessment models using the IPCC AR6 database ( [[#7.5|Section 7.5]] ). Values represent the mean, and full range of potential. Sectoral mitigation estimates are averaged for the years 2020–2050 to capture a wider range of literature, and the IAM estimates are given for 2050 as many model assumptions delay most land-based mitigation to mid-century. The sectoral potentials are the sum of global estimates for the individual measures listed for each option. IAM potentials are given for mitigation options with available data; for example, net land-use CO 2 for total forests and other ecosystems, and land sequestration from A/R, but not reduced deforestation (protect). Sectoral estimates predominantly use GWP100 IPCC AR5 values (CH 4 = 28, N 2 O = 265), although some use GWP100 IPCC AR4 values (CH 4 = 25, N 2 O = 298); and the IAMs use GWP100 IPCC AR6 values (CH 4 = 27, N 2 O = 273). The sectoral and IAM estimates reflected here do not account for the substitution effects of avoiding fossil fuel emissions nor emissions from other more energy intensive resources/materials. For example, BECCS estimates only consider the carbon dioxide removal (CDR) via geological storage component and not potential mitigation derived from the displacement of fossil fuel use in the energy sector. Mitigation potential from substitution effects are included in the other sectoral chapters like energy, transport, buildings and industry. The total AFOLU sectoral estimate aggregates potential from agriculture, forests and other ecosystems, and diverted agricultural production from avoided food waste and diet shifts (excluding land-use impacts to avoid double counting). Because of potential overlaps between measures, sectoral values from BECCS and the full value chain potential from demand-side measures are not summed with AFOLU. IAMs account for land competition and resource optimisation and can therefore sum across all available categories to derive the total AFOLU potential. Key: ND = no data; Sectoral = as assessed by sectoral literature review; IAM = as assessed by integrated assessment models; EJ = exajoule primary energy.

{| class="wikitable"
|-
! '''Mi''' '''tigation option'''

! '''Estimate type'''

! '''&lt;USD20 tCO''' 2 '''-eq''' –1

! '''&lt;USD50 tCO''' 2 '''-eq''' –1

! '''&lt;USD100''' '''tCO''' 2 '''-eq''' –1

! '''Technical'''

|-
| rowspan="2"| '''Agriculture total'''

| Sectoral

| 0.9 (0.5–1.4)

| 1.6 (1–2.4)

| 4.1 (1.7–6.7)

| 11.2 (1.6–28.5)

|-
| IAM

| 0.9 (0–3.1)

| 1.3 (0–3.2)

| 1.8 (0.7–3.3)

| ND

|-
| rowspan="2"| '''Agriculture – Carbon sequestration''' (Soil carbon management in croplands and grasslands, agroforestry, and biochar)

| Sectoral

| 0.5 (0.4–0.6)

| 1.2 (0.9–1.6)

| 3.4 (1.4–5.5)

| 9.5 (1.1–25.3)

|-
| IAM

| ND

| ND

| ND

| ND

|-
| rowspan="2"| '''Agriculture – Reduce CH''' 4 '''and N''' 2 '''O emissions''' (Improve enteric fermentation, manure management, nutrient management, and rice cultivation)

| Sectoral

| 0.4 (0.1–0.8)

| 0.4 (0.1–0.8)

| 0.6 (0.3–1.3)

| 1.7 (0.5–3.2)

|-
| IAM

| 0.9 (0–3.1)

| 1.3 (0–3.2)

| 1.8 (0.7–3.3)

| ND

|-
| rowspan="2"| '''Forests and other ecosystems total'''

| Sectoral

| 2.9 (2.2–3.5)

| 3.1 (1.4–5.1)

| 7.3 (3.9–13.1)

| 13 (5–29.5)

|-
| IAM

| 2.4 (0–10.5)

| 3.3 (0–9.9)

| 4.2 (0–12.1)

| ND

|-
| rowspan="2"| '''Forests and other ecosystems – Protect''' (Reduce deforestation, loss and degradation of peatlands, coastal wetlands, and grasslands)

| Sectoral

| 2.3 (1.7–2.9)

| 2.4 (1.2–3.6)

| 4.0 (2.5–7.4)

| 6.2 (2.8–14.4)

|-
| IAM

| ND

| ND

| ND

| ND

|-
| rowspan="2"| '''Forests and other ecosystems – Restore''' (Afforestation, reforestation, peatland restoration, coastal wetland restoration)

| Sectoral

| 0.15

| 0.7 (0.2–1.5)

| 2.1 (0.8–3.8)

| 5 (1.1–12.3)

|-
| IAM (A/R)

| 0.6 (0.2–6.5)

| 0.6 (0.01–8.3)

| 0.7 (0.07–6.8)

| ND

|-
| rowspan="2"| '''Forests and other ecosystems – Manage''' (Improve forest management, fire management)

| Sectoral

| 0.4 (0.3–0.4)

| ND

| 1.2 (0.6–1.9)

| 1.8 (1.1–2.8)

|-
| IAM

| ND

| ND

| ND

| ND

|-
| rowspan="2"| '''Demand-side measures''' (Shift to sustainable healthy diets, reduce food waste, and enhanced and improved use of wood products) ''* For all three only the direct avoided emissions; land-use effects are in measures above''

| Sectoral

| ND

| ND

| ''2.2 (1.1–3.6)*''

| ''4.2 (2.2–7.1)*''

|-
| IAM

| ND

| ND

| ND

| ND

|-
| rowspan="2"| '''BECCS''' (Only the CDR component, for example, the geological storage. Substitution effects are accounted in other sectoral chapters e.g: Energy (ch 6), Transport (ch 10))

| Sectoral

| ND

| ND

| 1.6 (0.5–3.5)

| 5.9 (0.5–11.3)

|-
| IAM

| 0.08 (0–0.7)

| 0.5 (0–6)

| 1.8 (0.2–9.9)

| ND

|-
| '''Bioenergy from residues'''

| Sectoral

| ND

| ND

| ND

| Up to 57 EJ yr –1

|-
| '''TOTAL AFOLU''' (Agriculture, forests and other ecosystems, diverted agricultural production from demand-side)

| Sectoral

| 3.8 (2.7–4.9)

| 4.3 (2.3–6.7)

| 13.6 (6.7–23.4)

| 28.4 (8.8–65.1)

|-
| '''TOTAL AFOLU''' (Agriculture, forests and other ecosystems, BECCS)

| IAM

| 3.4 (0–14.6)

| 5.3 (0.6–19.4)

| 7.9 (4.1–17.3)

| ND

|}

Two main approaches to estimating mitigation potentials include: (i) studies on individual measures and/or sectors – henceforth referred to as sectoral assessments, and (ii) integrated assessment models (IAM). Sectoral assessments include studies focusing on one activity (e.g., agroforestry) based on spatial and biophysical data, as well as econometric and optimisation models for a sector, for example, the forest or agriculture sector, and therefore cover a large suite of practices and activities while representing a broad body of literature. Sectoral assessments, however, rarely capture cross-sector interactions or impacts, making it difficult to completely account for land competition, trade-offs, and double counting when aggregating sectoral estimates across different studies and methods (Smith et al. 2014; [[#Jia--2019|Jia et al. 2019]] ). On the other hand, IAMs assess the climate impact of multiple and interlinked practices across sectors and therefore, can account for interactions and trade-offs (including land competition, use of other resources and international trade) between them. However, the number of land-based measures used in IAMs are limited compared with the sectoral portfolio (Figure 7.11). The resolution of land-based measures in IAMs are also generally coarser compared to some sectoral estimates, and as such, may be less robust for individual measures ( [[#Roe--2021|Roe et al. 2021]] ). Given the differences between and strengths and weaknesses of the two approaches, it is helpful to compare the estimates from both. We combine estimates from both approaches to establish an updated range of global land-based mitigation potential.

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[[File:2ad406a6ef1ac592127f53b23020298a IPCC_AR6_WGIII_Figure_7_11.png]]

'''Figure 7.11 | Global and regional mitigation potential (GtCO''' 2 '''-eq y''' '''r''' –1 ''')''' '''in''' '''2020–2050''' '''for 20 land-based measures.''' 2 '''-eq y''' '''r''' –1 ''')''' '''in''' '''2020–2050''' '''for 20 land-based measures.''' '''(a)''' Global estimates represent the mean (bar) and full range (error bars) of the economic potential (up to USD100 tCO 2 -eq –1 ) based on a comprehensive literature review of sectoral studies (references are outlined in the sub-section for each measure in Sections 7.4.2–7.4.5). Potential co-benefits and trade-offs for each of the 20 measures are summarised in icons. '''(b)''' Regional estimates illustrate the mean technical (T) and economic (E) (up to USD100 tCO 2 -eq –1 ) sectoral potential based on data from ( [[#Roe--2021|Roe et al. 2021]] ). IAM economic potential (M) (USD100 tCO 2 -eq –1 ) data is from the IPCC AR6 database.

For the 20 land-based mitigation measures outlined in this section, the mitigation potential estimates are largely derived from sectoral approaches, and where data is available, are compared to IAM estimates. Integrated assessment models and the emissions trajectories, cost-effectiveness and trade-offs of various mitigation pathways are detailed in [[#7.5|Section 7.5]] . It should be noted that the underlying literature for sectoral as well as IAM mitigation estimates consider GWP100 IPCC AR5 values (CH 4 = 28, N 2 O = 265) as well as GWP100 IPCC AR4 values (CH 4 = 25, N 2 O = 298) to convert CH 4 and N 2 O to CO 2 -eq. Where possible, we note the various GWP100 values (in IAM estimates, and the wetlands and agriculture sections), however in some instances, the varying GWP100 values used across studies prevents description of non-CO 2 gases in native units as well as conversion to AR6 GWP100 (CH 4 = 27, N 2 O = 273) CO 2 -eq values to aggregate sectoral assessment estimates.

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