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

==== 2.6.1.1 Land management in agriculture ====

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Reducing non-CO <sub>2</sub> emissions from agriculture through cropland nutrient management, enteric fermentation, manure management, rice cultivation and fertiliser production has a total mitigation potential of 0.30–3.38 GtCO <sub>2</sub> -eq yr <sup>–1</sup> ( ''medium confidence'' ) (combined sub-category measures in Figure 2.24, details below) with a further 0.25–6.78 GtCO <sub>2</sub> -eq yr <sup>–1</sup> from soil carbon management (Section 2.6.1.3). Other literature that looks at broader categories finds mitigation potential of 1.4–2.3 GtCO <sub>2</sub> -eq yr <sup>–1</sup> from improved cropland management (Smith et al. 2008 <sup>[[#fn:r1496|1496]]</sup> , 2014 <sup>[[#fn:r1497|1497]]</sup> ; Pradhan et al., 2013 <sup>[[#fn:r1498|1498]]</sup> ); 1.4–1.8 GtCO <sub>2</sub> -eq yr <sup>–1</sup> from improved grazing land management (Conant et al. 2017 <sup>[[#fn:r1499|1499]]</sup> ; Herrero et al. 2016 <sup>[[#fn:r1500|1500]]</sup> ; Smith et al. 2008 <sup>[[#fn:r1501|1501]]</sup> , 2014 <sup>[[#fn:r1502|1502]]</sup> ) and 0.2–2.4 GtCO <sub>2</sub> -eq yr <sup>–1</sup> from improved livestock management (Smith et al. 2008 <sup>[[#fn:r1503|1503]]</sup> , 2014 <sup>[[#fn:r1504|1504]]</sup> ; Herrero et al. 2016 <sup>[[#fn:r1505|1505]]</sup> , FAO 2007 <sup>[[#fn:r1506|1506]]</sup> ). Detailed discussions of the mitigation potential of agricultural response options and their co-benefits are provided in Chapter 5 and Sections 5.5 and 5.6.

The three main measures to reduce enteric fermentation include improved animal diets (higher quality, more digestible livestock feed), supplements and additives (reduce methane by changing the microbiology of the rumen), and animal management and breeding (improve husbandry practices and genetics). Applying these measures can mitigate 0.12–1.18 GtCO <sub>2</sub> -eq yr <sup>–1</sup> ( ''medium confidence'' ) (Hristov et al. 2013 <sup>[[#fn:r1507|1507]]</sup> ; Dickie et al. 2014 <sup>[[#fn:r1508|1508]]</sup> ; Herrero et al. 2016 <sup>[[#fn:r1509|1509]]</sup> ; Griscom et al. 2017 <sup>[[#fn:r1510|1510]]</sup> ). However, these measures may have limitations such as need of crop-based feed (Pradhan et al. 2013 <sup>[[#fn:r1511|1511]]</sup> ) and associated ecological costs, toxicity and animal welfare issues related to food additives (Llonch et al. 2017 <sup>[[#fn:r1512|1512]]</sup> ). Measures to manage manure include anaerobic digestion for energy use, composting as a nutrient source, reducing storage time and changing livestock diets, and have a potential of 0.01–0.26 GtCO <sub>2</sub> -eq yr <sup>–1</sup> (Herrero et al. 2016 <sup>[[#fn:r1513|1513]]</sup> ; Dickie et al. 2014 <sup>[[#fn:r1514|1514]]</sup> ).

On croplands, there is a mitigation potential of 0.03–0.71 GtCO <sub>2</sub> -eq yr <sup>–1</sup> for cropland nutrient management (fertiliser application) ( ''medium confidence'' ) (Griscom et al. 2017 <sup>[[#fn:r1515|1515]]</sup> ; Hawken 2017 <sup>[[#fn:r1516|1516]]</sup> ; Paustian et al. 2016 <sup>[[#fn:r1517|1517]]</sup> ; Dickie et al. 2014 <sup>[[#fn:r1518|1518]]</sup> ; Beach et al. 2015 <sup>[[#fn:r1519|1519]]</sup> ). Reducing emissions from rice production through improved water management (periodic draining of flooded fields to reduce methane emissions from anaerobic decomposition) and straw residue management (applying in dry conditions instead of on flooded fields and avoiding burning to reduce methane and N2O emissions) has the potential to mitigate up to 60% of emissions (Hussain et al. 2015 <sup>[[#fn:r1520|1520]]</sup> ), or 0.08–0.87 GtCO <sub>2</sub> -eq yr <sup>–1</sup> ( ''medium confidence'' ) (Griscom et al. 2017 <sup>[[#fn:r1521|1521]]</sup> ; Hawken 2017 <sup>[[#fn:r1522|1522]]</sup> ; Paustian et al. 2016 <sup>[[#fn:r1523|1523]]</sup> ; Hussain et al. 2015 <sup>[[#fn:r1524|1524]]</sup> ; Dickie et al. 2014 <sup>[[#fn:r1525|1525]]</sup> ; Beach et al. 2015 <sup>[[#fn:r1526|1526]]</sup> ). Furthermore, sustainable intensification through the integration of crop and livestock systems can increase productivity, decrease emission intensity and act as a climate adaptation option (Section 5.5.1.4).

Agroforestry is a land management system that combines woody biomass (e.g., trees or shrubs) with crops and/or livestock). The mitigation potential from agroforestry ranges between 0.08–5.7 GtCO <sub>2</sub> yr <sup>–1</sup> , ( ''medium confidence'' ) (Griscom et al. 2017 <sup>[[#fn:r1527|1527]]</sup> ; Dickie et al. 2014 <sup>[[#fn:r1528|1528]]</sup> ; Zomer et al. 2016 <sup>[[#fn:r1529|1529]]</sup> ; Hawken 2017 <sup>[[#fn:r1530|1530]]</sup> ). The high estimate is from an optimum scenario combing four agroforestry solutions (silvopasture, tree intercropping, multistrata agroforestry and tropical staple trees) of Hawken (2017a) <sup>[[#fn:r1531|1531]]</sup> . Zomer et al. (2016) <sup>[[#fn:r1532|1532]]</sup> reported that the trees in agroforestry landscapes had increased carbon stock by 7.33 GtCO <sub>2</sub> between 2000 and 2010, or 0.7 GtCO <sub>2</sub> yr <sup>–1</sup> (Section 5.5.1.3).

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'''Mitigation potential of response options in 2020–2050, measured in GtCO2-eq yr–1, adapted from Roe et al. (2017).Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability […]'''
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Mitigation potential of response options in 2020–2050, measured in GtCO <sub>2</sub> -eq yr <sup>–1</sup> , adapted from Roe et al. (2017).Mitigation potentials reflect the full range of low to high estimates from studies published after 2010, differentiated according to technical (possible with current technologies), economic (possible given economic constraints) and sustainable potential (technical or economic potential constrained by sustainability considerations). Medians are calculated across all potentials in categories with more than four data points. We only include references that explicitly provide mitigation potential estimates in CO <sub>2</sub> -eq yr <sup>–1</sup> (or a similar derivative) by 2050. Not all options for land management potentials are additive, as some may compete for land. Estimates reflect a range of methodologies (including definitions, global warming potentials and time horizons) that may not be directly comparable or additive. Results from IAMs are shown to compare with single option ‘bottom-up’ estimates, in available categories from the 2ºC and 1.5ºC scenarios in the SSP Database (version 2.0). The models reflect land management changes, yet in some instances, can also reflect demand-side effects from carbon prices, so may not be defined exclusively as ‘supply-side’. References: 1) Griscom et al. (2017) <sup>[[#fn:r2136|2136]]</sup> , 2) Hawken (2017) <sup>[[#fn:r2137|2137]]</sup> , 3) Paustian et al. (2016) <sup>[[#fn:r2138|2138]]</sup> , 4) Beach et al. (2016) <sup>[[#fn:r2139|2139]]</sup> , 5) Dickie et al. (2014) <sup>[[#fn:r2140|2140]]</sup> , 6) Herrero et al. (2013) <sup>[[#fn:r2141|2141]]</sup> , 7) Herrero et al. (2016) <sup>[[#fn:r2142|2142]]</sup> , 8) Hussain et al. (2015) <sup>[[#fn:r2143|2143]]</sup> , 9) Hristov, et al. (2013) <sup>[[#fn:r2144|2144]]</sup> , 10) Zhang et al. (2013) <sup>[[#fn:r2145|2145]]</sup> , 11) Houghton and Nassikas (2018) <sup>[[#fn:r2146|2146]]</sup> , 12) Busch and Engelmann (2017) <sup>[[#fn:r2147|2147]]</sup> , 13) Baccini et al. (2017) <sup>[[#fn:r2148|2148]]</sup> , 14) Zarin et al. (2016) <sup>[[#fn:r2149|2149]]</sup> , 15) Houghton, et al. (2015) <sup>[[#fn:r2150|2150]]</sup> , 16) Federici et al. (2015) <sup>[[#fn:r2151|2151]]</sup> , 17) Carter et al. (2015) <sup>[[#fn:r2152|2152]]</sup> , 18) Smith et al. (2013) <sup>[[#fn:r2153|2153]]</sup> , 19) Pearson et al. (2017) <sup>[[#fn:r2154|2154]]</sup> , 20) Hooijer et al. (2010) <sup>[[#fn:r2155|2155]]</sup> , 21) Howard (2017) <sup>[[#fn:r2156|2156]]</sup> , 22) Pendleton et al. (2012) <sup>[[#fn:r2157|2157]]</sup> , 23) Fuss et al. (2018) <sup>[[#fn:r2158|2158]]</sup> , 24) Dooley and Kartha (2018) <sup>[[#fn:r2159|2159]]</sup> , 25) Kreidenweis et al. (2016) <sup>[[#fn:r2160|2160]]</sup> , 26) Yan et al. (2017) <sup>[[#fn:r2161|2161]]</sup> , 27) Sonntag et al. (2016) <sup>[[#fn:r2162|2162]]</sup> , 28) Lenton (2014) <sup>[[#fn:r2163|2163]]</sup> , 29) McLaren (2012) <sup>[[#fn:r2164|2164]]</sup> , 30) Lenton (2010) <sup>[[#fn:r2165|2165]]</sup> , 31) Sasaki et al. (2016) <sup>[[#fn:r2166|2166]]</sup> , 32) Sasaki et al. (2012) <sup>[[#fn:r2167|2167]]</sup> , 33) Zomer et al. (2016) <sup>[[#fn:r2168|2168]]</sup> , 34) Couwenberg et al. (2010) <sup>[[#fn:r2169|2169]]</sup> , 35) Conant et al. (2017) <sup>[[#fn:r2170|2170]]</sup> , 36) Sanderman et al. (2017) <sup>[[#fn:r2171|2171]]</sup> , 37) Frank et al. (2017) <sup>[[#fn:r2172|2172]]</sup> , 38) Henderson et al. (2015) <sup>[[#fn:r2173|2173]]</sup> , 39) Sommer and Bossio (2014) <sup>[[#fn:r2174|2174]]</sup> , 40. Lal (2010) <sup>[[#fn:r2175|2175]]</sup> , 41. Zomer et al. (2017) <sup>[[#fn:r2176|2176]]</sup> , 42. Smith et al. (2016) <sup>[[#fn:r2177|2177]]</sup> , 43) Poeplau and Don (2015) <sup>[[#fn:r2178|2178]]</sup> , 44. Powlson et al. (2014) <sup>[[#fn:r2179|2179]]</sup> , 45. Powell and Lenton (2012) <sup>[[#fn:r2180|2180]]</sup> , 46) Woolf et al. (2010) <sup>[[#fn:r2181|2181]]</sup> , 47) Roberts et al. (2010) <sup>[[#fn:r2182|2182]]</sup> , 48. Pratt and Moran (2010) <sup>[[#fn:r2183|2183]]</sup> , 49. Turner et al. (2018) <sup>[[#fn:r2184|2184]]</sup> , 50) Koornneef et al. (2012) <sup>[[#fn:r2185|2185]]</sup> , 51) Bajželj et al. (2014) <sup>[[#fn:r2192|2192]]</sup> , 52) Springmann et al. (2016) <sup>[[#fn:r2187|2187]]</sup> , 53) Tilman and Clark (2014) <sup>[[#fn:r2188|2188]]</sup> , 54) Hedenus et al. (2014) <sup>[[#fn:r2189|2189]]</sup> , 55) Miner (2010) <sup>[[#fn:r2190|2190]]</sup> , 56) Bailis et al. (2015) <sup>[[#fn:r2191|2191]]</sup> .

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