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

=== Box 7.3 | Case Study: Agroforestry in Brazil – CANOPIES ===

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'''Summary'''

Brazilian farmers are integrating trees into their croplands in various ways, ranging from simple to highly complex agroforestry systems. While complex systems are more effective in the mitigation of climate change, trade-offs with scalability need to be resolved for agroforestry systems to deliver on their potential. The Brazilian-Dutch CANOPIES project ( [[#Janssen--2020|Janssen 2020]] ) is exploring transition pathways to agroforestry systems optimised for local ecological and socio-economic conditions.

'''Background'''

The climate change mitigation potential of agroforestry systems is widely recognised ( [[#Zomer--2016|Zomer et al. 2016]] ; [[#FAO--2017b|FAO 2017b]] ) and Brazilian farmers and researchers are pioneering diverse ways of integrating trees into croplands, from planting rows of eucalyptus trees in pastures up to highly complex agroforests consisting of &gt;30 crop and tree species. The degree of complexity influences the multiple functions that farmers and societies can attain from agroforestry: the more complex it is, the more it resembles a natural forest with associated benefits for its carbon storage capacity and its habitat quality for biodiversity ( [[#Santos--2019|Santos et al. 2019]] ). However, trade-offs exist between the complexity and scalability of agroforestry as complex systems rely on intensive manual labour to achieve high productivity ( [[#Tscharntke--2011|Tscharntke et al. 2011]] ). To date, mechanisation of structurally diverse agroforests is scarce and hence, efficiencies of scale are difficult to achieve.

'''Case description'''

These synergies and trade-offs between complexity, multifunctionality and scalability are studied in the CANOPIES (Co-existence of Agriculture and Nature: Optimisation and Planning of Integrated Ecosystem Services) project, a collaboration between Wageningen University (NL), the University of São Paulo and EMBRAPA (both Brazil). Soil and management data are collected on farms of varying complexity to evaluate carbon sequestration and other ecosystem services, economic performance and labour demands.

'''Interactions''' '''and limitations'''

The trade-off between complexity and labour demand is less pronounced in EMBRAPA’s integrated crop-livestock-forestry (ICLF) systems, where grains and pasture are planted between widely spaced tree rows. Here, barriers for implementation relate mostly to livestock and grain farmers’ lack of knowledge on forestry management and financing mechanisms 5 ( [[#Gil--2015|Gil et al. 2015]] ). Additionally, linking these financing mechanisms to carbon sequestration remains a Monitoring, Reporting and Verification challenge ( [[#Smith--2020b|Smith et al. 2020b]] ).

Box 7.3

'''Lessons'''

Successful examples of how more complex agroforestry can be upscaled do exist in Brazil. For example, on farm trials and consistent investments over several years have enabled Rizoma Agro to develop a citrus production system that integrates commercial and native trees in a large-scale multi-layered agroforestry system. The success of their transition resulted in part from their corporate structure that allowed them to tap into the certified Green Bonds market ( [[#CBI--2020|CBI 2020]] ). However, different transition strategies need to be developed for family farmers and their distinct socio-economic conditions.

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==== 7.4.3.4 Enteric Fermentation ====

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'''Activities, co-benefits, risks and implementation opportunities and barriers.''' Mitigating CH 4 emissions from enteric fermentation can be direct (i.e., targeting ruminal methanogenesis and emissions per animal or unit of feed consumed) or indirect, by increasing production efficiency (i.e., reducing emission intensity per unit of product). Measures can be classified as those relating to (i) feeding, (ii) supplements, additives and vaccines, and (iii) livestock breeding and wider husbandry ( [[#Jia--2019|Jia et al. 2019]] ). Co-benefits include enhanced climate change adaptation and increased food security associated with improved livestock breeding (Smith et al. 2014). Risks include mitigation persistence, ecological impacts associated with improving feed quality and supply, or potential toxicity and animal welfare issues concerning feed additives. Implementation barriers include feeding/administration constraints, the stage of development of measures, legal restrictions on emerging technologies and negative impacts, such as the previously described risks (Smith et al. 2014; [[#Jia--2019|Jia et al. 2019]] ; P. [[#Smith--2019|Smith et al. 2019]] a).

'''Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL); mitigation potential, costs, and pathways.''' The AR5 indicated medium (5–15%) technical mitigation potential from both feeding and breeding related measures (Smith et al. 2014). More recently, the SRCCL estimated with ''medium confidence'' , a global potential of 0.12–1.18 GtCO 2 -eq yr –1 between 2020 and 2050, with the range reflecting technical, economic and sustainability constraints (SRCCL, Chapter 2: [[#Hristov--2013|Hristov et al. 2013]] ; [[#Dickie--2014a|Dickie et al. 2014a]] ; [[#Herrero--2016|Herrero et al. 2016]] ; [[#Griscom--2017|Griscom et al. 2017]] ). The underlying literature used a mixture of IPCC GWP100 values for CH 4 , preventing conversion of CO 2 -eq to CH 4 . Improved livestock feeding and breeding were included in IAM emission pathway scenarios within the SRCCL and SR1.5, although it was suggested that the full mitigation potential of enteric CH 4 measures is not captured in current models ( [[#Rogelj--2018b|Rogelj et al. 2018b]] ; [[#IPCC--2018|IPCC 2018]] ).

'''Developments since AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL).''' Recent reviews generally identify the same measures as those outlined in the SRCCL, with the addition of early life manipulation of the ruminal biome ( [[#Grossi--2019|Grossi et al. 2019]] ; [[#Eckard--2020|Eckard and Clark 2020]] ; [[#Thompson--2020|Thompson and Rowntree 2020]] ; [[#Beauchemin--2020|Beauchemin et al. 2020]] ; [[#Ku-Vera--2020|Ku-Vera et al. 2020]] ; [[#Honan--2021|Honan et al. 2021]] ). There is ''robust evidence'' and ''high agreement'' that chemically synthesised inhibitors are promising emerging near-term measures ( [[#Patra--2016|Patra 2016]] ; [[#Jayanegara--2018|Jayanegara et al. 2018]] ; [[#Van%20Wesemael--2019|Van Wesemael et al. 2019]] ; [[#Beauchemin--2020|Beauchemin et al. 2020]] ) with high (e.g., 16–70% depending on study) mitigation potential reported (e.g., [[#Hristov--2015|Hristov et al. 2015]] ; [[#McGinn--2019|McGinn et al. 2019]] ; [[#Melgar--2020|Melgar et al. 2020]] ) and commercial availability expected within two years in some countries ( [[#Reisinger--2021|Reisinger et al. 2021]] ). However, their mitigation persistence ( [[#McGinn--2019|McGinn et al. 2019]] ), cost ( [[#Carroll--2019|Carroll and Daigneault 2019]] ; [[#Alvarez-Hess--2019|Alvarez-Hess et al. 2019]] ) and public acceptance ( [[#Jayasundara--2016|Jayasundara et al. 2016]] ) or regulatory approval is currently unclear while administration in pasture-based systems is likely to be challenging ( [[#Patra--2017|Patra et al. 2017]] ; [[#Leahy--2019|Leahy et al. 2019]] ). Research into other inhibitors/feeds containing inhibitory compounds, such as macroalga or seaweed ( [[#Chagas--2019|Chagas et al. 2019]] ; [[#Kinley--2020|Kinley et al. 2020]] ; [[#Roque--2019|Roque et al. 2019]] ), shows promise, although concerns have been raised regarding palatability, toxicity, environmental impacts and the development of industrial-scale supply chains ( [[#Abbott--2020|Abbott et al. 2020]] ; [[#Vijn--2020|Vijn et al. 2020]] ). In the absence of CH 4 vaccines, which are still under development ( [[#Reisinger--2021|Reisinger et al. 2021]] ) pasture-based and non-intensive systems remain reliant on increasing production efficiency ( [[#Beauchemin--2020|Beauchemin et al. 2020]] ). Breeding of low emitting animals may play an important role and is a subject under ongoing research ( [[#Pickering--2015|Pickering et al. 2015]] ; [[#Jonker--2018|Jonker et al. 2018]] ; [[#López-Paredes--2020|López-Paredes et al. 2020]] ).

Approaches differ regionally, with more focus on direct, technical options in Developed Countries, and improved efficiency in developing countries ( [[#Caro%20Torres--2016|Caro Torres et al. 2016]] ; [[#Mottet--2017b|Mottet et al. 2017b]] ; [[#MacLeod--2018|MacLeod et al. 2018]] ; [[#Frank--2018|Frank et al. 2018]] ). A recent assessment finds greatest economic (up to USD100 tCO 2 -eq –1 ) potential (using the IPCC AR4 GWP100 value for CH 4 ) for 2020–2050 in Asia and the Pacific (32.9 MtCO 2 -eq yr –1 ) followed by Developed Countries (25.5 MtCO 2 -eq yr –1 ) ( [[#Roe--2021|Roe et al. 2021]] ). Despite numerous country and sub-sector specific studies, most of which include cost analysis ( [[#Hasegawa--2012|Hasegawa and Matsuoka 2012]] ; [[#Hoa--2014|Hoa et al. 2014]] ; [[#Jilani--2015|Jilani et al. 2015]] ; [[#Eory--2015|Eory et al. 2015]] ; [[#Pradhan--2017|Pradhan et al. 2017]] ; [[#Pellerin--2017|Pellerin et al. 2017]] ; [[#Ericksen--2018|Ericksen and Crane 2018]] ; [[#Habib--2018|Habib and Khan 2018]] ; [[#Kashangaki--2018|Kashangaki and Ericksen 2018]] ; [[#Salmon--2018|Salmon et al. 2018]] ; [[#Brandt--2019b|Brandt et al. 2019b]] ; [[#Kiggundu--2019|Kiggundu et al. 2019]] ; [[#Kavanagh--2019|Kavanagh et al. 2019]] ; [[#Mosnier--2019|Mosnier et al. 2019]] ; [[#Pradhan--2019|Pradhan et al. 2019]] ; [[#Sapkota--2019|Sapkota et al. 2019]] ; [[#Carroll--2019|Carroll and Daigneault 2019]] ; [[#Leahy--2019|Leahy et al. 2019]] ; [[#Dioha--2020|Dioha and Kumar 2020]] ), sectoral assessment of regional technical and notably economic ( [[#Beach--2015|Beach et al. 2015]] ; [[#USEPA--2019|USEPA 2019]] ) potential is restricted by lack comprehensive and comparable data. Therefore, verification of regional estimates indicated by global assessments is challenging. Feed quality improvement, which may have considerable potential in developing countries ( [[#Caro--2016|Caro et al. 2016]] ; [[#Mottet--2017a|Mottet et al. 2017a]] ), may have negative wider impacts. For example, potential land-use change and greater emissions associated with production of concentrates ( [[#Brandt--2019b|Brandt et al. 2019b]] ).

'''Critical review and conclusion.''' Based on studies to date, using a range of IPCC GWP100 values for CH 4 , there is ''medium confidence'' that activities to reduce enteric CH 4 emissions have a global technical potential of 0.8 (0.2–1.2) GtCO 2 -eq yr –1 , of which 0.2 (0.1–0.3) GtCO 2 -eq yr –1 is available up to USD100 tCO 2 -eq –1 (Figure 7.11). The CO 2 -eq value may also slightly differ if the GWP100 IPCC AR6 CH 4 value was uniformly applied within calculations. Lack of comparable country and sub-sector studies to assess the context applicability of measures, associated costs and realistic adoption likelihood, prevents verification of estimates.

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==== 7.4.3.5 Improve Rice Management ====

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'''Activities, co-benefits, risks and implementation opportunities and barriers.''' Emissions from rice cultivation mainly concern CH 4 associated with anaerobic conditions, although N 2 O emission also occur via nitrification and denitrification processes. Measures to reduce CH 4 and N 2 O emissions include (i) improved water management (e.g., single drainage and multiple drainage practices), (ii) improved residue management, (iii) improved fertiliser application (e.g., using slow release fertiliser and nutrient specific application), and (iv) soil amendments (including biochar and organic amendments) ( [[#Pandey--2014|Pandey et al. 2014]] ; [[#Kim--2017b|Kim et al. 2017b]] ; [[#Yagi--2020|Yagi et al. 2020]] ; [[#Sriphirom--2020|Sriphirom et al. 2020]] ). These measures not only have mitigation potential but can improve water use efficiency, reduce overall water use, enhance drought adaptation and overall system resilience, improve yield, reduce production costs from seed, pesticide, pumping and labour, increase farm income, and promote sustainable development ( [[#Quynh--2015|Quynh and Sander 2015]] ; [[#Yamaguchi--2017|Yamaguchi et al. 2017]] ; [[#Tran--2018|Tran et al. 2018]] ; [[#Sriphirom--2019|Sriphirom et al. 2019]] ). However, in terms of mitigation of CH 4 and N 2 O, antagonistic effects can occur, whereby water management can enhance N 2 O emissions due to creation of alternate wet and dry conditions ( [[#Sriphirom--2019|Sriphirom et al. 2019]] ), with trade-offs between CH 4 and N 2 O during the drying period potentially offsetting some mitigation benefits. Barriers to adoption may include site-specific limitations regarding soil type, percolation and seepage rates or fluctuations in precipitation, water canal or irrigation infrastructure, paddy surface level and rice field size, and social factors including farmer perceptions, pump ownership, and challenges in synchronising water management between neighbours and pumping stations ( [[#Quynh--2015|Quynh and Sander 2015]] ; [[#Yamaguchi--2017|Yamaguchi et al. 2017]] ; [[#Yamaguchi--2019|Yamaguchi et al. 2019]] ).

'''Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL); mitigation potential, costs, and pathways.''' The AR5 outlined emissions from rice cultivation of 0.49–0.723 GtCO 2 -eq yr –1 in 2010 with an average annual growth of 0.4% yr –1 . The SRCCL estimated a global mitigation potential from improved rice cultivation of 0.08–0.87 GtCO 2 -eq yr –1 between 2020 and 2050, with the range representing the difference between technical and economic constraints, types of activities included (e.g., improved water management and straw residue management) and GHGs considered ( [[#Dickie--2014a|Dickie et al. 2014a]] ; [[#Beach--2015|Beach et al. 2015]] ; [[#Paustian--2016|Paustian et al. 2016]] ; [[#Griscom--2017|Griscom et al. 2017]] ; [[#Hawken--2017|Hawken 2017]] ) (SRCCL, Chapter 2).

'''Developments since AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL).''' Since AR5 and the SRCCL, studies on mitigation have principally focused on water and nutrient management practices with the aim of improving overall sustainability as well as measurements of site-specific emissions to help improve the resolution of regional estimates. Intensity of emissions show considerable spatial and temporal variation, dependent on site specific factors including degradation of soil organic matter, management of water levels in the field, the types and amount of fertilisers applied, rice variety and local cultivation practices. Variation in CH 4 emissions have been found to range from 0.5–41.8 mg m 2 hr –1 in South-East Asia ( [[#Sander--2014|Sander et al. 2014]] ; [[#Chidthaisong--2018|Chidthaisong et al. 2018]] ; [[#Setyanto--2018|Setyanto et al. 2018]] ; [[#Sibayan--2018|Sibayan et al. 2018]] ; J. [[#Wang--2018|Wang et al. 2018]] ; [[#Maneepitak--2019|Maneepitak et al. 2019]] ), 0.5–37.0 mg m 2 hr –1 in Southern and Eastern Asia ( [[#Zhang--2010|Zhang et al. 2010]] ; [[#Wang--2012|Wang et al. 2012]] ; [[#Oo--2018|Oo et al. 2018]] ; J. [[#Wang--2018|Wang et al. 2018]] ; [[#Takakai--2020|Takakai et al. 2020]] ) ''',''' and 0.5–10.4 mg m 2 hr –1 in North America (J. [[#Wang--2018|Wang et al. 2018]] ). Current studies on emissions of N 2 O also showed high variation in the range of 0.13–654 ug/m 2 /hr ( [[#Akiyama--2005|Akiyama et al. 2005]] ; [[#Islam--2018|Islam et al. 2018]] ; [[#Kritee--2018|Kritee et al. 2018]] ; [[#Zschornack--2018|Zschornack et al. 2018]] ; [[#Oo--2018|Oo et al. 2018]] ).

Recent studies on water management have highlighted the potential to mitigate GHG emissions, while also enhancing water use efficiency ( [[#Tran--2018|Tran et al. 2018]] ). A meta-analysis on multiple drainage systems found that Alternative Wetting and Drying (AWD) with irrigation management, can reduce CH 4 emissions by 20–30% and water use by 25.7%, though this resulted in a slight yield reduction (5.4%) ( [[#Carrijo--2017|Carrijo et al. 2017]] ). Other studies have described improved yields associated with AWD ( [[#Tran--2018|Tran et al. 2018]] ). Water management for both single and multiple drainage can (most likely ) reduce methane emissions by about 35% but increase N 2 O emissions by about 20% ( [[#Yagi--2020|Yagi et al. 2020]] ). However, N 2 O emissions occur only under dry conditions, therefore total reduction in terms of net GWP is approximately 30%. Emissions of N 2 O are higher during dry seasons ( [[#Yagi--2020|Yagi et al. 2020]] ) and depend on site specific factors as well as the quantity of fertiliser and organic matter inputs into the paddy rice system. Variability of N 2 O emissions from single and multiple drainage can range from 0.06–33 kg/ha ( [[#Hussain--2015|Hussain et al. 2015]] ; [[#Kritee--2018|Kritee et al. 2018]] ). AWD in Vietnam was found to reduce both CH 4 and N 2 O emissions by 29–30 and 26–27% respectively with the combination of net GWP about 30% as compared to continuous flooding ( [[#Tran--2018|Tran et al. 2018]] ). Overall, greatest average economic mitigation potential (up to USD100 tCO 2 -eq –1 ) between 2020 and 2050 is estimated to be in Asia and the Pacific (147.2 MtCO 2 -eq yr –1 ) followed by Latin America and the Caribbean (8.9 MtCO 2 -eq yr –1 ) using the IPCC AR4 GWP100 value for CH 4 ( [[#Roe--2021|Roe et al. 2021]] ).

'''Critical assessment and conclusion.''' There is ''medium confidence'' that improved rice management has a technical potential of 0.3 (0.1–0.8) GtCO 2 -eq yr –1 between 2020 and 2050, of which 0.2 (0.05–0.3) GtCO 2 -eq yr –1 is available up to USD100 tCO 2 -eq –1 (Figure 7.11). Improving rice cultivation practices will not only reduce GHG emissions, but also improve production sustainability in terms of resource utilisation including water consumption and fertiliser application. However, emission reductions show high variability and are dependent on site specific conditions and cultivation practices.

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==== 7.4.3.6 Crop Nutrient Management ====

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'''Activities, co-benefits, risks and implementation opportunities and barriers.''' Improved crop nutrient management can reduce N 2 O emissions from cropland soils. Practices include optimising fertiliser application delivery, rates and timing, utilising different fertiliser types (i.e., organic manures, composts and synthetic forms), and using slow or controlled-released fertilisers or nitrification inhibitors (Smith et al. 2014; [[#Griscom--2017|Griscom et al. 2017]] ; P. [[#Smith--2019|Smith et al. 2019]] a). In addition to individual practices, integrated nutrient management that combines crop rotations including intercropping, nitrogen biological fixation, reduced tillage, use of cover crops, manure and bio-fertiliser application, soil testing and comprehensive nitrogen management plans, is suggested as central for optimising fertiliser use, enhancing nutrient uptake and potentially reducing N 2 O emissions ( [[#Bationo--2012|Bationo et al. 2012]] ; [[#Lal--2018|Lal et al. 2018]] ; [[#Bolinder--2020|Bolinder et al. 2020]] ; [[#Jensen--2020|Jensen et al. 2020]] ; [[#Namatsheve--2020|Namatsheve et al. 2020]] ). Such practices may generate additional mitigation by indirectly reducing synthetic fertiliser manufacturing requirements and associated emissions, though such mitigation is accounted for in the Industry Sector and not considered in this chapter. Tailored nutrient management approaches, such as 4R nutrient stewardship, are implemented in contrasting farming systems and contexts and supported by best management practices to balance and match nutrient supply with crop requirements, provide greater stability in fertiliser performance and to minimise N 2 O emissions and nutrient losses from fields and farms ( [[#Fixen--2020|Fixen 2020]] ; [[#Maaz--2021|Maaz et al. 2021]] ). Co-benefits of improved nutrient management can include enhanced soil quality (notably when manure, crop residues or compost is utilised), carbon sequestration in soils and biomass, soil water holding capacity, adaptation capacity, crop yields, farm incomes, water quality (from reduced nitrate leaching and eutrophication), air quality (from reduced ammonia emissions) and in certain cases, it may facilitate land sparing ( [[#Sapkota--2014|Sapkota et al. 2014]] ; [[#Johnston--2014|Johnston and Bruulsema 2014]] ; [[#Zhang--2017|Zhang et al. 2017]] ; P. [[#Smith--2019|Smith et al. 2019]] a; [[#Mbow--2019|Mbow et al. 2019]] ).

A potential risk under certain circumstances, is yield reduction, while implementation of practices should consider current soil nutrient status. There are significant regional imbalances, with some regions experiencing nutrient surpluses from over fertilisation and others, nutrient shortages and chronic deficiencies ( [[#FAO--2021e|FAO 2021e]] ). Additionally, depending on context, practices may be inaccessible, expensive or require expertise to implement ( [[#Hedley--2015|Hedley 2015]] ; [[#Benson--2018|Benson and Mogues 2018]] ) while impacts of climate change may influence nutrient use efficiency ( [[#Amouzou--2019|Amouzou et al. 2019]] ) and therefore, mitigation potential.

'''Conclusions from AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL); mitigation potential, costs, and pathways.''' The SRCCL broadly identified the same practices as outlined in AR5 and estimated that improved cropland nutrient management could mitigate between 0.03 and 0.71 GtCO 2 -eq yr –1 between 2020 and 2050 (SRCCL Chapter 2) ( [[#Dickie--2014a|Dickie et al. 2014a]] ; [[#Beach--2015|Beach et al. 2015]] ; [[#Paustian--2016|Paustian et al. 2016]] ; [[#Griscom--2017|Griscom et al. 2017]] ; [[#Hawken--2017|Hawken 2017]] ).

'''Developments since AR5 and IPCC Special Reports (SR1.5, SROCC and SRCCL).''' Research since the SRCCL highlights the mitigation potential and co-benefits of adopting improved nutrient management strategies, notably precision fertiliser application methods and nutrient expert systems, and applicability in both large-scale mechanised and small-scale systems ( [[#USEPA--2019|USEPA 2019]] ; [[#Hijbeek--2019|Hijbeek et al. 2019]] ; [[#Griscom--2020|Griscom et al. 2020]] ; [[#Tian--2020|Tian et al. 2020]] ; [[#Aryal--2020|Aryal et al. 2020]] ; [[#Sapkota--2021|Sapkota et al. 2021]] ). Improved crop nutrient management is feasible in all regions, but effectiveness is context dependent. Sub-Saharan Africa has one of the lowest global fertiliser consumption rates, with increased fertiliser use suggested as necessary to meet projected future food requirements ( [[#Mueller--2012|Mueller et al. 2012]] ; [[#ten%20Berge--2019|ten Berge et al. 2019]] ; [[#Adam--2020|Adam et al. 2020]] ; [[#Falconnier--2020|Falconnier et al. 2020]] ). Fertiliser use in Developed Countries is already high (Figure 7.10) with increased nutrient use efficiency among the most promising mitigation measures ( [[#Roe--2019|Roe et al. 2019]] ; [[#Hijbeek--2019|Hijbeek et al. 2019]] ). Considering that Asia and Pacific, and Developed Countries accounted for the greatest share of global nitrogen fertiliser use, it is not surprising that these regions are estimated to have greatest economic mitigation potential (up to USD100 tCO 2 -eq –1 ) between 2020 and 2050, at 161.8 and 37.1 MtCO 2 -eq yr –1 respectively (using the IPCC AR4 GWP100 value for N 2 O) ( [[#Roe--2021|Roe et al. 2021]] ).

'''Critical assessment and conclusion.''' There is ''medium confidence'' that crop nutrient management has a technical potential of 0.3 (0.06–0.7) GtCO 2 -eq yr –1 of which 0.2 (0.05–0.6) GtCO 2 -eq yr –1 is available up to USD100 tCO 2 -eq –1 . This value is based on GWP100 using a mixture of IPCC values for N 2 O and may slightly differ if calculated using AR6 values. The development of national roadmaps for sustainable fertiliser (nutrient) management can help in scaling-up related practices and in realising this potential. Crop nutrient management measures can contribute not only to mitigation, but food and nutrition security and wider environmental sustainability goals.

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