Agricultural emissions account for 53% of 2010 global non-CO₂ emissions and are projected to increase substantially over the next 20 years, especially in Asia, Latin America and Africa. While agriculture is a substantial source of emissions, it is also generally considered to be a potential source of cost-effective non-CO₂ GHG abatement. Previous “bottom-up” analyses provided marginal abatement cost (MAC) curves for use in modeling these options within economy-wide and global mitigation analyses. In this paper, we utilize updated economic and biophysical data and models developed by the US Environmental Protection Agency (EPA) to investigate regional mitigation potential for major sources of agricultural GHG emissions. In addition, we explore mitigation potential available at costs at or below the estimated benefits of mitigation, as represented by the social cost of carbon. Key enhancements over previous regional assessments include incorporation of additional mitigation options, updated baseline emissions projections, greater spatial disaggregation, and development of MAC curves through 2030. For croplands and rice cultivation, biophysical, process-based models (DAYCENT and DNDC) are used to simulate yields and net GHG emissions under baseline and mitigation scenarios while the livestock sector is modeled by applying key mitigation options to baselines compiled by EPA. MAC curves are generated accounting for net GHG reductions, yield effects, livestock productivity effects, commodity prices, labor requirements, and capital costs where appropriate. MAC curves are developed at the regional level and reveal large potential for non-CO₂ GHG mitigation at low carbon prices, especially in Asia.

农业排放量占2010年全球非CO ₂排放量的53％，预计在未来20年内将大大增加，特别是在亚洲，拉丁美洲和非洲。尽管农业是主要的排放源，但通常也将其视为具有成本效益的非CO ₂的潜在来源。减少温室气体。先前的“自下而上”分析提供了边际减排成本（MAC）曲线，可用于在经济范围和全球减排分析中对这些方案进行建模。在本文中，我们利用由美国环境保护署（EPA）开发的更新的经济和生物物理数据及模型来研究主要农业温室气体排放源的区域减排潜力。此外，我们以碳的社会成本为代表，探索了以等于或低于估计的减排收益的成本可获得的减排潜力。与之前的区域评估相比，主要增强之处包括纳入了更多的缓解措施，更新的基准线排放量预测，更大的空间分类以及到2030年的MAC曲线发展。对于农田和水稻种植，生物物理，基于过程的模型（DAYCENT和DNDC）用于模拟基线和减排情景下的产量和净温室气体排放，而畜牧业则通过对EPA编制的基线应用关键的减排方案进行建模。生成MAC曲线，说明净温室气体减少，产量影响，牲畜生产率影响，商品价格，劳动力需求和资本成本（如果适用）。MAC曲线是在地区层面开发的，显示出非CO的巨大潜力 以及适当的资本成本。MAC曲线是在地区层面开发的，显示出非CO的巨大潜力 以及适当的资本成本。MAC曲线是在地区层面开发的，显示出非CO的巨大潜力₂以低碳价格缓解温室气体，尤其是在亚洲。