Agricultural emissions account for 53% of 2010 global non-CO2 emissions and are projected to increase substantially over the next 20years, 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.
Global mitigation potential and costs of reducing agricultural non-CO2 greenhouse gas emissions through 2030
Beach III, R., Creason, J., Ohrel, S. B., Ragnauth, S., Ogle, S., Li, C., Ingraham, P., & Salas, W. (2015). Global mitigation potential and costs of reducing agricultural non-CO2 greenhouse gas emissions through 2030. Journal of Integrative Environmental Sciences, 12(Sup1), 87-105. https://doi.org/10.1080/1943815X.2015.1110183