Preliminary mitigation estimates for soil N2O, enteric CH4, rice CH4 and manure CH4 emissions for major world agricultural regions
DeAngelo, B., de la Chesnaye, F., Wirth, T., Beach, R., Sommer, A., & Murray, B. (2003, November). Preliminary mitigation estimates for soil N2O, enteric CH4, rice CH4 and manure CH4 emissions for major world agricultural regions. Presented at 3rd International Methane and Nitrous Oxide Mitigation Conference, 17-21 November 2003, Beijing, China.
Agriculture accounts for a significant portion of the world’s anthropogenic greenhouse gas (GHG) emissions, and emissions in this sector are projected to increase for the foreseeable future. Though many mitigation options for agricultural GHG emissions can be readily identified, it has been more difficult to assess mitigation options in agriculture than in most othersectors. The difficulty has been due to 1) the relative uncertainty in quantifying emissions—and changes in emissions due to mitigation—in a sector characterized by emissions that are spatially dispersed, not directly monitored, and highly variable, not only from region to region but fromfarm to farm; 2) the lack of regionally specific cost data for implementing mitigation options; and 3) the difficulty in estimating the appropriate level of mitigation response to carbon prices (or other values for GHG mitigation).This analysis aims to improve our understanding of agricultural GHG mitigation for nitrous oxide (N2O) and methane (CH4) emissions from soils, livestock and rice, for major regions of the world. This paper provides general background information on non-CO2 GHG emissions from global agriculture, describes the methods used in our mitigation analysis, presents results in the form of marginal abatement curves (MACs) for major regions in year 2010, and outlines important caveats and next steps for this project. We characterize these results as “preliminary” because 1) they have not undergone expert review; and 2) we made many simplifyingassumptions in order to scale the mitigation estimates across regions.