Climate Change Mitigation and U.S. Agriculture: Promises, Preemption, and Pathways

Sunday, February 14, 2016: 10:00 AM-11:30 AM
Coolidge (Marriott Wardman Park)
Alison Eagle, Duke University, Durham, NC
In the absence of agricultural greenhouse gas mitigation by means of carbon offsets under federal climate policies, other less potent mechanisms attempted to fill the void. Voluntary and regional carbon markets include some agricultural offsets, but uptake is minimal, especially given measurement challenges and uncertainty. Practices that reduce net GHG emissions are incentivized by USDA programs that target other objectives, and the USDA supports research and decision-making tools that allow producers to calculate – and thus reduce – on-farm emissions. Also significant are supply-chain efforts where large purchasers require distributors and food processors to reduce overall GHG emissions. At the farm level this has provided some programs and GHG quantification tools. Supply chain incentives are further bolstered by the White House pledge to reduce supply-chain GHG emissions by 40% over 10 years, and by the 150+ signatories to the American Business Act Climate Pledge.

Even without specified mechanisms, the Paris agreement could reinforce existing U.S. emission-reduction efforts (offsets, programmatic, and supply-chain). These require accurate data to design and credit actual environmental benefit. Without a strong scientific foundation, investments may be inefficiently allocated, benefits under-estimated, and program credibility eroded. With many models in current agricultural protocols calibrated to narrow, regional data or using IPCC factors, emission reductions are discounted significantly to address uncertainties.

GHG mitigation opportunities in U.S. agriculture face measurement challenges, high variability, and a lack of comprehensive field data for key regions and practices. This is illustrated with a systematic review and meta-analysis of the impact of nutrient management on unintended losses of fertilizer nitrogen (N) as nitrous oxide (N2O). Multi-level (hierarchical) regression models found that, in spite of high variability, N2O emissions increased with N fertilizer rate, July temperature, and soil carbon. Nitrification inhibitors and delaying application of N fertilizer reduced yield-scaled N2O emissions 25% and 45%, respectively. However, poor data coverage limits the broad application of results. Research that targets data gaps and that validates and calibrates biophysical models is key to ensuring that real environmental benefits are achieved, and that agricultural producers receive appropriate credit for actions taken.