Atmospheric ammonia: Emission estimates, model evaluation, and opportunities for cost-effective control of particulate matter

Ammonia is an important pre-cursor for inorganic particulate matter (PM). While most of the regulatory focus has been directed towards SO2 and NOx reductions, recent work has shown that the effectiveness of these control strategies can be increased with simultaneous reductions in ammonia. However, previous emission inventories have not quantified the seasonal and geographic variations necessary for accurately predicting ammonium nitrate aerosol. This research seeks to develop a temporally and spatially resolved ammonia emission inventory based on a process-based model of ammonia emissions from livestock. A partially mechanistic model of a dairy farm has been developed and found to be robust across a range of conditions. This model has been combined with a national distribution of farming practices and climate data to estimate monthly, county-level ammonia emissions from dairy cows in the United States. Using the dairy model, the seasonal cycle of emissions is also estimated for other livestock groups. This seasonal and geographic distribution of emissions will be used as input to PMCAMx +, a three-dimensional regional air quality model. The PMCAMx+ predicted total ammonia will be compared with measurements to test the performance of the emission inventory. With a better estimate of emissions, it is possible to consider opportunities for controlling PM by reductions in ammonia. The final portion of this research is to estimate the potential for the reductions in ammonia emissions as a cost-effective control strategy for PM2.5. This research will estimate the costs and emission reductions possible in the livestock sector, compare the effectiveness of reductions in urban compared to rural areas, and analyze the uncertainty in these estimates.