14th International Emission Inventory Conference
Las Vegas, NV
Ammonia is an important atmospheric pollutant that combines with sulfuric acid and nitric acid to form aerosol sulfates and nitrate, respectively. These aerosol species are major components of fine particulate matter (PM) and contribute significantly to visibility impairment. Estimates of ammonia emission factors are both highly variable and uncertain. Emissions factors vary depending on meteorological conditions and seasonal and regional differences in farming practices. Previous ammonia emissions inventories have not adequately characterized seasonal and geographical variations in emissions factors. Recent chemical transport modeling suggests that daily and hourly variability in ammonia emissions is required to model accurately the formation of ammonium nitrate and ammonium sulfates.
In a companion paper, the development of a process-based model for predicting or estimating ammonia emission rates and factors from individual or a group of animal feeding operations at local, regional and national levels was presented. This paper discusses the data requirements and implementation of the process-based ammonia emission model. Preliminary emission estimates developed from the process-based ammonia emission model are also presented. Detailed description of databases used as input values for the process-developed model and recommendations for future improvement on the farm-based data regarding the animal feeding and manure management practices are documented. Where available, comparisons of the new ammonia emission estimates with existing ammonia emission inventories for livestock farms at a local, regional and national level are presented.
The work presented here is sponsored and funded by the Lake Michigan Air Directors Consortium (LADCO).
Mansell, Gerard E.; Wang, Zion; Zhang, Ruihong; Fadel, James G.; Rumery, Thomas R.; Xin, Hongwei; Liang, Yi; and Arogo, Jactone, "An Improved Process Based Ammonia Emission Model for Agricultural Sources—Emission Estimates" (2005). Agricultural and Biosystems Engineering Conference Proceedings and Presentations. 218.