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United States Department of Agriculture

Agricultural Research Service

Title: A Comparison of Ammonia Emission Rates from An Agricultural Area Source Using Disperson Modeling: Gaussian Versus Backward-Lagrangian Stochastic.

Authors
item Price, Jacqueline - TAMU
item Lacey, Ronald - TAMU
item Shaw, Bryan - TAMU
item Cole, Noel
item Todd, Richard
item Capareda, Sergio - TAMU
item Parnell, Calvin - TAMU

Submitted to: Proceedings of American Society of Agricultural Engineers
Publication Type: Proceedings
Publication Acceptance Date: February 1, 2004
Publication Date: August 1, 2004
Citation: Price, J., Lacey, R., Shaw, B., Cole, N.A., Todd, R.W., Capareda, S., Parnell, C. 2004. A comparison of ammonia emission rates from an agricultural area source using disperson modeling: gaussian versus backward-lagrangian stochastic. In: Proceedings of American Society of Agricultural Engineers 2004 Annual International Meeting, August 1-4, 2004, Ottawa, Ontario, Canada. Paper No. 044199.

Interpretive Summary: Agricultural operations are thought to be a major source of ammonia emissions in the U.S. Ammonia is one of the most prevalent alkaline gases in the earth's atmosphere; therefore, it is an important element in atmospheric computer models. Ammonia concentrations can affect the overall acidity of precipitation and atmospheric aerosols. These ammonia aerosols have the attention of the EPA and other regulatory agencies because under some circumstances, ammonia can react with other molecules in the atmosphere and cause potential adverse effects on surface waters, plants, and animals. Measuring emissions of ammonia and other gases from agricultural operations is difficult. A number of different models and experimental techniques are available to measure ammonia emissions. However their accuracy and agreement are not well documented. In this study, ammonia emission rates from a beef cattle feedyard were determined using two models: the Industrial Source Complex (Gaussian) model used by the EPA and WindTrax (backward-Lagrangian stochastic), a commercially available model. The calculated ammonia emissions calculated from each model using the average emission rate generated by the model varied by a factor of 10. Emission factors used by regulatory entities are derived based upon back-calculated model emission rates and site management practices. Thus, a difference of a factor of 10 in the emission rates could be troubling in determination of emission regulations. These results indicate that ammonia emission rates determined using one model may not be compatible with other models.

Technical Abstract: Agricultural operations are thought to contribute significantly to the overall anthropogenic ammonia emissions. Ammonia emissions serve as crucial elements of atmospheric models because ammonia is one of the most prevalent alkaline gaseous bases found in the planetary layer. Ammonia concentrations affect the overall acidity of precipitation and atmospheric aerosols. These ammonia aerosols have the attention of the EPA and other regulatory agencies because, when certain thresholds are exceeded, potential consequences result from these over-threshold concentrations of oxidized and reduced forms of nitrogen. In this study, an evaluation of ammonia emission rates generated by both the Industrial Source Complex (Gaussian) model and the WindTrax (backward-Lagrangian stochastic) model revealed that the calculated emission concentrations from each model using the average emission rate generated by the model vary by a factor of 10. Current and future sources are regulated by the emission rate data from previous time periods. Emission factors are published for regulation of various sources, and these emission factors are derived based upon back-calculated model emission rates and site management practices. Thus, a factor of 10 ratio in the emission rates could prove troubling in terms of regulation if the model that the emission rate is back-calculated from is not used as the model to predict a future downwind pollutant concentration.

Last Modified: 4/16/2014
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