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Title: ESTIMATING FARM EMISSIONS OF AMMONIA WITH AN INVERSE-DISPERSION TECHNIQUE

Author
item FLESCH, T - UNIVERSITY OF ALBERTA
item WILSON, J - UNIVERSITY OF ALBERTA
item Harper, Lowry
item CRENNA, B - UNIVERSITY OF ALBERTA

Submitted to: Atmospheric Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/25/2005
Publication Date: 8/1/2005
Citation: Flesch, T.K., Wilson, J.D., Harper, L.A., Crenna, B.P. 2005. Estimating farm emissions of ammonia with an inverse-dispersion technique. Atmospheric Environment. 39(27):4863-4874.

Interpretive Summary: Trace-gases such as ammonia and methane are natural in the environment but high concentrations may decrease air quality or promote global change. The determination of trace-gas emissions from animal feeding operations presents a challenge to get accurate results due to disturbed wind-flow patterns around confinement structures. The purpose of this research is to determine if a new dispersion analysis model may be used to infer emissions from a whole farm. Scientists at the University of Alberta, Edmonton, and USDA-ARS scientists at the J. Phil Campbell Sr. Natural Resources Research Center, Watkinsville, GA, applied an inverse-dispersion technique to determine emission rates from a swine farm in the Central Great Basin of the U.S. An important part of the analysis was identifying questionable measurements of climatic conditions and gas concentrations. After removing questionable periods, calculated ammonia emissions are consistent with other studies using different techniques. These results indicate that if judgement is applied in the proper placement of measuring equipment, the determinations will have acceptable accuracy. This technique will provide easier determinations and accurate air-quality gas emissions estimates for environmental protection agencies, animal industries, and designers to identify problem areas for development of best-management practices. Reduction of air-quality gas emissions by animal feeding operations will minimize environmental impact while continuing to provide a safe U.S. food supply.

Technical Abstract: An inverse-dispersion technique was used to diagnose gas emissions (ammonia) from a swine farm. This technique, the backward Lagrangian stochastic (bLS) model, gives the emission-concentration relationship so that downwind gas concentrations establish emissions. The bLS model takes as input the average wind velocity and direction, surface roughness, and atmospheric stability. Despite ignoring wind complexity and assuming a simplified source configuration in the model calculations, we argue that with concentration and wind measured sufficiently far from the farm, the errors can be relatively small. An important part of our analysis was identifying periods likely to give erroneous results. The resulting emission calculations (6.5 and 16 g animal-1 day-1 in March and July, respectively) are plausible in the light of comparative figures using other techniques.