Submitted to: Journal of Air and Waste Management Association
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 4, 2013
Publication Date: May 5, 2013
Citation: Bonifacio, H.F., Maghirang, R., Razote, E., Trabue, S.L., Prueger, J.H. 2013. Comparison of AERMOD and WindTrax dispersion models in determining PM10 emission rates from beef cattle feedlots. Journal of Air and Waste Management Association. 63(5):545-556. Interpretive Summary: Release of dust and particulate material (PM) from large cattle feedlots is both a health and environmental hazard. Determining how much PM is released from cattle feedlots is difficult and open cattle feedlots make monitoring efforts even more challenging due in part to the size and variable nature of open sources. Reverse-dispersion modeling is a potential tool that estimates emissions from open sources by measuring only upwind and downwind concentrations and back calculating how background air (i.e., upwind) concentrations could reach levels downwind. In this report, two differient models with different dispersion assumption and calcualtions were used to determine PM released from large beef cattle feedlot in Kansas. The two different models were AERMOD (EPA model) and WindTrax. Back-calculated emission fluxes from AERMOD were 32-69% higher than WindTrax. Differences in the model were based on differences in dispersion calculations with AERMOD assuming a gaussian based dispersion, while WindTrax uses Lagrangian stochastic based dispersion. Research results described in this report provides information for scientists, engineers, and regulatory officials on the use of air modeling for calculating emission of PM from large open beef feedlots in Kansas.
Technical Abstract: Reverse dispersion modeling has been used to determine air emission fluxes from ground-level area sources, including open-lot beef cattle feedlots. This research compared AERMOD, a Gaussian-based and currently the U.S. Environmental Protection Agency (EPA) preferred regulatory dispersion model, and WindTrax, a backward Lagrangian stochastic-based dispersion model, in determining PM10 emission rates for a large beef cattle feedlot in Kansas. The effect of the type of meteorological data was also evaluated. Meteorological conditions and PM10 concentrations at the feedlot were measured with micrometeorological/eddy covariance instrumentation and Tapered Element Oscillating Microbalance (TEOM) PM10 monitors, respectively, from May 2010 to September 2011. With an assumed emission flux, PM10 concentrations were predicted using measured meteorological conditions. PM10 emission fluxes were then back-calculated using both the predicted and the measured PM10 concentrations. For AERMOD, results showed that the PM10 emission fluxes determined using the two different meteorological data sets evaluated (eddy covariance-derived and AERMET-generated) were relatively the same. For WindTrax, the two meteorological data sets used (sonic anemometer data set, 3-variable data set composed of wind parameters, surface roughness and atmospheric stability) also produced relatively the same PM10 emission fluxes. Back-calculated emission fluxes from AERMOD were higher by 32 to 69% compared to WindTrax.