Comparison of AERMOD and WindTrax dispersion models in determining PM10 emission rates from a beef cattle feedlot

• Published in: Journal of the Air & Waste Management Association (1995) 2013-05, Vol.63 (5), p.545-556
• Main Authors: Bonifacio, Henry F., Maghirang, Ronaldo G., Razote, Edna B., Trabue, Steven L., Prueger, John H.
• Format: Article
• Language: English
• Subjects: Air Pollutants - analysis; Animal Feed; Animals; Applied sciences; Atmospheric pollution; Cattle; Convection; Environmental Monitoring - methods; Exact sciences and technology; Global environmental pollution; Kansas; Meteorological Concepts; Models, Theoretical; Normal Distribution; Particulate Matter - analysis; Pollution; Seasons; Stochastic Processes; Weather; Wind
• ISSN: 1096-2247; 2162-2906
• DOI: 10.1080/10962247.2013.768311

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 Gaussian-based AERMOD, the preferred regulatory dispersion model of the U.S. Environmental Protection Agency (EPA), and WindTrax, a backward Lagrangian stochastic-based dispersion model, in determining PM 10 emission rates for a large beef cattle feedlot in Kansas. The effect of the type of meteorological data was also evaluated. Meteorological conditions and PM 10 concentrations at the feedlot were measured with micrometeorological/eddy covariance instrumentation and tapered element oscillating microbalance (TEOM) PM 10 monitors, respectively, from May 2010 through September 2011. Using the measured meteorological conditions and assuming a unit emission flux (i.e., 1 µg/m 2 -sec), each model was used to calculate PM 10 concentrations (referred to as unit-flux concentrations). PM 10 emission fluxes were then back-calculated using the measured and calculated unit-flux PM 10 concentrations. For AERMOD, results showed that the PM 10 emission fluxes determined using the two different meteorological data sets evaluated (eddy covariance-derived and AERMET-generated) were basically the same. For WindTrax, the two meteorological data sets (sonic anemometer data set, a three-variable data set composed of wind parameters, surface roughness, and atmospheric stability) also produced basically the same PM 10 emission fluxes. Back-calculated emission fluxes from AERMOD were 32 to 69% higher than those from WindTrax.