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 backcalculated 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.
|Original language||English (US)|
|Number of pages||12|
|Journal||Journal of the Air and Waste Management Association|
|State||Published - Jan 1 2013|
ASJC Scopus subject areas
- Waste Management and Disposal
- Management, Monitoring, Policy and Law