Comparison of AERMOD and WindTrax dispersion models in determining PM ₁₀ emission rates from a beef cattle feedlot

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.