Emission of particulate matter (PM) and various gases from open-lot beef cattle feedlots is becoming a concern because of the adverse effects on human health and the environment; however, scientific information on feedlot emissions is limited. This research was conducted to estimate emission rates of PM 10 from large cattle feedlots. Specific objectives were to: (1) determine feedlot PM10 emission rates by reverse dispersion modeling using AERMOD; (2) compare AERMOD and WindTrax in terms of their predicted concentrations and back-calculated PM10 emission rates; (3) examine the sensitivity of both AERMOD and WindTrax to changes in meteorological parameters, source location, and receptor location; (4) determine feedlot PM10 emission rates using the flux-gradient technique; and (5) compare AERMOD and computational fluid dynamics (CFD) in simulating particulate dispersion from an area source.;PM10 emission rates from two cattle feedlots in Kansas were determined by reverse dispersion modeling with AERMOD using PM10 concentration and meteorological measurements over a 2-yr period. PM 10 emission rates for these feedlots varied seasonally, with overall medians of 1.60 and 1.10 g /m2-day. Warm and prolonged dry periods had significantly higher PM emissions compared to cold periods. Results also showed that the PM10 emissions had a diurnal trend; highest PM10 emission rates were observed during the afternoon and early evening periods.;Using particulate concentration and meteorological measurements from a third cattle feedlot, PM10 emission rates were back-calculated with AERMOD and WindTrax. Higher PM10 emission rates were calculated by AERMOD, but their resulting PM10 emission rates were highly linear (R2 ≥ 0.88). As such, development of conversion factors between these two models is feasible. AERMOD and WindTrax were also compared based on their sensitivity to changes in meteorological parameters and source locations. In general, AERMOD calculated lower concentrations than WindTrax; however, the two models responded similarly to changes in wind speed, surface roughness, atmospheric stability, and source and receptor locations.;The flux-gradient technique also estimated PM10 emission rates at the third cattle feedlot. Analyses of PM10 emission rates and meteorological parameters indicated that PM10 emissions at the feedlot were influenced by friction velocity, sensible heat flux, temperature, and surface roughness. Based on pen surface water content measurements, a water content of at least 20% (wet basis) significantly lowered PM10 emissions at the feedlot.;The dispersion of particulate from a simulated feedlot pen was predicted using CFD turbulence model (k-ε model) and AERMOD. Compared to CFD, AERMOD responded differently to wind speed setting, and was not able to provide detailed vertical concentration profiles such that the vertical concentration gradients at the first few meters from the ground were negligible. This demonstrates some limitations of AERMOD in simulating dispersion for area sources such as cattle feedlots and suggests the need to further evaluate its performance for area source modeling.
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