|Maghirang, Ronaldo - Kansas State University|
|Bonifacio, Edna - Kansas State University|
Submitted to: ASABE Annual International Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 12/19/2013
Publication Date: N/A
Technical Abstract: Several emission estimation methods can be used to determine emission fluxes from ground-level area sources, including open-lot beef cattle feedlots. This research determined PM10 emission fluxes from a commercial cattle feedlot in Kansas using WindTrax, a backward Lagrangian stochastic-based atmospheric dispersion model, and the flux-gradient technique, a widely used micrometeorological method for determining air emissions from open area sources. PM10 concentrations were measured at four heights (i.e., 2.00, 3.81, 5.34, and 7.62 m) using tapered element oscillating microbalance (TEOM) and low-volume (LV) PM10 samplers during nine 4/5-day intensive field sampling campaigns conducted at the feedlot from May 2010 through September 2011. Meteorological conditions were also monitored with micrometeorological/eddy covariance instrumentation (i.e., sonic anemometer and infrared hygrometer). In WindTrax, PM10 emission fluxes were calculated by inverse dispersion modeling using sonic anemometer and PM10 concentration measurements at the 3.81-m height, whereas in the flux-gradient technique, PM10 emission fluxes were determined using the calculated vertical PM10 concentration gradients and eddy diffusivities estimated from micrometeorological measurements. Median PM10 emission rates calculated using TEOM-measured hourly PM10 concentrations (n=207) were 23 and 15 µg/m2-s for WindTrax and the flux-gradient technique, respectively. Regression analyses showed that the two methods had high linear relationship (R2 = 0.81). Sensitivity of each method to sampler type used was also verified. In WindTrax (n = 174 sampling runs), TEOM-based PM10 emission rates were higher than LV-based PM10 emission rates by a factor of two. In the flux-gradient technique (n = 61 sampling runs), on the other hand, TEOM-based PM10 emission rates were higher than LV-based PM10 emission rates by 30% only. In both methods, high linear relationship (R2 > 0.81) was observed between TEOM- and LV-based PM10 emission rates.