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ARS Home » Plains Area » Las Cruces, New Mexico » Cotton Ginning Research » Research » Publications at this Location » Publication #320854

Research Project: Enhancing the Quality, Utility, Sustainability and Environmental Impact of Western and Long-Staple Cotton through Improvements in Harvesting, Processing, and Utilization

Location: Cotton Ginning Research

Title: Preliminary evaluation of AERMOD using site specific stack and ambient sampling data

Author
item MOORE, THOMAS - OKLAHOMA STATE UNIVERSITY
item BUSER, MICHAEL - OKLAHOMA STATE UNIVERSITY
item Whitelock, Derek
item Wanjura, John

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Abstract Only
Publication Acceptance Date: 1/5/2015
Publication Date: 5/11/2015
Citation: Moore, T.W., Buser, M.D., Whitelock, D.P., Wanjura, J.D. 2015. Preliminary evaluation of AERMOD using site specific stack and ambient sampling data. National Cotton Council Beltwide Cotton Conference, January 5-7, 2015, San Antonio, TX. 620-628.

Interpretive Summary:

Technical Abstract: A cotton ginning industry-supported project was initiated in 2008 to develop a robust particulate matter (PM) dispersion modeling dataset that could be used for evaluating current and future PM dispersion models. This paper compares total PM data collected by the industry-supported study at one gin to outputs from EPA’s AERMOD ambient air modelling software. Ambient air samplers were placed at 35 locations that were arranged around a gin in three concentric circles. Stack emissions data, on-site weather data, emissions points, and structure data were used as inputs in AERMOD. Modeled outputs were compared to the collected total PM concentrations at the specified locations around the gin. The percent difference of modeled from collected concentrations were mapped in order to analyze its spatial distribution. This analysis found that the model tended to underestimate concentrations close to the emission source. As distance increased from the emissions source, modeled and sampled data began to align then flipped, with the model overestimating nearly all concentrations at distances greater than 100 meters from the source. Slides used in this presentation are shown in Figure 1.