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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Cotton Production and Processing Research » Research » Publications at this Location » Publication #340978

Title: A simulated approach to estimating PM10 and PM2.5 concentrations downwind from cotton gins

item Wanjura, John
item Buser, Michael
item PARNELL, C - Texas A&M University
item SHAW, B - Texas A&M University
item LACEY, R - Texas A&M University

Submitted to: Transactions of the ASABE
Publication Type: Abstract Only
Publication Acceptance Date: 5/1/2005
Publication Date: 5/1/2005
Citation: Wanjura, J.D., Buser, M.D., Parnell, C.B., Shaw, B.W., Lacey, R.E. 2005. A simulated approach to estimating PM10 and PM2.5 concentrations downwind from cotton gins. Transactions of the ASABE. 48(5):1919-1925.

Interpretive Summary:

Technical Abstract: Cotton gins are required to obtain operating permits from state air pollution regulatory agencies (SAPRA), which regulate the amount of particulate matter that can be emitted. Industrial Source Complex Short Term version 3 (ISCST3) is the Gaussian dispersion model currently used by some SAPRAs to predict downwind concentrations used in the regulatory process in the absence of field sampling data. The maximum ambient concentrations for PM10 and PM2.5 are set by the National Ambient Air Quality Standard (NAAQS) at 150 'g/m3 and 65 'g/m3 (24 h average), respectively. Some SAPRAs use the NAAQS concentrations as property line concentrations for regulatory purposes. This article reports the results of a unique approach to estimating downwind PM10 and PM2.5 concentrations using Monte Carlo simulation, the Gaussian dispersion equation, the Hino power law, and a particle size distribution that characterizes the dust typically emitted from cotton gin exhausts. These results were then compared to a 10 min concentration (C10) and the concentrations that would be measured by an FRM PM10 and PM2.5 sampler. The total suspended particulate (TSP) emission rate, particle size distributions, and sampler performance characteristics were assigned to triangular distributions to simulate the real-world operation of the gin and sampling systems. The TSP emission factor given in AP-42 for cotton gins was used to derive the PM mass emission rate from a 40 bale/h plant. The Gaussian equation was used to model the ambient TSP concentration downwind from the gin. The performance characteristics for the PM10 and PM2.5 samplers were then used to predict what the measured concentration would be for two PSD conditions. The first PSD assumption was that the mass median diameter (MMD) and geometric standard deviation (GSD) were constant at 12 'm and 2, respectively, and the second scenario assigned a triangular distribution to the MMD and GSD of {15, 20, 25} 'm and {1.8, 2.0, 2.2}, respectively. The results show that the PM2.5 fraction of the dust emitted under either PSD condition was negligible when compared to the NAAQS for PM2.5 of 65 'g/m3. The results also demonstrate that correcting for wind direction changes within the hour using the power law reduces the ambient concentration by a factor of 2.45.