Off-site transport of atmospheric contaminants, such as agrochemicals, volatile organic compounds, and particulate matter (PM), from agricultural processes can have detrimental effects to surrounding ecosystems. Determining these losses from the various agricultural systems requires model modifications and ground truthing from field measurements. However, the data sets available for the models often scarce and lack the rigor for model use. This is a primary issue for United States cotton ginning industry which until now does not have scientifically-sound information about heterogeneous PM emissions from this low-altitude source. In addition, the regulation-recommended air dispersion models have a potential to overestimate the concentration for low-altitude emission sources by as much as a factor of ten. Therefore, a sampling campaign was conducted to collect PM emissions and associated meteorological data to provide a robust data set for assessment and modelling of PM concentrations and dispersion, and a dispersion correction factor was developed for improving the predictive accuracy for low-altitude emission sources. During the experiment, field samples of PM2.5, PM10, and total suspended particle (TSP) were collected during 11 experiments at a typical cotton gin. Concentration profiles were developed, dispersion of the air pollutants was assessed, and the regulatory recommended model (AERMOD) was modified and validated. Pollutant concentrations were negatively correlated with height (p &lt; 0.05), distance from source (p &lt; 0.05), and standard deviation of wind direction (p &lt; 0.001), and positively correlated with average wind speed (p &lt; 0.001). In addition, pollutant concentrations were overestimated by AERMOD by factors of 64.7, 6.97 and 7.44 on average for PM2.5, PM10, and TSP, and thus dispersion correction factors were developed. Cross-validation results showed that predictive accuracy was greatly improved by applying AERMOD coupled with dispersion correction factors, and the average overprediction factors decreased to 3.75, 1.52, and 1.44 for PM2.5, PM10, and TSP, respectively. Dispersion correction factors are recommended for regulatory and practical use. Similar approaches can be extended for a range of agriculturally related activities that are low-altitude emission sources, including animal operations, food and agricultural product processing facilities, and combustion of agricultural wastes.

Assessment and modeling of particulate matter concentration and dispersion from low-altitude emission sources

ACS Fall 2021

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