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Agricultural operations across the United States are encountering difficulties complying with current air pollution regulations for particulate matter (PM). PM is currently regulated in terms of particle diameters less than or equal to a nominal 10 μm (PM10); however, current legislation is underway to regulate PM with diameters less than or equal to a nominal 2.5 μm (PM2.5). The goals of this research were to determine the biases and uncertainties associated with current PM10 and PM2.5 sampling methods and to determine the extent to which these errors may impact the determination of cotton gin emission factors. Ideally, PM samplers would produce an accurate measure of the pollutant indicator; for instance, a PM10 sampler would produce an accurate measure of PM less than or equal to 10 μm. However, samplers are not perfect and errors are introduced because of the established tolerances associated with sampler performance characteristics and the interaction of particle size and sampler performance characteristics. Results of this research indicated that a source emitting PM characterized by a mass median diameter (MMD) of 20 μm and a geometric standard deviation (GSD) of 1.5 could be forced to comply with a 3.2 and 14 times more stringent regulation of PM10 and PM2.5, respectively, than a source emitting PM characterized by a MMD of 10 μm and a GSD of 1.5. These estimates are based on both sources emitting the same concentrations of true PM or concentrations corresponding to the particle diameters less than the size of interest. Various methods were used to estimate the true PM10 and PM2.5 emission factors associated with cotton gin exhausts and the extent to which the sampler errors impacted the PM regulation. Results from this research indicated that current cotton gin emission factors could be over-estimated by about 40%. This over-estimation is a consequence of the relatively large PM associated with cotton gin exhausts. These PM sampling errors are contributing to the misappropriation of source emissions in State Implementation Plans, essentially forcing Air Pollution Regulatory Agencies to require additional controls on sources that may be incorrectly classified has high emitters.

Knowledge gaps related to mass transfer processes involved in passive air sampling of semivolatile organic compounds and factors potentially influencing passive sampling rates (PSRs) were addressed with controlled laboratory experiments, mass transfer modeling, and a field sampling campaign. The observed non-uniform SVOC distributions within porous passive sampling media (PSMs) contradict an assumption in an earlier passive air sampling theory and proved the existence of a kinetic resistance on the PSM side. This resistance can affect PSRs as revealed by a new PAS model which is based on fundamental laws of mass transfer in air and porous media. By considering mass transfer processes within the PSM, the model is able to explain the large variations of field calibrated PSRs with temperature and between SVOC species and the two-stage uptake process, which cannot be addressed by the earlier PAS theory. Because the PSM side kinetic resistance invalidates the assumption that depuration compounds added to the PSM prior to deployment are subject to the same kinetic resistance as the sampled SVOCs, PSRs derived from the loss rates of depuration compounds can differ from the actual PSRs of the sampled SVOCs. Using such PSRs could thus introduce additional uncertainty to PAS-derived air concentrations. Experiments using XAD-resin and silica-gel filled mesh cylinder as PSMs for the uptake of SVOCs and water vapor respectively revealed that sorbent in the inner portion of the PSM does not take part in chemical uptake; PSRs are thus proportional to the interfacial transfer area but not the amount of the sorbent. Accordingly, thinner PSM can be used to reduce the amount of sorbent while keeping or even increasing the PSRs. Optimized designs of PASs could be tested time efficiently using the gravimetrical approach based on water vapor uptake by silica gel.

Knowledge gaps related to mass transfer processes involved in passive air sampling of semivolatile organic compounds and factors potentially influencing passive sampling rates (PSRs) were addressed with controlled laboratory experiments, mass transfer modeling, and a field sampling campaign. The observed non-uniform SVOC distributions within porous passive sampling media (PSMs) contradict an assumption in an earlier passive air sampling theory and proved the existence of a kinetic resistance on the PSM side. This resistance can affect PSRs as revealed by a new PAS model which is based on fundamental laws of mass transfer in air and porous media. By considering mass transfer processes within the PSM, the model is able to explain the large variations of field calibrated PSRs with temperature and between SVOC species and the two-stage uptake process, which cannot be addressed by the earlier PAS theory. Because the PSM side kinetic resistance invalidates the assumption that depuration compounds added to the PSM prior to deployment are subject to the same kinetic resistance as the sampled SVOCs, PSRs derived from the loss rates of depuration compounds can differ from the actual PSRs of the sampled SVOCs. Using such PSRs could thus introduce additional uncertainty to PAS-derived air concentrations. Experiments using XAD-resin and silica-gel filled mesh cylinder as PSMs for the uptake of SVOCs and water vapor respectively revealed that sorbent in the inner portion of the PSM does not take part in chemical uptake; PSRs are thus proportional to the interfacial transfer area but not the amount of the sorbent. Accordingly, thinner PSM can be used to reduce the amount of sorbent while keeping or even increasing the PSRs. Optimized designs of PASs could be tested time efficiently using the gravimetrical approach based on water vapor uptake by silica gel.