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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 #142075
Title: PM2.5 SAMPLER ERRORS DUE TO THE INTERACTION OF PARTICLE SIZE AND SAMPLER PERFORMANCE CHARACTERISTICS

Author
item Buser, Michael
item PARNELL, JR., CALVIN - TEXAS A&M UNIVERSITY
item LACEY, RONALD - TEXAS A&M UNIVERSITY
item SHAW, BRYAN - TEXAS A&M UNIVERSITY

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: 1/7/2003
Publication Date: 4/15/2003
Citation: Buser, M.D., Parnell, Jr., C.B., Lacey, R.E., Shaw, B.W. PM2.5 Sampler errors due to the interaction of particle size and sampler performance characteristics. Proceedings of Beltwide Cotton Conferences. Joint Cotton Ginning/Cotton Engineering Systems Conferences. CD-ROM. Memphis, TN: The National Cotton Council of America. 2003. p. 2429-2444.

Interpretive Summary: Agricultural operations are encountering difficulties complying with the current air pollution regulations for particulate matter (PM). The regulations are based on the National Ambient Air Quality Standards (NAAQS), which set maximum limits for ambient PM based on protecting public health. Current legislation is underway to enforce the regulation of PM with a particle diameter less than or equal to a nominal 2.5 um (PM2.5). Compliance with the PM regulations is determined by property line sampling or dispersion modeling. Modeling requires emission rates, which are determined from EPA's list of emission factors. Emission factors are industry specific. All property line sampling for compliance purposes require the use of EPA approved samplers. Ultimately, these samplers would produce an accurate measure of PM2.5 (i.e., produce an accurate measure of PM less than or equal to 2.5 um). However, samplers are not perfect and errors are introduced due to the interaction of the particle size and sampler performance characteristics. Theoretical simulations were used to demonstrate how these errors result in the unequal regulation between industries and create undue economic burdens on agricultural operations. In order to achieve equal regulation among all industries, PM2.5 measurements must account for these errors. Adoption of the findings in this report will provide a means to more equitably assess the contributions of various sources to air quality.

Technical Abstract: Agricultural operations across the United States are encountering difficulties in complying with the current air pollution regulations for particulate matter (PM). The National Ambient Air Quality Standards (NAAQS) for PM in terms of PM2.5, are ambient air concentration limits set by EPA that should not be exceeded. Further, State Air Pollution Regulatory Agencies (SAPRA's) utilize the NAAQS to regulate criteria pollutants emitted by industries by applying the NAAQS as a property line concentration limit. The primary NAAQS are health-based standards and therefore, an exceedance implies that it is likely that there will be adverse health effects for the public. Since the proposal of the PM2.5 regulation, numerous journal articles and technical references have been written to discuss the epidemiological effects, trends, regulation, methods of determining PM2.5, etc. A common trend among many of these publications is the use of samplers to collect information on PM2.5. All too often, the sampler data are assumed to be an accurate measure of PM2.5. The fact is that issues such as sampler uncertainties, environmental conditions, and material characteristics for which the sampler is measuring must be incorporated for accurate sampler measurements. The focus of this manuscript is on the errors associated with the particle size distribution (PSD) characteristics of the material in the air that is being sampled, sampler performance characteristics, the interaction between these two characteristics, and the effect of this interaction on the regulatory process. Theoretical simulations were conducted to determine the range of errors associated with this interaction for the PM2.5 sampler. Results from these simulations indicated that a source emitting PM characterized by a mass median diameter (MMD) of 20 um and a geometric standard deviation (GSD) of 1.5 could be forced to comply with a 14 times more stringent regulation than a source emitting PM characterized by a MMD of 10 um and a GSD of 1.5. Therefore, in order to achieve equal regulation among differing industries, PM2.5 measurements MUST be based on true concentration measurements.