As part of a Cooperative Agreement with DOE-NETL, the University of North Dakota Energy and Environmental Research Center (EERC) is developing advanced sampling and analysis methodologies for particulate matter that can be used for source apportionment and to assist in health studies. These techniques will be used to determine sources of fine particulate matter in rural states such as North Dakota.

Ambient particulate matter (PM) sampling and automated scanning electron microscopy, (ASEM) are being used to characterize and evaluate the sources of PM2.5 at three rural sites. Land use in the sampling site locations is dominated by ranching and small grain farming. Potential sources of PM in these areas include diesel- and gasoline-fueled motor vehicles, fugitive dust from gravel roads and agriculture, vegetation and fires, an oil refinery, and coal-fired power plants. PM2.5 samples were collected using an automatic cartridge collection unit for ASEM analysis. An ASEM method has been developed to size and chemically classify individual particles composing PM2.5.

Dispersion modeling was conducted to evaluate the potential effects of primary and secondary combustion PM2.5 on the samples collected. Dispersion modeling results indicate that the prevailing westerly and northwesterly winds during the sampling campaigns may have contributed primary and secondary combustion PM2.5 to the samples collected. Approximately 80 to 90 wt% of the PM2.5 consists of unclassified and organic components. The particles in these classification categories are mostly spores, pollen, soil, and fugitive dust. The remaining 10 to 20 wt% of PM2.5 is inorganic rich. PM2.5 samples from two of the sites are compositionally similar. PM2.5 from the third site, however, contains a greater proportion of sulfur-rich particles, presumably composed of secondary sulfate compounds.