Submitted to: California Regional Pm10 Pm2.5 Air Quality Study Report
Publication Type: Research Notes
Publication Acceptance Date: 1/15/2000
Publication Date: N/A
Citation: Interpretive Summary: Air and water pollution negatively affect offsite areas causing billions of dollars in damage in the United States annually. The health impact of particulate matter away from the source can be quite dramatic, and particulate matter has been implicated in adverse effects on human health. Pollution prevention and control costs over $1 billion annually, and to be successful requires accurate identification of the origins of displaced materials. Chemical composition and particle size distribution are currently used to identify pollution sources of nongeological sources, but are not successful in accurately identifying sources of geological materials such as soils. Methods to identify sources of particulates of geologic origin are needed because water and air quality are negatively affected by displaces soil or dust particulates. The present invention relates to methods to determine the source of soil particles. A biological lprofile of a soil sample is used to identify the geographic source of the soil sample. It has been discovered that soils from different geographic locations show unique biological profiles which can be used as fingerprints to identify the source of soil samples. This new source detection technology is useful to target nonpoint pollution as well as point sources, and provides a powerful tool for the development of policies for pollution control that are more effective than in the past.
Technical Abstract: Air quality concerns in the San Joaquin Valley stem from mineral dusts that originate in the valley and are transported as aerosols throughout the area. It has been shown that the origin of dust can be determined by comparing fatty acid methyl ester (FAME) fingerprints of dust samples back to a FAME generated soil fingerprint library. FAME analysis on whole soil was used to build a soil fingerprint library containing 14 sources in the San Joaquin Valley, including non-agricultural samples (disturbed, agricultural unpaved roads, construction, rural paved roads, urban paved roads, and residential unpaved roads) and agricultural operations (almond, cotton, dairy, safflower, feedlot, grapes, staging area, and tomato). Agricultural soils separated from the more urban type soils. Samples taken from almond, dairy, feedlot, and paved road sites separated clearly from other samples. When these samples were removed from the data set, separation of construction, staging, disturbed, and unpaved roads from the samples taken from cropped areas was evident. The location of the sample site did not greatly influence the fingerprint; however, greater variability in treatment fingerprint could be explained by location differences. Location differences were most evident with cotton and almond samples. These data demonstrate the ability of FAME fingerprints to differentiate among soils, and therefore potential dust sources.