We developed and applied two types of biological fingerprinting methods to characterize sources of fugitive dust. The first type was DNA based [Intergenic Transcribed Spacer (ITS) analysis), and the second type was fatty acid based (Phospholipid Fatty Acid (PLFA) and Soil Fatty Acid Methyl Ester (SFAME) analyses]. Major goals included overcoming detection limit problems associated with small samples of dust, determining relationships between sources and dust, and classifying source materials. Two dust generation/collection chambers were constructed to enable source and dust sample comparisons under controlled conditions. Source and dust comparisons were also performed on samples collected during an agricultural operation. Detection limits were lower for DNA-based than fatty acid-based methods. Both methods yielded unique biological signatures from Central Valley fugitive dust sources. The DNA-based method revealed strong similarities between source and dust fingerprints, indicating its promise for source characterization and apportionment. Classification models including artificial neural networks were optimized to ana lyze the large data sets generated by both types of biological fingerprinting. Appropriately applied, they classified source and dust samples with 99% accuracy. Continuing advances in molecular biology technologies will increase the ability to rapidly characterize large numbers of samples and streamline the biological fingerprinting methods currently used.
For questions regarding this research project, including available data and progress status, contact: Research Division staff at (916) 445-0753
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