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Application of pattern recognition and factor analysis for characterization of atmospheric particulate composition in southwest desert atmosphere

Journal Article · · Environ. Sci. Technol.; (United States)
DOI:https://doi.org/10.1021/es60131a003· OSTI ID:7291272
Measurements made of the composition of atmospheric particulate matter collected in the greater Tucson, Ariz., area are examined by use of pattern recognition and factor analysis. Cluster analysis shows Si, Ti, Cs, Li, Rb, Al, K, Fe, Ca, Mg, Na, Mn, Sr, Co, and Cr to be primarily of soil origin. Factor analysis is used to separate the variance of the data base into a small number of factors. Examination of these factors suggests that it is possible to interpret their chemical and physical significance in terms of sources, source strength, and gas-to-particle conversion processes. The results suggest that NH/sup +//sub 4/ and SO/sup 2 -//sub 4/ distributions can be explained by a diffuse area-wide gas-to-particle conversion process which produces these species in a chemically combined state. The species NO/sup -//sub 3/, Zn, Cu, Ni, and Cd would appear to result from multiple processes (sources). Relative to a remote desert location, all elements measured in this study show an enrichment in urban particulates, with Pb being the most enriched (1300%) and SO/sup 2 -//sub 4/, NH/sup +//sub 4/, Zn, Cu, and Cd among the least enriched (150%). These data evaluation techniques show great potential for helping to reduce the dimensionality and explaining the complicated problems associated with atmospheric chemistry and air quality investigations.
OSTI ID:
7291272
Journal Information:
Environ. Sci. Technol.; (United States), Journal Name: Environ. Sci. Technol.; (United States) Vol. 11:8; ISSN ESTHA
Country of Publication:
United States
Language:
English