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Pattern Recognition and Factor Analysis Applied to Characterization of Particulate Composition from Southwestern Desert Atmosphere.

机译:模式识别与因子分析在西南荒漠大气颗粒物组成特征分析中的应用。

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摘要

Measurements made of the composition of atmospheric particulates collected in the greater Tucson, Arizona, area have been examined using pattern recognition and factor analysis. Cluster analysis showed Si, Ti, Cs, Li, Rb, Al, K, Fe, Ca, Mg, Na, Mn, Sr, Co, and Cr to be primarily of soil origin. Factor analysis separated the variance of the data base into a small number of factors which can reproduce the correlation matrix and can identify other sources of particulates. The source of NH4(+) and SO4(2-) is external to the Tucson area. The remaining species--NO3(-), Zn, Pb, Cu, Ni, and Cd--have several sources. Relative to a remote desert location, Pb in the urban particulates is of the greatest enrichment, followed by the elements of a crustal origin.

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