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Source apportionment of ambient particles in steubenville,oh using specific rotation factor analysis
Institution:1. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 210008 Nanjing, PR China;2. College of Life Sciences, Zhejiang University, 310058 Hangzhou, Zhejiang, PR China;3. Biodesign Swette Center for Environmental Biotechnology, Arizona State University, 1001 South McAllister Avenue, Tempe, AZ 85287-5701, USA;1. Pharmaceutical Chemistry Department, Faculty of Pharmaceutical Sciences & Pharmaceutical Industries, Future University, 12311 Cairo, Egypt;2. Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, Egypt;3. Analytical Chemistry Department, Faculty of Pharmacy, Ahram Canadian University, Egypt
Abstract:A statistical approach, Specific Rotation Factor Analysis (SRFA), has been developed to identify and apportion sources of ambient air pollutants. To increase the statistical weight of the source tracer elements, this technique is based on the analysis of the covariance matrix. The obtained eigenvectors are obliquely rotated in order to maximize the loadings of the tracer quantities of the corresponding source (specific rotations). Source contributions and profiles are estimated by regressing elemental and mass concentrations on the factor loadings.The ability of the SRFA technique to resolve major aerosol sources and determine their profiles and contributions at the receptor site is demonstrated by applying it to a subset of fine particle elemental and mass concentration data from Steubenville, OH.
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