Investigation of the relationship between chemical composition and size distribution of airborne particles by partial least squares and positive matrix factorization

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Read Full Article (file size: 943269 bytes) Cited by JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 110, D07S18, doi:10.1029/2004JD005050, 2005 Investigation of the relationship between chemical composition and size distribution of airborne particles by partial least squares and positive matrix factorization Liming Zhou Center for Air Resources Engineering and Science and Department of Chemical Engineering, Clarkson University, Potsdam, New York, USA Philip K. Hopke Center for Air Resources Engineering and Science and Department of Chemical Engineering, Clarkson University, Potsdam, New York, USA Charles O. Stanier Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA Spyros N. Pandis Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA John M. Ondov Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, USA J. Patrick Pancras Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, USA Abstract Two multivariate data analysis methods, partial least square (PLS) and positive matrix factorization (PMF), were used to analyze aerosol size distribution data and composition data. The relationships between the size distribution data and composition data were investigated by PLS. Three latent variables summarized chemical composition data and most variations in size distribution data especially for large particles and proved the existence of the linearity between the two data sets. The three latent variables were associated with traffic and local combustion sources, secondary aerosol, and coal-fired power plants. The size distribution, particle composition, and gas composition data were combined and analyzed by PMF. Source information was obtained for each source using size distribution and chemical composition simultaneously. Eleven sources were identified: secondary nitrate 1 and 2, remote traffic, secondary sulfate, lead, diesel traffic, coal-fired power plant, steel mill, nucleation, local traffic, and coke plant. Received 20 May 2004; accepted 11 October 2004; published 9 March 2005. Keywords: aerosol; size distribution; chemical composition; partial least squares (PLS); positive matrix factorization (PMF); receptor model. Index Terms: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801, 4906); 0345 Atmospheric Composition and Structure: Pollution: urban and regional (0305, 0478, 4251); 0478 Biogeosciences: Pollution: urban, regional and global (0345, 4251); 0394 Atmospheric Composition and Structure: Instruments and techniques. Read Full Article (file size: 943269 bytes) Cited by Citation: Zhou, L., P. K. Hopke, C. O. Stanier, S. N. Pandis, J. M. Ondov, and J. P. Pancras (2005), Investigation of the relationship between chemical composition and size distribution of airborne particles by partial least squares and positive matrix factorization, J. Geophys. Res., 110, D07S18, doi:10.1029/2004JD005050. Copyright 2005 by the American Geophysical Union.

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