Multivariate Statistical Assessment of Air Quality: A Case Study |
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Authors: | Vasil Simeonov Stefan Tsakovski Tomaz Lavric Pavlina Simeonova Hans Puxbaum |
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Institution: | (1) Chair of Analytical Chemistry, Faculty of Chemistry, University of Sofia St. Kl. Okhridski , J. Bourchier Blvd. 1, 1164 Sofia, Bulgaria;(2) Institute of Chemical Technologies and Analytics, Vienna University of Technology, Getreidemarkt 9/164, 1060 Vienna, Austria;(3) Institute of Solid State Physics, Bulgarian Academy of Sciences, Tzarigradsko Chaussee 72, 1784 Sofia, Bulgaria |
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Abstract: | The present paper deals with the application of several chemometrical methods (cluster and principal components analysis, source apportioning on absolute principal components scores) to an aerosol data collection from Unterloibach, Austria. It is shown that seven latent factors explaining almost 80% of the total variance are responsible for the data structure and are conditionally identified as secondary aerosol , mineral dust , oil burning , lead smelter , coal burning , salt and fertilizer emission sources. Furthermore, the contribution of each identified source to the formation of the particle total mass and chemical compounds total concentration is calculated. Thus, a reliable assessment of the air quality in the region is performed. The requirements of the sustainability concept for ecological indicators in this case is easily transformed into a multivariate statistical problem taking into account not separate indicators but the specific multivariate nature of aerosol pollution. |
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Keywords: | : Chemometrics air quality cluster analysis principal components analysis source apportioning |
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