Source identification of PCBs in sediments from the Milwaukee Harbor Estuary,USA |
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| Affiliation: | 1. Department of Chemistry, Makerere University, P.O. Box 7062, Kampala, Uganda;2. Laboratory of Green Chemistry, Lappeenranta University of Technology, Sammonkatu 12, 50130 Mikkeli, Finland;3. State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;4. Institute of Groundwater Ecology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany;1. Department of Plant Sciences, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran;2. Department of Biology, Islamic Azad University, Gorgan Branch, Gorgan, Iran;1. Faculty of Chemistry, VNU University of Science, Vietnam National University, 19 Le Thanh Tong, Hoan Kiem, Hanoi, Viet Nam;2. Faculty of Environment, Hanoi University of Natural Resources and Environment, Cau Dien, Tu Liem, Hanoi, Viet Nam;3. Faculty of Geology, VNU University of Science, Vietnam National University, 334 Nguyen Trai, Thanh Xuan, Hanoi, Viet Nam;4. Institute for Nuclear Science and Technology, 179 Hoang Quoc Viet, Hanoi, Viet Nam;5. Hiyoshi Corporation, 908 Kitanosho, Omihachiman, Shiga 523-8555, Japan;6. Research Organization for University-Community Collaborations, Osaka Prefecture University, 1-2 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan |
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| Abstract: | This work focuses on the determination of PCB source profiles and their contributions to sediments in the Milwaukee Harbor Estuary by a principal component analysis (PCA) model. The model was recently developed and, for the first time, applied to apportion pollutant sources in sediments. Factor loadings and scores were computed, rotated via nonnegative constraints, and matched with candidate Aroclor profiles. Contamination by Aroclors 1016, 1242, 1254, and 1260 were identified for cores VC 6, 9, and 12 based on a log Q2 criterion. The majority of PCB contribution was from a combination of Aroclors 1016 and 1242. Similarity between Aroclors 1016 and 1242 obscured resolution between the two profiles. Results from a chemical mass balance (CMB) model with known Aroclor profiles were in good agreement with the prediction from the PCA model. |
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