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Application Of Two Receptor Models For The Investigation Of Sites Contaminated With Polychlorinated Biphenyls: Positive Matrix Factorization And Chemical Mass Balance

This study examines the application of two receptor models, namely Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB), on the investigation of sites contaminated with PCBs. Both models are typically used for apportionment of pollution sources in atmospheric pollution studies, however have gained popularity in the last decade on the investigation of PCBs in soil/sediments. The aim of the study is four-fold / (i) to identify the status of PCB pollution in Lake Eymir area via sampling and analysis of PCBs in collected soil/sediment samples, (ii) to modify the CMB model software in terms of efficiency and user-friendliness (iii) to apply the CMB model to Lake Eymir area PCB data for apportionment of the sources as well as to gather preliminary information regarding degradation of PCBs by considering the history of pollution in the area (iv) to explore the use of PMF for both source apportionment and investigation of fate of PCBs in the environment via use of Monte-Carlo simulated artificial data sets.
Total PCB concentrations (Aroclor based) were found to be in the range of below detection limit to 76.3 ng/g dw with a median of. 1.7 ng/g dw for samples collected from the channel between Lake Mogan and Lake Eymir. Application of the CMB model yield contribution of highly chlorinated PCB mixtures (Aroclor 1254 and Aroclor 1260 / typically used in transformers) as sources. The modified CMB model software provided user more efficient and user friendly working environment. Two uncertainty equations, developed and existing in literature, were found to be effective for better resolution of sources by the PMF model.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612190/index.pdf
Date01 June 2010
CreatorsDemircioglu, Filiz
ContributorsImamoglu, Ipek
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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