Polarizability as a single parameter to predict octanol-water partitioning coefficient and bioconcentration factor for persistent organic pollutants

Li, Xiaolei (2016) Polarizability as a single parameter to predict octanol-water partitioning coefficient and bioconcentration factor for persistent organic pollutants. Masters thesis, Memorial University of Newfoundland.

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Abstract

Surface microlayer (SML) is critical to various Earth system processes due to its unique physiochemical properties. One of main concerns regarding SML is regarding the persistent organic pollutants (POPs) partition. This process is vital in understanding air-sea exchange and, to a large extent, the global transportation of POPs. POPs have potential significant impacts on human health and on the aquatic environment, and their properties are critical to understanding and predicting the environmental fate of persistent chemicals. To study the partition properties of SML, it would be interesting to study two related properties of POPs, the octanol-water partitioning coefficient and the bioconcentration factor, both of which serve as criteria to determine the accumulation of a compound. Although numerous models have been previously published to predict Kow and/or BCF, the results are not statistically robust. The resulting linear free energy relationships obtained from poly-parameters on a strictly statistical basis, although they yield good results, may cause chance correlation and bear no physico-chemical meaning. Given that dispersion forces are the dominant inter-molecular interaction in non-polar compounds and that molecular polarizability can describe dispersion forces in condensed phase partitioning, we developed a method to predict Kow and BCF using molecular polarizability as a single parameter. The polarizabilities of non-polar compounds with available consistent measurement data were calculated using density functional theory with B3LYP functionals and the 6-311g(d, p) basis set in Gaussian program (09 version or 03 version); a single-parameter structure-activity relationship was then separately derived from the modeled compounds using a linear least-squares regression for Kow and BCF. We modelled BCF in the real world for a microorganism and a fish (Cyprinos Carpio). A comparison with data from other models showed that this is a simple but effective method to predict Kow and BCF for non-polar compounds. The prediction power for BCF using this method in microorganism shows that polarizability would be a good indication for partition SML due to the fact that both microorganism and SML can be seen as biofilms. Sampling POPs in the SML is a challenge to the scientist; a glass plate with a vacuum squeegee was developed to efficiently collect a freshwater SML sample from a local pond for GC-MS analysis of POPs.

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