QSPR-based prediction of gas/particle partitioning of polychlorinated biphenyls in the atmosphere Original Research Article

By reviewing the existing models for describing gas/particle partitioning of semi-volatile organic compounds in the atmosphere, it was assumed that gas/particle partition coefficient, expressed as Kp, may be predicted using molecular descriptors. Overall 14 molecular descriptors of each compound calculated using semi-empirical method parametric model 3 (PM3) were tested against log Kp of selected PCBs to determine the best ones governing partitioning. Eight descriptors molecular weight (Mw), molecular volume (Mv), total energy (TE), electronic energy (EE), squared atom electron densities on carbon, hydrogen and chlorine atoms in a given molecule image and average molecular polarizability (αm) were found to be highly correlated with log Kp compared to other molecular descriptors. Using Partial Least-Squares Regression method (PLS), two-, three- and four-descriptor QSPR models with high fitting characters were successfully developed and their robustness and predictive power were further validated by internal cross-validation and external test. Finally, the gas/particle partition coefficients of all 209 PCBs were predicted for the first time.