Prediction of soot–water partition coefficients for selected persistent organic pollutants from theoretical molecular descriptors

Quantitative structure–property relationship (QSPR) models were developed for soot–water partition coefficient (KSC) values of selected persistent organic pollutants (POPs), i.e. 10 polychlorinated dibenzo-p  -dioxins and dibenzofurans, nine polychlorinated biphenyls, four polycyclic aromatic hydrocarbons and two polybrominated diphenyl ethers, using partial least squares (PLS) regression. Quantum chemical descriptors computed by parameterized model revision 3 Hamiltonian method were used as predictor variables. The cross-validated Qcum2 value for the optimal QSPR model is 0.844, indicating a good predictive capability for the log KSC values of these chemicals. The QSPR results showed that average molecular polarizability (α), standard heat of formation (ΔHf) and energy of the lowest unoccupied molecular orbital (ELUMO) have dominant effects on KSC of POPs. The results suggested that log KSC values of POPs increase with the increase of α. Contrarily, log KSC values decrease with the increase of ELUMO and ΔHf of POPs.