Modeling and prediction of photolysis half-lives of polycyclic aromatic hydrocarbons in aerosols by quantum chemical descriptors.

Quantitative structure-property relationship (QSPR) modeling is a powerful approach for predicting environmental fate parameters of organic pollutants with their structure descriptors. This study reports QSPR models for photolysis half-lives of polycyclic aromatic hydrocarbons (PAHs) in aerosols. Quantum chemical descriptors computed with density functional theory at B3LYP/6-31G(d) level and partial least squares (PLS) analysis with optimizing procedure were used for generating QSPR models. The correlation coefficient of the optimal model was 0.993, and the fitting results showed this optimal model had high fitting precision and good predictability. The predicted photolysis half-lives by the optimal model are very close to those observed. The PLS assistant analysis indicated that PAHs with large electronic spatial extent tend to be photolyzed faster, while PAHs with high molecular total energy and small Mulliken atomic charges on the most negative carbon atom tend to be photolyzed slower in aerosols.