QSAR Models of Reaction Rate Constants of Alkenes with Ozone and Hydroxyl Radical

The reaction rate constants of ozone with 95 alkenes (-logk(O3)) and the hydroxyl radical (center dot OH) with 98 alkenes (-logk(OH)) in the atmosphere were predicted by quantitative structure-activity relationship (QSAR) models. Density functional theory (DFT) calculations were carried out on respective ground-state alkenes and transition-state structures of degradation processes in the atmosphere. Stepwise multiple linear regression (MLR) and general regression neural network (GRNN) techniques were used to develop the models. The GRNN model of -logk(O3) based on three descriptors and the optimal spread sigma of 0.09 has the mean root mean square (rms) error of 0.344; the GRNN model of -logk(OH) having four descriptors and the optimal spread sigma of 0.14 produces the mean rms error of 0.097. Compared with literature models, the GRNN models in this article show better statistical characteristics. The importance of transition state descriptors in predicting k(O3) and k(OH) of atmospheric degradation processes has been demonstrated.