Evaluation of estimation methods for organic carbon normalized sorption coefficients

A critically evaluated set of 94 soil water partition coefficients normalized to soil organic carbon content (K-oc) is presented for 11 classes of organic chemicals. This data set is used to develop and evaluate K-oc estimation methods using three different descriptors. The three types of descriptors used in predicting K-oc were octanol/water partition coefficient (K-ow), molecular connectivity ((m) chi(t)), and linear solvation energy relationships (LSERs). The best results were obtained estimating K-oc from K-ow, though a slight improvement in the correlation coefficient was obtained by using a two-parameter regression with K-ow and the third order difference term from (m) chi(t). Molecular connectivity correlations seemed to be best suited for use with specific chemical classes. The LSER provided a better fit than (m) chi(t) but not as good as the correlation with K-ow. The correlation to predict K-oc from K-ow was developed for 72 chemicals; log K-oc = 0.903* log K-ow + 0.094. This correlation accounts for 91% of the variability in the data for chemicals with log K-ow ranging from 1.7 to 7.0. The expression to determine the 95% confidence interval on the estimated K-oc is provided along with an example for two chemicals of different hydrophobicity showing the confidence interval of the retardation factor determined from the estimated K-oc. The data showed that K-oc is not likely to be applicable for chemicals with log K-ow < 1.7. Finally, the K-oc correlation developed using K-ow as a descriptor was compared with three nonclass-specific correlations and two ''commonly used'' class-specific correlations to determine which method(s) are most suitable.