Evaluation of estimation methods for organic carbon normalized sorption coefficients

Abstract

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 X 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 X t . Molecular connectivity correlations seemed to be best suited for use with specific chemical classes. The LSER provided a better fit than m X t but not as good as the correlation with K oc . 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.