Predicting Sorption of Pesticides and Other Multifunctional Organic Chemicals to Soil Organic Carbon

Abstract

Chemicals of current environmental concern are often multifunctional and more polar and more complex than classical pollutants such as polychlorinated biphenyls (PCB) or polycyclic aromatic hydrocarbons (PAH). Traditional models for predicting the partitioning in the environment such as group contribution methods or correlations with octanol-water partitioning cannot be expected to work well for such complex chemicals. In contrast, poly parameter Linear Free Energy Relationships (pp-LFERs) have been proven to describe partitioning of polar and nonpolar chemicals in all kinds of sorbing systems. Here, a pp-LFER model for soil-water partitioning was calibrated with data for 79 polar and nonpolar compounds that cover a very wide range of the relevant intermolecular interactions. The data set used for the model calibration in this work is more diverse and covers a wider range of the chemical space than other pp-LFERs published so far. Subsequently, the experimental data for about 50 pesticides and pharmaceuticals -not involved in the model calibration- were used as independent validation of this new calibrated model. The model performs well with a standard error of 0.25 log units for fitting the calibration data and with a root-mean-square error of 0.4 log units for the pesticides and pharmaceuticals. The validation with the independent data set for pesticides and pharmaceuticals also shows that the pp-LFER model reported here performs better compared to earlier published pp-LFER models and to the traditional log Kow correlation.