Article ID Journal Published Year Pages File Type
4410170 Chemosphere 2012 7 Pages PDF
Abstract

The hydrophobic parameter represented by the octanol/water partition coefficient (log P) is commonly used to predict the soil sorption coefficient (Koc). However, a simple non-linear relationship between log Koc and log P has not been reported in the literature. In the present paper, soil sorption data for 701 compounds was investigated. The results show that log Koc is linearly related to log P for compounds with log P in the range of 0.5–7.5 and non-linearly related to log P for the compounds in a wide range of log P. A non-linear model has been developed between log Koc and log P for a wide range of compounds in the training set. This model was validated in terms of average error (AE), average absolute error (AAE) and root-mean squared error (RMSE) by using an external test set with 107 compounds. Nearly the same predictive capacity was observed in comparison with existing models. However, this non-linear model is simple, and uses only one parameter. The best model developed in this paper is a non-linear model with six correction factors for six specific classes of compounds. This model can well predict log Koc for 701 diverse compounds with AAE = 0.37. The reasons for systemic deviations in these groups may be attributed to the difference of sorption mechanism for hydrophilic/polar compounds, low solubility for highly hydrophobic compounds, hydrolysis of esters in solution, volatilization for volatile compounds and highly experimental errors for compounds with extremely high or low sorption coefficients.

► We found a non-linear relationship between sorption coefficient and hydrophobicity. ► Hydrophobicity is the driving force of sorption for hydrophobic chemicals. ► Organic matter is not the sorption site for highly hydrophilic compounds. ► Chemical solubility, hydrolysis and volatilization affect sorption coefficient. ► The experimental error of sorption coefficient is related to soil/solution ratio.

Related Topics
Life Sciences Environmental Science Environmental Chemistry
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