A general-applicable model for estimating the binding coefficient of organic pollutants with dissolved organic matter

The binding constant (K_doc) of organic pollutants (OPs) with dissolved organic matter (DOM) is an important parameter in determining the partitioning of OPs in the aquatic environment. Most estimation models have focused on calculating the K_doc of a specific group of OPs but failed to obtain K_doc values of different OPs effectively over the last three decades. In this study, we attempted to build a general-applicable K_doc model based on various organic compounds' K_doc values from the literature since 1973. Two multiple linear regression models, a DOM nonspecific model and an Aldrich HA model, were developed based on two solid and easy to access parameters-molecular connectivity indices (MCI) and polarity correction factors (PCF). In addition, the models' corresponding K_ow-K_doc models, which were mostly used in previous model studies, were developed for comparison. The adjusted determining coefficient (adj-R²) and standard error of the estimate (SEE) of the DOM nonspecific MCI-PCF-K_doc model were 0.815 and 0.579, respectively, whereas the adj-R² and SEE for the MCI-PCF-K_doc model of Aldrich HA reached 0.907 and 0.438, respectively. The Aldrich HA model showed higher pertinence to the nonspecific model. Furthermore, both models exhibited better fit than the K_ow-K_doc models. The dipole moment modification attempts did not significantly improve either MCI-PCF-K_doc models; hence, the two models were not altered with the dipole moment. The robustness tests by a Jackknifed method showed that the two MCI-PCF-K_doc models exhibited higher robustness than the K_ow-K_doc. Of all of the OPs, the phenols contributed the most to their robustness. Furthermore, a sensitivity analysis showed that the two MCI-PCF-K_doc models were sensitive to the robust parameters.