Abstract
Dissolved organic matter (DOM) is a complex mixture of organic compounds with chemical heterogeneity in natural soils, sediments, and waters. Predicting the dissolved organic carbon (DOC)–water partition coefficients (KDOC) of organic pollutants to DOMs from various sources is important for assessing their fate and bioavailability. However, the accuracy of the recently developed polyparameter linear free energy relationship (pp-LFER) KDOC models is generally restricted by the small data set, inclusion of experimental data from unreliable measurement methods, or undefined selection standards. The aim of this study was to establish pp-LFER models for predicting the KDOC of nonionic organic chemicals to a variety of sources of DOMs and to get an understanding of DOM chemodiversity. A reliable and expanded experimental KDOC data set was compiled. Improved pp-LFER models were developed and assessed for All DOM (DOM from all sources), Aldrich humic acid (HA), Roth HA, soil porewater DOM, sediment porewater DOM, natural aquatic DOM, natural terrestrial DOM, natural DOM, and commercial DOM. The models developed in this study were reasonably robust and accurate with a root mean square error (RMSE) of 0.538 for the All DOM model and RMSE from 0.196 to 0.860 for the specific DOMs. Also, the models generally performed better than previously published ones. Moreover, the system parameters of the models well described the chemical variabilities between soil porewater DOM and sediment porewater DOM, between natural aquatic DOM and natural terrestrial DOM, and between natural DOM and commercial DOM regarding polarizability, dipolarity, H-bond-accepting and -donating ability, and cavity formation energy. This study provides effective tools to assess the tendencies of organic chemicals to DOMs and improves our understanding of the chemical heterogeneity of DOMs from different sources.
Published Version
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