Improved Predictions of Dissolved Organic Carbon-Water Partitioning and Unveiling the Chemodiversity of Dissolved Organic Matter

Dissolved organic matter (DOM) is a complex mixture oforganiccompounds with chemical heterogeneity in natural soils, sediments,and waters. Predicting the dissolved organic carbon (DOC)-waterpartition coefficients (K (DOC)) of organicpollutants to DOMs from various sources is important for assessingtheir fate and bioavailability. However, the accuracy of the recentlydeveloped polyparameter linear free energy relationship (pp-LFER) K (DOC) models is generally restricted by the smalldata set, inclusion of experimental data from unreliable measurementmethods, or undefined selection standards. The aim of this study wasto establish pp-LFER models for predicting the K (DOC) of nonionic organic chemicals to a variety of sources ofDOMs and to get an understanding of DOM chemodiversity. A reliableand expanded experimental K (DOC) data setwas compiled. Improved pp-LFER models were developed and assessedfor All DOM (DOM from all sources), Aldrich humic acid (HA), RothHA, soil porewater DOM, sediment porewater DOM, natural aquatic DOM,natural terrestrial DOM, natural DOM, and commercial DOM. The modelsdeveloped in this study were reasonably robust and accurate with aroot mean square error (RMSE) of 0.538 for the All DOM model and RMSEfrom 0.196 to 0.860 for the specific DOMs. Also, the models generallyperformed better than previously published ones. Moreover, the systemparameters of the models well described the chemical variabilitiesbetween soil porewater DOM and sediment porewater DOM, between naturalaquatic DOM and natural terrestrial DOM, and between natural DOM andcommercial DOM regarding polarizability, dipolarity, H-bond-acceptingand -donating ability, and cavity formation energy. This study provideseffective tools to assess the tendencies of organic chemicals to DOMsand improves our understanding of the chemical heterogeneity of DOMsfrom different sources.