Predicting Heavy Metal Partition Equilibrium in Soils: Roles of Soil Components and Binding Sites. Issue 4 (17th May 2018) - Peng, Shimeng; Wang, Pei; Peng, Lanfang; Cheng, Tao; Sun, Weimin; Shi, Zhenqing
Abstract : Core Ideas: WHAM 7 successfully predicted heavy metal partition in various soils. Major soil and solution parameters influenced the accuracy of model predictions. Soil organic matter dominated metal binding at most acidic to neutral pH in soils. WHAM 7 predicted bidentate binding as the dominant form of metal complexes. The reactivity and bioavailability of heavy metals in soils are controlled by their binding to reactive soil components, including soil organic matter (SOM), metal (hydr)oxides, and clay minerals. In this study, we specifically investigated how soil components and SOM binding sites controlled metal partition at various chemistry conditions. We used the Windermere Humic Aqueous Model (WHAM 7) to predict the solid‐solution partition and speciation of Cd, Cu, Ni, Pb, and Zn based on compiled literature data including 98 soil samples from five continents. Based on the root‐mean‐square‐error (RMSE) values of logarithm of dissolved metal concentrations between model predictions and experimental results, WHAM 7 reasonably predicted metal partition equilibrium over a wide range of reaction conditions, with RMSE less than 0.5 for Cd and Zn, and less than 1.0 for the other three metals. Soil organic matter dominated metal binding at most acidic to neutral pH, clay minerals were significant at low pH, and iron (hydr)oxides might effectively compete with SOM for metal binding when pH was high. For all five heavy metals, WHAM 7 predicted the bidentate bindings were the dominant form of metal complexes, in which both complexes formed by two carboxylic sites and that by one carboxylic and another phenolic sites were major complexes. The formation of monodentate complexes and electrostatic outer‐sphere complexes was significant at low pH, while tridentate complexes were only significant at high pH values. The modeling results help to accurately predict the environmental behavior of heavy metals in pH 3 to 7 soil environments.