4.7 Article

Modeling kinetics of Ni dissociation from humic substances based on WHAM 7

期刊

CHEMOSPHERE
卷 221, 期 -, 页码 254-262

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2019.01.012

关键词

Kinetics; Dissociation; Ni; Kinetics model; Humic substances; Competing ligand exchange

资金

  1. National Natural Science Foundation of China [41573090]
  2. Guangdong Innovative and Entrepreneurial Research Team Program [2016ZT06N569]
  3. Fundamental Research Funds for the Central Universities [2018PY10]

向作者/读者索取更多资源

Understanding the kinetics of Ni dissociation from dissolved organic matter (DOM) helps to better predict the fate and bioavailability of Ni ions in the environment. However, there is still a lack of predictive models for the kinetics of Ni dissociation from DOM under different reaction conditions. In this study, kinetics of Ni dissociation from humic acids (HA) and fulvic acids (FA), two most important components in DOM for Ni binding, was studied with a competing ligand exchange method at varying Ni concentrations, reaction pH, and ionic strength. The kinetic data were analyzed using a mechanistic kinetics model developed based on the Windermere Humic Aqueous Model (WHAM). Experimental results showed that Ni dissociation rates were affected by both Ni concentrations and pH, and Ni dissociation from FA had faster rates than that from HA. The kinetics model can reproduce the experimental data well, with only two model fitting parameters for different reaction conditions. The modeling results showed that various HA and FA binding sites played different roles in controlling Ni dissociation rates, with bidentate binding sites and the weak tridentate sites being the most significant. At high pH values the Ni re-association reactions were significant for controlling the overall rates of Ni dissociation but had minimal impact at lower pH values. Our model provided a modeling framework based on WHAM 7 for predicting Ni dissociation rates when humic substances were the dominant binding ligands. (C) 2019 Elsevier Ltd. All rights reserved.

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