Literature DB >> 21087041

Forward modeling of metal complexation by NOM: II. prediction of binding site properties.

Stephen E Cabaniss1.   

Abstract

An a priori model of metal complexation by natural organic matter (NOM) has previously been shown to predict experimental data at pH 7.0 and 0.1 M ionic strength (Cabaniss, S. E. Environ. Sci. Technol. 2009). Unlike macroscopic models based only on stoichiometry and thermodynamics, this a priori model also predicts the ligand groups and properties of complexed (occupied) molecules. Ligand molecules with strong binding sites form complexes at low metal concentrations and have average properties (molecular weight, charge, aromaticity) which can differ significantly from the average properties of bulk NOM. Cu(II), Ni(II) and Pb(II) preferentially bind to strong amine-containing sites which are often located on small (MW < 1000), lower-aromaticity molecules. Cd(II) and Zn(II) show generally weaker binding, although they also prefer amine-containing sites to pure carboxylates and bind to smaller, less aromatic molecules. Ca(II) shows no real preference for amine over carboxylate ligand groups, preferentially binding to larger and more negatively charged molecules. Al(III) has a unique preference for phenol-containing sites and larger, more aromatic molecules. While some predictions of this model are consistent with a variety of experimental data from the literature, others await validation by molecular-level analysis.

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Year:  2010        PMID: 21087041     DOI: 10.1021/es102408w

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  3 in total

1.  Binding characteristics of Cu2+ to natural humic acid fractions sequentially extracted from the lake sediments.

Authors:  En He; Changwei Lü; Jiang He; Boyi Zhao; Jinghua Wang; Ruiqing Zhang; Tao Ding
Journal:  Environ Sci Pollut Res Int       Date:  2016-08-24       Impact factor: 4.223

Review 2.  Electrical and Electrochemical Sensors Based on Carbon Nanotubes for the Monitoring of Chemicals in Water-A Review.

Authors:  Gookbin Cho; Sawsen Azzouzi; Gaël Zucchi; Bérengère Lebental
Journal:  Sensors (Basel)       Date:  2021-12-29       Impact factor: 3.576

3.  Mercury Removal from Contaminated Water by Wood-Based Biochar Depends on Natural Organic Matter and Ionic Composition.

Authors:  Sampriti Chaudhuri; Gabriel Sigmund; Sharon E Bone; Naresh Kumar; Thilo Hofmann
Journal:  Environ Sci Technol       Date:  2022-08-04       Impact factor: 11.357

  3 in total

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