Literature DB >> 17612178

A binary aqueous component model for the sediment-water partitioning of trace metals in natural waters.

Andrew Turner1.   

Abstract

A model defining the overall sediment-water partitioning of a chemical, K(D), and the partitioning of its conservative components, (K(D))i, is presented. With respect to many trace metals in natural waters it is proposed that, through strong and perhaps specific complexation, two independent aqueous components coexist and a binary form of the model is appropriate. For two components of a metal that exhibit unequal partitioning, an inverse relationship between K(D) and particle concentration is predicted. Published experimental measurements of K(D) for metals in river waters, derived under conditions which exclude variable concentrations of preexistent colloidal particles, displayed either an inverse dependence (Cu, Ni, and Pd) or little dependence (Cs) on particle concentration. Regarding the former, iterative fits with the binary model were better than empirical fits based on a third (colloidal) phase model, and suggested the presence of between about 10 and 75% of a particle-reactive component ((K(D))1 approximately 5 x 10(4) to 10(10) mL g(-1)) and 25 and 90% of a less reactive (e.g., strongly complexed) component ((K(D))2 < or = 2.5 x 10(3) mL g(-1)). Regarding Cs, data indicated the presence of a single component whose K(D) was on the order of 10(3) mL g(-1). These observations challenge the conventional means by which sediment-water partitioning is considered and modeled, and imply that a third phase is not always a prerequisite for the particle concentration effect frequently observed in laboratory and field studies.

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Year:  2007        PMID: 17612178     DOI: 10.1021/es0620336

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


  1 in total

1.  The Applicability of the Distribution Coefficient, KD, Based on Non-Aggregated Particulate Samples from Lakes with Low Suspended Solids Concentrations.

Authors:  Aine Marie Gormley-Gallagher; Richard William Douglas; Brian Rippey
Journal:  PLoS One       Date:  2015-07-22       Impact factor: 3.240

  1 in total

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