Literature DB >> 15926572

Modeling the influence of decomposing organic solids on sulfate reduction rates for iron precipitation.

Paulo S Hemsi1, Charles D Shackelford, Linda A Figueroa.   

Abstract

The influence of decomposing organic solids on sulfate (S04(2-)) reduction rates for metals precipitation in sulfate-reducing systems, such as in bioreactors and permeable reactive barriers for treatment of acid mine drainage, is modeled. The results are evaluated by comparing the model simulations with published experimental data for two single-substrate and two multiple-substrate batch equilibrium experiments. The comparisons are based on the temporal trends in SO4(2-), ferrous iron (Fe2+), and hydrogen sulfide (H2S) concentrations, as well as on rates of sulfate reduction. The temporal behaviors of organic solid materials, dissolved organic substrates, and different bacterial populations also are simulated. The simulated results using Contois kinetics for polysaccharide decomposition, Monod kinetics for lactate-based sulfate reduction, instantaneous or kinetically controlled precipitation of ferrous iron mono-sulfide (FeS), and partial volatilization of H2S to the gas phase compare favorably with the experimental data. When Contois kinetics of polysaccharide decomposition is replaced by first-order kinetics to simulate one of the single-substrate batch experiments, a comparatively poorer approximation of the rates of sulfate reduction is obtained. The effect of sewage sludge in boosting the short-term rate of sulfate reduction in one of the multiple-substrate experiments also is approximated reasonably well. The results illustrate the importance of the type of kinetics used to describe the decomposition of organic solids on metals precipitation in sulfate-reducing systems as well as the potential application of the model as a predictive tool for assisting in the design of similar biochemical systems.

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Year:  2005        PMID: 15926572     DOI: 10.1021/es0486420

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


  1 in total

1.  Pollutant concentration profile reconstruction using digital soft sensors for biodegradation and exposure assessment in the presence of model uncertainty.

Authors:  Nikolaos Kazantzis; Vasiliki Kazantzi; Emmanuel G Christodoulou
Journal:  Environ Sci Pollut Res Int       Date:  2014-03-02       Impact factor: 4.223

  1 in total

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