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Published on: October 15, 2015
Modeling arsenite oxidation by chemoautotrophic Thiomonas arsenivorans strain b6 in a packed-bed bioreactor
Aniruddha Dastidar1, Yi-Tin Wang
1USEPA Research Participant, Division of Water, Frankfort, KY 40601, USA. andy.dastidar@ky.gov
Abstract:
Arsenic is a major toxic pollutant of concern for the human health. Biological treatment of arsenic contaminated water is an alternative strategy to the prevalent conventional treatments. The biological treatment involves a pre-oxidation step transforming the most toxic form of arsenic, As (III), to the least toxic form, As (V), respectively. This intermediate process improves the overall efficiency of total arsenic removal from the contaminated water. As (III) oxidation by the chemoautotrophic bacterium Thiomonas arsenivorans strain b6 was investigated in a fixed-film reactor under variable influent As (III) concentrations (500-4000 mg/L) and hydraulic residence times (HRTs) (0.2-1 day) for a duration of 137 days. During the entire operation, seven steady-state conditions were obtained with As (III) oxidation efficiency ranging from 48.2% to 99.3%. The strong resilience of the culture was exhibited by the recovery of the bioreactor from an As (III) overloading of 5300±400 mg As (III)/L day operated at a HRT of 0.2 day. An arsenic mass balance revealed that As (III) was mainly oxidized to As (V) with unaccounted arsenic (≤4%) well within the analytical error of measurement. A modified Monod flux expression was used to determine the biokinetic parameters by fitting the model against the observed steady-state flux data obtained from operating the bioreactor under a range of HRTs (0.2-1 day) and a constant influent As (III) concentration of 500 mg/L. Model parameters, k=0.71±0.1 mg As (III)/mg cells h, and K(s)=13.2±2.8 mg As (III)/L were obtained using a non-linear estimation routine and employing the Marquardt-Levenberg algorithm. Sensitivity analysis revealed k to be more sensitive to model simulations of As (III) oxidation under steady-state conditions than parameter K(s).
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