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Author |
Peng, L.; Liu, Y.; Sun, J.; Wang, D.; Dai, X.; Ni, B.-J. |
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Title |
Enhancing immobilization of arsenic in groundwater: A model-based evaluation |
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A1 Journal article |
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Year |
2017 |
Publication |
Journal of cleaner production |
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Volume |
166 |
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Pages |
449-457 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL) |
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Abstract |
The mobilization of arsenic (As) in aquatic environment (groundwater) can cause severe environmental and healthy issues. To develop remediation strategies, we proposed a comprehensive mathematical model to describe the As removal in a arsenite (As (III)) oxidizing and ferrous iron (Fe (II)) oxidizing denitrifying granular biofilm system. In the model framework, the growth-linked microbial oxidation of As (III) and Fe (II) was coupled to chemolithotrophic denitrification of one-step reduction of nitrate to nitrogen gas. Meanwhile, the precipitation of ferric iron (Fe (III)) and adsorption of arsenate (As (V)) onto the biogenic Fe (III) (hydr)oxides were also considered. The model was calibrated by comparing the model predictions against experimental data from batch experiments. The validity of the model was further demonstrated through testing against long-term experimental results from five independent bioreactors with different reactor configurations and operational conditions. Modeling results revealed that the granule size would exert a limited impact on arsenic and iron removal. Nevertheless, their removal efficiencies increased rapidly with the increase of hydraulic retention time (HRT) from 1 h to 12 h, but became independent of HRT as it further increased. The established model framework enables interpretation of a range of experimental observations on As and Fe removal and helps to identify the optimal conditions for enhanced arsenic remediation. (C) 2017 Elsevier Ltd. All rights reserved. |
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Wos |
000412607100046 |
Publication Date |
2017-08-09 |
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ISSN |
0959-6526 |
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UA library record; WoS full record; WoS citing articles |
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Open Access |
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no |
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Call Number |
UA @ admin @ c:irua:146635 |
Serial |
7919 |
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