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Removal of arsenic from wastewater using chemical precipitation methods

Harper, Thomas R., Kingham, Neville W.·1992·Water Environment Research

Abstract

ABSTRACT: The use of arsenic in agriculture, industry, and domestic endeavors since the last century has increased the concentration of arsenic in the environment. During cleanup activities at a former pesticide facility, water that was collected during various operations was contaminated with arsenic and required treatment before discharge. Chemical precipitation was identified as being the most effective means of treatment. Bench‐scale treatability testing was completed to determine the effectiveness of various coagulants, including ferric chloride, hydrated lime, sodium sulfide, and alum. A combination of hydrated lime and ferric chloride was able to remove more than 99% of the original arsenic concentration. Contaminated water to be treated by the full‐scale system had arsenic concentrations up to 48 mg/L. The discharge limitation required that the arsenic concentration be reduced to less than 1 mg/L. More than 605 000 L (160 000 gal) of water were treated using a combination of chemical precipitation, filtration, and carbon absorption.

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Metadata

Authors
Harper, T. R., & Kingham, N. W.
Venue
Water Environment Research
Publisher
Wiley
Published
1992-05
Volume
64
Issue
3
Pages
200-203
ISSN
  • 0043-1303 (ISSN-L)
  • 1061-4303
  • 1554-7531
OpenAlex
W2307031817
Cited by
181
References
0
FWCI
2.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Removal of arsenic from wastewater using chemical precipitation methods. https://app.cochat.ai/papers/10.2175/wer.64.3.2
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Harper, T. R., & Kingham, N. W. (1992). Removal of arsenic from wastewater using chemical precipitation methods. Water Environment Research. https://doi.org/10.2175/wer.64.3.2

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.