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Cited by 330

The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.

Water Treatment by Adsorption Columns: Evaluation at Ground Level

Ali, Imran·2014·Separation & Purification Reviews

Abstract

Water is the most important and essential component of earth's ecosystem, playing a vital role in the proper functioning of flora and fauna. But water resources are contaminating continuously. The whole world may be in great water scarcity in the coming few decades. Among many water treatment methods, adsorption is considered to be one of the best. Many articles describe adsorption applications for water treatment in batch mode. Only few works report laboratory, pilot and commercial applications of adsorption technology. This review is a critical evaluation of the contribution of adsorption technology at laboratory, pilot and process scales. Water treatment, through column operations, has been divided into two parts: removal of (i) inorganic and (ii) organic pollutants. Attempts have been made to evaluate the application of adsorption columns at the ground level. Besides, efforts have also been made to emphasize the importance of adsorption columns at commercial levels to tackle water treatment problems in the future.

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Crossref · 10.1080/15422119.2012.748671

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Metadata

Authors
Ali, I.
Venue
Separation & Purification Reviews
Published
2013-08-14
Volume
43
Issue
3
Pages
175-205
ISSN
  • 1542-2119 (ISSN-L)
  • 1542-2127
OpenAlex
W1969861701
Cited by
330
References
88
FWCI
24.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Water Treatment by Adsorption Columns: Evaluation at Ground Level. https://app.cochat.ai/papers/10.1080/15422119.2012.748671
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Ali, I. (2014). Water Treatment by Adsorption Columns: Evaluation at Ground Level. Separation & Purification Reviews. https://doi.org/10.1080/15422119.2012.748671

Data sources

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.