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Cited by 422

The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.

Adsorption Technique for the Removal of Organic Pollutants from Water and Wastewater

Open access
Nageeb, Mohamed·2013·Organic Pollutants - Monitoring, Risk and Treatment

Abstract

Organic pollution is the term used when large quantities of organic compounds. It origi‐ nates from domestic sewage, urban run-off, industrial effluents and agriculture wastewater. sewage treatment plants and industry including food processing, pulp and paper making, agriculture and aquaculture. During the decomposition process of organic pollutants the dissolved oxygen in the receiving water may be consumed at a greater rate than it can be replenished, causing oxygen depletion and having severe consequences for the stream biota. Wastewater with organic pollutants contains large quantities of suspended solids which re‐ duce the light available to photosynthetic organisms and, on settling out, alter the character‐ istics of the river bed, rendering it an unsuitable habitat for many invertebrates. Organic pollutants include pesticides, fertilizers, hydrocarbons, phenols, plasticizers, biphenyls, de‐ tergents, oils, greases, pharmaceuticals, proteins and carbohydrates [1-3].

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Metadata

Authors
Nageeb, M.
Venue
Organic Pollutants - Monitoring, Risk and Treatment
Publisher
InTech
Published
2013-01-30
OpenAlex
W1547334386
Cited by
422
References
72
FWCI
45.60
Type
book chapter
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Adsorption Technique for the Removal of Organic Pollutants from Water and Wastewater. https://app.cochat.ai/papers/10.5772/54048
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Nageeb, M. (2013). Adsorption Technique for the Removal of Organic Pollutants from Water and Wastewater. Organic Pollutants - Monitoring, Risk and Treatment. https://doi.org/10.5772/54048

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.