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Cited by 574

The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.

Feasibility of industrial-scale treatment of dye wastewater via bio-adsorption technology

Open access
Li, Wei, Mu, Bingnan, Yang, Yiqi·2019·Bioresource Technology

Abstract

This review emphasizes the importance of costs in industrial-scale treatment of dye wastewater and provides a way to assess the cost-based feasibility of bio-adsorption technologies. Dye wastewater is one of the major contributors to environmental pollution. Bio-adsorption has attracted considerable attentions in dye wastewater treatment due to its technical feasibility, flexibility and operation simplicity. However, industrial-scale treatment of dye wastewater via bio-adsorption technologies remains stagnant, mainly due to high costs. So far, no review or research articles have systematically discussed the criteria for successful utilization of bio-adsorption technologies on a large scale. This review discusses the major factors affecting adsorption and desorption performance based on basic chemical and physical structures of bio-adsorbents available in literatures. A quantitative relationship has been summarized based on previous studies to assess the cost to utilize a bio-adsorption technology and serve as an access threshold for quality bio-adsorbents to be taken into real applications.

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Crossref · 10.1016/j.biortech.2019.01.002

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Metadata

Authors
Li, W., Mu, B., & Yang, Y.
Venue
Bioresource Technology
Publisher
Elsevier BV
Published
2019-04
Volume
277
Pages
157-170
ISSN
0960-8524 (ISSN-L)
OpenAlex
W2907263220
Cited by
574
References
93
FWCI
26.68
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Feasibility of industrial-scale treatment of dye wastewater via bio-adsorption technology. https://app.cochat.ai/papers/10.1016/j.biortech.2019.01.002
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Li, W., Mu, B., & Yang, Y. (2019). Feasibility of industrial-scale treatment of dye wastewater via bio-adsorption technology. Bioresource Technology. https://doi.org/10.1016/j.biortech.2019.01.002

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.