Abstract
Bioremediation is a sustainable and promising technology for the remediation of different kinds of pollutants, such as heavy metals, dyes, antibiotics, microplastics, and other contaminants present in industrial wastewater. These emergent toxic pollutants have adverse effects on human health. However, different conventional technologies such as filtration, ion exchange, precipitation, etc., are used to remove contaminants such as heavy metals and organic and inorganic pollutants. In this direction, the application of green materials, nanoparticles, and their composites, phyco-remediation, mycoremediation, and different kinds of bio(nano) sorbents such as biochar, hydrochar, chitin, and chitosan, etc., are used for the removal of hazardous pollutants from industrial wastewater. Green bio(nano) sorbent materials are eco-friendly, sustainable in nature, and offer enhanced adsorption efficiency and selectivity as compared to the conventional mode of wastewater treatment. A techno-economic analysis and a circular economy analysis are required for assessing bioremediation. The future perspective and challenges are addressed for the implementation of bioremediation-based technology. Integration of other techniques, such as artificial intelligence, advanced machine learning, and the Internet of Things (IoT) is used by researchers for the bioremediation of industrial wastewater. Thus, the application of green (nano)materials for industrial wastewater treatment is a sustainable environmental solution.
Acknowledgments
The author acknowledged the library support provided by Lovely Professional University, India.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: Ajay Kumar: Conceptualizations, Writing – Original Draft, investigation, and Validation. All the author read and approved the final manuscript.
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Use of Large Language Models, AI and Machine Learning Tools: Not applicable.
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Conflict of interest: The authors declare that they have no competing interests.
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Research funding: The author received no financial support for the research, authorship, or publication of this article.
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Data availability: We declare that all research data related to the article is available in the text of the article.
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