A review on the lignocellulosic derived biochar-based catalyst in wastewater remediation: Advanced treatment technologies and machine learning tools.

Adsorption Advanced oxidation process Biochar-based catalyst Machine learning algorithm Wastewater contamination

Journal

Bioresource technology
ISSN: 1873-2976
Titre abrégé: Bioresour Technol
Pays: England
ID NLM: 9889523

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 30 06 2023
revised: 25 07 2023
accepted: 27 07 2023
medline: 11 9 2023
pubmed: 8 8 2023
entrez: 7 8 2023
Statut: ppublish

Résumé

Wastewater disposal in the ecosystem affects aquatic and human life, which necessitates the removal of the contaminants. Eliminating wastewater contaminants using biochar produced through the thermal decomposition of lignocellulosic biomass (LCB) is sustainable. Due to its high specific surface area, porous structure, oxygen functional groups, and low cost, biochar has emerged as an alternate contender in catalysis. Various innovative advanced technologies were combined with biochar for effective wastewater treatment. This review examines the use of LCB for the synthesis of biochar along with its activation methods. It also elaborates on using advanced biochar-based technologies in wastewater treatment and the mechanism for forming oxidizing species. The research also highlights the use of machine learning in pollutant removal and identifies the obstacles of biochar-based catalysts in both real-time and cutting-edge technologies. Probable and restrictions for further exploration are discussed.

Identifiants

pubmed: 37549718
pii: S0960-8524(23)01015-5
doi: 10.1016/j.biortech.2023.129587
pii:
doi:

Substances chimiques

Wastewater 0
biochar 0
lignocellulose 11132-73-3
Charcoal 16291-96-6
Water Pollutants, Chemical 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

129587

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

V Godvin Sharmila (V)

Department of Civil Engineering, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India.

Vinay Kumar Tyagi (V)

Environmental Hydrology Division, National Institute of Hydrology, Roorkee 247667, India.

Sunita Varjani (S)

School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong; Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun 248 007, Uttarakhand, India.

J Rajesh Banu (J)

Department of Biotechnology, Central University of Tamil Nadu, Neelakudi, Thiruvarur, Tamil Nadu 610005, India. Electronic address: rajeshces@gmail.com.

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Classifications MeSH