Machine learning-based exploration of biochar for environmental management and remediation

• Published in: Journal of environmental management Vol. 360; p. 121162
• Main Authors: Oral, Burcu, Coşgun, Ahmet, Günay, M. Erdem, Yıldırım, Ramazan
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.06.2024
• Subjects: Biochar production; Biochar utilization; Environmental remediation; Machine learning; Environmental remediation; Biochar production; Biochar utilization; Machine learning
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2024.121162

Biochar has a wide range of applications, including environmental management, such as preventing soil and water pollution, removing heavy metals from water sources, and reducing air pollution. However, there are several challenges associated with the usage of biochar for these purposes, resulting in an abundance of experimental data in the literature. Accordingly, the purpose of this study is to examine the use of machine learning in biochar processes with an eye toward the potential of biochar in environmental remediation. First, recent developments in biochar utilization for the environment are summarized. Then, a bibliometric analysis is carried out to illustrate the major trends (demonstrating that the top three keywords are heavy metal, wastewater, and adsorption) and construct a comprehensive perspective for future studies. This is followed by a detailed review of machine learning applications, which reveals that adsorption efficiency and capacity are the primary utilization targets in biochar utilization. Finally, a comprehensive perspective is provided for the future. It is then concluded that machine learning can help to detect hidden patterns and make accurate predictions for determining the combination of variables that results in the desired properties which can be later used for decision-making, resource allocation, and environmental management. [Display omitted] •Machine learning (ML) works on biochar utilization is reviewed.•Bibliometric analysis and future perspectives on ML application are provided.•Biochar is mostly used to remove metal ions and pharmaceutical waste.•Artificial neural networks and random forests are the common algorithms used.