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

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dc.authorid0000-0003-0576-8724
dc.authorid0000-0003-1282-718X
dc.authorid0000-0001-5077-5689
dc.contributor.authorOral, Burcu
dc.contributor.authorCosgun, Ahmet
dc.contributor.authorGuenay, M. Erdem
dc.contributor.authorYildirim, Ramazan
dc.date.accessioned2026-04-04T18:55:35Z
dc.date.available2026-04-04T18:55:35Z
dc.date.issued2024
dc.departmentİstanbul Bilgi Üniversitesi
dc.description.abstractBiochar 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.
dc.identifier.doi10.1016/j.jenvman.2024.121162
dc.identifier.doi10.1016/j.jenvman.2024.121162
dc.identifier.issn0301-4797
dc.identifier.issn1095-8630
dc.identifier.pmid38749129
dc.identifier.scopus2-s2.0-85193009842
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.jenvman.2024.121162
dc.identifier.urihttps://hdl.handle.net/11411/10460
dc.identifier.volume360
dc.identifier.wosWOS:001241540900001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherAcademic Press Ltd- Elsevier Science Ltd
dc.relation.ispartofJournal of Environmental Management
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260402
dc.snmzKA_Scopus_20260402
dc.subjectBiochar Production
dc.subjectBiochar Utilization
dc.subjectEnvironmental Remediation
dc.subjectMachine Learning
dc.titleMachine learning-based exploration of biochar for environmental management and remediation
dc.typeArticle

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