The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
Mycoremediation: Expunging environmental pollutants
Open accessAbstract
The ever-increasing population, rapid rate of urbanization, and industrialization are exacerbating the pollution-related problems. Soil and water pollution affect human health and the ecosystem. Thus, it is crucial to develop strategies to combat this ever-growing problem. Mycoremediation, employing fungi or its derivatives for remediation of environmental pollutants, is a comparatively cost-effective, eco-friendly, and effective method. It has advantages over other conventional and bioremediation methods. In this review, we have elucidated the harmful effects of common pollutants on public health and the environment. The role of several fungi in degrading these pollutants such as heavy metals, agricultural, pharmaceutical wastes, including polycyclic aromatic hydrocarbons, is enumerated. Future strategies to improve the rate and efficiency of mycoremediation are suggested. The manuscript describes the strategies which can be used as a future framework to address the global problem of pollution.
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Cites
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The Lancet Commission on pollution and health
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Cited by
Ortúzar, M., Esterhuizen, M., Olicón-Hernández, D. R., González-López, J., & Aranda, E. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.869332 · Cited by 425
Microbial bioremediation of soils contaminated with petroleum hydrocarbons
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Metadata
- Authors
- Akhtar, N., & Mannan, M. A.-U.
- Venue
- Biotechnology Reports
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 26
- Pages
- e00452
- ISSN
- 2215-017X (ISSN-L)
- OpenAlex
- W3015454819
- Cited by
- 299
- References
- 82
- FWCI
- 6.72
- Type
- journal article
- Language
- en
- Open access
- gold
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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.
