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A review on control and abatement of soil pollution by heavy metals: Emphasis on artificial intelligence in recovery of contaminated soil

  • Krishna Gautam
  • , Poonam Sharma
  • , Shreya Dwivedi
  • , Amarnath Singh
  • , Vivek Kumar Gaur*
  • , Sunita Varjani*
  • , Janmejai Kumar Srivastava
  • , Ashok Pandey
  • , Jo-Shu Chang
  • , Huu Hao Ngo
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

“Save Soil Save Earth” is not just a catchphrase; it is a necessity to protect soil ecosystem from the unwanted and unregulated level of xenobiotic contamination. Numerous challenges such as type, lifespan, nature of pollutants and high cost of treatment has been associated with the treatment or remediation of contaminated soil, whether it be either on-site or off-site. Due to the food chain, the health of non-target soil species as well as human health were impacted by soil contaminants, both organic and inorganic. In this review, the use of microbial omics approaches and artificial intelligence or machine learning has been comprehensively explored with recent advancements in order to identify the sources, characterize, quantify, and mitigate soil pollutants from the environment for increased sustainability. This will generate novel insights into methods for soil remediation that will reduce the time and expense of soil treatment. © 2023 Elsevier Inc.
Original languageEnglish
Article number115592
JournalEnvironmental Research
Volume225
Online published28 Feb 2023
DOIs
Publication statusPublished - 15 May 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • Artificial intelligence
  • Microbial remediation
  • Omics approaches
  • Soil pollution

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