Biochar-Based Approaches for Heavy Metal Remediation in Agricultural Soils: Mechanisms, Optimization, and Emerging AI Applications

Authors

  • Rui Wu Sustainable Process Engineering Centre (SPEC), Department of Chemical Engineering, Faculty of Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
  • Mingxian Zhang School of Civil Engineering and Urban Planning, Liupanshui Normal University, Liupanshui 553004, China
  • Faidzul Hakim Adnan Sustainable Process Engineering Centre (SPEC), Department of Chemical Engineering, Faculty of Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia
  • Pei Yi Siow Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, Malaysia https://orcid.org/0000-0001-6837-500X
  • Mohd Izzudin Izzat Zainal Abidin Sustainable Process Engineering Centre (SPEC), Department of Chemical Engineering, Faculty of Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia https://orcid.org/0000-0002-3227-9670

Keywords:

Biochar, Agricultural soils, Heavy metal immobilization, Modification strategies, Machine learning (ML)

Abstract

Heavy metal contamination in agricultural soils poses persistent risks to crop safety and food-chain exposure. Although biochar is widely proposed—and increasingly applied—as a remediation amendment, field performance remains highly variable across soil constraints, metal speciation, and biochar designs. This review addresses this uncertainty by translating immobilization pathways (sorption/ complexation, precipitation, and redox-mediated stabilization) into a decision-oriented “mechanism–lever–endpoint” framework, thus linking mechanistic hypotheses to controllable engineering strategies such as feedstock selection, pyrolysis windows, and mineral/composite design. Beyond established plant–microbe interactions, there is a critical assessment of under-synthesized biochar–soil fauna pathways, with a focus on earthworms, and a reconciliation of conflicting evidence by highlighting boundary conditions that shift biological responses. Agronomic trade-offs and environmental risks are considered, associated with biochar production and application, emphasizing failure modes relevant to long-term soil health and remediation reliability. To support decision-grade deployment under heterogeneous evidence, a bias-aware AI-assisted workflow is outlined, which stresses standardized reporting, interpretability, and leakage-safe validation. Overall, the review integrates engineering options with biological synergies into a practical roadmap for more predictable and site-specific remediation in agricultural soils.

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Published

2026-05-26 — Updated on 2026-07-31

How to Cite

Wu, R., Zhang, M., Adnan, F. H., Siow, P. Y., & Zainal Abidin, M. I. I. (2026). Biochar-Based Approaches for Heavy Metal Remediation in Agricultural Soils: Mechanisms, Optimization, and Emerging AI Applications. BioResources, 21(3), 8771–8820. Retrieved from https://ojs.bioresources.com/index.php/BRJ/article/view/25513

Issue

Section

Scholarly Review