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AI-driven biochar engineering for emerging pollutants removal from water: performance, mechanisms, and environmental perspectives
Summary
Researchers reviewed how biochar — a charcoal-like material made from organic waste — can be engineered at different levels of complexity, from raw biochar to AI-optimized advanced composites, to remove emerging pollutants like pharmaceuticals, PFAS, and micro- and nanoplastics from water. The review advocates for using AI to guide material design and prioritizing simpler, more sustainable biochar forms unless more advanced composites are truly necessary.
Abstract The global prevalence of emerging pollutants (EPs) in aqueous systems presents a significant environmental threat that conventional treatments cannot adequately address. This review provides a comprehensive analysis of biochar-based systems as a sustainable solution, charting a path from foundational material science to advanced, data-driven engineering. We critically evaluate these solutions through a tiered framework: starting with Tier 1 (Pristine Biochar), which is highly reliant on physisorption mechanisms; moving to Tier 2 (Modified Biochar) with enhanced surface properties through activation and/or heteroatom doping; and culminating in Tier 3 (Advanced Composites) incorporating materials like nanoparticles and graphene, which offer superior removal mechanisms, including chemisorption and photocatalysis. A central focus is placed on the transformative role of Artificial Intelligence (AI), which enables predictive modelling and optimization to accelerate the design of tailored, high-performance adsorbents. Beyond performance, this review delves into the critical aspects of scalability, presenting a detailed analysis of the economic trade-offs and environmental/ecotoxicity considerations that govern real-world deployment. We demonstrate how this tiered approach leads to targeted solutions for challenging EPs, such as cationic composites for per- and polyfluoroalkyl substances and engineered surface porosity for the physical entrapment of micro- and nanoplastics. Ultimately, we advocate for an AI-guided strategy, prioritizing sustainable pristine biochar where effective and strategically deploying advanced composites as a last resort. This work concludes by outlining a roadmap for future research, emphasizing the need for standardized and robust datasets, green synthesis protocols, and rigorous safety assessments to ensure the responsible development of these next-generation water treatment technologies. Graphical Abstract
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