Occurrence, fate, monitoring challenges, and bio-based adsorbents for sustainable remediation of emerging contaminants in low- and middle-income countries

Abstract

Emerging contaminants (ECs) are increasingly reported in surface water, groundwater, wastewater, sediments, and drinking water sources. However, their occurrence, environmental fate, exposure risks, monitoring challenges, and treatment needs remain inadequately assessed in many low- and middle-income countries (LMICs). This review critically examines and provides an update on recent evidence on EC occurrence, with emphasis on monitoring gaps and biomass-based remediation. The literature review shows that EC monitoring in LMICs remains fragmented, geographically uneven, and often restricted to a narrow set of target compounds, creating uncertainty in exposure assessment, risk prioritization, and water-safety planning. Similarly, bio-based adsorbents derived from agricultural residues, forestry by-products, aquatic biomass, cellulose, chitosan, lignocellulosic waste, and biochar offer locally adaptable options for decentralized EC remediation. Their performance is governed by pore structure, surface charge, aromaticity, mineral content, and oxygen- and nitrogen-containing functional groups, which promote pore filling, electrostatic attraction, ion exchange, hydrogen bonding, π–π interactions, hydrophobic partitioning, and surface complexation. However, reported adsorption capacities remain difficult to compare because performance is strongly influenced by pH, initial concentration, contact time, adsorbent dose, matrix composition, regeneration cycles, and the selected performance metric. Although these bio-based adsorbents are often considered low-cost and sustainable, this cannot guarantee their practical adoption. Field deployment requires validation in real-water matrices, continuous-flow testing, regeneration safety, spent-media management, life-cycle and cost assessment, regulatory acceptance, and community-level usability. Future studies should prioritize multi-contaminant systems, standardized metrics, and AI-assisted material optimization linked to global monitoring frameworks.