Multi-compartmental risk assessment of heavy metal contamination in soil, plants, and wastewater: A model from Industrial Gazipur, Bangladesh

Heavy metal contamination in industrial-agricultural regions poses global challenges, yet comprehensive risk assessment models addressing both ecological and human health impacts are scarce. This study introduces a novel multi-compartmental risk assessment framework applied to the Saldha River region of Gazipur, Bangladesh, a rapidly industrialising area experiencing significant environmental stress. Here, we analysed eight heavy metals (Cr, Pb, Cu, Fe, Mn, Zn, Ni, and Cd) in soil, wastewater, and plant samples (spinach, wild rice, and nut grass) via atomic absorption spectrophotometry (AAS). Ecological risks were evaluated through contamination factor (CF), pollution load index (PLI), and geo-accumulation index (I_geo), while human health risks were assessed using hazard indices (HI). Results revealed severe Cd contamination (enrichment factor 2563.19), indicating substantial anthropogenic influence. Correlation analysis of wastewater samples showed strong associations between metal pairs, such as Cu-Zn (0.92), Cu-Fe (0.90) and Zn-Mn (0.87), indicating common industrial sources. Transfer factor (TF) analysis in plants demonstrated substantial variability in metal uptake, with Mn and Ni showing the highest bioavailability, increasing risks to local food chains. Human health risk assessments indicated hazard indices (HI) exceeding safety thresholds for both adults and children, underscoring the urgent need for mitigation strategies. This study offers a novel, integrative framework for assessing multi-source contamination and provides critical baseline data for future environmental policy development. The model is adaptable to industrial regions worldwide, such as textile hubs in Southeast Asia or metal processing zones in Europe and North America, offering new insights into contamination pathways and risk management.