Critical review of adsorption technologies for heavy metal removal: mechanistic, computational, and policy perspectives.

The main sources of heavy metal pollution in groundwater include discharges from petroleum refining plants, agricultural runoff, hospital wastewater, and environmental damage caused by war. Advances in adsorbents provide safe, efficient, and economical techniques for contaminant removal. This study presents a critical review of adsorption applications worldwide, particularly in Iraq, evaluating the effectiveness, large-scale applicability, and long-term sustainability of selected adsorbents. Furthermore, the study focuses on adsorption mechanisms, criteria for selecting appropriate adsorbents, process design, and advanced computational methods such as machine learning algorithms and molecular dynamics simulations. Biochar prepared from rice husk removes over 90% of Pb2+ under optimal batch conditions, while zeolite sourced from Samaraa removes more than 92% of Cr6+ and Cd2+. All machine learning models achieved prediction accuracies of more than 95% for adsorption performance. In addition, molecular dynamics simulations provide more insight at the atomic scale. This work addresses three primary problems: elevated salinity in the Euphrates river, ranging from 1000 to 3000 mg L-1; organic fouling resulting from effluent; and limitations imposed by existing infrastructure. In light of these conditions, the study recommends using advanced computational optimization models with mobile treatment units (MTUs) to provide solutions tailored to local conditions. The study further highlights the significance of pilot-scale testing and incorporation into policy frameworks. This helps close gaps related to Sustainable Development Goal 6 (SDG 6) on clean water and sanitation in Iraq, while also supporting environmental sustainability.