Qasim Ali, Qi Li, Shahzad Ahmed, Marwa Yasmeen, Asma Mukhtar, Longfei Liu, Muhammad Akraam, Muhammad Azeem Sabir, Adnan Hussain, Rashid Hussain, Maqshoof Ahmad, Muhammad Mahroz Hussain, Shengsen Wang
Heavy-metal pollution of soil, sediments, and water remains a major environmental and public health concern worldwide. Conventional remediation methods (excavation, soil washing, chemical stabilization, and pump-and-treat) frequently suffer from high costs, low selectivity, and the generation of secondary wastes. Engineered nanomaterials (ENMs) provide a complementary toolkit that leverages nanoscale properties, such as a large specific surface area, controlled surface chemistry, and redox or photocatalytic functionality to bind, transform, or immobilize toxic metals in situ or ex situ. This review critically synthesizes recent advancements in nanomaterial classes used for heavy-metal mitigation, such as nanoscale zero-valent iron and iron oxides, titanium dioxide, and other metal oxides, carbonaceous materials including graphene derivatives, and biochar-based composites, and hybrid magnetic/functionalized composites. We discussed the detailed mechanistic pathways (adsorption and surface complexation, ion exchange, electron-transfer reduction, photocatalytic transformation, and co-precipitation), and how environmental parameters—pH, redox potential, ionic strength, natural organic matter, and particle aging—influence efficacy and permanence. We compare laboratory, mesocosm, and field studies to highlight practical performance, limitations in transport and delivery, and ecological trade-offs. Remaining barriers to deployment include nanoparticle transformation and mobility in complex matrices, standardized ecotoxicological testing, techno-economic assessment, and regulatory acceptance. The review concludes with recommended research directions to enhance stability, selectivity, recovery, and life cycle sustainability of nanoremediation technologies, emphasizing integrated approaches that combine mechanistic insight with field-scale validation.