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Heavy metal contamination has emerged as a serious environmental issue because of its persistence, toxicity, and bioaccumulation in the environmental matrix. Accurate classification of heavy metals is vital for environmental forensics, pollutant source identification, and sustainable environmental monitoring. Conventional analytical techniques such as atomic absorption spectroscopy, inductively coupled plasma mass spectrometry, and X-ray fluorescence provide excellent analytical sensitivity but usually require complicated sample preparation, high energy consumption, hazardous reagents, and lab-based equipment. The present review critically discusses recent advances in green analytical chemistry for the determination of heavy metals, with an emphasis on environmentally friendly sample preparation methods, biosensors, electrochemical sensors, nanotechnology-based detection, colorimetric detection, portable analytical devices, and microfluidic platforms. The analytical performance reported includes detection limits ranging from sub-ng L−1 to low µg L−1, recovery efficiencies of >80%–100%, and reduced solvent usage through microextraction and solvent-free methods. The report also discusses the applications of these technologies in environmental forensic investigations for pollutant source attribution and field monitoring. It offers a comprehensive evaluation of current issues, research gaps, and future potential, including artificial intelligence-enabled data interpretation, wearable sensor technologies, and sustainable portable analytical systems.
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Awasthi et al. (2026) studied this question.
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