Analytical techniques and source apportionment for heavy metal(loid)s in groundwater: A comprehensive review

Abstract

• Assesses analytical methodology for trace heavy metal(loid)s (HMs) in groundwater • Advances in hyphenated techniques and portable sensors enable on-site HM detection • Instrumental GC- and LC-ICP-MS parameters for Cr, As, Sb, Se, Hg, and Sn speciation • Employs multivariate and isotopic techniques to apportion HM contamination sources • Identifies knowledge gaps and guides future research to improve groundwater safety Groundwater contamination by heavy metal(loid)(HM) is a pervasive global issue threatening drinking water quality and public health. Effective mitigation requires robust analytical methodologies and predictive modeling frameworks. This review critically assesses cutting-edge instrumental techniques and source apportionment methods for detecting and understanding HM pollution in groundwater. Advanced laboratory techniques, exemplified by inductively coupled plasma mass spectrometry (ICP-MS), now achieve extraordinary sensitivity with detection limits in the sub-μg/L range and exhibit high precision (relative standard deviations between 2-3%). Furthermore, hyphenated chromatography-spectrometry techniques, such as ion chromatography coupled to ICP-MS, facilitate detailed chemical speciation, effectively resolving redox-sensitive pairs such as Cr(III)/Cr(VI) and As(III)/As(V) at environmental concentrations (1-50 µg/L). Meanwhile, emerging electrochemical portable sensors enable on-site, real-time monitoring of groundwater quality. For source apportionment, multivariate statistical methods (including receptor models), isotopic fingerprinting, and machine learning algorithms have been increasingly integrated to disentangle complex mixtures of natural versus anthropogenic metal sources. By combining improved detection limits, enhanced speciation insights, and powerful data analytics and modeling tools, modern approaches support groundwater monitoring and pollution source tracking. Nevertheless, challenges such as matrix interferences, instability of metal species during sampling, and overlapping source signatures continue to complicate analysis, underscoring the need for integrated approaches that merge analytical innovation with data-driven tools to refine source attribution and ultimately ensure groundwater safety. Critical knowledge gaps are identified, including the need for more consistent monitoring approaches, closer integration of new analytical tools with field practice, and stronger policies to make sure scientific progress actually leads to better groundwater protection.

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