MODERN ANALYTICAL APPROACHES FOR THE DETECTION AND QUANTITATIVE ANALYSIS OF HEAVY METALS IN ENVIRONMENTAL MATRICES

Ezekiel Izudike Odimgbe, Micheal Abimbola Oladosu*, Moses Adondua Abah, Joseph Ezeani, Alaba Oladapo Gbadebo, Chigozirim Steve Amadi

ABSTRACT

Heavy metal contamination of environmental matrices including water, soil, sediment, and biological specimens, constitutes a pervasive public health and ecological concern of global magnitude. The accurate detection and quantitative determination of heavy metals are indispensable for environmental monitoring, risk assessment, and regulatory compliance. This review critically appraises modern analytical strategies employed for heavy metal analysis across diverse environmental matrices. Classical techniques including flame atomic absorption spectrometry (FAAS), graphite furnace atomic absorption spectrometry (GFAAS), inductively coupled plasma-optical emission spectrometry (ICP-OES), and inductively coupled plasma-mass spectrometry (ICP-MS) are evaluated alongside emerging approaches such as laser-induced breakdown spectroscopy (LIBS), portable X-ray fluorescence (pXRF), electrochemical sensors, and aptamer-based biosensors. Special attention is accorded to sample preparation strategies, multi-element analysis capabilities, detection limits, matrix interferences, and green analytical chemistry considerations. The comparative strengths and limitations of each technique are discussed in the context of their field and laboratory applicability. The review further highlights the integration of nanomaterials, machine learning algorithms, and miniaturised platforms as transformative innovations enhancing sensitivity, selectivity, and throughput. Prospects for point-of-care and real-time environmental monitoring are identified, with implications for low-resource settings such as those encountered in sub-Saharan Africa.

Keywords: heavy metals; environmental matrices; ICP-MS; electrochemical sensors; LIBS; atomic absorption spectrometry; XRF; biosensors; nanomaterials; environmental monitoring.