Spectroscopic fingerprinting of water contaminants: laser-based methods for chemical and biological sensing

Purpose This study aims to explore laser-based spectroscopic “fingerprinting” techniques for monitoring water quality in real time. Traditional laboratory-based analysis is frequently too slow to efficiently reduce the growing threat of chemical and biological contamination to global water resources. To establish an authoritative technical reference for developing next-generation, field-deployable sensing solutions, this review aims to assess the fundamental physical principles, operational features and practical applicability of emerging laser technologies, such as laser-induced breakdown spectroscopy (LIBS), laser-induced fluorescence (LIF), Raman/surface-enhanced Raman scattering (SERS), Fourier transform infrared spectroscopy and terahertz (THz) spectroscopy. Design/methodology/approach The paper follows a comparative review approach, starting with an analysis of laser-matter interactions in aquatic settings. It provides a structured review of five main spectroscopic techniques, evaluating their performance on sensitivity, selectivity and robustness. The methodology incorporates a cross-section of current advances (2020–2025) in nano-enhanced substrates, lab-on-a-chip integration and the role of data-driven frameworks [artificial intelligence (AI)/machine learning] in automating the identification of complicated chemical fingerprints in different water matrices. Findings The review concludes that, whereas LIBS and LIF succeed in detecting elements and aromatics, Raman/SERS and THz spectroscopy provide higher molecular specificity for pathogens and trace organics. The most recent development is the move to “intelligent” sensors that use graphene-based metasurfaces and photonic crystal fibers to solve water’s infrared absorption problems. The study finds that the incorporation of AI-driven chemometrics is critical for the shift from binary detection to autonomous “fingerprinting” and quantification in diverse environmental settings. Originality/value This research offers a novel design perspective by bridging the gap between fundamental optics and autonomous environmental monitoring. It provides value to researchers and practitioners by combining the most recent “nano-to-macro” sensing trends into a unified technical framework. Unlike previous studies, it focuses on the “spectroscopic fingerprint” a contaminant’s unique identifier, as the foundation for the future generation of intelligent, autonomous water quality regulation systems.