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Emerging contaminants (ECs), encompassing pharmaceuticals, personal care products, pesticides, and industrial chemicals, represent a growing threat to ecosystems and human health due to their persistence, bioaccumulation potential, and often-unknown toxicological profiles. Addressing these challenges necessitates advanced analytical tools capable of detecting and quantifying trace levels of ECs in complex environmental matrices. This review highlights the pivotal role of mass spectrometry (MS) in monitoring ECs, emphasizing its high sensitivity, specificity, and versatility across various techniques such as Gas Chromatography-Mass Spectrometry (GC-MS), Liquid Chromatography-Mass Spectrometry (LC-MS), and High-Resolution Mass Spectrometry (HR-MS). The application of MS has facilitated the real-time detection of volatile organic compounds, the comprehensive non-targeted screening of unknown contaminants, and accurate quantification in diverse matrices including water, soil, and air. Despite its effectiveness, challenges such as matrix interferences, a lack of standardized methodologies, and limited spectral libraries persist. However, recent advancements, including hybrid MS systems and the integration of artificial intelligence (AI), are paving the way for more efficient environmental monitoring and predictive modeling of contaminant behavior. Continued innovation in MS technologies and collaborative efforts are essential to overcome existing challenges and ensure sustainable solutions for mitigating the risks associated with emerging contaminants.
Meher et al. (Fri,) studied this question.