Specifying and interpreting the occurrence of emerging pollutants is essential for assessing treatment processes and plants, conducting wastewater-based epidemiology, and advancing environmental toxicology research. In recent years, artificial intelligence (AI) has been increasingly applied to enhance chemical analysis and monitoring of contaminants in environmental water and wastewater. However, their specific roles targeting pharmaceuticals and personal care products (PPCPs) have not been reviewed sufficiently. This review aims to narrow the gap by highlighting, scoping, and discussing the incorporation of AI during the detection and quantification of PPCPs when utilising chemical analysis equipment and interpreting their monitoring data for the first time. In the chemical analysis of PPCPs, AI-assisted prediction of chromatographic retention times and collision cross-sections (CCS) in suspect and non-target screenings using high-resolution mass spectrometry (HRMS) enhances detection confidence, reduces analysis time, and lowers costs. AI also aids in interpreting spectroscopic analysis results. However, this approach still cannot be applied in all matrices, as it offers lower sensitivity than liquid chromatography coupled with tandem or HRMS. For the interpretation of monitoring of PPCPs, unsupervised AI methods have recently presented the capacity to survey regional or national community health and socioeconomic factors. Nevertheless, as a challenge, long-term monitoring data sources are not given in the literature, and more comparative AI studies are needed for both chemical analysis and monitoring. Finally, AI assistance anticipates more frequent applications of CCS prediction to enhance detection confidence and the use of AI methods in data processing for wastewater-based epidemiology and community health surveillance.

Centre for Urban Sustainability and Resilience Department of Civil Environmental and Geomatic Engineering University College London London WC1E6BT UK

Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec 46117 Liberec Czech Republic

School of Computing and Engineering University of West London St Mary's Rd London W5 5RF UK

School of Computing and Engineering University of West London St Mary's Rd London W5 5RF UK; Centre for Engineering Research School of Physics Engineering and Computer Science University of Hertfordshire Hatfield AL10 9AB UK

School of Computing and Engineering University of West London St Mary's Rd London W5 5RF UK; Centre for Urban Sustainability and Resilience Department of Civil Environmental and Geomatic Engineering University College London London WC1E6BT UK

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