Non-Target Profiling of the Wastewater Metabolome Using a Suite of HRMS Tools: A Study Across Diverse Treatment Plants

Wastewater analysis has emerged as a powerful tool for wastewater-based epidemiology, environmental surveillance, and monitoring of emerging contaminants. While most studies rely on targeted approaches focusing on predefined compound lists, untargeted metabolomics offers potential to capture a broader and less biased chemical snapshot. However, the complexity of wastewater matrices and the chemical diversity of small molecules pose analytical challenges. In this study, we apply a multi-platform, untargeted metabolomics workflow to profile the influent wastewater metabolome of five wastewater treatment plants in Spain, differing in geographic context, population size, and industrial activity. Twenty-four-hour composite samples were collected in three seasons and analyzed using gas chromatography, reversed-phase liquid chromatography, and hydrophilic interaction liquid chromatography, all coupled to mass spectrometry. A total of 828 unique compounds were annotated across platforms, with minimal overlap, highlighting the complementarity of analytical approaches and extraction strategies. Multivariate analyses revealed reproducible site-associated chemical patterns consistent across seasons and platforms. Dominant contributors included lipids, organic acids, organic oxygen compounds, organoheterocyclic compounds, and benzenoids, reflecting differences in population and human activity. This work demonstrates the feasibility of a multi-platform untargeted workflow for generating complementary and reproducible comparative profiles of wastewater influent. The resulting public dataset is intended as a methodological and exploratory comparative resource, and broader spatial and longitudinal validation is required before generalization or use for source attribution.