Assessing water pollution by micropollutants using passive sampling and forensic intelligence

Water pollution from agricultural, industrial, and urban activities poses a significant threat to ecosystems and human health. Traditional water monitoring methods, such as active sampling, often provide limited temporal resolution and/or spatial coverage. As an alternative, this study explores the use of passive sampling within a forensic operational monitoring framework to assess river pollution. Passive samplers were deployed across three rivers in Switzerland with diverse land-use profiles, to collect time-weighted average concentrations of various micropollutants, including pesticides, pharmaceuticals and industrial chemicals. These micropollutants were viewed as traces of anthropogenic activities. The collected data were integrated into a memory that enabled the detection of spatial and temporal pollution patterns and the formulation of hypotheses on potential contamination sources. This forensic intelligence framework provided a structured, iterative process for both monitoring and investigative purposes. The integration of passive sampling data within an operational monitoring cycle facilitated continuous data acquisition across multiple sites, allowing for an in-depth spatio-temporal assessment of river pollution. The memory component enabled systematic pattern detection, linking specific pollution profiles to land use types such as agriculture, industrial, and urban zones. By supporting hypothesis testing and refinement over time, the forensic monitoring framework offered a dynamic tool not only to detect pollution trends but also to identify their sources, potentially guiding timely and targeted environmental actions. This methodology highlights the utility of forensic science in environmental monitoring, providing actionable intelligence for stakeholders to enhance water quality management and inform adaptive policy interventions in response to recurring pollution events.