Monitoring of psychoactive drugs and their metabolites in wastewater is critical to understanding their environmental fate and potential impacts. Passive sampling offers a complementary approach to conventional composite sampling, providing time-integrated monitoring, while offering insights into bioavailable fractions of compounds. This study evaluates the applicability of an active-passive sampling (APS) approach for monitoring eight psychoactive compounds in effluent wastewater, integrating field deployments with predictive modelling of sorbent-to-water partition coefficients (). APS and diffusive gradients in thin films (DGT) samplers, equipped with hydrophilic-lipophilic balanced (HLB) and mixed-mode cation exchange (MCX) sorbents were deployed alongside daily composite sampling during 2023-2024 monitoring campaigns in Belgium and Slovenia. APS exhibited non-linear uptake kinetics indicative of non-ideal sink behaviour and additional mass-transfer limitations, including interfacial effects, while DGT uptake remained predominantly diffusion-controlled over the deployment periods. values were predicted using tree-based machine-learning models (Random Forest and XGBoost), enabling robust interpretation of APS data under near-equilibrium conditions. APS and DGT measurements generally showed good agreement, though APS concentrations were systematically higher for most compounds, with differences influenced by sorbent type and environmental factors. The controlled laminar flow of APS enhanced sorption consistency under variable wastewater conditions. Comparisons with composite sampling highlighted the complementary nature of these approaches, with APS providing additional insights on bioavailable and particle-bound fractions. Overall, APS presents a robust and versatile tool for monitoring psychoactive compounds, supporting quantitative assessment of contaminant dynamics, bioavailability, and fate in aquatic systems.
Anies et al. (Tue,) studied this question.