Determination of a comprehensive set of drugs of abuse, metabolites and human biomarkers in wastewater using passive sampling followed by UHPLC-MS/MS analysis

Abstract

Passive sampling of wastewater using polar organic chemical integrative samplers (POCIS) is an interesting and cost-effective strategy for the quantification of biomarkers of drugs of abuse consumption in epidemiological studies. Particularly when combined with sensitive analytical method as ultra-high-performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS), POCIS sampling allows the long-term and sensitive determination of a wide range of analytes. In this study, a comprehensive analytical method integrating POCIS sampling, selective solid-phase extraction (SPE) of POCIS extracts, and analysis by UHPLC-MS/MS was developed and successfully validated for 12 biomarkers of substance use, with potential use in wastewater-based epidemiology. Chromatographic separation was achieved in 11 min. The assay has a wide liner range, with lower limits of quantification of 5 ng g−1 of POCIS sorbent. The selective SPE procedure, combining both cation and anion exchange cartridges, resulted in low matrix effects (-19.3 to 22.8% for compounds with a deuterated analog internal standard and 33.4 to 42.5% for anhydroecgonine methyl ester) and high extraction yields (93.4 to 106.4%). The lab-made POCIS sampler with Oasis® HLB sorbent was adequately calibrated for 9 compounds (4 drugs of abuse, 4 drug metabolites, and 1 human non-drug lifestyle markers). The method was applied in a wastewater treatment plant in Brazil, with continuous monitoring for 392 days in 2020–2021. The highest calculated wastewater concentration among drugs of abuse and metabolites was found for benzoylecgonine (431.5 ± 190.6 ng L-1), followed by 11-nor-9-carboxy-Δ9-THC (58.3 ± 21.1 ng L-1). The assay described in this study can be used as an effective tool to monitor the presence of relevant drug consumption biomarkers in wastewater, a relevant epidemiologic strategy currently limited due to the sophisticated infrastructure needed for representative sampling.