Retrospective suspect and non-target screening combined with similarity measures to prioritize MDMA and amphetamine synthesis markers in wastewater

• Published in: The Science of the total environment 2022-03, Vol.811, p.152139-152139, Article 152139
• Main Authors: Reymond, Naomi, Emke, Erik, Boucheron, Thea, ter Laak, Thomas, de Voogt, Pim, Esseiva, Pierre, Been, Frederic
• Format: Article
• Language: English
• Subjects: (pre-)precursors; Amphetamine; Chromatography, Liquid; LC-HRMS; Manufacturing; MDMA; N-Methyl-3,4-methylenedioxyamphetamine; Retrospective Studies; Substance Abuse Detection; Waste Water; Wastewater
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2021.152139

3,4-Methylenedioxymethamphetamine (MDMA) and amphetamine are commonly used psychoactive stimulants. Illegal manufacture of these substances, mainly located in the Netherlands and Belgium, generates large amounts of chemical waste which is disposed in the environment or released in sewer systems. Retrospective analysis of high-resolution mass spectrometry (HRMS) data was implemented to detect synthesis markers of MDMA and amphetamine production in wastewater samples. Specifically, suspect and non-target screening, combined with a prioritization approach based on similarity measures between detected features and mass loads of MDMA and amphetamine was implemented. Two hundred and thirty-five 24 h-composite wastewater samples collected from a treatment plant in the Netherlands between 2016 and 2018 were analyzed by liquid chromatography coupled to high-resolution mass spectrometry. Samples were initially separated into two groups (i.e., baseline consumption versus dumping) based on daily loads of MDMA and amphetamine. Significance testing and fold-changes were used to find differences between features in the two groups. Then, associations between peak areas of all features and MDMA or amphetamine loads were investigated across the whole time series using various measures (Euclidian distance, Pearson's correlation coefficient, Spearman's rank correlation coefficient, distance correlation and maximum information coefficient). This unsupervised and unbiased approach was used for prioritization of features and allowed the selection of 28 presumed markers of production of MDMA and amphetamine. These markers could potentially be used to detect dumps in sewer systems, help in determining the synthesis route and track down the waste in the environment. [Display omitted] •Suspect and non-target screening of drug manufacturing waste in wastewater•A novel prioritization approach was implemented based on distance measures.•Selection of 28 presumed markers of production of MDMA and amphetamine•Detect disposal of illegal waste and monitor synthesis route