A SPE-HPLC-MS/MS method for the simultaneous determination of prioritised pharmaceuticals and EDCs with high environmental risk potential in freshwater

Stuart W. Gibb , Yuan Li , Mark A. Taggart , Craig McKenzie , Zulin Zhang , Yonglong Lu , Sabolc Pap


Received April 17, 2020,Revised , Accepted July 09, 2020, Available online July 21, 2020

Volume 33,2021,Pages 18-27

This work describes the development, optimisation and validation of an analytical method for the rapid determination of 17 priority pharmaceutical compounds and endocrine disrupting chemicals (EDCs). Rather than studying compounds from the same therapeutic class, the analyses aimed to determine target compounds with the highest risk potential (with particular regard to Scotland), providing a tool for further monitoring in different water matrices. Prioritisation was based on a systematic environmental risk assessment approach, using consumption data; wastewater treatment removal efficiency; environmental occurrence; toxicological effects; and pre-existing regulatory indicators. This process highlighted 17 compounds across various therapeutic classes, which were then quantified, at environmentally relevant concentrations, by a single analytical methodology. Analytical determination was achieved using a single-step solid phase extraction (SPE) procedure followed by high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS). The fully optimised method performed well for the majority of target compounds, with recoveries >71% for 15 of 17 analytes. The limits of quantification for most target analytes (14 of 17) ranged from 0.07 ng/L to 1.88 ng/L in river waters. The utility of this method was then demonstrated using real water samples associated with a rural hospital/setting. Eight compounds were targeted and detected, with the highest levels found for the analgesic, paracetamol (at up to 105,910 ng/L in the hospital discharge). This method offers a robust tool to monitor high priority pharmaceutical and EDC levels in various aqueous sample matrices.

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