Suspect Screening and Prioritization as an Analytical Strategy for the Identification of Persistent, Mobile, and Toxic (PMT) Substances in Surface Water

Persistent, mobile,
and toxic (PMT) substances have gained increasing
scientific and regulatory attention due to their capacity to bypass
natural and artificial barriers and spread throughout the water cycle.
However, knowledge of their environmental occurrence remains limited
due to analytical challenges, particularly in detecting highly polar
substances that are often overlooked in monitoring studies. This study
aims to identify PMT substances that are worth monitoring in surface
waters strongly influenced by wastewater treatment plant effluents.
A suspect screening analysis (SSA) approach based on the use of LC-HRMS
was integrated with a tiered prioritization strategy. Our workflow
integrates multimodal SPE and LC approaches to improve PMT detection
coverage across polarity gradients. A total of 305 substances were
tentatively identified, and 103 of them were prioritized as PMT substances,
encompassing industrial chemicals, personal care products, pharmaceuticals,
illicit drugs, pesticides, and transformation products. Notably, only
13% of PMT substances are currently included in the European Water
Framework Directive legislation or the REACH list of substances of
very high concern. Among them, 35 high-priority PMT substances were
confirmed with analytical standards through mass spectrometry (MS/MS)
in tandem with HRMS, providing reliable fragmentation data. Some of
these substances such as the pharmaceutical celecoxib, the ultrashort-chain
per- and polyfluoroalkyl substance (PFAS) bis(trifluoromethylsulfonyl)imide,
or the industrial chemical 1,3-di-o-tolylguanidine
(DTG) have been scarcely investigated in environmental monitoring
efforts. The methodological framework presented in this study is readily
adaptable to a wide range of environmental scenarios. The results
obtained highlight the importance of integrating SSA as a complementary
approach to conventional target analysis.