Retrospective screening of high-resolution mass spectrometry archived digital samples can improve environmental risk assessment of emerging contaminants: A case study on antifungal azoles
- Journal Article
Environmental risk assessment associated with aquatic and terrestrial contamination is mostly based on predicted or measured environmental concentrations of a limited list of chemicals in a restricted number of environmental compartments. High resolution mass spectrometry (HRMS) can provide a more comprehensive picture of exposure to harmful chemicals, particularly through the retrospective analysis of digitally stored HRMS data. Using this methodology, our study characterized the contamination of various environmental compartments including 154 surface water, 46 urban effluent, 67 sediment, 15 soil, 34 groundwater, 24 biofilm, 41 gammarid and 49 fish samples at 95 sites widely distributed over the Swiss Plateau. As a proof-of-concept, we focused our investigation on antifungal azoles, a class of chemicals of emerging concern due to their endocrine disrupting effects on aquatic organisms and humans. Our results demonstrated the occurrence of antifungal azoles and some of their (bio)transformation products in all the analyzed compartments (0.1–100 ng/L or ng/g d.w.). Comparison of actual and predicted concentrations showed the partial suitability of level 1 fugacity modelling in predicting the exposure to azoles. Risk quotient calculations additionally revealed risk of exposure especially if some of the investigated rivers and streams are used for drinking water production. The case study clearly shows that the retrospective analysis of HRMS/MS data can improve the current knowledge on exposure and the related risks to chemicals of emerging concern and can be effectively employed in the future for such purposes. Show more
Journal / seriesEnvironment International
Pages / Article No.
SubjectEnvironmental risk assessment; Antifungal-azoles; High resolution mass spectrometry; Partitioning; Exposure assessment; Retrospective screening; Digital samples
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