Mapping the Limits of Passive Samplers in Water: Chemical Space Coverage Using Nontargeted Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) Analysis

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Publikace nespadá pod Ústav výpočetní techniky, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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CETL Pavla TYSKLIND Mats GOLOSOVSKAIA Elena GRABICOVA Katerina VRANA Branislav GRABIC Roman

Rok publikování 2025
Druh Článek v odborném periodiku
Časopis / Zdroj ACS ES&T WATER
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://pubs.acs.org/doi/10.1021/acsestwater.5c00565
Doi https://doi.org/10.1021/acsestwater.5c00565
Klíčová slova POCIS; <italic>o</italic>-DGT; Speedisk; pharmaceuticals; pesticides; suspect screening; molecular descriptor; multivariate characterization
Popis Passive sampling (PS) combined with nontargeted analysis provides a time-representative picture of contaminants in water that are not covered by conventional monitoring. This innovative approach was further enhanced by chemical space modeling to predict the chemical space captured by passive samplers. In this study, three passive samplers for polar compounds, i.e., POCIS, hydrogel-based passive sampler (HPS), and Speedisk, were deployed in municipal wastewater treatment plant effluent and analyzed by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with data-independent acquisition (DIA). Compounds identified by suspect screening were used together with target compounds to map the sampled chemical space using a multivariate analysis of 1686 compounds and 31 physicochemical descriptors. In total, 216 unique compounds were identified, including 127 compounds from suspect screening, of which 61 were not covered by targeted analysis. A similar number of compounds were detected in all three passive samplers, indicating a surprisingly similar sampled chemical space. Using chemical space mapping, a chemical domain of 1150 compounds within the molar mass range of 150-600 was identified to be sampled by PS with 95% confidence. This novel approach emphasizes combining analytical and modeling tools to provide deeper insight into the limitations of passive sampler coverage.
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