Data-driven prioritization of chemicals for various water types using suspect screening LC-HRMS
“For the prioritization of more than 5200 anthropogenic chemicals authorized on the European market, we use a large scale liquid chromatography-high resolution mass spectrometry (LC-HRMS) suspect screening study. The prioritization is based on occurrence in 151 water samples including effluent, surface water, ground water and drinking water. The suspect screening linked over 700 detected compounds with known accurate masses to one or multiple suspects. Using a prioritization threshold and removing false positives reduced this to 113 detected compounds linked to 174 suspects, 24 compounds reflect a confirmed structure by comparison with the pure reference standard. The prioritized compounds and suspects are relevant for detailed risk assessments after confirmation of their identity. Only one of the 174 prioritized compounds and suspects is mentioned in water quality regulations, and only 20% is mentioned on existing lists of potentially relevant chemicals. This shows the complementarity to commonly used target-based methods. The semi-quantitative total concentration, expressed as internal standard equivalents of detected compounds linked to suspects, in effluents is approximately 10 times higher than in surface waters, while ground waters and drinking waters show the lowest response. The average retention time, a measure for hydrophobicity, of the detected compounds per sample decreased from effluent to surface- and groundwater to drinking water, confirming the occurrence of more polar compounds in drinking water. The semi-quantitative total concentrations exceed the conservative and precautionary threshold of toxicological concern. Therefore, adverse effects of mixtures cannot be neglected without a more thorough risk assessment.”
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(Citaat: Sjerps, R.M.A., Vughs, D.M., van Leerdam, J.A., ter Laak, T.L., van Wezel, A.P. – Data-driven prioritization of chemicals for various water types using suspect screening LC-HRMS – Water Research 93(2016)254-264)