Efficient PFAS prioritization in non-target HRMS data: systematic evaluation of the novel MD/C-m/C approach

Abstract

Non-target screening (NTS) based on high-resolution mass spectrometry (HRMS) is necessary to comprehensively characterize per- and polyfluoroalkyl substances (PFAS) in environmental, biological, and technical samples due to the very limited availability of authentic PFAS reference standards. Since in trace analysis, MS/MS information is not always achievable and only selected PFAS are present in homologous series, further techniques to prioritize measured HRMS data (features) according to their likelihood of being PFAS are highly desired due to the importance of efficient data reduction during NTS. Kaufmann et al. (J AOAC Int, 2022) presented a very promising approach to separate selected PFAS from sample matrix features by plotting the mass defect (MD) normalized to the number of carbons (MD/C) vs. mass normalized to the number of C (m/C). We systematically evaluated the advantages and limitations of this approach by using ~ 490,000 chemical formulas of organic chemicals (~ 210,000 PFAS, ~ 160,000 organic contaminants, and 125,000 natural organic matter compounds) and calculating how efficiently, and especially which, PFAS can be prioritized. While PFAS with high fluorine content (approximately: F/C > 0.8, H/F < 0.8, mass percent of fluorine > 55%) can be separated well, partially fluorinated PFAS with a high hydrogen content are more difficult to prioritize, which we discuss for selected PFAS. In the MD/C-m/C approach, even compounds with highly positive MDs above 0.5 Da and hence incorrectly assigned to negative MDs can still be separated from true negative mass defect features by the normalized mass (m/C). Furthermore, based on the position in the MD/C-m/C plot, we propose the estimation of the fluorine fraction in molecules for selected PFAS classes. The promising MD/C-m/C approach can be widely used in PFAS research and routine analysis. The concept is also applicable to other compound classes like iodinated compounds. Graphical Abstract: [Figure not available: see fulltext.]