A stochastic approach for parameter optimization of feature detection algorithms for non-target screening in mass spectrometry

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

Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that are used in countless products and applications. Due to the high stability of their C-F bonds, PFAS or their transformation products (TPs) are persistent in the environment, leading to ubiquitous detection in various samples worldwide. Since PFAS are industrial chemicals, the availability of authentic PFAS reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for a more comprehensive characterization. NTS usually is a time-consuming process, since only a small fraction of the detected chemicals can be identified. Therefore, efficient prioritization of relevant HRMS signals is one of the most crucial steps. We developed PFΔScreen, a Python-based open-source tool with a simple graphical user interface (GUI) to perform efficient feature prioritization using several PFAS-specific techniques such as the highly promising MD/C-m/C approach, Kendrick mass defect analysis, diagnostic fragments (MS2), fragment mass differences (MS2), and suspect screening. Feature detection from vendor-independent MS raw data (mzML, data-dependent acquisition) is performed via pyOpenMS (or custom feature lists) with subsequent calculations for prioritization and identification of PFAS in both HPLC- and GC-HRMS data. The PFΔScreen workflow is presented on four PFAS-contaminated agricultural soil samples from south-western Germany. Over 15 classes of PFAS (more than 80 single compounds with several isomers) could be identified, including four novel classes, potentially TPs of the precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). PFΔScreen can be used within the Python environment and is easily automatically installable and executable on Windows. Its source code is freely available on GitHub ( https://github.com/JonZwe/PFAScreen ).

The continuous release of perfluoroalkyl acids (PFAAs) from the transformation of per- and polyfluoroalkyl substances (PFAS) precursors presents a significant and often overlooked challenge in contaminated soils. In south-western Germany a large-scale agricultural topsoil contamination PFAS was discovered, which is known as the Rastatt case, and was traced back to the past application of paper sludge as soil amendment. In this study, 40 PFAS were monitored in eight topsoil samples from Rastatt according to the EPA 1633 method. Additionally, non-target screening was performed to identify PFAS precursors. FTMAPs, diPAPs, and diSAmPAP were identified and accounted for &gt; 80% of the total PFAS burden, which ranged from ~ 280 to 9,700 ng PFAS g-1. These levels were confirmed by both, non-target screening (semi)quantifications and chemical oxidation of precursors (TOP assay) in order to close the fluorine mass balance against extractable organic fluorine (EOF). Notably, in some organic carbon rich samples, repeated oxidation was needed to achieve a complete fluorine mass balance, highlighting the need to include EOF as quality assurance of TOP assays and (semi)quantifications derived from non-target screening approaches.Batch microcosm incubations were additionally set up to assess short-chain PFAS production over time. The linear increase of short-chain PFAS concentrations in solution, in combination with TOP estimates, allows to derive respective production rate constants and, therefore, estimate contamination time scales. This methodology may potentially apply to other precursor-driven contaminant sources such as those present in aqueous film-forming foam (AFFF) sites. Contamination time scales in the assessed locations indicate that leaching of short-chain PFAS to groundwater resulting from ongoing precursor transformation will continue for decades. The variability in time scale estimates across the eight examined soils encouraged the examination of specific soil properties affecting PFAS production rates, particularly assessing the role of certain phosphatase enzymatic activities and microbial biomass carbon. FTMAPs, diPAPs, and diSAmPAP all contain a phosphate moiety which is hydrolyzed during biotransformation processes. A principal component analysis (PCA) indicated the positive role of both acid phosphomonoesterase activities and, in lesser extent, microbial biomass carbon on the production of short-chain PFAS in soils. Nonetheless, further research on isolated bacteria strains is needed to elucidate the role of phosphatases as well as other enzymatic activities in the decay of P-containing PFAS precursors.

Characterization and risk prioritization of PFAS via nontarget screening in soil and maize near a fluoropolymer manufacturing facility.

Occurrence and patterns of legacy and emerging per- and polyfluoroalkyl substances (PFAS) in bones of white-beaked dolphin (Lagenorhynchus albirostris) using target, suspect, and non-target screening.

Soil contaminations with per- and polyfluoroalkyl substances (PFAS) are of great concern due to their persistence, leading to continuous, long-term groundwater contamination. A composite sample from contaminated agricultural soil from northwestern Germany (Brilon-Scharfenberg, North Rhine-Westphalia) was investigated in depth with nontarget screening (NTS) (Kendrick mass defect and MS2 fragment mass differences with FindPFΔS). Several years ago, selected PFCAs and PFSAs were identified on this site by detection in nearby surface and drinking water. We identified 10 further PFAS classes and 7 C8-based PFAS (73 single PFAS) previously unknown in this soil including some novel PFAS. All PFAS classes except for one class comprised sulfonic acid groups and were semi-quantified with PFSA standards from which ∼97% were perfluorinated and are not expected to be degradable. New identifications made up >75% of the prior known PFAS concentration, which was estimated to >30 μg/g. Pentafluorosulfanyl (-SF5) PFSAs are the dominant class (∼40%). Finally, the soil was oxidized with the direct TOP (dTOP) assay, revealing PFAA precursors that were covered to a large extent by identified H-containing PFAS and additional TPs (perfluoroalkyl diacids) were detected after dTOP. In this soil, however, dTOP + target analysis covers <23% of the occurring PFAS, highlighting the importance of NTS to characterize PFAS contaminations more comprehensively.

Integration of target, suspect, and nontarget screening with risk modeling for per- and polyfluoroalkyl substances prioritization in surface waters

PFAS levels in paired drinking water and serum samples collected from an exposed community in Central North Carolina

Risk prioritization and experimental validation of per- and polyfluoroalkyl substances (PFAS) in Chaohu Lake: Based on nontarget and target analyses.

Screening for 26 per- and polyfluoroalkyl substances (PFAS) in German drinking waters with support of residents

Prevalence of per- and polyfluoroalkyl substances (PFASs) in drinking and source water from two Asian countries

Novel per- and polyfluoroalkyl substances (PFASs) in various environmental media have attracted increasing attention; however, the information regarding PFASs exposure in pregnant women and fetuses is insufficient. In this study, we built and applied suspect and nontarget screening strategies based on the mass difference of the CF2, CF2O, and CH2CF2 units to select potential novel PFASs from 117 paired maternal and cord sera. In total, 10 legacy PFASs and 19 novel PFASs from 10 classes were identified to be above confidence levels 3, among which 14 were not previously reported in human serum. Novel PFASs accounted for a considerable percentage of total PFASs in pregnant women and can be transferred to fetuses at non-negligible concentrations (i.e., 27.9% and 30.3% of total PFAS intensities in maternal and cord sera, respectively). The transplacental transfer efficiency (TTE) of PFASs showed a U-shape trend in the series of perfluoroalkyl carboxylic acids, perfluoroalkyl sulfonic acids, and unsaturated perfluorinated alcohols. The TTE of novel PFASs is suggested to be structure-dependent, based on a flexible docking experiment. This study provides comprehensive TTE information on legacy and novel PFASs for the first time, and additional toxicity studies are needed to evaluate the risk of novel PFASs further.

Occurrence and contamination profile of legacy and emerging per- and polyfluoroalkyl substances (PFAS) in Belgian wastewater using target, suspect and non-target screening approaches

Due to the lack of transparency in the production and applications of emerging per- and polyfluoroalkyl substances (PFAS), it is a huge challenge to grasp the real PFAS pollution profile in a specific region or industry by target analysis. This study collected extensive samples across China, including municipal wastewater from 9 major cities and wastewater from various manufacturing stages at 3 large semiconductor factories. Suspect and nontarget screening were conducted along with target analysis, and 82 PFAS in 25 classes were identified. Notably, this is the first study to investigate PFAS contamination in semiconductor wastewater on the Chinese mainland. Moreover, 13 classes of PFAS were reported for the first time worldwide in semiconductor wastewater, including multiple hydrosubstituted perfluoroalkyl carboxylic acid (mH-PFCA), ether-inserted PFCA (OPFCA), and perfluoroalkyl alcohol (PA) derivatives. The highest total concentrations of target, suspect, and nontarget PFAS in semiconductor wastewater (12 μg/L) were substantially higher than those measured in all municipal wastewater (25-950 ng/L). The composition of PFAS varied regionally in semiconductor wastewater. Total oxidizable precursor assay revealed the presence of unknown precursors (0.043-0.83 nmol/L), which cannot be directly monitored but may pose a greater PFAS contamination risk in semiconductor water treatment and discharge processes.

Nontarget screening strategies for PFAS prioritization and identification by high resolution mass spectrometry: A review