Practical Semiquantification Strategy for Estimating Suspect Per- and Polyfluoroalkyl Substance (PFAS) Concentrations

Hunting the missing fluorine in aqueous film-forming foams containing per- and polyfluoroalkyl substances

Since aqueous film-forming foams (AFFFs) are major sources of per- and polyfluoroalkyl substances (PFAS), understanding the quantity and type of PFAS present in AFFFs is crucial for assessing environmental risk and remediation. We characterized 25 foams from Canada and Europe, including two non-AFFFs and two fluorine-free AFFFs. We used liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) to identify novel PFAS, as well as total oxidizable precursor assays (TOP) and total organofluorine (TOF) measurements for comparison. LC-HRMS showed that the two non-AFFF foams and two PFAS-free AFFFs contained little or no PFAS, confirmed by TOF measurement using combustion ion chromatography (CIC). The PFAS-containing AFFFs, however, spanned a wide concentration range of TOF (2200-45,000 mg F/L) and contained 22 new classes of polyfluoroalkyl substances not previously reported. As a result of identifying new compounds, LC-HRMS was fully able to capture the oxidizable precursors determined by TOP assay in all tested fluorotelomer (FT) AFFFs, while unknown compounds still constituted a significant fraction (19-53 mol%) in most electrochemical fluorination (ECF) AFFFs. A fluorine mass balance was achieved by comparing the amounts of compounds identified by LC-HRMS with those detected by CIC, although LC-HRMS overestimated TOF with a recovery of 127 ± 36%.

Detection, Quantification, and Isomer Differentiation of Per- and Polyfluoroalkyl Substances (PFAS) Using MALDI-TOF with Trapped Ion Mobility

Per- and polyfluoroalkyl substances (PFAS) are a class of organic compounds that have attracted global attention for their persistence in the environment, exposure to biological organisms, and their adverse health effects. There is an urgent need to develop analytical methodologies for the characterization of PFAS in various sample matrices. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) represents a chromatography-free MS method that performs laser-based ionization and in situ analysis on samples. In this study, we present PFAS analysis by MALDI-time-of-flight (TOF) MS with trapped ion mobility spectrometry (TIMS), which provides an additional dimension of gas phase separation based on the size-to-charge ratios. MALDI matrix composition and key instrument parameters were optimized to produce different ranges of calibration curves. Parts per billion (ppb) range of calibration curves were achieved for a list of legacy and alternative perfluorosulfonic acids (PFSAs) and perfluorocarboxylic acids (PFCAs), while ion mobility spectrum filtering enabled parts per trillion (ppt) range of calibration curves for PFSAs. We also successfully demonstrated the separation of three perfluorooctanesulfonic acid (PFOS) structural isomers in the gas phase using TIMS. Our results demonstrated the new development of utilizing MALDI-TOF-MS coupled with TIMS for fast, quantitative, and sensitive analysis of PFAS, paving ways to future high-throughput and in situ analysis of PFAS such as MS imaging applications.

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances

Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration "surrogates," which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from "global" chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using "global" surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using "expert-selected" surrogates (n = 3) instead of "global" surrogates (n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases.

Target and Suspect Screening Integrated with Machine Learning to Discover Per- and Polyfluoroalkyl Substance Source Fingerprints

This study elucidates per- and polyfluoroalkyl substance (PFAS) fingerprints for specific PFAS source types. Ninety-two samples were collected from aqueous film-forming foam impacted groundwater (AFFF-GW), landfill leachate, biosolids leachate, municipal wastewater treatment plant effluent (WWTP), and wastewater effluent from the pulp and paper and power generation industries. High-resolution mass spectrometry operated with electrospray ionization in negative mode was used to quantify up to 50 target PFASs and screen and semi-quantify up to 2,266 suspect PFASs in each sample. Machine learning classifiers were used to identify PFASs that were diagnostic of each source type. Four C5-C7 perfluoroalkyl acids and one suspect PFAS (trihydrogen-substituted fluoroethernonanoic acid) were diagnostic of AFFF-GW. Two target PFASs (5:3 and 6:2 fluorotelomer carboxylic acids) and two suspect PFASs (4:2 fluorotelomer-thia-acetic acid and N-methylperfluoropropane sulfonamido acetic acid) were diagnostic of landfill leachate. Biosolids leachates were best classified along with landfill leachates and N-methyl and N-ethyl perfluorooctane sulfonamido acetic acid assisted in that classification. WWTP, pulp and paper, and power generation samples contained few target PFASs, but fipronil (a fluorinated insecticide) was diagnostic of WWTP samples. Our results provide PFAS fingerprints for known sources and identify target and suspect PFASs that can be used for source allocation.

The environmental degradability of DEMNUM, a typical PFPE polymer

The three environmental degradation tests of hydrolysis, indirect photolysis and Zahn-Wellens microbial degradation were conducted according to the OECD and the US EPA guidelines on DEMNUM, a typical linear perfluoropolyether polymer. Low mass degradation products that formed in each test were structurally characterized and indirectly quantified by liquid chromatography mass spectrometry (LC/MS) using a reference compound and an internal standard of similar structure. The degradation of the polymer was assumed to directly correlate with the appearance of lower mass species. The hydrolysis experiment at 50 °C showed the appearance of less than a dozen low mass species with increasing pH but at the negligible total estimated amount of ∼2 ppm relative to polymer. A dozen low mass perfluoro acid entities also appeared following the indirect photolysis experiment in synthetic humic water. Their maximum total amount was at ∼150 ppm relative to polymer. The largest amount of low mass species formed during the Zahn-Wellens biodegradation test amounted to only ∼80 ppm relative to polymer. The Zahn-Wellens conditions tended to produce larger low mass molecules than the ones formed under photolysis. The results from all three tests indicate that the polymer is stable and non-degradable in the environment.