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.

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

Semiquantitation of suspect per- and polyfluoroalkyl substances (PFAS) in complex mixtures is challenging due to the increasing number of suspect PFAS. Traditional 1:1 matching strategies require selecting calibrants (target-surrogate standard pairs) based on head group, fluorinated chain length, and retention time, which is time-consuming and requires expert knowledge. Lack of uniformity in calibrant selection for estimating suspect concentrations among different laboratories makes comparing reported suspect concentrations difficult. In this study, a practical approach whereby the area counts for 50 anionic and 5 zwitterionic/cationic target PFAS were ratioed to the average area of their respective stable-isotope labeled surrogates to create "average PFAS calibration curves" for suspects detected in negative- and positive-ionization mode liquid chromatography quadrupole time-of-flight mass spectrometry. The calibration curves were fitted with log-log and weighted linear regression models. The two models were evaluated for their accuracy and prediction interval in predicting the target PFAS concentrations. The average PFAS calibration curves were then used to estimate the suspect PFAS concentration in a well-characterized aqueous film-forming foam. Weighted linear regression resulted in more target PFAS that fell within 70-130% of their known standard value and narrower prediction intervals than the log-log transformation approach. The summed suspect PFAS concentrations calculated by weighted linear regression and log-log transformation were within 8 and 16% of those estimated by a 1:1 matching strategy. The average PFAS calibration curve can be easily expanded and can be applied to any suspect PFAS even if the confidence in the suspect structure is low or unknown.

Enrichment of poly- and perfluoroalkyl substances (PFAS) in the surface microlayer and foam in synthetic and natural waters.

Bench-scale experiments were performed to interrogate poly- and perfluoroalkyl substance (PFAS) enrichment in the water surface microlayer (SML). In initial experiments using electrolyte-only solutions, the perfluorooctane sulfonate (PFOS) and perfluorooctane carboxylate (PFOA) enrichment in the SML were reasonably (with a factor of 2) described by the Gibbs adsorption equation coupled with a Freundlich-based interfacial adsorption model. Enrichment in the SML among perfluorinated sulfonates and perfluorinated carboxylates of varying chain lengths was proportional to their surface activity. The PFOS enrichment factor (EF), defined as the PFAS concentration in the SML divided by the concentration in the bulk water, was 18 in a 200 mg/l NaCl solution. The presence of elevated organic carbon levels in synthetic surface waters inhibited PFAS accumulation in the SML, with resulting EF values of approximately 1 for all PFAS. However, in the presence of elevated organic levels coupled with foam, PFAS enrichment in the foam was observed, with a foam EF of 25 measured for PFOS in synthetic surface waters. PFAS EF values measured in several natural surface waters without foam showed little variation among the waters tested, with PFOS EF values ranging between 6 and 10. Together, these results suggest that PFAS accumulation in the SML is largely controlled by PFAS sorption at the air-water interface for the conditions examined in this study, and the presence of foam with natural organics enhances PFAS uptake at the water surface.

Communicating Confidence of Per- and Polyfluoroalkyl Substance Identification via High-Resolution Mass Spectrometry.

Per- and polyfluoroalkyl substances (PFASs) are important environmental contaminants, yet relatively few analytical reference standards exist for this class. Nontarget analyses performed by means of high-resolution mass spectrometry (HRMS) are increasingly common for the discovery and identification of PFASs in environmental and biological samples. The certainty of PFAS identifications made via HRMS must be communicated through a reliable and harmonized approach. Here, we present a confidence scale along with identification criteria specific to suspect or nontarget analysis of PFASs by means of nontarget HRMS. Confidence levels range from level 1a-"Confirmed by Reference Standard," and level 1b-"Indistinguishable from Reference Standard," to level 5-"Exact Masses of Interest," which are identified by suspect screening or data filtering, two common forms of feature prioritization. This confidence scale is consistent with general criteria for communicating confidence in the identification of small organic molecules by HRMS (e.g., through a match to analytical reference standards, library MS/MS, and/or retention times) but incorporates the specific conventions and tools used in PFAS classification and analysis (e.g., detection of homologous series and specific ranges of mass defects). Our scale clarifies the level of certainty in PFAS identification and, in doing so, facilitates more efficient identification.

The chemistry and toxicology of vaping.

Vaping is the process of inhaling and exhaling an aerosol produced by an e-cigarette, vape pen, or personal aerosolizer. When the device contains nicotine, the Food and Drug Administration (FDA) lists the product as an electronic nicotine delivery system or ENDS device. Similar electronic devices can be used to vape cannabis extracts. Over the past decade, the vaping market has increased exponentially, raising health concerns over the number of people exposed and a nationwide outbreak of cases of severe, sometimes fatal, lung dysfunction that arose suddenly in otherwise healthy individuals. In this review, we discuss the various vaping technologies, which are remarkably diverse, and summarize the use prevalence in the U.S. over time by youths and adults. We examine the complex chemistry of vape carrier solvents, flavoring chemicals, and transformation products. We review the health effects from epidemiological and laboratory studies and, finally, discuss the proposed mechanisms underlying some of these health effects. We conclude that since much of the research in this area is recent and vaping technologies are dynamic, our understanding of the health effects is insufficient. With the rapid growth of ENDS use, consumers and regulatory bodies need a better understanding of constituent-dependent toxicity to guide product use and regulatory decisions.

PFAS and Dissolved Organic Carbon Enrichment in Surface Water Foams on a Northern U.S. Freshwater Lake.

Information is needed on the concentration of per- and polyfluoroalkyl substances (PFAS) in foams on surface waters impacted by aqueous film-forming foam (AFFF). Nine pairs of foam and underlying bulk water were collected from a single freshwater lake impacted by PFAS and analyzed for PFAS by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF) and for dissolved organic carbon (DOC). The DOC of two foam:bulk water pairs was characterized by 1H NMR. Foams were comprised of 16 PFAS with concentrations as high as 97 000 ng/L (PFOS) along with longer-chain, more hydrophobic PFAS. Only five PFAS (PFOS and shorter chain lengths) were quantified in underlying bulk waters. Enrichment factors (foam:bulk water) ranged from 10 (PFHxA) up to 2830 (PFOS). Foams impacted by AFFF gave the greatest concentrations and number of PFAS classes with PFOS concentrations exceeding the EPA health advisory level (70 ng/L). PFAS concentrations were significantly below published critical micelle concentrations and constituted <0.1% of overall DOC concentrations in foam, indicating that PFAS are a minor fraction of DOC and that DOC likely plays a central role in foam formation. Estimates indicate that foam ingestion is a potentially important route of exposure for children and adults when they are in surface waters where foam is present.