Christopher P. Higgins

The South Platte River is a major Colorado waterway and effluent-dominated river receiving inputs from wastewater treatment plants and tributaries. Among the contaminants of concern, poly- and perfluoroalkyl substances (PFAS) have gained increasing attention due to their persistence and widespread occurrence in impacted rivers. This study investigates the occurrence, composition, and spatial variability of PFAS and select constituents in the South Platte River. Samples were collected (two campaigns) from multiple locations along the river (upstream, downstream, side streams, and major wastewater discharge points) and analyzed for both regulated and unregulated PFAS, major ions, nitrogen species, total organic carbon, and sucralose. Results indicate that effluents from wastewater treatment facilities are important contributors to nutrient loading and the primary source of sucralose in the river. However, total detected PFAS concentrations in several natural tributaries exceeded those in all effluents, highlighting the substantial role of tributary inputs in watershed PFAS loading and variability. Moreover, river foam samples contained PFAS concentrations of ∼25,000 ng/L, substantially higher than surrounding waters, highlighting the potential for foam-mediated contaminant transport. Results indicate that while sucralose effectively traces municipal wastewater inputs, its lack of correlation with total detected PFAS concentrations limits its use as a standalone tool for PFAS source attribution in complex watersheds.

The widespread use of aqueous film–forming foam (AFFF) for firefighting and firefighter training has led to extensive per- and polyfluoroalkyl substance (PFAS) contamination in the environment, yet the mass budget for PFASs in AFFF-impacted groundwater across diverse sites remains uncertain. Here, we integrated targeted analysis, high-resolution mass spectrometry (HRMS)-based suspect screening, extractable organofluorine (EOF), and the total oxidizable precursor (TOP) assay to evaluate total organic fluorine in 23 groundwater samples collected from 12 AFFF-impacted sites. Across all samples, total targeted PFAS concentrations ranged from 0.35 to 980 μg/L, and the highest summed PFAS concentrations, including suspect PFASs, reached 1,000 μg/L. EOF levels ranged from 5.9 to 670 μg F/L. Targeted PFASs explained 0.82–93% of the EOF (median: 44%), whereas targeted and suspect PFASs contributed 0.82–100% (median: 50%). Targeted PFASs together with oxidizable precursors quantified by the TOP assay accounted for 5.7–100% of the EOF (median: 54%). Importantly, the majority of EOF (>50%) could be explained by targeted and suspect PFASs or precursors from the TOP assay in groundwater where EOF concentrations were high (e.g., ≥50 μg F/L). These results demonstrate that combining suspect screening, EOF, and the TOP assay provides a more comprehensive assessment of PFAS contamination in AFFF-impacted groundwater, while the unresolved organofluorine indicates the presence of unidentified fluorinated compounds not captured by current workflows.

Per- and polyfluoroalkyl substances (PFAS) are synthetic compounds found widely in the environment, posing concerns due to their persistence, recalcitrant nature, and limited regulatory standards. Recently, foam fractionation (FF) has attracted interest for PFAS removal by concentrating contaminants at air–water interfaces within the generated foam. This study evaluates the effectiveness of FF for the removal of PFAS from waters impacted by aqueous film-forming foam (AFFF). The performance of conventional bubble-induced (BI) FF and an innovative shear-induced (SI) FF system was assessed, and 12 different single-stage FF scenarios (2 systems, 2 water types, and 3 surfactant dosages) revealed a direct correlation between removal efficiency and PFAS chain length, surfactant concentration, and aeration/mixing duration. Results also confirmed higher removals for sulfonate PFAS compared to carboxylates. While both systems achieved high removal efficiencies (>90% for long-chain PFAS with 6 and 9 mg/L CTAB), the SI system reached similar removal levels in approximately 80% less time while exhibiting higher velocity gradients, energy consumption, and foam generation across all cases. Moreover, SI-FF’s faster operation and higher foamate generation suggest its suitability for final stage fractionation, which was tested and shown to substantially outperform BI-FF in a dual-stage system.

Hydrothermal alkaline treatment (HALT) is an innovative approach that was developed for the destruction of per- and polyfluoroalkyl substances (PFAS). While HALT has been shown to effectively destroy a wide range of PFAS detected in various sample matrices, a comprehensive understanding of the controlling reaction mechanisms and transformation pathways remains limited. Herein, we selected trifluoromethanesulfonate (TFMS), the shortest-chain and likely one of the most recalcitrant PFAS reported to date, to probe degradation mechanisms and identify transformation products. The results indicate that HALT of TFMS proceeds via general nucleophilic substitution and base-promoted pathways, leading to 65.7% mineralization of the parent compound after a 180 min reaction of 0.1 M TFMS at 350 °C in 1 M NaOH. For the degraded TFMS, approximately 100% of fluorine and sulfur were converted to fluoride and sulfate, respectively, while carbon was distributed mainly as carbonate (95%) and formate (5%), along with the production of hydrogen. These findings are supported by both experimental and computational evidence. Hydroxide plays dual roles by initiating the reaction as the nucleophile and promoting subsequent steps by maintaining strongly basic conditions. The initial degradation step is rate-determining, with an estimated energy barrier of 27.8 kcal/mol. Similar mechanisms are proposed for reactions of longer-chain perfluoroalkyl sulfonic acids (PFSAs). Finally, the key factors governing PFSA reactivity across chain lengths from C1 to C8 were identified as reaction temperature, nucleophile type and concentration, and reaction time. This study addresses a critical knowledge gap in PFAS hydrothermal reactions and further establishes HALT as an effective technology for PFAS destruction and defluorination.

This multisite study analyzed depth-discrete soil samples in 12 cores (≤2 m from the ground surface) from 10 aqueous film-forming foam (AFFF)-impacted U.S. Department of Defense installations. A broad suite of per- and polyfluoroalkyl substances (PFASs) were analyzed using extraction protocols designed for source-zone soils and liquid chromatography-high resolution mass spectrometry (LC-HRMS) with targeted and semiquantitative workflows. Across all samples, 162 PFASs spanning 50 classes were identified, with both electrochemical fluorination (ECF)- and fluorotelomer (FT)-derived signatures present at nearly all sites. Class-level detection frequency analysis showed that shallow intervals (down to 30 cm below ground surface) captured most class diversity at the studied sites. Regarding total PFAS mass within a soil core, precursors frequently dominated, though several cores were perfluoroalkyl acid (PFAA)-dominated. These data indicate that reliance on the Environmental Protection Agency (EPA) Method 1633 target list alone substantially underestimated precursor mass in all 12 studied cores. Vertical profiles of PFAAs and precursors showed varying trends and correlations in concentration with depth, suggesting site-specific transport and transformation phenomena. The results of this study point toward several polyfluoroalkyl substances that may be considered for prompt investigation while also highlighting a need for detailed characterizations of diverse AFFF-impacted sites.

Perfluoroalkyl sulfonamides (FASAs) have been detected in aqueous film-forming foams (AFFF), municipal wastewater, and consumer products, among others. Although the compounds can be quantified directly by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS–MS), methods that are frequently used to measure poly- and perfluoroalkyl substances (PFASs) for which standards are not available, like the total oxidizable precursor (TOP) assay, 19F-NMR and nontarget analysis often employ solid-phase extraction followed by elution in a polar organic solvent, such as methanol. Volatilization of FASAs during open blowdown of polar organic solvent extracts from soil, sediment, or aqueous samples leads to underestimation of PFAS concentrations. To assess the importance of this loss mechanism, we measured recovery of three FASAs under conditions relevant to environmental analysis. Recoveries of FASAs and other neutral PFAS, including FASAAs and FTCAs, from methanol during the nitrogen blowdown step decreased as analyte concentrations decreased, with recoveries of less than 1% at 2 μg/L (i.e., a concentration corresponding to about 4 ng/L in water samples prior to solid-phase extraction). The addition of 10 mM NaOH prior to the blowdown step improved recoveries to greater than 80% for all FASAs. NaOH addition prior to blowdown also resulted in an approximately 40% increase in the concentrations of precursors detected in diluted AFFF as measured with the total oxidizable precursor (TOP) assay. The increased concentrations could not be explained by analytes for which analytical standards were available. These findings highlight that volatilization during solvent evaporation can be a significant source of analytical bias for a broader class of neutral PFAS, with FASAs serving as an important example.

Anthropogenic chemicals and their transformation products are increasingly found in the environment, with persistence being a major driver of chemical risk. Methods for predicting biotransformation products and dissipation kinetics are needed to help regulators identify potentially persistent chemicals and prevent their release to the market and eventually to the environment. Leveraging machine learning and artificial intelligence is a promising avenue to tackle this problem. However, predictive models are only as good as the data used to train them, calling for large, high-quality data sets of biotransformation pathways and kinetics, which are currently lacking. The objectives of this Global Perspective are to (i) emphasize the importance of effectively communicating biotransformation data on chemical contaminants in the environment, (ii) describe specific components of reporting biotransformation pathways in a findable, accessible, interoperable, and reusable (FAIR) format, and (iii) provide a standardized tool for researchers to use for reporting their biotransformation data, with the intent to boost the quality and quantity of available biotransformation data. We demonstrate the application of our reporting tool for the case of perfluoroalkyl and polyfluoroalkyl substances (PFASs) as a means to develop a PFAS biotransformation database, thereby illustrating how the research community could profit from standard biotransformation data reporting.

The objective of this study was to identify chemical constituents as markers of six per- and polyfluoroalkyl substance (PFAS) sources including aqueous film-forming foam-impacted groundwater, landfill leachate, biosolids leachate, municipal wastewater treatment plant effluent, and wastewater effluents from the pulp and paper and power generation industries. Previous chemical fingerprinting methods relying on target and suspect PFASs alone have been unable to differentiate PFAS sources containing complex target and suspect PFAS profiles. Here, we demonstrate that high-resolution mass spectral acquisitions from six distinct PFAS sources can be processed by means of an integrated nontarget analysis (NTA) and machine learning (ML) classification-based approach to improve source classification. NTA was conducted from negative- and positive-mode acquisitions, resulting in 21,815 chemical features from 92 samples and 114,660 chemical features from 88 samples, respectively. The inclusion of non-PFAS markers such as preservatives, pesticides, pharmaceuticals, manufacturing intermediates, spectroscopy materials, fatty acids, metabolites, and plant-derived chemicals substantially enhanced the classification performance compared to PFAS-only classifiers. This study significantly advances PFAS forensic capabilities by offering a practical framework for source differentiation and providing critical tools for environmental monitoring and remediation efforts.