
Pittcon 2026: Jennifer Field on PFAS Environmental Forensics, Part II
Key Takeaways
- Legacy AFFF discharges remain a dominant PFAS source, yet formulation evolution over 20–30 years is insufficiently characterized across manufacturers and chemistry platforms.
- Archived AFFF profiling uses ¹⁹F/¹H NMR to quantify total organic fluorine/fluoride and differentiate electrofluorination-derived products from fluorotelomer-based formulations.
At Pittcon 2026, Jennifer Field of Oregon State University sat down with LCGC International to discuss her laboratory's forensic approach to tracing PFAS sources in watersheds.
At Pittcon 2026 in San Antonio, Texas, Jennifer Field, a professor in the Department of Environmental and Molecular Toxicology at Oregon State University, delivered a presentation as part of the symposium on Integrated Nontarget Analysis Workflows: From Environmental Monitoring to Human Exposure Assessment.
Field's talk, titled "Advancing the Environmental Forensics of Per- and Polyfluoroalkyl Substances (PFAS) Through Non-Target Workflows," was delivered on Sunday, March 8th.1 In her presentation, Field addressed the challenge of understanding the sources of PFAS in watersheds—a top priority given the pervasive nature of PFAS contamination nationally and internationally. Aqueous film-forming foams (AFFFs) remain a major source of PFAS that were deliberately discharged to the environment during firefighter training practices and emergencies. However, it has been 20 to 30 years since the discharge of AFFF was largely curtailed by municipal, state, and federal entities, and there remains a limited amount of information on how the fluorinated and non-fluorinated composition of AFFF has changed over time, between formulation types, and among manufacturers.
To address this, Field's group is characterizing an archived collection of over 200 AFFFs using ¹⁹F and ¹H nuclear magnetic resonance (NMR) for total organic fluorine and fluoride, and for differentiating electrofluorination from fluorotelomer-based formulations. A combination of liquid chromatography (LC) and gas chromatography (GC) coupled with high resolution mass spectrometry (HRMS) is being used to discern trends in precursor concentrations and composition as a function of time. Advanced statistical tools and machine learning approaches are being used to identify diagnostic features, track temporal trends, and differentiate AFFF types and manufacturers.2,3
This work is central to the broader mission of the Field Laboratory. The laboratory focuses on creating and applying analytical methodology to quantify PFAS occurrence, fate, and transport in environmental and engineered systems, with projects covering PFAS in municipal and industrial wastewaters, landfill leachates, and AFFF-impacted waters—including surface water and groundwater—for the purpose of source apportionment. Field is considered a pioneer in the area of PFAS occurrence and behavior, with a long-standing focus on groundwater contaminated by firefighting foams and PFAS in municipal wastewater treatment systems and landfills.
On the question of her forensic framework for attributing PFAS sources in watersheds, Field was candid about where the science currently stands. "Our work is the first step toward source apportionment in watersheds," she told LCGC International. "We have characterized and fingerprinted sources, but the next steps need to include the impact of dilution, transformation, and transport, and how they alter the source fingerprints.”
In part II of our conversation with Field, she discusses the partitioning behavior of PFAS, the QA/QC challenges involved in ensuring comparability across complex environmental matrices, and how to translate these findings into practical guidance for utilities and regulators.
References
- Field, J. Advancing the Environmental Forensics of Per- and Polyfluoroalkyl Substances (PFAS) Through NonTarget Workflows. Presented at Pittcon 2026, in San Antonio, Texas. Available at:
https://app.swapcard.com/event/pittcon-2026/planning/UGxhbm5pbmdfNDMwMzQzNw== - Joseph, N. T.; Droz, B.; Schwichtenberg T.; et al. Discovery of Comprehensive Sets of Chemical Constituents as Markers of PFAS Sources Through a Nontarget Screening and Machine Learning Approach. Environ Sci Technol 2025, 59, 22852–22865. DOI: 10.1021/acs.est.5c07560
- Joseph, N. T.; Schwichtenberg T.; Cao, D.; et al. Target and Suspect Screening Integrated with Machine Learning to Discover Per- and Polyfluoroalkyl Substance Source Fingerprints. Environ Sci Technol 2023, 57, 14351–14362. DOI: 10.1021/acs.est.3c03770




