Moving beyond monitoring legacy per and polyfluoroalkyl substances PFAS screening strategies for the growing list

Importance of the topic

PFAS are persistent contaminants that accumulate in the environment and pose challenges for remediation. Traditional analytical methods target a limited set of end-product compounds. Monitoring precursor molecules and degradation by-products is essential for understanding environmental fate, guiding treatment strategies and protecting human health.

Study objectives and overview

The study demonstrates a unified workflow combining targeted quantitation of approximately 20 PFAS with untargeted suspect screening in a single LC Q-TOF analysis. The approach is applied to environmental water samples to detect both regulated legacy PFAS and emerging compounds from a broad suspect database.

Methodology

The workflow was designed for comprehensive PFAS coverage through simple sample treatment and high resolution data acquisition.

Sample preparation

• Dilution of 5 mL water samples with 5 mL methanol
• Filtration using 0.45 µm nylon discs
• Acidification with acetic acid before injection

Data acquisition

• LC separation on a C18 Poroshell column with a water–acetonitrile gradient
• AllIons MS/MS acquisition on a high resolution Q-TOF
• Simultaneous collection of precursor ions for quantitation and fragment spectra for confirmation

Used instrumentation

Key instrument components and settings

• High speed pump: Agilent 7120A, 0.4 mL/min, gradient up to 97 % B
• Multisampler: Agilent 7167B with seat-back flush and multiwash
• Column thermostat: Agilent 7116B at 30 °C
• Column: Agilent InfinityLab Poroshell HPH-C18 2.1×100 mm, 1.9 µm
• Mass spectrometer: Agilent 6546 LC/Q-TOF in negative ion mode, 50–1100 m/z, collision energies 0, 10, 20 V

Main results and discussion

The LC/Q-TOF method achieved quantitation limits close to those of conventional triple quadrupole systems. Chromatographic separation of 22 PFAS standards produced sharp, well-resolved peaks and linear calibration down to low ppt levels. Retention time prediction models were built by correlating literature RT data and physiochemical descriptors such as LogP, LogS and CF2 count. A suspect screening database derived from the US EPA PFAS inventory was used to identify putative emerging PFAS. In a wastewater sample, perfluoro(2-ethoxyethane) sulfonic acid was detected based on accurate mass, predicted RT, isotope pattern and MS/MS fragments. The untargeted data acquisition allows retrospective analysis as new PFAS structures are discovered.

Benefits and practical applications

• Combined targeted quantitation and broad suspect screening in a single run
• Extended coverage of both legacy and emerging PFAS without requiring standards for every compound
• Accelerated data processing and confirmation through high resolution accurate mass and fragment spectra
• Enhanced decision support for environmental remediation and regulatory compliance

Future trends and opportunities

Expansion of comprehensive PFAS spectral libraries and suspect databases will further improve screening capabilities. Advanced retention time prediction algorithms and machine learning approaches can increase confidence in identifications. Integration of additional MSn fragmentation data and harmonized global standards will support more robust environmental monitoring and risk assessment.

Conclusion

This work demonstrates the power of high resolution LC/Q-TOF workflows for simultaneous targeted PFAS quantitation and untargeted suspect screening. The approach provides near-triple quadrupole sensitivity while enabling discovery of novel PFAS compounds, offering a versatile tool for environmental analysis and monitoring programs.

References

1. Zweigenbaum J and Zhao H, Agilent Technologies, inc 5994-0678EN, 2019
2. Agilent SureMass Document 5991-8048EN, 2017
3. Coggan TL et al., Anal Bioanal Chem, 2019
4. Mansouri K et al., J Cheminform, 2018
5. US EPA PFAS Inventory List, EPA CompTox Dashboard