UTILIZING ION MOBILITY TO ENHANCE TARGETED AND NON-TARGETED ANALYSIS OF PFAS FROM ENVIRONMENTAL SAMPLES COLLECTED AT A SKI RESORT

Significance of the Topic

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals renowned for their hydrophobic and non-stick properties. Despite regulatory efforts to limit their use, PFAS persist in the environment, leading to long-term contamination concerns. Ski resorts, where PFAS-containing wax is applied to equipment, represent a potential source of local environmental release. Monitoring and characterizing both known and emerging PFAS at such sites are critical for risk assessment and remediation strategies.

Study Objectives and Overview

This work aimed to evaluate the presence of legacy and novel PFAS in environmental water samples collected at a New Hampshire ski resort. By combining high-resolution mass spectrometry (HRMS) with ion mobility spectrometry (IMS), the study sought to enhance both targeted screening of a known PFAS library and non-targeted discovery of unknown PFAS structures.

Methodology and Instrumentation

Sample Preparation:

• Collection: Surface and retention pond waters collected at multiple ski area locations.
• Extraction: Acidification followed by weak anion exchange solid phase extraction using Oasis™ WAX cartridges.

Analytical Platform:

• Separation: ACQUITY UPLC™ BEH™ C18 column (2.1×100 mm, 1.7 μm), 35 °C; mobile phases water with 2 mM ammonium acetate and methanol.
• Mass Spectrometry: SELECT SERIES™ Cyclic™ IMS QTOF with ESI source; DIA HDMSE acquisition; mass range m/z 50–2000; resolution ~50,000 FWHM.
• Ion Mobility: Cyclic IMS cell, resolution ~65 Ω/ΔΩ to differentiate fluorinated species by collision cross section (CCS) values.

Key Results and Discussion

Targeted Screening:
The HRMS data were matched against an internal library of 30 PFAS standards. Accurate mass (<5 ppm), retention time, fragmentation patterns, and observed CCS values provided confirmation of legacy PFAS across samples.

Non-Targeted Screening:
An IMS-based drift time filter was applied to isolate candidate PFAS peaks from thousands of detected features. Two novel series of perfluorinated compounds were tentatively identified:

• H-substituted perfluorocarboxylic acids (C9–C24) detected in multiple samples.
• Perfluorinated dioic acids (C10–C17) observed uniquely in a snowmaking retention pond sample.

Structural proposals were based on elemental composition, collision-induced dissociation spectra, and CCS trends relative to non-fluorinated analogs.

Confirmation of Tentative Identifications:
Authentic standards for 9H-perfluorononanoic acid and perfluorodecanedioic acid were analyzed. Matching retention times, MS/MS fragmentation, and drift profiles validated the proposed structures in environmental samples.

Benefits and Practical Applications

Integrating IMS with HRMS improves spectral clarity by filtering interferences and highlights fluorinated signatures. This approach enables both reliable detection of regulated PFAS and discovery of previously uncharacterized analogs, advancing environmental monitoring protocols at recreational and industrial sites.

Future Trends and Opportunities

Continued refinement of ion mobility filters and expansion of CCS libraries will enhance non-targeted PFAS identification. Development of isotopically labeled standards and machine-learning models for drift time prediction may further streamline analysis. Broader application to soils, biota, and indoor dust can extend risk assessments across environmental matrices.

Conclusion

The combination of cyclic IMS and HRMS has proven effective for comprehensive PFAS screening in complex environmental samples. Targeted methods confirmed known contaminants, while non-targeted workflows revealed emerging perfluorinated species. These insights support more informed management of PFAS pollution at ski resorts and similar locations.

References

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