Analysis of PFAS and Other Environmental Contaminants in Soil and Oat Plants Using High Resolution GC/MS

Importance of the Topic

Per- and polyfluoroalkyl substances (PFAS) are highly persistent synthetic pollutants that accumulate in soil and biota, posing risks to groundwater and ecosystems. Alongside other legacy contaminants such as pesticides, PAHs, PCBs and flame retardants, they require sensitive, high-throughput analytical workflows to assess environmental fate and transport.

Objectives and Study Overview

The study aimed to develop and evaluate extraction and GC/Q-TOF screening approaches for both target and nontarget analysis of PFAS and a broad range of environmental contaminants in soil and oat plant samples collected from biosolid-amended and organic fields.

Methodology and Instrumentation

• Sampling scheme: Soil and oat plants were obtained from two biosolid-treated fields (F1, F2) at preapplication (PreA) and harvest, plus an organic field treated with compost and compost + lime.
• Extraction strategies: Liquid DCM extraction for GC injections; headspace solid-phase microextraction (HS-SPME) for volatile analytes.
• Screening workflows: Targeted PFAS screening using an Agilent PFAS PCDL (>150 EI spectra with RTs and RIs) and nontarget analysis via deconvolution and NIST23 library searches.

Used Instrumentation

• Gas chromatograph: Agilent 8890 GC.
• High-resolution mass spectrometer: Agilent 7250 Q-TOF.
• SPME autosampler: Agilent PAL 3 CTC; fiber: 80 µm DVB/CWR/PDMS; conditioning at 300 °C.
• Columns: DB-5MS UI (30 m×0.25 mm×0.25 µm) and DB-624 UI (30 m×0.25 mm×1.4 µm).
• Acquisition: Electron ionization at 70 eV, mass range m/z 50-1200, spectral rate 5 Hz.

Main Results and Discussion

• SPME fiber evaluation: DVB/CWR/PDMS delivered the highest number of identifiable components (~683 peaks) and hits (~570) in soil headspace extracts.
• Volatile PFAS detection: HS-SPME enabled identification of compounds such as ethyl perfluorobutyl ether, 6:1 and 6:2 fluorotelomer alcohols, and N-methyl perfluorooctanesulfonamide at pg-level on-column.
• Targeted vs nontargeted PFAS screening: Both suspect screening with PFAS PCDL and high-resolution deconvolution detected the same suite of abundant PFAS in soil and plant matrices.
• Nontarget contaminant profiling: PCBs (e.g., nonachlor isomers), PBDEs (including BDE-47 in oat samples), PAHs (phenanthrene, fluoranthene), ~50 pesticides, and various flame retardants were reliably detected using combined suspect and unknown analysis workflows.

Benefits and Practical Applications

• The integrated GC/Q-TOF workflow enables simultaneous, high-confidence analysis of dozens of PFAS and hundreds of other organic pollutants, supporting environmental monitoring and risk assessment.
• HS-SPME reduces solvent consumption and enhances sensitivity for volatile PFAS, while the PFAS PCDL streamlines target screening.

Future Trends and Potential Applications

• Expansion of accurate mass libraries and machine learning–driven deconvolution to capture emerging PFAS and transformation products.
• Integration of LC/GC hybrid HRMS workflows for comprehensive PFAS speciation.
• Development of portable GC/MS platforms for on-site field screening and rapid decision-making.

Conclusion

The combination of optimized HS-SPME, DCM extraction, high-resolution GC/Q-TOF acquisition, and both suspect and nontarget screening provides a robust, sensitive platform for comprehensive analysis of PFAS and co-occurring environmental contaminants in soil and plants.