Comparison of automated gas-assisted dynamic accelerated solvent extraction (GA-dASE) workflow and EPA method 1633A for PFAS analysis in soil, biosolids, and tissues

Significance of the topic

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants of growing regulatory and public-health concern. Accurate, reproducible quantitation of PFAS in complex solid and semi-solid matrices (soils, sediments, biosolids, tissues) is critical for site assessment, remediation decisions, and compliance monitoring. Standard methods such as US EPA Method 1633A provide validated workflows, but sample preparation for these matrices is labor-intensive and a common source of variability. Streamlined, automated extraction and cleanup approaches that maintain analytical performance while increasing throughput and reducing manual handling are therefore highly valuable to laboratories performing routine PFAS analyses.

Objectives and overview of the study

• Compare an automated gas-assisted dynamic accelerated solvent extraction (GA-dASE) workflow implemented on the Thermo Fisher Extreva platform against the reference US EPA Method 1633A for PFAS analysis in soils, biosolids, sediments, and tissues.
• Evaluate analytical performance metrics including analyte concentrations, percent recovery relative to EPA 1633A, relative standard deviation (RSD), internal standard behavior, matrix effects, and pH sensitivity for labile PFAS species.
• Assess operational advantages such as reduced manual handling, elimination of evaporation steps, and improved sample throughput using automated GCB/WAX SPE cleanup integrated with the Extreva ASE system.

Methodology and used instrumentation

• Sample matrices: AFFF-contaminated field soils and spiked soils, biosolids (native and spiked), sediments (including NIST SRM 1936), and fish tissues with variable fat content (including NIST SRM 1947).
• Extraction: Automated GA-dASE on the Thermo Fisher Extreva ASE platform, leveraging gas-assisted dynamic extraction chemistry similar to that used in EPA 1633A but implemented to avoid offline evaporation and minimize sample transfers.
• Cleanup: Automated graphitized carbon black (GCB) and weak anion exchange (WAX) solid-phase extraction (SPE) performed in-line following extraction to remove matrix interferences prior to analysis.
• Analysis: Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) for quantitation of a suite of perfluoroalkyl acids, sulfonates, fluorotelomer sulfonates, precursors, and other target PFAS analytes. Internal standards were used according to standard quantitative practice.
• Comparative reference: Results benchmarked against manual EPA Method 1633A sample preparation and LC-MS/MS analysis.

Main results and discussion

• Overall analytical agreement: The GA-dASE workflow produced PFAS concentrations generally comparable to EPA 1633A. For an AFFF-contaminated soil example, GA-dASE measured concentrations ranged from ~74% to 91% of values obtained with EPA 1633A across the reported analytes, demonstrating good concordance for most compounds.
• Precision: RSDs for GA-dASE were typically acceptable for routine analysis (commonly single-digit to low double-digit percent), although variability increased slightly for some low-level or trace analytes compared with the manual method.
• Recovery patterns: Relative recoveries versus EPA 1633A varied by analyte and matrix. Long-chain PFAS and major analytes such as PFOS and PFOA showed consistent detection, while certain short-chain or labile precursors returned lower recoveries without specific extract modification.
• pH effect: Adjusting extract pH to neutral (pH 6–7) improved recovery for pH-sensitive analytes, notably 3:3 FTCA, PFMPA, and M4PFBA, indicating that pH control during extraction/cleanup is important for preserving these species.
• Matrix-dependent cleanup needs: High-lipid tissues required more extensive cleanup to avoid matrix effects in LC-MS/MS; automated GCB/WAX SPE reduced interferences but additional cleanup steps or method tailoring may be necessary for heavily fatty samples.
• Standard reference materials: Analysis of NIST SRMs (1936 sediment and 1947 tissue) demonstrated that the automated workflow could achieve comparable results to EPA 1633A and align with certified values (e.g., PFOS in SRM 1947), supporting method robustness for regulated analytes.

Benefits and practical applications of the GA-dASE method

• Operational efficiency: Automation reduces manual sample transfers, filtrations, and evaporation steps, lowering hands-on time and potential for cross-contamination or analyst-to-analyst variability.
• Throughput and reproducibility: Integrated automated extraction and cleanup increase sample throughput while maintaining reproducible instrument-ready extracts suitable for LC-MS/MS.
• Compatibility with regulatory workflows: The chemistry and target analyte coverage were designed to be compatible with EPA Method 1633A, enabling laboratories to adopt the automated workflow without sacrificing regulatory comparability.
• Adaptability: The approach can be applied across diverse solid and semi-solid matrices (soils, biosolids, sediments, tissues) with adjustments (pH control, enhanced cleanup) to optimize recoveries for specific analytes or matrix types.

Future trends and potential applications

• Automation and method consolidation: Continued adoption of integrated automated extraction/cleanup platforms will likely expand for PFAS and other emerging contaminants, driven by the need for higher throughput and consistent data for regulatory actions.
• Method refinement for precursors and short-chain PFAS: Improved strategies for stabilizing and recovering labile precursors (pH control, tailored sorbents) will increase confidence in measuring broader PFAS suites.
• Enhanced lipid removal workflows: For high-fat tissues, development of targeted lipid-removal modules compatible with automated platforms will be important to reduce matrix effects and lower detection limits.
• Interoperability with high-resolution MS: Integrating automated sample prep with high-resolution mass spectrometry will support non-target screening and suspect screening workflows alongside targeted quantitation.

Conclusions

• The automated GA-dASE (Extreva) workflow with automated GCB/WAX SPE cleanup demonstrated comparable analytical performance to EPA Method 1633A for most PFAS analytes across soils, biosolids, sediments, and tissue matrices while reducing manual handling and eliminating evaporation steps.
• Recoveries relative to EPA 1633A typically ranged from roughly 74% to 91% for the tested analytes in an AFFF-contaminated soil example, with precision generally acceptable for routine monitoring purposes.
• Controlling extract pH to near-neutral improves recovery of pH-sensitive PFAS species, and enhanced cleanup may be required for lipid-rich tissues.
• Overall, the GA-dASE automated workflow offers a practical, scalable alternative for laboratories seeking to increase throughput and reduce variability without sacrificing compatibility with established regulatory methods.

References

• Bera G., Gomez G., Liu Y., Thermo Fisher Scientific. Comparison of automated GA-dASE workflow and EPA Method 1633A for PFAS analysis in soil, biosolids, and tissues. Thermo Fisher Scientific application note, 2026.
• US EPA. Method 1633A: Determination of Per- and Polyfluoroalkyl Substances (PFAS) in Drinking Water, Wastewater and Solid Matrices by LC-MS/MS. U.S. Environmental Protection Agency.
• NIST Standard Reference Materials: SRM 1936 (sediment) and SRM 1947 (fish tissue) used as quality-control benchmarks in the study.