Navigating the Complexities of PFAS Analysis, a Laboratory Perspective

Characterization of Polyfluoroalkyl Substances in the Environment
Oral Presentation

Prepared by J. Thorn1, Z. Willenberg2, D. Schumitz1, S. Schultz1
1 - Battelle, 141 longwater Drive, Suite 202, Norwell, MA, 02368, United States
2 - Battelle, 505 King Ave, Columbus, Ohio, 43201, United States


Contact Information: [email protected]; 781-681-5565


ABSTRACT

The analysis of PFAS continues to be an evolving landscape, with ever changing methods, method quality objectives, and target analyte lists. Beyond these changes, complex sample matrices, often with co-contaminants, requiring rapid turnaround add to the complexity of these analyses.

In an environment driven by commodity analytical work for the lowest cost, how does a laboratory navigate the complexity of PFAS analytical work?

This presentation will cover:
• Background sources of PFAS contamination and the need for trace-level analysis for field samples;
• Detection limits, limits of detection, and limits of quantitation – is there such a thing as “too low”?
• Navigating state level accreditations for unregulated contaminants;
• Certified pre-cleaned bottles and PFAS free water for field work;
• Sample volumes, sample counts, and containers to be requested from field sites;
• Levels of contamination and sample pre-screening, is there a value to pre-screening and does it outweigh the costs?
• Sedimentation levels in non-potable water samples – best practices for handling high solid content waters;
• Availability of published methodology and suitability of methods for QSM Table B-15 analysis;
• Extraction and analysis of complex matrices, including environmental tissues, crops, and other matrices;
• Applying GC/MS criteria to LC/MS/MS technology;
• Final data reports, fitting LC/MS/MS data into a CLP report world.

Analysis of complex matrices for PFAS potentially has many challenges. Awareness of the potential challenges; a solid working partnership between clients, field teams, laboratories, and data users; and frequent communication between these stakeholders will overcome these potential pitfalls and generate usable data for the end users.