Practical Semiquantification Strategy for Estimating Suspect Per- and Polyfluoroalkyl Substance (PFAS) Concentrations

Area of Science:

• Environmental Chemistry
• Analytical Chemistry
• Mass Spectrometry

Background:

• Semiquantifying per- and polyfluoroalkyl substances (PFAS) in complex mixtures presents significant challenges due to their expanding number.
• Traditional methods rely on time-consuming 1:1 matching strategies, requiring expert knowledge for calibrant selection and leading to inter-laboratory comparison difficulties.

Purpose of the Study:

• To develop a practical and standardized approach for the semiquantitation of suspect PFAS.
• To establish "average PFAS calibration curves" to streamline concentration estimations for a wide range of PFAS.

Main Methods:

• Area counts of target PFAS were ratioed to the average area of stable-isotope labeled surrogates.
• Developed "average PFAS calibration curves" using both log-log and weighted linear regression models.
• Evaluated model accuracy and prediction intervals for target PFAS concentrations.

Main Results:

• Weighted linear regression demonstrated higher accuracy, with more target PFAS falling within 70-130% of their known standard values and narrower prediction intervals compared to log-log transformation.
• Summed suspect PFAS concentrations derived from both regression methods showed good agreement with traditional 1:1 matching strategies (within 8-16% difference).

Conclusions:

• The "average PFAS calibration curve" approach offers a practical, expandable, and robust method for semiquantifying suspect PFAS.
• This method enhances consistency and comparability across laboratories, even for compounds with low structural confidence.