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

Abstract

Semiquantitation of suspect per-and polyfluoroalkyl substances (PFAS) in complex mixtures is challenging due to the increasing number of suspect PFAS. Traditional 1:1 matching strategies require selecting calibrants (target−surrogate standard pairs) based on head group, fluorinated chain length, and retention time, which is time-consuming and requires expert knowledge. Lack of uniformity in calibrant selection for estimating suspect concentrations among different laboratories makes comparing reported suspect concentrations difficult. In this study, a practical approach whereby the area counts for 50 anionic and 5 zwitterionic/cationic target PFAS were ratioed to the average area of their respective stable-isotope labeled surrogates to create "average PFAS calibration curves" for suspects detected in negative-and positive-ionization mode liquid chromatography quadrupole time-of-flight mass spectrometry. The calibration curves were fitted with log−log and weighted linear regression models. The two models were evaluated for their accuracy and prediction interval in predicting the target PFAS concentrations. The average PFAS calibration curves were then used to estimate the suspect PFAS concentration in a well-characterized aqueous film-forming foam. Weighted linear regression resulted in more target PFAS that fell within 70−130% of their known standard value and narrower prediction intervals than the log−log transformation approach. The summed suspect PFAS concentrations calculated by weighted linear regression and log−log transformation were within 8 and 16% of those estimated by a 1:1 matching strategy. The average PFAS calibration curve can be easily expanded and can be applied to any suspect PFAS even if the confidence in the suspect structure is low or unknown.

Target and Suspect Screening Integrated with Machine Learning to Discover Per- and Polyfluoroalkyl Substance Source Fingerprints

“…Thirty-four of the 50 target PFASs were quantified above the LOQ in at least one of the 92 samples. A total of 188 suspect PFASs from the NIST list were identified with a confidence of Level 4 or higher and semi-quantified in at least one of the 92 samples. PFAS occurrence and concentration data from AFFF-GW, LL, BL, and WWTP samples have been previously reported from sites around the world.…”

“…Details on assigning confidence to suspect matching is provided in the Supporting Information . Suspect concentrations were estimated using an average PFAS calibration curve constructed from the area of target PFASs divided by the average area of the 22 surrogate areas versus target concentration in units of nmoles/L . Suspect concentrations were reported in ng/L after converting from nmoles/L using the suspect molar mass.…”

“…The LOQ for suspects was 5 ng/L, the minimum LOQ for target PFASs. In this manner, 1:1 matching was avoided given the number of suspects detected and treated by a single common calibration curve …”

Analysis of needs for enforcement of PFAS in articles and chemical products

“…To simplify this process, surrogates are often used but there is a lack of uniformity in calibrant selection for estimating suspect concentrations among different laboratories, making comparison of reported suspect concentrations dif icult. In this context, Cao et al (2023) recently proposed a practical approach in which the area counts for 50 anionic and 5 zwitterionic/ cationic target PFAS were ratioed to the average area of their respective stable-isotope labelled surrogates to create "average PFAS calibration curves" for suspects detected in both negative-and positive-electrospray ionization modes. The method was developed on a LC-Q-ToF instrument using data-independent acquisition and applied to a well characterized aqueous ilm forming foam standard sample.…”

Detection, Quantification, and Isomer Differentiation of Per- and Polyfluoroalkyl Substances (PFAS) Using MALDI-TOF with Trapped Ion Mobility

“…Chromatography, high-resolution and tandem MS, and Kendrick Mass Defect (KMD) analysis are among tools that are widely used. 14,24,25 In recent years, ion mobility spectrometry (IMS) has shown unique strength in the analysis of halogenated xenobiotics, including PFAS, due to its capability in separating ions by size, shape and charge state in the gas phase. 26−29 By coupling drift-time ion mobility spectrometry (DTIMS) to LC-MS, Foster et al demonstrated a unique trendline of collision cross section vs m/z for halogenated xenobiotics compared to biological molecules, facilitating the identification of xenobiotics in a complex sample matrix.…”