Cao Dunping, Schwichtenberg Trever, Duan Chenyang, Xue Lan, Muensterman Derek, Field Jennifer
Department of Chemistry, Oregon State University, Corvallis, Oregon 97331, United States.
Department of Statistics, Oregon State University, Corvallis, Oregon 97331, United States.
J Am Soc Mass Spectrom. 2023 May 3;34(5):939-947. doi: 10.1021/jasms.3c00019. Epub 2023 Apr 5.
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.
由于可疑的全氟和多氟烷基物质(PFAS)数量不断增加,对复杂混合物中可疑PFAS进行半定量分析具有挑战性。传统的1:1匹配策略需要根据头部基团、氟化链长度和保留时间选择校准物(目标-替代标准对),这既耗时又需要专业知识。不同实验室在选择校准物以估计可疑浓度方面缺乏一致性,使得比较报告的可疑浓度变得困难。在本研究中,采用了一种实用方法,即将50种阴离子型和5种两性离子/阳离子型目标PFAS的面积计数与其各自稳定同位素标记替代物的平均面积进行比值计算,以创建“平均PFAS校准曲线”,用于负离子和正离子模式液相色谱-四极杆飞行时间质谱中检测到的可疑物。校准曲线采用对数-对数和加权线性回归模型进行拟合。对这两种模型在预测目标PFAS浓度时的准确性和预测区间进行了评估。然后使用平均PFAS校准曲线来估计一种特征明确的水成膜泡沫中可疑PFAS的浓度。与对数-对数变换方法相比,加权线性回归使得更多的目标PFAS落在其已知标准值的70-130%范围内,且预测区间更窄。通过加权线性回归和对数-对数变换计算得到的可疑PFAS总浓度与通过1:1匹配策略估计的浓度相差在8%和16%以内。平均PFAS校准曲线可以轻松扩展,并且即使对可疑物结构的置信度较低或未知,也可应用于任何可疑PFAS。