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一种用于检测乳制品中传统和新兴的全氟和多氟烷基物质(PFAS)的敏感方法。

A sensitive method for the detection of legacy and emerging per- and polyfluorinated alkyl substances (PFAS) in dairy milk.

机构信息

Graduate School of Oceanography, University of Rhode Island, Narragansett, RI, USA.

出版信息

Anal Bioanal Chem. 2022 Jan;414(3):1235-1243. doi: 10.1007/s00216-021-03575-2. Epub 2021 Aug 5.

Abstract

There is widespread contamination by per- and polyfluoroalkyl substances (PFAS) across the globe, with adverse effects on human and environmental health. For human exposure, drinking water and dietary exposure have been recognized as important PFAS exposure pathway for the general population. Several documented cases of dairy milk contamination by PFAS have raised concerns over this exposure pathway in general. A sensitive method for determination of 27 PFAS in milk was hence modified and applied on raw and processed milk samples from 13 farms across the United States (U.S.). A combination of acid and basic extraction method and ENVI-Carb clean-up achieved recoveries of targeted PFAS between 70 and 141%. The method detection limits (MDL) ranged from 0.8 to 22 ng/L (for 26 PFAS) and 144 ng/L for perfluorobutanoic acid (PFBA). The uniqueness of this method is considered in the targeted screening of a broad range of legacy PFAS, as well as perfluorinated sulfonamide species and fluorotelomer sulfonates. No legacy PFAS were detected in 13 milk samples from regions of concern given local use of biosolids or proximity to fire training areas. Overall, then, the uptake of perfluoroalkyl acids (PFAA) from dairy milk in the U.S. is considered low.

摘要

全球范围内普遍存在全氟和多氟烷基物质(PFAS)的污染,对人类和环境健康造成不良影响。对于人类暴露,饮用水和饮食暴露已被认为是普通人群中 PFAS 的重要暴露途径。一些有记录的牛奶被 PFAS 污染的案例引起了人们对这种暴露途径的关注。因此,对一种测定牛奶中 27 种 PFAS 的敏感方法进行了修改,并应用于来自美国 13 个农场的生奶和加工奶样品。酸碱性提取方法和 ENVI-Carb 净化相结合,实现了目标 PFAS 的回收率在 70%至 141%之间。方法检测限(MDL)范围为 0.8 至 22 纳克/升(26 种 PFAS),以及 144 纳克/升的全氟丁酸(PFBA)。该方法的独特之处在于可以对广泛的传统 PFAS 进行靶向筛选,以及全氟磺酰胺类和氟端基磺酸盐。在有当地使用生物固体或靠近消防训练区的关注地区的 13 个牛奶样本中,未检测到传统 PFAS。总的来说,美国从牛奶中摄取全氟烷基酸(PFAA)的情况被认为很低。

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