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<p>The escalating diversity of per- and polyfluoroalkyl substances (PFAS), arising from both intentional synthesis and inadvertent generation and release, has led to increasingly complex environmental PFAS compositions. In recent years, unknown PFAS have been frequently identified in the environment. However, the structural diversity and lack of corresponding reference standards pose significant challenges for the detection and identification of PFAS. Traditional targeted screening methods are often inadequate for detecting these compounds, making nontargeted analysis (NTA) using high-resolution mass spectrometry (HRMS) essential for identifying unknown or suspected contaminants. Nevertheless, existing NTA techniques still face limitations in comprehensively characterizing the full spectrum of PFAS in the environment. Continuous optimization and development of sample preparation methods, instrumental analytical techniques, data processing algorithms, and software are gradually expanding the coverage of NTA for diverse PFAS. This review summarizes recent advances in HRMS-based NTA methodologies for PFAS, encompassing sample preparation, separation techniques, HRMS instrument and data acquisition modes, PFAS screening strategies, and NTA data processing approaches. Furthermore, the review discusses the current challenges and prospects of PFAS NTA, such as an in-depth exploration of gas chromatography-HRMS (GC-HRMS) applications in NTA, and the utilization of machine learning (ML) models for efficient processing of complex NTA datasets. Addressing these challenges will significantly enhance the accuracy and efficiency of PFAS identification in the environment, providing a scientific basis for the regulation and control of PFAS in the future.</p>

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Advances in Nontargeted Analysis of Per- and Polyfluoroalkyl Substances Based on High-Resolution Mass Spectrometry

  • 期刊论文

  • 发表日期：

    2025年12月3日

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  • Xinyu Wang,
  • Feng Zhang,
  • Xiaodong Wu,
  • Zhengquan Ji,
  • Yali Shi,
  • Yaqi Cai

摘要

The escalating diversity of per- and polyfluoroalkyl substances (PFAS), arising from both intentional synthesis and inadvertent generation and release, has led to increasingly complex environmental PFAS compositions. In recent years, unknown PFAS have been frequently identified in the environment. However, the structural diversity and lack of corresponding reference standards pose significant challenges for the detection and identification of PFAS. Traditional targeted screening methods are often inadequate for detecting these compounds, making nontargeted analysis (NTA) using high-resolution mass spectrometry (HRMS) essential for identifying unknown or suspected contaminants. Nevertheless, existing NTA techniques still face limitations in comprehensively characterizing the full spectrum of PFAS in the environment. Continuous optimization and development of sample preparation methods, instrumental analytical techniques, data processing algorithms, and software are gradually expanding the coverage of NTA for diverse PFAS. This review summarizes recent advances in HRMS-based NTA methodologies for PFAS, encompassing sample preparation, separation techniques, HRMS instrument and data acquisition modes, PFAS screening strategies, and NTA data processing approaches. Furthermore, the review discusses the current challenges and prospects of PFAS NTA, such as an in-depth exploration of gas chromatography-HRMS (GC-HRMS) applications in NTA, and the utilization of machine learning (ML) models for efficient processing of complex NTA datasets. Addressing these challenges will significantly enhance the accuracy and efficiency of PFAS identification in the environment, providing a scientific basis for the regulation and control of PFAS in the future.