PFAS ghosts: how to identify, evaluate, and exorcise new and existing analytical interference

Area of Science:

• Environmental Science
• Analytical Chemistry
• Toxicology

Background:

• Growing public awareness of per- and polyfluoroalkyl substances (PFAS) has led to increased monitoring studies globally.
• PFAS are detected in various biological and environmental matrices, necessitating accurate analytical measurements.
• Matrix interferents can falsely appear as PFAS, creating analytical challenges and impacting risk assessments.

Purpose of the Study:

• To establish a publicly accessible dataset of known PFAS analytical interferents.
• To facilitate the expansion of this dataset as new interferents are identified.
• To provide guidance for identifying and eliminating analytical interference in PFAS analyses.

Main Methods:

• Compilation of a comprehensive dataset of identified PFAS analytical interferents.
• Review of existing literature and analytical methodologies for PFAS detection.
• Development of strategies for interference identification and mitigation.

Main Results:

• A foundational dataset of known PFAS analytical interferents has been created.
• The dataset is designed for ongoing expansion as research progresses.
• Recommendations for analytical best practices to address interference are provided.

Conclusions:

• Accurate PFAS measurements are critical for informed decision-making regarding human and environmental health.
• Addressing analytical interference is vital for the reliability of PFAS monitoring studies.
• The developed dataset and guidance will support the scientific community in improving PFAS analysis.