Identification of Known and Novel PFAS in Aqueous Film-Forming Foam (AFFF) by Non-targeted Analysis with High Resolution Mass Spectrometry, Ion Mobility, and Pattern Analysis

Emerging Environmental Applications for High Resolution Mass Spectrometry
Oral Presentation

Prepared by S. Dowd1, N. Meruva1, J. Goshawk2, R. Mortishire-Smith2, A. Tudor3
1 - Waters Corporation, 34 Maple Street, Milford, MA, 01757, United States
2 - Waters Corporation, Stamford Ave, Wilmslow, , United Kingdom
3 - Waters Corporation, Stamford Avenue, Wilmslow, , United Kingdom


Contact Information: [email protected]; 978-810-2891

ABSTRACT

Non-targeted analysis (NTA) with high-resolution mass spectrometry is a powerful approach for detecting known and unknown compounds in food and environmental samples. A major challenge with NTA is the vast amount of data produced and finding the molecules of interest among thousands of detected peaks is a monumental task. To address this challenge particularly for environmental pollutants, like per-and polyfluoroalkyl substances (PFAS), data reduction tools that take advantage of the mass spectral properties of PFAS can enhance their detection and identification. The Pattern Analysis Application, part of the waters_connect™ software platform, can be used to discriminate the detected compounds which are most likely to be PFAS from other naturally occurring compounds. To demonstrate the power of this tool for discovering new PFAS in a complex sample, NIST SRM 8690 PFAS in Aqueous-Film-Forming Foams Formulation I was analyzed with HRMS coupled with liquid chromatography and ion mobility separation (IMS) on the SELECT SERIES™ Cyclic™ IMS mass spectrometer (Waters Corporation). Detected peaks were first compared to a PFAS mass spectral library for identification. The reference material does contain several known PFAS and those along with a few additional compounds were identified. The sample also contained an additional >10,000 detected components that did not match the library. Flagging in the Pattern Analysis Application highlighted the components most likely to be PFAS and led to the identification of nine additional homologue series, three of which were not previously reported.