Rapid Characterization of Emerging Per- and Polyfluoroalkyl Substances in Aqueous Film-Forming Foams Using Ion Mobility Spectrometry–Mass Spectrometry

Aqueous film-forming foams (AFFF) are mixtures formulated with numerous hydrocarbon- and fluoro-containing surfactants. AFFF use leads to environmental releases of unknown per- and polyfluoroalkyl substances (PFAS). AFFF composition is seldom disclosed, and their use elicits concerns from both regul...

Full description

Saved in:
Bibliographic Details
Published in:Environmental science & technology 2020-12, Vol.54 (23), p.15024-15034
Main Authors: Luo, Yu-Syuan, Aly, Noor A, McCord, James, Strynar, Mark J, Chiu, Weihsueh A, Dodds, James N, Baker, Erin S, Rusyn, Ivan
Format: Article
Language:English
Subjects:
Algorithms
Contaminants in Aquatic and Terrestrial Environments
Contamination
Data processing
Fluorocarbons - analysis
Foams
Formulations
Health risks
Homology
Ion Mobility Spectrometry
Ionic mobility
Ions
Liquid chromatography
Mass spectrometry
Mass spectroscopy
Mobility
Perfluoroalkyl & polyfluoroalkyl substances
Pollutants
Positive ions
Scientific imaging
Spectroscopy
Surfactants
Tandem Mass Spectrometry
Water
Water Pollutants, Chemical - analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Aqueous film-forming foams (AFFF) are mixtures formulated with numerous hydrocarbon- and fluoro-containing surfactants. AFFF use leads to environmental releases of unknown per- and polyfluoroalkyl substances (PFAS). AFFF composition is seldom disclosed, and their use elicits concerns from both regulatory agencies and the public because PFAS are persistent in the environment and potentially associated with adverse health effects. In this study, we demonstrate the use of coupled liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) to rapidly characterize both known and unknown PFAS in AFFF. Ten AFFF formulations from seven brands were analyzed using LC-IMS-MS in both negative and positive ion modes. Untargeted analysis of the formulations was followed by feature identification of PFAS-like features utilizing database matching, mass defect and homologous series evaluation, and MS/MS fragmentation experiments. Across the tested AFFF formulations, we identified 33 homologous series; only ten of these homologous series have been previously reported. Among tested AFFF, the FireStopper (n = 85) contained the greatest number of PFAS-like features and Phos-Check contained zero. This work demonstrates that LC-IMS-MS-enabled untargeted analysis of complex formulations, followed by feature identification using data-processing algorithms, can be used for rapid exposure characterization of known and putative PFAS during fire suppression-related contamination events.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.0c04798