Comparison of High-Resolution Data Dependent MSMS Strategies for Best Precursor Coverage of Aqueous Film Forming Foam Formulations

Aqueous film forming foam (AFFF) is an effective fire suppressant for petroleum-based fires. Foams are primarily composed of complex mixtures of per- and polyfluorinated substances (PFAS), but the exact composition is protected business information. Identification of PFAS using High–resolution mass spectrometry (HR-MS) only utilizes the accurate mass and isotope pattern of the molecular ion and is not robust as formulas do not provide structural information.

Fragment ions from MSMS spectra can greatly improve identification confidence with software tools such as Fluoromatch. Data dependent acquisition (DDA) is a common tool used to acquire MSMS spectra when the composition is unknown.

In this study, three approaches based on DDA acquisition for the MSMS fragmentation of fluorinated compounds were optimized and compared.

Presenter: Emily Parry, PhD (LC/MS Applications Scientist, Agilent Technologies, Inc.)

Emily Parry received her PhD degree in Environmental Chemistry from the University of California, Davis. She joined Agilent after completing her postdoctoral work at the Environmental Protection Agency (EPA). Her specialty is method development and measurement of emerging contaminants.