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Assessment on data processing methods for nontarget identification of per- and polyfluoroalkyl substances using liquid chromatography-high-resolution mass spectrometry

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Evaluates data processing methods for PFAS identification, indicating an optimal approach for environmental analysis.

The aim is to evaluate data processing methods for non-target identification of PFAS using mass spectrometry.
Used ultra-high performance liquid chromatography coupled with an Orbitrap mass spectrometer.
Assessed data processing methods under data-dependent and data-independent acquisition modes.
Compared peak picking capabilities of MS-DIAL and MZmine software.
Evaluated deconvolution performance with MS2Dec and IonDecon algorithms.
Applied methods to analyze electroplating sludge samples for PFAS identification.
MS-DIAL achieved a 100% detection rate for all spiked PFAS samples.
In DDA mode, true positive rate increased from 80% to 100% with rising concentration.
DIA mode maintained a 100% true positive rate across concentrations, but positive predictive value decreased.
Identified 36 PFAS species across 10 classes in electroplating sludge samples.
Combined DDA and DIA data improved PFAS identification efficiency.

ZHANG et al. (2026) studied this question.

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