Automated derivatization and sample preparation protocol for ultrashort-chain PFCAs of water samples for GC-MS/MS detection
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Author (Corporation)
Publication date
26.08.2026
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01A - Journal article
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Green Analytical Chemistry
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Volume
19
Issue / Number
Pages / Duration
100385
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Elsevier
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Abstract
This study presents a robust and largely automated workflow for the determination of ultra short-chain perfluorocarboxylic acids (PFCAs) in water by GC–MS/MS following in-vial derivatization with diphenyl diazomethane (DDM). The method combines two robotic platforms: one performs automated synthesis, cooling and dispensing of the DDM reagent, while the other carries out μSPE enrichment of water samples. Using the high resolution of gas chromatography with pulsed splitless injection provided low-noise baselines, well-defined peak shapes and highly reproducible automated integration. Method validation showed acceptable recoveries and precision according to the ICH guideline over a concentration range from 0.1 – 50 μg/L. Detection limits range from 0.26 – 0.52 pg on column and although they do not surpass the most sensitive LC-MS/MS methods, they are fit-for-purpose in an established workflow optimized for robustness, effectiveness and sustainability. Comparison of micro solid phase extraction (μSPE) cartridge loading by syringe driver (SD) versus the robotic system demonstrated similar retention performance but substantially reduced hands-on time and more standardized operation mode with the automated robotic system. The μSPE cartridges drastically lower the use of sorbent material by 90% and polypropylene housing by 75% compared to conventional applied SPE materials. The fully automated protocol consumes <1 mL of methanol per sample, achieving a > 95% reduction in organic solvent consumption relative to standard protocols. Application to Swiss tap, filter and surface waters revealed ubiquitous occurrence of trifluoroacetic acid, underscoring the need to monitor ultra short-chain PFCAs in the environment.
Keywords
PFCAs, GC-MS, Derivatization, Automation, Environmental analysis
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ISBN
ISSN
2772-5774
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
peer-reviewed
Open access category
Gold
License
Citation
Häusler, R., Laver, A., Freilinger, J., Gegner, H. M., Rupprich, M., Häussinger, D., & Gaugler, S. (2026). Automated derivatization and sample preparation protocol for ultrashort-chain PFCAs of water samples for GC-MS/MS detection. Green Analytical Chemistry, 19, 100385. https://doi.org/10.1016/j.greeac.2026.100385