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GCC: PFAS by CIC workflow

Presentations | 2022 | Thermo Fisher ScientificInstrumentation
Ion chromatography
Industries
Environmental
Manufacturer
Thermo Fisher Scientific

Summary

Importance of the topic


Per- and polyfluoroalkyl substances (PFAS) represent a persistent environmental and health concern due to their widespread use and chemical stability. Traditional targeted liquid chromatography-mass spectrometry (LC-MS/MS) approaches capture only a subset of known PFAS, leaving many fluorinated compounds undetected. Adsorbable organic fluorine (AOF) by combustion ion chromatography (CIC) offers a complementary, cumulative screening parameter that quantifies the total fluorine bound to organic moieties, enabling broader monitoring of known and unknown PFAS in water, soil, polymers and other matrices.

Objectives and overview of the article


This whitepaper by Thermo Fisher Scientific and Nittoseiko details a workflow for AOF determination via automated CIC. The goals are to describe the sample adsorption step, combustion and gas absorption modules, and subsequent ion chromatography analysis. Standard compliance (ASTM, JIS, VDI, DIN, ISO) and integration with high-throughput laboratory automation are highlighted to optimize PFAS screening and refine selection of samples for targeted LC-MS/MS or GC-MS/MS.

Methodology and instrumentation


The method comprises:
  • Offline adsorption of organic fluorine onto activated carbon (Nittoseiko TXA-04 AOX Adsorption Unit).
  • Elimination of inorganic fluoride by aqueous washing (0.01 M NaNO₃).
  • Ceramic-protected combustion of loaded carbon boats in pure oxygen (Nittoseiko AQF-2100H furnace with ceramic insert and boats).
  • Absorption of combustion gases in a heated glass absorption tube connected to a syringe burette (AQF-2100H Gas Absorption Unit).
  • Automated transfer of absorbate to a Dionex Integrion HPIC system for fluoride detection using eluent generation (KOH), anion traps, suppressors and optional preconcentration modules.
  • Chromeleon CDS software drives combustion sequencing and IC analysis for high throughput.

Key results and discussion


Validation on wastewater and spiked samples demonstrated:
  • Detection limits for AOF around 10 µg/L (as F).
  • Linear calibration across 0.1 – 10 µg/L with excellent correlation.
  • Recoveries of PFAS standards consistently above 90%.
  • Robust operation with high sodium or alkali earth content samples afforded by ceramic tube protection.
Automated sequencing reduced idle time and improved laboratory productivity.

Benefits and practical applications


AOF by CIC:
  • Provides a broad, non-targeted screening tool that covers known and unknown fluorinated organics.
  • Excludes inorganic fluoride for specificity to organic-bound F.
  • Enables economical prioritization of samples for detailed LC-MS/MS or GC-MS/MS analysis.
  • Aligns with emerging regulatory standards (DIN/ISO/U.S. EPA forthcoming).

Future trends and potential applications


As regulatory requirements evolve, CIC workflows may expand to include additional halogens (Cl, Br, S) and integration with suspect screening by high-resolution mass spectrometry. Miniaturization of adsorption units and continuous flow combustion modules could further enhance throughput. Data-driven selection of “suspicious” samples based on AOF results will refine resource allocation in water quality monitoring and industrial QA/QC.

Conclusion


Combustion ion chromatography for AOF measurement represents a sensitive, automated and cost-effective screening approach for total organic fluorine. Its complementarity to targeted MS methods improves overall PFAS surveillance by flagging samples with elevated fluorine loading, guiding more detailed analyses and supporting regulatory compliance.

References


  • ASTM, JIS, VDI, DIN and ISO standard methods for halogen combustion and IC analysis.
  • Thermo Fisher Scientific Dionex Integrion HPIC system documentation.
  • Nittoseiko TXA-04 and AQF-2100H product manuals.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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