Bridging target analysis and total-fluorine screening: TOP-AOF enables improved assessment of PFAS contamination in industrialized watersheds

Abstract

Per- and polyfluoroalkyl substances (PFAS) are persistent contaminants of increasing concern in aquatic environments, yet assessment remains challenging due to the diversity of target compounds and precursors. This study investigated PFAS occurrence, composition, and sources in industrial and municipal wastewater effluents and river waters from the Nakdong River basin, Republic of Korea, using an integrated framework bridging target analysis and total-fluorine screening through liquid chromatography–tandem mass spectrometry (LC-MS/MS), the total oxidizable precursor (TOP) assay, and combustion ion chromatography for adsorbable organofluorine (AOF). Method validation demonstrated that AOF preferentially recovers intermediate- and long-chain PFAS while excluding ultrashort-chain PFAS and inorganic fluorinated species. The application of sequential TOP oxidation (TOP-AOF) enhanced selectivity by eliminating interferences from non-PFAS organofluorines. Although the TOP-AOF method retains limitations regarding short-chain recovery, this trade-off demonstrates its potential as a robust, risk-oriented screening tool focused on the toxicologically significant fraction of adsorbable total PFAS. Distinct sector-specific fingerprints were observed. Dyeing, textile, and pulp and paper effluents exhibited the highest PFAS concentrations and precursor contributions, dominated by short-chain perfluoroalkyl carboxylic acids and perfluorobutane sulfonate. Electronics-related wastewater was enriched in short-chain PFAS, whereas metal-processing effluents showed perfluoroalkyl sulfonate-dominated profiles. Municipal effluents contained lower PFAS concentrations, but their large discharge volumes produced mass loads comparable to major industrial sources. Overall, TOP-AOF enables improved assessment of PFAS contamination by linking compound-specific LC-MS/MS with total-fluorine screening for source identification and mass-load assessment in industrialized watersheds. © 2026 Elsevier Ltd.