Due to the ultra-trace concentrations of perfluoroalkyl compounds (PFCs) existing in environmental aqueous matrices, it is imperative to develop sensitive and high-enrichment-efficiency approaches for the determination of these emerging pollutants. In this study, a nitrogen-doped carbon dot-functionalized hollow fiber membrane (NCDs@HFM) was fabricated and employed in solid-phase microextraction (SPME) mode for the simultaneous identification of eight perfluoroalkyl carboxylates (PFCAs). The NCDs@HFM offers several advantages, including multiple active binding sites, chemical durability, a large specific surface area and environmental compatibility. Owing to these properties, the NCDs@HFM-based SPME demonstrated high extraction efficiency for PFCAs, where enrichment factors for target molecules could reach 35–61 fold under the optimum conditions. This established method was then integrated with liquid chromatography–tandem mass spectrometry (LC-MS/MS) for the qualitative and quantitative analysis of eight representative PFCAs in drinking and environmental water samples. The limits of detection (LODs, S/N = 3) and quantitation (LOQs, S/N = 10) of the method were at the scale of 0.0018–0.015 μg/L and 0.006–0.050 μg/L, respectively. This proposed method exhibited good precision, with RSDs below 13.2% and satisfactory accuracy, with recoveries ranging from 70.6% to 122.5%. The developed method was successfully applied in the identification of eight typical PFCAs in drinking and environmental water samples. This method exhibits several merits, including low cost, high sensitivity, good reliability and reusability, representing a promising alternative for measuring trace levels of PFCAs in aqueous matrices.
Building similarity graph...
Analyzing shared references across papers
Loading...
Lou et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69db38534fe01fead37c69b4 — DOI: https://doi.org/10.3390/molecules31081255
Cheng Lou
Shaojie Pan
Kaidi Zhang
Molecules
Zhejiang University
Ningbo University
China Jiliang University
Building similarity graph...
Analyzing shared references across papers
Loading...