Issue 36, 2023

Determination of 25 polybrominated diphenyl ethers in Chinese mitten crab ecosystems by gas chromatography-mass spectrometry

Abstract

A sensitive and reliable method for determining 25 polybrominated diphenyl ethers (PBDEs) in Chinese mitten crabs and their ecosystems ranging from the growing environment to edible feed by gas chromatography coupled to triple quadrupole mass spectrometry with advanced electron ionization (GC-AEI-MS/MS) was developed and validated. Accelerated solvent extraction (ASE) and liquid–liquid extraction were used to extract solid and water samples, respectively. On the basis of a traditional acid–base silica column, deactivated silica was added and n-hexane elution was used to increase the effect of separation and purification. Two oven temperature programs were applied to achieve good separation of low brominated congeners and increase the sensitivity of high brominated congeners. The method provided good linearity (>0.9996). The recoveries of four matrices were in the range of 82–115% and the method quantification limits (MQLs) in crabs, feed, sediment and water ranged from 0.36–6 pg per g wet weight, 0.69–22.29 pg per g dry weight, 1.02–25.26 pg per g dry weight, and 2.43–40.14 pg L−1, respectively. The proposed method was used for ten samples from two aquatic sites and PBDEs were detected in Chinese mitten crabs, commercial feed and sediment, with the highest in crabs. This analytical technique can be used to monitor the content and the accumulation behavior of PBDEs in Chinese mitten crab ecosystems or other aquaculture systems.

Graphical abstract: Determination of 25 polybrominated diphenyl ethers in Chinese mitten crab ecosystems by gas chromatography-mass spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
04 Jul 2023
Accepted
12 Jul 2023
First published
21 Jul 2023

Anal. Methods, 2023,15, 4700-4709

Determination of 25 polybrominated diphenyl ethers in Chinese mitten crab ecosystems by gas chromatography-mass spectrometry

Q. Zhang, W. Song, X. Wang, C. Liu, S. Chen, H. Li and Q. Rao, Anal. Methods, 2023, 15, 4700 DOI: 10.1039/D3AY01123B

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