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Structure prediction of methyoxy-polybrominated diphenyl ethers (MeO-PBDEs) through GC-MS analysis of their corresponding PBDEs
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
Örebro University, School of Science and Technology. (MTM Research Centre)ORCID iD: 0000-0002-5729-1908
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
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2016 (English)In: Talanta: The International Journal of Pure and Applied Analytical Chemistry, ISSN 0039-9140, E-ISSN 1873-3573, Vol. 152, 9-14 p.Article in journal (Refereed) Published
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Abstract [en]

It is hard to quantify the trace pollutants in the environment without the corresponding reference standards. Structure identifications of unknown organic pollutants are thus of great importance in environmental analysis. As for polybrominated diphenyl ethers (PBDE) with one substituent of methoxyl group, there are 837 congeners, but only 32 standards are commercially available. In this work, an effective method based on gas chromatography coupled with mass spectrometry (GC-MS) was proposed to predict the potential structures of methoxylated polybrominated diphenyl ethers (MeO-PBDEs). The mass fragmentation pattern using SIM mode not only provided the useful information on the substitution position of methoxyl group, the number of Br atoms, but also guaranteed the high sensitivity for trace analysis. Br distribution patterns of the unknown MeO-PBDEs were revealed by a linear regression model with dummy variables which described the retention time relationship between MeO-PBDEs and the corresponding PBDEs on different types of GC columns. This method was successfully used to identify three new MeO-PBDEs metabolites of BDE-28 as 4-MeO-BDE-22, 4'-MeO-BDE-25 and 4-MeO-BDE-31 in the pumpkins. Therefore, the newly developed structure prediction model based on GC-MS behavior is helpful in the evaluation of unknown PBDE metabolites in the environment.

Place, publisher, year, edition, pages
Amsterdam, Netherlands: Elsevier, 2016. Vol. 152, 9-14 p.
Keyword [en]
PBDEs, MeO-PBDEs, Structure identification, Metabolism, GC-MS
National Category
Analytical Chemistry
Research subject
Analytical Chemistry
Identifiers
URN: urn:nbn:se:oru:diva-50053DOI: 10.1016/j.talanta.2016.01.047ISI: 000373651000002PubMedID: 26992489Scopus ID: 2-s2.0-84957591595OAI: oai:DiVA.org:oru-50053DiVA: diva2:925485
Note

Funding Agencies:

National Basic Research Program of China 2014CB441105

National Natural Science Foundation of China 21277153  21177147

Strategic Priority Research Program of the Chinese Academy of Sciences XDB14010400

Available from: 2016-05-02 Created: 2016-05-02 Last updated: 2017-10-17Bibliographically approved

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