Literature DB >> 25087743

Multidimensional gas chromatography in combination with accurate mass, tandem mass spectrometry, and element-specific detection for identification of sulfur compounds in tobacco smoke.

Nobuo Ochiai1, Kazuhisa Mitsui2, Kikuo Sasamoto3, Yuta Yoshimura4, Frank David5, Pat Sandra5.   

Abstract

A method is developed for identification of sulfur compounds in tobacco smoke extract. The method is based on large volume injection (LVI) of 10μL of tobacco smoke extract followed by selectable one-dimensional ((1)D) or two-dimensional ((2)D) gas chromatography (GC) coupled to a hybrid quadrupole time-of-flight mass spectrometer (Q-TOF-MS) using electron ionization (EI) and positive chemical ionization (PCI), with parallel sulfur chemiluminescence detection (SCD). In order to identify each individual sulfur compound, sequential heart-cuts of 28 sulfur fractions from (1)D GC to (2)D GC were performed with the three MS detection modes (SCD/EI-TOF-MS, SCD/PCI-TOF-MS, and SCD/PCI-Q-TOF-MS). Thirty sulfur compounds were positively identified by MS library search, linear retention indices (LRI), molecular mass determination using PCI accurate mass spectra, formula calculation using EI and PCI accurate mass spectra, and structure elucidation using collision activated dissociation (CAD) of the protonated molecule. Additionally, 11 molecular formulas were obtained for unknown sulfur compounds. The determined values of the identified and unknown sulfur compounds were in the range of 10-740ngmg total particulate matter (TPM) (RSD: 1.2-12%, n=3).
Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

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Keywords:  Accurate mass detection; Positive chemical ionization (PCI); Selectable (1)D/(2)D GC–Q-TOF-MS; Sulfur chemiluminescence detection (SCD); Tandem mass spectrometry (MS/MS); Tobacco smoke

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Year:  2014        PMID: 25087743     DOI: 10.1016/j.chroma.2014.06.106

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  1 in total

1.  Identification of Cigarette Brands by Soft Independent Modeling of Class Analogy of Volatile Substances.

Authors:  Zuzana Zelinkova; Thomas Wenzl
Journal:  Nicotine Tob Res       Date:  2020-05-26       Impact factor: 4.244

  1 in total

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