侧流烟气VOCs分析及VOC预浓缩- gc - o技术表征

N. Higashi, H. Shikata, M. Shimoda, I. Hayakawa
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摘要

摘要:挥发性有机化合物(VOCs)的分析采用了多种技术。然而,由于操作系统的复杂性、系统的不稳定性或灵敏度较差,这些技术不足以精确分析烟草烟雾中的VOCs。为了克服这些问题,我们开发了一种由VOC预浓缩器、气相色谱仪和嗅觉计组成的组合系统。该系统在烟草烟雾中挥发性有机化合物的分析中得到了评价,并应用于过去未得到充分研究的侧流烟雾(SSS)气味分析。将气体取样袋中的VOC样品通过预浓缩器注入气相色谱仪,在那里进行浓缩、脱水和低温聚焦。分离的挥发性有机化合物通过分离装置引入质谱仪(用于定性和定量分析)和嗅探口(用于气味分析)。除了传统的气相色谱-嗅觉测定(GC-O)技术用于描述每种化合物的气味质量外,气味强度是根据样品的稀释比,香气直接稀释分析(ADDA)来估计的。此外,通过感官评价来估计每种挥发性有机化合物对SSS整体气味的贡献。该系统允许充分表征挥发性有机化合物。定量重现性也很好,变异系数小于5% (n = 5)。采用气相色谱- o技术,我们获得了由30多种气味剂组成的SSS气味谱。ADDA表明,7种气味剂足以表征SSS气味。此外,省略测试显示,三种气味属性(“金属”,“土豆”和“爆米花”)对SSS气味的表征最重要。
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Analysis of Sidestream Smoke VOCs and Characterization of their Odor Profiles by VOC Preconcentrator-GC-O Techniques
Abstract Various techniques have been employed in the analysis of volatile organic compounds (VOCs). However, these techniques are insufficient for the precise analysis of tobacco smoke VOCs because of the complexity of the operating system, system instability, or poor sensitivity. To overcome these problems, a combined system of VOC preconcentrator, gas chromatograph, and olfactometer has been developed. The performance of this new system was evaluated in the analysis of VOCs in tobacco smoke and applied to the odor profiling of sidestream smoke (SSS) that has not been sufficiently investigated in the past. A VOC sample in a gas-sampling bag was injected into a gas chromatograph through a preconcentrator, where it was concentrated, dehydrated, and cryo-focused. Separated VOCs were introduced into a mass spectrometer (for qualitative and quantitative analysis) and a sniffing port (for odor profiling) by a splitting device. In addition to the conventional Gas Chromatography-Olfactometry (GC-O) technique that was used for describing the odor quality of each compound, the odor intensity was estimated based on the dilution ratio of the sample, Aroma Direct Dilution Analysis (ADDA). Also, the contribution of each VOC to the overall SSS odor was estimated by sensory evaluation. This system permitted adequate characterization of the VOCs. The reproducibility of quantification was also good enough with Coefficient of Variation (CV) values less than about 5% (n = 5). With the GC-O technique, we obtained an SSS odor profile composed of over 30 odorants. ADDA indicated that seven odorants were sufficient to characterize SSS odor. In addition, the omit-test revealed that three odor attributes, (‘metallic’, ‘potato-like’, and ‘popcorn-like’) were most important for the characterization of SSS odor.
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