| 光谱学与光谱分析 |
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| Methane Concentration Detection System for Cigarette Smoke Based on TDLAS Technology |
| YANG Ke1,2, ZHANG Long1, WU Xiao-song1, LI Zhi-gang1, WANG An1, LIU Yong1, JI Min1* |
1. Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
2. University of Science and Technology of China, Hefei 230026, China |
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Abstract Rapid and real-time analysis of cigarette smoke is of great significance to study the puff-by-puff transfer rules in the suction process and to explore the relationship between smoking and health. By combining with the modified commercial smoking machine herein, cigarette smoke online analysis system was established based on the TDLAS technology. The puff-by-puff stability of this system was verified by simulated cigarette composed of a pocket containing CH4 (volume fraction of 0.4), of which the second harmonic peaks are near 1.39. Using this system, the concentration of CH4 in four different kinds of cigarettes was analyzed puff-by-puff by a semiconductor laser, of which center wavelength was at 1 653.72 nm. The results showed that the CH4 concentration of cigarette smoke increased puff-by-puff. CH4 concentration in the flue-cured cigarette is obviously higher than that of blended cigarette by comparing the content of all and puff-by-puff concentration. The puff-by-puff concentration of flue-cured cigarette increased from 400 to 900 ppm, however, the puff-by-puff concentration of blended cigarette increased from 200 to 600 ppm. Simultaneously, there was significant difference between different kinds of the flue-cured. Comparing to traditional analysis methods, this system can effectively avoid the interference of other gases in the smoke cigarette as a result of its strong anti-interference. At the same time, it can finish analysis between suction interval without sample pretreatment. The technology has a good prospect in the on-line puff-by-puff analysis of cigarette smoke.
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Received: 2014-07-30
Accepted: 2014-10-28
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Corresponding Authors:
JI Min
E-mail: jimin@aiofm.ac.cn
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[1] Baker R R. Progress in Energy and Combustion Science, 2006, 32: 374.
[2] Adam T, Baker R R, Zimmermann R. Agricultural and Food Chemistry, 2007, 55: 2055.
[3] Jiang C Y, Sun S H, Zhang Q D, et al. International Journal of Mass Spectrometry, 2013, 353: 43.
[4] Zhang Z W, Xu Y B, Wang C H, et al. Journal of Chromatography A, 2011, 1218: 1016.
[5] Yang X, Meng X, Ricky R A, et al. Journal of Chromatography B, 2011, 879: 2142.
[6] WANG Hong-bo, GUO Jun-wei, PENG Bin, et al(王洪波，郭军伟，彭 斌，等). Tobacco Science & Technology(烟草科技), 2011, 11: 30.
[7] Smith C J, So S, Xia L, et al. Apply Physics B, 2013, 110: 242.
[8] Wiesen P, Kleffmann J, Kurtenbach R, et al. Infrared Physics and Technology, 1996, 37: 76.
[9] Deguchi Y, Noda M, Fukuda Y, et al. Measurement Science and Technology, 2002, 13: R109.
[10] Bacsik Z, McGregor J, Mink J. Food and Chemical Toxicology, 2007, 45: 268.
[11] Song J M, Jagannathan R, Stokes D L, et al. Polycyclic Aromatic Compounds, 2003, 23: 430.
[12] Bigourd D, Cuisset A, Hindle F, et al. Optics Letters, 2006, 31(15): 2357.
[13] KAN Rui-feng, LIU Wen-qing, ZHANG Yu-jun, et al(阚瑞峰，刘文清，张玉钧，等). Chinese Journal of Lasers(中国激光), 2005, 32(9): 1218.
[14] XIA Hua, DONG Feng-zhong, TU Guo-jie, et al(夏 滑，董凤忠，涂郭结，等). Acta Optica Sinica(光学学报), 2010, 30(9): 2598.
[15] HE Ying, ZHANG Yu-jun, WANG Li-ming, et al(何 莹，张玉钧，王立明，等). Optical Technique(光学技术), 2012, 38(4): 425.
[16] Dong J Z, Glass J N, Moldoveanu S C. Journal of Microcolumn Separations, 2000, 12(3): 142.
[17] Rostami A A, Hajaligol M R. Analytical and Applied Pyrolysis, 2003, 66: 276.
[18] Ding Y S, Yan X J, Jain R B, et al. Environmental Sciences & Ecology, 2006, 40: 1135.
[19] Liu C, Feng S, Heemst J V, et al. Analytical and Bioanalytical Chemistry, 2010, 396: 1824. |
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