Volume 14 Issue 6
Nov.  2021
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XIE Yao, HUA Dao-zhu, QI Yu, SHEN Ting-ting, LIU Zhen-qiang, YE Hua-jun, LIU Wei-ping. Applications of GFC-IFC in trace multi-component gas analysis[J]. Chinese Optics, 2021, 14(6): 1378-1386. doi: 10.37188/CO.2021-0064
Citation: XIE Yao, HUA Dao-zhu, QI Yu, SHEN Ting-ting, LIU Zhen-qiang, YE Hua-jun, LIU Wei-ping. Applications of GFC-IFC in trace multi-component gas analysis[J]. Chinese Optics, 2021, 14(6): 1378-1386. doi: 10.37188/CO.2021-0064

Applications of GFC-IFC in trace multi-component gas analysis

doi: 10.37188/CO.2021-0064
Funds:  Supported by Central Government′s Guidance for Local Science and Technology Development Funds (No. 2021ZY1028)
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  • Corresponding author: xie_yao3@163.com
  • Received Date: 19 May 2021
  • Rev Recd Date: 25 May 2021
  • Available Online: 02 Jun 2021
  • Publish Date: 19 Nov 2021
  • Ultra-low emission standards of flue gas emitted from stationary sources have been proposed, which creates a new challenge for Continuous Emission Monitoring (CEM). Peak carbon dioxide emissions and carbon neutrality are frequently-mentioned concepts, which means the monitoring of CO2 will eventually be necessary. It is difficult to satisfy the strict limits of ultra-low emission standards with conventional CEM systems. A multi-component trace gas analysis system based on non-dispersive infrared is promoted in this paper to monitor trace gases of continuous emission. A Gas Filter Correlation (GFC) model and Interference Filter Correlation (IFC) model were established, which can describe the relationship of optical length, center wavelength, bandwidth of the filters and gas concentration with measure and reference signals. To confirm the measurement technique of gases, the GFC technique combines with the IFC technique to achieve a double-beam path. With the help of white cells, a small-scale, and the detection limit better than 0.5 mg/m3 can be realized. Zero and span drift are no more than ±2% of the full scale. SO2, NO, NO2, CO and CO2 can be simultenously and continuously monitored to satisfy the requirements of ultra-low and carbon emission monitoring. This technique is helpful for obtaining factual, accurate and comprehensive CEM data.


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