Gas filter correlation technique applied to in-situ monitoring of nitrogen monoxide (NO) in industrial exhaust

Emily Y. Shu; M. Kent Cueman; Gabriel Fortin; Greg Gilmore; H. Andrew Wallio

doi:10.1117/12.255329

21 October 1996 Gas filter correlation technique applied to in-situ monitoring of nitrogen monoxide (NO) in industrial exhaust

Emily Y. Shu, M. Kent Cueman, Gabriel Fortin, Greg Gilmore, H. Andrew Wallio

Author Affiliations +

Proceedings Volume 2834, Application of Tunable Diode and Other Infrared Sources for Atmospheric Studies and Industrial Process Monitoring; (1996) https://doi.org/10.1117/12.255329
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

An in situ gas filter correlation spectrometer is applied to measure gas emission in smoke stacks. Experiments were performed at a simulated stack with NO at parts per million level for various elevated temperatures. A line-by-line spectroscopic computational model, originally developed at NASA Langley Research Center, was applied to the analysis. This paper summarizes recent development work at GE CRD and GE Reuter-Stokes to understand and to improve the sensitivity and efficiency of the analyzer for in situ monitoring nitrogen monoxide (NO) in the fossil fuel-fired power plants. The model calculation agreed very well with the experimental results. Special consideration was given to analyzing the detector response and light source effect on the performance of the system. The report concludes with a discussion of several design improvements and their potential impact on the signal to noise ratio and, therefore, the NO detection sensitivity.

Citation Download Citation

Emily Y. Shu, M. Kent Cueman, Gabriel Fortin, Greg Gilmore, and H. Andrew Wallio "Gas filter correlation technique applied to in-situ monitoring of nitrogen monoxide (NO) in industrial exhaust", Proc. SPIE 2834, Application of Tunable Diode and Other Infrared Sources for Atmospheric Studies and Industrial Process Monitoring, (21 October 1996); https://doi.org/10.1117/12.255329

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