title: [Research on the influence of infrared spectral resolution on gas quantitative analysis].
abstract: Spectra with different resolution (1, 2, 4 and 8 cm(-1)) of samples with combined CO/CO2/NO were used to build models for quantitative analysis of each component. Using these models, the influence of spectral resolution on gas quantitative analysis was studied. Research data show that for each component there is a best competent resolution for its quantitative analysis. And the quantitative analysis of all involved components has good calibration accuracy with higher resolution (1/2 cm(-1)) and lower resolution (8 cm(-1)), giving the relatively high mean of correlation coefficient of each component (r) more than 0.999 5, and the mean of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) of each component below 18.36 and 15.43 respectively, but the calibration accuracy of the model with moderate resolution of 4 cm(-1) dropped sharply, giving the mean of correlation coefficient of each component (r) of 0.989 66,and the mean of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) of each component of 90.37 and 64.33 respectively. These results demonstrate that the spectral resolution has an important effect on the calibration accuracy of gas quantitative analysis model and the successful application of FTIR As can be seen, the accuracy of gas quantitative analysis is highly dependent on the proper selection of spectral resolution. In order to improve the accuracy of gas quantitative analysis, it is very important to select suitable spectral resolution depending on different components and various application situations.
authors.affiliation: State Key Lab of Fire Science, University of Science and Technology of China, Hefei 230027, China. zhaojh@ustc.edu.cn
authors.forename: Jian-Hua
authors.initials: JH
authors.lastname: Zhao
authors.forename: Zhou-Jun
authors.initials: ZJ
authors.lastname: Wei
authors.forename: Ming-Liang
authors.initials: ML
authors.lastname: Gao
authors.forename: Jun
authors.initials: J
authors.lastname: Fang