Measurement of carbon monoxide pressure broadening and temperature dependence coefficients in the 1 ← 0 band
Abstract
Two laser absorption spectroscopy (LAS)-based spectrometers have been developed for measuring carbon monoxide (CO) pressure broadening and temperature dependency coefficients in the 1 ← 0 band. Using a scanned-wavelength LAS at 140 Hz, pressure broadening coefficients of four CO transition lines P(16), P(20), P(26), and P(27), perturbed by Ar, He, H2, O2, N2, CO2, and Air have been systematically measured in a gas cell using a consistent metrological approach. Results indicate that the CO pressure broadening coefficient decreases monotonically as the line number |m| increases. The variation of pressure broadening coefficients at different buffer gases follow a consistent trend for all four measured lines: CO–H2 and CO–Ar show the highest and lowest pressure broadening coefficients, respectively. Compared to the literature results with relatively large uncertainties or even unavaible uncertainty information, the uncertainty of measured pressure broadening coefficients is below 1% for most cases. Further, using a scanned-wavelength LAS at 20 kHz, temperature dependence coefficients of P(20) in Ar, He, N2 and CO2 were measured at a temperature range of 430–1648 K in a shock tube. With this rapid scan frequency, the spectrum between incident shock and reflected shock was also used for temperature dependence coefficient calculation. The uncertainty of the measured temperature dependence coefficients are under 6.2%. Toward combustion systems as an application case, the CO mole fraction during CH4 oxidation in the shock tube was quantified using a fixed-wavelength LAS. The results reveal that the uncertainty in CO mole fraction was reduced by a factor of 2.7 when using the line parameters obtained in this study compared to those from the HITRAN database. Thus, the newly measured data with low uncertainties substantially enhance the spectroscopic database, enabling more precise CO mole fraction quantification across a range of application scenarios such as environmental monitoring, industrial control, safety monitoring, medicine, astronomy, and scientific research.
- This article is part of the themed collection: Bunsen-Tagung 2024: High-Resolution Structural Methods in Material and Life Sciences