Improved Sensitivity of Infrared Spectroscopy by the Application of Least Squares Methods

Abstract

Improved sensitivity and precision in the quantitative analysis of trace gases by Fourier transform infrared spectroscopy have been achieved by the application of new spectral least squares methods. By relating all of the spectral information present in the reference spectrum of a trace gas to that of the unknown sample and by appropriately fitting the baseline, detections of trace gases can be obtained even though the individual spectral features may lie well below the noise level. Four least squares methods incorporating different baseline assumptions were investigated and compared using calibrated gases of CO, N₂O, and CO₂ in dry air. These methods include: (I) baseline known, (II) baseline linear over the spectral region of interest, (III) baseline linear over each spectral peak, and (IV) negligible baseline shift between successive data points. Methods III and IV were found to be most reliable for the gases studied. When method III is applied to the spectra of these trace gases, detection limits improved by factors of 5 to 7 over conventional methods applied to the same data. “Three sigma” detection limits are equal to 0.6, 0.2, and 0.08 ppm for CO, N₂O, and CO₂, respectively, when a 10-cm pathlength at a total pressure of 640 Torr is used with a ∼35 min measurement time at 0.06 cm⁻¹ resolution.