Calibration spectra of CO in the 2.38-5100 ppm concentration range (22 spectra) have been measured with a spectral resolution of 4 cm-1, in the mid-IR (2186-2001 cm-1) region, with a Fourier transform infrared (FT-IR) instrument. The multivariate calibration method partial least-squares (PLS1) was used to model the CO calibration spectra in order to improve the sensitivity and to flag possible outliers in the prediction step. The relation between the absorbance values and concentrations was strongly nonlinear. This result was caused mainly by the low spectral resolution of the instrument. To improve the model predictions, we have linearized the data prior to making the model calculations. The linearization scheme presented here simplified the data pretreatment, because the function needed to linearize the data might be approximated by co-absorbance peak areas representing the concentrations. The integrated absorbance areas, rather than the concentration values, were used as input to the PLS algorithm. A fifth-order polynomial was used to calculate the concentrations from the predicted absorbance areas. The PLS algorithm used on the linearized data reduced the number of factors in the calibration model. Our results reveal that the calibration model based on the linearized data had a high concentration prediction accuracy throughout the entire concentration range.
Jimmy Bak and Anders Larsen, "Quantitative Gas Analysis with FT-IR: A Method for CO Calibration Using Partial Least-Squares with Linearized Data," Appl. Spectrosc. 49, 437-443 (1995)