Multivariate Analysis as a Tool to Identify Concentrations from Strongly Overlapping Gas Spectra - Yannick Saalberg and Marcus Wolff (Sensors, 2018)
We applied a multivariate analysis (MVA) to spectroscopic data of gas mixtures in the mid-IR in order to calculate the concentrations of the single components which exhibit strongly overlapping absorption spectra. This is a common challenge in broadband spectroscopy. Photoacoustic (PA) measurements of different volatile organic compounds (VOCs) in the wavelength region of 3250 nm to 3550 nm served as the exemplary detection technique. Partial least squares regression (PLS) was used to calculate concentrations from the PA spectra. After calibration, the PLS model was able to determine concentrations of single VOCs with a relative accuracy of 2.60%.
Keywords: multivariate analysis; partial least squares regression; photoacoustic spectroscopy; overlapping spectra; concentration determination