A Rapid and Simplified Approach to Correct Atmospheric Absorptions in Infrared Spectra.

Abstract

Infrared (IR) spectroscopy is a powerful analytical technique used to identify and quantify different components within a sample. However, spectral interference from fluctuating concentrations of water vapor and CO₂ in the measurement chamber can significantly impede the extraction of quantitative information. These temporal fluctuations cause absorption variations that interfere with the sample's spectrum, making accurate analysis challenging. While several techniques to overcome this problem exist in the literature, many are time-consuming or ineffective. We present a simple method utilizing just two sample spectra taken sequentially. The difference of these spectra, multiplied by a scaling factor, determined by minimization of the point-to-point spectral length, provides a correction spectrum. Subtracting this from the spectrum to be corrected results in a fully corrected spectrum. We demonstrate the effectiveness of this method via the improved ability to determine analyte concentration from corrected spectra over uncorrected spectra using a partial least square regression (PLSR) model. This technique therefore offers rapid, effective, and automated spectral correction, which is ideal for a nonexpert user in a clinical or industrial setting.