Using Multiple Calibration Sets to Improve the Quantitative Accuracy of Partial Least Squares (PLS) Regression on Open-Path Fourier Transform Infrared (OP/FT-IR) Spectra of Ammonia over Wide Concentration Ranges

The use of multiple calibration sets in partial least squares (PLS) regression was proposed to improve the quantitative determination of NH₃ over wide concentration ranges from open-path Fourier transform infrared (OP/FT-IR) spectra. The spectra were measured near animal farms, where the path-integrated concentration of NH₃ can fluctuate from nearly zero to as high as approximately 1000 ppm-m. PLS regression with a single calibration set did not cover such a large concentration range effectively, and the quantitative accuracy was degraded due to the nonlinear relationship between concentration and absorbance for spectra measured at low resolution (1 cm⁻¹ and poorer.) In PLS regression with multiple calibration sets, each calibration set covers a part of the entire concentration range, which significantly decreases the serious nonlinearity problem in PLS regression occurring when only a single calibration set is used. The relative error was reduced from approximately 6% to below 2%, and the best results were obtained with four calibration sets, each covering one quarter of the entire concentration range. It was also found that it was possible to build the multiple calibration sets easily and efficiently without extra measurements.