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Comparison of an Innovative Nonlinear Algorithm to Classical Least-Squares for Analyzing Open-Path Fourier Transform Infrared Spectra Collected at a Concentrated Swine Production Facility

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Abstract:

Open-path Fourier transform infrared (OP/FT-IR) spectrometry was used to measure the concentrations of ammonia, methane, and other atmospheric gases at an integrated swine production facility. The concentration-pathlength products of the target gases at this site often exceeded the linear dynamic range of the OP/FT-IR spectrometer. To minimize the effect of this nonlinearity on the accuracy of the reported concentrations, a piecewise, linear classical least-squares (CLS) analysis method, which used a calibration set containing multiple reference spectra for each target gas at concentration-pathlength products that encompassed those found in the field spectra, was used to predict the path-averaged concentrations of the target gases. The predicted concentrations reported by this piecewise, linear CLS method were compared to those predicted by a conventional linear CLS method, which used a calibration set consisting of only one reference spectrum at a single concentration-pathlength product for each target gas, and an innovative nonlinear algorithm (NLA), which performs an iterative fit of the convolved spectral line data from the high-resolution transmission molecular absorption (HITRAN) database to the single-beam field spectra. The conventional, linear CLS method generally under-reported the target gas concentrations relative to those predicted by the piecewise, linear CLS method when the field spectra exhibited concentration-pathlength products larger than those of the reference spectra in the single-level calibration set. In extreme cases, for example, during measurements of methane along the waste lagoon, the concentrations predicted by the conventional CLS methods were more than 30% lower than those predicted by the piecewise, linear CLS method. In contrast, the concentrations of methane predicted by the NLA were, on average, within 4% of those predicted by the piecewise, linear CLS method. For ammonia, however, the concentrations predicted by the NLA were slightly higher than those predicted by the piecewise, linear CLS method at the lower range of observed concentration-pathlength products and slightly lower than those predicted by the piecewise, linear CLS method at the upper range of concentration-pathlength products. The NLA also consistently predicted higher concentrations of nitrous oxide and carbon dioxide relative to that predicted by the piecewise, linear CLS method. Differences in the background spectra and spectral ranges over which the analyses were conducted apparently did not contribute to the differences in the path-averaged concentrations predicted by these two analysis methods.

Keywords: CLASSICAL LEAST-SQUARES; INNOVATIVE NONLINEAR ALGORITHM; OPEN-PATH FOURIER TRANSFORM INFRARED SPECTROMETRY

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/0003702021954917

Publication date: March 1, 2002

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