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Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis

An imaging Fourier-transform spectrometer in the mid-infrared (1850–6667 cm [Formula: see text]) has been used to acquire transmittance spectra at a resolution of 1 cm [Formula: see text] of three atmospheric pollutants with known column densities (Q): methane (258 ppm·m), nitrous oxide (107.5 ppm·m...

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Autores principales: Meléndez, Juan, Guarnizo, Guillermo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8002400/
https://www.ncbi.nlm.nih.gov/pubmed/33802670
http://dx.doi.org/10.3390/s21062092
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author Meléndez, Juan
Guarnizo, Guillermo
author_facet Meléndez, Juan
Guarnizo, Guillermo
author_sort Meléndez, Juan
collection PubMed
description An imaging Fourier-transform spectrometer in the mid-infrared (1850–6667 cm [Formula: see text]) has been used to acquire transmittance spectra at a resolution of 1 cm [Formula: see text] of three atmospheric pollutants with known column densities (Q): methane (258 ppm·m), nitrous oxide (107.5 ppm·m) and propane (215 ppm·m). Values of Q and T have been retrieved by fitting them with theoretical spectra generated with parameters from the HITRAN database, based on a radiometric model that takes into account gas absorption and emission, and the instrument lineshape function. A principal component analysis (PCA) of experimental data has found that two principal components are enough to reconstruct gas spectra with high fidelity. PCA-processed spectra have better signal-to-noise ratio without loss of spatial resolution, improving the uniformity of retrieval. PCA has been used also to speed up retrieval, by pre-calculating simulated spectra for a range of expected Q and T values, applying PCA to them and then comparing the principal components of experimental spectra with those of the simulated ones to find the gas Q and T values. A reduction in calculation time by a factor larger than one thousand is achieved with improved accuracy. Retrieval can be further simplified by obtaining T and Q as quadratic functions of the two first principal components.
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spelling pubmed-80024002021-03-28 Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis Meléndez, Juan Guarnizo, Guillermo Sensors (Basel) Article An imaging Fourier-transform spectrometer in the mid-infrared (1850–6667 cm [Formula: see text]) has been used to acquire transmittance spectra at a resolution of 1 cm [Formula: see text] of three atmospheric pollutants with known column densities (Q): methane (258 ppm·m), nitrous oxide (107.5 ppm·m) and propane (215 ppm·m). Values of Q and T have been retrieved by fitting them with theoretical spectra generated with parameters from the HITRAN database, based on a radiometric model that takes into account gas absorption and emission, and the instrument lineshape function. A principal component analysis (PCA) of experimental data has found that two principal components are enough to reconstruct gas spectra with high fidelity. PCA-processed spectra have better signal-to-noise ratio without loss of spatial resolution, improving the uniformity of retrieval. PCA has been used also to speed up retrieval, by pre-calculating simulated spectra for a range of expected Q and T values, applying PCA to them and then comparing the principal components of experimental spectra with those of the simulated ones to find the gas Q and T values. A reduction in calculation time by a factor larger than one thousand is achieved with improved accuracy. Retrieval can be further simplified by obtaining T and Q as quadratic functions of the two first principal components. MDPI 2021-03-17 /pmc/articles/PMC8002400/ /pubmed/33802670 http://dx.doi.org/10.3390/s21062092 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Meléndez, Juan
Guarnizo, Guillermo
Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis
title Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis
title_full Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis
title_fullStr Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis
title_full_unstemmed Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis
title_short Fast Quantification of Air Pollutants by Mid-Infrared Hyperspectral Imaging and Principal Component Analysis
title_sort fast quantification of air pollutants by mid-infrared hyperspectral imaging and principal component analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8002400/
https://www.ncbi.nlm.nih.gov/pubmed/33802670
http://dx.doi.org/10.3390/s21062092
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