Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels

Bibliographic Details
Main Author: Ribessi,Rafael L.
Publication Date: 2022
Other Authors: Jardim,Wilson F., Rohwedder,Jarbas J. R., Neves,Thiago A.
Format: Article
Language: eng
Source: Journal of the Brazilian Chemical Society (Online)
Download full: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532022000400340
Summary: In this work we developed a promising analytical method combining Fourier transform near-infrared (FT-NIR) spectroscopic technique and first-order multivariate calibration using partial least-squares (PLS) model to simultaneously quantify the main greenhouse gases (GHG’s): methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O) and water vapor (H2O). The models were built using 70 mixtures with different concentration of these gases, 0.25-32.0 ppm to CH4 and N2O, and 50-1100 ppm to CO2 and different values of relative humidity (52-85%, 20 ºC) in synthetic air. After preparing each of the mixtures, they were analyzed by using FT-NIR and a reference analytical technique based on gas chromatography with mass spectrometric detection (GC-MS). The FT-NIR spectrometer was coupled with a long optical path cell, with 105.6 meters of optical path. In sequence, the spectra of all mixtures and its concentration values for each gas were used to build the multivariate calibration models, using PLS regressions. For this, the mixtures were grouped with Kennard Stone algorithm, 50 samples to calibration set and 20 samples to prediction set. The values of RMSEP (root mean square error of prediction) obtained for each model are 0.66, 28.7 and 0.66 ppm, respectively, for CH4, CO2, and N2O. The limits of quantification (LOQ) for each PLS models are 0.26, 3.6, and 0.99 ppm, respectively, for CH4, CO2, and N2O. The results show the potentiality of application of this system to monitoring emission sources in which the concentration of these gases are relatively high, as urban centers, industrial areas, and landfills.
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spelling Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levelsgreenhouse gaseschemometricsNIR spectroscopyhigh humidity levelsPLSIn this work we developed a promising analytical method combining Fourier transform near-infrared (FT-NIR) spectroscopic technique and first-order multivariate calibration using partial least-squares (PLS) model to simultaneously quantify the main greenhouse gases (GHG’s): methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O) and water vapor (H2O). The models were built using 70 mixtures with different concentration of these gases, 0.25-32.0 ppm to CH4 and N2O, and 50-1100 ppm to CO2 and different values of relative humidity (52-85%, 20 ºC) in synthetic air. After preparing each of the mixtures, they were analyzed by using FT-NIR and a reference analytical technique based on gas chromatography with mass spectrometric detection (GC-MS). The FT-NIR spectrometer was coupled with a long optical path cell, with 105.6 meters of optical path. In sequence, the spectra of all mixtures and its concentration values for each gas were used to build the multivariate calibration models, using PLS regressions. For this, the mixtures were grouped with Kennard Stone algorithm, 50 samples to calibration set and 20 samples to prediction set. The values of RMSEP (root mean square error of prediction) obtained for each model are 0.66, 28.7 and 0.66 ppm, respectively, for CH4, CO2, and N2O. The limits of quantification (LOQ) for each PLS models are 0.26, 3.6, and 0.99 ppm, respectively, for CH4, CO2, and N2O. The results show the potentiality of application of this system to monitoring emission sources in which the concentration of these gases are relatively high, as urban centers, industrial areas, and landfills.Sociedade Brasileira de Química2022-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532022000400340Journal of the Brazilian Chemical Society v.33 n.4 2022reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.21577/0103-5053.20210152info:eu-repo/semantics/openAccessRibessi,Rafael L.Jardim,Wilson F.Rohwedder,Jarbas J. R.Neves,Thiago A.eng2022-03-15T00:00:00Zoai:scielo:S0103-50532022000400340Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2022-03-15T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false
dc.title.none.fl_str_mv Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
title Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
spellingShingle Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
Ribessi,Rafael L.
greenhouse gases
chemometrics
NIR spectroscopy
high humidity levels
PLS
title_short Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
title_full Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
title_fullStr Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
title_full_unstemmed Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
title_sort Quantification of Carbon Dioxide (CO2), Methane (CH4), and Nitrous Oxide (N2O) Using Near Infrared Spectroscopy and Multivariate Calibration in High Humidity Levels
author Ribessi,Rafael L.
author_facet Ribessi,Rafael L.
Jardim,Wilson F.
Rohwedder,Jarbas J. R.
Neves,Thiago A.
author_role author
author2 Jardim,Wilson F.
Rohwedder,Jarbas J. R.
Neves,Thiago A.
author2_role author
author
author
dc.contributor.author.fl_str_mv Ribessi,Rafael L.
Jardim,Wilson F.
Rohwedder,Jarbas J. R.
Neves,Thiago A.
dc.subject.por.fl_str_mv greenhouse gases
chemometrics
NIR spectroscopy
high humidity levels
PLS
topic greenhouse gases
chemometrics
NIR spectroscopy
high humidity levels
PLS
description In this work we developed a promising analytical method combining Fourier transform near-infrared (FT-NIR) spectroscopic technique and first-order multivariate calibration using partial least-squares (PLS) model to simultaneously quantify the main greenhouse gases (GHG’s): methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O) and water vapor (H2O). The models were built using 70 mixtures with different concentration of these gases, 0.25-32.0 ppm to CH4 and N2O, and 50-1100 ppm to CO2 and different values of relative humidity (52-85%, 20 ºC) in synthetic air. After preparing each of the mixtures, they were analyzed by using FT-NIR and a reference analytical technique based on gas chromatography with mass spectrometric detection (GC-MS). The FT-NIR spectrometer was coupled with a long optical path cell, with 105.6 meters of optical path. In sequence, the spectra of all mixtures and its concentration values for each gas were used to build the multivariate calibration models, using PLS regressions. For this, the mixtures were grouped with Kennard Stone algorithm, 50 samples to calibration set and 20 samples to prediction set. The values of RMSEP (root mean square error of prediction) obtained for each model are 0.66, 28.7 and 0.66 ppm, respectively, for CH4, CO2, and N2O. The limits of quantification (LOQ) for each PLS models are 0.26, 3.6, and 0.99 ppm, respectively, for CH4, CO2, and N2O. The results show the potentiality of application of this system to monitoring emission sources in which the concentration of these gases are relatively high, as urban centers, industrial areas, and landfills.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532022000400340
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532022000400340
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.21577/0103-5053.20210152
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Química
publisher.none.fl_str_mv Sociedade Brasileira de Química
dc.source.none.fl_str_mv Journal of the Brazilian Chemical Society v.33 n.4 2022
reponame:Journal of the Brazilian Chemical Society (Online)
instname:Sociedade Brasileira de Química (SBQ)
instacron:SBQ
instname_str Sociedade Brasileira de Química (SBQ)
instacron_str SBQ
institution SBQ
reponame_str Journal of the Brazilian Chemical Society (Online)
collection Journal of the Brazilian Chemical Society (Online)
repository.name.fl_str_mv Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)
repository.mail.fl_str_mv ||office@jbcs.sbq.org.br
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