An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil

Detalhes bibliográficos
Autor(a) principal: da Costa, Luis Miguel [UNESP]
Data de Publicação: 2022
Outros Autores: de Araújo Santos, Gustavo André [UNESP], Panosso, Alan Rodrigo [UNESP], de Souza Rolim, Glauco [UNESP], La Scala, Newton [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1186/s13021-022-00209-7
http://hdl.handle.net/11449/241153
Resumo: Background: The recent studies of the variations in the atmospheric column-averaged CO2 concentration (XCO2) above croplands and forests show a negative correlation between XCO2and Sun Induced Chlorophyll Fluorescence (SIF) and confirmed that photosynthesis is the main regulator of the terrestrial uptake for atmospheric CO2. The remote sensing techniques in this context are very important to observe this relation, however, there is still a time gap in orbital data, since the observation is not daily. Here we analyzed the effects of several variables related to the photosynthetic capacity of vegetation on XCO2 above São Paulo state during the period from 2015 to 2019 and propose a daily model to estimate the natural changes in atmospheric CO2. Results: The data retrieved from the Orbiting Carbon Observatory-2 (OCO-2), NASA-POWER and Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) show that Global Radiation (Qg), Sun Induced Chlorophyll Fluorescence (SIF) and, Relative Humidity (RH) are the most significant factors for predicting the annual XCO2 cycle. The daily model of XCO2 estimated from Qg and RH predicts daily XCO2 with root mean squared error of 0.47 ppm (the coefficient of determination is equal to 0.44, p < 0.01). Conclusion: The obtained results imply that a significant part of daily XCO2 variations could be explained by meteorological factors and that further research should be done to quantify the effects of the atmospheric transport and anthropogenic emissions.
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spelling An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, BrazilCarbon cycleClimate changeMeteorologyOCO-2Remote sensingStepwise regression analysisBackground: The recent studies of the variations in the atmospheric column-averaged CO2 concentration (XCO2) above croplands and forests show a negative correlation between XCO2and Sun Induced Chlorophyll Fluorescence (SIF) and confirmed that photosynthesis is the main regulator of the terrestrial uptake for atmospheric CO2. The remote sensing techniques in this context are very important to observe this relation, however, there is still a time gap in orbital data, since the observation is not daily. Here we analyzed the effects of several variables related to the photosynthetic capacity of vegetation on XCO2 above São Paulo state during the period from 2015 to 2019 and propose a daily model to estimate the natural changes in atmospheric CO2. Results: The data retrieved from the Orbiting Carbon Observatory-2 (OCO-2), NASA-POWER and Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) show that Global Radiation (Qg), Sun Induced Chlorophyll Fluorescence (SIF) and, Relative Humidity (RH) are the most significant factors for predicting the annual XCO2 cycle. The daily model of XCO2 estimated from Qg and RH predicts daily XCO2 with root mean squared error of 0.47 ppm (the coefficient of determination is equal to 0.44, p < 0.01). Conclusion: The obtained results imply that a significant part of daily XCO2 variations could be explained by meteorological factors and that further research should be done to quantify the effects of the atmospheric transport and anthropogenic emissions.Departament of Engineering and Exact Sciences São Paulo State University, Via de Acesso Prof. Paulo Donato Castellane s/n, JaboticabalCampus Avançado Porto Franco Instituto Federal de Educação Ciência e Tecnologia do Maranhão – IFMA, Rua Custódio Barbosa, no 09, Centro, MaranhãoCenter of Agricultural Natural and Literary Sciences State University of the Tocantina Region of Maranhão (UEMASUL), Av. Brejo do Pinto, S/N – Brejo do Pinto, MaranhãoDepartament of Engineering and Exact Sciences São Paulo State University, Via de Acesso Prof. Paulo Donato Castellane s/n, JaboticabalUniversidade Estadual Paulista (UNESP)Ciência e Tecnologia do Maranhão – IFMAUniversidade Estadual de Maringá (UEM)da Costa, Luis Miguel [UNESP]de Araújo Santos, Gustavo André [UNESP]Panosso, Alan Rodrigo [UNESP]de Souza Rolim, Glauco [UNESP]La Scala, Newton [UNESP]2023-03-01T20:49:20Z2023-03-01T20:49:20Z2022-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s13021-022-00209-7Carbon Balance and Management, v. 17, n. 1, 2022.1750-0680http://hdl.handle.net/11449/24115310.1186/s13021-022-00209-72-s2.0-85131821913Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCarbon Balance and Managementinfo:eu-repo/semantics/openAccess2023-03-01T20:49:20Zoai:repositorio.unesp.br:11449/241153Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-03-01T20:49:20Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
title An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
spellingShingle An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
da Costa, Luis Miguel [UNESP]
Carbon cycle
Climate change
Meteorology
OCO-2
Remote sensing
Stepwise regression analysis
title_short An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
title_full An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
title_fullStr An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
title_full_unstemmed An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
title_sort An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
author da Costa, Luis Miguel [UNESP]
author_facet da Costa, Luis Miguel [UNESP]
de Araújo Santos, Gustavo André [UNESP]
Panosso, Alan Rodrigo [UNESP]
de Souza Rolim, Glauco [UNESP]
La Scala, Newton [UNESP]
author_role author
author2 de Araújo Santos, Gustavo André [UNESP]
Panosso, Alan Rodrigo [UNESP]
de Souza Rolim, Glauco [UNESP]
La Scala, Newton [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Ciência e Tecnologia do Maranhão – IFMA
Universidade Estadual de Maringá (UEM)
dc.contributor.author.fl_str_mv da Costa, Luis Miguel [UNESP]
de Araújo Santos, Gustavo André [UNESP]
Panosso, Alan Rodrigo [UNESP]
de Souza Rolim, Glauco [UNESP]
La Scala, Newton [UNESP]
dc.subject.por.fl_str_mv Carbon cycle
Climate change
Meteorology
OCO-2
Remote sensing
Stepwise regression analysis
topic Carbon cycle
Climate change
Meteorology
OCO-2
Remote sensing
Stepwise regression analysis
description Background: The recent studies of the variations in the atmospheric column-averaged CO2 concentration (XCO2) above croplands and forests show a negative correlation between XCO2and Sun Induced Chlorophyll Fluorescence (SIF) and confirmed that photosynthesis is the main regulator of the terrestrial uptake for atmospheric CO2. The remote sensing techniques in this context are very important to observe this relation, however, there is still a time gap in orbital data, since the observation is not daily. Here we analyzed the effects of several variables related to the photosynthetic capacity of vegetation on XCO2 above São Paulo state during the period from 2015 to 2019 and propose a daily model to estimate the natural changes in atmospheric CO2. Results: The data retrieved from the Orbiting Carbon Observatory-2 (OCO-2), NASA-POWER and Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) show that Global Radiation (Qg), Sun Induced Chlorophyll Fluorescence (SIF) and, Relative Humidity (RH) are the most significant factors for predicting the annual XCO2 cycle. The daily model of XCO2 estimated from Qg and RH predicts daily XCO2 with root mean squared error of 0.47 ppm (the coefficient of determination is equal to 0.44, p < 0.01). Conclusion: The obtained results imply that a significant part of daily XCO2 variations could be explained by meteorological factors and that further research should be done to quantify the effects of the atmospheric transport and anthropogenic emissions.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-01
2023-03-01T20:49:20Z
2023-03-01T20:49:20Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1186/s13021-022-00209-7
Carbon Balance and Management, v. 17, n. 1, 2022.
1750-0680
http://hdl.handle.net/11449/241153
10.1186/s13021-022-00209-7
2-s2.0-85131821913
url http://dx.doi.org/10.1186/s13021-022-00209-7
http://hdl.handle.net/11449/241153
identifier_str_mv Carbon Balance and Management, v. 17, n. 1, 2022.
1750-0680
10.1186/s13021-022-00209-7
2-s2.0-85131821913
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Carbon Balance and Management
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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