An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
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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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 |
|
_version_ |
1799965094439813120 |