Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models

The application of the multivariate curve resolution method to the analysis of temporal and spatial data variability of hourly measured O3 and NO2 concentrations at nineteen air quality monitoring stations across Catalonia, Spain, during 2015 is shown. Data analyzed included ground-based experimenta...

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Autores: Platikanov, Stefan, Terrado, Marta, Pay, María Teresa, Soret, Albert, Tauler, Romà
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/253921
Acceso en línea:http://hdl.handle.net/10261/253921
Access Level:acceso abierto
Palabra clave:Air quality modelling
Chemometrics
MCR-ALS
Ozone
Nitrogen dioxide
CALIOPE system
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spelling Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport modelsPlatikanov, StefanTerrado, MartaPay, María TeresaSoret, AlbertTauler, RomàAir quality modellingChemometricsMCR-ALSOzoneNitrogen dioxideCALIOPE systemThe application of the multivariate curve resolution method to the analysis of temporal and spatial data variability of hourly measured O3 and NO2 concentrations at nineteen air quality monitoring stations across Catalonia, Spain, during 2015 is shown. Data analyzed included ground-based experimental measurements and predicted concentrations by the CALIOPE air quality modelling system at three horizontal resolutions (Europe at 12 × 12 km2, Iberian Peninsula at 4 × 4 km2 and Catalonia at 1 × 1 km2). Results obtained in the analysis of these different data sets allowed a better understanding of O3 and NO2 concentration changes as a sum of a small number of different contributions related to daily sunlight radiation, seasonal dynamics, traffic emission patterns, and local station environments (urban, suburban and rural). The evaluation of O3 and NO2 concentrations predicted by the CALIOPE system revealed some differences among data sets at different spatial resolutions. NO2 predictions, showed in general a better performance than O3 predictions for the three model resolutions, specially at urban stations. Our results confirmed that the application of the trilinearity constraint during the multivariate curve resolution factor analysis decomposition of the analyzed data sets is a useful tool to facilitate the understanding of the resolved variability sources.SP and RT would like to acknowledge the Spanish Ministerio de Ciencia e Innovación for the project PID2019-105732GB-C21. SP and RT work at IDAEA-CSIC which is a Center of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018-000794-S). MTP would like to acknowledge the Spanish Ministry of Economy and Competitiveness and FEDER funds under the PAISA (CGL2016-75725-R) project.Peer reviewedElsevierMinisterio de Ciencia e Innovación (España)Tauler, Romà [0000-0001-8559-9670]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202120212021info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/253921reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CEX2018-000794-Sinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105732GB-C21https://doi.org/10.1016/j.scitotenv.2021.150923Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2539212026-05-22T06:33:51Z
dc.title.none.fl_str_mv Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
title Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
spellingShingle Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
Platikanov, Stefan
Air quality modelling
Chemometrics
MCR-ALS
Ozone
Nitrogen dioxide
CALIOPE system
title_short Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
title_full Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
title_fullStr Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
title_full_unstemmed Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
title_sort Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models
dc.creator.none.fl_str_mv Platikanov, Stefan
Terrado, Marta
Pay, María Teresa
Soret, Albert
Tauler, Romà
author Platikanov, Stefan
author_facet Platikanov, Stefan
Terrado, Marta
Pay, María Teresa
Soret, Albert
Tauler, Romà
author_role author
author2 Terrado, Marta
Pay, María Teresa
Soret, Albert
Tauler, Romà
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (España)
Tauler, Romà [0000-0001-8559-9670]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Air quality modelling
Chemometrics
MCR-ALS
Ozone
Nitrogen dioxide
CALIOPE system
topic Air quality modelling
Chemometrics
MCR-ALS
Ozone
Nitrogen dioxide
CALIOPE system
description The application of the multivariate curve resolution method to the analysis of temporal and spatial data variability of hourly measured O3 and NO2 concentrations at nineteen air quality monitoring stations across Catalonia, Spain, during 2015 is shown. Data analyzed included ground-based experimental measurements and predicted concentrations by the CALIOPE air quality modelling system at three horizontal resolutions (Europe at 12 × 12 km2, Iberian Peninsula at 4 × 4 km2 and Catalonia at 1 × 1 km2). Results obtained in the analysis of these different data sets allowed a better understanding of O3 and NO2 concentration changes as a sum of a small number of different contributions related to daily sunlight radiation, seasonal dynamics, traffic emission patterns, and local station environments (urban, suburban and rural). The evaluation of O3 and NO2 concentrations predicted by the CALIOPE system revealed some differences among data sets at different spatial resolutions. NO2 predictions, showed in general a better performance than O3 predictions for the three model resolutions, specially at urban stations. Our results confirmed that the application of the trilinearity constraint during the multivariate curve resolution factor analysis decomposition of the analyzed data sets is a useful tool to facilitate the understanding of the resolved variability sources.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/253921
url http://hdl.handle.net/10261/253921
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CEX2018-000794-S
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105732GB-C21
https://doi.org/10.1016/j.scitotenv.2021.150923
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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