High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions

Autores
Pineda Rojas, Andrea Laura; Borge, Rafael; Mazzeo, Nicolás A.; Saurral, Ramiro Ignacio; Matarazzo, Bruno Nicolas; Cordero, Jose M.; Kropff, Emilio
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, the first long-term (eight years) record of hourly concentrations of carbon monoxide (CO), nitrogen dioxide (NO2) and particulate matter with diameter less than 10 μm (PM10) from three sites in the city of Buenos Aires is analysed. Considering the short-term guidelines suggested by the WHO, the daily mean PM10 concentrations present a relatively large number of exceedances at the three sites. Different statistical techniques are combined to study the relationship between these relatively high PM10 concentrations and relevant surface meteorological variables. For all pollutants and sites, wind speed shows the largest differences between the lowest and highest concentration quartiles. To further explore its role on daily mean PM10 concentration, a k-means algorithm is applied, grouping days with similar surface 1h-wind sequences. Five wind sequence clusters are found, presenting distinctive air quality data features. Two clusters (1 and 2) show that PM10 exceedances occurring with winds entering the city from the river represent between 10 and 21% of total events at the three sites. The frequency of exceedance under these conditions decreases with the distance to the coast. For cluster 1, the hourly PM10 concentration profile and its associated daily wind sequence suggest an important contribution to exceedance events from the city's southernmost power plant. Two clusters (3 and 4), exhibiting continental winds, account for 49–59% of the exceedances and co-occur with relatively drier air conditions. The correlation between CO and PM10 for days belonging to cluster 3 supports the hypothesis of a potential remote or distributed source contribution with SW winds. For cluster 4, differences among sites in the number of events under NNW winds suggest an important contribution from the city's widest avenue to the PM10 levels at the most coastal site. A large contribution coming from urban sources is also indicated for these winds. Finally, cluster 5, exhibiting low wind speed sequences, accounts for 23–33% of the exceedances at the three sites. The average PM10 concentration increases with persistence of this cluster, which could be a driver for exceedances. These results contribute to show the importance of simple methods such as clustering analysis to obtain insights into air quality features such as exceedances and their potential drivers. They also suggest that further efforts in monitoring, modelling and emission estimates may help to better understand local, urban and regional source contributions to these events in the city of Buenos Aires.
Fil: Pineda Rojas, Andrea Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Borge, Rafael. Universidad Politécnica de Madrid; España
Fil: Mazzeo, Nicolás A.. Universidad Tecnológica Nacional. Facultad Regional Avellaneda; Argentina
Fil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Matarazzo, Bruno Nicolas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina
Fil: Cordero, Jose M.. Universidad Politécnica de Madrid; España
Fil: Kropff, Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina
Materia
AIR QUALITY DATA
BUENOS AIRES
EXCEEDANCE CONDITIONS
METEOROLOGICAL DATA
Nivel de accesibilidad
acceso embargado
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/143678

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network_name_str CONICET Digital (CONICET)
spelling High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditionsPineda Rojas, Andrea LauraBorge, RafaelMazzeo, Nicolás A.Saurral, Ramiro IgnacioMatarazzo, Bruno NicolasCordero, Jose M.Kropff, EmilioAIR QUALITY DATABUENOS AIRESEXCEEDANCE CONDITIONSMETEOROLOGICAL DATAhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1In this work, the first long-term (eight years) record of hourly concentrations of carbon monoxide (CO), nitrogen dioxide (NO2) and particulate matter with diameter less than 10 μm (PM10) from three sites in the city of Buenos Aires is analysed. Considering the short-term guidelines suggested by the WHO, the daily mean PM10 concentrations present a relatively large number of exceedances at the three sites. Different statistical techniques are combined to study the relationship between these relatively high PM10 concentrations and relevant surface meteorological variables. For all pollutants and sites, wind speed shows the largest differences between the lowest and highest concentration quartiles. To further explore its role on daily mean PM10 concentration, a k-means algorithm is applied, grouping days with similar surface 1h-wind sequences. Five wind sequence clusters are found, presenting distinctive air quality data features. Two clusters (1 and 2) show that PM10 exceedances occurring with winds entering the city from the river represent between 10 and 21% of total events at the three sites. The frequency of exceedance under these conditions decreases with the distance to the coast. For cluster 1, the hourly PM10 concentration profile and its associated daily wind sequence suggest an important contribution to exceedance events from the city's southernmost power plant. Two clusters (3 and 4), exhibiting continental winds, account for 49–59% of the exceedances and co-occur with relatively drier air conditions. The correlation between CO and PM10 for days belonging to cluster 3 supports the hypothesis of a potential remote or distributed source contribution with SW winds. For cluster 4, differences among sites in the number of events under NNW winds suggest an important contribution from the city's widest avenue to the PM10 levels at the most coastal site. A large contribution coming from urban sources is also indicated for these winds. Finally, cluster 5, exhibiting low wind speed sequences, accounts for 23–33% of the exceedances at the three sites. The average PM10 concentration increases with persistence of this cluster, which could be a driver for exceedances. These results contribute to show the importance of simple methods such as clustering analysis to obtain insights into air quality features such as exceedances and their potential drivers. They also suggest that further efforts in monitoring, modelling and emission estimates may help to better understand local, urban and regional source contributions to these events in the city of Buenos Aires.Fil: Pineda Rojas, Andrea Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Borge, Rafael. Universidad Politécnica de Madrid; EspañaFil: Mazzeo, Nicolás A.. Universidad Tecnológica Nacional. Facultad Regional Avellaneda; ArgentinaFil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Matarazzo, Bruno Nicolas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; ArgentinaFil: Cordero, Jose M.. Universidad Politécnica de Madrid; EspañaFil: Kropff, Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaPergamon-Elsevier Science Ltd2020-11info:eu-repo/date/embargoEnd/2021-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/143678Pineda Rojas, Andrea Laura; Borge, Rafael; Mazzeo, Nicolás A.; Saurral, Ramiro Ignacio; Matarazzo, Bruno Nicolas; et al.; High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions; Pergamon-Elsevier Science Ltd; Atmospheric Environment; 241; 11-2020; 1-37; 1177731352-2310CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S1352231020305057info:eu-repo/semantics/altIdentifier/doi/10.1016/j.atmosenv.2020.117773info:eu-repo/semantics/embargoedAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:41:51Zoai:ri.conicet.gov.ar:11336/143678instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:41:52.001CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
title High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
spellingShingle High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
Pineda Rojas, Andrea Laura
AIR QUALITY DATA
BUENOS AIRES
EXCEEDANCE CONDITIONS
METEOROLOGICAL DATA
title_short High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
title_full High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
title_fullStr High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
title_full_unstemmed High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
title_sort High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions
dc.creator.none.fl_str_mv Pineda Rojas, Andrea Laura
Borge, Rafael
Mazzeo, Nicolás A.
Saurral, Ramiro Ignacio
Matarazzo, Bruno Nicolas
Cordero, Jose M.
Kropff, Emilio
author Pineda Rojas, Andrea Laura
author_facet Pineda Rojas, Andrea Laura
Borge, Rafael
Mazzeo, Nicolás A.
Saurral, Ramiro Ignacio
Matarazzo, Bruno Nicolas
Cordero, Jose M.
Kropff, Emilio
author_role author
author2 Borge, Rafael
Mazzeo, Nicolás A.
Saurral, Ramiro Ignacio
Matarazzo, Bruno Nicolas
Cordero, Jose M.
Kropff, Emilio
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv AIR QUALITY DATA
BUENOS AIRES
EXCEEDANCE CONDITIONS
METEOROLOGICAL DATA
topic AIR QUALITY DATA
BUENOS AIRES
EXCEEDANCE CONDITIONS
METEOROLOGICAL DATA
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this work, the first long-term (eight years) record of hourly concentrations of carbon monoxide (CO), nitrogen dioxide (NO2) and particulate matter with diameter less than 10 μm (PM10) from three sites in the city of Buenos Aires is analysed. Considering the short-term guidelines suggested by the WHO, the daily mean PM10 concentrations present a relatively large number of exceedances at the three sites. Different statistical techniques are combined to study the relationship between these relatively high PM10 concentrations and relevant surface meteorological variables. For all pollutants and sites, wind speed shows the largest differences between the lowest and highest concentration quartiles. To further explore its role on daily mean PM10 concentration, a k-means algorithm is applied, grouping days with similar surface 1h-wind sequences. Five wind sequence clusters are found, presenting distinctive air quality data features. Two clusters (1 and 2) show that PM10 exceedances occurring with winds entering the city from the river represent between 10 and 21% of total events at the three sites. The frequency of exceedance under these conditions decreases with the distance to the coast. For cluster 1, the hourly PM10 concentration profile and its associated daily wind sequence suggest an important contribution to exceedance events from the city's southernmost power plant. Two clusters (3 and 4), exhibiting continental winds, account for 49–59% of the exceedances and co-occur with relatively drier air conditions. The correlation between CO and PM10 for days belonging to cluster 3 supports the hypothesis of a potential remote or distributed source contribution with SW winds. For cluster 4, differences among sites in the number of events under NNW winds suggest an important contribution from the city's widest avenue to the PM10 levels at the most coastal site. A large contribution coming from urban sources is also indicated for these winds. Finally, cluster 5, exhibiting low wind speed sequences, accounts for 23–33% of the exceedances at the three sites. The average PM10 concentration increases with persistence of this cluster, which could be a driver for exceedances. These results contribute to show the importance of simple methods such as clustering analysis to obtain insights into air quality features such as exceedances and their potential drivers. They also suggest that further efforts in monitoring, modelling and emission estimates may help to better understand local, urban and regional source contributions to these events in the city of Buenos Aires.
Fil: Pineda Rojas, Andrea Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Borge, Rafael. Universidad Politécnica de Madrid; España
Fil: Mazzeo, Nicolás A.. Universidad Tecnológica Nacional. Facultad Regional Avellaneda; Argentina
Fil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Matarazzo, Bruno Nicolas. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina
Fil: Cordero, Jose M.. Universidad Politécnica de Madrid; España
Fil: Kropff, Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina
description In this work, the first long-term (eight years) record of hourly concentrations of carbon monoxide (CO), nitrogen dioxide (NO2) and particulate matter with diameter less than 10 μm (PM10) from three sites in the city of Buenos Aires is analysed. Considering the short-term guidelines suggested by the WHO, the daily mean PM10 concentrations present a relatively large number of exceedances at the three sites. Different statistical techniques are combined to study the relationship between these relatively high PM10 concentrations and relevant surface meteorological variables. For all pollutants and sites, wind speed shows the largest differences between the lowest and highest concentration quartiles. To further explore its role on daily mean PM10 concentration, a k-means algorithm is applied, grouping days with similar surface 1h-wind sequences. Five wind sequence clusters are found, presenting distinctive air quality data features. Two clusters (1 and 2) show that PM10 exceedances occurring with winds entering the city from the river represent between 10 and 21% of total events at the three sites. The frequency of exceedance under these conditions decreases with the distance to the coast. For cluster 1, the hourly PM10 concentration profile and its associated daily wind sequence suggest an important contribution to exceedance events from the city's southernmost power plant. Two clusters (3 and 4), exhibiting continental winds, account for 49–59% of the exceedances and co-occur with relatively drier air conditions. The correlation between CO and PM10 for days belonging to cluster 3 supports the hypothesis of a potential remote or distributed source contribution with SW winds. For cluster 4, differences among sites in the number of events under NNW winds suggest an important contribution from the city's widest avenue to the PM10 levels at the most coastal site. A large contribution coming from urban sources is also indicated for these winds. Finally, cluster 5, exhibiting low wind speed sequences, accounts for 23–33% of the exceedances at the three sites. The average PM10 concentration increases with persistence of this cluster, which could be a driver for exceedances. These results contribute to show the importance of simple methods such as clustering analysis to obtain insights into air quality features such as exceedances and their potential drivers. They also suggest that further efforts in monitoring, modelling and emission estimates may help to better understand local, urban and regional source contributions to these events in the city of Buenos Aires.
publishDate 2020
dc.date.none.fl_str_mv 2020-11
info:eu-repo/date/embargoEnd/2021-12-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/143678
Pineda Rojas, Andrea Laura; Borge, Rafael; Mazzeo, Nicolás A.; Saurral, Ramiro Ignacio; Matarazzo, Bruno Nicolas; et al.; High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions; Pergamon-Elsevier Science Ltd; Atmospheric Environment; 241; 11-2020; 1-37; 117773
1352-2310
CONICET Digital
CONICET
url http://hdl.handle.net/11336/143678
identifier_str_mv Pineda Rojas, Andrea Laura; Borge, Rafael; Mazzeo, Nicolás A.; Saurral, Ramiro Ignacio; Matarazzo, Bruno Nicolas; et al.; High PM10 concentrations in the city of Buenos Aires and their relationship with meteorological conditions; Pergamon-Elsevier Science Ltd; Atmospheric Environment; 241; 11-2020; 1-37; 117773
1352-2310
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S1352231020305057
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.atmosenv.2020.117773
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv embargoedAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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