Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)

Autores
Lopez Noreña, Ana; Berná, Lucas; Tames, Florencia; Puliafito, Enrique; Fernandez, Rafael
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
The temporal and spatial resolution of the emission inventory included into an air quality model plays a key role in the appropriate representation of air pollution events and background atmospheric chemistry. Here, we use the Weather Research and Forecasting coupled with Chemistry (WRF-Chem v4.0) model to perform highresolution air quality simulations over the city of Buenos Aires, Argentina, with two different anthropogenic emissions datasets: the High-resolution Emissions Inventory of Argentina (GEAA-AEI) and the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP). A local optimized configuration considering 3 nested domains with a horizontal grid size of 20 × 20 km, 4 × 4 km, and 1.3 × 1.3 km and the MOZART chemical scheme was used. The model performance for NO2, PM10, PM2.5, and O3 concentrations was validated against measurements from the existing air quality monitoring stations in the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. Our results show that the daytime concentrations of air pollutants are influenced by the shape and shift of the hourly emissions profile, especially for NO2 where the reduction in nighttime emissions decreased the mean model bias by ~50%. PM10 and PM2.5 generally satisfied the model performance criteria, but underestimation tended to occur in the GEAA-AEI simulations and overestimation for the EDGAR-HTAP case. Comparison with TROPOMI-derived tropospheric NO2 columns showed a high positive correlation (r > 0.75) and a positive bias. We found large discrepancies between the spatial distribution patterns of the simulations within the innermost high-resolution domain centered on AMBA, mostly in suburban areas where no observations are available. We propose additional monitoring sites to address such differences and determine the size and shape of the main pollutant plume. We conclude that high-resolution air quality modeling is important within underdeveloped or developing South American cities that lack continuous air quality measurements, as it represents a powerful tool in supporting the design of governmental monitoring networks and air pollution mitigation policies.
Fil: Universidad Tecnológica Nacional. Facultad Regional Mendoza, Argentina
Peer Reviewed
Fuente
Atmospheric Environment 269, (2021)
Materia
WRF-Chem, High resolution emissions inventory, South America air quality modeling, GEAA-AEI, EDGAR-HTAP, TROPOMI
Nivel de accesibilidad
acceso abierto
Condiciones de uso
2024-08-08T13:43:09Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/11275
Acceder
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oai_identifier_str oai:ria.utn.edu.ar:20.500.12272/11275
network_acronym_str RIAUTN
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network_name_str Repositorio Institucional Abierto (UTN)
spelling Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)Lopez Noreña, AnaBerná, LucasTames, FlorenciaPuliafito, EnriqueFernandez, RafaelWRF-Chem, High resolution emissions inventory, South America air quality modeling, GEAA-AEI, EDGAR-HTAP, TROPOMIThe temporal and spatial resolution of the emission inventory included into an air quality model plays a key role in the appropriate representation of air pollution events and background atmospheric chemistry. Here, we use the Weather Research and Forecasting coupled with Chemistry (WRF-Chem v4.0) model to perform highresolution air quality simulations over the city of Buenos Aires, Argentina, with two different anthropogenic emissions datasets: the High-resolution Emissions Inventory of Argentina (GEAA-AEI) and the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP). A local optimized configuration considering 3 nested domains with a horizontal grid size of 20 × 20 km, 4 × 4 km, and 1.3 × 1.3 km and the MOZART chemical scheme was used. The model performance for NO2, PM10, PM2.5, and O3 concentrations was validated against measurements from the existing air quality monitoring stations in the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. Our results show that the daytime concentrations of air pollutants are influenced by the shape and shift of the hourly emissions profile, especially for NO2 where the reduction in nighttime emissions decreased the mean model bias by ~50%. PM10 and PM2.5 generally satisfied the model performance criteria, but underestimation tended to occur in the GEAA-AEI simulations and overestimation for the EDGAR-HTAP case. Comparison with TROPOMI-derived tropospheric NO2 columns showed a high positive correlation (r > 0.75) and a positive bias. We found large discrepancies between the spatial distribution patterns of the simulations within the innermost high-resolution domain centered on AMBA, mostly in suburban areas where no observations are available. We propose additional monitoring sites to address such differences and determine the size and shape of the main pollutant plume. We conclude that high-resolution air quality modeling is important within underdeveloped or developing South American cities that lack continuous air quality measurements, as it represents a powerful tool in supporting the design of governmental monitoring networks and air pollution mitigation policies.Fil: Universidad Tecnológica Nacional. Facultad Regional Mendoza, ArgentinaPeer Reviewed2024-08-08T13:43:09Z2024-08-08T13:43:09Z2021-11-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfAtmospheric Environmenthttp://hdl.handle.net/20.500.12272/11275https://doi.org/10.1016/j.atmosenv.2021.118839Atmospheric Environment 269, (2021)reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacionalenginfo:eu-repo/semantics/openAccess2024-08-08T13:43:09Zhttp://creativecommons.org/publicdomain/zero/1.0/CC0 1.0 UniversalUniversidad Tecnológica Nacional. Facultad Regional MendozaCC BY (Autoría) CC BY-NC (Autoría – No Comercial)2026-09-24T12:43:54Zoai:ria.utn.edu.ar:20.500.12272/11275instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:43:55.9Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
title Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
spellingShingle Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
Lopez Noreña, Ana
WRF-Chem, High resolution emissions inventory, South America air quality modeling, GEAA-AEI, EDGAR-HTAP, TROPOMI
title_short Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
title_full Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
title_fullStr Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
title_full_unstemmed Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
title_sort Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
dc.creator.none.fl_str_mv Lopez Noreña, Ana
Berná, Lucas
Tames, Florencia
Puliafito, Enrique
Fernandez, Rafael
author Lopez Noreña, Ana
author_facet Lopez Noreña, Ana
Berná, Lucas
Tames, Florencia
Puliafito, Enrique
Fernandez, Rafael
author_role author
author2 Berná, Lucas
Tames, Florencia
Puliafito, Enrique
Fernandez, Rafael
author2_role author
author
author
author
dc.subject.none.fl_str_mv WRF-Chem, High resolution emissions inventory, South America air quality modeling, GEAA-AEI, EDGAR-HTAP, TROPOMI
topic WRF-Chem, High resolution emissions inventory, South America air quality modeling, GEAA-AEI, EDGAR-HTAP, TROPOMI
dc.description.none.fl_txt_mv The temporal and spatial resolution of the emission inventory included into an air quality model plays a key role in the appropriate representation of air pollution events and background atmospheric chemistry. Here, we use the Weather Research and Forecasting coupled with Chemistry (WRF-Chem v4.0) model to perform highresolution air quality simulations over the city of Buenos Aires, Argentina, with two different anthropogenic emissions datasets: the High-resolution Emissions Inventory of Argentina (GEAA-AEI) and the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP). A local optimized configuration considering 3 nested domains with a horizontal grid size of 20 × 20 km, 4 × 4 km, and 1.3 × 1.3 km and the MOZART chemical scheme was used. The model performance for NO2, PM10, PM2.5, and O3 concentrations was validated against measurements from the existing air quality monitoring stations in the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. Our results show that the daytime concentrations of air pollutants are influenced by the shape and shift of the hourly emissions profile, especially for NO2 where the reduction in nighttime emissions decreased the mean model bias by ~50%. PM10 and PM2.5 generally satisfied the model performance criteria, but underestimation tended to occur in the GEAA-AEI simulations and overestimation for the EDGAR-HTAP case. Comparison with TROPOMI-derived tropospheric NO2 columns showed a high positive correlation (r > 0.75) and a positive bias. We found large discrepancies between the spatial distribution patterns of the simulations within the innermost high-resolution domain centered on AMBA, mostly in suburban areas where no observations are available. We propose additional monitoring sites to address such differences and determine the size and shape of the main pollutant plume. We conclude that high-resolution air quality modeling is important within underdeveloped or developing South American cities that lack continuous air quality measurements, as it represents a powerful tool in supporting the design of governmental monitoring networks and air pollution mitigation policies.
Fil: Universidad Tecnológica Nacional. Facultad Regional Mendoza, Argentina
Peer Reviewed
description The temporal and spatial resolution of the emission inventory included into an air quality model plays a key role in the appropriate representation of air pollution events and background atmospheric chemistry. Here, we use the Weather Research and Forecasting coupled with Chemistry (WRF-Chem v4.0) model to perform highresolution air quality simulations over the city of Buenos Aires, Argentina, with two different anthropogenic emissions datasets: the High-resolution Emissions Inventory of Argentina (GEAA-AEI) and the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP). A local optimized configuration considering 3 nested domains with a horizontal grid size of 20 × 20 km, 4 × 4 km, and 1.3 × 1.3 km and the MOZART chemical scheme was used. The model performance for NO2, PM10, PM2.5, and O3 concentrations was validated against measurements from the existing air quality monitoring stations in the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. Our results show that the daytime concentrations of air pollutants are influenced by the shape and shift of the hourly emissions profile, especially for NO2 where the reduction in nighttime emissions decreased the mean model bias by ~50%. PM10 and PM2.5 generally satisfied the model performance criteria, but underestimation tended to occur in the GEAA-AEI simulations and overestimation for the EDGAR-HTAP case. Comparison with TROPOMI-derived tropospheric NO2 columns showed a high positive correlation (r > 0.75) and a positive bias. We found large discrepancies between the spatial distribution patterns of the simulations within the innermost high-resolution domain centered on AMBA, mostly in suburban areas where no observations are available. We propose additional monitoring sites to address such differences and determine the size and shape of the main pollutant plume. We conclude that high-resolution air quality modeling is important within underdeveloped or developing South American cities that lack continuous air quality measurements, as it represents a powerful tool in supporting the design of governmental monitoring networks and air pollution mitigation policies.
publishDate 2021
dc.date.none.fl_str_mv 2021-11-01
2024-08-08T13:43:09Z
2024-08-08T13:43:09Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv Atmospheric Environment
http://hdl.handle.net/20.500.12272/11275
https://doi.org/10.1016/j.atmosenv.2021.118839
identifier_str_mv Atmospheric Environment
url http://hdl.handle.net/20.500.12272/11275
https://doi.org/10.1016/j.atmosenv.2021.118839
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-08-08T13:43:09Z
http://creativecommons.org/publicdomain/zero/1.0/
CC0 1.0 Universal
Universidad Tecnológica Nacional. Facultad Regional Mendoza
CC BY (Autoría) CC BY-NC (Autoría – No Comercial)
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-08-08T13:43:09Z
http://creativecommons.org/publicdomain/zero/1.0/
CC0 1.0 Universal
Universidad Tecnológica Nacional. Facultad Regional Mendoza
CC BY (Autoría) CC BY-NC (Autoría – No Comercial)
dc.format.none.fl_str_mv pdf
application/pdf
dc.source.none.fl_str_mv Atmospheric Environment 269, (2021)
reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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