Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations

An application of a simple urban air quality model (DAUMOD-GRS) shows that summer maximum O3 hourly concentrations (Cmax) above 40 ppb occur outside the Metropolitan Area of Buenos Aires (MABA) where the absence of observations impedes model testing. In addition, those relatively high values present...

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Autores principales: Pineda Rojas, A.L., Mazzeo, N.A., Castelli S.T., Di Sabatino S., Brattich E., ARIANET srl-Aria Technologies SA; Combustion Ltd.; Eurelettronica ICAS; Lombard and Marozzini srl
Formato: CONF
Materias:
Air quality modelling
Buenos Aires
Clustering analysis
Monte Carlo analysis
Ozone
Air quality
Monte Carlo methods
Quality control
Uncertainty analysis
Model uncertainties
Monte carlo analysis
Peak ozone concentration
Probability assessments
Urban air quality
Atmospheric movements
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_NIS17737_v2017-October_n_p566_PinedaRojas
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_NIS17737_v2017-October_n_p566_PinedaRojas
record_format dspace
spelling todo:paper_NIS17737_v2017-October_n_p566_PinedaRojas2023-10-03T16:45:56Z Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations Pineda Rojas, A.L. Mazzeo, N.A. Castelli S.T. Di Sabatino S. Brattich E. ARIANET srl-Aria Technologies SA; Combustion Ltd.; Eurelettronica ICAS; Lombard and Marozzini srl Air quality modelling Buenos Aires Clustering analysis Monte Carlo analysis Ozone Air quality Monte Carlo methods Ozone Quality control Uncertainty analysis Air quality modelling Buenos Aires Clustering analysis Model uncertainties Monte carlo analysis Peak ozone concentration Probability assessments Urban air quality Atmospheric movements An application of a simple urban air quality model (DAUMOD-GRS) shows that summer maximum O3 hourly concentrations (Cmax) above 40 ppb occur outside the Metropolitan Area of Buenos Aires (MABA) where the absence of observations impedes model testing. In addition, those relatively high values present the greatest model uncertainty caused by possible errors in model input variables. In order to tackle this issue, a probability assessment of Cmax values exceeding 40 ppb is performed applying a Monte Carlo analysis. On the other hand, a non-hierarchical (k-means) clustering analyses is applied to analyse the Monte Carlo outcomes. Results show three main clusters with a marked spatial distribution resembling that of the ozone precursor species emissions, which highlights an important role of the emissions on the regimes under which modelled Cmax values in the MABA can occur. © 2018 Hungarian Meteorological Service. All Rights Reserved. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_NIS17737_v2017-October_n_p566_PinedaRojas
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Air quality modelling
Buenos Aires
Clustering analysis
Monte Carlo analysis
Ozone
Air quality
Monte Carlo methods
Ozone
Quality control
Uncertainty analysis
Air quality modelling
Buenos Aires
Clustering analysis
Model uncertainties
Monte carlo analysis
Peak ozone concentration
Probability assessments
Urban air quality
Atmospheric movements
spellingShingle Air quality modelling
Buenos Aires
Clustering analysis
Monte Carlo analysis
Ozone
Air quality
Monte Carlo methods
Ozone
Quality control
Uncertainty analysis
Air quality modelling
Buenos Aires
Clustering analysis
Model uncertainties
Monte carlo analysis
Peak ozone concentration
Probability assessments
Urban air quality
Atmospheric movements
Pineda Rojas, A.L.
Mazzeo, N.A.
Castelli S.T.
Di Sabatino S.
Brattich E.
ARIANET srl-Aria Technologies SA; Combustion Ltd.; Eurelettronica ICAS; Lombard and Marozzini srl
Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
topic_facet Air quality modelling
Buenos Aires
Clustering analysis
Monte Carlo analysis
Ozone
Air quality
Monte Carlo methods
Ozone
Quality control
Uncertainty analysis
Air quality modelling
Buenos Aires
Clustering analysis
Model uncertainties
Monte carlo analysis
Peak ozone concentration
Probability assessments
Urban air quality
Atmospheric movements
description An application of a simple urban air quality model (DAUMOD-GRS) shows that summer maximum O3 hourly concentrations (Cmax) above 40 ppb occur outside the Metropolitan Area of Buenos Aires (MABA) where the absence of observations impedes model testing. In addition, those relatively high values present the greatest model uncertainty caused by possible errors in model input variables. In order to tackle this issue, a probability assessment of Cmax values exceeding 40 ppb is performed applying a Monte Carlo analysis. On the other hand, a non-hierarchical (k-means) clustering analyses is applied to analyse the Monte Carlo outcomes. Results show three main clusters with a marked spatial distribution resembling that of the ozone precursor species emissions, which highlights an important role of the emissions on the regimes under which modelled Cmax values in the MABA can occur. © 2018 Hungarian Meteorological Service. All Rights Reserved.
format CONF
author Pineda Rojas, A.L.
Mazzeo, N.A.
Castelli S.T.
Di Sabatino S.
Brattich E.
ARIANET srl-Aria Technologies SA; Combustion Ltd.; Eurelettronica ICAS; Lombard and Marozzini srl
author_facet Pineda Rojas, A.L.
Mazzeo, N.A.
Castelli S.T.
Di Sabatino S.
Brattich E.
ARIANET srl-Aria Technologies SA; Combustion Ltd.; Eurelettronica ICAS; Lombard and Marozzini srl
author_sort Pineda Rojas, A.L.
title Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
title_short Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
title_full Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
title_fullStr Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
title_full_unstemmed Clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
title_sort clustering of atmospheric and emission conditions that lead to modelled peak ozone concentrations
url http://hdl.handle.net/20.500.12110/paper_NIS17737_v2017-October_n_p566_PinedaRojas
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AT mazzeona clusteringofatmosphericandemissionconditionsthatleadtomodelledpeakozoneconcentrations
AT castellist clusteringofatmosphericandemissionconditionsthatleadtomodelledpeakozoneconcentrations
AT disabatinos clusteringofatmosphericandemissionconditionsthatleadtomodelledpeakozoneconcentrations
AT brattiche clusteringofatmosphericandemissionconditionsthatleadtomodelledpeakozoneconcentrations
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