Evaluation of the influence of micrometeorological data on concentration estimates

A dispersion model for continuous releases of pollutants in the atmospheric boundary layer is applied to study the influence on modelled concentrations of different estimates of the key micrometeorological variables that represent the dispersion processes. The modelling approach is based on the adve...

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Autor principal:	Ulke, A.G.
Formato:	JOUR
Materias:	Air pollution modelling Dispersion model Model evaluation Prairie grass Advection Atmospheric boundary layer Atmospheric movements Advection-diffusion equation Crosswind integrated concentrations Dispersion modeling Prairie Grass Turbulent mechanism Unstable conditions Air pollution airflow boundary layer concentration (composition) data acquisition dispersivity estimation method micrometeorology parameterization pollution monitoring prairie turbulence air pollution Article dispersion meteorology methodology
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_09574352_v55_n1-4_p113_Ulke
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_09574352_v55_n1-4_p113_Ulke
record_format	dspace
spelling	todo:paper_09574352_v55_n1-4_p113_Ulke2023-10-03T15:52:32Z Evaluation of the influence of micrometeorological data on concentration estimates Ulke, A.G. Air pollution modelling Dispersion model Model evaluation Prairie grass Advection Atmospheric boundary layer Atmospheric movements Advection-diffusion equation Air pollution modelling Crosswind integrated concentrations Dispersion modeling Model evaluation Prairie Grass Turbulent mechanism Unstable conditions Air pollution airflow boundary layer concentration (composition) data acquisition dispersivity estimation method micrometeorology parameterization pollution monitoring prairie turbulence air pollution Article boundary layer dispersion meteorology methodology prairie A dispersion model for continuous releases of pollutants in the atmospheric boundary layer is applied to study the influence on modelled concentrations of different estimates of the key micrometeorological variables that represent the dispersion processes. The modelling approach is based on the advection-diffusion equation and includes profiles of wind and eddy diffusivity for the entire atmospheric boundary layer. Their functional forms depend on relevant parameters that represent the turbulent mechanisms in a wide range of stabilities. The Prairie Grass experiments were considered for the evaluation. The model performed satisfactorily in the estimation of the near surface crosswind integrated concentrations. The distinct micrometeorological parameters caused, in general, minor differences in the concentrations. However, a greater impact was found during very stable or unstable conditions. In consequence, in these particular situations, the methodologies to obtain the micrometeorological parameters must be carefully analysed. Copyright © 2014 Inderscience Enterprises Ltd. Fil:Ulke, A.G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_09574352_v55_n1-4_p113_Ulke
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 pollution modelling Dispersion model Model evaluation Prairie grass Advection Atmospheric boundary layer Atmospheric movements Advection-diffusion equation Air pollution modelling Crosswind integrated concentrations Dispersion modeling Model evaluation Prairie Grass Turbulent mechanism Unstable conditions Air pollution airflow boundary layer concentration (composition) data acquisition dispersivity estimation method micrometeorology parameterization pollution monitoring prairie turbulence air pollution Article boundary layer dispersion meteorology methodology prairie
spellingShingle	Air pollution modelling Dispersion model Model evaluation Prairie grass Advection Atmospheric boundary layer Atmospheric movements Advection-diffusion equation Air pollution modelling Crosswind integrated concentrations Dispersion modeling Model evaluation Prairie Grass Turbulent mechanism Unstable conditions Air pollution airflow boundary layer concentration (composition) data acquisition dispersivity estimation method micrometeorology parameterization pollution monitoring prairie turbulence air pollution Article boundary layer dispersion meteorology methodology prairie Ulke, A.G. Evaluation of the influence of micrometeorological data on concentration estimates
topic_facet	Air pollution modelling Dispersion model Model evaluation Prairie grass Advection Atmospheric boundary layer Atmospheric movements Advection-diffusion equation Air pollution modelling Crosswind integrated concentrations Dispersion modeling Model evaluation Prairie Grass Turbulent mechanism Unstable conditions Air pollution airflow boundary layer concentration (composition) data acquisition dispersivity estimation method micrometeorology parameterization pollution monitoring prairie turbulence air pollution Article boundary layer dispersion meteorology methodology prairie
description	A dispersion model for continuous releases of pollutants in the atmospheric boundary layer is applied to study the influence on modelled concentrations of different estimates of the key micrometeorological variables that represent the dispersion processes. The modelling approach is based on the advection-diffusion equation and includes profiles of wind and eddy diffusivity for the entire atmospheric boundary layer. Their functional forms depend on relevant parameters that represent the turbulent mechanisms in a wide range of stabilities. The Prairie Grass experiments were considered for the evaluation. The model performed satisfactorily in the estimation of the near surface crosswind integrated concentrations. The distinct micrometeorological parameters caused, in general, minor differences in the concentrations. However, a greater impact was found during very stable or unstable conditions. In consequence, in these particular situations, the methodologies to obtain the micrometeorological parameters must be carefully analysed. Copyright © 2014 Inderscience Enterprises Ltd.
format	JOUR
author	Ulke, A.G.
author_facet	Ulke, A.G.
author_sort	Ulke, A.G.
title	Evaluation of the influence of micrometeorological data on concentration estimates
title_short	Evaluation of the influence of micrometeorological data on concentration estimates
title_full	Evaluation of the influence of micrometeorological data on concentration estimates
title_fullStr	Evaluation of the influence of micrometeorological data on concentration estimates
title_full_unstemmed	Evaluation of the influence of micrometeorological data on concentration estimates
title_sort	evaluation of the influence of micrometeorological data on concentration estimates
url	http://hdl.handle.net/20.500.12110/paper_09574352_v55_n1-4_p113_Ulke
work_keys_str_mv	AT ulkeag evaluationoftheinfluenceofmicrometeorologicaldataonconcentrationestimates
_version_	1782030623455576064

Evaluation of the influence of micrometeorological data on concentration estimates

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