Retrieval of Annual Air Quality Statistics from a Limited Number of LES Model Simulations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00604658" target="_blank" >RIV/67985807:_____/24:00604658 - isvavai.cz</a>

Výsledek na webu

<a href="https://palm.muk.uni-hannover.de/trac/raw-attachment/wiki/conference/pmc24_book_of_abstracts.pdf" target="_blank" >https://palm.muk.uni-hannover.de/trac/raw-attachment/wiki/conference/pmc24_book_of_abstracts.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Retrieval of Annual Air Quality Statistics from a Limited Number of LES Model Simulations

Popis výsledku v původním jazyce

ZÁKLADNÍ ÚDAJE: PMC 24 Book of Abstracts. Offenbach: Leibniz University Hannover (LUH) and the German Weather Service (DWD), 2024. s. 7-7. [PMC 24: PALM Model Conference 2024. 17.09.2024-20.09.2024, Offenbach] ABSTRAKT: Legislative air quality limits are based on annual statistics, like annual mean or n-th highest hourly or daily concentration. Complex CFD models may provide air quality simulations at the street level. However, these simulations are computationally too expensive for large time periods like a year. For RANS models this is usually solved by calculation of steady-state concentration fields for different wind directions, which are then scaled by the wind speed to provide concentrations for a particular hour. However this approach is not suitable for the LES models, which count for time-evolving resolved turbulence. With these models usually several periods of time extent of days are calculated. Annual statistics have to be constructed from a limited number of ’typical’ days, which guarantee a reasonable coverage of different scenarios during the year. We propose a method for identification of ’typical’ days based on k-medoids clustering. The method was validated on monitoring stations. We also demonstrate its performance on pilot PALM simulations. Target of this pilot experiment is to prove the potential to retrieve the fields of annual statistics from LES models.

Název v anglickém jazyce

Retrieval of Annual Air Quality Statistics from a Limited Number of LES Model Simulations

Popis výsledku anglicky

ZÁKLADNÍ ÚDAJE: PMC 24 Book of Abstracts. Offenbach: Leibniz University Hannover (LUH) and the German Weather Service (DWD), 2024. s. 7-7. [PMC 24: PALM Model Conference 2024. 17.09.2024-20.09.2024, Offenbach] ABSTRAKT: Legislative air quality limits are based on annual statistics, like annual mean or n-th highest hourly or daily concentration. Complex CFD models may provide air quality simulations at the street level. However, these simulations are computationally too expensive for large time periods like a year. For RANS models this is usually solved by calculation of steady-state concentration fields for different wind directions, which are then scaled by the wind speed to provide concentrations for a particular hour. However this approach is not suitable for the LES models, which count for time-evolving resolved turbulence. With these models usually several periods of time extent of days are calculated. Annual statistics have to be constructed from a limited number of ’typical’ days, which guarantee a reasonable coverage of different scenarios during the year. We propose a method for identification of ’typical’ days based on k-medoids clustering. The method was validated on monitoring stations. We also demonstrate its performance on pilot PALM simulations. Target of this pilot experiment is to prove the potential to retrieve the fields of annual statistics from LES models.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů