Retrieval of air quality annual statistics from a limited number of profiles

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00603599" target="_blank" >RIV/67985807:_____/24:00603599 - isvavai.cz</a>
Result on the web
<a href="https://www.harmo.org/Conferences/Proceedings/_P%C3%A4rnu/publishedSections/H22-099_Tereza_Pikousova_T3.pdf" target="_blank" >https://www.harmo.org/Conferences/Proceedings/_P%C3%A4rnu/publishedSections/H22-099_Tereza_Pikousova_T3.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Retrieval of air quality annual statistics from a limited number of profiles
Original language description
Annual air quality statistics in an urban environment are usually computed from data collected from a sparsely distributed network of monitoring stations. Complex numeric models may provide air quality simulations at the street level, these simulations, however, are not computationally feasible for large time periods like a year. We propose a method for identification of a limited number of 'typical' days, which, if simulated in microscale, guarantee a reasonable coverage of different scenarios during the year. Annual statistics then can then be estimated on street level from simulated fields. The identification method is based on k-medoids clustering. We also develop a means for validating the approach so as to add confidence in estimates derived in this manner.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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