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    0585437 - ÚI 2025 RIV CH eng L2 - Special Maps
    Geletič, Jan - Bauerová, P. - Belda, M. - Bureš, Martin - Eben, Kryštof - Fuka, V. - Jareš, R. - Karel, J. - Krč, Pavel - Patiño, W. - Radović, J. - Resler, Jaroslav - Řezníček, Hynek - Vlček, O.
    Maps of the detailed spatially and temporally attributed emission for area of Legerova and Sokolska (TURBAN-D18).
    Internal code: TURBAN-D18 ; 2024
    Technical parameters: Each selected epizode (s1-s6) has three subfolders; input files in ASCII (output-ascii) or GeoTiff (output-gis) formats that can be viewed in many GIS applications. In the third subfolder are maps in the PNG format (output-png). Each subfolder includes 4 subfolders with emissions summarized in all layers above ground. Variable vsrc_PM10 is the concentration of volume source emissions (VSRC) of the PM10, vsrc_PM25 is the concentration of PM2.5, vsrc_NO is the concentration of NO and vsrc_NO2 is the concentration of NO2. Each file (PRJ, TIF, ASC or PNG) has the same nomenclature. An example (vsrc_NO_abs-01h_20220717_1200-1300.png) could be parsed as: variable name (vsrc_NO), processed input (abs-01h), date (20220717) and period (1200-1300). So, the result is a map with emission fluxes of NO between 12:00 and 13:00 UTC 24 Jul 2019.
    Economic parameters: This dataset contains six folders with maps of input data for simulations published in project TURBAN as result D17 (see https://zenodo.org/records/10982836). Each folder contains air quality inputs for the so-called Legerova domain, an area in the city of Prague, Czech Republic, centred around the traffic-heavy streets Legerova and Sokolská. They are the first outputs in a similar level of detail simulated using LES and freely available for state administration. It is available under CC BY 4.0 Licence.
    R&D Projects: GA TA ČR(CZ) TO01000219
    Institutional support: RVO:67985807
    Keywords : air quality * air pollution * GIS
    OECD category: Meteorology and atmospheric sciences
    https://doi.org/10.5281/zenodo.10993880
    Permanent Link: https://hdl.handle.net/11104/0353146
     

    Research data: Zenodo.org
     

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