Published April 18, 2024 | Version 1
Dataset Open

Maps of the detailed spatially and temporally attributed emission for area of Legerova and Sokolska (TURBAN-D18)

  • 1. ROR icon Czech Academy of Sciences, Institute of Computer Science
  • 2. ROR icon Czech Hydrometeorological Institute
  • 3. Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University
  • 4. ROR icon Studio of Ecological Models

Description

Basic information

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. All times are in UTC (local time in winter, CET, is UTC +01:00, summer time, CEST, is UTC +02:00). In total 6 episodes in 2022 and 2023 were selected:

  1. s1 2022-07-17 00:00:00 - 2022-07-20 00:00:00
  2. s2: 2022-08-02 00:00:00 - 2022-08-05 00:00:00
  3. s3: 2022-09-22 00:00:00 - 2022-09-25 00:00:00
  4. s4: 2022-12-08 00:00:00 - 2022-12-11 00:00:00
  5. s5: 2023-01-27 00:00:00 - 2023-01-30 00:00:00
  6. s6: 2023-02-13 00:00:00 - 2023-02-16 00:00:00

For more detailed description of the experiments see the TURBAN project website at https://www.project-turban.eu/.

General organisation, variables and file nomenclature

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.

Emissions (see section 2.4.3 in Resler et al., 2024)

The data were processed from datasets published by CHMI, data collected by the Municipality of Prague and its organizations, data obtained by the researcher (ATEM) while providing expert studies in the past, and results of previous research projects. The input data of the used emission sources can be divided into two basic groups: emission from local heating and transport sources.

Emissions for local heating were determined by calculations based on data from CHMI and the Czech Statistical Office (CZSO). Emissions from the transport sources were modeled using the MEFA transportation emission model which is recommended for the use in the Czech Republic by the Ministry of Environment of the Czech Republic. The model takes into account factors such as road gradient, the number of vehicles on the road, the flow of traffic, the composition of car types, and the emission characteristics of the individual car types. The emission calculation is based on data from the traffic census provided by the Prague Technical Administration of Roads (TSK Praha) and on data from the census of the composition of the transportation fleet in Prague built in the MEFA emission model. The data are based on regular surveys of the fleet composition carried out in Prague (Karel et al., 2021). The dust resuspension was computed according to the methodology published by the Ministry of Environment (Karel et. al., 2015). This methodology is based on US EPA methodology AP-42 (EPA, 2011) and was adjusted for the conditions of the Czech Republic. For the garages and parking lots, the results of the project TH03030496 (Karel et al., 2020) were used and for the bus stations, publicly available data about transportation were gathered from the Prague Public Transit Company (DPP).

The disaggregation of the annual emissions into hourly intervals was then performed according to the type of source. For combustion sources distribution of emissions to days was done according to natural gas supply profiles for category DOM4 were used (OTE, 2024) and complemented by daily profiles for SNAP 2 (van der Gon, 2011). For transport sources, the census data from TSK Praha was utilized for all streets where it was available. For Legerova and Sokolská streets, hourly traffic intensity data were obtained and used directly for the selected episodes. For streets that were not covered by regular traffic surveys, the spatial and temporal distribution of the traffic intensities were based on analysis and evaluation of the relevant studies for the particular area (e.g. urban planning studies, Environmental Impact Assessment (EIA), etc.) and combined with information like street type, location, traffic regime, and pavement type. This approach allowed us to specify the distribution of the transportation intensities on smaller streets. For the detailed modeling of emissions from rail transport (diesel locomotives), the data of train rides were obtained from the Railway Administration (SŽ) and emission factors from the EMEP/EEA Air Pollutant Emission Inventory Guidebook 2019 (EEA, 2019) were used. Emissions from river ships were obtained from the CHMI national database and spatially distributed to the area of the river.

Spatial transformation of the line and point emission into the corresponding areas was done with the utilization of the surrogates representing corresponding areas (e.g. areas of the street traffic lines and parking places for traffic emission and areas of the building roofs for local heating sources). This not only ensured the reasonable spatial distribution of the emission in the street canyon but also decreased the gradients of the emission field and with this proneness of the model to numerical inaccuracy of the micro-scale model. The processing of the emission sources into hourly emission flows was done in the emission model FUME recently extended for processing of the PALM emission (Belda et al., 2024).

Acknowledgements

The PALM simulations, and pre- and postprocessing were performed partially on the HPC infrastructure of the Institute of Computer Science of the Czech Academy of Sciences (ICS), supported by the long-term strategic development financing of the ICS (RVO:67985807) and partially on the IT4I HPC infrastructure supported by the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90254). The work was performed within the project TURBAN (TO01000219; TURBAN – Turbulent-resolving urban modelling of air quality and thermal comfort) supported by Norway Grants and Technology Agency of the Czech Republic.

Literature

Note that some sources are available only in Czech language.

Belda, M., et al. (2024) FUME 2.0 – Flexible Universal processor for Modeling Emissions, EGUsphere [preprint]. https://doi.org/10.5194/egusphere-2023-2740

Karel, J., et al. (2020) Projekt TH03030496 - Zmapování a emisní bilance neevidovaných zdrojů emisí znečišťujících látek na území městských aglomerací. Mapa neevidovaných zdrojů emisí znečišťujících látek na území aglomerace CZ01 Praha. Partially available at: https://www.atem.cz/neevidovane_zdroje.php

Karel, J., et al. (2015) Metodika pro výpočet emisí částic pocházejících z resuspenze ze silniční dopravy, CENEST, s. r. o., Prague. Available at: https://www.mzp.cz/C1257458002F0DC7/cz/doprava/$FILE/OOO-resuspenze_metodika-20190708.pdf

Karel J., et. al. (2021) Zpráva o dynamické skladbě vozového parku na území hlavního města Prahy v roce 2020, Prague 2021. Available upon request from the Environmental Protection Division of the Prague Municipality.

EPA (2011) Compilation of Air Pollutant Emission Factors, Volume I, AP-42. Section 13.2.1. Paved roads. EPA Research Triangle Park, US, 2003, updated 2011. Available at: https://www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-air-emissions-factors-stationary-sources

van der Gon, H.D., et al. (2011) Description of Current Temporal Emission Patterns and Sensitivity of Predicted AQ for Temporal Emission Patterns. EU FP7 MACC Deliverable Report D_D-EMIS_1.3. Available at: https://atmosphere.copernicus.eu/sites/default/files/2019-07/MACC_TNO_del_1_3_v2.pdf

EEA (2019) European Environment Agency, EMEP/EEA air pollutant emission inventory guidebook 2019 – Technical guidance to prepare national emission inventories, Publications Office. Available at: https://data.europa.eu/doi/10.2800/293657

OTE (2024) Gas Load Profiles - temperature and recalculated TDD. Available at: https://www.ote-cr.cz/en/statistics/gas-load-profiles/normalized-lp?set_language=en

 

 

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Additional details

Related works

Is part of
Dataset: 10.5281/zenodo.10982836 (DOI)

Funding

Turbulent-resolving urban modelling of air quality and thermal comfort TO01000219
Technology Agency of the Czech Republic