High Resolution Air Quality Forecasting Over Prague within the URBI PRAGENSI Project: Model Performance During the Winter Period and the Effect of Urban Parameterization on PM

0525251 - ÚI 2021 RIV CH eng J - Journal Article
Ďoubalová, J. - Huszár, P. - Eben, Kryštof - Benešová, N. - Belda, M. - Vlček, O. - Karlický, J. - Geletič, Jan - Halenka, T.
High Resolution Air Quality Forecasting Over Prague within the URBI PRAGENSI Project: Model Performance During the Winter Period and the Effect of Urban Parameterization on PM.
Atmosphere. Roč. 11, č. 6 (2020), č. článku 625. E-ISSN 2073-4433
R&D Projects: GA KHP(CZ) UH0383
Institutional support: RVO:67985807
Keywords : air pollution * emissions * urban canopy * weather prediction * particulate matter * validation
OECD category: Meteorology and atmospheric sciences
Impact factor: 2.686, year: 2020
Method of publishing: Open access

The overall impact of urban environments on the atmosphere is the result of many different nonlinear processes, and their reproduction requires complex modeling approaches. The parameterization of these processes in the models can have large impacts on the model outputs. In this study, the evaluation of a WRF/Comprehensive Air Quality Model with Extensions (CAMx) forecast modeling system set up for Prague, the Czech Republic, within the project URBI PRAGENSI is presented. To assess the impacts of urban parameterization in WRF, in this case with the BEP+BEM (Building Environment Parameterization linked to Building Energy Model) urban canopy scheme, on Particulate Matter (PM) simulations, a simulation was performed for a winter pollution episode and compared to a non-urbanized run with BULK treatment. The urbanized scheme led to an average increase in temperature at 2 m by 2 ∘ C, a decrease in wind speed by 0.5 m s − 1 , a decrease in relative humidity by 5%, and an increase in planetary boundary layer height by 100 m. Based on the evaluation against observations, the overall model error was reduced. These impacts were propagated to the modeled PM concentrations, reducing them on average by 15–30 μ g m − 3 and 10–15 μ g m − 3 for PM 10 and PM 2 . 5 , respectively. In general, the urban parameterization led to a larger underestimation of the PM values, but yielded a better representation of the diurnal variations.
Permanent Link: http://hdl.handle.net/11104/0309434