Influence of WRF Parameterization on Coupled Air Quality Modeling Systems

Gašparac, Goran; Jeričević, Amela; Grisogono, Branko

doi:10.1007/978-3-319-24478-5_90

Cited by 2 publications

(3 citation statements)

References 3 publications

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“…-Underestimation of background (PM 10 ) d concentrations with regional models is in accordance with other modelling studies (Gauss et al, 2016;Forkel et al, 2015).…”

Section: Discussionsupporting

confidence: 89%

“…The overall performance of the models regarding (PM 10 ) d is in agreement with similar modelling studies (e.g. Werner et al, 2015;Baró et al, 2015;Forkel et al, 2015;Gauss et al, 2016). Due to the coarser grid resolutions, differences in terrain height could lead to a problem in station representativeness in regional models.…”

Section: Chemistrysupporting

confidence: 83%

“…The most recent studies showed significant technical improvements with updated initial and boundary conditions as well as with newer model versions, which include various modifications in the chemistry modules. Throughout the performed extensive tests (Gauss et al, 2016), the model generally underestimated the observed annual mean PM 10 levels by 24 %. However, there was an overall relatively good agreement (correlation coefficient, r = 0.74) between modelled and measured annual mean PM 10 concentrations.…”

Section: Introductionmentioning

confidence: 94%

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Regional-scale modelling for the assessment of atmospheric particulate matter concentrations at rural background locations in Europe

Gašparac

Jeričević²,

Kumar

et al. 2020

Atmos. Chem. Phys.

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Abstract. The application of regional-scale air quality models is an important tool in air quality assessment and management. For this reason, the understanding of model abilities and performances is mandatory. The main objective of this research was to investigate the spatial and temporal variability of background particulate matter (PM) concentrations, to evaluate the regional air quality modelling performance in simulating PM concentrations during statically stable conditions and to investigate processes that contribute to regionally increased PM concentrations with a focus on eastern and central Europe. The temporal and spatial variability of observed PM was analysed at 310 rural background stations in Europe during 2011. Two different regional air quality modelling systems (offline coupled European Monitoring and Evaluation Programme, EMEP, and online coupled Weather Research and Forecasting with Chemistry) were applied to simulate the transport of pollutants and to further investigate the processes that contributed to increased concentrations during high-pollution episodes. Background PM measurements from rural background stations, wind speed, surface pressure and ambient temperature data from 920 meteorological stations across Europe, classified according to the elevation, were used for the evaluation of individual model performance. Among the sea-level stations (up to 200 m), the best modelling performance, in terms of meteorology and chemistry, was found for both models. The underestimated modelled PM concentrations in some cases indicated the importance of the accurate assessment of regional air pollution transport under statically stable atmospheric conditions and the necessity of further model improvements.

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“…-Underestimation of background (PM 10 ) d concentrations with regional models is in accordance with other modelling studies (Gauss et al, 2016;Forkel et al, 2015).…”

Section: Discussionsupporting

confidence: 89%