Setting-up a Real-Time Air Quality Forecasting system for Serbia: a WRF-Chem feasibility study with different horizontal resolutions and emission inventories.

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2019
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Abstract
In this paper, the influence of the horizontal model grid size and anthropogenic gridded emissions on the air quality forecast in Serbia was analyzed using the online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem). For that purpose, six simulations were performed. The model horizontal grid size was 20 × 20 km, 10 × 10 km, and 5 × 5 km. Two anthropogenic gridded emission inventories with different grid sizes were used, the global RETRO (REanalysis of the TROpospheric chemical composition) and the EMEP (The European Monitoring and Evaluation Program) for each model horizontal grid size. The modeled O, NO, and PM concentrations in all six simulations were compared with the measured hourly data at the Serbian Environmental Protection Agency (SEPA) stations and an EMEP station during August 2016. The analysis shows that the influence of the model grid size is larger on PM than on the O and NO concentration. The concentration of O and PM has a similar dependence on the emissions and the model grid size, while NO has a larger dependence on the emission than on the model grid size. The simulation with the 5 × 5 km grid size and the EMEP anthropogenic emissions has optimal performance compared with the measured concentration. In this optimal simulation, the modeled O concentrations overestimated the measured values at 3 stations and underestimated the measured values at 2 stations. At most stations, the modeled NO concentrations underestimated the measured values. The modeled PM concentrations highly underestimated the measured values at all stations.
Reference Key
podrascanin2019setting-up Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Podrascanin, Zorica;
Journal Environmental science and pollution research international
Year 2019
DOI
10.1007/s11356-019-05140-y
URL
Keywords Keywords not found

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