• Roberto San José Software and Modelling Group, Computer Science School, Technical University of Madrid (UPM), Madrid, Spain
  • Juan L Pérez Software and Modelling Group, Computer Science School, Technical University of Madrid (UPM), Madrid, Spain
  • Libia Pérez Software and Modelling Group, Computer Science School, Technical University of Madrid (UPM), Madrid, Spain
  • Rosa Maria Gonzalez Barras Department of Physics and Meteorology, Faculty of Physics, Complutense University of Madrid (UCM), Ciudad Universitaria, 28040 Madrid, Spain



WRF/Chem, Urban Emission, Madrid Air Quality


In the cities, traffic emissions are the largest contributor to the exceedances of NO2 limit values. It is necessary to develop tools to evaluate if the traffic measures can reduce the air pollution. EMIMO-WRF/Chem air quality modeling system (1 km) has been used to assess the effectiveness of emergency measures based on traffic restrictions to reduce concentrations of air pollutants during the NO2 pollution episode in the city of Madrid. Two simulations were designed: “REAL" including traffic restrictions and "BAU" representing what would happen if no action were taken. The difference between the two simulations (BAU-REAL) gives us the contribution of traffic restriction measures to reduce concentrations of pollutants in the air. An evaluation of the modelling system's performance has previously been carried out and found to be very satisfactory, demonstrating that the proposed system can be used to simulate pollution episodes in cities. The results indicate that the daily concentration of NO2 decreased by only about 1.3 % and so the measures taken were not sufficiently effective compared to the traffic reduction effort that reached around 10 %. More effective measures must be explore and analyze with the proposed tool. 


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How to Cite

José, R. S., Pérez, J. L., Pérez, L., & Barras, R. M. (2018). USING THE WRF/CHEM MODEL TO EVALUATE URBAN EMISSION REDUCTION STRATEGIES: MADRID CASE STUDY. LIFE: International Journal of Health and Life-Sciences, 4(1), 101–121.