Air quality forecasts using an off-line WRF-ADMS coupling: a verification study for the city of Bologna (IT)

Air pollution continues to pose significant threats in many regions of the world, including Europe where exceedances of limit values are still frequent in urban areas for most pollutants (nitrogen oxides NOx, particulate matter in form of PM10 and PM2.5, and ozone O3). The control and prevention of episodes of severe air quality is very important both for the management of traffic in urban areas and for citizens’ health and life quality. In fact, the availability of accurate forecasts for air pollution episodes could further support decisions related to traffic closures and make also a significant impact on lifestyles especially for citizens suffering from respiratory problems. In this study, the Atmospheric Dispersion Modelling System (ADMS) is used in combination with the mesoscale Weather Research and Forecasting (WRF) for making good accurate predictions of spatial variations in the concentrations of the main air pollutants in the urban area of Bologna, Italy. The study area includes all emitting sources of air quality pollutants, as well as meteorological and air quality monitoring stations from the reference network, over a domain of 20 x 30 km with a resolution of 200x200 m. The WRF model was used to simulate hourly forecasts of the meteorological variables necessary for the initialization of the ADMS dispersion model. The output parameters obtained from WRF such as simulated air temperature, wind intensity and wind direction were also compared with the data observed in the meteorological station of the Marconi airport in Bologna. The suggested integrated strategy and the performance of the model is verified comparing with the observations of air quality pollutants from the Emilia Romagna Environmental Protection Agency (ARPAE) network in the urban area of Bologna. The ADMS model shows good agreement with observed concentrations over the whole considered reference year (2017). The results of different case studies will be presented and discussed. In particular, we will present the first results obtained spanning different weather conditions both in the summer and in winter seasons. The aims of this work are: test the WRF-ADMS Urban coupling, automate the steps of the methodology and verify the reliability of air quality forecasts. Possible developments of this work will be the use of machine learning techniques to improve local air quality forecasts which is current under study.