Spatial Interpolation Techniques For innovative Air Quality Monitoring Systems

New technologies for air quality measurement, including real-time on-road air quality monitoring systems (ROMs), have improved the spatial resolution of data. However, measured data can miss due to restricted traffic zones. Different algorithms can estimate the missing data in these points, using available measured data in the neighbourhood. In this study, the results of the applications of an interpolation method taking into account the effect of wind direction and intensity by means of a simple dispersion model is presented. Thanks to the large amount of data provided by the innovative dynamic monitoring system (ROM), the proposed model is able to return, with a good approximation, reliable PM10 and PM2.5 concentration values, with a resolution of 1 km2.