Towards a Digital Twin for Air Quality Monitoring Networks in Smart Cities

In the context of smart cities, high-resolution air quality monitoring with low-cost sensor systems has seen remarkable interest. These systems, however, need frequent recalibration to maintain metrological traceability. Air pollution models based on partial differential equations offer an arbitrary spatial and temporal resolution, but they require some experimental data as initial and boundary conditions in order to be solved. This theoretical paper makes considerations that air quality monitoring networks and air pollution models could be combined into one single measurement instrument. Not only would this allow a high resolution with a lower number of network nodes but it would also result in a simple method for recalibration, given the traceability of simulations. At the same time, the performed measurements would serve as input for the solution of the differential equations. While all necessary parts for a potential realization are available, challenges such as low data quality and computational burden have to be overcome first.