Modeling of an air quality monitoring network with high space-time resolution

With regard to pollution produced in urban areas, low-cost sensors offer the possibility to collect temporal and spatial data and they have a great potential to change the way to monitor the exposure of the population to the atmospheric pollution. However, one of the challenges associated with data coming from this kind of sensors is to try to make them more significant by combing sensors in network. In this work a dispersion model is used to test the distribution of dust (10 μm) measured by individual points of the network. The monitoring area considered is within a seaside town in southern Italy. The monitoring network is made of three sensors placed in points sensitive for the anthropic activity. We have applied an interpolation model to determine the areas of greatest pollution concentration within the monitored area. The model simulated the pollution movements at the level of the individual monitoring points taking into account the weather conditions.