The aims of this project are to develop models and techniques that will afford significantly improved monitoring and communication of the pollution level in cities without the need to significantly invest in monitoring equipment.
The core aims of this PhD project are to understand spatiotemporal variability of air quality and determine the main drivers of air pollution in urban areas by: (a) deploying a dense network of air quality sensors based on multiple criteria, and (b) employing various air quality modelling and mapping techniques including geostatistical interpolations, statistical and dispersion modelling and data fusion approaches.