The sustained growth of urban settlements in the last years has had an inherent impact on the environment and the quality of life of their inhabitants. In order to support sustainability and improve quality of life in this context, we advocate the fostering of ICT-empowered initiatives that allow citizens to self-monitor their environment and assess the quality of the resources in their surroundings. More concretely, we present the case of such a self-monitoring Smart City platform for estimating the air quality in urban environments at high resolution and large scale. Our approach is a combination of mobile and human sensing that exploits both dedicated and participatory monitoring. We identify the main challenges in such a crowdsensing scenario for Smart Cities, and in particular we analyze issues related to scalability, accuracy, accessibility, privacy, and discoverability, among others. Moreover, we show that our approach has the potential to empower citizens to diagnose their environment using mobile and portable sensing devices, combining their personal data with a public higher accuracy air quality network.