The rapid progress of urbanization is leading to serious air and noise pollution. Therefore, significant research effort is focused on creating a fine-grained pollution and noise maps to identify urban areas with critical negative impact on human health. The traditional measuring methods typically use expensive and static equipment which is not suitable for dynamic urban environments because of the low spatio-temporal density of measurements. On the other hand, the growing popularity of mobile phones, and their technological capabilities, opens a new perspective on citizen-assisted environmental monitoring. In this paper we present a mobile crowdsensing (MCS) solution for air quality and noise pollution monitoring. More specifically, we show a practical experience of a real-world system deployment, from sensor calibration to data acquisition and analysis. Our initial results indicate a correlation between air and noise pollution with higher values during peak hours due to an increased number of vehicles on the streets.