Vehicle-based sensing is a valuable paradigm to serve third-party applications, but understanding the coverage of such networks is not trivial. For urban buses, trajectories are spatially predictable, but traffic conditions can hinder data timeliness. In this paper, we propose a metric to quantify the contribution of individual buses to the coverage of different applications. We apply this metric to bus mobility traces from Rio de Janeiro for applications of waste management, air quality, and noise monitoring, ranking buses accordingly. We show that bus contribution is strongly related to the application-23% of buses change more than 2,000 places in different application rankings.