Recent acceleration in the development of sensing and data acquisition technologies has led to the dramatic reduction in the cost of monitoring solutions while functionality has improved. These trends have made instrumentation of large, complex infrastructure systems for long-term monitoring possible. For many structures, long-term monitoring provides a massive data set upon which the system’s modal properties can be empirically identified. Modal properties have been previously used for model updating and to better understand the performance of the instrumented structure. In this study, a low-cost wireless sensing platform has been used to permanently instrument a long-span bridge for long-term monitoring of structural behavior under normal operational loading profiles including exposure to wind, temperature and traffic loads. The Alfred Zampa Memorial Bridge (also termed the New Carquinez Suspension Bridge) located in Vallejo, California was instrumented to monitor bridge accelerations, strains, and displacements. In addition, the wireless monitoring system was used to indirectly monitor thermal and wind loads by measuring temperature and wind characteristics (i.e.,direction and speed) respectively. The study’s primary focus is on the autonomous extraction of modal characteristics of the bridge using the output-only stochastic subspace identification (SSI) method. Using extracted modal frequencies, relationships are presented between the modal characteristics of the bridge and environmental parameters such as temperature and traffic activity.