Urban air quality affects health and well-being of more than half of the world's population. Measurement, modeling and real time action on pollution sources can alleviate their impact. A preliminary study for drone-based image acquisition and processing steps required for 3D reconstruction of potential pollution sources is presented. The 3D surface terrain models combined with sensor data are inputs into air pollution models for visualization, understanding and potential mitigation of methane plumes. Scaling these technologies across large areas requires the integration of big geospatial data with modeling, machine learning, and image processing.