We don’t all breathe the same air. Urban air pollution varies sharply owing to unevenly distributed pollution sources. While fine-scale spatial variation in air quality has profound implications for public health and environmental equity, air pollution measurements are routinely collected at only a few locations in every city. Therefore, a major need in developing community resilience is to better understand the connections between transit, transportation-related air pollution, health, and community resilience. In this project, researchers collected air pollution data using mobile sensors and low-cost sensors and generated a dataset that integrates multiple data types to support cross-disciplinary research. A Hackathon event engaged the UT community and encouraged students to explore the data, resulting in a series of project ideas and presentations made on the day of the event. Research supported by this project explored the challenges of using data collected from mobile sensors to understand the impacts of TRAP on health, the feasibility of using the project dataset to understand the impact of COVID-19 on air pollution and traffic, and the possibility of determining epidemiologically significant variances of PM2.5 in urban areas, including SE Austin, using low-cost sensors.