Poor air quality disproportionally impacts cities in low- and middle-income countries. In Bogotá, Colombia, a metropolitan area with over 10 million inhabitants, fine particulate matter (PM ) levels regularly exceed air quality guidelines, leading to detrimental effects on health. Although there is public interest to improve the city's air quality, the main sources of PM pollution have not been clearly identified and the use of modeling for policy development in Bogotá has been limited. Here, we apply a modeling framework based on the Community Multiscale Air Quality Modeling System (CMAQ) to conduct seasonal simulations of air pollution in Bogotá and reveal the emissions sectors with the largest contributions to PM . Based on these results, we project and compare the air quality benefits of potential pollution mitigation strategies focused on these sources. The analysis finds that resuspended dust from unpaved roads is the largest local source of PM and can contribute over 30% of seasonally-averaged concentration across the city. Vehicles, industrial activity, and unpaved road dust combined are responsible for over 60% of PM pollution in Bogotá. A scenario analysis shows that paving roads can lead to PM decreases of nearly 10 μg/m by 2030 in some areas of the city, but air quality will deteriorate significantly over others in the absence of additional emissions control measures. Mitigation strategies designed to target the sectors with the largest contributions to PM , including road cleaning systems, controls for industrial point sources, cleaner transportation fuels, and updated vehicle fleets, can largely avert projected increases in concentrations, although the impacts of different approaches vary throughout the city. This study is the first to use a comprehensive model to determine sector contributions to air pollution and inform potential emissions control policies in Bogotá, demonstrating an approach to guide pollution management in developing cities facing comparable challenges. 2.5 2.5 2.5 2.5 2.5 2.5 2.5 3