Urban air quality — the concentration of PM2.5 — is of great importance in protecting human health. While there are limited air-quality-monitor-stations in a city, air quality varies by location significantly and is influenced by multiple complex factors, such as traffic flow and land use. Consequently, people cannot know the air quality of a location without a monitoring station. This project infers real-time, fine-grained air-quality information throughout a city, based on air-quality data reported by existing monitor stations and a variety of data sources observed in the city, such as meteorology, traffic flow, human mobility, the structure of road networks, and points of interest. This fine-grained air-quality information could help people figure out when and where to go jogging—or when they should shut the window or put on a face mask in locations where air quality is already a daily issue. This could lead to long-term solutions in predicting forthcoming air quality and identifying the root cause of air pollution.