Current methods of estimating air quality involve assigning a single value called the Air Quality Index (AQI) to a large land area for a 24-hour period based on a very few, sparsely-located sensors. This produces a low-resolution image of the air quality in that region. We have devised a new mobile air quality monitoring network with the ability to provide high-resolution realtime pollution data at any location within the coverage area. We have prototyped sensors and proven the feasibility of the approach, and are currently testing a small-scale implementation using irregularly-sampled spatiotemporal measurements from mobile car-mounted sensors coupled with existing static data. This data feeds a web-based application, enabling users to view air quality in specific regions as well as estimate exposure over specied time periods and plan routes based on minimal exposure to a given pollutant.