Developing Descriptive and Predictive Causal Models to Study the Impacts of Highway Construction on Ambient Air Quality in the Front Range
Principal Researchers: Farnoush Banaei-Kashani
Unit: Department of Computer Science and Engineering
The Colorado Department of Transportation (CDOT), building on a collaboration with Denver Department of Public Health and Environment (DDPHE), is initiating a multi-year Federal Highway Administration (FHWA) funded project to document and understand impacts of typical highway construction activities on air quality in the Front Range. As part of this project the team is deploying a variety of environmental monitoring sensors along the I-270 corridor, collecting multimodal environmental data including PM2.5, PM10, NOx, and total tVOC (Total Volatile Organic Compounds), to name a few. The existing collaboration has similar suites of sensors along the central I-70 corridor. With our proposed project, in partnership with the aforementioned team we will (1) obtain air quality data from the location targeted by the FHWA sponsored project, (2) augment and fuse the air quality data with publicly available construction, traffic, and weather datasets, and finally, (3) use the fused data to develop descriptive and predictive causal models that can quantify the impact of highway construction projects on air quality.