Using Big Data Analytic Techniques to Understand Air Quality Impacts of Oil and Gas Activity in an Urban Environment
CIVE Professor Ken Carlson is working with a CSU-derived start-up company on a project to bring real-time, high spatial resolution monitoring of air quality to the City of Broomfield, CO. The project will utilize large and diverse datasets with machine learning techniques to understand air quality patterns in an urban environment with multiple pollution sources including oil and gas activity. Monitoring includes traditional whole-air summa canister analyses that provides high resolution, speciated data but with limited temporal coverage. These analyses are combined with Internet-of-Things (IOT) sensors that can monitor multiple air quality parameters in real-time but cannot provide the level of speciation (e.g. benzene) that the canister approach does.