Artificial Intelligence for Air Quality  

Artificial Intelligence for Air Quality 

1) AI/ML air quality modeling system that can mimic full chemical transport model such as CMAQ, CAMX to rapidly assess the impacts of local emissions control on local and regional air quality.

(2) Development and applications of AI/ML inverse modeling system that can rapidly infer spatiotemporal top-down emissions constrained by observations of ground monitoring networks and statelites.

(3) AI/ML-based model-measurement data fusion techniques development to develop high-resolution criteria and toxics air quality datasets for human exposure epidemiology studies as well as the environmental justices communities

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