Project Summary:

1. Will develop modeling and deployment strategies for low-cost air quality sensors in urban India.
2. Tailor policy recommendations to different affected populations and the appropriate government authorities.

We propose to develop modeling and deployment strategies for low-cost air quality sensors in the dense built environment of urban India. This builds on and complements ongoing work by Professor Jesse Kroll and David Hagan to develop low-cost sensors that can gather pollutant-specific, air quality data at high spatial and temporal resolution. Using uncertainty quantification, inverse modeling, and strategic experimental deployments, we aim to: apportion sources of air pollution in specific times, places, and seasons; optimize observation networks for sensor capabilities; and tailor policy recommendations and findings to different affected populations and the appropriate government authorities and levels.