PM 2.5 Modeling with Community Air Monitoring Network data
In the first publication, we describe how we used IVAN AIR data to estimate PM in locations without government monitors, suggesting that community air monitoring data may be useful for developing spatial and temporal models to estimate pollution levels for vulnerable communities. View the article: Use of Citizen Science-Derived Data for Spatial and Temporal Modeling of Particulate Matter near the US/Mexico Border.

In the second, we describe our finding that the IVAN AIR monitors identified more than 10 times as many episodes of high particulate matter (PM) levels as the regulatory monitors alone. This suggests that dense networks of community air monitors may be useful for real-time warnings of high pollution episodes to local communities. View the article: Next-Generation Community Air Quality Sensors for Identifying Air Pollution Episodes