(312b) Understanding How Pollution Episodes Affect Community-Level Air Quality with a Distributed Sensor Network

Short- and long-term exposure to fine particulate matter (PM2.5) pollution is linked to numerous adverse health effects, and acute events, like wildfires and fireworks, can cause dramatic increases in PM2.5 levels. Although fewer studies have examined the health effects of PM2.5 from these types of events, several studies suggest wildfire smoke and fireworks cause adverse respiratory effects. Pollution impacts from wildfires are becoming an increasing concern as both the number and size of wildfires continues to increase. In fact, although air quality has improved in the US over the past 30 years, it has declined in wildfire-prone states. Conventional PM2.5 measurements are expensive, resulting in spatially and temporally sparse data that may not accurately represent local-scale pollution gradients and may be slow to detect a pollution event. New low-cost PM sensor technologies offer the potential to improve the spatial and temporal resolution of PM2.5 measurements although they have limitations in terms of accuracy and precision. Here we demonstrate how air quality measurements from a network of 134 citizen-hosted, low-cost PM2.5 sensors can be integrated with dynamic data-fusion algorithms and visualization strategies to understand and communicate highly resolved PM2.5 concentrations in an intuitive way during two pollution events in the Salt Lake Valley. The results illustrate how local policy on fireworks affects community-scale PM concentrations and how the network can serve an early warning of an approaching pollution event.

Drs. K. Kelly and P.-E. Gaillardon have an interest in the company Tetrad: Sensor Network Solutions, LLC, which commercializes solutions for environmental monitoring.