Using Low-Cost Sensors to Evaluate Community-Scale Air Pollution Trends
Particulate air pollution contributes to millions of premature deaths worldwide annually and has major climate feedback effects. This is particularly true of black carbon (BC), a component of particulate matter (PM) that results from incomplete combustion sources and has not been as thoroughly assessed as other air pollutants. Gathering particulate air pollution data within communities most affected by industrial activities and vehicle traffic is necessary in developing solutions to mitigate the social and health inequities that result from exposure.
My team at LBNL aims to analyze spatiotemporal trends of PM and BC concentrations in vulnerable California communities using our low-cost sensor technology. Our goal is to use high-density air sensor networks to understand the trends in BC concentrations and BC/PM ratios over daily, weekly, and seasonal periods. This will allow us to identify localized regions where air pollution levels are highest as well as the magnitude of different pollutant sources. Once analyzed and visualized, the data will be made widely accessible to the affected communities, local environmental justice organizations, and air quality agencies to empower action.
Message to Sponsor
- Major: Civil and Environmental Engineering
- Sponsor: Rose Hill Foundation
- Mentor: Thomas Kirchstetter