Abstract View
Using Low-Cost Sensors to Trace Biomass Burning Aerosol Plumes from Wildfires in Southern California
DANIELLE ROCCO, Esther Morales, Jaebin Ju, Linh Luu, Daniel B. Curtis, California State University, Fullerton
Abstract Number: 242
Working Group: Wildfire Aerosols
Abstract
Wildfires are a major source of particulate matter in the atmosphere and have important implications for air quality, especially if they occur near highly populated areas. Additionally, due to climate change and other factors, wildfire frequency and size are expected to increase in certain areas such as the Western United States. PurpleAir sensors are low-cost air quality monitors that provide real time measurements of PM2.5 concentration, among other quantities. They have become increasingly popular due to their affordability, user-friendly operation, and low maintenance. Although questions remain about the accuracy of low-cost sensors, as a result of their low-cost and ease of use, there are now thousands of these sensors located across California (and other areas) that can be viewed publicly in real time on an interactive map and the data compared to better understand regional air quality.
The unique traits of low-cost sensors, especially the ability to have provided a new and affordable technique to potentially track biomass burning aerosol plumes from wildfires in the area. In this study, multiple local PurpleAir Sensors were used to analyze and track plumes from two fires located in Southern California, the Silverado Fire and the Blue Ridge Fire. Both fires ignited on October 26th, 2020 and were fully extinguished on November 7th, 2020. Preliminary results reveal that PurpleAir Sensors are efficient in detecting fires. Particle concentrations were observed for each sensor and a trend for the Silverado Fire was observed with concentration decreasing as distance away from the fire increases. The results from the Blue Ridge fire appear to be more complex. Further comparisons were conducted using the NOAA Hysplit Model to take meteorological conditions into consideration and the model shows agreement with the PurpleAir sensors.