Abstract View
Using Low-Cost Air Sensors to Assess Community Level PM Exposure from California Wildfires
AMBER KRAMER, Jonathan Liu, Liqiao Li, Yifang Zhu, University of California, Los Angeles
Abstract Number: 294
Working Group: Wildfire Aerosols
Abstract
The use of low-cost air sensors has become a vital key to understanding air quality at the community level. In this study we demonstrate the efficacy of using publicly available PurpleAir sensor data to assess community exposures to wildfire-induced fine particulate matter (PM2.5, da < 2.5 μm). We sourced publicly available sensor data within 25 miles of ten wildfires in the state of California in 2020, one in 2019, and one in 2018, and paired the indoor PurpleAir sensors with nearby outdoor PurpleAir sensors (within 5 km). We observed that the average outdoor PM2.5 concentrations could increase up to 100-fold during the early stages of nearby wildfires compared to pre-fire levels. Indoor PM2.5 concentrations peaked up to 40-fold over pre-fire averages between 80 and 350 minutes after the observed outdoor PM peak. The peaks and troughs of indoor PM2.5 concentrations followed the observed outdoor PM2.5 levels in a similar and delayed pattern throughout the time of wildfire, indicating that wildfire-induced PM2.5 could infiltrate into the indoor environments. In addition, we found that indoor PM2.5 concentrations returned to pre-fire averages within the period of time it takes to contain fires, while outdoor PM2.5 concentrations can stay upwards of two weeks before returning to pre-fire averages. This study demonstrates the efficacy to use low-cost air sensor data to better understand the community level impacts of wildfires. Our results suggest indoor PM2.5 concentrations could reach dramatically higher levels during wildfire events and the Public Health warnings to remain indoors during nearby wildfires may not be sufficient to protect community health.