  The increased frequency of wildfires in the Western United States has raised
public concerns. Exposure to wildfire smoke has been linked to an increased
risk of cancer and cardiorespiratory morbidity. Evidence-driven interventions
can alleviate the adverse health impact of wildfire smoke. Public health
guidance during wildfires is based on regional air quality data with limited
spatiotemporal resolution. We demonstrate the use of a network of low-cost
particulate matter (PM) sensors to gather indoor, outdoor, and personal PM2.5
exposure data from seven locations in the urban Seattle area, along with a
personal exposure monitor worn by a resident living in one of these locations
during the 2020 Washington wildfire event. The data were used to determine PM
concentration indoor/outdoor (I/O) ratios, PM reduction, and personal exposure
levels. The result shows that locations equipped with high-efficiency
particulate air (HEPA) filters and HVAC filtration systems had significantly
lower I/O ratios (median I/O = 0.43) than those without air filtration (median
I/O = 0.82). The median PM2.5 reduction for the locations with HEPA is 58 %
compared to 20% for the locations without HEPA. The outdoor PM sensors showed a
high correlation to the nearby regional air quality monitoring stations (R2 =
0.93). The personal monitor showed high variance in PM measurements as the user
moved through different microenvironments and could not be fully characterized
by the network of indoor or outdoor monitors. The findings imply evidence-based
interventions can be developed for reducing pollution exposure based on the
combination of indoor, outdoor sensors. Personal exposure monitoring in
individuals' breathing zones provided the highest fidelity data capturing
temporal spikes in PM exposure.
