Spatial and temporal estimates of population exposure to wildfire smoke during the Washington state 2012 wildfire season using blended model, satellite, and in situ data

Abstract

In the western U.S., smoke from wild and prescribed fires can severely degrade air quality. Due to changes in climate and land management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of air pollutants in the western U.S. Hence, there is a need to develop a quantitative understanding of wildfire‐smoke‐specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools have been used in past studies to assess exposure to wildfire smoke: in situ measurements, satellite‐based observations, and chemical‐transport model (CTM) simulations. Each of these exposure‐estimation tools has associated strengths and weakness. We investigate the utility of blending these tools together to produce estimates of PM2.5 exposure from wildfire smoke during the Washington 2012 fire season. For blending, we use a ridge‐regression model and a geographically weighted ridge‐regression model. We evaluate the performance of the three individual exposure‐estimate techniques and the two blended techniques by using leave‐one‐out cross validation. We find that predictions based on in situ monitors are more accurate for this particular fire season than the CTM simulations and satellite‐based observations because of the large number of monitors present; therefore, blending provides only marginal improvements above the in situ observations. However, we show that in hypothetical cases with fewer surface monitors, the two blending techniques can produce substantial improvement over any of the individual tools.

Connecting smoke plumes to sources using Hazard Mapping System (HMS) smoke and fire location data over North America

“…10. This figure provides context for isolated case studies of smoke transport associated with extreme periods including the summer 2013 Quebec wildfires (Laffineur et al, 2014), the summer 2012 wildfires in the Rocky Mountain region (Val Martin et al, 2013b), and the 2008 California wildfires (SW region; Gyawali et al, 2009). Supplement Table S3 shows the total smoke hours produced by and over each US region and the differences between using the GDAS and EDAS meteorology datasets for the trajectory calculations.…”

A low-cost particulate matter (PM<sub>2.5</sub>) monitor for wildland fire smoke

“…AOD is an integrated extinction of light from the total mass of aerosol present in a vertical column of the atmosphere; thus, AOD includes total aerosol mass at all elevations. Satellite-based aerosol measurements, however, still lack precision and fine spatial resolution and do not quantify air quality specifically at ground level (Lassman et al, 2017). As a result, a need still exists for spatially-resolved measurements of surface air quality in the vicinity of fires.…”

A low-cost PM<sub>2.5</sub> monitor for wildland fire smoke

“…AOD is an integrated extinction of light from the total mass of aerosol present in a vertical column of the atmosphere; thus, AOD includes total aerosol mass at all elevations. Satellite-based aerosol measurements, however, 55 still lack precision and fine spatial resolution and do not quantify air quality specifically at ground level (Lassman et al, 2017).…”