Estimating spatiotemporal trends in wildfire smoke concentrations in the western United States
Date
2018
Authors
O'Dell, Katelyn, author
Pierce, Jeffrey R., advisor
Fischer, Emily V., advisor
Ford, Bonne, committee member
Magzamen, Sheryl, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
The United States (US) has seen significant improvements in seasonal air quality over the past several decades. However, particulate air quality in summer over the majority of the western US has seen little improvement in recent decades. Particulate matter with diameters < 2.5 microns (PM2.5) is a large component of ambient air quality that is associated with negative health effects and visibility degradation. Wildfires are a major summer source of PM2.5 in the western US. While anthropogenic-related sources of PM2.5 have decreased across the US, wildfires have increased in both frequency and burn area since the 1980s. It is currently uncertain how this increase in wildfires has impacted seasonal air quality trends and how the health effects of wildfire-emitted PM2.5 may differ from anthropogenic-sourced PM2.5. We do not directly address the latter uncertainty, but rather focus on improving smoke-exposure estimates, which are a critical, yet challenging, component to understanding the health effects of wildfire-emitted PM2.5. In this thesis, we use a combination of satellite estimates, surface observations, and chemical transport models to distinguish wildfire smoke PM2.5 from non-wildfire-smoke PM2.5 during the summer in the US. We update the record of seasonal trends in PM2.5 observed at surface monitors and provide the first estimates of trends in wildfire smoke-specific PM2.5. We find continued decreases in total-PM2.5 in most seasons and regions of the US. In the summer in heavily fire-impacted regions of the western US, we find non-decreasing total-PM2.5 while wildfire smoke-specific PM2.5 has increased and non-wildfire-smoke PM2.5 has decreased. We test the application of blended smoke exposure models, which use multiple data sources as input variables (e.g. satellite-derived aerosol optical depth, chemical transport models, etc.), across the full western US. We incorporate a novel dataset into the model, Facebook posts, which have been shown to correlate well with surface PM2.5 concentrations during the western US wildfire season. We find the blended smoke exposure model performs well across the western US (R2 = 0.66). However, the Facebook dataset is well correlated with interpolated surface monitors (another input variable) and thus does not significantly improve blended smoke-exposure estimates in the western US.