Presentation Type
Poster Presentation
Category
STEM (science, technology, engineering, mathematics)
Abstract/Artist Statement
Air pollution and PM2.5 from wildfire smoke have steadily increased over the last decade despite decreasing anthropogenic emissions. The increase in wildfires in the western US has highlighted the need to understand better how wildfire-specific PM2.5 affects human health. To support health risk assessment studies from wildfire smoke inhalation, differentiating between wildfire-specific PM2.5 and non-wildfire-specific PM2.5 is essential. We used PM2.5 data developed by Swanson et al. and three different methods to isolate wildfire-specific PM2.5. The PM2.5 data uses air quality station observations, Moderate Resolution Imaging Spectroradiometer, aerosol optical thickness data, and meteorological data to produce daily 1-km resolution PM2.5 concentration estimates for the 11 western US states from 2003-2021. The three methods we used to isolate wildfire-specific PM2.5 are (i) extraction from maps based on wildfire season window, (ii) top-down approach used satellite National Oceanic and Atmospheric Administration Hazard Mapping System smoke plume data, extracted to the corresponding PM2.5 values within these polygon spatial layers and filter ambient PM2.5 through a two-stage regression model, (iii) combined both mentioned methods for a spatiotemporal approach by first temporally defining a wildfire season window and then extracted spatial locations with smoke plume data. To determine which of these models was most informative and valid, we compared and contrasted, producing summary statistics for each. Our results suggest that depending on the variables used in estimating wildfire-specific PM2.5, there are many variabilities, highlighting potential problems with study accuracy. Many studies that have connected wildfire-specific PM2.5 and human health effects have devised methods for differentiating PM2.5. Various methods and results make it challenging to determine the actual population-level burden due to wildfire-specific PM2.5. The results of our study highlight the need for more in-depth studies showing the impacts of PM2.5 on public health, as policies may need to be adapted based on the emission source.
Mentor Name
Erin Landguth
Personal Statement
My work seeks to isolate wildfire-specific PM2.5 from other sources to understand better how wildfire-specific PM2.5 affects human health. Considering current events, this work has broad implications for global human health. In the last few decades, there has been an 18.7% global increase in the length of wildfire season and a 53.4% increase in wildfire frequency. In the United States, wildfires are estimated to contribute approximately 18% of the total PM2.5 in the atmosphere. Wildfire smoke dispersion from the wind causes smoke to travel across many geographical boundaries, degrading air quality across the US, thus causing many more people to be affected. Increased wildfire smoke exposure is associated with increased respiratory and cardiovascular hospitalizations, emergency department visits, and medication dispensations for asthma, bronchitis, chest pain, chronic obstructive pulmonary disease, and other respiratory infections. Current air quality standards for PM2.5 from the Clean Air Act Amendments do not distinguish the sources of emission or chemical composition. These standards consider PM2.5 from wildfires and other ambient sources (e.g., industrial plants and traffic emissions) equally harmful to human health. Recent animal toxicological studies suggest that PM2.5 from wildfires may be more toxic than ambient PM2.5. Accurate estimates of human exposure to inhaled air pollutants are necessary to understand the risks these pollutants pose and to design and implement strategies to control and limit those risks. Due to the complex nature of wildfire smoke, estimating the air pollution attributed to wildfires is challenging. My work allows for an assessment of the impact of wildfire-specific PM2.5 as it differs from other PM2.5 sources at a fine spatial resolution for all of the western US over ten years. Only a handful of studies have solely focused on isolating wildfire-specific PM2.5. Many studies have attempted similar approaches as a precursor to connecting wildfires and human health effects, but all have vastly different exposure estimates. With so many different techniques, this makes it challenging to determine the actual population-level burden due to wildfire-specific PM2.5. By providing a publicly available dataset, I aim to promote the usage of a standardized method, thus allowing for more accurate comparisons across wildfire human health research. For this reason, I request your consideration for the Best of GradCon award.
Methods for Extracting Wildfire Specific PM2.5 for the Western United States
UC North Ballroom
Air pollution and PM2.5 from wildfire smoke have steadily increased over the last decade despite decreasing anthropogenic emissions. The increase in wildfires in the western US has highlighted the need to understand better how wildfire-specific PM2.5 affects human health. To support health risk assessment studies from wildfire smoke inhalation, differentiating between wildfire-specific PM2.5 and non-wildfire-specific PM2.5 is essential. We used PM2.5 data developed by Swanson et al. and three different methods to isolate wildfire-specific PM2.5. The PM2.5 data uses air quality station observations, Moderate Resolution Imaging Spectroradiometer, aerosol optical thickness data, and meteorological data to produce daily 1-km resolution PM2.5 concentration estimates for the 11 western US states from 2003-2021. The three methods we used to isolate wildfire-specific PM2.5 are (i) extraction from maps based on wildfire season window, (ii) top-down approach used satellite National Oceanic and Atmospheric Administration Hazard Mapping System smoke plume data, extracted to the corresponding PM2.5 values within these polygon spatial layers and filter ambient PM2.5 through a two-stage regression model, (iii) combined both mentioned methods for a spatiotemporal approach by first temporally defining a wildfire season window and then extracted spatial locations with smoke plume data. To determine which of these models was most informative and valid, we compared and contrasted, producing summary statistics for each. Our results suggest that depending on the variables used in estimating wildfire-specific PM2.5, there are many variabilities, highlighting potential problems with study accuracy. Many studies that have connected wildfire-specific PM2.5 and human health effects have devised methods for differentiating PM2.5. Various methods and results make it challenging to determine the actual population-level burden due to wildfire-specific PM2.5. The results of our study highlight the need for more in-depth studies showing the impacts of PM2.5 on public health, as policies may need to be adapted based on the emission source.