*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
School of Civil and Environmental Engineering
Ph.D. Thesis Defense Announcement
Spatiotemporal modeling of PM2.5 oxidative potential using source impact and model fusion techniques
By
Josephine Bates
Advisor:
Armistead Russell (CEE)
Committee Members:
James Mulholland (CEE), Rodney Weber (EAS), Joseph Brown (CEE), Howard Chang (Emory University)
Date & Time: Friday, June 1, 2018 , 1:00PM
Location: Ford ES&T L1114
Exposure to elevated levels of air pollution can lead to cardiorespiratory disease, birth defects, and cancer. However, observational air quality data are spatially and temporally sparse due to high cost of monitors, limiting the scope of epidemiologic analyses and introducing error in exposure assessments. This dissertation presents the development, evaluation, and applications of multiple mathematical and computational modeling approaches for estimating spatiotemporal trends in air pollutant concentrations where and when data is not available for use in health studies. Specifically, source apportionment techniques with multivariate regression analyses are used to estimate long-term (years 1998—2010) and large-scale (eastern US) spatiotemporal trends in a novel pollutant metric, fine particulate matter (PM2.5) oxidative potential measured with a dithiothreitol assay (OPDTT). OPDTT measures a particle’s ability to catalytically generate reactive oxygen species while simultaneously depleting a body’s antioxidant defenses, leading to oxidative stress and, in turn, inflammation in the respiratory tract and cardiovascular system. Results show that biomass burning and vehicle sources are significant contributors to OPDTT and that OPDTT exposure presents higher risk ratios for asthma/wheezing and congestive heart failure emergency department visits than PM2.5 mass. Additionally, statistical downscaling techniques and model fusion approaches are developed to simulate fine-scale spatiotemporal trends (250m resolution) in air pollutant concentrations (OPDTT, PM2.5, carbon monoxide, and nitrogen oxides) in Atlanta, GA. These methods estimate steep spatial gradients in pollutant concentrations near roadways that monitors and regional air quality models with coarse grid resolutions do not capture. The models developed in this dissertation can estimate concentration fields of air pollutants, including the novel pollutant metric OPDTT, at regional and local scales, making them valuable tools for current and future epidemiologic and environmental justice research.
