A111-0012
Using MAIA Data to Investigate PM Health Effects in Selected Urban Areas Around the World

Friday, 11 December 2020
Poster
Yang Liu, Emory University, Gangarosa Department of Environmental Health, Atlanta, GA, United States, Guannan Geng, Tsinghua University, Beijing, China, Xia Meng, Fudan University, Shanghai, China, Howard H. Chang, Emory University, Department of Biostatistics and Bioinformatics, Atlanta, GA, United States and David J Diner, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
Abstract:
Exposure to ambient fine particulate matter (PM2.5) has been associated with various adverse health outcomes such as respiratory illness, cardiovascular diseases, adverse birth outcomes and premature death. The sparse coverage of PM composition data presents a serious challenge to assessing the health effects due to PM exposure in most parts of the world. NASA’s Multi-Angle Imager for Aerosols (MAIA) investigation will generate daily ground level concentrations of major PM2.5 components at 1 km spatial resolution in selected urban centers around the world. A Bayesian spatial statistical modeling framework will be implemented to transform MAIA retrieved aerosol optical and microphysical properties into near-surface mass concentrations of PM2.5 components including sulfate, nitrate, organic carbon, elemental carbon, and mineral dust. Previous studies using MISR data products have demonstrated the feasibility of this approach in various regions in the US. MAIA science team members, in collaboration with local researchers, will conduct epidemiological studies in different MAIA target areas to investigate the association of PM2.5 components with various health endpoints.
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