American Association for Aerosol Research - Abstract Submission

AAAR 38th Annual Conference
October 5 - October 9, 2020

Virtual Conference

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MAIA: A Satellite Investigation of PM Health Effects in Selected Global Cities

YANG LIU, David Diner, Howard Chang, Feng Xu, Jun Wang, Randall Martin, Christian L'Orange, Kristal Verhulst-Whitten, Sina Hasheminassab, Emory University, Atlanta, GA

     Abstract Number: 94
     Working Group: Urban Aerosols

Abstract
Exposure to ambient particulate matter (PM) has been associated with various adverse health outcomes such as respiratory illness, cardiovascular diseases, adverse birth outcomes and premature death. PM is a complex mixture of chemical components with different sizes and shapes. Routine measurements of PM composition are costly and labor intensive, therefore are not readily available in most parts of the world. The sparse coverage of PM composition data presents a serious challenge to the assessment of population health effects due to PM exposure. To address this issue, NASA’s Multi-Angle Imager for Aerosols (MAIA) investigation will generate daily estimates of PM composition estimates at 1 km spatial resolution in selected urban centers around the world. The MAIA satellite instrument is currently undergoing fabrication and testing, and is scheduled for launch in 2022 into sun-synchronous orbit aboard the General Atomics Orbital Test Bed-2 spacecraft. To provide sensitivity to aerosol properties such as optical depth, effective radius, and complex refractive index, MAIA’s multispectral camera includes 14 bands in the ultraviolet (UV), VNIR, and shortwave infrared (SWIR), three of which are polarimetric, and is mounted on a gimbal to provide multiangular views of the target areas. Bayesian geostatistical regression models (GRMs) will be used to transform the retrieved aerosol optical and microphysical properties into near-surface mass concentrations of PM10, PM2.5, and speciated PM2.5 constituents (sulfate, nitrate, organic carbon, elemental carbon, and mineral dust). In addition to retrieved aerosol properties, the GRM predictors include geospatial data such as population and roadway densities along with meteorological parameters and estimated PM concentrations from the WRF-Chem chemical transport model. Filter-based PM speciation monitors within the Surface Particulate Matter Network (SPARTAN) plus a set of Aerosol Mass and Optical Depth (AMOD) samplers will be deployed to calibrate the coefficients of the GRMs. MAIA science team members, in collaboration with local researchers, will conduct epidemiological studies in different MAIA target areas to investigate the association of speciated particle mixtures with various health endpoints.