Ambient air pollution is the leading environmental determinant of health. However, ground-level monitoring remains sparse in many regions of the world. Satellite remote sensing of aerosols and nitrogen dioxide offers global data to address this issue. Global modeling plays a critical role in relating these observations to ground-level concentrations. The resultant satellite-based estimates indicate pronounced variation around the world, with implications for global public health. Sensitivity simulations with the GEOS-Chem model provide information on the sources of ambient fine particulate matter contributions that affect human health. A new ground-based aerosol network (SPARTAN) offers valuable measurements to evaluate and improve satellite-based PM2.5 estimates. Algorithmic advances applied to the TROPOMI instrument yield new insight into the air pollution mixture. These tools offer information about the effects of COVID-19 lockdowns on air quality. Advanced high-performance modeling offers capabilities to connect the local to the global scale. This talk will highlight recent advances in combining satellite remote sensing, global modeling, and ground-based measurements to improve understanding of air quality from global toward urban scales.
Professor Randall Martin is the Raymond R. Tucker Distinguished Professor in the Department of Energy, Environmental & Chemical Engineering at Washington University in St. Louis. He received an MSc in Environmental Change and Management from Oxford University, and a MS and PhD in Engineering Sciences from Harvard University. He completed his postdoctoral research at the Harvard-Smithsonian Center for Astrophysics, before joining the faculty of Dalhousie University in 2003. In 2019, he joined the faculty of the McKelvey School of Engineering at Washington University in St. Louis. He has been awarded the AGU Atmospheric Sciences Ascent Award, the Steacie Memorial Fellowship, and is a member of the Royal Society of Canada.
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