Abstract View
Fine Particulate Matter: Interpreting Satellite Observations to Advance Understanding for Health Applications
RANDALL MARTIN, Washington University in St. Louis
Abstract Number: 498
Working Group: Invited by Conference Chair
Abstract
Exposure to fine particulate matter (PM2.5) is the leading global environmental determinant of longevity. However, ground-level monitoring remains sparse in many regions of the world. Satellite remote sensing of aerosol optical depth offers global data to address this observational gap. Global modeling plays a critical role in relating satellite observations to ground-level concentrations. The resultant satellite-based PM2.5 estimates indicate pronounced variation around the world, with implications for global health and insight into the association of PM2.5 with health outcomes. Sensitivity simulations with the GEOS-Chem model provide information on the sources of ambient fine particulate matter contributions that affect human health. These capabilities offer information about the effects of COVID-19 lockdowns on air quality. The Surface Particulate Matter Network (SPARTAN) is designed to evaluate and enhance satellite-based PM2.5 estimates. Advanced high-performance modeling offers increasingly fine resolution to connect across scales. This talk will highlight recent advances in combining satellite remote sensing, global modeling, and ground-based measurements to improve understanding of PM2.5 for health applications from global toward urban scales.