Advancing Understanding of Air Quality from Global to Urban Scales

Ambient air pollution is the leading environmental risk factor for global burden of disease. 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. Algorithmic advances applied to the TROPOMI instrument yield new insight into the air pollution mixture. 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 to urban scales.