A100-08
Monitoring Air Quality from Space: Perspectives from Modeling and Sub-orbital Measurements to Understand the AOD-PM2.5 Relationship on Different Time Scales
Thursday, 10 December 2020: 10:58
Virtual
Mian Chin, NASA Goddard SFC, Greenbelt, MD, United States, Qian Tan, Bay Area Environmental Research Institute, San Jose, CA, United States, Gao Chen, NASA Langley Research Ctr, Hampton, VA, United States, Huisheng Bian, NASA Goddard Space Flight Ctr, Greenbelt, MD, United States, Zhining Tao, NASA GSFC Code 614, Greenbelt, MD, United States, Dongchul Kim, Universities Space Research Association, Greenbelt, MD, United States and Hongbin Yu, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Abstract:
Monitoring air quality from space has played a key role in our understanding of the status and trends of air pollution. In the past two decades, observations from low earth orbiting (LEO) satellite imagers (e.g., MODIS, MISR and VIIRS) have offered promising opportunities to estimate PM
2.5 levels on the ground. More recently, high temporal resolution AOD observations from geostationary satellites have helped to estimate sub-daily aerosol variability and characterize the diurnal behavior of PM
2.5. However, there remain fundamental challenges when rely on AOD for estimating the PM
2.5. The AOD-PM
2.5 relationship is not constant but depends on many factors, all of which have large spatial and temporal variations. Consequently, transforming the satellite AOD data into surface PM
2.5 requires an undertaking to quantify the controlling factors of the AOD-PM
2.5 relationship in the context of different time scales and various meteorological and chemical environments.
In this presentation, we analyze the AOD-PM2.5 relationship using an atmospheric model and suborbital data from ground-based measurements of AOD, PM2.5, and extinction, and the aircraft measurements of aerosol vertical profiles to delineate the variability of aerosols at the surface and aloft on hourly, daily, and monthly time scales in different locations in the United States and Asia. We will quantify the dependence of AOD and PM2.5 on aerosol properties (amount, composition, size, vertical profile, and hygroscopic growth) and meteorological conditions (PBL height, relative humidity or water vapor amount, winds) in order to understand their variability. Finally, we will provide our viewpoints on the applications of remote sensing data for air quality applications.
