Surface concentration of aerosol particles, also known as particulate matter (PM), is a key component determining air quality, especially with small articles (diameter less than 2.5 µm, or PM2.5) which are known to cause respiratory diseases. Local emissions and long-range transport can both contribute to the PM2.5 levels at the surface. In the past decade, satellites remote sensing measurements of global aerosol distributions have become available, continuously providing large-scale “chemical weather” pictures, which can be potentially useful for estimating surface PM2.5 levels. In this presentation, we discuss the possibilities and challenges in using satellite data for air quality applications, in particular, we will address the following questions: (1) What is the relationship between column aerosol optical depth (AOD), which is the quantity measured by satellite, and surface PM2.5 concentrations? (2) How and why this relationship varies with time and location? (3) What is the optimal approach to use model and satellite data for air quality studies? We will present case studies over the U.S. using the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, satellite data from MODIS and MISR, and surface PM2.5 concentration data from the U.S. EPA and IMPROVE monitoring networks. We will also explore the use of the lidar data from CALIPSO.

Location: Physics Bldg., room 401