In 2006, we began a three-year project funded by the NASA Integrated Decisions Support program to develop a three-dimensional air quality system (3D-AQS). The focus of 3D-AQS is on the integration of aerosol-related NASA Earth Science Data into key air quality decision support systems used for air quality management, forecasting, and public health tracking. These will include the U.S. Environmental Protection Agency (EPA)'s Air Quality System/AirQuest and AIRNow, Infusing satellite Data into Environmental Applications (IDEA) product, U.S. Air Quality weblog (Smog Blog) and the Regional East Atmospheric Lidar Mesonet (REALM). The project will result in greater accessibility of satellite and lidar datasets that, when used in conjunction with the ground-based particulate matter monitors, will enable monitoring across horizontal and vertical dimensions. Monitoring in multiple dimensions will enhance the air quality community's ability to monitor and forecast the geospatial extent and transboundary transport of air pollutants, particularly fine particulate matter. This paper describes the concept of this multisensor system and gives current examples of the types of products that will result from it.
Satellite remote sensing data are another source of information to study air quality, supplementing the in situ monitoring networks. Satellite data have primarily been used to study specific events that affect air quality, such as wildfires, biomass burning, dust storms, and volcanoes. In this exploratory analysis we have used the monthly averaged aerosol optical depth (AOD) product of the MODIS sensor data from the Terra satellite platform to study fine particulate matter throughout the contiguous U.S. While most of the previous quantitative work has focused on hourly correlations between in situ monitors and satellite AOD data, we have attempted to quantify monthly, seasonal, and annual correlations. Our analysis of 2001 monthly data found that correlations do exist, but not throughout the entire study period or area. The best correlations were seen in the northeast and industrial Midwest during the summer months.