Particular matter (PM), or aerosol, is the general term used for a mixture of solid particles and liquid droplets found in the atmosphere. Monitoring natural (dust and volcanic ash) and anthropogenic aerosols (biomass burning smoke, industrial pollution) is important because they influence cloud properties, alter the radiation budget of the earth-atmosphere system, affect atmospheric circulation patterns and cause changes in surface temperature and precipitation.

           Aerosols also reduce visibility and induce respiratory diseases when sub-micron sized aerosols penetrate the lungs thereby affecting air quality and health. Increased exposure to particular matter with particle diameters less than 2.5?m (PM2.5) can cause lung and respiratory diseases and even premature death.

           Although several ground measurement networks are currently in operation to monitor aerosols for different purposes, these network are inadequate for monitoring air pollution on global scales. However, satellite imagery, due to their large spatial coverage and reliable repeated measurements, provide another important tool to monitor aerosols and their transport patterns.

           Satellite data have tremendous potential for mapping the global distribution of aerosols and their properties. The MODIS on NASA’s Earth Observation System (EOS) Terra and Aqua provide near daily observations of aerosols over global land and ocean surfaces with moderate spatial resolution. Recent studies have demonstrated the potential of using satellite-derived columnar aerosol properties as a surrogate for fine particulate matter (PM2.5) air quality over local, regional and global scales. Recently we have developed a long term (10 year) integrated data base of satellite, surface and model outputs for the particulate matter air quality research. This data base can be utilized to explore the possibility of combining satellite data with model derived meteorological field into different statistical model frameworks for estimation of particulate matter air quality. The online tool also provides access to preprocessed data sets. This tool also facilitates online visualization of several satellite, surface and meteorological parameters over ground stations. Spatial distribution maps, scatter plots, and time series analysis can also be performed using this online tool. Online availability of such data base in easy to use format will encourage more research studies towards application of satellite data for air quality monitoring and forecasting.

         This online research tool is an attempt to provide complete research package to the community.