During the last several decades, urbanization and industrialization have continued to amplify, thus more than half the world’s population is now living in urban areas. With surface particle matter (PM) concentration five or ten times higher than World Health Organization guidelines in some cities, it is very critical to accurately monitor PM air quality for global cities on a daily basis. The new version (C6) of MODIS Dark Target Land Aerosol Algorithm (MDT) provides near-daily aerosol optical depth (AOD) retrievals at 10km2 and 3km2 spatial resolutions, which can be used to estimate surface PM. However, initial validation efforts showed that MDT overestimates AOD over urban areas, primarily because the bright and complex urban surface does not meet MDT assumptions. We combined the MODIS Land Classification Product (MCD12Q1) with MODIS land surface spectral reflectance product (MOD09A1) to develop new surface characterization scheme to be used within the MDT algorithm framework. We applied the new surface characterization to the MDT algorithm and compared the retrieved AOD with AOD observed from the ground-based AERONET. AOD retrievals show significant improvement in urban areas over the U.S. The new surface scheme is also applied in other global regions and we found encouraging results. I will also present long-term aerosols trends at regional and city scales and its implication to air quality.
Seminar Series Coordinators