A modified MODIS dark-target aerosol retrieval over urban areas: Evaluation and applications

Abstract:

With amplified urbanization and industrialization during the last few decades, now more than half of the world’s population lives 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’s DRAGON network operated during four DISCOVER-AQ field campaigns. AOD retrievals both in 10km and 3km spatial resolution show significant improvement over urban areas over the U.S. The bias in AOD reduced to -0.01 from 0.07, percentage of retrievals within uncertainty window increased to 85% from 62%. We will also present air quality assessment and implication of air quality monitoring in cities using revised MODIS aerosol retrievals.