Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 2: Downscaling techniques for air quality analysis and forecasts
Yi Wang,Jun Wang,Meng Zhou,Daven K. Henze,Cui Ge,and Wei Wang
Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA 52242, USA
Department of Chemical and Biochemical Engineering, and Center for
Global and Regional Environmental Research, The University of Iowa, Iowa
City, IA 52242, USA
Meng Zhou
Interdisciplinary Graduate Program in Informatics, The University of Iowa, Iowa City, IA 52242, USA
Daven K. Henze
Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
Cui Ge
Department of Chemical and Biochemical Engineering, and Center for
Global and Regional Environmental Research, The University of Iowa, Iowa
City, IA 52242, USA
South Coast Air Quality Management District, Diamond Bar, CA 91765,
USA
Wei Wang
China National Environmental Monitoring Center, Beijing 100012, China
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We developed four different methods to downscale SO2 and NO2 emissions derived from OMPS satellite observations (in Part 1) for regional air quality modeling at a spatial resolution that is finer than satellite observations. The VIIRS (city lights), TROPOMI, and OMI satellite data as well as surface data are used to evaluate the model. The method of using the top-down emissions from the past month for the air quality forecast in the present month is also shown to have practical merit.
We developed four different methods to downscale SO2 and NO2 emissions derived from OMPS...
