Our last research paper focused on the challenging topics of aerosol layer height (ALH) retrieval from hyperspectral visible measurements, aerosol correction, and tropospheric NO2 retrieval from satellite sensors like OMI was published in the Atmospheric Measurement Techniques (AMT) journal. This work relies on the activities achieved during the last months of my thesis research with my colleagues of the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI: Dr. J. Pepijn Veefkind, Dr. Johan de Haan, Dr. Piet Stammess, and Prof. Dr. Pieternel F. Levelt.
This paper is based on the last developments we published during 2016, 2017, and 2018. During these years, not only the OMI cloud algorithm was improved (Veefkind et al., 2016), but also an OMI aerosol layer height (and optical thickness) neural network algorithm was developed (Chimot et al., 2017, 2018). This time, we directly evaluate the impacts of these developments to correct of aerosol absorption and scattering effects in the visible spectral range in view of retrieving tropospheric NO2, an important trace gas affecting air quality in urban and industrialised areas.
What are the main conclusions? Aerosol correction on tropospheric NO2 retrieval from OMI has been greatly improving the last 2-3 years for UV-Vis air quality satellites. Notably thanks to the updated effective cloud retrievals. But also there is a clear potential from the ALH based on the 477 nm O2-O2 band. However, the decision for the future processors is not necessarily easy to take: accuracy vs. radiance closure budget are clearly competing.
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I greatly thank my co-authors from the Netherlands for this very interesting work! This paper closes the loop of my whole research work achieved during the last 4 years with the Geoscience and Remote Sensing (GRS) department of TU Delft and KNMI.
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