12 August 2014 High spatial resolution NO2 tropospheric slant columns retrieved from OMI spatial-zoom spectra using an earthshine reference
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Proceedings Volume 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014); 922904 (2014) https://doi.org/10.1117/12.2066154
Event: Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 2014, Paphos, Cyprus
Abstract
Future satellite instruments measuring urban NO2 will need to have high spatio-temporal resolution in order to improve air quality model forecasts. However, the likely cost and data telemetry requirements for such instruments will be high with current techniques. In this work we propose a new retrieval algorithm for deriving tropospheric NO2 slant column densities (SCDs) by DOAS fitting an earthshine reference spectrum measured over the Pacific to account for stratospheric NO2, which would eliminate the need for a solar reference and simplify instrument and retrieval design. The retrieval is tested by fitting earthshine radiance spectra measured by the Ozone Measuring Instrument (OMI) during its spatial-zoom mode (nadir pixel size: 13 x 12 km2) and super-zoom mode (nadir pixel size: 13 x 3 km2) using a Pacific reference spectrum. Transects taken over urban areas showed that the retrieval appears to retrieve tropospheric NO2 SCDs with good agreement with the operational L2 DOMINO product over regions with high NOx emissions. The retrieval also appeared to supress across-track striping without the need for a posteriori correction and showed sensitivity to absorption due to sand and liquid water over deserts and oceans. Comparisons with operational-scale retrievals also showed improved SCD precision, if random noise is expected to be the cause of retrieval uncertainty.
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Jasdeep S. Anand, Jasdeep S. Anand, Roland J. Leigh, Roland J. Leigh, Paul S. Monks, Paul S. Monks, "High spatial resolution NO2 tropospheric slant columns retrieved from OMI spatial-zoom spectra using an earthshine reference", Proc. SPIE 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 922904 (12 August 2014); doi: 10.1117/12.2066154; https://doi.org/10.1117/12.2066154
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