An improved retrieval of tropospheric NO2 from space over polluted regions using an Earth radiance reference

A novel tropospheric NO[Subscript: 2] DOAS retrieval algorithm optimised for a nadir-viewing satellite instrument imaging polluted areas is proposed in this work. Current satellite DOAS retrievals have relied on using a solar reference spectrum to derive a total slant column, then using either model assimilation or spatial filtering to derive the tropospheric component. In the ERrs-DOAS (Earth radiance reference sector DOAS) algorithm, tropospheric NO[Subscript: 2] slant columns are derived using spectra averaged from measurements over unpolluted regions, thus removing the need for post-hoc separation techniques, though some residual stratospheric biases may still remain. To validate the ERrs-DOAS algorithm, DOAS retrievals were performed on modelled spectra created by the radiative transfer model SCIATRAN, as well as L1B Earth radiance data measured by the NASA/KNMI Ozone Monitoring Instrument (OMI). It was found that retrievals using an Earth radiance reference produce spatial distributions of tropospheric NO[Subscript: 2] over eastern China during June 2005 that highly correlate with those derived using existing retrieval algorithms. Comparisons with slant columns retrieved by the operational NO2 retrieval algorithm for OMI (OMNO2A) show that the ERrs-DOAS algorithm greatly reduces the presence of artificial across-track biases (stripes) caused by calibration errors, as well as the removal of path length enhancement in off-nadir pixels. Analysis of Pacific SCDs suggests that the algorithm also produces a 27% reduction in retrieval uncertainty, though this may be partially due to biases introduced by differences in the retrieval algorithm settings. The ERrs-DOAS technique also reveals absorption features over the Sahara and similar regions characteristic of sand and liquid H[Subscript: 2]O absorption, as first discovered in the analysis of GOME-2 NO[Subscript: 2] retrievals.