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

Abstract. A novel tropospheric NO₂ 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 NO₂ 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 NO₂ 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 H₂O absorption, as first discovered in the analysis of GOME-2 NO₂ retrievals.