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Institute of Environmental Physics and Institute of Remote Sensing University of Bremen

Tropospheric NO 2 H eight Determination. S5P Verification Meeting Bremen, November 29, 2013. Andreas Richter , A. H ilboll, and J. P. Burrows. Institute of Environmental Physics and Institute of Remote Sensing University of Bremen. Introduction.

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Institute of Environmental Physics and Institute of Remote Sensing University of Bremen

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  1. Tropospheric NO2Height Determination S5P Verification Meeting Bremen, November 29, 2013 Andreas Richter, A. Hilboll, and J. P. Burrows Institute of Environmental Physics and Institute of Remote Sensing University of Bremen

  2. Introduction • Satellite observations provide nice global maps of tropospheric NO2 • Absolute values depend strongly on assumed vertical distribution • This information currently comes completely from a priori data • Can‘t we do better than that?

  3. What triggered this study? • Monthly GOME-2 tropospheric NO2 data are missing most of the large values • These were removed by cloud filtering as aerosol was so thick that data were classified as partially cloudy Nocloudscreening

  4. Is it only Aerosols? • Even without cloud screening, there are data gaps over pollution hot spots on some days • This is due to quality checking as these fits are poor NoChisq. screening

  5. Why are the fits poorer at strong pollution? • There are large and clearly structured residuals in fits over pollution hot spots • This is not random noise! • Comparison to NO2 cross-sections shows that scaling of NO2 should change over fitting window

  6. Wavelength dependence of Air Mass Factor • For constant albedo, AMF of NO2 layer close to the surface increases with wavelength in a Rayleigh atmosphere • For a surface layer, this can be a significant effect • With radiative transfer modelling and a formal inversion, this should provide information on the altitude of the NO2 About+/- 20%

  7. Empirical Approach • Take standard NO2 x-section • Scale to increase amplitude with wavelength • Orthogonalise to leave NO2 columns unchanged When introduced in the fit, large residuals are fixed

  8. Results Empirical Approach • The empirical NO2 AMF proxy is found over the pollution hotspot in China • It is not found at other locations where the NO2 slant column is large • There is some noise in the retrieval of the proxy

  9. Results Empirical Approach: OMI • As for GOME-2 data, the empirical NO2 AMF proxy is found over the pollution hotspot in China • There is more noise than in GOME-2 data • Problems with row anomaly

  10. Is there more than China? • Fit is improved by AMF proxy everywhere over pollution hotspots

  11. Comparison to NO2columns • Overall pattern similar to NO2 map • Differences in distributions of maxima • Artefacts over water • noise

  12. Impact of Clouds • On many days in winter, very large NO2 slant columns are observed over Europe and the US • The NO2 AMF proxy picks up only very few of these signals • This is linked to the fact that most of the events are related to cloudy scenes or snow on the surface, resulting in small wavelength dependence

  13. Sensitivity Study • Synthetic data: • Rayleigh atmosphere • Constant albedo • NO2 layer in different altitudes • DOAS fit on spectra • NO2 temperature dependence corrected by using 2 NO2 x-sections • AMF proxyincluded • Ratio of AMF proxy / NO2 to normalise signal • Ratio of AMF proxy and NO2 has strong dependence on NO2 layer height • Dependence on albedo is small between 3% and 7%

  14. Sensitivity Study: SZA • Effect varies with SZA; larger effect at larger SZA • At large SZA, AMF proxy also found for elevated NO2 • Dependence on albedo is small between 3% and 7%

  15. Sensitivity Study: Bright Surfaces • multiple scattering over bright surfaces is stronger at shorter wavelengths • wavelength dependence of AMF is inverted • Increasing albedo reduces effect as expected for reduced importance of Rayleigh scattering • For large albedo (> 50%), negative fit factors are found for AMF proxy => wavelength dependence is inverted and only weakly dependent on altitude

  16. Impact of Aerosols and Clouds Shielding • Similar effect for both, AMF proxy and NO2=> will cancel in ratio • Ratio will give layer height for cloud free part of pixel Light path enhancement • Light path enhancement in clouds / aerosols depends only weakly on wavelength • Effect on NO2 but no effect on AMF proxy • Ratio will no longer be representative of NO2 layer height

  17. Case Study Highveld • NO2 plume from Highveld power plants can be tracked onto the ocean • NO2 SC values increase downwind of the source • AMF Proxy also has higher values within the plume, but • Is more narrow • Has largest values at beginning of plume, not at the end of it

  18. Whatabout larger wavelengthdifference? • Troposphericsignalmuchsmaller in UV fit • Ratio betweentwofitsdepends on location (=> NO2height) • BUT: UV fit isnoisy

  19. Summary • A simple empirical pseudo-cross-section was used to detect and correct the AMF wavelength dependence of tropospheric NO2 in GOME-2 data • Application improves NO2 fits over pollution hotspots under clear sky conditions • As expected, the signature is not found over clouds and bright surfaces or in cases of large stratospheric NO2 • The results can at least give an indication for where an AMF for BL NO2 is appropriate • Tests on synthetic data suggest that for good signal to noise, an effective NO2 layer height can be determined • Using more separated wavelengths and applying a formal inversion including aerosol properties might provide more vertical information • Application to more data also from OMI and S5P foreseen Funding by DLR Bonnunder Contract 50EE1247

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