1. Institute of Environmental Physics and Remote Sensing IUP/IFE-UB Physics/Electrical Engineering Department 1 Andreas.Richter@iup.physik.uni-bremen.de Institute of Environmental Physics and Institute of Remote Sensing University of Bremen Tropospheric NO 2 Height Determination Andreas Richter, A. Hilboll, and J. P. Burrows S5P Verification Meeting Bremen, November 29, 2013

2. Andreas.Richter@iup.physik.uni-bremen.de 2 Introduction Satellite observations provide nice global maps of tropospheric NO 2 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. Andreas.Richter@iup.physik.uni-bremen.de 3 What triggered this study? Monthly GOME-2 tropospheric NO 2 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 No cloud screening

4. Andreas.Richter@iup.physik.uni-bremen.de 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 No Chisq. screening

5. Andreas.Richter@iup.physik.uni-bremen.de 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 NO 2 cross-sections shows that scaling of NO 2 should change over fitting window

6. Andreas.Richter@iup.physik.uni-bremen.de 6 Wavelength dependence of Air Mass Factor For constant albedo, AMF of NO 2 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 NO 2 About +/- 20%

7. Andreas.Richter@iup.physik.uni-bremen.de 7 Empirical Approach Take standard NO 2 x-section Scale to increase amplitude with wavelength Orthogonalise to leave NO 2 columns unchanged When introduced in the fit, large residuals are fixed

8. Andreas.Richter@iup.physik.uni-bremen.de 8 Results Empirical Approach The empirical NO 2 AMF proxy is found over the pollution hotspot in China It is not found at other locations where the NO 2 slant column is large There is some noise in the retrieval of the proxy

9. Andreas.Richter@iup.physik.uni-bremen.de 9 Results Empirical Approach: OMI As for GOME-2 data, the empirical NO 2 AMF proxy is found over the pollution hotspot in China There is more noise than in GOME-2 data Problems with row anomaly

10. Andreas.Richter@iup.physik.uni-bremen.de 10 Is there more than China? Fit is improved by AMF proxy everywhere over pollution hotspots

11. Andreas.Richter@iup.physik.uni-bremen.de 11 Comparison to NO 2 columns Overall pattern similar to NO 2 map Differences in distributions of maxima Artefacts over water noise

12. Andreas.Richter@iup.physik.uni-bremen.de 12 Impact of Clouds On many days in winter, very large NO 2 slant columns are observed over Europe and the US The NO 2 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. Andreas.Richter@iup.physik.uni-bremen.de 13 Sensitivity Study Ratio of AMF proxy and NO 2 has strong dependence on NO 2 layer height Dependence on albedo is small between 3% and 7% Synthetic data: Rayleigh atmosphere Constant albedo NO 2 layer in different altitudes DOAS fit on spectra NO 2 temperature dependence corrected by using 2 NO 2 x-sections AMF proxy included Ratio of AMF proxy / NO 2 to normalise signal

14. Andreas.Richter@iup.physik.uni-bremen.de 14 Sensitivity Study: SZA Effect varies with SZA; larger effect at larger SZA At large SZA, AMF proxy also found for elevated NO 2 Dependence on albedo is small between 3% and 7%

15. Andreas.Richter@iup.physik.uni-bremen.de 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. Andreas.Richter@iup.physik.uni-bremen.de 16 Impact of Aerosols and Clouds Shielding Similar effect for both, AMF proxy and NO 2 => 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 NO 2 but no effect on AMF proxy Ratio will no longer be representative of NO 2 layer height

17. Andreas.Richter@iup.physik.uni-bremen.de 17 Case Study Highveld NO 2 plume from Highveld power plants can be tracked onto the ocean NO 2 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. Andreas.Richter@iup.physik.uni-bremen.de 18 What about larger wavelength difference? Tropospheric signal much smaller in UV fit Ratio between two fits depends on location (=> NO 2 height) BUT: UV fit is noisy

19. Andreas.Richter@iup.physik.uni-bremen.de 19 Summary A simple empirical pseudo-cross-section was used to detect and correct the AMF wavelength dependence of tropospheric NO 2 in GOME-2 data Application improves NO 2 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 NO 2 The results can at least give an indication for where an AMF for BL NO 2 is appropriate Tests on synthetic data suggest that for good signal to noise, an effective NO 2 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 Bonn under Contract 50EE1247