1. Page 1 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Tropospheric NO 2 from space: retrieval issues and perspectives for the future Michel Van Roozendael BIRA-IASB, Brussels, Belgium

2. Page 2 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Overview F Retrieval method (basics) F Main issues regarding: u Spectral fitting u Stratospheric correction u Tropospheric AMFs u Cloud correction F How to assess the accuracy of our retrievals? F Challenges for the future

3. Page 3 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael GOME tropospheric NO 2 intercomparison Van Noije et al., ACP, 2006 Why such differences? Who is right?

4. Page 4 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael NO 2 remote sensing using DOAS F UV-Vis NO 2 absorption is: u Structured u Independent of pressure u Weakly dependent on T° F Total atmospheric attenuation is small (<< 1)  Atmospheric transmission follows Beer-Lambert law in a simple way: P SCD NO2

5. Page 5 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Strat. NO 2 The 3 steps to tropospheric NO 2 VCDs STEP 1: DOAS  NO 2 SCD NO 2 Surface STEP 2: Remove the stratospheric part  tropospheric NO 2 (TSCD) STEP 3: Convert TSCD into tropospheric VCD NO2

6. Page 6 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael STEP 1: Spectral fitting issues F Error on DOAS fit controlled by: u S/N ratio, limited by shot noise of detector u Possible systematic bias due to: 1)Temperature dependence of NO 2 cross-sections 2)Interferences with unknown or badly known absorbers (e.g. absorption from water vapor and/or liquid water) 3)Inaccurate correction for Raman scattering by air and/or water 4)Instrumental artefacts. DOAS is insensitive to spectrally smooth radiometric errors, but very sensitive to “offset type” errors as well as to radiance errors displaying high frequency structures (e.g. polarisation, undersampling, …) F Choice of fitting interval  trade-off between S/N and minimisation of bias effects. Differences in settings/correction schemes applied by different groups may result in significant SCD differences.

7. Page 7 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Accuracy of measured radiances: what does matter for DOAS? F S/N ratio  the more photons the best (in practice trade-off between spatial/spectral resolution and S/N) F Instrument/radiometric calibration issues: u Wavelength calibration u Knowledge of instrumental slit function u Dark-current correction u Straylight correction u Polarization correction u Diffuser plate response

8. Page 8 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Courtesy J. Gleason, NASA F OMI dark current mis- corrections leading to across- track fluctuations in the retrieved NO 2 field  also requires the application of “soft calibration” procedures Examples of known instrumental problems affecting DOAS retrievals F GOME diffusor plate spectral features interfering with NO 2 absorption  time-dependent bias, requiring special treatment Richter & Wagner, 2001

9. Page 9 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael STEP 2: Stratospheric correction F Different methods can be used to extract the tropospheric signal from the total column seen from space (e.g. use cloud shielding effect, limb-nadir matching, wavelength dependence of AMFs, etc) F By far, the most popular ones are: u The “reference sector” technique and its variants (e.g. harmonic analysis)  use NO 2 columns measured over unpolluted regions to infer the stratospheric part over source regions u The model based technique  use NO 2 columns from 3D-CTM constrained by observations over unpolluted regions u The assimilation technique  assimilate NO 2 SCD in 3D-CTM (variant of model method)

10. Page 10 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael STEP 3: get VCDs using tropospheric AMFs F Most complex and error prone part of the retrieval F Tropospheric NO 2 AMFs depend on: u Solar and viewing geometries u Surface properties (albedo, ground elevation) u Aerosols u Cloud properties u Shape of tropospheric NO 2 profiles Problem: these properties are to a large extent unknown, or there are known at inappropriate resolution !

11. Page 11 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Examples of solutions currently in use PropertyCurrent treatment in AMF calculationGroups Surface albedo- GOME/TOMS data baseAll groups Cloud fraction and cloud top height - Screening based on cloud fraction - Explicit correction using IPA and accounting for ghost column - Bremen, Heid - KNMI, NASA, SAO NO 2 profiles- Scenarios - Monthly mean profiles (MOZART) - Daily profiles (GEOS-CHEM) - Daily profiles (TM4) - Heid, NASA - Bremen - SAO - KNMI Aerosols- Neglected - Scenarios (Lowtran) - Implicitly corrected by cloud treatment - Complex aerosol model - Heid - Bremen - KNMI, NASA - SAO

12. Page 12 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael F Clouds shield surface NO 2 F Clouds enhance sensitivity to NO 2 located above or at cloud altitude Cloud correction scheme NO 2 layer Surface AMF = (1-f).AMF clear + f.AMF cloud AMF cloud requires estimation of the NO 2 column underneath the cloud (ghost column) ! F Clouds generally treated as lambertian reflectors  effective cloud fraction and scattering cloud top height

13. Page 13 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Impact of clouds on tropospheric AMFs

14. Page 14 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Clouds as a mean to retrieve information on the NO 2 vertical distribution F Idea: because of their shielding effect and high albedo, clouds reduce the sensitivity to surface NO 2 and increase the sensitivity to “free-tropospheric” NO 2 F Possible applications: u Quantify NO 2 produced by lightning (Boersma et al., 2005) u Relate altitude of NO 2 plumes to the location of sources (Beirle et al., 2007) u Identify long-range transport events (TEMIS) u … Bas Mijling and R. van der A, KNMI

15. Page 15 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael How to assess the accuracy of our NO 2 retrievals? F Differences in retrieval strategies result in inconsistencies beteween NO 2 products derived from different groups. Problem even larger when different instruments are analysed by different groups. F Strategies to assess the accuracy of NO 2 retrievals: u Comprehensive error analysis ( cf. Boersma et al., 2004 ) u Intercomparison of satellite data sets ( cf. van Noije et al., 2006 ) u Validation using external correlative data sets

16. Page 16 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Tropospheric NO 2 validation: a challenge F Why is difficult to valide tropospheric NO 2 from satellites? u NO 2 emissions are extremely variable in space in time  the NO 2 field as sampled by the satellite can hardly be matched by correlative measurements. u Suitable validation data sets are currently limited: H In-situ surface measurements (difficult to compare with satellite columns) H Remote-sensing network from NDACC (focus on stratospheric columns) H In-situ aircraft (excellent but expensive -> lack of statistics) H MAXDOAS (promising technique under development – need for network deployment) H NO 2 Lidar (interesting but expensive -> lack of statistics)

17. Page 17 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael InstrumentSatellite platform Launch date Equator crossing time Resolution HorizontalRevisit Time GOMEERS-2199510:30 LT320x40 km 2 3 days at equator SCIAMACHYENVISAT200210:00 LT60x30 km 2 6 days at equator OMIEOS AURA (A-train) 200413:30 LT15x25 km 2 1 day GOME-2METOP20069:30 LT80x40 km 2 1 day Status of tropospheric NO 2 sounders

18. Page 18 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael ERS2-GOME 10:30 LT 320x40 km 2 Current status: GOME, SCIAMACHY, GOME-2 and OMI SCIAMACHY 10:00 LT 60x30 km 2 GOME-2 9:30 LT 80x40 km 2 OMI 13:30 LT 15x25 km 2

19. Page 19 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Requirements for future NO 2 monitoring systems F Driving requirements for air quality (Capacity study) u Spatial resolution5-20 km u Revisit time0.5 – 2h  Trade-off between Options 1 and 2 must be evaluated (ongoing CAMELOT study) F Can be met through: u Option 1: combination of (at least one) geostationary satellite and one sun-synchronous low earth orbit satellite (LEO) u Option 2: constellation of several instruments in LEO – a minimum of 3 instruments is needed to satisfy sampling requirements at mid-latitude

20. Page 20 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Challenges for the future (1) 1)How to ensure the consistency of the global NO 2 observing system (GEOSS/GMES requirement) when the fleet of instruments expands more and more?  Evolve towards common retrieval approaches?  Rely on both operational (standardised) and scientific (state- of-art) retrieval approaches

21. Page 21 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Challenges for the future (2) 2)What to do to improve NO 2 retrievals? A) Enhance sensitivity to detect lower levels of pollution u Using better instruments  improve S/N ratio through better photon collection efficiency H Larger throughput (limited by weight and size!) H Longer integration time (GEO) H Multiply instruments u Using improved algorithms H Expand fitting range using direct-fitting  puts high requirements on the quality of Level 1 data, and on data processing

22. Page 22 Tropospheric NO 2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007M. Van Roozendael Challenges for the future (3) B) Improve treatment of radiative transport u Use synergy with other (co-located) instruments to get better information on albedo, aerosols and clouds u Use more advanced model data or higher resolution u Improve cloud retrieval algorithms in synergy with those of NO2 (combined cloud-trace gas retrievals) C) Get more than the column (vertical profiling) u Expand fitting range using direct-fitting and optimal estimation  requirements on Level 1 quality (cf. sensitivity) u Further develop cloud slicing techniques u Use dual/multiple view geometry?