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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Tropospheric NO2 from space: retrieval issues and perspectives for
the future
Michel Van RoozendaelBIRA-IASB, Brussels, Belgium
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Overview
Retrieval method (basics)
Main issues regarding: Spectral fitting Stratospheric correction Tropospheric AMFs Cloud correction
How to assess the accuracy of our retrievals?
Challenges for the future
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
GOME tropospheric NO2 intercomparison
Van Noije et al., ACP, 2006
Why such differences?
Who is right?
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
NO2 remote sensing using DOAS
UV-Vis NO2 absorption is: Structured Independent of pressure Weakly dependent on T°
Total atmospheric attenuation is small (<< 1)
Atmospheric transmission follows Beer-Lambert law in a simple way:
20 2.exp [ ]. . .NO r mI I NO ds k ds k ds P
SCDNO2
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Strat. NO2
The 3 steps to tropospheric NO2 VCDs
STEP 1: DOAS NO2 SCD
NO2
Surface
STEP 2: Remove the stratospheric part tropospheric NO2 (TSCD)
STEP 3:Convert TSCD into tropospheric VCDNO2
2NO
TSCDVCD
AMF
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
STEP 1: Spectral fitting issues
Error on DOAS fit controlled by: S/N ratio, limited by shot noise of detector Possible systematic bias due to:
1) Temperature dependence of NO2 cross-sections2) 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
water4) 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, …)
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.
Page 7
Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Accuracy of measured radiances: what does matter for DOAS?
S/N ratio the more photons the best (in practice trade-off between spatial/spectral resolution and S/N)
Instrument/radiometric calibration issues: Wavelength calibration Knowledge of instrumental slit function Dark-current correction Straylight correction Polarization correction Diffuser plate response
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Courtesy J. Gleason, NASA
OMI dark current mis-corrections leading to across-track fluctuations in the retrieved NO2 field also requires the application of “soft calibration” procedures
Examples of known instrumental problems affecting DOAS retrievals
GOME diffusor plate spectral features interfering with NO2 absorption time-dependent bias, requiring special treatment
Richter & Wagner, 2001
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
STEP 2: Stratospheric correction
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)
By far, the most popular ones are: The “reference sector” technique and its variants (e.g.
harmonic analysis) use NO2 columns measured over unpolluted regions to infer the stratospheric part over source regions
The model based technique use NO2 columns from 3D-CTM constrained by observations over unpolluted regions
The assimilation technique assimilate NO2 SCD in 3D-CTM (variant of model method)
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
STEP 3: get VCDs using tropospheric AMFs
Most complex and error prone part of the retrieval Tropospheric NO2 AMFs depend on:
Solar and viewing geometries Surface properties (albedo,
ground elevation) Aerosols Cloud properties Shape of tropospheric NO2
profiles
Problem: these properties are to a large extent unknown, or there are known at inappropriate resolution !
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Examples of solutions currently in use
Property Current treatment in AMF calculation Groups
Surface albedo - GOME/TOMS data base All 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
NO2 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
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Clouds shield surface NO2
Clouds enhance sensitivity to NO2 located above or at cloud altitude
Cloud correction scheme
NO2 layer
Surface
AMF = (1-f).AMFclear + f.AMFcloud
AMFcloud requires estimation of the NO2 column underneath the cloud (ghost column) !
Clouds generally treated as lambertian reflectors effective cloud fraction and scattering cloud top height
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Impact of clouds on tropospheric AMFs
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
How to assess the accuracy of our NO2 retrievals?
Differences in retrieval strategies result in inconsistencies beteween NO2 products derived from different groups. Problem even larger when different instruments are analysed by different groups.
Strategies to assess the accuracy of NO2 retrievals: Comprehensive error analysis (cf. Boersma et al., 2004) Intercomparison of satellite data sets (cf. van Noije et al., 2006) Validation using external correlative data sets
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Tropospheric NO2 validation: a challenge
Why is difficult to valide tropospheric NO2 from satellites? NO2 emissions are extremely variable in space in time
the NO2 field as sampled by the satellite can hardly be matched by correlative measurements.
Suitable validation data sets are currently limited: In-situ surface measurements (difficult to compare with
satellite columns) Remote-sensing network from NDACC (focus on stratospheric
columns) In-situ aircraft (excellent but expensive -> lack of statistics) MAXDOAS (promising technique under development – need
for network deployment) NO2 Lidar (interesting but expensive -> lack of statistics)
Page 17
Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Instrument Satellite platform
Launch date
Equator crossing
time
Resolution
Horizontal Revisit Time
GOME ERS-2 1995 10:30 LT 320x40 km2 3 days at equator
SCIAMACHY ENVISAT 2002 10:00 LT 60x30 km2 6 days at equator
OMI EOS AURA (A-train)
2004 13:30 LT 15x25 km2 1 day
GOME-2 METOP 2006 9:30 LT 80x40 km2 1 day
Status of tropospheric NO2 sounders
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
ERS2-GOME 10:30 LT 320x40 km2
Current status:GOME, SCIAMACHY, GOME-2 and OMI
SCIAMACHY 10:00 LT 60x30 km2
GOME-2 9:30 LT 80x40 km2
OMI 13:30 LT 15x25 km2
Page 19
Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Requirements for future NO2 monitoring systems
Driving requirements for air quality (Capacity study) Spatial resolution 5-20 km Revisit time 0.5 – 2h
Trade-off between Options 1 and 2 must be evaluated (ongoing CAMELOT study)
Can be met through: Option 1: combination of (at least one) geostationary satellite
and one sun-synchronous low earth orbit satellite (LEO)
Option 2: constellation of several instruments in LEO – a minimum of 3 instruments is needed to satisfy sampling requirements at mid-latitude
Page 20
Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Challenges for the future (1)
1) How to ensure the consistency of the global NO2 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
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Challenges for the future (2)
2) What to do to improve NO2 retrievals?A) Enhance sensitivity to detect lower levels of pollution Using better instruments improve S/N ratio through
better photon collection efficiency Larger throughput (limited by weight and size!) Longer integration time (GEO) Multiply instruments
Using improved algorithms Expand fitting range using direct-fitting puts high
requirements on the quality of Level 1 data, and on data processing
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Tropospheric NO2 workshop, KNMI, De Bilt NL, 10-12 Sept 2007 M. Van Roozendael
Challenges for the future (3)
B) Improve treatment of radiative transport Use synergy with other (co-located) instruments to get
better information on albedo, aerosols and clouds Use more advanced model data or higher resolution Improve cloud retrieval algorithms in synergy with those
of NO2 (combined cloud-trace gas retrievals)
C) Get more than the column (vertical profiling) Expand fitting range using direct-fitting and optimal
estimation requirements on Level 1 quality (cf. sensitivity)
Further develop cloud slicing techniques Use dual/multiple view geometry?