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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.

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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)

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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

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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

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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?