Transcript Results from the TEMIS project

Tropospheric Formaldehyde (CH2O) from
Satellite Observations.
Isabelle De Smedt1, M. Van Roozendael1,
R. Van Der A2, H. Eskes2.
1: BIRA-IASB, 2: KNMI
TEMIS user workshop, Frascati, 8-9 October 2007
Formaldehyde in the troposphere
• NOx/VOCs ratio determines the production of ozone in the troposphere.
Satellite observation of NO2 and CH2O support air quality control.
• CH2O is one of the most abundant carbonyl compounds and a central
component of VOCs oxidation. Its observation can help to constrain VOC
emissions.
• Sources:
- Methane oxidation (background)
- Biogenic VOCs oxidation (isoprene)
- Anthropogenic hydrocarbon oxidation
- Biomass burning (as first and secondary product)
• Sinks : Oxidation by OH radical and Photolysis
- Major source of CO
- Production of HO2
• CH2O has a spectral signature of absorption in the near UV and can
therefore been retrieved from satellite observations with the DOAS
technique.
TEMIS user workshop, Frascati, 8-9 October 2007
The TEMIS Project
• Objective within the TEMIS project: improve the quality of CH2O
retrieval from satellite and provide a consistent long term series of
CH2O observation combining different instruments.
• Two satellite instruments:
1. GOME on ERS2:
– launched in 1995. Full coverage until June 2003.
– 320 x 40 km2 ground pixel
– sun-synchronous orbit, 10:30
– global coverage in 3 days
2. SCIAMACHY on ENVISAT:
– launched in 2002.
– 60 x 30 km2 ground pixel
– sun-synchronous orbit, 10:00
– global coverage in 6 days
TEMIS user workshop, Frascati, 8-9 October 2007
The TEMIS Project
• Tropospheric CH2O is a joined product between BIRA-IASB and
KNMI.
• DOAS technique in two
independent steps:
1. Fit of slant columns (absorption
along the satellite viewing path).
SCD are retrieved with the
WINDOAS software.
2. Determination of air mass factors to
obtain vertical columns. AMF are
computed with radiative transfer
calculations to model scattering in
the troposphere and CH2O profile
shape from 3D-CTM.
TEMIS user workshop, Frascati, 8-9 October 2007
1: CH2O Slant Columns
Optical densities: SC.σ(λ)
• In UV, main absorbers are
Ozone and Ring effect.
• CH2O optical depth smaller.
SC O3 = 2x1019 mol/cm²
SC NO2 = 5x1016
SC CH2O = 1x1016
SC BrO = 1x1014
• Fit very sensitive to:
•
•
•
•
S/N ratio
Other molecules absorption
Fitting window
DOAS corrections
TEMIS user workshop, Frascati, 8-9 October 2007
1: CH2O Slant Columns
• DOAS settings have been optimized in order to obtain a consistent
time series combining the two instruments.
• Particularly, the fitting windows has been shifted more in the UV to
avoid a spectral artefact in SCIAMACHY spectra.
• I0: radiance selected daily
in the Pacific Ocean.
• Reference sector correction
based on the background of
CH2O in the Pacific only
due to CH4 oxidation.
 ( )  
ln I ( )
ln I 0 ( )
  SCi ' i ( )   a p  p
i
TEMIS user workshop, Frascati, 8-9 October 2007
p
1: CH2O Slant Columns
GOME CH2O SCD [x1015 mol/cm²]
1997-2002
• Compared to first version of the TEMIS GOME CH2O product, SCD
have been analysed in a new fitting window (328.5-346 nm).
• For GOME: Reduction of the background noise and several artefacts
above desert regions.
• For SCIA: Allows to retrieve CH2O consistent with GOME.
TEMIS user workshop, Frascati, 8-9 October 2007
2: AMF Determination
AMF 
 WF ( z , angles , CF , CT , Alb, Alt ). S ( z , lat , long , month ).dz
atm
• Scattering by clouds and air particles makes the
AMF dependant on the vertical distribution of
the molecule.
• Scattering properties of the atmosphere
modelled with a RTM (Disort). WF depend on
observation angles, cloud properties, albedo and
ground Altitude.
• Cloud Correction based on the independent
pixel approximation and on the FRESCO
product.
• Vertical distribution of CH2O is taken from the
tropospheric 3D-CTM IMAGES. The profile
shape S(z) is the normalized profile: S(z) =
P(z)/∫P(z).
TEMIS user workshop, Frascati, 8-9 October 2007
Profile as seen by GOME
WF
NCAR
URI
• Intex-A
campaign
• Jul.2004
CH2O Vertical Columns
Apr.1996 – Dec.2001
•
•
Jan.2003 – Jun.2007
GOME CH2O VC averaged over 7 years (from 1996 to 2002) and the
SCIAMACHY CH2O VC over the next 4 years and half (from 2003 to mid 2007).
The general agreement between both instruments allows the generation of a
combined long-term time series of CH2O vertical columns covering a full decade
from 1997 until 2006.
TEMIS user workshop, Frascati, 8-9 October 2007
CH2O Vertical Columns
GOME – SCIAMACHY CH2O VCD [x1016 mol/cm²]
Jan. – Jun. 2003
Over the 6 first months of 2003:
• General agreement within
7.5x1015 mol/cm².
• SCIA is higher than GOME
from 40° in latitudes N and S.
• South Atlantic Anomaly effect
is different.
TEMIS user workshop, Frascati, 8-9 October 2007
•
•
CH2O Vertical Columns: America
Good agreement over the six first months
Stronger seasonal variability with SCIA.
•
•
Very good agreement in South America
Stronger SAA effect with SCIA
TEMIS user workshop, Frascati, 8-9 October 2007
•
•
CH2O Vertical Columns: Asia
Good agreement over the six first
months, SCIA a bit lower.
Much stronger seasonal variability with
SCIA.
•
Very good agreement in biomass
burning regions.
TEMIS user workshop, Frascati, 8-9 October 2007
CH2O Vertical Columns: Africa
•
Very good overall agreement in Africa.
TEMIS user workshop, Frascati, 8-9 October 2007
Special Event: Greek Fires this Summer
CH2O as measured by SCIA on 26 August 2007 superimposed over an
image made by MODIS. Due to the strong north-easterly wind the smoke
from the forest fires is blown all the way to the coast of Lybia.
TEMIS user workshop, Frascati, 8-9 October 2007
Total VCD Error Evaluation
• Vertical columns calculated from the slant columns (SC), air mass
factors (AMF) and a zonal correction above Pacific Ocean (SCO and
VCO):
SC
 SC  SC 
VC  

O
AMF
  VCO  AMF  VCO

• As the determination of the SC, AMF and VCO are independent, the
total error on the tropospheric vertical column can be expressed as:
 ²VC  (
VC
VC
VC
)² ² SC  (
)² ² AMF  (
)² ²VCO
SC
AMF
VCO
1  ² SCrand
1
SC


 ² SCsyst  (
)² ² AMF   ²VCO
AMF ² N
AMF ²
AMF ²
•
•
•
σSC: error on the SC. Can be separated into its random and systematic part.
σAMF : error on the AMF evaluation.
σVC0 : error on the background correction above Pacific Ocean.
TEMIS user workshop, Frascati, 8-9 October 2007
Global Error Budget
 ²VCD 
1  ² SCrand
1
SC

 ² syst  (
)² ² AMF   ²VCo
AMF ²
N
AMF ²
AMF ²
• Total Error around 25%.
• At low and mid latitudes,
AMF error dominates with
the main contribution from
clouds and profile shape
uncertainties.
• At higher latitudes, SC error
dominates because of higher
Ozone concentrations.
• Monthly average allows to
reduce SC random error.
TEMIS user workshop, Frascati, 8-9 October 2007
Users
• Modellers community:
– IMAGES (J-F Muller and J. Stavrakou, BIRA-IASB, Brussels):
current user, paper in preparation.
– CHIMERE (G. Dufour, LISA, Paris): future user, data provided.
– GEOS-CHEM (P. Palmer, Tropospheric Chemistry Earth
Observation Modelling and Measurement Group, University of
Edinburgh): other possible user.
• National and regional environmental protection agencies:
– Europe: UBA-Austria, EMPA Switzerland and LANUV
Northrhine-Westfalia: users within Promote.
– China: National Satellite Meteorological Centre NSMC (Peng
Zhang), Institute of Atmospheric Physics, CAS IAP-CAS (Pucai
Wang): Contacts in China through the AMFIC project, can help to
find users there.
TEMIS user workshop, Frascati, 8-9 October 2007
Conclusions and Outlook
• On the TEMIS website, you will find:
– Daily, monthly and yearly maps for GOME and SCIAMACHY.
– Data files with averaging kernels and error estimation for each
satellite pixel.
• The dataset will be regularly extended with fresh SCIA data.
• The analysis of GOME-2 data will start within the next months.
The global coverage in 1,5 day should allow to reduce the noise in
the results.
• Consistency between the platforms needs to be evaluated regularly
(changes in time) and validated with ground-based measurements
that become more and more available for CH2O.
TEMIS user workshop, Frascati, 8-9 October 2007
Conclusions and Outlook
• The quality and the consistency of the data is very important to be
able to detect possible trends in emissions.
• A derived product based on inverse modelling could be developed
within TEMIS to provide constraints on VOC emissions.
Possibilities of more users working on emission inventories (GFED,
MEGAN).
TEMIS user workshop, Frascati, 8-9 October 2007