Tropospheric NO2 and ozone

Ronald van der A, Michel Van Roozendael, Isabelle De Smedt, Jos de Laat, Ruud Dirksen,

Folkert Boersma

KNMI and BIRA-IASB

Thessaloniki, May 2008

Tropospheric NO2

Tropospheric NO2 from satellite measurements

• Observed total slant column• Subtract stratospheric part (model)• Convert slant column into vertical column (air mass factor, RT)

Surface

Stratospheric NO2

CloudTropospheric NO2

Retrieval approach

• CTM (TM4) Assimilation fed by satellite measurements (unpolluted pixels only) and ECMWF data gives:

•Estimation of stratospheric column

•A priori NO2 profile AMFtrop

• Surface albedo + cloud info + a priori profile AMFtrop

• Measured column + stratospheric column + AMFtrop

Tropospheric NO2 column

trop

stratobstrop AMF

SSV

1: TM4 forecast

How does it work?

GOME

• Archive: Apr. 1996 - Jul. 2003 • Format: HDF4• Monthly mean files

– TOMS ASCII-format– ESRI grid format

• Pixel size: 320x80 km

SCIAMACHY• version 1.1: July 2002 till today• version 1.1 uses FRESCO+• Format: HDF4• Monthly mean files:

– TOMS ASCII-format– ESRI grid format– Regional images

• Pixel size is 60x30 km

OMI

• L1b reprocessing of entire mission completed• version 1.1: October 2004 till March 2008• NRT processing has to be updated

• Format: HDF5• Monthly mean files

– TOMS ASCII-format– ESRI grid format

• Pixel size: > 24x12 km

GOME-2

• Data available: April 2007 till today• NRT processing is operational

• Format: HDF5• Monthly mean files

– TOMS ASCII-format– ESRI grid format

• Pixel size: 30x60 km

Based on monthly averaged NO2 columns from GOME (1996-2003) and SCIAMACHY (2003-2006) measurements.

Large increase of NO2 over industrial and economical areas of eastern China.

Trend detection of tropospheric NO2 over China

van der A et al., J. Geophys. Res., 111, 2006

Mean NO2

1996

Trend(%/yr)

Error on

trend

Beijing 11.1 11 3

Shanghai 5.2 25 5

Chongqing

3.8 12 3

ShenYang 4.5 16 6

Seoul 10.4 1.3 1

NO2 correlated with vehicles population during 1996~2006 in Beijing (top) and Shanghai (bottom)

0.0

30.0

60.0

90.0

120.0

150.0

180.0

210.0

240.0

270.0

300.0

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006Year

Ca

r a

mo

un

t

(m

illi

on

)

0.0

5.0

10.0

15.0

20.0

25.0

NO 2 v

ertic

al

co

lum

n a

mo

un

t

(×

1015 m

ole

cu

les c

m- 2

)

Car amount

NO2 volumn amount

0.0

30.0

60.0

90.0

120.0

150.0

180.0

210.0

240.0

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

veh

icle

am

ou

nt

(m

illion

)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

Tro

pospheri

c N

O2 concentr

ation

(101

5 mole

c/c

m2 )

Vehicle amount

Tro NO2

OMI

Concurrent measurements of tropospheric NO2 from OMI and SCIAMACHY

• Retrieved with common, consistent algorithm

• Collocated, cloud-free measurements at common grid (0.5°x0.5°)

• Differences large over source regions, and larger than combined errors

• Differences in spectra (slant columns) and in AMF (profile shape)

10:00 hrs SCIAMACHY

13:40 hrs OMI

August 2006

What does GEOS-Chem simulate?

Relative decrease in NO2 column from 10am to 1:30 pm

Observed GEOS-Chem

US: -16% -28%

EU: -6% -13%

China: -26% -22%

200320052001

20042002

Biomass burning mainly in afternoon

Jun Wang

Relative increase in NO2 column from 10am to 1:30 pm

Observed GEOS-Chem

Africa: +48% +16%

Indon.: +60% +10%

Brazil: +54% +13%

Summary Tropospheric NO2

GOME/SCIAMACHY NO2 data available for 1996-today, allowing trend analysis.

OMI data (based on collection 3) and GOME-2 is also available now.

Monitoring of China with SCIAMACHY/GOME-2 (overpass at 10.00/9.30 AM ) and OMI (overpass at 13.30 PM)

Data for China will soon be presented on the AMFIC web site.

GOME tropospheric O3 columns

J. de Laat, R. van der A, M. van Weele, R. van Oss, O. Tuinder, B. Mijling and

A. Segers.

Royal Dutch Meteorological Institute (KNMI)

Measuring tropospheric O3 column from space

- air pollution/air quality & greenhouse gas

- Stratosphere > 90 % of total O3 column- Troposphere < 10 % of total O3 column

- Tropospheric O3 is highly variable in space and time:

- Global: - in situ production (tropics and extra-tropics)

- complex chemistry

- Extratropics: - Stratosphere-troposphere exchange

- Tropopause height variations

- Clouds, aerosols (interpretation)

Method Satellite Geographical location

Time resolution

Fishman et al. 1996

TOR TOMS/SBUV Tropics Monthly means

Kim et al. 1996 WAVE 1 TOMS Tropics Monthly means

Hudson and Thompson 1998

MRM TOMS Tropics Monthly means (15 –days)

Munro et al. 1998 GOME Global ??

Ziemke et al. 1998

CCD TOMS Tropics Monthly means

Ziemke et al. 1998

TOMS/MLS/HALOE Tropics Monhtly means

Fishman and Balok 1999

TOR TOMS/SBUV TropicsMid-latitudes (- 50°N)

Monthly means

Kim et al. 2001 SCAN-ANGLE TOMS Tropics Monthly means

Newchurch et al. 2001

LTO TOMS Mountains Monthly means

Fishman et al. 2003

TOR TOMS/SBUV TropicsMid-latitudes

Monthly means

Newchurch et al. 2003

CCP TOMS Tropics Monthly means

Liu et al. 2005 Direct GOME Global Daily

Previous work

Limited height information

[Degrees of Freedom for Signal]

About 5 independent pieces of vertical

information Smoothing of actual profile !!

about 1 piece of tropospheric information [cf. Liu et al., JGR, 2005]

separate troposphere – stratosphere !!!

Directly measuring tropospheric O3 from space:

GOME OPERA algorithm (Ozone ProfilE Retrieval Algorithm)

Tuinder, Van der A, van Oss, Mijling [KNMI]

Non-linear Optimal Estimation [Rodgers], iterative, use of a-priori

Courtesy J. Landgraf, SRON

New approach: data assimilation

Determine SOC by assimilating OPERA O3 profiles using CTM (TM5)

Then: TTOC = TOC - SOC

Advantages:

- No gaps in SOC internal consistency- Better solution for “smoothing error”- Internally consistent tropopause- different O3 (profile) measurements can be used and even combined

Best available estimate of SOC

This figure was originally published in Liu et al. [JGR, 2006]. The upper panel shows the tropospheric O3 columns from GOME O3 profiles for a region over Indonesia in 1997 (7S, 110-125E). Added are also results from a chemistry-transport model calculation (GEOS-CHEM) with realistic emissions and nearby O3 sonde measurements. The lower panel is for a region over the central Pacific.

Added are the black lines: the GOME TOC values from the KNMI OPERA algorithm.

Algorithm development and current status• Assimilation system/algorithm development

– Several problems in the system and algorithm – hampering long assimilation runs – were detected

– Slow progress of solving problems due to long duration of assimilation runs to test stability

– In the mean time …• OPERA algorithm was also considerably improved (Tuinder and Mijling)• New linearized strat. O3 chemistry scheme published

• Current status– Stable assimilation algorithm– 6 test runs with different settings performed for year 2000:– 1 run (iterative assimilation, Cariole v2.1) for 1996 to 2001, currently running

year 2001 [1996-2000 are finished]

• Height depend error propagation in the assimilation included