observations of tropospheric chemistry from space ii

28/1/08 Dr. J.J. Remedios, ERCA Space 3 1

Observations of tropospheric chemistry from space IIJ.J. Remedios

EOS-SRC, Physics and Astronomy, University of Leicester, U.K.

[email protected]

http://www.leos.le.ac.uk/home/


GOME/SCIAMACHY/OMI/GOME-2

EXAMPLE: SCIAMACHY=The Scanning Imaging Absorption Spectrometer for Atmospheric Chartography.

• Grating spectrometer

• Measures solar backscattered radiation in the U/V

• Spectral coverage: 237 to 2380 nm at a spectral resolution of 0.2-1.5 nm.

• Standard mode=nadir

• Also offers limb mode for combined viewing with separation of 7 mins between view of same area.

• The chief target gases are O3, NO2, SO2, HCHO, H2O, CO2, CO and CH4


SCIAMACHY instrument on ENVISAT I


SCIAMACHY instrument on ENVISAT[NADIR MODE]


SCIAMACHY instrument on ENVISAT[SIMILAR BUT MORE LIMITED SPECTRAL RANGES FOR GOME/OMI


NO2 Pollution

Image Courtesy Andreas Richter, IUP Bremen


OMI

• The Ozone Monitoring Instrument (OMI) was launched onboard the NASA EOS Aura satellite in July 2004.

• OMI is a Nadir viewing spectrometer that measures in the spectral range between 270 and 500 nm.

• Has a spectral resolution of 0.52 and 0.45 nm in the UV-1 and UV-2 channels and 0.63 nm in the visible channel.

• OMI has a large swath width of 2600 km, to obtain this viewing swath the viewing angle is 114°

• In the normal operation mode, the OMI pixel size is 13 x 24 km2 making it suitable for comparisons with measurements on an urban scale.


2006 heat wave: UK 15-18 July 2006


In situ

Ground based remote sensing: CMAX-DOAS

Satellites

L. Kramer et al., accepted JGR 2008

Leicester pollution monitoring: NO2


Leicester pollution monitoring of NO2: Seasonal cycle

Leicester in situ sensors

OMI Trop VCD vs field-of-view weighted in situ

VCD = Vertical column density


Leicester pollution monitoring of NO2: Weekly cycle

Gp 1 in situ Rural in situ

OMI VCD FOV-WEIGHTED IN SITU

28/1/08 Dr. J.J. Remedios, ERCA Space 3 13SCIAMACHY HCHO AND GLYOXAL


Biogenic Emissions (C1)Biogenic Emissions (C1)

Formaldehyde is a break-down product of isoprene which is produced by vegetation. Isoprene production is strongly temperature dependent.


Stochastic Events (C1)Stochastic Events (C1)


Role of halogens in the troposphere (C1)

Role of halogens in the troposphere (C1)


Observations of Carbon Monoxide from the MOPITT instrument

J.J. Remedios, Nigel Richards, Robert Parker and Manasvi Panchal

EOS-SRC, Physics and Astronomy, University of Leicester, U.K.

http://www.leos.le.ac.uk/home/


Carbon Monoxide

Why carbon monoxide (CO):• CO is a marker of large-scale influences of pollution on regional and global

scales– It is strongly enhanced in both urban pollution and biomass burning.– It traces regional and inter-continental transport or export/import of such air

(lifetime of a few months)– it marks emission “hot spots”

• Its concentration is related to the oxidising capacity of the troposphere (through OH) and hence it provides a marker of “local” chemical environment and its state – hemispheric differences in CO indicate differing source strengths and

differing chemical lifetimes. – long term trends in CO indicate changes in OH and hence the lifetimes of

greenhouse gases and pollutants.

• It acts as a reference source for incomplete combustion so that many emission factors of other gases are calculated with respect to CO.

• Satellite measurements of CO are available for a long time period of 6 years (MOPITT and other sensors) and illustrate the use of such data in the above applications


MOPITT

• The Measurements of Pollution in the Troposphere (MOPITT) experiment is onboard the EOS-TERRA satellite

• EOS-TERRA was launched on Dec. 18th, 1999 and is still active.

• MOPITT observes infra-red emission at 4.6 m using gas-correlation spectroscopy (length and pressure modulated radiometry).

• Nadir measurements

• For each measurement, both total columns and vertical “profiles” are determined and distributed

• The horizontal resolution is 22 km, swath width of 640 km. The vertical “resolution” of the retrieved profiles is closer to 6-8 km.


Measurements of CO from MOPITT: July 2001

Monthly mean CO observed from daytime retrievals of CO (“surface” retrieved level) – figure from N. Richards, PhD thesis, Leicester, 2004.

Using diagnostics, we can show that there really are enhanced ‘surface’ CO concentrations in regions of biomass burning (Africa) and industrial activity (Houston, South East Asia and China)


“SURFACE” POLLUTION

MOPITT SEVEN DAY COMPOSITE (“700 mb” level) ABOVE HOUSTON, U.S.A.

Sept. 6-15 2002


• MOPITT data can also be used for the monitoring of intense pollution events such as wildfires.

• MOPITT daytime data for August 2000 (monthly mean diagnostic field) indicates high ‘surface’ level CO associated with forest fires in Montana.

WILDFIRES


Fires

MODIS Fire Map: 9th - 19th July, 2004


Deducing horizontal and vertical information

Horizontal

Spatial information: trade-off is “cloud-free coverage” vs spatial resolution vs temporal resolution vs time

Satellite data utility depends on application

Vertical

Conventional wisdom is satellite is measuring vertical column without good vertical resolution.

For infra-red, “conventional” = no sensitivity to surface but not true!

Nighttime MOPITT = sensitive to mid-troposphere

Daytime MOPITT has some surface sensitivity to lower troposphere when T surface > T atmosphere.

Hence day – night is more sensitive to surface/lower troposphere


MOPITT data, single day, 0.5 deg. resolution

Single day of “surface” level MOPITT data: 15th July 2004, 0.5 deg. resolution


MOPITT data, single day, “model” resolution

Single day of “surface” level MOPITT data: 15th July 2004, 2.5 deg. resolution


MOPITT data, 5 days, 0.5 deg. resolution

5 days of “surface” level MOPITT data: 13-17th July 2004, 0.5 deg. resolution


MOPITT data, 5 days, “model” resolution

5 days of “surface” level MOPITT data: 13-17th July 2004, 2.5 deg. resolution


MOPITT data for whole summer

50 days of “surface” level MOPITT data: summer 2004, 0.5 deg. resolution


Deducing horizontal and vertical information

Horizontal

Spatial information: trade-off is “cloud-free coverage” vs spatial resolution vs temporal resolution vs time

Satellite data utility depends on application

Vertical

Conventional wisdom is satellite is measuring vertical column without good vertical resolution.

For infra-red, “conventional” = no sensitivity to surface but not true!

Nighttime MOPITT = sensitive to mid-troposphere

Daytime MOPITT has some surface sensitivity to lower troposphere when T surface > T atmosphere and more CO near surface

Hence day – night is more sensitive to surface/lower troposphere


MONTHLY MEAN, MEXICO CITY. APRIL 2000

MOPITT day (top left), night (top right) and day-night difference (bottom left). 2.5 degree gridded monthly mean surface CO concentrations in the region of Mexico City for April 2000. Also shown (bottom right) are typical day and night mean MOPITT averaging kernels for the Mexico City region of 18-20 degrees North, 98-100 degrees West

DAY

DY-NT

NGT


MONTHLY MEAN U.S. JANUARY 2001

MOPITT day (top left), night (top right) and day-night difference (bottom left) 1 degree gridded monthly mean surface CO concentrations over the United States in January 2001. Also shown (bottom right) are typical day and night mean MOPITT averaging kernels for South Eastern United States in the region of 32-37 degrees North, 85-90 degrees West

DAY

DY-NT

NGT


MONTHLY MEAN, ASIAN EXPORT APRIL 2000

MOPITT day (top left), night (top right) and day-night difference (bottom left) 1 degree gridded monthly mean surface CO concentrations over the United States in January 2001. Also shown (bottom right) are typical day and night mean MOPITT averaging kernels for South Eastern United States in the region of 32-37 degrees North, 85-90 degrees West

DAYNGT

DY-NT


AFRICAN BIOMASS BURNING: 15th JUNE to 3rd

AUGUST 2004

Uplifted air in outflow

“Source” regions for CO

DAY

NGT

DN-NTAATSR FIRES


“Surface” level MOPITT monthly mean CO data: INDONESIA

October 2002, 0.5 deg. resolution

Day

DY-NT

Night


27/09/02 - Orbit 03006

Ethane

EthyneSIMULATION. RED=WITH; BLUE=WITHOUT

MIPAS LIMB VIEWING. R. Parker

9.5 km

ALSO PAN, ACETONE, FORMIC ACID


BIOMASS BURNING SUMMARY

• Pyrogenic emissions have a large, varying impact on the troposphere.

• CO is a natural marker of biomass burning in the absence of strong industrial pollution. It should provide regional and seasonal estimates of flux into the troposphere but remains a challenge for research.

• Satellite CO provides some good information as to origin of air masses.

• Exciting development is the observation of organic speciation (see next section) which will permit more precise studies of biomass plume outflow characteristics. Differentiation of outputs from different vegetation types?

• Laboratory for looking at inter-annual changes in pollutant chemistry


CONCLUSIONS FOR CO

What can we do now:

• Harness the observing power of satellites to provide regional and global information previously unavailable

Megacities

Strong stationary emission sources (can do this for shortwave i/r also and potentially better)

Intercontinental transport of pollution

Global (climate) impact of anthropogenic urban and fire emissions

• Inverse modelling to derive regional fluxes

• Assimilation to improve daily CO fields


Assimilated MOPITTCO at 3-5 km


Mid-trop /UT limb sounding, i/r instruments: MIPAS on ENVISAT, ACE on SCISAT

MIPAS on ENVISAT

LAUNCHED ON MARCH 1st 2002

MIPAS as an example

a) Limb Sounding, Profiles: 6- 68 km; nominal 3 km vert. resn/spacing (6-48 km)

b) F.T. i/r emission spectrom: 685-2410 cm-1 in 4 bands. 0.025 cm-1 resn. (unapod.)

c) Coverage: pole to pole. Profiles every 75 s or approx. 500 km.

d) VOCs are non-operational products:

• Ethane, ethyne, acetone, PAN, formic acid, formaldehyde


Measurement range (km)

Vertical sampling Observation mode

Observation description

Scientific objective 90o 0o 90o 0o

Number of samples per

limb sequence

Along track

sampling (km)

N/A Nominal Stratospheric chemistry and

dynamics 12-76 5-69

1.5 km steps in UTLS, widened to 4.5 km in the lower mesosphere

27 410

UTLS-1

Upper Troposphere Lower Stratosphere

(primary UTLS mode)

Atmospheric processes in the UTLS region (including the Tropical Tropopause Layer)

5.5-49 11.5-55

1.5 km steps at altitudes below 19 km, widening to

4.5 km steps by 49 km

1.5 km steps at altitudes below 25 km, widening to 4.5 km steps by

55 km

19 290

UTLS-2 Upper Troposphere Lower Stratosphere

Higher spatial sampling than UTLS-1 to test the capabilities of 2-D retrievals for increasing

the along-track resolution.

12-42 2 km steps between 12 and 20 km, increasing to 5 km steps by 42 km.

11 180

MA Middle Atmosphere

Used to study linkages between the upper atmosphere and the

stratosphere, i.e. global circulation.

18-102 3 km steps 29 430

UA Upper Atmosphere Mainly dedicated to

measurements of high-altitude NO.

42-172 3 km steps between 42 and 102 km and

5 km steps above 102 km 35 515

NLC Middle/Upper Atmosphere in

summer

Detection of noctilucent clouds which occur in the polar

summer mesopause region 39-102

Generally 3 km steps but reduced to 1.5 km steps between 78 and 87 km

35

515

AE Aircraft Emissions Detection of aircraft emissions

and their effects on the chemistry in the UTLS.

7-38 1.5 km steps below 13 km increasing to 4.5 km steps by 38 km.

12 N/A

MIPAS special observation modes at reduced resolution (current mode)


MIPAS Infra-red spectra – unprecedented series of thermal emission spectra

Influence of clouds observed as:

• distinct spectral offset dependent on optical depth (extinction)

• pressure-broadened gas absorption lines from tropospheric radiation scattered into the limb path (cloud location, temp., mean particle size)

• characteristic spectral features for NAT PSCs

• Influence on trace gas retrievals

Comparison of MIPAS spectra for clouds of different optical depth in the field of view, tangent height 15.7 km, 5 th May 2003. J. Greenhough, Leicester


DETECTION RESULTS (PAN):Remedios et al., ACP, 2007

Left: ΔY (black) overplotted with ΔF (red) for the 794 cm-1 PAN band fitted for 490 pptv PAN at 10.9 km.

Below: Close up of above between 775 – 810 cm-1 with ΔY shifted by -200 nW.

Above: ΔY + ΔF for the 1163 cm-1 PAN band also fitted for 490 pptv PAN at 10.9 km.

Simultaneous detection of 2 PAN bands in separate measurement channels with the same fitted concentrations provide confirmation of detection and accuracy of inferred PAN concentrations.


DETECTION RESULTS (OTHER ORGANICS)

FORMIC ACID (“620 pptv”) 11 km

ACETONE (540 pptv) 11 km


PAN/Acetone Retrieval method [David Moore]

• Optimal estimation

• a priori estimates for PAN/Acetone based on mid-latitude MIPAS balloon measurements (300 % a priori covariance)

• OPtimal Estimation Retrieval Algorithm (OPERA)

– Performs a joint retrieval of a target gas and total particle extinction from MIPAS-E spectral data by integrating spectral signals at each altitude in two distinct regions:

• Regions sensitive to target gas

– PAN (4 regions between 787 – 790 cm-1)

– Acetone (1216.75 – 1217.375 cm-1)

• One region sensitive to aerosol/clouds (dependent on the MIPAS-E band)

– 832.3125 – 834.4375 cm-1 for band A retrievals (PAN), 1232.25-1234.375 cm-1 for band B retrievals (Acetone)

• Allows retrievals in presence of thin cloud in upper troposphere and lower stratosphere

• Retrievals performed from reduced-resolution (0.0625 cm-1) MIPAS-l1b spectra (version 4.65) in UTLS-1 mode.

• P, T, H2O, O3 and HNO3 - offline l2 products incorporated (v 4.65)

• Spectroscopic data from MIPAS spectroscopic database (J.M. Flaud), PAN cross-section (G. Allen); Acetone cross-sections (Alison Waterfall)


Global PAN – 160, 220 mb level

• Orbits 12777-12863• 9-15th August 2004• 160 mb level (~13km)• 260 mb level (~11 km)


Global PAN – 220 mb level

• Orbits 12777-12863

• 9-15th August 2004

• 220 mb level (~ 13 km)

Biomass burning?


PAN zonal cross-section

• OPERA retrieved PAN from MIPAS-E spectra

• (9-15th August 2004, orbits 12777-12863)

• GEOS-CHEM PAN

• 9th August 2004 at 12 GMT

units of pptv


ACETONE – 160 mb

ACETONE – 220 mb

• MIPAS-E Orbits 12777-12794

• 9-10th August 2004


Acetone zonal cross-section

• OPERA retrieved acetone from MIPAS-E spectra

• 9-10th August 2004, orbits 12777-12792

• GEOS-CHEM Acetone

• 9th August 2004 at 12 GMT

units of pptv


Oceanic sources of acetone: ARNOLD ET AL.: 3-D MODEL STUDY OF NEW

ACETONE PHOTOLYSIS, JGR, 110, 2005

Changes in photolysis rate alter perceptions of oceanic source/sink.

Direct measurements of ocean sink not possible so indirect test via upper troposphere chemistry


ACE BIOMASS PROFILESACE P.I. Peter Bernath, York

ACE Enhanced and Background Mixing Ratios from the 2004 Fire Period

Dufour et al, ACPD, 2006 Rinsland, GRL, 2005


ACE HCN, CO, and C2H6 Tropical Biomass Burning Measurements

ACE Measurements

Rinsland, GRL, 2005


Methanol Retrieval

Dufour et al, ACP, 2006


ACE measurements of methanol:G. Dufour et al., Atmos. Chem. Phys., 6, 3463–3470, 2006


ACE methanol: locations of enhancements (UT)


Implications for VOC emissions

PYROGENICS

• We observe big influences of pyrogenic VOC emissions on the mid-troposphere and UT. What are the pyrogenic emission factors for VOCs and what is the near-surface fast chemistry effect?

• Critical areas for pyrogenics? – Central and Central-South Africa, Amazonia, Chnia and S.E. Asia, Siberia and Alaska/Canada, Australia.

OCEANIC SOURCES

• To reconcile tropospheric estimates of acetone/PAN, for example, oceanic sources/sinks have been postulated. Large uncertainties!

• How do we find new oceanic sources – are they related to biology?

• How do we measure the influence of the ocean mixed layer as a potential reservoir of VOC, for example for methanol?

SATELLITES AND TOP-DOWN ESTIMATES

• Emission verification

• Inverse modelling

• Identification of knowledge gaps


FUTURE SATELLITE SUPPORT:

RESEARCH AND GMES MISSIONS

What can we do further

• Improve the swath width of new sensors

• Improve the vertical resolution – combine UV-VIS-SWIR with TIR infra-red sensors, combine with limb measurements, e.g. of CO.

• Improve the temporal resolution through the day – multiple LEO sensors (constellations) / geostationary

[e.g. traffic sources peak in rush hours, factories have different temporal signatures, fires peak in afternoon and smoulder into early evening]

• Measure a range of species

• Inverse model the data to derive detailed emission sources

• Assimilate the data to enhance “chemical weather” forecasts


Acknowledgements

• EOS, Leicester University

• Cambridge University

• MOPITT team at NCAR (P.I. John Gille)

• MOPITT team at Toronto (P.I. Jim Drummond)

• NASA for provision of data

• All the satellite teams of the instruments in this talk!

Acknowledgments to ESA, NERC and EC for support

Contrails, Burton-on-Trent,

Dave Moore, Weather, Feb 2005

observations of tropospheric chemistry from space ii

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