Retrieval and Interpretation of UV/Vis Satellite Observations of Tropospheric Composition

Randall Martin

With contributions from:With contributions from:Rongming Hu (Dalhousie University)Rongming Hu (Dalhousie University)

Chris Sioris, Xiong Liu, Kelly Chance (Smithsonian Astrophysical Observatory)Chris Sioris, Xiong Liu, Kelly Chance (Smithsonian Astrophysical Observatory)Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington)Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington)

Yongtao Hu, Armistead Russell (Georgia Tech)Yongtao Hu, Armistead Russell (Georgia Tech)Tom Ryerson, Andy Neuman (NOAA/CIRES)Tom Ryerson, Andy Neuman (NOAA/CIRES)

Ron Cohen (Berkeley)Ron Cohen (Berkeley)Aaron Swanson, Frank Flocke (NCAR)Aaron Swanson, Frank Flocke (NCAR)Andreas Richter (University of Bremen)Andreas Richter (University of Bremen)

Major Challenges in Tropospheric Chemistry Major Challenges in Tropospheric Chemistry More Accurate Emission InventoriesMore Accurate Emission Inventories

Understand Processes Controlling Tropospheric OzoneUnderstand Processes Controlling Tropospheric OzoneConstrain Aerosol PropertiesConstrain Aerosol Properties

Top-Down Information from the GOME and Top-Down Information from the GOME and SCIAMACHY Satellite InstrumentsSCIAMACHY Satellite Instruments

GOME 1995-2002Spatial resolution 320x40 km2

Global coverage in 3 days

SCIAMACHY 2002-presentSpatial resolution 60x30 km2

Global coverage in 6 days

Spectral Fit

Remove Stratosphere

Total NO2 Slant Column

Tropospheric NO2 Slant Column

Calculate AMF

Tropospheric NO2 Column

Martin et al., 2002, 2005

Martin et al., 2002

Palmer et al. 2001 Martin et al., 2002, 2003, 2005

5-10x1014

molec cm-2

2-10x1014

molec cm-2

40%

Pixel Uncertainty

Mean Total ±(5x1014 + 30%)

ICARTT Campaign Over and Downwind of Eastern North America in ICARTT Campaign Over and Downwind of Eastern North America in Summer 2004 Summer 2004

Aircraft Flight Tracks and Aircraft Flight Tracks and Validation LocationsValidation Locations Overlaid on SCIAMACHY Overlaid on SCIAMACHY Tropospheric NOTropospheric NO2 2 ColumnsColumns

NASA DC-8 NOAA WP-3D

May-Oct 2004

Air Mass Factor Calculation in SCIAMACHY Retrieval Needs Air Mass Factor Calculation in SCIAMACHY Retrieval Needs External Info on Shape of Vertical Profile External Info on Shape of Vertical Profile

Increased NOIncreased NOxx Emissions from Midlatitude Improves GEOS-CHEM Emissions from Midlatitude Improves GEOS-CHEM

Simulation of NOSimulation of NO22 Profiles Profiles

Remaining Discrepancy In Vertical Profile of NOx EmissionsRemaining Discrepancy In Vertical Profile of NOx Emissions

Midlatitude lightning Mean Bias in AMF:

0.4 Tg N yr-1 12% 9% 3%

1.6 Tg N yr-1 1% 5% 3%

In Situ

0.4 Tg N yr-1

1.6 Tg N yr-1

NO2 Measurements from Cohen (DC-8) and Ryerson (WP-3D)

Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY over North Atlanticover North Atlantic

Profile of NOx Emissions (lifetime) May Explain Remaining DiscrepancyProfile of NOx Emissions (lifetime) May Explain Remaining Discrepancy

May-Oct 2004

SCIAMACHY NO2 (1015 molec cm-2)

GEOS-Chem NO2 (1015 molec cm-2)

1.6 Tg N in Midlat

GEOS-Chem NO2 (1015 molec cm-2)

0.4 Tg N in Midlat

Significant Agreement Between Coincident Cloud-Filtered Significant Agreement Between Coincident Cloud-Filtered SCIAMACHY and In-Situ MeasurementsSCIAMACHY and In-Situ Measurements

r = 0.79

slope = 0.8

1:1 line

Ryerson (WP-3D)

Cohen (DC-8)

Chris Sioris

Cloud-radiance fraction < 0.5

In-situ measurements below 1 km & above 3 km

Assume constant mixing ratio below lowest measurement

Add upper tropospheric profile from mean obs

Horizontal bars show 17th & 83rd percentiles

Cloud-filtered Tropospheric NOCloud-filtered Tropospheric NO22 Columns Retrieved from Columns Retrieved from

SCIAMACHYSCIAMACHY

May-Oct 2004

detectionlimit

A. Richter et al. Nature, 437, 129-132, 2005

1996 - 2002

Annual changes in tropospheric NO2 observed with GOME

Errorweightin

g

Conduct a Chemical Inversion & Combine Top-Down Conduct a Chemical Inversion & Combine Top-Down and Bottom-up Inventories with Error Weightingand Bottom-up Inventories with Error Weighting

A posteriori emissionsTop-Down Emissions

1015 molec cm-2

A Priori NOx EmissionsSCIAMACHY NO2 Columns

1011 molec N cm-2 s-1

GEOS-CHEM model

GEIA

May-Oct 2004

Global Optimal Emission Inventory RevealsGlobal Optimal Emission Inventory RevealsMajor Discrepancy in NOx Emissions from MegacitiesMajor Discrepancy in NOx Emissions from Megacities

r2=0.82 vs a priori

A Posteriori NOx Emissions from East Asia Exceed A Posteriori NOx Emissions from East Asia Exceed Those from Either North America or EuropeThose from Either North America or Europe

A priori (Tg N yr-1)

A posteriori (Tg N yr-1)

East Asia 6.8 9.2

North America 8.1 8.8

Europe 6.5 8.5

Africa 7.1 8.2

SE Asia & India 5.0 5.3

South America 4.4 5.1

Australia 1.1 1.9

Total 39.1 47.0

Large Change in NOx Emissions Near New York CityLarge Change in NOx Emissions Near New York City

1011 atoms N cm-2 s-1 1011 atoms N cm-2 s-1 1011 atoms N cm-2 s-1

A priori A posteriori A posteriori – A priori

7.8 Tg N 0.6 Tg N

r2 = 0.92

Evaluate Each Inventory By Conducting GEOS-CHEM Simulation & Evaluate Each Inventory By Conducting GEOS-CHEM Simulation & Sampling Model Along Aircraft Flight TracksSampling Model Along Aircraft Flight Tracks

NOx (pptv)

Simulation with A Posteriori – Simulation with A Priori

HNO3 (pptv)

7.2 Tg N

PAN (pptv)

In Situ Airborne Measurements Support In Situ Airborne Measurements Support A Posteriori InventoryA Posteriori Inventory

In Situ

GEOS-CHEM (A priori)

GEOS-CHEM (A posteriori)

New England New England New England + Gulf

P-3 Measurements from

Tom Ryerson (NOAA) Aaron Swanson Andy Neuman Frank Flocke (NCAR) (CIRES/NOAA)

Errorweightin

g

EMIS: Emissions Mapping Integration ScienceEMIS: Emissions Mapping Integration ScienceOptimize NOOptimize NOxx Emissions Emissions

A posteriori emissionsTop-Down Emissions

May-Oct 2004

1015 molecules cm-2

NOx Emissions (SMOKE/G.Tech)SCIAMACHY NO2 Columns

1011 molec N cm-2 s-1

Aug 2004

CMAQ

Algorithm for partitioning top-down NOAlgorithm for partitioning top-down NOxx inventory (2000) inventory (2000)

Algorithm tested using synthetic retrieval

GOME NOx emissions

Fuel Combustion1. Spatial location of FF-dominated regions in a priori (>90%)1

Biomass Burning2. Spatiotemporal distribution of fires used to separate BB/soil

VIRS/ATSR fire countsSoils

No fires + background

2

Jaeglé et al., 2005

Biomass Burning (2000)Biomass Burning (2000)

A prioriA priori A posterioriA posteriori

Good agreement with BB seasonality from Duncan et al. [2003]

(±200%)

r2 = 0.72

(±80%)

SE Asia/India N. Eq. Africa S. Eq. Africa

N. Eq. Africa:50% increase

SE Asia/India:46% decrease

Line: A priori(BB)

Bars: A posteriori(BB)

1010atoms N cm-2 s-1

A posteriori total

Jaeglé et al., 2005

Speciated Inventory for Soil emissionsSpeciated Inventory for Soil emissionsA posteriori 70% larger than a priori!

A prioriA priori A posterioriA posteriori

Largest soil emissions: seasonally dry tropical + fertilized cropland ecosystems

(±200%) (±90%)

r2 = 0.62

Soils

Onset of rainy season: Pulsing of soil NOx!

North Eq. Africa

Jaeglé et al., 2005

Soils

East Asia

Liu, Chance, et al., 2005

Direct Retrieval of Tropospheric Ozone from GOMEDirect Retrieval of Tropospheric Ozone from GOMEUsing Optimal Estimation in Ultraviolet with TOMS V8 Using Optimal Estimation in Ultraviolet with TOMS V8 a prioria priori

GOME GEOS-CHEM

Tro

po

sph

eric Ozo

ne C

olu

mn

(Do

bso

n U

nits)

Northern Tropics Remain a Challenge for Satellites and ModelsNorthern Tropics Remain a Challenge for Satellites and Models

Liu, Chance, et al., 2005

GOME GEOS-CHEM

R Bias R Bias

Caracas 0.57 0.8 0.54 8.7

Dakar -0.37 -3.8 0.81 5.2

Tel Aviv 0.96 -1.5 0.94 1.4

Bangkok 0.83 -2.4 0.94 7.2

Comparison with MOZAIC Ozone Measurements

Backscattered Radiation is Sensitive to Single Scattering Albedo Over Backscattered Radiation is Sensitive to Single Scattering Albedo Over Bright Surfaces Bright Surfaces

TOMS Aerosol Index Measures Absorbing Aerosols In Ultraviolet TOMS Aerosol Index Measures Absorbing Aerosols In Ultraviolet Where Rayleigh Scattering Acts as Bright SurfaceWhere Rayleigh Scattering Acts as Bright Surface

]})/[(log])/[({log100 3603311036033110 Rayleighmeas IIIIAI

July 2000

Aerosol Absorption Contributes to Differences Between Aerosol Absorption Contributes to Differences Between Aerosol Optical Depth and the Absorbing Aerosol IndexAerosol Optical Depth and the Absorbing Aerosol Index

Aerosol Vertical Profile Also ImportantAerosol Vertical Profile Also Important

July 2000

1.5

1.1

0.8

0.4

0

3.0

2.2

1.6

0.8

0

July 2000

MODIS

TOMS

Retrieval of Aerosol Single Scattering AlbedoRetrieval of Aerosol Single Scattering AlbedoDetermined with radiative transfer calculation as Determined with radiative transfer calculation as SSA that reproduces

TOMS Aerosol Index when constrained by MODIS aerosol optical depth and GEOS-CHEM aerosol vertical profile

Rongming Hu

July 2000

MODIS AOT

GEOS-CHEM profiles

LIDORT RTM

Min calc – obs aerosol index

SSA

Significant Agreement With Aerosol Single Scattering Albedo Significant Agreement With Aerosol Single Scattering Albedo Determined from AERONETDetermined from AERONET

Rongming Hu

r = 0.8

Slope = 1.01

Intercept = -0.02

ConclusionsConclusions

Growing confidence in top-down constraint on NOx emissions

Underestimate in NOx emissions from megacities, in soils, and North American lightning

Puzzling ozone distribution in northern tropics

Promise for global retrieval of aerosol single scattering albedo

AcknowledgementsAcknowledgements

Rongming Hu (Dalhousie University)Chris Sioris, Xiong Liu, Kelly Chance (Smithsonian Astrophysical Observatory)Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington)Yongtao Hu, Armistead Russell (Georgia Tech)Tom Ryerson, Andy Neuman (NOAA/CIRES)Ron Cohen (Berkeley)Aaron Swanson, Frank Flocke (NCAR)Andreas Richter (University of Bremen)

Funding: • National Aeronautics and Space Administration (NASA)• Canadian Foundation for Innovation (CFI)• Canadian Foundation for Climate and Atmospheric Sciences (CFCAS)• Natural Sciences and Engineering Research Council of Canada (NSERC)• Nova Scotia Research and Innovation Trust (NSRIT)