Randall Martin

Applying Space-Based Measurements of Ultraviolet and Visible Radiation to Understand Tropospheric

Composition

With contributions from:With contributions from:Aaron Van Donkelaar, Rongming Hu (Dalhousie University)Aaron Van Donkelaar, Rongming Hu (Dalhousie University)

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

Yunsoo Choi, Yuhang Wang, Yongtao Hu, Armistead Russell (Georgia Tech)Yunsoo Choi, Yuhang Wang, Yongtao Hu, Armistead Russell (Georgia Tech)Arlene Fiore (GFDL)Arlene Fiore (GFDL)

Tom Ryerson (NOAA)Tom Ryerson (NOAA)Ron Cohen (Berkeley)Ron Cohen (Berkeley)Bill Brune (Penn State)Bill Brune (Penn State)

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

Understand Aerosol Sources and Properties Understand Aerosol Sources and Properties

Relative Uncertainty

Global Surface NOGlobal Surface NOx x Emissions Uncertain to Factor of 2Emissions Uncertain to Factor of 2Implications for Tropospheric Ozone, Aerosols, and Indirect EffectImplications for Tropospheric Ozone, Aerosols, and Indirect Effect

Here in Tg N yr-1 (based on)Fossil Fuel 24 (GEIA)

Biomass Burning 6 (Duncan et al., 2003)

Soils 5 (Yienger and Levy, 1995)

NOx Emissions (Tg N yr-1)Fossil Fuel (20-33) Biomass Burning (3-13) Soils (4-21)

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

•Nadir-viewing solar backscatter instruments including ultraviolet and visible wavelengths

• Low-elevation polar sun-synchronous orbit, late morning observation time

•GOME 1995-2002•Spatial resolution 320x40 km2

•Global coverage in 3 days

•SCIAMACHY 2002-presentSpatial resolution 60x30 km2

Global coverage in 6 days

Spectral Fit of NOSpectral Fit of NO22

Scattering by Earth surface and by atmosphere

Backscatteredintensity IB

Solar Io

Distinct NO2 Spectrum

RingeIAI s

B )()()( 0

Nonlinear least-squares fitting

Ozone

NO2

O2-O2

Albedo A

Also Weak H2O line

Based on Martin et al., 2002

Total NOTotal NO22 Slant Columns Observed from SCIAMACHY Slant Columns Observed from SCIAMACHY Dominant stratospheric background (where NODominant stratospheric background (where NO22 is produced from N is produced from N22O oxidation)O oxidation)

Also see tropospheric hot spots (fossil fuel and biomass burning)Also see tropospheric hot spots (fossil fuel and biomass burning)

May-October 2004

Perform a Radiative Transfer Calculation to Account for Perform a Radiative Transfer Calculation to Account for Viewing Geometry and ScatteringViewing Geometry and Scattering

RcRo

IB,o IB,c

Pc

Rs

•GOMECAT (Kurosu) & FRESCO Clouds Fields [Koelemeijer et al., 2002]

•Surface Reflectivity [Koelemeijer et al., 2003]

•LIDORT Radiative Transfer Model [Spurr et al., 2002]

•GEOS-CHEM NO2 & aerosol profiles d

Io

Based on Martin et al., 2002, 2003

Cloud Radiance Fraction IB,c / (IB,o + IB,c)

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

SCIAMACHY SCIAMACHY (Data (Data NASA) NASA)

May-Oct 2004

detectionlimit

USE RETRIEVED NOUSE RETRIEVED NO22 COLUMNS TO MAP NO COLUMNS TO MAP NOx x EMISSIONSEMISSIONS

Emission

NO NO2

HNO3

lifetime ~hours

NITROGEN OXIDES (NOx)

BOUNDARYLAYER

GOMESCIAMACHY

NO/NO2

W ALTITUDE

Tropospheric NO2

column ~ ENOx

Errorweightin

g

EMIS: Emissions Mapping Integration ScienceEMIS: Emissions Mapping Integration ScienceOptimize North American NOOptimize North American 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

Interpret Satellite Observations Using Interpret Satellite Observations Using GEOS-CHEM Chemical Transport ModelGEOS-CHEM Chemical Transport Model

• Assimilated Meteorology (GEOS)

• 2ox2.5o horizontal resolution, 30 vertical layers

• O3-NOx-VOC chemistry

• SO42--NO3

--NH4+-H2O, dust, sea-salt, organic & elemental carbon aerosols

• Interactive aerosol-chemistry

• Anthropogenic and natural emissions

• Cross-tropopause transport

• Deposition

Calculated Mean Surface Ozone for August 1997

May-Oct 2004

48 Tg N yr-1

48 - 38 Tg N yr-1

Global Top-Down Emission Inventory RevealsGlobal Top-Down Emission Inventory RevealsMajor Discrepancy in NOx Emissions from MegacitiesMajor Discrepancy in NOx Emissions from Megacities

GEIA

ICARTT: COORDINATED ATMOSPHERIC CHEMISTRY CAMPAIGN OVER ICARTT: COORDINATED ATMOSPHERIC CHEMISTRY CAMPAIGN OVER EASTERN NORTH AMERICA AND NORTH ATLANTIC IN SUMMER 2004EASTERN NORTH AMERICA AND NORTH ATLANTIC IN SUMMER 2004

International, multi-agency collaboration targeted at regional air quality, pollution outflow, transatlantic transport, aerosol radiative forcing

Terra

ERS

MISR, MODIS, MOPITT

ERS-2

GOME

Envisat

SCIAMACHY

Aqua

AIRS, MODIS

NASA DC-8

UK BAE-143

DLR Falcon

NOAA-P3

Canada Convair

NASAProteus

North American NOx Emissions (May – October)North American NOx Emissions (May – October)Largest Change in Northeastern US CoastLargest Change in Northeastern US Coast

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

GEOS-CHEM (NAPAP) SCIAMACHY SCIAMACHY - NAPAP

7.6 Tg N 8.4 Tg N 0.8 Tg Nr2

= 0.85

Evaluate Top-Down and Bottom-Up NOx InventoriesEvaluate Top-Down and Bottom-Up NOx InventoriesConduct GEOS-CHEM Simulation For Each InventoryConduct GEOS-CHEM Simulation For Each Inventory

Sampled GEOS-CHEM Along Flight TracksSampled GEOS-CHEM Along Flight Tracks

NOx (ppbv)

Simulation with SCIAMACHY – Original NOx Emission Inventory

HNO3 (ppbv)

In Situ Airborne Measurements Support Top-Down In Situ Airborne Measurements Support Top-Down InventoryInventory

In Situ

GEOS-CHEM (Bottom-up)

GEOS-CHEM (Top-Down)

New England New England + Gulf Remote

P-3 Measurements from Tom Ryerson (NOAA)

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

Soil emissionsSoil 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

Transient Enhancements In GOME NOTransient Enhancements In GOME NO2 2 Columns from LightningColumns from Lightning

Choi et al., GRL, 2005

SCIAMACHY Shows Elevated NOx Export from North AmericaSCIAMACHY Shows Elevated NOx Export from North America

May-Oct 2004

SC

IAM

AC

HY

NO

2 (1015

mo

lec cm-2

)G

EO

S-C

HE

M N

O2 (101

5 m

olec cm

-

2)

May-Oct 2004

Explained by Model Bias in Upper Tropospheric NOExplained by Model Bias in Upper Tropospheric NOxx

GEOS-CHEM NO2

Cohen NO2

Errorbars Show 17th and 83rd percentiles

West of -60 degrees lon, “land” East of -60 degrees lon, “ocean”

GEOS-CHEM NO

Brune NO

GEOS-CHEM low by 7.5% in column

GEOS-CHEM low by factor of 2 in column

EMISSION CONTROL STRATEGY FOR OZONE POLLUTION:EMISSION CONTROL STRATEGY FOR OZONE POLLUTION: ARE NO ARE NOxx OR VOCs THE LIMITING PRECURSORS? OR VOCs THE LIMITING PRECURSORS?

HCHO/NO2 < 1 (blue) VOC-limited

HCHO/NO2 > 1 (green-red) NOx-limited

Use GOME observations ofHCHO/NO2 ratio to determineozone production regime[Sillman, 1995]

Martin et al. [2004]

Aerosol Single Scattering Albedo Major Source of Aerosol Single Scattering Albedo Major Source of Uncertainty in Global Radiative Forcing EstimatesUncertainty in Global Radiative Forcing Estimates

IPCC [2001]

Maximum Sensitivity to Aerosol Optical Thickness Over Dark SurfacesMaximum Sensitivity to Aerosol Optical Thickness Over Dark SurfacesMore Sensitive to Single Scattering Albedo Over Bright SurfacesMore Sensitive to Single Scattering Albedo Over Bright Surfaces

King et al., BAMS, 1999

Saharan Dust Plume Staten Island Refinery Fire

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

300 400 500 600 700 800W avelength [nm ]

0.0

0.2

0.4

0.6

Ref

lect

ivity

TOA spectral albedo measured by GOME

MODIS Aerosol Optical Depth Includes Both MODIS Aerosol Optical Depth Includes Both Scattering and Absorbing AerosolsScattering and Absorbing Aerosols

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

Rongming Hu

July 2000

Modeled Organic Carbon Too Low in Southeast in JulyModeled Organic Carbon Too Low in Southeast in July

Ground-Based Measurements from IMPROVE (ug m-3)

GEOS-CHEM model calculation (ug m-3)

Aaron Van Donkelaar

IMPROVE minus GEOS-CHEM OC [ug/m3], 2001

Summer Organic Carbon BiasSummer Organic Carbon BiasGEOS-CHEM already accounts for primary and secondary GEOS-CHEM already accounts for primary and secondary

sources of organic aerosolsources of organic aerosol

Aaron Van Donkelaar

Distribution of Isoprene Emissions Similar to OC BiasDistribution of Isoprene Emissions Similar to OC BiasMounting Field and Laboratory Evidence of OC Yield from Isoprene Mounting Field and Laboratory Evidence of OC Yield from Isoprene

Oxidation ProductsOxidation Products

2001 Isoprene Emission (1012 moles C cm-2 s-1)

Aaron Van Donkelaar

IMPROVE minus GEOS-CHEM OC [ug/m3], 2001

Organic Carbon from Isoprene Oxidation Products Organic Carbon from Isoprene Oxidation Products Largely Corrects BiasLargely Corrects Bias

Aaron Van Donkelaar

ConclusionsConclusions

•Growing confidence in top-down constraint on NOx emissions

•Gross-underestimate in NOx emissions from megacities

•Soil NOx emissions underestimated, especially from Northern Equatorial Africa

•North American lightning NOx emissions underestimated

•Promise for global retrieval of aerosol single scattering albedo

•Low yield of organic carbon from isoprene oxidation products reduces model bias

AcknowledgementsAcknowledgements

Aaron Van Donkelaar, Rongming Hu (Dalhousie U.)Chris Sioris, Kelly Chance (Smithsonian)Lyatt Jaeglé, Linda Steinberger (U. of Washington)Yunsoo Choi, Yuhang Wang, Yongtao Hu, Armistead Russell (Georgia Tech)Arlene Fiore (GFDL)Tom Ryerson (NOAA)Ron Cohen (Berkeley)Bill Brune (Penn State)

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)