space-based insight into the global sources of nitrogen oxides with implications for tropical...
TRANSCRIPT
Space-based insight into the global sources of nitrogen oxides with implications for tropical tropospheric ozone
Randall Martin
Dalhousie University
With contributions from
Bastien Sauvage, Neil Moore, Thomas Walker: Dalhousie University
Christopher Sioris: Environment Canada
Christopher Boone and Peter Bernath: University of Waterloo
Jerry Ziemke: NASA Goddard
Lyatt Jaegle: University of Washington
Xiong Liu, Kelly Chance: Harvard-Smithsonian Center for Astrophysics
Tropospheric Ozone is a Key Species in Climate and Air Tropospheric Ozone is a Key Species in Climate and Air QualityQuality
Tropopause
Stratopause
•Major greenhouse gas
•Largely controls atmospheric oxidation
•Primary constituent of smog
Stratosphere
Troposphere
Ozonelayer
Mesosphere
Half of all Americans live in regions that exceed the surface ozone standard
Fires Biosphere Humanactivity
Nitrogen oxides (NOx) CO, Volatile Organic Compounds (VOCs)
Ozone (O3) Hydroxyl (OH)
Global Budget of Tropospheric Ozone Driven By Production in the Troposphere
hv hv,H2O
Ozone Production is Largely NOx-Limited
Bottom-up Estimates for Global NOx Emissions (Range) in Tg N yr-1 for 2000
Fossil Fuel 24 (20-33)
Biomass Burning 6 (3-13) Soils 7 (4-21) Lightning 6 (1-20)
How Do We Evaluate and Improve A Priori Bottom-up How Do We Evaluate and Improve A Priori Bottom-up Inventories? Inventories?
Top-Down Information from Satellite ObservationsTop-Down Information from Satellite Observations
•Nadir-viewing solar backscatter instruments including ultraviolet and visible wavelengths
• GOME 1995-2003•Spatial resolution 320x40 km2
•Global coverage in 3 days
•SCIAMACHY 2002-presentSpatial resolution 60x30 km2
Global coverage in 6 days
•OMI 2004-presentSpatial resolution up to 13x24 km2
Daily global coverage
•GOME-2 2006-presentSpatial resolution up to 40x80 km2
Daily global coverage
Retrieve NORetrieve NO22 Columns To Map Surface NO Columns To Map Surface NOx x EmissionsEmissions
Emission
NO NO2
HNO3
lifetime <1 day
NITROGEN OXIDES (NOx)
BOUNDARYLAYER
NO/NO2
W ALTITUDE
Tropospheric NO2 column ~ ENOx
O3
hv
NOx = NO + NO2
Spectral Fit of NOSpectral Fit of NO22
Scattering by Earth surface and by atmosphere
Backscatteredintensity IB
Solar Io
Distinct NO2 Spectrum
seIAIB )()()( 0
Nonlinear least-squares fitting
Ozone
NO2
O2-O2
Albedo A
Martin et al., JGR, 2002, 2006
Fitting Uncertainty 5-10x1014 molec cm-2
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
Uncertainty in Stratospheric Removal 2-10x1014 molec cm-2
Perform an Air Mass Factor (AMF) Calculation to Account for Perform an Air Mass Factor (AMF) 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
Martin et al., JGR, 2002, 2003, 2006
Cloud Radiance Fraction IB,c / (IB,o + IB,c)
AMF Uncertainty 40%
Cloud-filtered Tropospheric NOCloud-filtered Tropospheric NO22 Columns Retrieved from Columns Retrieved from
SCIAMACHYSCIAMACHY
May 2004 – Apr 2005
Martin et al., JGR, 2006
Mean Uncertainty ±(5x1014 + 30%) NO/NO2
W ALTITUDE
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
GEOS-Chem Chemical Transport ModelGEOS-Chem Chemical Transport Model
• Assimilated Meteorology (NASA GMAO)
• 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
Solve continuity equation for individual gridboxes
n
n P Lt
U
AccumulationTransport flux divergence
Sources:-emissions-chemical prod.
Sinks: - chemical loss - deposition
x ~ 200 km
z ~ 1 km
41 tracers ~90 species 300 reactions
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 Lightning NOIncreased Lightning NOxx Emissions Improves GEOS-CHEM Emissions Improves GEOS-CHEM
Simulation of Midlatitude NOSimulation of Midlatitude 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
Martin et al., JGR, 2006
Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY over North Atlanticover North Atlantic
Profile of NOx Emissions (lifetime) Contributes to Remaining Profile of NOx Emissions (lifetime) Contributes to Remaining DiscrepancyDiscrepancy
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
Martin et al., JGR, 2006
Significant Agreement Between Coincident Cloud-Filtered Significant Agreement Between Coincident Cloud-Filtered SCIAMACHY and In-Situ MeasurementsSCIAMACHY and In-Situ Measurements
r = 0.77
slope = 0.82
1:1 line
Ryerson (WP-3D)
Cohen (DC-8)
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 percentilesMartin et al., JGR, 2006
Errorweighting
Conduct a Chemical Inversion For NOx EmissionsConduct a Chemical Inversion For NOx Emissions
A posteriori emissionsxTop-Down Emissions
1015 molec N cm-2
A Priori NOx Emissions (xa)SCIAMACHY NO2 Columns (y)
1011 molec N cm-2 s-1
GEOS-CHEM model F(x)
( ) ( T TJ -1 -1y a a ax y F(x)) S (y -F(x)) + (x - x ) S (x - x )min cost function
Sy
Sa
Significant Agreement Between A Priori and A PosterioriSignificant Agreement Between A Priori and A PosterioriLargest Discrepancy in East Asia and Major Urban CentersLargest Discrepancy in East Asia and Major Urban Centers
r2=0.82
Martin et al., JGR, 2006
(2000)
0
2
4
6
8
10
12
East Asia NorthAmerica
Europe Africa SE Asia& India
SouthAmerica
Australia
NO
x E
mis
sio
ns
(Tg
N/y
r)
A Posteriori NOx Emissions from East Asia Exceed Those from Either A Posteriori NOx Emissions from East Asia Exceed Those from Either North America or EuropeNorth America or Europe
Implications for North American Air QualityImplications for North American Air Quality
A posteriori (46 Tg N/yr)
A priori (38 Tg N/yr)
Martin et al., JGR, 2006
Thomas Walker
INTEX-B: Long-Range Transport to North AmericaINTEX-B: Long-Range Transport to North AmericaAverage over April – May 2006Average over April – May 2006
standard
No lightning
No Asian NOx
Whistler, BC
Ozo
ne
Co
lum
n
(Do
bso
n
Un
its)
ΔO
zon
e C
olu
mn
(D
ob
son
Un
its)
ΔO
zon
e (pp
bv)
Sensitivity at 750 hPa to PAN
Sensitivity to Asian Emissions Sensitivity to Lightning
Liu et al., JGR, 2006
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)
In Situ Data Used for Tropical Evaluation
1.MOZAIC programme 1994-2005
MOZAIC & SHADOZ sites used for model evaluation
2.SHADOZ ozone sonde network (Thompson et al., 2003a;b): 1998-2004
> 9000 vertical profiles within the Tropics (30°N-30°S)
Northern Tropics Remain a Challenge for Satellites and ModelsNorthern Tropics Remain a Challenge for Satellites and ModelsScan-Angle Method (Kim et al., 2005) UV Method That Best Captures In Scan-Angle Method (Kim et al., 2005) UV Method That Best Captures In
Situ Seasonal VariationSitu Seasonal Variation
Liu et al., JGR, 2006
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
Biomass Burning2. Spatiotemporal distribution of fires used to separate BB/soil
VIRS/ATSR fire countsSoils
No fires + background
2
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
Jaeglé et al., 2005
8.9
Speciated 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
Improved Bottom-up Inventory for Soil NOx Emissions
Developments of soil temp/soil moisture, pulsing, fertilizer application
Change in NOx Emissions Soil NOx Emissions
Δ Global Total = +1.9 Tg N/yr Global Total = 7.8 Tg N/yr
molec cm-2 s-1Δ molec cm-2 s-1
Neil Moore
GOME Model originalModel constrained
NO2 Column (1015 molec cm-2)
Top-down Constraint on Biomass Burning NOx Emissions
DJF
MAM
Improved simulation of lower tropospheric O3 versus aircraft measurements
Pre
ssur
e (h
Pa)
O3 Mixing Ratio (ppbv) Sauvage et al., ACP, 2007
Bottom-upTop-down
Observed
Global Lightning NOx Source Remains UncertainGlobal Lightning NOx Source Remains UncertainConstrain with Top-down Satellite ObservationsConstrain with Top-down Satellite Observations
SCIAMACHY Tropospheric NO2 Columns
ACE-FTS Limb HNO3 Measurements in the Upper Troposphere
OMI & MLSTropospheric O3
Flashes km-2 min-1
10-year Mean Flash Rate from the OTD & LIS Satellite Instruments10-year Mean Flash Rate from the OTD & LIS Satellite Instruments
Global rate 44±5 flash/sec [Christian et al. 2003]
30 – 500 moles NO per flash
Current Estimate of Annual Global NOx SourcesCurrent Estimate of Annual Global NOx SourcesAs Used In GEOS-ChemAs Used In GEOS-Chem
1010 molecules N cm-2 s-1
Lightning
Global: 6.0 Tg N yr-1
Tropics: 4.4 Tg N yr-1
Other NOx sources: (fossil fuel, biofuel, biomass burning, soils)
39 Tg N yr-1
Simplified Chemistry of Nitrogen OxidesSimplified Chemistry of Nitrogen OxidesExploit Longer Lifetimes in Upper TroposphereExploit Longer Lifetimes in Upper Troposphere
NO NO2
NOx lifetime < day
Nitrogen Oxides (NOx)
BoundaryLayer
NO/NO2
with altitude
hv
NO NO2
O3, RO2
hv
HNO3
NOx lifetime ~ week
lifetime ~ weeks
Ozone (O3)lifetime ~ month
Upper Troposphere
Ozone (O3)
lifetime ~ days
HNO3
O3, RO2
StrategyStrategy
1) Use GEOS-Chem model to identify species, regions, and time periods dominated by the effects of lightning NOx production
2) Constrain lightning NOx source by interpreting satellite observations in those regions and time periods
Simulated Monthly Contribution of Lightning, Soils, and Simulated Monthly Contribution of Lightning, Soils, and Biomass Burning to NOBiomass Burning to NO22 Column Column
Tropospheric NO2 (1014 molec cm-2)
Annual Mean NOAnnual Mean NO22 Column at Locations & Months with >60% Column at Locations & Months with >60%
from Lightning, <25% from Surface Sourcesfrom Lightning, <25% from Surface Sources
Meridional Average
SCIAMACHY (Uses 15% of Tropical Observations)
GEOS-Chem with Lightning (8% bias, r=0.75)
GEOS-Chem without Lightning (-60% bias)
NO2 Retrieval Error ~ 5x1014 molec cm-2
GEOS-Chem with Lightning (6±2 Tg N yr-1)
SCIAMACHY
GEOS-Chem without Lightning
Martin et al., 2007
ACE HNOACE HNO33 over 200-350 hPa for Feb 2004 – Feb 2006 over 200-350 hPa for Feb 2004 – Feb 2006
HNO3 Mixing Ratio (pptv)
Data from Boone et al., 2005
GEOS-Chem Calculation of Contribution of Lightning to HNOGEOS-Chem Calculation of Contribution of Lightning to HNO33
HNO3 from Lightning Fraction from Lightning
Focus on 200-350 hPa
HNO3 With Lightning (6±2 Tg N yr-1)
No Lightning
Fraction of HNO3 from Lightning
Jan
Jul
Annual Mean HNOAnnual Mean HNO33 Over 200-350 hPa at Locations & Over 200-350 hPa at Locations &
Months with > 60% of HNOMonths with > 60% of HNO33 from Lightning from Lightning
Meridional AverageACE (Uses 83% of Tropical Measurements)
GEOS-Chem with Lightning (-12% bias, r=0.75)
GEOS-Chem without Lightning (-80% bias)
HNO3 Mixing Ratio (pptv)
ACE-FTS
GEOS-Chem with Lightning (6±2 Tg N yr-1)
GEOS-Chem without Lightning
HNO3 Retrieval Error ~35 pptv
Martin et al., 2007
OMI/MLS Tropospheric Ozone ColumnOMI/MLS Tropospheric Ozone Column
Jan
Jul
Data from Ziemke et al. (2006)
Calculated Monthly Contribution of Lightning to OCalculated Monthly Contribution of Lightning to O33 Column Column
O3 Column from Lightning Column Fraction from Lightning
Martin et al., 2007
Annual Mean Tropospheric OAnnual Mean Tropospheric O33 Columns at Locations & Columns at Locations &
Months with > 40% of Column from LightningMonths with > 40% of Column from Lightning
Meridional AverageOMI/MLS (Uses 15% of Tropical Measurements)
GEOS-Chem with Lightning (-1% bias, r=0.85)
GEOS-Chem without Lightning (-45% bias)
Tropospheric O3 (Dobson Units)
OMI/MLS
GEOS-Chem with Lightning (6±2 Tg N yr-1)
GEOS-Chem without Lightning
O3 Retrieval Error < 5 Dobson Units
Martin et al., 2007
Scaled versionOriginal version
Same intensity: 6 Tg N yr-1
Spatial Distribution of GEOS-Chem Lightning NOx SourceSpatial Distribution of GEOS-Chem Lightning NOx Source
DJF DJF
JJA JJA
Lightning NOx emissions (109 molec N cm-2 s)
Sauvage et al., ACP, 2007
Local Scaling to Match 10-year HRAC Seasonal OTD-LIS Climatology
Ozone Sensitivity to Spatial Distribution of Lightning NOx
-O3 highly sensitive in the MT-UT
-O3 simulations improved by 5-15 ppbv versus In situ
-Main influence near subsidence areas: South America; Middle East; Atlantic
Pre
ssu
re (
hP
a)
Pre
ssu
re (
hP
a)
O3 (ppbv)O3 (ppbv)
OriginalModifiedIn situ
Snapshot of the model evaluation
Sauvage et al., ACP, 2007
Scaled
Ozone sensitivity to Lightning NOx4 TgN/yr; 6 TgN/yr; 8 TgN/yr
Evaluation for the Tropics 8Tg N/yr O3 over estimation 4Tg N/yr O3 under estimation 6±2Tg N/yr general agreement
Pre
ssu
re (
hP
a)
Pre
ssu
re (
hP
a)
O3 (ppbv)
O3 (ppbv)Sauvage et al., ACP, 2007
ScaledScaledScaled
Lightning NOx Dominant Source for Tropical Tropospheric OzoneLightning NOx Dominant Source for Tropical Tropospheric OzoneSensitivity to decreasing NOx emissions by 1% for each source
ΔDU
DJF
MAM
JJA
SON
Lightning Ozone Production Efficiency = 3 times OPE of each surface source
Sauvage et al., JGR, in press
6 Tg N/yr 6 Tg N/yr 6 Tg N/yr
Atmospheric Oxidation Largely Controlled by Lightning NOx Source
Simulated Annual Mean CharacteristicsSimulated Annual Mean Characteristics
O3 ppb NOx ppb
3/O3 production during transport and subsidence over South Atlantic basin
1/Surface emissions of O3 precursors
S. Am. Africa
2/Injection of NOx (mostly from lightning) into the upper troposphere
Sauvage et al., JGR, in press
ConclusionsConclusions
Growing confidence in top-down constraints on NOx emissions
South Atlantic Maximum largely results from lightning NOx due to high ozone production efficiency
Global lightning NOx source likely between 4 – 8 Tg N / yr
6 Tg N / yr is a best estimate
Further refinement of lightning source will require
- stronger constraints on midlatitude source
- improved satellite retrieval accuracy (e.g. NO2)
- more observations (e.g. HNO3)
- model development to better represent processes (e.g. lightning NOx representation, vertical transport)
AcknowledgementsAcknowledgementsSupported by NASA, CFCAS, and NSERC