randall martin
DESCRIPTION
Using Satellite Data to Infer Surface Emissions and Boundary Layer Concentrations of NO x (and SO 2 ). Randall Martin. With contributions from: Xiong Liu, Chris Sioris, Kelly Chance (Harvard-Smithsonian Center for Astrophysics) Rob Pinder, Robin Dennis (EPA/NOAA). - PowerPoint PPT PresentationTRANSCRIPT
Using Satellite Data to Infer Surface Emissions and Boundary Layer Concentrations of NOx (and SO2)
Randall Martin
With contributions from:With contributions from:Xiong Liu, Chris Sioris, Kelly Chance (Harvard-Smithsonian Center for Astrophysics)Xiong Liu, Chris Sioris, Kelly Chance (Harvard-Smithsonian Center for Astrophysics)
Rob Pinder, Robin Dennis (EPA/NOAA)Rob Pinder, Robin Dennis (EPA/NOAA)
Satellite Instruments With the Capability of Remote Satellite Instruments With the Capability of Remote Sensing of Tropospheric NOSensing of Tropospheric NO22 and SO and SO2 2 ColumnsColumns
•Nadir-viewing solar backscatter instruments including visible (NO2) and ultraviolet (SO2) wavelengths
GOME/ERS-2 1995-2002•Spatial resolution 320x40 km2
•Global coverage in 3 days
•SCIAMACHY/Envisat 2002-presentSpatial resolution 60x30 km2
Global coverage in 6 days
•OMI/Aura 2004-presentSpatial resolution 24x13 km2
Daily global coverage
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., 2002, 2006
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
Retrieval Uncertainty
Spectral fit 5-10x1014 molec cm-2
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
Palmer et al., 2001; Martin et al., 2002, 2003
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., 2006
Mean Uncertainty ±(5x1014 + 30%)
Tropospheric NOTropospheric NO22 Columns More Sensitive to Lower Columns More Sensitive to Lower
Tropospheric NOxTropospheric NOx
NO NO2
NOx lifetime < day
Nitrogen Oxides (NOx)
BoundaryLayer
NO/NO2
with altitude
hv
NO NO2
O3, RO2
hv
HNO3
NOx lifetime ~ week
Ozone (O3)
Upper Troposphere
Ozone (O3)
HNO3
O3, RO2
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
Martin et al., 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., 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
19982004-2005
Significant Agreement Between A Priori and A PosterioriSignificant Agreement Between A Priori and A PosterioriLargest Discrepancy in East AsiaLargest Discrepancy in East Asia
r=0.91
Martin et al., 2006
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 A Posteriori NOx Emissions from East Asia Exceed Those from Either North America or EuropeThose from Either North America or Europe
A posteriori (46 Tg N/yr)
A priori (38 Tg N/yr)
CMAQ SCIAMACHY
On-going efforts:• Model Evaluation (2004)• Test and Improve NOx Emission Inventories
molec/cm2
Evaluation of Modeled Spatial DistributionsEvaluation of Modeled Spatial DistributionsNONO22 Columns: Summer 2004 Columns: Summer 2004
Rob Pinder, Robin Dennis
Similar discrepancies at surface
Comparable spatial distributionsSCIAMACHY higher in rural areas higher regional background missing source (lightning) or NOxNOy too rapid
CMAQ higher downwind of urban areas (e.g., Atlanta, St. Louis), Point sourcesair mass factor from GEOS-CHEM NOx lifetime difference due to resolution
Evaluation of NOEvaluation of NO22 Spatial Distributions (contd.) Spatial Distributions (contd.)
Rob Pinder, Robin Dennis
CMAQ EvaluationCMAQ -SCIAMACHY
Can Satellite Measurements of Tropospheric NOCan Satellite Measurements of Tropospheric NO22
Columns Provide a Proxy for Surface NOColumns Provide a Proxy for Surface NO22 In Regions In Regions
Without In Situ Measurements?Without In Situ Measurements?
Highest NO2 maximum quarterly mean by county, 2001
Relationship Between Surface NORelationship Between Surface NO22 and GOME NO and GOME NO22
Columns Northern ItalyColumns Northern Italy
Ordonez et al., JGR, 2006
Fall/Winter Spring/Summer
In Situ Measurements Corrected for NOy Contamination
Relationship Between Simulated (GEOS-Chem) Relationship Between Simulated (GEOS-Chem) and Measured NOand Measured NO22 Profiles over Land Profiles over Land
Martin et al., 2004
Texas AQSTexas AQS
ICARTTICARTT
Martin et al., 2006
In Situ
GEOS-Chem (standard) (lightning x 4)
In Situ
GEOS-Chem
CMAQ SCIAMACHY
molec/cm2
Infer Surface NOInfer Surface NO22 from Tropospheric NOfrom Tropospheric NO22 Column Using Column Using
Model Vertical ProfileModel Vertical Profile
(Courtesy: R. Martin)
Rob Pinder, Robin Dennis
ppm
Satellite Retrieval of SOSatellite Retrieval of SO22
• Challenging! (Ozone Interference, Rayleigh Scattering <330 nm)
• TOMS: detect volcanic eruptions (detection limit: 4-6 DU) [Krueger, 1983; Krueger et al., 1995]
• GOME: detect both volcanic & anthropogenic SO2 [Eisinger & Burrows, 1998; Khokhar et al., 2005] using the DOAS technique (detection limit: 0.5-1 DU)
Global Distribution of SOGlobal Distribution of SO2 2 Columns Retrieved from GOMEColumns Retrieved from GOME
Missing Source from Nyamuragira Volcano in October 1998Missing Source from Nyamuragira Volcano in October 1998Retrieval Issues in July?Retrieval Issues in July?
GOMEGEOS-Chem
Xiong Liu
Do
bso
n U
nits
Oct98 Oct98
Jul97 Jul97
ConclusionsConclusions
• Top-down information from satellites can be applied to improve NOx emission inventories
• OMI will provide this capability at higher resolution
• Additional model development necessary for application at local scale
• Encouraging prospect of inferring surface NO2 from satellite/model