inferring so 2 and no x emissions from satellite remote sensing
DESCRIPTION
Inferring SO 2 and NO x Emissions from Satellite Remote Sensing. Randall Martin with contributions from Akhila Padmanabhan , Gray O’Byrne, Sajeev Philip Dalhousie U. Chulkyu Lee, Dalhouse U NIMR, Korea. Environment Canada Seminar 17 Jan 2011. - PowerPoint PPT PresentationTRANSCRIPT
Inferring SO2 and NOx Emissions from Satellite Remote Sensing
Randall Martin
with contributions from
Akhila Padmanabhan, Gray O’Byrne, Sajeev Philip
Dalhousie U
Environment Canada Seminar
17 Jan 2011
Chulkyu Lee, Dalhouse U NIMR, Korea
Information about Anthropogenic SO2 Sources?Need Accurate SO2 Retrieval Algorithm
Lee et al., JGR, 2009
Local Air Mass Factor (AMF) Calculation
dt()
IoIB
EARTH SURFACE
Radiative Transfer Model
Scattering weight t
B
e
I1wln)(
AMF)(
G
Atmospheric Chemistry Model
“a-priori” Shape factor
2
2
OO
( ) ( ) airS
S
S C
1
TdSw )()(AMF
verticalslantAMF G
Calculate w() as function of:• solar and viewing zenith angle• surface albedo, pressure• cloud pressure, aerosol• OMI O3 column
INDIVIDUALOMI SCENES
SO2 mixing ratio CSO2()
() is temperature dependent cross-section
sigm
a (
)
Local Air Mass Factor Improves Agreement with Aircraft Observations (INTEX-A and B)
Lee et al., JGR, 2009
Uniform AMF: slope = 1.6, r = 0.71 Local AMF: slope = 0.95, r = 0.92
Uniform AMF: slope = 1.3, r = 0.78 Local AMF: slope = 1.1, r = 0.89
SCIAMACHYOMI
Extend Air Mass Factor Calculation to Longer Time Period
SCIAMACHY OMILaunch 2002 2004
Resolution (km) 30x60 >13x24
Repeat (days) 6 1-2
Equator Crossing Time 10:00 1:45
Provide daily local SO2 AMFs and scattering weights so any model can be used in the analysis
NO2 & SO2 Retrievals Affected by Errors in Surface Reflectance and Clouds
Winter OMI NO2 over Calgary & Edmonton
6OMI Reported Cloud Fraction
≥ 5cm of snow
0 > snow < 5cm
no snow
Mea
n Tr
op. N
O2 (
mol
ec/c
m2 )
O’Byrne et al., JGR, 2010
Expected Retrieval Bias OMI NO2 for Snow-Covered ScenesDue to Errors in Accounting for Transient Snow & Ice
7
2original correctedRelative NO Bias
corrected
With CloudFractionThreshold (f < 0.3)
-0.5 0 1.0
O’Byrne et al., JGR, 2010
Trend in Summer Tropospheric NO2 Column over 2003-2009 from SCIAMACHY
Akhila Padmanabhan & Chris Sioris
Bottom-Up Emission Inventories Take Years to Compile
Evaluate Hindcast Inventory Versus Bottom-upHindcast for 2003 Based on Bottom-up for 2006 and Monthly
NO2 for 2003-2006
Lamsal et al., GRL, 2011
HindcastBottom-up
Application of Satellite Observations for Timely Updates to NOx Emission Inventories
Use Model to Calculate Local Sensitivity of Changes in Trace Gas Column to Changes in Emissions
Forecast Inventory for 2009 Based on Bottom-up for 2006 and Monthly SCIAMACHY NO2 for 2006-2009
Temporary Dataset Until Bottom-Up Inventory Available
Lamsal et al., GRL, 2011
9% increase in global emissions
19% increase in Asian emissions
6% decrease in North American emissions
Top-Down (Mass Balance) Constraints on Emissions
SCIAMACHY Tropospheric NO2 (1015 molec cm-2) NOx emissions (1011 atoms N cm-2 s-1)
Lee et al., 2011
2004-2005
Inverse Modeling
SOx emissions (1011 atoms N cm-2 s-1)SCIAMACHY SO2 (1016 molec cm-2)
200652.4 Tg S yr-1
Martin et al., 2006
Accuracy of Mass Balance Approach for SO2 and NOx Emissions?
Mass Balance Approach•exploits short lifetimes
•Easily implemented for many forward models
•Infer emissions E from local trace gas column Ω
modeltop-down sat
model
EE
Box A Box B
Accuracy of Mass Balance Approach for SO2 and NOx Emissions?
Test with Adjoint Approach
Mass Balance Approach•exploits short lifetimes
•Easily implemented for many forward models
•Infer emissions E from trace gas column Ω
Adjoint Approach•Explicitly accounts for spatial smearing
•Minimize Cost Function J~[model(E)-obs(Ω)]2
•Use adjoint model to calculate sensitivities λto produce improve estimate of E
modeltop-down sat
model
EE
EJ