advances in applying satellite remote sensing to the aqhi
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Advances in Applying Satellite Remote Sensing to the AQHI. Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Akhila Padmanabhan, Dalhousie University Lok Lamsal, Dalhousie U NASA Goddard. 45 th CMOS Congress, Victoria 7 June 2011. - PowerPoint PPT PresentationTRANSCRIPT
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Advances in Applying Satellite Remote Sensing to Advances in Applying Satellite Remote Sensing to the AQHIthe AQHI
Randall Martin, Dalhousie and Harvard-Smithsonian
Aaron van Donkelaar, Akhila Padmanabhan, Dalhousie University
Lok Lamsal, Dalhousie U NASA Goddard
45th CMOS Congress, Victoria
7 June 2011
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Large Regions Have Insufficient Measurements for AQHI Large Regions Have Insufficient Measurements for AQHI MeasurementMeasurement
Locations of NAPS Sites
Southern Ontario
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Major Nadir-viewing Space-based Measurements Major Nadir-viewing Space-based Measurements of AQHI Speciesof AQHI Species
Sensor GOES Imager
MISR MODIS SCIA-MACHY
TES OMI PARASOL CALIOP GOME-2
IASI
Platform (launch)
GOES (varied)
Terra Aqua
(1999) (2002)
Envisat (2002)
Aura
(2004)
PARASOL (2004)
CALIPSO MetOp
(2006)
Equator Crossing
n/a 10:30 1:30 10:00 1:45 1:30 1:30 9:30
Typical Res (km)
4x4 18x18 10x10 60x30 8x5 >24x13 18x16 40x40 80x40 12x12
Global Obs
(w/o clouds)
n/a 7 2 6 n/a 1 1 n/a 1 0.5
Aerosol X X X X X X 1 X
NO2 X X X
Ozone X X X X X
Solar Backscatter, Thermal Infrared, Active
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General Approach to Estimate Surface ConcentrationsGeneral Approach to Estimate Surface Concentrations
NO2 Column
S → Surface Concentration
Ω → Tropospheric column
In Situ
GEOS-Chem
Model Profile
OM
MO S
S
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Ground-Level Afternoon NOGround-Level Afternoon NO2 2 Inferred From OMI for 2005-2007 Inferred From OMI for 2005-2007
Lok LamsalNO2 [ppbv]
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Ground-Level NOGround-Level NO2 2 Inferred From OMI for 2005 Inferred From OMI for 2005
Temporal Correlation with In Situ Over 2005
×In situ—— OMI
Works in Near-Real-Time!
Values Estimated Using Monthly NO2 Profiles for Different Year (2006)
Insignificant change in results if profiles are daily coincident values from 2005
Lok Lamsal
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Aerosol Most Visible over Dark TargetsAerosol Most Visible over Dark Targets
Pollution haze over East Coast Dust off West Africa
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Aerosol Optical Depth (AOD) from MODIS and MISR over 2001-2006Aerosol Optical Depth (AOD) from MODIS and MISR over 2001-2006
MODIS1-2 days for global coverage (w/o
clouds)
AOD retrievals at 10 km x 10 km
Requires assumptions about surface reflectivity
MISR6-9 days for global coverage (w/o
clouds)
AOD retrievals at 18 km x 18 km
Simultaneous retrieval of surface reflectance and aerosol optical properties
0 0.1 0.2 0.3AOD [unitless]
MODISr = 0.40
vs. in-situ PM2.5
MISRr = 0.54
vs. in-situ PM2.5
van Donkelaar et al., EHP, 2010
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Agreement With AERONET Varies with Surface Type
9 surface types, defined by monthly mean surface albedo ratios,evaluation against AERONET AOD
MODIS
MISR
Jul
y
van Donkelaar et al., EHP, 2010
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Combined AOD from MODIS and MISRCombined AOD from MODIS and MISRRejected Retrievals for Land Types with Monthly Error vs AERONET >0.1 or 20%Rejected Retrievals for Land Types with Monthly Error vs AERONET >0.1 or 20%
MODISr = 0.40
(vs. in-situ PM2.5)
MISRr = 0.54
(vs. in-situ PM2.5)
CombinedMODIS/MISR
r = 0.63 (vs. in-situ PM2.5)
0.3
0.25
0.2
0.15
0.1
0.05
0
AO
D [u
nitle
ss]
van Donkelaar et al., EHP, 2010
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Significant Agreement with Coincident In situ MeasurementsSignificant Agreement with Coincident In situ MeasurementsUsed GEOS-Chem to CalculateUsed GEOS-Chem to Calculate AOD/PMAOD/PM2.52.5 ( (η)η)
SatelliteDerived
In-situ
Sat
ellit
e-D
eriv
ed
[μg/
m3]
In-situ PM2.5 [μg/m3]
Ann
ual M
ean
PM
2.5 [
μg/
m3]
(200
1-20
06)
r
MODIS AOD 0.40
MISR AOD 0.54
Combined AOD 0.63
Combined PM2.5 0.77
van Donkelaar et al., EHP, 2010
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Error Sources in Satellite-Derived PMError Sources in Satellite-Derived PM2.52.5
Satellite• Error limited to 0.1 + 20% by
AERONET filter
• Implication for satellite PM2.5
determined by AOD/PM2.5
Model• Affected by aerosol optical
properties, concentrations, vertical profile, relative humidity
• Most sensitive to vertical profile [van Donkelaar et al., 2006]
• Evaluate vs Calipso lidar obs
• Estimate error from bias in profile and AOD ±(1 μg/m3 + 15%)
• Contains 68% (1 SD) of North American data
Sat
ellit
e-D
eriv
ed
[μg/
m3]
In-situ PM2.5 [μg/m3]
van Donkelaar et al., EHP, 2010
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USA Today: Hundreds Dead from Heat, Smog, USA Today: Hundreds Dead from Heat, Smog, Wildfires in MoscowWildfires in Moscow
9 Aug 2010: “Deaths in Moscow have doubled to an average of 700 people a day as the Russian capital is engulfed by poisonous smog from wildfires and a sweltering heat wave, a top health official said Monday.”
MODIS/Aqua: 7 Aug 2010
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Spatial and Temporal Variation in Satellite-Based PMSpatial and Temporal Variation in Satellite-Based PM2.52.5
during Moscow 2010 Firesduring Moscow 2010 Fires
van Donkelaar et al., AE, submitted
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Satellite-Based PMSatellite-Based PM2.5 2.5 Insensitive to Emission InventoryInsensitive to Emission Inventory
Daily Meteorology More ImportantDaily Meteorology More Important
van Donkelaar et al., AE, submitted
GEOS-Chem Calculation of AOD / PM2.5
Different Emission Inventories
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Application of Satellite-based Estimates to Moscow Application of Satellite-based Estimates to Moscow Smoke EventSmoke Event
Before Fires During Fires
van Donkelaar et al., submitted
MODIS-based
In Situ PM2.5
In Situ from PM10
r2 =0.85, slope=1.06
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Acknowledgements:Acknowledgements: Environment Canada, Health Canada, NASA Environment Canada, Health Canada, NASA
• Simple Method for Near-Real-Time Estimates of Ground-Level NO2
• Satellite-based PM2.5 Estimate for Long-Term and Extreme Events
Ongoing Work
• Develop daily PM2.5 estimate for Canada
• Improve spatial resolution from 10 km to 3 km
• Evaluate AOD/PM2.5 ratio
Growing Confidence in Application of Satellite Growing Confidence in Application of Satellite Remote Sensing for PMRemote Sensing for PM2.52.5 and NO and NO22