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![Page 1: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/1.jpg)
Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter
Concentrations
Randall Martin, Dalhousie and Harvard-Smithsonian
with contributions from
Aaron van Donkelaar, Dalhousie University
Rob Levy, Ralph Kahn NASA
Michael Brauer, UBC
Michal Krzyzanowski, WHO
Aaron Cohen, HEI
21st Annual International Society of Exposure Science Conference
24 October 2011
![Page 2: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/2.jpg)
Large Regions Have Insufficient Measurements for Air Large Regions Have Insufficient Measurements for Air Pollution Exposure AssessmentPollution Exposure Assessment
Locations of Publicly-Available Long-Term PM2.5 Monitoring Sites (2001-2006)
Monitor locations can be driven by compliance objectives
~1 site / 10,000 km2 in continental US & southern Canada
![Page 3: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/3.jpg)
Aerosol Remote Sensing: Analogy with Visibility Aerosol Remote Sensing: Analogy with Visibility Effects of Aerosol LoadingEffects of Aerosol Loading
PM2.5 = 7.6 ug m-3
Pollution haze over East Coast
Waterton Lakes/Glacier National Park
PM2.5 = 22 ug m-3
![Page 4: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/4.jpg)
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 = 0.39
(vs. in-situ PM2.5)
MISRr = 0.39
(vs. in-situ PM2.5)
CombinedMODIS/MISR
r = 0.61 (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
![Page 5: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/5.jpg)
Calculate Coincident PMCalculate Coincident PM2.52.5/AOD with Chemical /AOD with Chemical
Transport Model (GEOS-Chem)Transport Model (GEOS-Chem)
Aaron van Donkelaar
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Significant Agreement with Coincident In situ MeasurementsSignificant Agreement with Coincident In situ Measurements
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 τ 0.39
MISR τ 0.39
Combined τ 0.61
Combined PM2.5 0.77
van Donkelaar et al., EHP, 2010
![Page 7: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/7.jpg)
Evaluation with measurements outside Canada/US
Global Climatology (2001-2006) of PMGlobal Climatology (2001-2006) of PM2.52.5
Better than in situ vs model (GEOS-Chem): r=0.52-0.62, slope = 0.63 – 0.71
Number sites Correlation Slope Offset (ug/m3)
Including Europe 244 0.83 0.86 1.15
Excluding Europe 84 0.83 0.91 -2.5
van Donkelaar et al., EHP, 2010
![Page 8: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/8.jpg)
Error in Satellite-Derived PMError in Satellite-Derived PM2.52.5 has Three Primary Sources has Three Primary Sources
Satellite• Error limited to 0.1 + 20% by
AERONET filter
• Implication for satellite PM2.5
determined by η
Satellite-derived PM2.5 = AOD
Model• Affected by aerosol optical
properties, concentrations, vertical profile, relative humidity
• Most sensitive to vertical profile [van Donkelaar et al., 2006]
Sampling Biases
Satellite retrievals are at specific time of day for cloud-free conditions
2.5PM
AOD Model
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τa(z)/τa(z=0)
Alti
tud
e [k
m]
Evaluate GEOS-Chem Evaluate GEOS-Chem Vertical Profile with Vertical Profile with
CALIPSO ObservationsCALIPSO Observations
• Coincidently sample model and CALIPSO extinction profiles
– Jun-Dec 2006
• Compare % within boundary layer
Model (GC)CALIPSO (CAL)
Optical depth above altitude zTotal column optical depth
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Error EstimateError Estimate• Estimate error from bias in profile and
AOD ±(1 μg/m3 + 15%) • Contains 68% (1 SD) of North
American data
• Total uncertainty 25% (with sampling)• Global population-weighted mean
uncertainty 7 μg/m3
van Donkelaar et al., EHP, 2010
Sat
ellit
e-D
eriv
ed
[μg/
m3]
In-situ PM2.5 [μg/m3]
![Page 11: Applications of Satellite Remote Sensing to Estimate Global Ambient Fine Particulate Matter Concentrations Randall Martin, Dalhousie and Harvard-Smithsonian.](https://reader035.fdocuments.us/reader035/viewer/2022062517/56649f125503460f94c24cf0/html5/thumbnails/11.jpg)
van Donkelaar et al., EHP, 2010
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van Donkelaar et al., EHP, 2010
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Emerging ApplicationsEmerging Applications
• Estimate global outdoor air pollution exposure for global burden of disease (WHO) (Brauer et al., ES&T, submitted)
• Significant association of long-term PM2.5 exposure and cardiovascular mortality at low PM2.5 levels (Crouse et al., EHP, submitted)
• Satellite dataset dominant contributor to Canada-wide PM2.5 model (Hystad et al., EHP, 2011)
• Cigarette smoking is a negative confounder in epidemiological studies of long-term ambient air pollution and mortality outcomes in Canada (Villeneuve et al., OEM, 2011)
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Wildfires near Moscow in Summer 2010Wildfires near Moscow in Summer 2010
MODIS/Aqua: 7 Aug 2010
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Relaxed Cloud Screening Needed for this Extreme EventRelaxed Cloud Screening Needed for this Extreme Event
van Donkelaar et al., AE, 2011
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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, 2011
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Satellite-based Estimates of PMSatellite-based Estimates of PM2.52.5 in Moscow in Moscow
Before Fires During Fires
van Donkelaar et al., 2011
MODIS-based
In Situ PM2.5
In Situ from PM10
r2 =0.85, slope=1.06
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ChallengesChallengesRemote Sensing: Improved algorithms to increase accuracy and resolution
Modeling: Develop representation of vertical profile
Measurements: More needed for evaluation throughout the world
Encouraging Prospects for Satellite Remote Encouraging Prospects for Satellite Remote Sensing of Air PollutantsSensing of Air Pollutants
Acknowledgements:Acknowledgements: Health Canada Health Canada NSERC NSERC NASA NASA
Health Applications:Close interaction to develop appropriate applications