Satellite Remote Sensing of a Multipollutant Air Quality Health Index Randall Martin, Dalhousie and...
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![Page 1: Satellite Remote Sensing of a Multipollutant Air Quality Health Index Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Lok Lamsal,](https://reader035.fdocuments.us/reader035/viewer/2022062714/56649d375503460f94a0fbc0/html5/thumbnails/1.jpg)
Satellite Remote Sensing of a Multipollutant Air Quality Health Index
Randall Martin, Dalhousie and Harvard-Smithsonian
Aaron van Donkelaar, Lok Lamsal, Dalhousie University
Xiong Liu, NASA Goddard
![Page 2: Satellite Remote Sensing of a Multipollutant Air Quality Health Index Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Lok Lamsal,](https://reader035.fdocuments.us/reader035/viewer/2022062714/56649d375503460f94a0fbc0/html5/thumbnails/2.jpg)
Multipollutant Air Quality Health Index (AQHI)
Use Canadian AQHI (Stieb et al., JAWMA, 2008)3
2 2.5 3AQHI 0.09 NO (ppbv) 0.05 PM (ug/m ) 0.05 O (ppbv)
AQHI Excess Mortality Risk (%)
Satellite Observations Provide Context to Satellite Observations Provide Context to Ground-Based MeasurementsGround-Based Measurements
Insufficient In Situ Measurements for Exposure AssessmentInsufficient In Situ Measurements for Exposure Assessment
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Challenging to Infer Boundary Layer Ozone Concentration Challenging to Infer Boundary Layer Ozone Concentration
S(z) = shape factor C(z) = concentration Ω = columnNO2
Aerosol Extinction
O3
Martin, AE, 2008
0.30 0.36 0.43 0.52 0.62 2.2 4.7
O3 Aerosol O3 NO2
0.75 9.6
Normalized GEOS-Chem Normalized GEOS-Chem Summer Mean Profiles Summer Mean Profiles over North Americaover North America
Strong Rayleigh Scattering
( )( )
C zS z
Weak Thermal Contrast
Vertical Profile Affects Boundary-Layer Information in Satellite ObsVertical Profile Affects Boundary-Layer Information in Satellite Obs
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General Approach to Estimate Surface ConcentrationGeneral Approach to Estimate Surface Concentration
Daily Observed Column
S → Surface Concentration
Ω → Tropospheric column
In Situ
GEOS-Chem
Coincident GEOS-Chem Profile
OM
MO S
S
Actual approach (not shown) exploits sub-grid satellite information to improve profile estimate
MODIS/MISR AOD OMI NO2 (DOMINO) OMI O3 (Xiong Liu)
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Significant Spatial Correlation from NOSignificant Spatial Correlation from NO22 and PM and PM2.52.5
(OMI-derived NO (OMI-derived NO22, MODIS/MISR-derived PM, MODIS/MISR-derived PM2.52.5))
Mean over Jun – Aug 2005
Partial AQHI (NO2 and PM2.5)
y=1.4x-0.57 r=0.87
In Situ Partial AQHI
Sat
ellit
e-de
rived
Par
tial A
QH
I
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Evaluation of Surface OEvaluation of Surface O33 Estimate with AQ Network Estimate with AQ Network
O3 Mixing Ratio (ppbv)
OMI-Derived Surface O3 for North America (Jun – Aug 2005)
GEOS-Chem simulates strong correlation (r=0.9) between tropospheric O3 Column and surface O3 concentration during summer
r=0.77 y=0.89 + 20.0
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Significant Spatial Correlation in Satellite-derived and In Situ AQHISignificant Spatial Correlation in Satellite-derived and In Situ AQHI (OMI-derived NO (OMI-derived NO22 and O and O33, MODIS/MISR-derived PM, MODIS/MISR-derived PM2.52.5))
Mean values over June – August 2005 for North America
AQHI
1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 In Situ AQHI
Sat
ellit
e-de
rived
AQ
HI
r=0.85 y=1.1x+0.47
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Significant Correlation of Satellite-derived and In Situ AQHISignificant Correlation of Satellite-derived and In Situ AQHI
Jun – Aug 2005
Correlation Coefficient
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Aerosol Size-Dependent Below-Cloud ScavengingAerosol Size-Dependent Below-Cloud Scavenging
Betty Croft, Randall Martin, Dalhousie University
Ulrike Lohmann, Sylvaine Ferrachat, ETH
Philip Stier, Oxford University
Sabine Wurzler, LANUV, Germany
Hans Feichter, Max Plank
Rebecca Posselt, Meteoswiss
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Below-Cloud Aerosol Scavenging by Precipitation Varies with Size
Croft et al., ACPD, 2009
Aerosol Collection Efficiency
Implemented into ECHAM5-HAM GCM
Reduces global mean AOD by 15%
Changes dust & sea-salt mass burdens by 10-30% vs fixed model approach
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Modeling Challenges: Continue to develop simulation of vertical profile Comprehensive assimilation capability
Encouraging Prospects for Satellite Remote Encouraging Prospects for Satellite Remote Sensing of Air QualitySensing of Air Quality
Implications of Size-Resolved Aerosol-Scavenging for GEOS-Chem