1. 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

2. Multipollutant Air Quality Health Index (AQHI)
Satellite Observations Provide Context to Ground-Based Measurements
Insufficient In Situ Measurements for Exposure Assessment
Multipollutant Air Quality Health Index (AQHI)
Use Canadian AQHI (Stieb et al., JAWMA, 2008)
AQHI
Excess Mortality Risk (%)

3. Challenging to Infer Boundary Layer Ozone Concentration
Strong Rayleigh Scattering
Weak Thermal Contrast
O Aerosol
NO2 O3
0.30
0.36
0.43
0.52
0.62
0.75
2.2
4.7
9.6
Vertical Profile Affects Boundary-Layer Information in Satellite Obs
Normalized GEOS-Chem Summer Mean Profiles over North America O3
Aerosol Extinction
S(z) = shape factor C(z) = concentration Ω = column
NO2
Martin, AE, 2008

4. General Approach to Estimate Surface Concentration
Coincident GEOS-Chem Profile
Daily Observed Column
In Situ
GEOS-Chem
MODIS/MISR AOD OMI NO2 (DOMINO) OMI O3 (Xiong Liu)
Actual approach (not shown) exploits sub-grid satellite information to improve profile estimate
S → Surface Concentration
Ω → Tropospheric column

5. Satellite-derived Partial AQHI
Significant Spatial Correlation from NO2 and PM2.5 (OMI-derived NO2, MODIS/MISR-derived PM2.5)
Mean over Jun – Aug 2005
y=1.4x-0.57 r=0.87
Satellite-derived Partial AQHI
In Situ Partial AQHI
Partial AQHI (NO2 and PM2.5)

6. Evaluation of Surface O3 Estimate with AQ Network
GEOS-Chem simulates strong correlation (r=0.9) between tropospheric O3 Column and surface O3 concentration during summer
OMI-Derived Surface O3 for North America (Jun – Aug 2005)
Mar 30
r= y=
O3 Mixing Ratio (ppbv)

7. Satellite-derived AQHI
Significant Spatial Correlation in Satellite-derived and In Situ AQHI (OMI-derived NO2 and O3, MODIS/MISR-derived PM2.5)
Mean values over June – August 2005 for North America
Satellite-derived AQHI
r=0.85 y=1.1x+0.47
March 29 calc
In Situ AQHI
AQHI

8. Significant Correlation of Satellite-derived and In Situ AQHI
Jun – Aug 2005
April 2
Correlation Coefficient

9. Aerosol 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

10. Below-Cloud Aerosol Scavenging by Precipitation Varies with Size
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
Croft et al., ACPD, 2009

11. Encouraging Prospects for Satellite Remote Sensing of Air Quality
Modeling Challenges:
Continue to develop simulation of vertical profile
Comprehensive assimilation capability
Implications of Size-Resolved Aerosol-Scavenging for GEOS-Chem