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

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

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

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)

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

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

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

Significant Correlation of Satellite-derived and In Situ AQHISignificant Correlation of Satellite-derived and In Situ AQHI

Jun – Aug 2005

Correlation Coefficient

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

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

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