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Satellite Remote Sensing of the Air Quality Health Index Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Lok Lamsal, Dalhousie University Xiong Liu, NASA Goddard

Satellite Remote Sensing of the Air Quality Health Index

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Satellite Remote Sensing of the Air Quality Health Index. Randall Martin, Dalhousie and Harvard-Smithsonian Aaron van Donkelaar, Lok Lamsal, Dalhousie University Xiong Liu, NASA Goddard. Satellite Observations Complement Ground-Based Measurements. - PowerPoint PPT Presentation

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Page 1: Satellite Remote Sensing of the Air Quality Health Index

Satellite Remote Sensing of the 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 the Air Quality Health Index

Satellite Observations Complement Ground-Based Measurements

Large Regions Have Insufficient In Situ Measurements for Air Quality Assessment

~1 site / 10,000 km2 in continental US & southern Canada

In situ NO2 measurements contaminated with NOz

Page 3: Satellite Remote Sensing of the Air Quality Health Index

Major Nadir-viewing Space-based Measurements of AQHI Species

Sensor GOME MISR MODIS SCIA-MACHY

TES OMI PARA-SOL

GOME-2

IASI

Platform (launch) ERS-2 (1995)

Terra Aqua (1999) (2002)

Envisat (2002)

Aura (2004)

PARA-SOL

(2004)

MetOp(2006)

Equator Crossing 10:30 10:30 1:30 10:00 1:45 1:30 9:30

Typical Res (km) 320x40 18x18 10x10 60x30 8x5 >24x13 18x16 80x40 12x12

Global Obs (w/o clouds)

3 7 2 6 n/a 1 1 1 0.5

Aerosol X X X X X X X

NO2 X X X X

Ozone X X X X X X

Solar Backscatter & Thermal Infrared

Page 4: Satellite Remote Sensing of the Air Quality Health Index

Retrievals of Aerosol and NO2 Most Sensitive to Boundary Layer

0.30 0.36 0.43 0.52 0.62 2.2 4.7

O3 Aerosol

O3

NO2

0.75 9.6

Wavelength (μm)

Strong Rayleigh Scattering

Weak Thermal Contrast with

Surface

Page 5: Satellite Remote Sensing of the Air Quality Health Index

Relative Vertical Profile Affects Boundary-Layer Information in Satellite Observations

Normalized Simulated (GEOS-Chem) Summer Mean Profiles over North America

S(z) = shape factor C(z) = concentration Ω = column

( )( )

C zS z

NO2

Aerosol Extinction

O3

Martin, AE, 2008

Page 6: Satellite Remote Sensing of the Air Quality Health Index

OMI Tropospheric NO2 Column Proxy for Surface Concentration

NO/NO2

with altitude

October 2004 – September 2007 Inclusive

Page 7: Satellite Remote Sensing of the Air Quality Health Index

Promising Relationship Between Modeled and In-Situ NO2 Profiles

Martin et al., JGR, 2004

Texas AQS

ICARTT

Martin et al., JGR, 2006

In Situ

GEOS-Chem

In Situ

GEOS-Chem

Eastern North America

New England

Page 8: Satellite Remote Sensing of the Air Quality Health Index

General 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

MODIS/MISR AOD OMI NO2 (DOMINO) OMI O3 (Xiong Liu)

Page 9: Satellite Remote Sensing of the Air Quality Health Index

Significant Spatial Correlation from NO2 and PM2.5

(OMI-derived NO2, MODIS/MISR-derived PM2.5)

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

Page 10: Satellite Remote Sensing of the Air Quality Health Index

Evaluation of Surface O3 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

Page 11: Satellite Remote Sensing of the Air Quality Health Index

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

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

Page 12: Satellite Remote Sensing of the Air Quality Health Index

Temporal Variation in the AQHI

In Situ

Satellite

Page 13: Satellite Remote Sensing of the Air Quality Health Index

Significant Correlation of Satellite-derived and In Situ AQHI

Jun – Aug 2005

Correlation Coefficient

Page 14: Satellite Remote Sensing of the Air Quality Health Index

Challenges

Remote Sensing Community: Boundary-layer ozone Higher spatial resolution obs (urban scales, cloud-free, validation)

Modeling Community: Develop representation of vertical profile Comprehensive assimilation capability

Measurement Community: Develop robust validation networks

• vertical profile• span satellite footprint• full year • research quality (e.g. NO2)

Encouraging Prospects for Satellite Remote Sensing of Air Quality