Applications of Satellite Remote Sensing to Inform Air Quality Management

Randall Martin

with contributions from

Aaron van Donkelaar, Brian Boys, Matthew Cooper, Shailesh Kharol, Colin Lee, Sajeev Philip

Fall AGUSan Francisco

3 Dec 2012

Daven Henze (UC Boulder), Yuxuan Wang (Tsinghua), Qiang Zhang (Tsinghua), Dan Crouse (Health Canada), Rick Burnett (Health Canada), Mike Brauer (UBC),

Jeff Brook (Environment Canada), Aaron Cohen (HEI)

Vast Regions Have Insufficient Measurements for Exposure Assessment to Fine Particulate Matter (PM2.5)

Locations of Publicly-Available Long-Term PM2.5 Monitoring Sites

Previous WHO Global Burden of Disease Project for the Year 2000Impaired by Insufficient Global Observations of PM2.5

Cohen et al., 2005

General Approach to Estimate Surface Concentration

Daily Satellite(MODIS, MISR, SeaWifs, OMI)

Column of AOD or NO2

S → Surface Concentration

Ω → Tropospheric column

Coincident Model

(GEOS-Chem) Profile

OM

MO S

S

Alti

tude

Concentration

Climatology (2001-2006) of MODIS- and MISR-Derived PM2.5

van Donkelaar et al., EHP, 2010EHP Paper of the Year

Evaluation in North America:r=0.77slope = 1.07N=1057

Included in current Global Burden of Disease report

Outside Canada/USN = 244 (84 non-EU)r = 0.83 (0.83)Slope = 0.86 (0.91)Bias = 1.15 (-2.64) μg/m3

Significant Association of Long-term PM2.5 Exposure and Cardiovascular Mortality at Low PM2.5

Crouse et al., EHP, 2012

ΔP

M2

.5 [

µg

m-3 y

r-1]

2

-2

Coherent PM2.5 Trends Inferred from MISR and SeaWiFS AOD Uses Coincident AOD/PM2.5 from GEOS-Chem

Boys et al., in prep.

0

-1

1

Tuesday, 5:24

3012 Moscone West

MISR2000 - 2011

SeaWiFS1998 - 2010

SPARTAN: An Emerging Global Network to Evaluate and Enhance Satellite-Based Estimates of PM2.5

Measures PM2.5 Mass & Composition at AERONET sites

PM2.5 Sampling Station fromVanderlei Martins (Airphoton)

Filter PM2.5 & PM10

3-λ Nephelometer

AOD from CIMEL Sunphotometer (AERONET)

www.spartan-network.org

PM2.5 Nearly as Sensitive to Emissions of NOx as to SO2

Kharol et al., GRL, in prep

GEOS-Chem Calculation of Annual PM2.5 Response to 10% Change in Emissions

Supported by Comparison of GEOS-Chem vs IASI NH3

ΔNOx Emissions ΔSO2 Emissions ΔNH3 Emissions

25%41%34%

Using NH3 emissions from Streets et al. (2003) reduced by 30% following Huang et al. (2012)

DJF

JJA

IASI GC (w/AK) IASI - GC

ΔP

M2.

5 (u

g m

-3)

-0.5

0

1

2

Change in PM2.5 Exposure from Local Changes in EmissionsUse GEOS-Chem Adjoint & Satellite PM2.5 Distribution

Lee et al., EHP, in prep

Change in Global Premature Mortality for 10% change in Emissions

Uses relation of exposure and mortality from Global Burden of Disease Project

Δ Anthropogenic NOx EmissionsΔ Anthropogenic SO2 Emissions

2

a2

aa2 2a ε

dρρ AOD

dAODAOD AODJ(AOD)

σ σ

Observed TOAreflectance

a priori AODa posteriori

AOD

a priori errorobservational

error

Optimal Estimation allows:• Error-constrained AOD solution• Consistent optical properties• Local reflectance information

Chemical Transport Model

CALIOPSpace-borne LIDAR

• Optimal Estimation AOD• CALIOP-adjusted AOD/PM2.5

MODISImaging Spectroradiometer

Optimal Estimation constrains AOD retrieval by error:

Enhanced Algorithm to Infer PM2.5 from MODIS

van Donkelaar et al., in prep

Optimal Estimation Improves Global AOD Retrieval Used to Infer Global PM2.5

van Donkelaar et al., in prep

Western North America

Eastern North America

EuropeOp

tim

al E

stim

atio

n A

OD

(U

nit

less

) slope=1.47r=0.65

slope=0.87r=0.80

slope=0.55r=0.53

slope=1.25r=0.85

slope=0.95r=0.86

slope=0.70r=0.72

n = 29,976

n = 15,554

n = 25,497

slope=1.36r=0.62

slope=1.11r=0.77

slope=1.23r=0.77

Use CALIOP Observations (2006-2011) to Correct Bias in Simulated Aerosol Extinction

van Donkelaar et al., in prep

η =

PM

2.5

/ AO

D

Southeast US China

Optimal Estimation Retrieval Improves Accuracy and CoverageMODIS-Derived PM2.5 for 2005

van Donkelaar et al., in prep

A Satellite-Based Multipollutant Index from PM2.5 & NO2

OMI-derived NO2 Indicator of Combustion Sources

𝑀𝑃𝐼=𝑃𝑀 2.5

𝐴𝑄𝐺𝑃𝑀 2.5[1+

𝑁𝑂2

𝐴𝑄𝐺𝑁𝑂 2]

Cooper et al., ES&T, 2012

PM2.5

NO2

MPI0 4 8 12

Multipollutant Index

Satellite-Based Multipollutant Index (Unitless)

ShanghaiBeijing

DelhiKarachi

SeoulCairoLima

TehranLos Angeles

BerlinMoscowNairobi 0 1 2 5 7 9 11 13 15

AQG = WHO Air Quality Guideline

PM2.5 [μg/m

3]M

PI [unitless]

East

ern

Chin

a

150

75

015

7.5

0

PM2.5 [μg/m

3]M

PI [unitless]

Mos

cow

25

15

5

2.5

1.5

0.5

Numerous Opportunities to Inform Air Quality Management through Satellite Remote Sensing and Modeling

Acknowledgements: NSERC, Environment Canada, Health Canada, NASA

• Particulate matter is major risk factor for global mortality

• Evidence of no lower limit on the health effects of PM2.5

• Controls on Chinese NOx emissions reduce PM2.5

• SPARTAN and CALIOP evaluate AOD/PM2.5 simulation

• Asian PM2.5 increasing by 1-2 ug/m3/yr

• Optimal estimation improves retrieval of PM2.5

• Satellite-based indicator of air pollution from PM2.5 and NO2

Optimal Estimation Improves Global AOD Retrieval Used to Infer Global PM2.5

van Donkelaar et al., in prep

East Asia

South Asia

South America

Op

tim

al E

stim

atio

n A

OD

(U

nit

less

)