insight into global air quality using satellite remote sensing and modeling randall martin with...

Insight into Global Air Quality using Satellite Remote Sensing and Modeling

Randall Martin

with contributions from

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

Lok Lamsal (Dalhousie NASA), Chulkyu Lee (Dalhousie KMA)

Siwen Wang (Tsinghua & Dalhousie), Qiang Zhang (Tsinghua)

10 Oct 2012

Two Major Applications of Satellite Observations of Atmospheric Composition

Top-down Constraints on Emissions

Estimating Pollution Concentrations

(large regions w/o ground-based obs)

(to improve air quality and climate

simulations)

Column Observations of Aerosol and NO2 Strongly Influenced by Boundary Layer Concentrations

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

Aerosol O3 NO2

0.75 9.6

Normalized Model Summer Mean Profiles over North America

Strong Rayleigh Scattering

( )( )

C zS z

Weak Thermal Contrast

Vertical Profile Affects Boundary-Layer Information in Satellite Obs

O3

Wavelength (μm)

WHO Global Burden of Disease Report for 2000Impaired by Insufficient Global Observations of

Fine Particulate Matter (PM2.5)

• Estimated air pollution in urban areas causes ~1 million excess deaths (~1%)

• Could not estimate effects outside of urban areas for 2000 report

• Could this be improved with satellite remote sensing?

Cohen et al., 2005

~ 1 year increase of life expectancy for decreasing long-term exposure of PM2.5 by 10 ug/m3

Aerosol Optical Depth (AOD) for 2001-2006Rejected Retrievals for Land Types with Monthly Error vs AERONET >0.1 or 20%

MODISr = 0.39

(vs. in-situ PM2.5)

MISRr = 0.39

(vs. in-situ PM2.5)

CombinedMODIS/MISR

r = 0.61 (vs. in-situ PM2.5)

0.3

0.25

0.2

0.15

0.1

0.05

0

AO

D [u

nitle

ss]

van Donkelaar et al., EHP, 2010

Chemical Transport Model (GEOS-Chem) Simulation of Aerosol Optical Depth

Use GEOS-Chem to Calculate AOD/PM2.5 Ratio for Each Obs

Aaron van Donkelaar

τa(z)/τa(z=0)

Alti

tud

e [k

m]

Evaluate GEOS-Chem Vertical Profile with

CALIOP Observations

• Coincidently sample model and CALIOP extinction profiles– Jun-Dec 2006

• Compare % within boundary layer

Model (GC)CALIOP (CAL)

Optical depth above altitude zTotal column optical depth

SatelliteDerived

In-situ

Sat

ellit

e-D

eriv

ed [

μg/

m3]

In-situ PM2.5 [μg/m3]

Ann

ual M

ean

PM

2.5 [

μg/

m3]

(200

1-20

06)

r

MODIS AOD 0.39

MISR AOD 0.39

Combined AOD 0.61

Combined PM2.5 0.77


Significant Agreement of Satellite-Derived PM2.5 with Coincident In situ Measurements

Evaluation with measurements outside Canada/US

Global Climatology (2001-2006) of PM2.5

Better than in situ vs model (GEOS-Chem): r=0.52-0.62, slope = 0.63 – 0.71

Number sites Correlation Slope Bias (ug/m3)

Including Europe 244 0.83 0.86 1.15

Excluding Europe 84 0.83 0.91 -2.5


• 80% of global population exceeds WHO guideline of 10 μg/m3

• 35% of East Asia exposed to >50 μg/m3 in annual mean

PM2.5 Exposure [μg/m3]

Long-term Exposure to Outdoor Ambient PM2.5


100

90

80

70

60

50

40

30

20

10

0

AQG IT-3 IT-2 IT-1

Pop

ulat

ion

[%]

5 10 15 25 35 50 100

WHO Guideline & Interim Targets

Forthcoming Global Burden of Disease (WHO) Study

PM2.5 Causal Role in ~70 Million Disability Adjusted Life Years (~3%)~3 Million Excess Deaths (~5%)

Wildfires near Moscow in Summer 2010

MODIS/Aqua: 7 Aug 2010

Spatial and Temporal Variation in Satellite-Based PM2.5 during Moscow 2010 Fires

van Donkelaar et al., AE, 2011

Satellite-based Estimates of PM2.5 in Moscow

Before Fires During Fires

van Donkelaar et al., AE, 2011

MODIS-based

In Situ PM2.5

In Situ from PM10

r =0.92, slope=1.06

Daily Satellite-based Estimates for North America>30M People Live in Regions w/o Local Air Quality Info

GOCI and GEMS Provide Opportunities for Asia

van Donkelaar et al., ES&T, in press

In Situ Satellite-derived

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

Measures PM2.5 Mass & Composition at AERONET sites

PM2.5 Sampling Station fromVanderlei Martins (UMBC)

AOD from CIMEL Sunphotometer (AERONET)

General Approach to Estimate Surface NO2 Concentration

NO2 Column

S → Surface Concentration

Ω → Tropospheric column

In Situ

GEOS-Chem

Model Profile

OM

MO S

S

NO2: Indicator of Population Exposure to Combustion SourcesOMI-Derived NO2

Lamsal et al., ES&T, in prep

• Mortality not well explained by PM2.5 and O3 alone

• Mortality can be more strongly associated with NO2 than either PM2.5 or O3 (e.g. Stieb et al. 2007)

• NO2 is an indicator of exposure to combustion sources that increase airmass toxicity (Brook et al., 2007)

Multiple Pollutants Affect Air Quality

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

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 GuidelinePM2.5 (ug/m3)

MPI (unitless)

Emission Inventories are Notoriously Difficult to Determineand Take Years to Compile

Top-Down Constraints on NOx & SOx Emissions

SCIAMACHY Tropospheric NO2 (1015 molec cm-2) NOx emissions (1011 atoms N cm-2 s-1)

Lee et al., 2011

2004-2005

Inverse Modeling

SOx emissions (1011 atoms N cm-2 s-1)OMI SO2 (1016 molec cm-2)

2006

Martin et al., 2006

49.9 Tg S yr-1

Global Anthropogenic Sulfur Emissions Over Land for 2006Volcanic SO2 Columns (>1x1017 molec cm-2) Excluded From Inversion

49.9 Tg S/yr

54.6 Tg S/yr

r = 0.77

SO2 Emissions (1011 molecules cm-2 s-1)Cloud Radiance Fraction < 0.2

Top-Down (OMI)

Bottom-Up in GEOS-Chem (EDGAR2000, NEI2005, EMEP2005, Streets2006) Scaled to 2006

Lee et al., JGR, 2011

Anthropogenic Emissions Differences (2006)

-2.2 Tg S/yr

-4.7 Tg S/yr

Cloud Radiance Fraction < 0.2, SZA < 50o Lee et al., JGR, 2011

OMI Observations of Changes in NOx Emissions from Chinese Power Plants

Ratio of OMI NO2 Columns for 2007 / 2005Open Circles Indicate New Power Plants

Wang et al., ACP, 2012

Lamsal et al., GRL, 2011

Application of Satellite Observations for Timely Updates to NOx Emission Inventories

Use GEOS-Chem to Calculate Local Sensitivity of Changes in Trace Gas Column to Changes in Emissions

Forecast Inventory for 2009 Based on Bottom-up for 2006 and Monthly OMI NO2 for 2006-2009

9% increase in global emissions

19% increase in Asian emissions

6% decrease in North American emissions

PM2.5 Nearly as Sensitive to NOx as to SO2 and NH3

Kharol et al., GRL, in prep

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

ΔNOx Emissions ΔSO2 Emissions ΔNH3 Emissions

Increasing NOx Emissions Increases NO3-, NH4

+, and SO42-

Increasing SO2 Emissions Decreases NO3-

Kharol et al., GRL, in prep

Preliminary GEOS-Chem Adjoint Calculation of the Change in Annual Mortality to Local Changes in Emissions

Effects of PM2.5 on Mortality from WHO Global Burden of Disease Project

Lee et al., EHP, in prep

ΔM = Change in Global Mortality

Emerging Applications of Satellite Remote Sensing of Atmospheric Composition

Acknowledgements: NSERC, Environment Canada, Health Canada, NASA

Chemical Transport Model Plays a Valuable Role in

Relating Retrieved and Desired Quantity

Challenges

• Continue to develop retrieval capability

• Evaluate and improve simulation to relate retrieved and desired quantity

(e.g. AOD/PM2.5, NO2 / NOx emissions)

• Estimates of Ground-level Air Pollutants

• Top-down Constraints on Emission Inventories

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