Global Fine Particulate Matter Concentrations and Trends Inferred from Satellite Observations, Modeling, and Ground-Based Measurements

Randall Martin

with contributions from

Aaron van Donkelaar, Brian Boys, Matthew Cooper, Colin Lee, Ryan MacDonell, Graydon Snider, Crystal Weagle, Mark Gibson

EGU 30 April 2014

Michael Brauer (UBC), Aaron Cohen (HEI), Daven Henze (CU Boulder), Christina Hsu (NASA), Yang Liu (Emory), Zifeng Lu (Argonne), Vanderlei Martins (AirPhoton),

David Streets (Argonne), Siwen Wang (Tsinghua), Qiang Zhang (Tsinghua)

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

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

Emerging Network

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

General Approach to Estimate Daily PM2.5 Concentration

Daily Satellite(MODIS, MISR, SeaWifs) Column of AOD Coincident Model

(GEOS-Chem) Profile

2.5,sat2.5,model

modelsat

PMA

PM OD

A DO

Alti

tude

Concentration

Accounts for • relation of “dry” PM2.5 with ambient extinction• relation of aerosol during satellite-observation vs continuous

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

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

Used in Global Burden of Disease Study 2010

Lim et al., Lancet, 2012

PM2.5 Causal Role in

70 Million Disability Adjusted Life Years (~3%)>3 Million Excess Deaths (~5%)

Similar Conclusions Reached by WHO in 2014

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

Three-fold increase in premature mortality rate over previous GBD study for 2000

Crouse et al., EHP, 2012

Benefits from Large Statistical Power

2

a2

aa2 2a ε

dρρ AODdAODAOD AOD

J(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

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., JGR, 2013

Optimal Estimation (OE) Can Improve Global AOD Retrieval

van Donkelaar et al., JGR, 2013

Opt

imal

Est

imat

ion

AO

D (U

nitle

ss)

2005 slope correlation

Region Operational

OE Simulated

Operational

OE Simulated

E NA 1.3 0.9 0.7 0.9 0.9 0.7

W NA 1.5 0.8 0.6 0.7 0.8 0.5

EU 1.2 1.1 1.4 0.8 0.8 0.6

India 1.2 0.7 0.7 0.8 0.8 0.5

E Asia 1.1 0.8 0.7 0.9 0.8 0.7

Africa 0.9 0.8 1.0 0.9 0.9 0.8

Western North America

Eastern North America

Num

ber o

f O

bser

vatio

ns

Best agreement

slope=1.47r=0.65

slope=0.81r=0.75

slope=0.56r=0.53

slope=1.25r=0.85

slope=0.94r=0.87

slope=0.71r=0.71

Operational

Operational = NASA MODIS Collection 5

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

van Donkelaar et al., JGR, 2013

η =

PM2.

5 / A

OD

Eastern US East China

Satellite-Derived PM2.5 Trends Inferred from SeaWifs & MISR AOD and GEOS-Chem AOD/PM2.5

Boys et al., submitted

MISR2000 -2012

SeaWiFS1998 -2010

PM2.5 Trend [μg m-3 yr-1]

Combine SeaWifs & MISR to Calculate 15-Year PM2.5 Timeseries (1998-2012)

Boys et al., submitted

Eastern North America

Middle East South Asia

East AsiaPM

2.5 (μ

g m

-3)

PM2.

5 (μ

g m

-3)

PM2.

5 (μ

g m

-3)

00.25

-0.25 1-1 1.5

-1.5 2-2

0.010.05

0.1

P- v

alue

PM2.5 Trend [µg m-3 yr-1]

-0.5

0.5

Consistent Trends in Satellite-Derived and In Situ PM2.5

Boys et al., submitted

Sate

llite

-D

eriv

edIn

Situ

In Situ (1999-2012)0.37 ± 0.06 μg m-3 yr-1

Satellite-Derived (1999-2012)0.36 ± 0.13 μg m-3 yr-1

Eastern US

PM2.

5 A

nom

aly

(ug

m-3)

SeaWifs & MISR

In Situ

1999-2012

Interpret Satellite-derived PM2.5 Trends with GEOS-Chem

Boys et al., submitted

Eastern North America Middle East

South Asia East Asia

Year Year

GEOS-Chem Secondary Inorganic -0.4 μg m-3 yr-1 GEOS-Chem Mineral Dust 0.7 μg m-3 yr-1

GEOS-Chem Secondary Inorganic 0.7 μg m-3 yr-1

GEOS-Chem Secondary Inorganic 0.8 μg m-3 yr-1

GEOS-Chem Organic 0.04 μg m-3 yr-1 GEOS-Chem Organic 0.2 μg m-3 yr-1

SeaWifs & MISR -0.39±0.10 μg m-3 yr-1 SeaWifs & MISR 0.81±0.21 μg m-3 yr-1

SeaWifs & MISR 0.93±0.22 μg m-3 yr-1 SeaWifs & MISR 0.79±0.27 μg m-3 yr-1

PM2.

5 [ug

/m3 ]

PM2.

5 [ug

/m3 ]

van Donkelaar et al., submitted

Changes in Long-term Population-Weighted Ambient PM2.5

Clean Areas are Improving; High PM2.5 Areas are DegradingWHO Guideline & Interim Targets

van Donkelaar et al., submitted

Changes in Long-term Population-Weighted Ambient PM2.5

Clean Areas are Improving; High PM2.5 Areas are DegradingWHO Guideline & Interim Targets

Exceedance of WHO AQG drops from 62% to 19%

Exceedance of WHO IT1 increases from 51% to 70%

1998

2012

1998 (51%)

2012 (70%)

WHO AQG

WHO IT1

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

Measures PM2.5 Mass & Composition at Sites Measuring AOD

Semi-Autonomous PM2.5 & PM10 Impaction Sampling Station (AirPhoton)Ions & metals

3-λ Nephelometer

AOD from CIMEL Sunphotometer (e.g. AERONET)

www.spartan-network.orgSnider et al., in prep

Testing

Deployed

Committed

Prospective

Nonlinear Relation Between PM2.5 and SourcesWhich Local Sources Should be Reduced to

Decrease Mortality from PM2.5?

PM2.5Primary Chemistry Precursors

Sulfur Dioxide (SO2)Nitrogen Oxides (NOx)

Ammonia (NH3)

Adjoint Model: Calculate Sensitivity of Global Premature Mortality to Local Emissions

Emissions Chemistry & Transport Concentrations

Health Impact

Function

∂∂Emissions

Chemistry & Transport ∂

∂Concentrations

Global Mortality

GEOS-Chem

GEOS-Chem Adjoint

Colin Lee

Sensitivity of Global Premature Mortality to SO2 Emissions

Lee et al., in prep

PM2.5 subgrid variability resolved using satellite AODExposure-response function from Global Burden of Disease Project

ΔMortalityglobal / 10% ΔEmissions

Sensitivity of Global Premature Mortality to:

SO2 Emissions

NH3 Emissions

Lee et al., in prep

ΔMortalityglobal / 10% ΔEmissions

Insight into Global PM2.5 through Satellite Remote Sensing Modeling, and Ground-based Instruments

Acknowledgements:NSERC, Health Canada, Environment Canada

• Particulate matter is major risk factor for global premature mortality

• Regions with high PM2.5 have increasing concentrations

• Regions with low PM2.5 have decreasing concentrations

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

• SPARTAN and CALIOP evaluate AOD/PM2.5 simulation

• Adjoint allows efficient calculation of sensitivity of premature

mortality to emissions changes

• Controls in South Asia on SO2 much more effective than on NH3