Transcript Aura NO2 talk - Dalhousie University

Advances in Studies of Air Quality and Health
Informed with Satellite Remote Sensing
Randall Martin
with contributions (alphabetical) from
Brian Boys, Jeff Geddes, Mark Gibson, Colin Lee, Caroline Nowlan (now SAO),
Sajeev Philip, Graydon Snider, Crystal Weagle, Aaron van Donkelaar, Junwei Xu
Michael Brauer (UBC), Myungie Choi (Yonsei), Aaron Cohen (HEI), Daven Henze (CU
Boulder), Christina Hsu (NASA), Jhoon Kim (Yonsei), Yang Liu (Emory), Zifeng Lu
(Argonne), Vanderlei Martins (AirPhoton), David Streets (Argonne), Siwen Wang
(Tsinghua), Qiang Zhang (Tsinghua), SPARTAN Team
AGU
19 December 2014
Insufficient In Situ Measurements for Exposure Assessment
General Approach to Estimate Daily PM2.5 Concentration
Coincident Model
(GEOS-Chem) Profile
Altitude
Daily Satellite(MODIS, MISR, SeaWifs, GOCI)
GOME, SCIAMACHY, OMI, GOME-2)
Column of AOD or NO2
Concentration
PM 2.5,sat
 PM 2.5,model 
 AODsat 

A
O
D
model 

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
Global Burden of Disease 2010
PM2.5 Causal Role in
70 Million Disability Adjusted Life Years (~3%)
>3 Million Excess Deaths (~5%)
Three-fold increase in
premature mortality rate
over previous Global Burden
of Disease study for 2000
Lim et al., Lancet, 2012
Similar Conclusions Reached by WHO in 2014
Evaluation in
North America:
r=0.77
slope = 1.07
N=1057
EHP Paper of the Year
Outside Canada/US
N = 244 (84 non-EU)
r = 0.83 (0.83)
Slope = 0.86 (0.91)
Bias = 1.15 (-2.64) μg/m3
van Donkelaar et al., EHP, 2010
PM2.5 (μg m-3)
PM2.5 (μg m-3)
Combine SeaWifs & MISR to Calculate 15-Year PM2.5
East Asia
Eastern North America
Timeseries (1998-2012)
0.1
0.05
0.01
-2
-1
0
1
2
South Asia
PM2.5 (μg m-3)
P- value
Middle East
PM2.5 Trend [µg m-3 yr-1]
Boys et al., ES&T, 2014
Consistent Trends in Satellite-Derived and In Situ PM2.5
Eastern US
PM2.5 Anomaly (ug m-3)
Satellite-Derived
In Situ
1999-2012
SeaWifs & MISR
In 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
Boys et al., ES&T, 2014
Interpret Satellite-derived PM2.5 Trends with GEOS-Chem
Eastern North America
PM2.5 [ug/m3]
SeaWifs & MISR -0.39±0.10 μg m-3 yr-1
GEOS-Chem Secondary Inorganic -0.4 μg m-3 yr-1
PM2.5 [ug/m3]
South Asia
SeaWifs & MISR 0.93±0.22 μg m-3 yr-1
Middle East
SeaWifs & MISR 0.81±0.21 μg m-3 yr-1
GEOS-Chem Mineral Dust 0.7 μg m-3 yr-1
East Asia
SeaWifs & MISR 0.79±0.27 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 0.2 μg m-3 yr-1
Year
GEOS-Chem Organic 0.04 μg m-3 yr-1
Year
Boys et al., ES&T, 2014
Changes in Long-term Population-Weighted Ambient PM2.5
Clean Areas are Improving; High PM2.5 Areas are Degrading
WHO Guideline & Interim Targets
1998 (51%)
1998
Exceedance of
WHO AQG
drops from
62% to 19%
2012
WHO
AQG
2012 (70%)
Exceedance of
WHO IT1
increases from
51% to 70%
WHO
IT1
Exceedance of
WHO AQG
drops from
62% to 19%
van Donkelaar et al., EHP, 2014
Population Weighted PM2.5 Composition
Use GEOS-Chem to Partition Satellite AOD into PM2.5 Composition
Secondary Inorganic Aerosols (SIA)
Particulate Organic Matter (OM)
11 ug/m3
12 ug/m3
r=0.70, slope=0.44
r=0.94, slope=0.89
Mineral Dust
Global Population-Weighted PM2.5 Composition
Sea Salt (1%)
Sulfate (17%)
11 ug/m3
Mineral Dust (30%)
Nitrate (6%)
Ammonium (7%)
Satellite-Model outperforms pure model.
Examples:
Black Carbon (7%)
Slope GEOS-Chem SIA = 0.65 (vs 0.93 with sat)
Organic Mass (32%)
GEOS-Chem OM: r = 0.61 (vs r=0.70 with sat)
Philip et al., ES&T, 2014
GOCI Offers High Temporal and Spatial Resolution
for Inference of PM2.5
In Situ PM2.5 better represented by GOCI-derived PM2.5 (slope = 0.91) than by
GEOS-Chem (slope =0.53)
Also better than MODIS (r=0.8, slope=1.3)
Junwei Xu et al., in prep
AOD from Jhoon Kim
SPARTAN: An Emerging Global Network to Evaluate and
Enhance Satellite-Based Estimates of PM2.5
Measures PM2.5 Mass & Composition at Sites Measuring AOD
Testing
Deployed
Committed
Prospective
Semi-Autonomous
PM2.5 & PM10
Impaction
Sampling Station
(AirPhoton)
Ions & metals
3-λ Nephelometer
AOD from CIMEL
Sunphotometer
(e.g. AERONET)
www.spartan-network.org
Snider et al., AMTD, 2014
PM2.5/AOD Driven by Scattering Vertical Profile &
Mass Scattering Efficiency
PM 2.5  bsp ,overpass   bsp ,24 h   PM 2.5,24h 

 
 


AOD  AODoverpass   bsp ,overpass   bsp ,24 h 
bsp = nephelometer measurements of aerosol scatter
overpass = satellite overpass times (taken as 10am – 2pm)
www.spartan-network.org
PM2.5 / AOD (μg / m3)
Snider et al., AMTD, 2014
Nonlinear Relation Between PM2.5 and Sources
Which Local Sources Should be Reduced to
Decrease Premature Mortality from PM2.5?
Primary
PM2.5
Chemistry
Precursors
Nitrogen Oxides (NOx)
Sulfur Dioxide (SO2)
Ammonia (NH3)
Adjoint Model: Calculate Sensitivity of Global
Premature Mortality to Local Emissions
∂
∂Emissions
Chemistry &
Transport
∂
∂Concentrations
Global
Premature
Mortality
Sensitivity of Global Premature Mortality to:
SO2
Emissions
NH3
Emissions
ΔMortalityglobal / 10% ΔEmissions
Lee et al., in prep
Relative NO2 (unitless)
For Surface NO2
Also Consistent Trends (1996-2012) in In Situ and
Satellite-Derived (GOME, SCIAMACHY, GOME-2)
Year
Geddes et al., submitted
Surface NO2 Trends over 1996-2012 from GOME,
SCIAMACHY, GOME-2
NO2(ppbv)
NO2(ppbv)
NO2(ppbv)
Similarities with PM2.5 Trends where Driven by Secondary Inorganics
Differences Elsewhere
Geddes et al., submitted
Dry Deposition of NO2 and SO2 Inferred from OMI
(2005-2008) and GEOS-Chem Deposition Velocity
NO2
SO2
Nowlan et al., GBC, 2014
Insight into Global PM2.5 & NO2 through Satellite Remote
Sensing Modeling, and Ground-based Instruments
• 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 evaluates AOD/PM2.5 simulation
• Controls in South Asia on SO2 much more effective than on NH3
• Dramatic trends in NO2 worldwide indicate changing air quality mix
• NO2 and SO2 offer constraints on dry deposition
Acknowledgements:
NSERC, Health Canada,
Environment Canada