development of fused spatiotemporal air pollutant exposure surrogates for health studies
DESCRIPTION
R834799. Development of Fused Spatiotemporal Air Pollutant Exposure Surrogates for Health Studies. Mariel D. Friberg 1 , S. Sororian 1 , H . Holmes 1 , C. Ivey 1 , Yongtao Hu 1 , A . Russell 1 , J. Mulholland 1 , R. Kahn 2 , M. Chin 2 - PowerPoint PPT PresentationTRANSCRIPT
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Development of Fused Spatiotemporal Air Pollutant Exposure Surrogates for Health
StudiesMariel D. Friberg1, S. Sororian1, H. Holmes1, C. Ivey1, Yongtao Hu1, A. Russell1, J. Mulholland1, R. Kahn2, M. Chin2
1Georgia Institute of Technology, 2NASA Goddard Space Flight Center
24 October 2013Air & Waste Management Association
Georgia Chapter Fall ConferenceAtlanta, GA
R834799
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• classified outdoor air pollution as carcinogenic to humans
• evaluation showed an increasing risk of lung cancer with increasing levels of exposure to particulate matter and air pollution
• in 2010, 223 000 deaths from lung cancer worldwide resulted from air pollution
Motivation: Health
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Motivation: Health
*Image From: Lim et al (2012), Lancet
Burden of disease attributable to 20 leading risk factors in 2010, expressed as a percentage of global disability-adjusted life-years.
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Motivation: MonetaryBenefits and Costs of the Clean Air Act from 1990 to 2020
*Image From: U.S. EPA OAR. The Benefits and Costs of the Clean Air Act from 1990 to 2020: Summary Report. March 2011.
.
$1.9 Trillion
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• Surrogate exposure metrics can help explain apparent between-city heterogeneity in acute associations between ambient air quality and morbidity.
Overall Objective
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Overview
SCAPE Center Organization
Southeastern Center for Air Pollution and Epidemiology (SCAPE)
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• Develop and evaluate surrogate exposure metrics to better understand the impact of exposure measurement error and the benefits of using fused air pollutant data at higher spatial resolution in time-series studies.
?-10
-9
-8
-7
-6
-5
-4
1 1.1 1.2 1.3 1.4 1.5 1.6
JST
YRK
130210012
130510021
130590002
130670003
130730001
130770002
130850001
130890002
130970004
131270006
131350002
131510002
132130003
132150008
132230003
132450091
132611001
131210055
132470001
7774
56
61
52
51
54
6250
64
70
73
6879
68
58
67
6574
75
Specific Objective
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SCAPE Multi-City Study Area
Atlanta, Georgia1999-2004JST SEARCHPM2.5 = 16.6mg m-3
Dallas-Fort Worth, Texas2006-2010 Hinton CSNPM2.5 = 10.3mg m-3
St. Louis, Missouri2001-2003Blair St. CSNPM2.5 = 14.5mg m-3
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NOx
0
0.2
0.4
0.6
0.8
1
JST SDekalb Conyers YRK
R2
temporal R2 < 0.5
0
0.2
0.4
0.6
0.8
1
1 2 3 4 5 6 7 8 9 10 11
R2
temporal R2 < 0.5
spatial R2 ~ 0.9
PM2.5
spatial R2 < 0.5
Dataset Comparison
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NOx
0
0.2
0.4
0.6
0.8
1
JST SDekalb Conyers YRK
R2
temporal R2 < 0.5
0
0.2
0.4
0.6
0.8
1
1 2 3 4 5 6 7 8 9 10 11
R2
temporal R2 < 0.5
spatial R2 ~ 0.9
PM2.5
spatial R2 < 0.5
Dataset Comparison
CMAQ AssessmentTemporal variance
Spatial variance – secondary pollutant
Spatial variance – primary pollutant
Strong seasonal trends
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Example: 1-hr max NO2 (ppb) in Georgia for 21 September 2010, using 4-km resolution CTM data
48.216.3
40 714
Combine to maximize correlation over time
and space
CMAQ80
60
40
20
21 *)1(** CFCFC
90
70
50
30
10
Data Fusion Methodology
0
0.2
0.4
0.6
0.8
1
0 50 100 150 200 250 300
R
D (km)
OBS
CMAQOBS-CMAQ
R1 = a e g D
R2
Weighting Factors
Spatially Resolved Pollutant Field, C*
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• Apply data fusion method• Pollutants: 5 air pollutant gases and 7
airborne particulate matter measures • Location: 5 cities• Time Period: 1998-2010
• Conduct uncertainty analysis • Data Withholding
Future Work
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1 Multi-angle Imaging SpectroRadiometer.2 Southeastern Center for Air Pollution and Epidemiology.3 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality field campaign.
Model Evaluation(DISCOVER-AQ3)
Uncertainty Analysis(Patadia et al., 2013; Errico, 1997)
Model Application(SCAPE2)
Model Development
Ground Observations
CTM Results(SCAPE2,
DISCOVER-AQ3)
MISR1 Research Aerosol Retrieval
Algorithm (Kahn et al., 2001)
Future Fusion Methodology
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• Surrogate exposure metrics from fusion method will be used in health studies to:• Provide best risk estimate in each city• Estimate impact of error due to spatial
variation
Conclusion
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• Special thanks to: – Dr. Mulholland, Dr. Russell, Dr.
Holmes, Dr. Kahn, Ms. Ivey
• U.S. EPA SCAPE• NASA Jenkins Graduate Fellowship• AWMA Georgia Chapter• Southern Company/ARA
SCAPE Center Organization
This presentation was made possible in part by USEPA and NASA. Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the funding sources and those sources do not endorse the purchase of any commercial products or services mentioned in the publication.
Acknowledgments
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• http://www.scape.gatech.edu/• [email protected]
SCAPE Center Organization
Questions?