development of fused spatiotemporal air pollutant exposure surrogates for health studies

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1/16 scape.gatech.edu 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 1 Georgia Institute of Technology, 2 NASA Goddard Space Flight Center 24 October 2013 Air & Waste Management Association Georgia Chapter Fall Conference Atlanta, GA R834799

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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 Presentation

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Page 1: Development of Fused  Spatiotemporal Air Pollutant  Exposure Surrogates for  Health Studies

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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?