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Article
Estimating Population Exposure to Fine Particulate Matter in the Conterminous U.S. Using Shape Function-Based Spatiotemporal Interpolation Method: A County Level Analysis
GSTF Journal on Computing
  • Lixin Li, Georgia Southern University
  • Xingyou Zhang, Centers For Disease Control and Prevention
  • James B. Holt, Centers for Disease Control and Prevention
  • Jie Tian, Georgia Southern University
  • Reinhard Piltner, Georgia Southern University
Document Type
Article
Publication Date
1-1-2012
DOI
10.5176_2010-2283_1.4.99
Disciplines
Abstract

This paper investigates spatiotemporal interpolation methods for the application of air pollution assessment. The air pollutant of interest in this paper is fine particulate matter PM2.5. The choice of the time scale is investigated when applying the shape function-based method. It is found that the measurement scale of the time dimension has an impact on the quality of interpolation results. Based upon the result of 10-fold cross validation, the most effective time scale out of four experimental ones was selected for the PM2.5 interpolation. The paper also estimates the population exposure to the ambient air pollution of PM2.5 at the county-level in the contiguous U.S. in 2009. The interpolated county-level PM2.5 has been linked to 2009 population data and the population with a risky PM2.5 exposure has been estimated. The risky PM2.5 exposure means the PM2.5 concentration exceeding the National Ambient Air Quality Standards. The geographic distribution of the counties with a risky PM2.5 exposure is visualized. This work is essential to understanding the associations between ambient air pollution exposure and population health outcomes.

Comments

The GSTF Journal on Computing is an open access journal that publishes its articles under a Creative Commons Attribution Non-Commercial (CC BY-NC 3.0) license.

Citation Information
Lixin Li, Xingyou Zhang, James B. Holt, Jie Tian, et al.. "Estimating Population Exposure to Fine Particulate Matter in the Conterminous U.S. Using Shape Function-Based Spatiotemporal Interpolation Method: A County Level Analysis" GSTF Journal on Computing Vol. 1 Iss. 4 (2012) p. 24 - 30 ISSN: 2010-2283
Available at: http://works.bepress.com/reinhard_piltner/8/