Estimating Population Exposure to Fine Particulate Matter in the Conterminous U.S. using Shape Function-based Spatiotemporal Interpolation Method: A County Level Analysis.

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 PM. 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 PM interpolation. The paper also estimates the population exposure to the ambient air pollution of PM at the county-level in the contiguous U.S. in 2009. The interpolated county-level PM has been linked to 2009 population data and the population with a risky PM exposure has been estimated. The risky PM exposure means the PM concentration exceeding the National Ambient Air Quality Standards. The geographic distribution of the counties with a risky PM exposure is visualized. This work is essential to understanding the associations between ambient air pollution exposure and population health outcomes.