|
Detailed Reference Information |
Smith, R.L., Kolenikov, S. and Cox, L.H. (2003). Spatiotemporal modeling of PM2.5 data with missing values. Journal of Geophysical Research 108: doi: 10.1029/2002JD002914. issn: 0148-0227. |
|
We propose a method of analyzing spatiotemporal data by decomposition into deterministic nonparametric functions of time and space, linear functions of other covariates, and a random component that is spatially, though not temporally, correlated. The resulting model is used for spatial interpolation and especially for estimation of a spatially dependent temporal average. The results are applied to part of the PM2.5 network established by the U.S. Environmental Protection Agency, covering three southeastern U.S. states. A novel feature of the analysis is a variant of the expectation-maximization algorithm to account for missing data. The results show, among other things, that a substantial part of the region is in violation of the proposed long-term average standard for PM2.5. |
|
|
|
BACKGROUND DATA FILES |
|
|
Abstract |
|
|
|
|
|
Keywords
Atmospheric Composition and Structure, Aerosols and particles (0345, 4801), Atmospheric Composition and Structure, Pollution--urban and regional, Mathematical Geophysics, Modeling |
|
Publisher
American Geophysical Union 2000 Florida Avenue N.W. Washington, D.C. 20009-1277 USA 1-202-462-6900 1-202-328-0566 service@agu.org |
|
|
|