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Comparative spatiotemporal analysis of fine particulate matter pollution
Pang W.; Christakos G.; Wang J. F.
Source PublicationEnvironmetrics
KeywordSpatiotemporal Analysis Air Pollution Particulate Matter Bayesian Maximum Entropy Kriging Geostatistics Bayesian-maximum-entropy Site-specific Information Eastern United-states Air-pollution Spatial Prediction Soft Data Exposure Space Distributions Mortality
AbstractThe prime focus of this work is the comparative investigation, theoretical and numerical, of spatiotemporal techniques used in air pollution studies. Space-time statistics techniques are classified on the basis of a set of criteria and the relative theoretical merits of each technique are discussed accordingly. The numerical comparison involves the applications of two representative techniques. For this purpose, the popular spatiotemporal epistemic knowledge synthesis and graphical user interface (SEKS-GUI) software of spatiotemporal statistics is used together with a dataset of PM(2.5) daily measurements obtained at monitoring stations geographically distributed over the state of North Carolina, USA. The analysis offers valuable insight concerning the choice of an appropriate spatiotemporal technique in air pollution studies. Copyright (C) 2009 John Wiley & Sons, Ltd.
Indexed BySCI
Document TypeSCI/SSCI论文
Recommended Citation
GB/T 7714
Pang W.,Christakos G.,Wang J. F.. Comparative spatiotemporal analysis of fine particulate matter pollution. 2010.
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