## Abstract Researchers are beginning to realize the need to take spatial structure into account when modeling data on air pollutants. We develop several models for particulate matter in an urban region that allow spatial dependence to be represented in different manners over a time period of one y
Comparative spatiotemporal analysis of fine particulate matter pollution
β Scribed by W. Pang; G. Christakos; J-F Wang
- Book ID
- 102188149
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 187 KB
- Volume
- 21
- Category
- Article
- ISSN
- 1180-4009
- DOI
- 10.1002/env.1007
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β¦ Synopsis
Abstract
The prime focus of this work is the comparative investigation, theoretical and numerical, of spatiotemporal techniques used in air pollution studies. Spaceβtime 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 (SEKSβGUI) 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 Β© 2009 John Wiley & Sons, Ltd.
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