Comparative spatiotemporal analysis of fine particulate matter pollution
文献类型：SCI/SSCI论文
| 作者 | Pang W. ; Christakos G. ; Wang J. F. |
| 发表日期 | 2010 |
| 关键词 | spatiotemporal 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 |
| 英文摘要 | The 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. |
| 出处 | Environmetrics |
| 卷 | 21 |
| 期 | 3-4 |
| 页 | 305-317 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1180-4009 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/23236]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Pang W.,Christakos G.,Wang J. F.. Comparative spatiotemporal analysis of fine particulate matter pollution. 2010. |
入库方式： OAI收割
来源：地理科学与资源研究所
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