期刊文献+

基于空间自相关的水污染空间聚类研究 被引量:3

Spatial Clustering of Water Pollution Based on Spatial Autocorrelation Analysis
下载PDF
导出
摘要 运用空间自相关分析方法对《中国环境质量报告2012》中全国地表水监测点位的溶解氧、高锰酸钾指数、五日生化需氧量、氨氮、石油类、挥发酚、汞和铅8项主要污染物水质常规监测指标进行了空间分布特征的定量研究。结果表明,各污染物的Moran指数都大于0,说明我国主要污染物的空间分布具有明显的空间自相关性;局部自相关分析的Moran散点图表明,各类污染物形成了多种空间分布格局。总体而言,我国污染物的扩散分布与地区社会经济有着密切关系,人口活动密集地区的水污染程度明显较高,如京津冀地区。从宏观格局看,我国水污染可分为东西、南北两大格局,东部沿海地区的水污染高集聚区明显高于中西部地区;北方地区的水环境污染状况比南方地区严重,且各种污染物指标在全国范围内有不同的集聚地域。 The spatial autocorrelation analysis was performed to quantitatively analyze the spatial distribution characteristics of water pollution monitoring indices , based on China Status of Environment in 2012.Eight water pollution indices , including dissolved oxygen , potassium permanganate index , BOD5 , ammonia nitrogen , petroleum, volatile phenol, mercury and lead.The Moran’s I is greater than 0 for all pollution indices, indicating that the spatial distribution of the main pollutants in China has significant spatial autocorrelation .The result of Moran scatter diagram of LISA shows that the pollutants have developed several kinds of spatial patterns .In general , the distribution of the water pollutants has close relationship with regional socio-economic situations , with obviously higher pollution in densely populated areas , such as Beijing-Tianjin-Hebei region .The water pollution in China could be divided into two major patterns ‘east-west’ and ‘north-south’, namely, the water pollution in China’s eastern coastal areas were significantly higher than that in the midwest , and the water pollution in northern China was worse than that in southern region .Different water pollution indices had different agglomeration areas .
出处 《环境工程技术学报》 CAS 2014年第4期293-298,共6页 Journal of Environmental Engineering Technology
基金 山东省科技发展计划项目(2011SJGZ03) 北京联合大学人才强校计划人才资助项目(BPHR2012E01)
关键词 水污染 空间自相关 空间聚类 water pollution spatial autocorrelation analysis spatial clustering
  • 相关文献

参考文献14

  • 1中国工程院,环境保护部.中国环境宏观战略研究(综合报告卷)[M].北京:中国环境科学出版社,2011.
  • 2TSAI C F,TSAI C W,WU H C,et al.A novel data clustering approach for mining in large databases[J].The Journal of Systems and Software,2004,73(1):133-145.
  • 3WONG H,HU B Q.Application of interval clustering approach to water quality evaluation[J].Journal of Hydrology,2013,491:1-12.
  • 4SARMIENTO M H,ISAZA N C.Identification and estimation of functional states in drinking water plant based on fuzzy clustering[J].Computer Aided Chemical Engineering,2012,30:1317-1321.
  • 5王清芬,王伯铎,马俊杰,王文春,冯护国,王秋侠.用灰色聚类关联分析法对水环境质量的评价[J].环境工程,2008,26(3):59-62. 被引量:18
  • 6赵玉婷,张征,吕连宏,牟向玉,李道峰.基于地下水多变量空间聚类分析的变异性评价[J].地球科学与环境学报,2009,31(1):79-84. 被引量:9
  • 7LI X,GRIFFIN W A.Using ESDA with social weights to analyze spatial and social patterns of preschool children's behavior[J].Applied Geography,2013,43:67-80.
  • 8戴晓燕,过仲阳,石纯,吴健平.空间聚类在农业非点源污染研究中的应用[J].华东师范大学学报(自然科学版),2005(3):59-64. 被引量:5
  • 9张学霞,武鹏飞,刘奇勇.基于空间聚类分析的松辽流域水资源利用风险评价[J].地理科学进展,2010,29(9):1032-1040. 被引量:11
  • 10YE X Y,WU L.Analyzing the dynamics of homicide patterns in Chicago:ESDA and spatial panel approaches[J].Applied Geography,2011,31(2):800-807.

二级参考文献89

共引文献427

同被引文献42

引证文献3

二级引证文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部