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基于GIS和化学计量学方法的近岸水体污染源识别与空间格局研究

Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach.

作者信息

Zhou Feng, Guo Huai-Cheng, Liu Yong, Hao Ze-Jia

机构信息

College of Environmental Sciences, Peking University, Beijing 100871, China.

出版信息

J Environ Sci (China). 2007;19(7):805-10. doi: 10.1016/s1001-0742(07)60135-1.

Abstract

Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set (5 years (2000-2004), 17 parameters) obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May (the 1st period) and June-August (the 2nd period). Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns.

摘要

地理信息系统(GIS)与化学计量学方法的综合联合应用,被用于香港南部水质管制区近岸水域监测所获大型数据集(2000 - 2004年的5年数据,17个参数)的近岸水污染来源识别及空间格局分析。根据聚类分析,9月至次年5月(第1阶段)与6月至8月(第2阶段)的污染程度存在显著差异。基于这些结果,通过因子分析/主成分分析识别出有机/富营养化污染、自然污染、矿物/人为污染和粪便污染这4种潜在污染源。然后采用反距离加权法分析各监测点的因子得分,结果表明各潜在污染源对不同监测点的影响程度存在差异。本研究表明,混合方法在近岸水污染来源及空间格局识别方面是有用且有效的。

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