title: Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach.
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.
authors.affiliation: College of Environmental Sciences, Peking University, Beijing 100871, China. jardon.zhou@gmail.com
authors.forename: Feng
authors.initials: F
authors.lastname: Zhou
authors.forename: Huai-Cheng
authors.initials: HC
authors.lastname: Guo
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
authors.forename: Ze-Jia
authors.initials: ZJ
authors.lastname: Hao
mesh_terms: D016000:Cluster Analysis; D004784:Environmental Monitoring / Q000706:statistics & numerical data; D005068:Eutrophication; D005163:Factor Analysis, Statistical; D040362:Geographic Information Systems; D006723:Hong Kong; D025341:Principal Component Analysis; D012722:Sewage; D014873:Water Pollutants / Q000032:analysis*; D014876:Water Pollution / Q000032:analysis*
chemical_list: D012722:Sewage; D014873:Water Pollutants