Assessment of water quality of Beijing lakes using principal component analysis

摘要：

　　Combined with SPSS software, water quality of four lakes in Beijing from 2009 to 2011 were evaluated in this study by using principal component analysis(PCA), which use correlation among multiple water quality constituents to effectively reduce the number of variables. Two main components which accounted for 93.508% of the total variance contribution rates were chosen from seven indicators. Water quality evaluation function of each principal component and comprehensive function were set up to identify and describe spatial patterns in water quality that result from hydrologic and geochemical processes and from sources of contamination. Research showed that the major pollutant that affected the lakes in Beijing were organic matter and eutrophication caused by nitrogen and phosphorus, the most severe polluted lake is Liuyin park lake and the lightest is Tuancheng lake.

关键词： Principal component analysis SPSS Surface water quality

作者: X.J.Chen X.H.Yang Z.H.Dong

作者单位: State Key Laboratory of Water Environment Simulation, School of Environment,Beijing Normal University, Beijing 100875, China

会议类型: 国际会议

会议名称: The 3rd Biennial ISRS Symposium Achieving Healthy and Viable Rivers (ISRS)第3届国际河流大会

会议地点: 北京

会议语种:英文

页码: 437-442

在线出版日期: 2013-08-05（万方平台首次上网日期，不代表论文的发表时间）