title: Integrated Application of Multivariate Statistical Methods to Source Apportionment of Watercourses in the Liao River Basin, Northeast China.
abstract: Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009-2011) on water quality in the Liao River system (China). Cluster analysis (CA) classified the 12 months of the year into three groups (May-October, February-April and November-January) and the 66 sampling sites into three groups (groups A, B and C) based on similarities in water quality characteristics. Discriminant analysis (DA) determined that temperature, dissolved oxygen (DO), pH, chemical oxygen demand (CODMn),5-day biochemical oxygen demand (BOD₅), NH₄⁺-N, total phosphorus (TP) and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics.
authors: National & Local United Engineering Laboratory of Petroleum Chemical Process Operation, Optimization and Energy Conservation Technology, Liaoning Shihua University, Fushun 113001, China. chenjiabo@126.com.|Institute of Eco-Environmental Sciences, Liaoning Shihua University, Fushun 113001, China. chenjiabo@126.com.
authors: Jiabo
authors: J
authors: Chen
authors: National & Local United Engineering Laboratory of Petroleum Chemical Process Operation, Optimization and Energy Conservation Technology, Liaoning Shihua University, Fushun 113001, China. chenjiabo@lnpu.edu.cn.|Institute of Eco-Environmental Sciences, Liaoning Shihua University, Fushun 113001, China. chenjiabo@lnpu.edu.cn.
authors: Fayun
authors: F
authors: Li
authors: National & Local United Engineering Laboratory of Petroleum Chemical Process Operation, Optimization and Energy Conservation Technology, Liaoning Shihua University, Fushun 113001, China. zhiping_fan@hotmail.com.|Institute of Eco-Environmental Sciences, Liaoning Shihua University, Fushun 113001, China. zhiping_fan@hotmail.com.
authors: Zhiping
authors: Z
authors: Fan
authors: National & Local United Engineering Laboratory of Petroleum Chemical Process Operation, Optimization and Energy Conservation Technology, Liaoning Shihua University, Fushun 113001, China. yanjie_wang0810@hotmail.com.|Institute of Eco-Environmental Sciences, Liaoning Shihua University, Fushun 113001, China. yanjie_wang0810@hotmail.com.
authors: Yanjie
authors: Y
authors: Wang
mesh_terms: D057919:Biological Oxygen Demand Analysis; D002681:China; D016000:Cluster Analysis; D016002:Discriminant Analysis; D004784:Environmental Monitoring / Q000379:methods*; D015999:Multivariate Analysis; D010100:Oxygen / Q000378:metabolism; D010758:Phosphorus / Q000032:analysis; D025341:Principal Component Analysis; D045483:Rivers / Q000737:chemistry*; D012621:Seasons; D014876:Water Pollution / Q000032:analysis / Q000706:statistics & numerical data*; D060753:Water Quality
chemical_list: D010758:Phosphorus; D010100:Oxygen
keywords: Liao River; geographic information system (GIS); multivariate analysis; source apportionment; spatial and temporal patterns