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A framework of characteristics identification and source apportionment of water pollution in a river: A case study in the Jinjiang River, China

机译:河流水污染特征识别与源解析的框架-以晋江为例

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摘要

A framework for characteristics identification and source apportionment of water pollution in the Jinjiang River of China was proposed in this study for evaluation. A total of 114 water samples which were generated between May 2009 and September 2010 at 13 sites were collected and analysed. First, support vector machine (SVM) and water quality pollutant index (WQPI) were used for water quality comprehensive evaluation and identifying characteristic contaminants. Later, factor analysis with nonnegative constraints (FA-NNC) was employed for source apportionment. Finally, multi-linear regression of the absolute principal component score (APCS/MLR) was applied to further estimate source contributions for each characteristic contaminant. The results indicated that the water quality of the Jinjiang River was mainly at the third level (65.79%) based on national surface water quality permissible standards in China. Ammonia nitrogen, total phosphorus, mercury, iron and manganese were identified as characteristic contaminants. Source apportionment results showed that industrial activities (63.16%), agricultural non-point source (16.50%) and domestic sewage (12.85%) were the main anthropogenic pollution sources which were influencing the water quality of Jinjiang River. This proposed method provided a helpful framework for conducting water pollution management in aquatic environment.
机译:提出了晋江水污染特征识别与源解析的框架进行评价。收集并分析了2009年5月至2010年9月在13个站点产生的114个水样。首先,使用支持向量机(SVM)和水质污染物指数(WQPI)进行水质综合评估和识别特征污染物。后来,采用具有非负约束的因素分析(FA-NNC)进行了源分配。最后,应用绝对主成分评分(APCS / MLR)的多线性回归进一步估算每种特征污染物的来源贡献。结果表明,按中国国家地表水水质允许标准计算,晋江水质主要处于三级(65.79%)。氨氮,总磷,汞,铁和锰被确定为特征性污染物。污染源分配结果表明,工业活动(63.16%),农业面源(16.50%)和生活污水(12.85%)是影响晋江水质的主要人为污染源。该方法为水生环境水污染管理提供了有益的框架。

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