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Spatio-Temporal Evaluation and Quantification of Pollutant Source Contribution in Little Akaki River, Ethiopia: Conjunctive Application of Factor Analysis and Multivariate Receptor Model

机译:埃塞俄比亚小阿卡基河污染物源贡献的时空评估和量化:因子分析和多元受体模型的联合应用

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摘要

Little Akaki River (LAR) is among the heavily polluted urban rivers in Ethiopia. A bimonthly physico-chemical and heavy metals water quality analysis was conducted aimed at assessing the spatio-temporal characteristics and quantifying sources contributing to the pollution during dry and wet season at 22 montoring stations. Accordingly, laboratory analysis results indicated that most of the constituents deviated from the national and international guideline limits and the river is critically polluted at the middle and downstream segment. Factor Analysis (FA) was used to qualitatively determine the possible sources contributing to the pollution of LAR where three factors are identified that determine the pollution level during wet and dry season explaining 79.26 % and 79.47 % of the total variance respectively. Agricultural and urban runoff (nonpoint pollution sources), industrial and domestic waste are the three dominant factors that contribute to pollution in LAR. On the other hand, pollution sources of heavy metals in LAR are mostly dominated by industrial release whereas urban washouts from garages and automobile oil spills are other possible sources. Cluster Analysis spatially grouped all 22 monitoring stations into four and three clusters during the dry and wet season respectively. USEPA's receptor model, UNMIX, was used to quantify the composition and contribution of LAR constituents. The model predicted quite well with a minimum Signal to Noise ratio (S/N) of 2.71 and 2.162 and R-2 of 0.91 and 0.880.8 for the dry and wet season respectively. The UNMIX model effectively predicted the water quality source composition with a model predicted to measured ratio (P:M) of 1.04 and 1.16 during the dry season and wet season with an average percentage error of 1.38 % and 17.13 % respectively. LAR water quality management approach incorporating all the three pollution sources could be feasible.
机译:小阿卡基河(LAR)是埃塞俄比亚的重大污染城市河流之一。进行了双月性物理化学和重金属水质分析,旨在评估22个蒙特站在干燥和潮湿季节污染的时空特征和量化来源。因此,实验室分析结果表明,大多数偏离国家和国际指南限额和河流的成分在中下部和下游部门受到严重污染。因子分析(FA)用于定性确定有助于污染的可能源,其中确定了三种因素,以确定潮湿和旱季期间的污染水平分别解释总差异的79.26%和79.47%。农业和城市径流(非点污染源),工业和国内废物是三种主要因素,有助于污染。另一方面,在LAR的重金属污染源主要由工业释放占主导地位,而车库和汽车漏油的城市冲刷是其他可能的来源。聚类分析分别在干湿季节分别将所有22个监测站分组为四个和三个簇。使用PA的受体模型,Unmix用于量化LAR成分的组成和贡献。该模型预测到2.71和2.16& 2和R-2的最小信号与2.71和2.16& 0.91和0.88& 0.8分别为干燥和湿季。本发明模型有效地预测了在干燥季节和湿季期间预测到1.04和1.16的测量比(P:M)的模型的水质源组合物分别为1.38%误差为1.38%和17.13%。纳入所有三种污染源的水质管理方法可能是可行的。

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