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首页> 外文期刊>Geochemistry: exploration, environment, analysis >Quantitative source apportionment of groundwater pollution: a case study of alluvial fan groundwater in the Hun river region, NE China
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Quantitative source apportionment of groundwater pollution: a case study of alluvial fan groundwater in the Hun river region, NE China

机译:地下水污染的定量源分配 - 以南北河河地区发生冲积风扇地下水的案例研究

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摘要

Groundwater pollution is controlled by many anthropogenic processes, and source apportionment is particularly difficult in cases with multiple superimposed anthropogenic influences. Forty-three shallow groundwater samples in the Hun River alluvial fan were collected and 15 parameters comprising Ca2+, Mg2+, Fe2+, Mn2+, NH4+, NO3-, NO2-, F-, SO42-, PO43-,Cl-, COD, TDS, CN- and HCO3- were studied using principal component analysis (PCA) and factor analysis (FA), coupled with the absolute principal-component-score multiple-linear-regression (APCS-MLR) receptor model. The relationship among land-use types, hydrochemical composition and change of the groundwater quality from natural and anthropogenic sources was demonstrated. The results show that the four major potential pollution sources were water-rock interaction, agricultural fertilizer pollution, geological background and domestic and industrial wastewater; the contribution was 36.4%, 24.1%, 14.7% and 11.8%, respectively. The high-concentration areas were mainly located in the western and northwestern areas, especially in the downstream portion of the Hun River. Rapid economic development and the acceleration of urbanization led to an increase in industrial sewage effluent with complex and changeable composition. The variation of land-use type and evolution of the spatial distribution of the pollution sources in the groundwater show good consistency, which demonstrate that PCA/FA coupled with APCS-MLR is a versatile tool for comprehensive source apportionment of groundwater.
机译:地下水污染受许多人类过程控制,在多重叠加的人体发生影响的情况下,源分数特别困难。收集了匈河冲积风扇中的四十三个浅层地下水样本,15个参数包含Ca2 +,Mg2 +,Fe2 +,Mn2 +,NH4 +,No3-,No2-,F-,SO42-,PO43-,CL-,COD,TDS,使用主成分分析(PCA)和因子分析(FA)研究CN-和HCO3-与绝对主分量分数多指数(APCS-MLR)受体模型耦合。证实了土地使用类型,水化学组成和自然和人为源的地下水质量的变化的关系。结果表明,四大潜在污染源是水岩相互作用,农业肥料污染,地质背景和国内和工业废水;贡献分别为36.4%,24.1%,14.7%和11.8%。高浓度区域主要位于西北地区,特别是在浑河下游。经济快速发展和城市化的加速导致工业污水污水的增加,具有复杂和变化的组成。地下水中污染源的空间分布的土地使用类型和演化的变化显示出良好的一致性,这表明与APCS-MLR联系的PCA / FA是用于地下水综合源源分配的多功能工具。

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