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Nitrate source identification in groundwater of multiple land-use areas by combining isotopes and multivariate statistical analysis: A case study of Asopos basin (Central Greece)

机译:同位素和多元统计分析相结合的多种土地利用区域地下水硝酸盐源识别-以阿苏波斯盆地为例(希腊中部)

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摘要

Nitrate (NO_3) is one of the most common contaminants in aquatic environments and groundwater. Nitrate concentrations and environmental isotope data (δ~(15)N-NO_3 and δ~(18)O-NO_3) from groundwater of Asopos basin, which has different land-use types, i.e., a large number of industries (e.g., textile, metal processing, food, fertilizers, paint), urban and agricultural areas and livestock breeding facilities, were analyzed to identify the nitrate sources of water contamination and N-biogeochemical transformations. A Bayesian isotope mixing model (S1AR) and multivariate statistical analysis of hydrochemical data were used to estimate the proportional contribution of different NO_3 sources and to identify the dominant factors controlling the nitrate content of the groundwater in the region. The comparison of SIAR and Principal Component Analysis showed that wastes originating from urban and industrial zones of the basin are mainly responsible for nitrate contamination of groundwater in these areas. Agricultural fertilizers and manure likely contribute to groundwater contamination away from urban fabric and industrial land-use areas. Soil contribution to nitrate contamination due to organic matter is higher in the south-western part of the area far from the industries and the urban settlements. The present study aims to highlight the use of environmental isotopes combined with multivariate statistical analysis in locating sources of nitrate contamination in groundwater leading to a more effective planning of environmental measures and remediation strategies in river basins and water bodies as defined by the European Water Frame Directive (Directive 2000/60/EC).
机译:硝酸盐(NO_3)是水生环境和地下水中最常见的污染物之一。来自阿苏波斯盆地地下水的硝酸盐浓度和环境同位素数据(δ〜(15)N-NO_3和δ〜(18)O-NO_3),具有不同的土地利用类型,即许多工业(例如纺织业) ,金属加工,食品,化肥,油漆),城市和农业地区以及牲畜饲养设施进行了分析,以确定水污染和N-生物地球化学转化的硝酸盐来源。使用贝叶斯同位素混合模型(S1AR)和水化学数据的多元统计分析来估计不同NO_3来源的比例贡献,并确定控制该地区地下水硝酸盐含量的主要因素。 SIAR与主成分分析的比较表明,流域城市和工业区产生的废物主要是这些地区地下水硝酸盐污染的原因。农业肥料和肥料可能会导致远离城市结构和工业用地的地下水污染。在该地区的西南部,远离工业和城市居民区的土壤对有机物引起的硝酸盐污染的贡献较高。本研究旨在强调使用环境同位素与多元统计分析相结合来确定地下水中硝酸盐污染的来源,从而根据欧洲水框架指令的要求,对流域和水体的环境措施和补救策略进行更有效的规划(指令2000/60 / EC)。

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