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Discriminatory classification of natural and anthropogenic waters in two UK estuaries

机译:英国两个河口的自然水和人为水的歧视性分类

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The ability to distinguish water inputs from both natural and anthropogenic sources was investigated in the complex environment of an urban estuary (Tyne) and a relatively pristine estuary (Tweed). We used a data set from a total of 11 estuarine transects, comprising measurements of bulk dissolved organic matter (dissolved organic carbon and nitrogen), dissolved nitrogen (total dissolved nitrogen, ammonium, nitrate+nitrite and dissolved organic nitrogen), optical absorbance measurements (a(350), S290-350) and fluorescence excitation emission matrix measurements (fluorophores A, H, B and T intensity and A and H emission wavelength maxima). In order to investigate trends within the numerous parameters measured, multivariate statistics were employed. Principal components analyses showed 63.4% of the variability in the total data set can be explained by two sets of components and 74.9% of the variability by the spectrophotometric measurements alone. In both analyses the first component correlated to the mixing of terrestrial and marine waters and the second component was correlated to sources of pollution such as domestic sewage. Within the data set, river flow and terrestrially derived DOM were significantly correlated, and situations with high river input showed an increase in terrestrial signature in the estuary. Discriminant analyses were also carried out and indicated that 59.8% (total data set) and 53.3% (solely spectrophotometric data) of the samples can be correctly classified into their respective groups (water categories) assigned on the basis of salinity and sampling location. Overall the results clearly show the potential of spectrophotometric techniques to discriminate distinct water categories with different DOM characteristics. In particular, measurement of the fluorophore H emission maxima, the spectral slope parameter, S290-350, and fluorophores T and B intensity enabled discrimination of DOM from riverine, estuarine, marine, and sewage affected water categories. The results presented here indicate the ability of spectrophotometric data alone to distinguish between marine, anthropogenic and terrestrial DOM and distinguish terrestrial DOM from different catchments (Tyne vs. Tweed). With current advances in the in-situ deployment of absorbance and fluorescence spectroscopy it is anticipated that multivariate statistics will gain importance as a cost effective, powerful and diagnostic approach to assessing the distributions of water types and their associated DOM characteristics and fluxes at the land-ocean interface. (c) 2006 Elsevier B.V All rights reserved.
机译:在城市河口(泰恩河)和相对原始河口(特威德河)的复杂环境中,研究了区分水源与自然源和人为源的能力。我们使用了总共​​11个河口样线的数据集,包括大块溶解有机物(溶解的有机碳和氮),溶解氮(溶解的总氮,铵,硝酸盐+亚硝酸盐和溶解的有机氮)的测量值,光吸收率测量值( a(350),S290-350)和荧光激发发射矩阵测量(荧光团A,H,B和T强度以及A和H发射波长最大值)。为了调查众多测量参数内的趋势,采用了多元统计。主成分分析表明,总数据集中63.4%的可变性可以由两组成分解释,而仅通过分光光度法测量可以解释74.9%的可变性。在这两项分析中,第一个成分与陆地和海水的混合有关,第二个成分与污染源(如生活污水)有关。在数据集内,河流流量和陆源DOM显着相关,河水输入量高的情况表明河口内陆标增加。还进行了判别分析,结果表明,根据盐度和采样位置,可以正确地将样品的59.8%(总数据集)和53.3%(单光度法数据)分类到各自的组(水类别)中。总体而言,结果清楚地表明了分光光度技术识别具有不同DOM特性的不同水类别的潜力。特别是,通过测量荧光团H的最大值,光谱斜率参数S290-350以及荧光团T和B的强度,可以区分DOM与受河流,河口,海洋和污水影响的水类别。此处显示的结果表明,仅使用分光光度数据就可以区分海洋,人为和陆地DOM,以及区分来自不同集水区的陆地DOM(泰恩河与特威德河)。随着吸收剂和荧光光谱原位部署的最新进展,预计多元统计将作为一种经济有效,功能强大且具有诊断性的方法来评估陆地上水的类型及其相关的DOM特性和通量的分布,将变得越来越重要。海洋接口。 (c)2006 Elsevier B.V保留所有权利。

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