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Mixtures of co-occurring chemicals in freshwater systems across the continental US

机译:美国陆大陆淡水系统中共同发生化学品的混合物

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Trace chemicals are common in marine and freshwater ecosystems globally. It is recognized that in the environment, individual chemicals are rarely found in isolation. Insufficient work has examined which chemicals co-occur and which methods best identify these mixtures. Using an existing data set, we found evidence that simple correlation analysis is better at identifying mixtures of commonly co-occurring trace chemicals than more commonly used PCA methods. Moreover, simple correlation analysis, unlike PCA, can be used in cases with unbalanced designs and with data points below reportable limits. Application of this approach allowed identification of 10 groups of chemicals commonly found together in freshwaters of the continental US, representing common "chemical syndromes." Better identification of co-occurring chemical combinations could aid in our understanding of biological and ecological effects of aquatic contaminants. This research provides evidence of correlation analyses as a more effective method for identifying commonly co-occurring aquatic contaminants. We also examined the patterns of these mixtures with a dataset consisting of concentrations of 406 trace chemicals from 38 sample locations across the continental US. (C) 2020 Elsevier Ltd. All rights reserved.
机译:痕量化学品在全球海洋和淡水生态系统中常见。据认识到,在环境中,迅速分离地发现各种化学品。工作不足检查了哪些化学品以及最佳识别这些混合物的方法。使用现有数据集,我们发现证据表明,简单的相关性分析识别通常共同发生的痕量化学品的混合物比更常用的PCA方法更好。此外,与PCA不同,可以在具有不平衡设计的情况下使用的简单相关性分析,并在可报告限制以下数据点。这种方法的应用允许鉴定在美国大陆大陆的新鲜水域中常见的10组化学品,代表普通的“化学综合症”。更好地识别共同发生的化学组合可以帮助我们对水生污染物的生物和生态影响的理解。本研究提供了相关性分析作为鉴定常规共同发生的水生污染物的更有效方法。我们还将这些混合物的模式进行了与大陆大陆38个样本地点的406种痕量化学品组成的数据集。 (c)2020 elestvier有限公司保留所有权利。

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