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多元素同位素示踪有机物降解的机理研究方法。

Mechanistic approach to multi-element isotope modeling of organic contaminant degradation.

机构信息

Center for Applied Geosciences, University of Tübingen, Sigwartstrasse 10, D-72076 Tübingen, Germany.

出版信息

Chemosphere. 2014 Jan;95:131-9. doi: 10.1016/j.chemosphere.2013.08.050. Epub 2013 Sep 12.

Abstract

We propose a multi-element isotope modeling approach to simultaneously predict the evolution of different isotopes during the transformation of organic contaminants. The isotopic trends of different elements are explicitly simulated by tracking position-specific isotopologues that contain the isotopes located at fractionating positions. Our approach is self-consistent and provides a mechanistic description of different degradation pathways that accounts for the influence of both primary and secondary isotope effects during contaminant degradation. The method is particularly suited to quantitatively describe the isotopic evolution of relatively large organic contaminant molecules. For such compounds, an integrated approach, simultaneously considering all possible isotopologues, would be impractical due to the large number of isotopologues. We apply the proposed modeling approach to the degradation of toluene, methyl tert-butyl ether (MTBE) and nitrobenzene observed in previous experimental studies. Our model successfully predicts the multi-element isotope data (both 2D and 3D), and accurately captures the distinct trends observed for different reaction pathways. The proposed approach provides an improved and mechanistic methodology to interpret multi-element isotope data and to predict the extent of multi-element isotope fractionation that goes beyond commonly applied modeling descriptions and simplified methods based on the ratio between bulk enrichment factors or on linear regression in dual-isotope plots.

摘要

我们提出了一种多元素同位素模拟方法,以同时预测有机污染物转化过程中不同同位素的演变。通过跟踪位于分馏位置的同位素的位置特异性同位素异构体,明确模拟不同元素的同位素趋势。我们的方法是一致的,并提供了一种对不同降解途径的机械描述,该描述考虑了污染物降解过程中主要和次要同位素效应的影响。该方法特别适合定量描述相对较大的有机污染物分子的同位素演变。对于此类化合物,由于同位素异构体的数量众多,同时考虑所有可能的同位素异构体的综合方法是不切实际的。我们将提出的建模方法应用于先前实验研究中观察到的甲苯、甲基叔丁基醚(MTBE)和硝基苯的降解。我们的模型成功预测了多元素同位素数据(二维和三维),并准确捕捉到不同反应途径观察到的不同趋势。该方法提供了一种改进的和基于机制的方法来解释多元素同位素数据,并预测多元素同位素分馏的程度,超越了常用的建模描述和基于整体富集因子比或双同位素图中的线性回归的简化方法。

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