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Multi-elemental compound-specific isotope analysis of pesticides for source identification and monitoring of degradation in soil: a review
Environmental Chemistry Letters ( IF 15.7 ) Pub Date : 2022-07-28 , DOI: 10.1007/s10311-022-01489-8
Patrick Höhener , Delphine Guers , Laure Malleret , Ouassim Boukaroum , Fabrice Martin-Laurent , Jérémy Masbou , Sylvain Payraudeau , Gwenaël Imfeld

The transfer of pesticides from agricultural soils to food and drinking water is a major health issue. There are actually few robust methods to identify, characterize and quantify the dissipation of pesticides in complex media such as soils, waters and sediments. Here, we review multi-elemental compound-specific isotope analysis to study sources and transformations of pesticides in agricultural soils. First, we discuss advanced extraction and purification techniques for pesticides in soils. Then, analytical techniques for reliable measurements of the stable isotope composition of the pesticides are presented. We report a unique dataset of 547 isotopic compositions of 71 active molecules produced by various pesticide manufacturers, for the following isotopes: 13C, 15N, 37Cl, and 2H. We also report 270 isotope fractionation values for 33 compounds, which might help to elucidate the mechanisms of pesticide transformation by biodegradation, photodegradation and other abiotic processes. Compounds include legacy pesticides such as atrazine, lindane, dichlorodiphenyltrichloroethane, chlordecone and organophosphorus compounds. Transformation processes may be identified and quantified using the Rayleigh concept for isotope fractionation during reaction.



中文翻译:

农药多元素化合物特异性同位素分析用于土壤降解的来源识别和监测:综述

农药从农业土壤转移到食物和饮用水是一个重大的健康问题。实际上,几乎没有可靠的方法来识别、表征和量化农药在土壤、水和沉积物等复杂介质中的消散。在这里,我们回顾了多元素化合物特异性同位素分析,以研究农业土壤中农药的来源和转化。首先,我们讨论土壤中农药的先进提取和纯化技术。然后,介绍了可靠测量农药稳定同位素组成的分析技术。我们报告了由不同农药制造商生产的 71 种活性分子的 547 种同位素组成的独特数据集,用于以下同位素:13 C、15 N、37Cl 和2 H。我们还报告了 33 种化合物的 270 个同位素分馏值,这可能有助于阐明农药通过生物降解、光降解和其他非生物过程转化的机制。化合物包括传统农药,例如阿特拉津、林丹、二氯二苯基三氯乙烷、十氯酮和有机磷化合物。可以使用反应期间同位素分馏的瑞利概念来识别和量化转化过程。

更新日期:2022-07-28
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