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首页> 外文期刊>The Science of the Total Environment >Comprehensive two-dimensional gas-chromatography-based property estimation to assess the fate and behavior of complex mixtures: A case study of vehicle engine oil
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Comprehensive two-dimensional gas-chromatography-based property estimation to assess the fate and behavior of complex mixtures: A case study of vehicle engine oil

机译：基于二维气相色谱的综合性能评估，可评估复杂混合物的命运和行为：以汽车机油为例

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A method was developed to estimate the properties and assess the potential environmental risk of analytes in a complex mixture by comprehensive two-dimensional gas chromatography (GC x GC). A GC x GC-based estimation model was calibrated for 12 physicochemical properties that were relevant to the environment or to biological organisms, including human beings. Vehicle engine oil that had been contaminated by numerous compounds during its use was investigated as a case study to which the GC x GC model could be applied. Engine-oil samples were collected from a vehicle at intervals over a distance of 11407 km. The carbon and nitrogen contents in the oil remained unchanged at 83%-84% and 2%-5%, respectively, during the run; however, in excess of 100 compounds were present in the oil upon completion of the run. Post analyses of the studied mixture samples were performed with the developed GC x GC model, which links mass spectral information for structural identification. The GC x GC model allows us to classify the detected analytes in complex mixtures in terms of their properties, such as their aquatic bioaccumulation potential. The application of the model showed that the analyzed engine oil contained in excess of 100 compounds that could accumulate in aquatic biota and reach the arctic via long-range transport, which suggests that the components in the complex mixture of engine oil could pose a risk. The newly developed model that was derived in this study shows great potential for use in the mixture assessment. (C) 2019 Elsevier B.V. All rights reserved.
机译：通过全面的二维气相色谱（GC x GC），开发了一种方法来评估性质并评估复杂混合物中分析物的潜在环境风险。针对与环境或与生物（包括人类）相关的12种物理化学特性，对基于GC x GC的估算模型进行了校准。作为案例研究，对在使用过程中被多种化合物污染的汽车发动机油进行了研究，可以将其应用于GC x GC模型。从汽车上以11407 km的间隔每隔一段时间收集机油样品。在运行过程中，油中的碳和氮含量分别保持在83％-84％和2％-5％不变。但是，运行完成后，油中存在超过100种化合物。使用已开发的GC x GC模型对研究的混合物样品进行后分析，该模型将质谱信息链接在一起以进行结构鉴定。 GC x GC模型使我们能够根据其性质（例如其水生生物蓄积潜力）对复杂混合物中检测到的分析物进行分类。该模型的应用表明，所分析的机油中含有超过100种可能在水生生物区积累并通过远程运输到达北极的化合物，这表明机油的复杂混合物中的成分可能构成危险。在这项研究中得出的新开发的模型显示出在混合物评估中使用的巨大潜力。 （C）2019 Elsevier B.V.保留所有权利。

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