Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba, Ibaraki 305-8569, Japan.
Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba, Ibaraki 305-8569, Japan.
Sci Total Environ. 2019 Jun 15;669:739-745. doi: 10.1016/j.scitotenv.2019.03.157. Epub 2019 Mar 12.
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 × GC). A GC × 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 × 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 × GC model, which links mass spectral information for structural identification. The GC × 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.
建立了一种通过全二维气相色谱（GC×GC）综合评估复杂混合物中分析物特性和潜在环境风险的方法。该方法针对与环境或生物有机体（包括人类）相关的 12 种理化性质，建立了 GC×GC 估算模型并进行了校准。将使用过程中被多种化合物污染的车辆发动机油作为案例研究，应用 GC×GC 模型进行了评估。从行驶距离为 11407km 的车辆上每隔一定距离收集一次发动机油样品。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；然而，在运行结束时，油中存在超过 100 种化合物。使用开发的 GC×GC 模型对研究的混合样品进行了后分析，该模型将质谱信息链接起来进行结构鉴定。GC×GC 模型允许我们根据其性质（如水生生物蓄积潜力）对复杂混合物中的检测到的分析物进行分类。模型的应用表明，分析的发动机油中含有超过 100 种化合物，这些化合物可能在水生生物中积累，并通过远程传输到达北极，这表明发动机油中复杂混合物的成分可能存在风险。本研究中开发的新模型在混合物评估中具有很大的应用潜力。
