Lola Rabinovitch, Genesis Saturos, Paige McCallum, Honoria Kwok, Jeffrey Yan, Taylor Filewood, Robert Cody, Pamela Brunswick, Dayue Shang
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引用次数: 0
Abstract
Oil spills are widespread and can cause devastating environmental consequences. Rapid oil identification is critical to find the origin of the spill, monitor the environment, and lead to informed mitigation measures. The current standard methods in oil spill identification are precise and reliable, but require extensive sample preparation, long instrument runs, and time-consuming data processing. Direct analysis in real time time-of-flight mass spectrometry (DART-ToF MS) has been employed to screen for spilled petroleum oils, with results obtained in mere hours. The present study introduced an innovative, simple, and fast oil sampling method using hydrophobic filter paper and demonstrated its compatibility with DART-ToF MS analysis. Motor oils, jet fuels, marine diesels, crude oils, intermediate fuel oils, heavy fuel oils, and diluted bitumen were collected using the filter paper sampling method. Classification models were constructed from the spectral data by heat map inspection followed by principal component analysis (PCA) and discriminant analysis of principal components (DAPC). Oil slicks and weathered oil slicks were prepared from five oil types, and samples from each slick were collected using filter paper. The filter paper technique allowed for effective oil sampling and data acquisition by DART-ToF MS for diluted source oils, oil slicks and weathered oil slicks. Classification via the constructed DAPC models indicated that the DART-ToF MS instrument in tandem with filter paper sampling and multivariate statistics can accurately identify common oil types, with significant improvement of sample collection and turnaround time. The promising classification results, simple sample collection, and rapid data analysis illustrate the potential use of hydrophobic filter paper and DART-ToF MS as tools in managing large scale oil spill emergency situations.
油类泄漏非常普遍,可能会对环境造成破坏性后果。快速识别油类对于找到泄漏源、监控环境和采取明智的缓解措施至关重要。目前油类泄漏鉴定的标准方法精确可靠,但需要大量的样品制备、长时间的仪器运行和耗时的数据处理。实时飞行时间质谱直接分析法(DART-ToF MS)已被用于筛选泄漏的石油,只需数小时即可获得结果。本研究采用疏水滤纸引入了一种创新、简单、快速的油类取样方法,并证明了该方法与 DART-ToF MS 分析的兼容性。使用滤纸取样法收集了机油、喷气燃料、船用柴油、原油、中间燃料油、重燃料油和稀释沥青。通过热图检测从光谱数据中构建分类模型,然后进行主成分分析(PCA)和主成分判别分析(DAPC)。从五种油类中制备了浮油和风化浮油,并使用滤纸收集了每种浮油的样本。使用滤纸技术可以有效地进行油类取样,并通过 DART-ToF MS 采集稀释源油、浮油和风化浮油的数据。通过构建的 DAPC 模型进行的分类表明,DART-ToF MS 仪器与滤纸取样和多元统计相结合,可以准确识别常见的油类类型,并显著改善样本采集和周转时间。这些可喜的分类结果、简单的样本采集和快速的数据分析说明,疏水滤纸和 DART-ToF MS 可用作管理大规模溢油紧急情况的工具。