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Fingerprinting Oils in Water via Their Dissolved VOC Pattern Using Mid-Infrared Sensors

机译:使用中红外传感器通过溶解的VOC模式对水中的油进行指纹识别

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摘要

An infrared attenuated total reflection (IR-ATR) method for detecting, differentiating, and quantifying hydrocarbons dissolved in water relevant for oil spills by evaluating the "fingerprint" of the volatile organic compounds (VOCs) associated with individual oil types in the mid-infrared spectral range (i.e., 800-600 cm~(-1)) is presented. In this spectral regime, these hydrocarbons provide distinctive absorption features, which may be used to identify specific hydrocarbon patterns that are characteristic for different crude and refined oils. For analyzing the "VOC fingerprint" resulting from various oil samples, aqueous solutions containing the dissolved hydrocarbons from different crude oils (i.e., types "Barrow", "Goodwyn", and "Saladin") and refined oils (i.e., "Petrol" and "Diesel") were analyzed using a ZnSe ATR waveguide as the optical sensing element. To minimize interferences from the surrounding water matrix and for amplifying the VOC signatures by enrichment, a thin layer of poly(ethylene-co-propylene) was coated onto the ATR waveguide surface, thereby enabling the establishment of suitable calibration functions for the quantification of characteristic concentration patterns of the detected VOCs. Multivariate data analysis was then used for a prelininary classification of various oil-types via their VOC patterns.
机译:红外衰减全反射(IR-ATR)方法,通过评估与中红外中各个油类相关的挥发性有机化合物(VOC)的“指纹”,来检测,区分和量化与溢油有关的水中溶解的碳氢化合物。给出了光谱范围(即800-600 cm〜(-1))。在此光谱范围内,这些碳氢化合物提供了独特的吸收特征,可用于识别特定的碳氢化合物模式,这些模式是不同原油和精炼油的特征。为了分析各种油样产生的“ VOC指纹”,需要使用含有来自不同原油(即“ Barrow”,“ Goodwyn”和“ Saladin”类型)和精制油(即“ Petrol”和“使用ZnSe ATR波导作为光学传感元件来分析“ Diesel”。为了最大程度地减少来自周围水基质的干扰并通过富集来放大VOC信号,在ATR波导表面上涂覆了一层薄薄的聚乙烯(乙烯-共-丙烯),从而可以建立合适的校准功能来量化特征检测到的挥发性有机化合物的浓度模式。然后将多元数据分析通过其VOC模式用于各种油类的初步分类。

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