ANSES, Laboratoire de Sécurité des Aliments, Boulevard du Bassin Napoléon, 62200, Boulogne, France.
UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, CNRS, University of Littoral Côte d'Opale, University of Lille, 32 Avenue Foch, 62930, Wimereux, France.
Anal Bioanal Chem. 2018 Oct;410(25):6663-6676. doi: 10.1007/s00216-018-1279-0. Epub 2018 Jul 27.
Plastics are found to be major debris composing marine litter; microplastics (MP, < 5 mm) are found in all marine compartments. The amount of MPs tends to increase with decreasing size leading to a potential misidentification when only visual identification is performed. These last years, pyrolysis coupled with gas chromatography/mass spectrometry (Py-GC/MS) has been used to get information on the composition of polymers with some applications on MP identification. The purpose of this work was to optimize and then validate a Py-GC/MS method, determine limit of detection (LOD) for eight common polymers, and apply this method on environmental MP. Optimization on multiple GC parameters was carried out using polyethylene (PE) and polystyrene (PS) microspheres. The optimized Py-GC/MS method require a pyrolysis temperature of 700 °C, a split ratio of 5 and 300 °C as injector temperature. Performance assessment was accomplished by performing repeatability and intermediate precision tests and calculating limit of detection (LOD) for common polymers. LODs were all below 1 μg. For performance assessment, identification remains accurate despite a decrease in signal over time. A comparison between identifications performed with Raman micro spectroscopy and with Py-GC/MS was assessed. Finally, the optimized method was applied to environmental samples, including plastics isolated from sea water surface, beach sediments, and organisms collected in the marine environment. The present method is complementary to μ-Raman spectroscopy as Py-GC/MS identified pigment containing particles as plastic. Moreover, some fibers and all particles from sediment and sea surface were identified as plastic. Graphical abstract ᅟ.
塑料是海洋垃圾的主要组成部分;微塑料(MP,<5 毫米)存在于所有海洋环境中。随着尺寸的减小,MP 的数量趋于增加,这导致仅进行目视识别时存在潜在的误识别。近年来,热解-气相色谱/质谱联用(Py-GC/MS)已被用于获取聚合物组成的信息,并在 MP 识别方面得到了一些应用。本工作旨在优化并验证一种 Py-GC/MS 方法,确定八种常见聚合物的检测限(LOD),并将该方法应用于环境 MP。使用聚乙烯(PE)和聚苯乙烯(PS)微球对多个 GC 参数进行了优化。优化后的 Py-GC/MS 方法需要 700°C 的热解温度、5 的分流比和 300°C 的进样口温度。通过进行重复性和中间精密度测试,并计算常见聚合物的检测限(LOD)来完成性能评估。LOD 均低于 1μg。对于性能评估,尽管信号随时间降低,但识别仍然准确。评估了与拉曼微光谱法进行的识别之间的比较。最后,将优化后的方法应用于环境样品,包括从海水表面、海滩沉积物和海洋环境中收集的塑料。该方法与 μ-Raman 光谱法互补,因为 Py-GC/MS 将含有颜料的颗粒识别为塑料。此外,沉积物和海表面的一些纤维和所有颗粒均被鉴定为塑料。