Py-GC/MS method development and application for the identification of microplastics from seafood

International audiencePlastics 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 degrees C, a split ratio of 5 and 300 degrees 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 mug. 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 mu-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