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Determination of atmospherically deposited microplastics in moss: Method development and performance evaluation
Summary
German researchers developed a new method called µPEEL to extract microplastics from moss samples for atmospheric deposition monitoring, enabling both particle-count (Raman) and mass-based (thermal desorption GC-MS) analysis while avoiding harsh chemicals. The method outperformed conventional Fenton reagent digestion on environmental greenness and data quality metrics. Mosses are already used to monitor atmospheric heavy metals and nitrogen, and this work expands their utility to tracking airborne microplastic fallout.
The investigation of atmospheric microplastic pollution is a rising topic within microplastic research. However, sampling strategies concerning atmospheric microplastics are not standardized yet and strongly depend on the scientific objectives investigated. A few research groups are currently focused on determining atmospherically deposited microplastics in moss, as it can be a biomonitoring system for other atmospheric pollutants such as heavy metals, nitrogen, and persistent organic components. In this context, and for atmospheric microplastics in general, almost all examinations focus on determining microplastic numbers and shapes, while polymer masses are barely investigated. However, particle- and mass-based information are needed to assess the fate of atmospherically transported microplastics in the environment. For this purpose, this study shows the development and evaluation of a new sample preparation method for determining microplastics in moss for both analytical approaches using thermal extraction desorption-gas chromatography-mass spectrometry (TED-GC-MS) and Raman microspectroscopy (µRaman). Further, this newly developed microplastics/moss separation method (µPEEL) was compared to oxidative digestion using Fenton's reagent, usually used as a sample preparation method for organic-rich samples and moss. The method comparison was performed concerning green analytical chemistry (GAC) and its respective method functionality. The greenness was assessed using the software tool AGREEprep, which covers ten comprehensive aspects of GAC. Both methods’ functionality was assessed regarding observable matrix interferences and the data quality achieved. It is demonstrated that µPEEL benefits GAC and method functionality since harmful chemicals can be avoided, matrix interferences can be minimized, and the separation quality is increased.
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