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Application of multi-step approach for comprehensive identification of microplastic particles in diverse sediment samples
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Researchers developed a multi-step analytical approach to comprehensively identify and characterize microplastics in environmental samples, combining visual, spectroscopic, and thermal analysis. A systematic, multi-method approach is needed to capture the full diversity of microplastic types present in complex environmental matrices.
The tremendous increase of plastic production, its intensive usage in packaging, as transport material, and the insufficient management of plastic garbage have led to a rise in microplastic particles as an anthropogenic contaminant in our environment. To develop appropriate management and remediation strategies for this global pollution problem, reliable and consistent analytical procedures for measuring plastics in the complex matrices need to be designed. The applicability of an easy, robust and fast multi-step approach was tested on three sediment samples from riverine, beach and backwater areas of varying origin, grain size and organic matter content, and is reported here. The optimized method included grain size fractionation, density separation and μ-FTIR analyses. Identification was based on two complementary methods of μ -FTIR measurements, the Image mode for small microplastics (<1 mm) and the ATR method for bigger (1-5 mm) particles. The analyses revealed the identification of several polymers in various grain sizes at different pollution levels. Major findings are the dominance of PET particles and the highest frequency of microplastic particles in the midsize fraction of 100-500 μm. Generally, the method was able to reliably detect microplastic particles in several grain size fractions and down to very low contamination levels of approximately. ten particles per 50 g of sediments with different organic matter content and various grain size characteristics. Moreover, the presented multi-step approach represents a fast, easy and less cost-effective method as an alternative to more expensive and time-consuming methods.
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