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Combination of oil-based separation and differential scanning calorimetry towards a methodological setup for microplastic analysis in sediments
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Scientists developed a new lab method that uses oil to separate tiny plastic particles from sediment (like sand or soil from rivers and oceans), then uses heat-based testing to identify and measure them. This matters because tracking microplastics in the environment is a key step toward understanding how much of this pollution ends up in water, soil, and ultimately the food chain — and this simpler, more efficient method could make widespread environmental monitoring more realistic, with potential to eventually detect even smaller nanoplastic particles too.
Abstract Analyzing microplastics (MP) and nanoplastics (NP) in sediments remains challenging due to low particle concentrations and complex sample composition. We present an integrated workflow combining oil-based separation with differential scanning calorimetry (DSC) for the isolation and thermal quantification of MP from particulate environmental samples. While the present study focuses on micrometer-sized MP, the methodological principle of oil-based separation combined with DSC provides a scalable foundation for future extending monitoring toward NP. This dual perspective strengthens the relevance of the approach for future environmental analytics. The method enriches MP in an organic phase, facilitates substantial sediment removal, and yields a polymer-rich fraction suitable for DSC-based identification and quantification. Recovery experiments with four common polymers reveal that separation efficiency is primarily influenced by polymer-specific properties such as wettability and density, as well as particle size. Despite moderate recovery rates, the approach proved to be effective for isolating MP < 500 μm from sediment-rich matrices. Its operational simplicity, high matrix reduction, and compatibility with thermal analysis underscore its potential for routine environmental MP monitoring and offer a scalable foundation for future NP detection.
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