Regression analysis for the determination of microplastics in sediments using differential scanning calorimetry

This research addresses the growing need for fast and cost-efficient methods for microplastic (MP) analysis. We present a thermo-analytical method that enables the identification and quantification of different polymer types in sediment and sand composite samples based on their phase transition behavior. Differential scanning calorimetry (DSC) was performed, and the results were evaluated by using different regression models. The melting and crystallization enthalpies or the change in heat capacity at the glass transition point were measured as regression analysis data. Ten milligrams of sea sand was spiked with 0.05 to 1.5 mg of microplastic particles (size: 100 to 200 µm) of the semi-crystalline polymers LD-PE, HD-PE, PP, PA6, and PET, and the amorphous polymers PS and PVC. The results showed that a two-factorial regression enabled the unambiguous identification and robust quantification of different polymer types. The limits of quantification were 0.13 to 0.33 mg and 0.40 to 1.84 mg per measurement for semi-crystalline and amorphous polymers, respectively. Moreover, DSC is robust with regard to natural organic matrices and allows the fast and non-destructive analysis of microplastic within the analytical limits. Hence, DSC could expand the range of analytical methods for microplastics and compete with perturbation-prone chemical analyses such as thermal extraction-desorption gas chromatography-mass spectrometry or spectroscopic methods. Further work should focus on potential changes in phase transition behavior in more complex matrices and the application of DSC for MP analysis in environmental samples.