Microplastics in environmental compartments are a topic of serious concern. Time-consuming processes and analytical methods hamper not only the understanding of occurance and fate of microplastics, but also the derivation of regulatory actions to monitor and minimise inputs in the environment. Therefore, the establishment of a fast, reliable, robust and cost-efficient method for environmental monitoring is required. Most of the common used methods do not fit all requirements. They are highly time-consuming, require high investments or may not give chemical confirmation of the polymer.Here we want to present an approach for microplastic identification and quantification by a combination of separation and differential scanning calorimetry. In the present work, experimental data sets for the determination of LOQ for semi-crystalline and amorphous polymers as well as mixtures of polymers in an inert mineral matrix were generated. These data sets were evaluated by different regression methods. In addition to the regression according to DIN 32645, the two-factor regression was also included. The result shows that the two-parameter regression enables a clear identification and robust quantification. The LOQ of the overall process is thereby dependent on the choice of separation method. The method was applied to investigate sediment samples from the entire course of the Elbe River. These examples can be used to illustrate the influence of the separation method on the LOQ, but also the performance and limitations of the method.

Identification and Quantification of Microplastic in Environmental Samples by a Combinded Method of Separation and Differential Scanning Calorimetry (confex.com)