Optimized microplastic analysis based on size fractionation, density separation and μ-FTIR

Abstract

Microplastic particles have been recognized as global hazardous pollutants in the last few decades pointing to the importance of analyzing and monitoring microplastics, especially in soils and sediments. This study focused on a multi-step approach for microplastic analysis combining grain size fractionation, density separation and identification by μ-FTIR-spectroscopy. Eight widely used polymers (polyethylene (PE), polypropylene (PP), polyvinylchloride (PVC), polystyrol (PS), polyethylenterephthalate (PET), polymethylmethacrylate (PMMA), polyurethane (PU) and polyamide (PA)) were fractionated into four groups of grain sizes (0.1-5 mm). Thereafter, sea sand was spiked with these particles to test a ZnCl2-based density separation for the polymer types and the various grain sizes. The obtained recovery rates were close to 100% showing that ZnCl2-based density separation is suitable to separate the polymer particles from a sandy matrix. This approach was extended on three further environmental matrices and recovery rates for two of them (sandy-silty and fine-grained sediment) also provided reliable values (94-106%). Lastly, the developed multi-step approach was verified by analyzing an environmental sample (sediment from river Tiranë, Albania) characterized by smaller grain size and moderate organic matter content. Identification of two polymer types in different grain size classes verified the suitability of the developed approach for microplastic analyses on particulate matter such as soils and sediments.