Gomes, Uttam Dominic2022-09-262022-09-262022-07https://hdl.handle.net/11299/241698University of Minnesota M.S. thesis. 2022. Major: Chemistry. Advisor: Elizabeth Austin-Minor. 1 computer file (PDF); 95 pages.The demand for plastic items in the everyday life of people and the subsequent hazards to the environment are both rising rapidly. Notably, plastic particles in the micro form (< 5 mm) are being found incorporated within aquatic systems and the human food chain. To track the introduction, incorporation, and distribution of microplastic particles in aquatic systems, their characterization in terms of size, abundance, and polymer type are important. Although there are no universal methods to characterize microplastic, currently popular methods have critical limitations, including the extensive time needed for analysis and an inability to easily identify smaller microplastic particles. Therefore, we are exploring the use of Nile Red (NR) staining and Flow Cytometric (FCM) sorting to identify and isolate small microplastics from aqueous samples. During preliminary tests with known plastic polymers, samples were NR stained, FCM sorted, concentrated by centrifuge filtering, dried, and analyzed with pyrolysis gas chromatography mass spectrometry (pyGCMS) to determine their composition. Results show that polymer composition remained identifiable by pyGCMS after NR staining and FCM sorting. Centrifuge filtration of test particles in similar concentrations to those within our sorts showed an average recovery of >40% of the original plastic polymer mass.Based on these preliminary test results, we applied this method to small microplastic particles (5-45 μm) from Lake Superior surface water collected in August 2021. Concentrated particle samples were processed by oxidization and density separation to simplify matrix effects. Afterwards, samples were stained with NR prior to FCM sorting. Subsequently, sorted samples were concentrated by centrifuge filtration and drying prior to pyGCMS analysis. From these samples we obtained enough material for pyGCMS after approximately 2 hours of sorting. Analysis of Lake Superior particles indicates the presence of polystyrene, polypropylene, and polyethylene, although the mixture of polymers complicates the full identification of pyGCMS peaks.enThesis or Dissertation