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Development of Microplastic Identification using Raman Microspectrophotometry

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This study developed and refined Raman microspectrophotometry as an identification tool for microplastics, evaluating its accuracy for distinguishing different polymer types in environmental samples. Improved microplastic identification methods are critical for generating reliable and comparable data on environmental plastic contamination.

Study Type Environmental

Microplastics are microscopic particles that range from 0.1µm -  5mm that originate from a variety of sources such as larger plastics that degrade into smaller pieces, microbeads from beauty products, and the fibers from clothes that come off when washing them. Most microplastics end up in the oceans and freshwaters and has the possibility of persisting and affecting the aquatic ecosystem globally. Due to their minute size and unknown or altered composition, microplastics have been difficult to study and there is still no general method to determine their chemical identity. The most common technique involves the visual identification of the microplastics by microscopy. This technique can sometimes lead to misidentification due to the altered composition of the microplastic or the difficulty in differentiating plastics from natural particles. In this study, further verification of the microplastic composition is done using Raman Microspectrophotometry, which allows a direct measurement on the microplastic particles, to further identify their chemical composition and differentiate them from other organic or natural particles. Different variables on the Raman Microspectrophotometry such as laser power, laser wavelength, spectral integration time, and the number of co-additions are optimized to provide the best spectra for microplastic identification. This approach can help identify and quantify the microplastics present in the environment and will be applied to the samples from the North Saskatchewan River and the Arctic. Discipline: Chemistry Faculty Mentor: Dr. Matthew Ross

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