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Multivariate classification of Raman spectra from synthetic polymers – an approach for the improved detection of microplastics
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Multivariate classification of Raman spectral data was applied to identify common synthetic polymers, advancing the use of Raman spectroscopy as a tool for detecting and quantifying microplastics in environmental samples. The approach addresses limitations of traditional infrared spectroscopy by enabling analysis of wet samples, though fluorescence interference remains a challenge.
The increasing pollution of terrestrial and aquatic ecosystems with plastic debris, which leads to the accumulation of microscopic plastic particles of still unknown fate, is an upcoming problem of our time. In order to monitor the degree of contamination and to understand the underlying processes of degradation and internalization of plastic debris, analytical methods are urgently needed, which help to identify and quantify microplastics. Currently, expensive collected and purified materials enriched on filters are investigated by (micro) infrared spectroscopy (FTIR). Few studies using micro-Raman spectroscopy have been published as well. In contrast to FTIR, Raman spectroscopy can handle wet samples, but it suffers from interference of fluorescent materials. Both micro-FTIR- and micro-Raman, always include time consuming scanning and mapping procedures followed by the manual inspection and measurement of selected particles.
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