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Visual detection of microplastics using Raman spectroscopic imaging
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Researchers developed a visual detection method for microplastics using Raman spectroscopic imaging that generates pseudo-color maps to identify different polymer types. The technique successfully identified microplastics as small as 1 micrometer and could distinguish between different plastic compositions in environmental samples. The study suggests this imaging approach could serve as an efficient and accurate tool for routine microplastic monitoring.
As a new type of pollutant in the marine environment and terrestrial ecosystems, microplastics have attracted widespread attention. Assessing the ecological risk of microplastics relies on accurately detecting small-sized particles in the environment. Microplastics exhibit unique "fingerprint" characteristics in Raman spectroscopy, making them suitable for rapid identification. In this study, we achieved visualization of microplastics through pseudo-color images generated by Raman spectroscopy imaging. Pseudo-color imaging maps were generated by selecting characteristic peaks and the classical least-squares fitting method was used to visually represent the distribution of different microplastics. The study explored the potential of Raman spectroscopy and its mapping mode in distinguishing various types of mixed microplastics and demonstrated that this approach can identify microplastics in complex environmental samples. Specifically, a cloud-point extraction followed by membrane filtration method was successfully applied to identifying mixed-component microplastics. In summary, the category, quantity, location, and differentiation of microplastics can be accurately analyzed by Raman spectroscopy, which provides a basis for assessing their ecological risk.
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