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Evaluating the impact of digestion pre-treatments on microplastics using NIR spectroscopy
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Scientists tested a fast scanning technique (NIR spectroscopy) to detect microplastics after samples are chemically cleaned of organic material, a common prep step in microplastic testing. The method accurately identified plastic type, cleaning chemical used, and even particle size, suggesting it could make microplastic pollution monitoring quicker and more reliable, which matters since we're still learning how these particles affect human health.
ABSTRACT Microplastics represent the biggest proportion of plastic residues found in the environment. Their monitoring often requires the elimination of organic matrices through digestion treatments, as these matrices hinder their detection and identification. NIR spectroscopy is a rapid technique for microplastic analysis, however its application to chemically digested particles remain underexplored. The present study evaluates the capability of NIR spectroscopy to identify digested microplastics and to assess the impact of chemical digestion on NIR spectra. The feasibility of using single particle NIR spectroscopy to predict particle size was explored. To do so, polyethylene terephthalate (PET), polystyrene (PS), polypropylene (PP), and low-density polyethylene (LDPE) were digested with three different digestion protocols (65% HNO 3 , 10% KOH and 30% H 2 O 2 ). Partial Least Square Discriminant Analysis (PLS-DA) enabled accurate classification of both polymer type and digestion protocol, achieving sensitivities and specificities generally above 0.9. Variable importance in projection (VIP) analysis revealed digestion-induced spectral changes in NIR region. Complementary ATR-FTIR and SEM analysis confirmed chemical and morphological alterations across all four polymers. Furthermore, PLS regression model successfully predicted microplastic particle size, further demonstrating the versatility of NIR spectroscopy.
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