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A New Chemometric Approach for Automatic Identification of Microplastics from Environmental Compartments Based on FT-IR Spectroscopy
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Researchers developed a new chemometric approach for automatic identification of microplastics from environmental samples, designed to handle the challenges of biofilm contamination and surface aging that typically impede standard spectroscopic characterisation methods.
One key step studying interactions of microplastics with our ecological system is to identify plastics within environmental samples. Aging processes and surface contamination especially with biofilms impede this characterization. A complex and time-consuming cleaning procedure is a common solution for this problem. However, it implies an artificial change of sample composition with a risk of losing important information or even damaging microplastic particles. In the present work, we introduce a new chemometric approach to identify heavily weathered and contaminated microplastics without any cleaning. The main idea of this concept is based on an automated curve fitting of most relevant vibrational bands to calculate a highly characteristic fingerprint that contains all vibrational band area ratios. This new data set will be used to estimate the similarity of samples and reference standards for identification. A total of 300 individual naturally weathered plastic particles were measured with Fourier transformation infrared spectroscopy in attenuated total reflection mode (FT-IR ATR) and identified successfully with the new method. To that end, all samples were compared with a selection of common reference plastics and bio polymers. As it turns out, the accuracy of identification rises significantly from 76% by means of conventional library searching algorithms to 96% by identifying microplastics with our new method. Therefore, the new approach can be a useful tool to compare and describe similarities of FT-IR spectra of microplastics, which may improve further research studies on this topic.
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