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Degradation degree analysis of environmental microplastics by micro FT-IR imaging technology
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Researchers used micro-FTIR spectral-image fusion to classify the degradation degree of polyethylene microplastics collected from coastal environments, achieving 97.1% classification accuracy and enabling estimation of environmental persistence time from spectral data.
The degradation potential of microplastics remains a critical issue for researching marine litter, and it is one of the most important factors that can be used for calculating the persistence time of microplastics in certain conditions. However, there are lack of standard or approved methods for estimating the ageing stage of environmental microplastics. In this study, the potential of spectral-image fusion strategy was investigated to analyze the degradation degree of polyethylene microplastics in natural exposure of coastline. The proposed spectral-image fusion linear model showed a significant ability to classify the degradation degree of environmental microplastics samples with the best accuracy of 97.1% as compared to two single-sensing information-based linear models (with one spectral wavelength of the carbonyl index at 1720 cm or three-channel components from LAB color-space). This is the first attempt to qualitatively measure the degradation degree of the naturally exposed microplastics based on spectral-image fusion model. The proposed fusion model based strategy is an effective tool for predicting the degradation degree of the field exposed microplastics.
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