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Developing and testing a workflow to identify microplastics using near infrared hyperspectral imaging
Summary
Researchers developed a near-infrared hyperspectral imaging workflow with an open spectral database to rapidly identify microplastics by polymer type, achieving over 88% accuracy for polypropylene, polyethylene, PET, and polystyrene particles larger than 500 micrometers.
The analysis of microplastics (MP) is time-consuming which limits our capacity to monitor and mitigate plastic pollution. Here, near infrared (1000-2500 nm) hyperspectral imaging (NIR-HSI) offers an advantage over other spectroscopic techniques because it can rapidly image large areas relative to other systems. While NIR-HSI can successfully detect MP, accuracy and limitations of the method have not been fully explored. In addition, lack of open databases and analysis pipelines increases the barrier to use. In this work, we developed a spectral database containing preproduction pellets, consumer products and marine plastic debris, imaged using a Hyspex SWIR-320me imager. A SIMCA model identified four polymer types: polypropylene, polyethylene, polyethylene terephthalate and polystyrene (PP, PE, PET, PS) to identify MP in hyperspectral images. We determined the accuracy of size estimates for PS MP > 1000 μm using fluorescence microscopy and tested the impact of photooxidation on detection of plastics by NIR-HSI (PE, PP, PS, PET) and subsequent prediction by the SIMCA model. The model performed well across all polymers as shown by high specificity, sensitivity, and accuracy for internal cross validation (>88%), and sensitivity >80% for external validation. PS MP < 500 μm Feret diameter were not consistently detected by NIR-HSI when compared with fluorescence microscopy. However, estimates for Feret diameter were consistent for PS MP > 1000 μm. Analysis by NIR-HSI showed no spectral changes and SIMCA showed no decreased precision with increased photooxidation across polymer types. Recall varied across polymer type and photooxidation stage with no clear trends. This study shows that NIR-HSI is a rapid method which can accurately identify MP of the four most relevant polymer types, precluding the need to analyze particles one at a time. NIR-HSI can be a key technology for environmental monitoring of plastic debris where rapid analysis of multiple samples is required.
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