Abstract
Microplastics and nanoplastics have secretly entered our daily lives but the extent of the problem is still unclear, as the characterisation is still a challenge, particularly for nanoplastics. Herein we test a blender that we use in our kitchen to make juice and we find that a significant amount of microplastics and nanoplastics (∼0.36–0.78 × 109 within 30 s) are released from the plastic container. We advance the characterisation of microplastics and nanoplastics using Raman imaging to generate a scanning spectrum matrix, akin to a hyperspectral matrix, which contains 900 spectra (30 × 30). By mapping these hundreds of spectra as images, with help of algorithms, we can directly visualise the microplastics and nanoplastics with an increased sensitivity from statistical point of view. Raman imaging has a main disadvantage of the imaging resolution, originating from the diffraction of the laser spot, which is proposed to be improved by shrinking the scanning pixel size, zooming in the scanning area to capture details of nanoplastics. Using image re-construction towards deconvolution, the nanoplastics can be effective characterised and the bumpy image of microplastics stemming from the signal variation can be subsequently smoothened to further increase the signal-noise ratio. Overall, the advancements on Raman imaging can provide a suitable approach to characterise microplastics and nanoplastics released in our daily lives, for which we should be cautious.
Original language | English |
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Article number | 131403 |
Pages (from-to) | 1-9 |
Number of pages | 9 |
Journal | Journal of Hazardous Materials |
Volume | 453 |
Early online date | 14 Apr 2023 |
DOIs | |
Publication status | Published - 5 Jul 2023 |
Externally published | Yes |
Bibliographical note
Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Blender
- Microplastic
- Nanoplastic
- Raman imaging
- Algorithm
- SEM