Raman imaging of microplastics and nanoplastics generated by cutting PVC pipe
The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The ima...
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| Published in | Environmental pollution (1987) Vol. 298; p. 118857 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Elsevier Ltd
01.04.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0269-7491 1873-6424 1873-6424 |
| DOI | 10.1016/j.envpol.2022.118857 |
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| Abstract | The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The images mapping multiple characteristic peaks can be merged into one using logic-based algorithm, in order to cross-check these images and to further increase the signal-noise ratio. We demonstrate how to capture and identify microplastics, and then zoom down gradually to visualise nanoplastics, in order to avoid the shielding effect of the microplastics to shadow and obscure the nanoplastics. We also carefully compare the advantages and disadvantages of Raman imaging, while giving recommendations for improvement. We validate our approach to capture the microplastics and nanoplastics as particles released when we cut and assemble PVC pipes in our garden. We estimate that, during a cutting process of the PVC pipe, thousands of microplastics in the range of 0.1–5 mm can be released, along with millions of small microplastics in the range of 1–100 μm, and billions of nanoplastics in the range of <1 μm. Overall, Raman imaging can effectively capture microplastics and nanoplastics.
[Display omitted]
•Raman imaging can increase the signal-noise ratio by mapping the scanning spectrum matrix.•Changing the height of focal plane by ∼50 μm notably affects the confocal Raman results.•Microplastics can easily mask and shield nanoplastics.•Gradual zooming-in is recommended, using objective lens with different magnifications.•Thousands microplastics, billions of nanoplastics might be released by one PVC pipe-cutting. |
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| AbstractList | The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The images mapping multiple characteristic peaks can be merged into one using logic-based algorithm, in order to cross-check these images and to further increase the signal-noise ratio. We demonstrate how to capture and identify microplastics, and then zoom down gradually to visualise nanoplastics, in order to avoid the shielding effect of the microplastics to shadow and obscure the nanoplastics. We also carefully compare the advantages and disadvantages of Raman imaging, while giving recommendations for improvement. We validate our approach to capture the microplastics and nanoplastics as particles released when we cut and assemble PVC pipes in our garden. We estimate that, during a cutting process of the PVC pipe, thousands of microplastics in the range of 0.1–5 mm can be released, along with millions of small microplastics in the range of 1–100 μm, and billions of nanoplastics in the range of <1 μm. Overall, Raman imaging can effectively capture microplastics and nanoplastics. The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The images mapping multiple characteristic peaks can be merged into one using logic-based algorithm, in order to cross-check these images and to further increase the signal-noise ratio. We demonstrate how to capture and identify microplastics, and then zoom down gradually to visualise nanoplastics, in order to avoid the shielding effect of the microplastics to shadow and obscure the nanoplastics. We also carefully compare the advantages and disadvantages of Raman imaging, while giving recommendations for improvement. We validate our approach to capture the microplastics and nanoplastics as particles released when we cut and assemble PVC pipes in our garden. We estimate that, during a cutting process of the PVC pipe, thousands of microplastics in the range of 0.1–5 mm can be released, along with millions of small microplastics in the range of 1–100 μm, and billions of nanoplastics in the range of <1 μm. Overall, Raman imaging can effectively capture microplastics and nanoplastics. [Display omitted] •Raman imaging can increase the signal-noise ratio by mapping the scanning spectrum matrix.•Changing the height of focal plane by ∼50 μm notably affects the confocal Raman results.•Microplastics can easily mask and shield nanoplastics.•Gradual zooming-in is recommended, using objective lens with different magnifications.•Thousands microplastics, billions of nanoplastics might be released by one PVC pipe-cutting. The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The images mapping multiple characteristic peaks can be merged into one using logic-based algorithm, in order to cross-check these images and to further increase the signal-noise ratio. We demonstrate how to capture and identify microplastics, and then zoom down gradually to visualise nanoplastics, in order to avoid the shielding effect of the microplastics to shadow and obscure the nanoplastics. We also carefully compare the advantages and disadvantages of Raman imaging, while giving recommendations for improvement. We validate our approach to capture the microplastics and nanoplastics as particles released when we cut and assemble PVC pipes in our garden. We estimate that, during a cutting process of the PVC pipe, thousands of microplastics in the range of 0.1-5 mm can be released, along with millions of small microplastics in the range of 1-100 μm, and billions of nanoplastics in the range of <1 μm. Overall, Raman imaging can effectively capture microplastics and nanoplastics.The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The images mapping multiple characteristic peaks can be merged into one using logic-based algorithm, in order to cross-check these images and to further increase the signal-noise ratio. We demonstrate how to capture and identify microplastics, and then zoom down gradually to visualise nanoplastics, in order to avoid the shielding effect of the microplastics to shadow and obscure the nanoplastics. We also carefully compare the advantages and disadvantages of Raman imaging, while giving recommendations for improvement. We validate our approach to capture the microplastics and nanoplastics as particles released when we cut and assemble PVC pipes in our garden. We estimate that, during a cutting process of the PVC pipe, thousands of microplastics in the range of 0.1-5 mm can be released, along with millions of small microplastics in the range of 1-100 μm, and billions of nanoplastics in the range of <1 μm. Overall, Raman imaging can effectively capture microplastics and nanoplastics. The characterisation of nanoplastics is much more difficult than that of microplastics. Herewith we employ Raman imaging to capture and visualise nanoplastics and microplastics, due to the increased signal-noise ratio from Raman spectrum matrix when compared with that from a single spectrum. The images mapping multiple characteristic peaks can be merged into one using logic-based algorithm, in order to cross-check these images and to further increase the signal-noise ratio. We demonstrate how to capture and identify microplastics, and then zoom down gradually to visualise nanoplastics, in order to avoid the shielding effect of the microplastics to shadow and obscure the nanoplastics. We also carefully compare the advantages and disadvantages of Raman imaging, while giving recommendations for improvement. We validate our approach to capture the microplastics and nanoplastics as particles released when we cut and assemble PVC pipes in our garden. We estimate that, during a cutting process of the PVC pipe, thousands of microplastics in the range of 0.1-5 mm can be released, along with millions of small microplastics in the range of 1-100 μm, and billions of nanoplastics in the range of <1 μm. Overall, Raman imaging can effectively capture microplastics and nanoplastics. |
| ArticleNumber | 118857 |
| Author | Luo, Yunlong Chuah, Clarence Fang, Cheng Tang, Youhong Naidu, Ravi Al Amin, Md Gibson, Christopher T. |
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| Keywords | Logic-based algorithm Microplastics PVC pipe Raman imaging Nanoplastics |
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| SubjectTerms | Algorithms Gardens Logic-based algorithm Microplastics Nanoplastics Plastics pollution Polyvinyl Chloride PVC pipe Raman imaging Water Pollutants, Chemical - analysis |
| Title | Raman imaging of microplastics and nanoplastics generated by cutting PVC pipe |
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