Applying Raman imaging to capture and identify microplastics and nanoplastics in the garden

被引:19
|
作者
Luo, Yunlong [1 ,2 ]
Gibson, Christopher T. [3 ,4 ]
Chuah, Clarence [4 ]
Tang, Youhong [4 ]
Naidu, Ravi [1 ,2 ]
Fang, Cheng [1 ,2 ]
机构
[1] Univ Newcastle, Global Ctr Environm Remediat GCER, Callaghan, NSW 2308, Australia
[2] Univ Newcastle, Cooperat Res Ctr Contaminat Assessment & Remediat, Callaghan, NSW 2308, Australia
[3] Flinders Univ S Australia, Coll Sci & Engn, Flinders Inst NanoScale Sci & Technol, Bedford Pk, SA 5042, Australia
[4] Flinders Univ S Australia, Coll Sci & Engn, Flinders Microscopy & Microanal, Bedford Pk, SA 5042, Australia
关键词
Raman mapping; PCA-based algorithm; Signal-noise ratio; Microplastics; Nanoplastics;
D O I
10.1016/j.jhazmat.2021.127788
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The characterisation of microplastics is still a challenge, and the challenge is even greater for nanoplastics, of which we only have a limited knowledge so far. Herewith we employ Raman imaging to directly visualise microplastics and nanoplastics which are released from the trimmer lines during lawn mowing. The signal-noise ratio of Raman imaging is significantly increased by generating an image from hundreds or thousands of Raman spectra, rather than from a single spectrum, and is further increased by combining with the logic-based and PCAbased algorithms. The increased signal-noise ratio enables us to capture and identify microplastics and particularly nanoplastics, including plastic fragments or shreds (with diameters / widths of 80 nm - 3 mu m) and nanoparticles (with diameters of < 1000 nm) that are released during the mimicked mowing process. Using Raman imaging, we estimate that thousands of microplastics (0.1-5 mm), and billions of nanoplastics (< 1000 nm), are released per minute when a line trimmer is used to mow lawn. Overall, Raman imaging provides effective characterisation of the microplastics and is particularly suitable for nanoplastics.
引用
收藏
页数:11
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