TY - JOUR
T1 - Applying Raman imaging to capture and identify microplastics and nanoplastics in the garden
AU - Luo, Yunlong
AU - Gibson, Christopher T.
AU - Chuah, Clarence
AU - Tang, Youhong
AU - Naidu, Ravi
AU - Fang, Cheng
PY - 2022/3/15
Y1 - 2022/3/15
N2 - 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 PCA-based 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 µm) 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.
AB - 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 PCA-based 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 µm) 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.
KW - Microplastics
KW - Nanoplastics
KW - PCA-based algorithm
KW - Raman mapping
KW - Signal-noise ratio
UR - http://www.scopus.com/inward/record.url?scp=85119625738&partnerID=8YFLogxK
U2 - 10.1016/j.jhazmat.2021.127788
DO - 10.1016/j.jhazmat.2021.127788
M3 - Article
AN - SCOPUS:85119625738
VL - 426
JO - Journal of Hazardous Materials
JF - Journal of Hazardous Materials
SN - 0304-3894
M1 - 127788
ER -