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

Yunlong Luo, Christopher T. Gibson, Clarence Chuah, Youhong Tang, Ravi Naidu, Cheng Fang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

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.
Original languageEnglish
Article number127788
Pages (from-to)1-11
Number of pages11
JournalJournal of Hazardous Materials
Volume426
Early online date19 Nov 2021
DOIs
Publication statusPublished - 15 Mar 2022
Externally publishedYes

Keywords

  • Raman mapping
  • PCA-based algorithm
  • Signal-noise ratio
  • Microplastics
  • Nanoplastics

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