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

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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
Number of pages11
JournalJournal of Hazardous Materials
Publication statusPublished - 15 Mar 2022


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


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