Collecting microplastics in gardens: Case study (ii) from ropes

Zahra Sobhani, Yunlong Luo, Christopher T. Gibson, Youhong Tang, Ravi Naidu, Cheng Fang

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
12 Downloads (Pure)


The characterisation of microplastics is still a challenge. To avoid the “false” characterisation and to increase the signal-noise ratio, we employ Raman imaging to scan the sample surface and generate a Raman spectrum matrix. We then simultaneously map several characteristic peaks to generate several images in parallel, akin to image at multi-channels, to cross-check and visualise the microplastics, via a logic-based algorithm. For comparison, we also employ a principal component analysis (PCA)-based algorithm to automatically decode the Raman spectrum matrix to map an image, not from the individual peaks, but from whole set of the PCA spectrum, meaning a much higher signal-noise ratio and image certainty. Due to the increased signal-noise ratio, we are able to apply this characterisation protocol to directly capture and identify microplastics in our gardens, such as from the plastic ropes used to hang a swing or a ladder for children to play, without any sample preparation. We estimate that at least 6280 microplastics have been released from a nylon rope in 10 years, due to ageing and weathering. We recommend to use polypropylene (PP) rope, rather than nylon rope, and to change the plastic ropes within 10 years.

Original languageEnglish
Article number102322
Number of pages11
JournalEnvironmental Technology and Innovation
Publication statusPublished - May 2022


  • Garden
  • Logic-based algorithm
  • Microplastics
  • PCA-based algorithm
  • Raman imaging
  • Rope


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