Raman imaging to identify microplastics released from toothbrushes: algorithms and particle analysis.
Algorithm
Microplastic
Particle analysis
Raman imaging
SEM
Toothbrush
Journal
Environmental pollution (Barking, Essex : 1987)
ISSN: 1873-6424
Titre abrégé: Environ Pollut
Pays: England
ID NLM: 8804476
Informations de publication
Date de publication:
15 Nov 2023
15 Nov 2023
Historique:
received:
08
06
2023
revised:
14
08
2023
accepted:
03
09
2023
medline:
26
10
2023
pubmed:
10
9
2023
entrez:
9
9
2023
Statut:
ppublish
Résumé
Microplastics are small plastic fragments that are of increasing concern due to their potential impacts on the environment and human health. The source of microplastics is not completely clear and might originate in daily lives such as from toothbrushes. When toothbrushes are used to clean teeth, small plastic debris and fragments can be potentially released into mouths directly or environment indirectly. This study aims to examine the release of microplastics from toothbrushes, using Raman imaging to identify and visualise the plastic debris with an increased signal-noise ratio via hyper-spectrum analysis. Using algorithms to convert the hyper-spectrum to an image, the plastic can be distinguished from the co-formulated titanium oxide particles that are not uniformly distributed along the plastics. The non-uniform distribution can lead to the bias results if a single spectrum analysis is conducted at one position rather than imaging analysis to scan an area. The potential false image originating from the off-focal position for the confocal Raman is overcome using the terrain map to guide the Raman imaging. The imaging analysis balancing between the low magnification to capture the overview and the high magnification to test the details is also discussed. While the release amount of microplastics from the toothbrush is estimated at thousands daily with the expected variation, the results of this study have confirmed the release of microplastics in daily lives. The imaging analysis approach along with algorithm can help to identify the chemical elements of microplastics from the complex background, which can benefit the further research on microplastics towards risk assessment and remediation.
Identifiants
pubmed: 37689132
pii: S0269-7491(23)01512-9
doi: 10.1016/j.envpol.2023.122510
pii:
doi:
Substances chimiques
Microplastics
0
Plastics
0
Water Pollutants, Chemical
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
122510Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.