Neo, Edward Ren Kai, Yeo, Zhiquan, Low, Jonathan Sze Choong, Goodship, Vannessa and Debattista, Kurt (2022) A review on chemometric techniques with infrared, Raman and laser-induced breakdown spectroscopy for sorting plastic waste in the recycling industry. Resources, Conservation and Recycling, 180 . 106217. doi:10.1016/j.resconrec.2022.106217

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Abstract

Mismanagement of plastic waste globally has resulted in a multitude of environmental issues, which could be tackled by boosting plastic recycling rates. Chemometrics has emerged as a useful tool for boosting plastic recycling rates by automating the plastic sorting and recycling process. This paper will comprehensively review the recent works applying chemometric methods to plastic waste sorting. The review begins by introducing spectroscopic methods and chemometric tools that are commonly used in the plastic chemometrics literature. The spectroscopic methods include near-infrared spectroscopy (NIR), mid-infrared spectroscopy (MIR), Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS). The chemometric tools include principal component analysis (PCA), linear discriminant analysis (LDA), partial least square (PLS), k-nearest neighbors (k-NN), support vector machines (SVM), random forests (RF), artificial neural networks (ANNs), convolutional neural networks (CNNs) and K-means clustering. This review revealed four main findings. (1) The scope of plastic waste should be expanded in terms of types, contamination and degradation level to mirror the heterogeneous plastic waste received at recycling plants towards understanding potential application in the recycling industry. (2) The use of hybrid spectroscopic method could potentially overcome the limitations of each spectroscopic methods. (3) Develop an open-sourced standardized database of plastic waste spectra would help to further expand the field. (4) There is limited use of more novel machine learning tools such as deep learning for plastic sorting.

Item Type:	Journal Article
Subjects:	Q Science > QD Chemistry T Technology > TD Environmental technology. Sanitary engineering
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
SWORD Depositor:	Library Publications Router
Library of Congress Subject Headings (LCSH):	Chemometrics, Machine learning, Environmental chemistry -- Statistical methods, Environmental chemistry -- Mathematics, Recycling (Waste, etc.) -- Research, Plastics -- Environmental aspects, Plastics -- Biodegradation
Journal or Publication Title:	Resources, Conservation and Recycling
Publisher:	Elsevier
ISSN:	0921-3449
Official Date:	May 2022
Dates:	Date Event May 2022 Published 5 February 2022 Available 31 January 2022 Accepted
Volume:	180
Article Number:	106217
DOI:	10.1016/j.resconrec.2022.106217
Status:	Peer Reviewed
Publication Status:	Published
Publisher Statement:	** Article version: AM ** Embargo end date: 05-02-2023 ** From Elsevier via Jisc Publications Router ** History: accepted 31-01-2022; epub 05-02-2022; issued 31-05-2022. ** Licence for AM version of this article starting on 05-02-2023: http://creativecommons.org/licenses/by-nc-nd/4.0/
Access rights to Published version:	Restricted or Subscription Access

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