Proceedings of the 7th International Conference on Civil Engineering for Sustainable Development (ICCESD 2024)

Classification of Recyclable Plastic Waste by Near-Infrared Spectrometer

Authors
Md. Emran Hossain Emon1, *, Quazi Hamidul Bari2, Jobaer Ahmed Saju3, Md. Rafizul Islam4, Abhishek Sarkar5
1Undergraduate Student, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
2Professor, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
3Postgraduate Student, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
4Professor, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
5Postgraduate Student, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
*Corresponding author. Email: emrankuet38@gmail.com
Corresponding Author
Md. Emran Hossain Emon
Available Online 23 July 2024.
DOI
10.2991/978-94-6463-478-5_5How to use a DOI?
Keywords
Solid Waste Management (SWM); Municipal Solid Waste (MSW); Recyclable Plastics; Near-Infrared (NIR) Spectroscopy; Recycling Shops (RS)
Abstract

This study addresses the pressing issue of plastic waste management in Khulna City, Bangladesh, highlighting its direct impact on health and the environment. The conventional methods of sorting plastic waste in the existing Recycling Shops (RSs) in Khulna City are time-consuming and rely on visual inspection. The research proposes the application of handheld Near-InfraRed (NIR) spectrometers in RSs for efficient plastic waste identification. This spectrometer provides cloud-based computing and a centralised database for material classification based on their chemical composition. A survey conducted in three selected RSs over six months reveals an average monthly input of 15 tons of plastic waste per RS, with a 75% recycling rate. The NIR analysis classifies plastics into eight distinct types, including Polyamide (PA), Polyethylene (PE), Polyethylene terephthalate (PET), Polymethylmethacrylate (PMMA), Polypropylene (PP), Polystyrene (PS), Polyvinyl chloride (PVC), and Styrene Acrylonitrile Resin (SAN). Notably, PP and PET emerge as the most abundant materials, consisting of 65% of the total plastic handled. The study detailed the monthly input and output data, indicating the percentages of various plastics handled in the RS. The performance evaluation of the handheld NIR spectrometer for five known plastic types demonstrated an overall accuracy rate of 87.6%. The existing manual sorting process of plastic waste in RS of Khulna was found to be convenient and accurate. However, incorporating the NIR spectrometer into Khulna City’s plastic waste management system for automatically sorting plastic waste can further improve the efficiency of recycling practices. The proposed solution holds the potential to address environmental concerns, promote sustainability, and contribute to a healthier future in waste management practices in Bangladesh.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 7th International Conference on Civil Engineering for Sustainable Development (ICCESD 2024)
Series
Atlantis Highlights in Engineering
Publication Date
23 July 2024
ISBN
10.2991/978-94-6463-478-5_5
ISSN
2589-4943
DOI
10.2991/978-94-6463-478-5_5How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Md. Emran Hossain Emon
AU  - Quazi Hamidul Bari
AU  - Jobaer Ahmed Saju
AU  - Md. Rafizul Islam
AU  - Abhishek Sarkar
PY  - 2024
DA  - 2024/07/23
TI  - Classification of Recyclable Plastic Waste by Near-Infrared Spectrometer
BT  - Proceedings of the 7th International Conference on Civil Engineering for Sustainable Development (ICCESD 2024)
PB  - Atlantis Press
SP  - 47
EP  - 62
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-478-5_5
DO  - 10.2991/978-94-6463-478-5_5
ID  - Emon2024
ER  -