Detail publikace
Plastic Waste Circularity with Data-Driven Approach Considering Polymer Heterogeneity
Chin, H.H. Varbanov, P.S. Klemeš, J.J. Tan, R.R. Aviso, K.B.
Anglický název
Plastic Waste Circularity with Data-Driven Approach Considering Polymer Heterogeneity
Typ
článek v časopise ve Scopus, Jsc
Jazyk
en
Originální abstrakt
Plastic debris has been a consistent issue in the global environment, and plastic waste recycling is the most promising option to avoid further accumulation. The waste quality serves as a crucial restriction for recycling planning and requires proper definition. This work aims to extend the previously developed data-driven approach to quantifying the recyclability clusters of plastic waste to consider polymer heterogeneity in the evaluation. Heterogeneity estimation is conducted by identifying the compatibility between polymers based on their surface tension. The applicability of the polymers mix (targeted and non-targeted polymers) can then be decided based on the Q-value approach. The method identifies the quality class of the plastic mixture based solely on the compatibility of the polymer, where the quality trend varies for each identified compatibility class. This gives insights into the suitability of mixing different polymers type prior to recycling. The recycling potential/circularity of the plastic waste can then be identified based on the Plastic Pinch Analysis, which outputs the ideal maximum external plastic demands with a certain threshold grade of the plastic (Pinch Quality). A case study is shown using three types of polymers: Polyethylene Terephthalate (PET), Polyethylene (PE) and Polypropylene (PP), to showcase the polymers heterogeneity evaluation. The results show that around 32.4 % of disposed PP waste could potentially be mixed with PE to have a compatible mixture. However, it is also crucial to check the properties of the mixed polymers to fulfil the demands of site requirements prior to recycling.
Anglický abstrakt
Plastic debris has been a consistent issue in the global environment, and plastic waste recycling is the most promising option to avoid further accumulation. The waste quality serves as a crucial restriction for recycling planning and requires proper definition. This work aims to extend the previously developed data-driven approach to quantifying the recyclability clusters of plastic waste to consider polymer heterogeneity in the evaluation. Heterogeneity estimation is conducted by identifying the compatibility between polymers based on their surface tension. The applicability of the polymers mix (targeted and non-targeted polymers) can then be decided based on the Q-value approach. The method identifies the quality class of the plastic mixture based solely on the compatibility of the polymer, where the quality trend varies for each identified compatibility class. This gives insights into the suitability of mixing different polymers type prior to recycling. The recycling potential/circularity of the plastic waste can then be identified based on the Plastic Pinch Analysis, which outputs the ideal maximum external plastic demands with a certain threshold grade of the plastic (Pinch Quality). A case study is shown using three types of polymers: Polyethylene Terephthalate (PET), Polyethylene (PE) and Polypropylene (PP), to showcase the polymers heterogeneity evaluation. The results show that around 32.4 % of disposed PP waste could potentially be mixed with PE to have a compatible mixture. However, it is also crucial to check the properties of the mixed polymers to fulfil the demands of site requirements prior to recycling.
Klíčová slova anglicky
plastic; waste; circularity; data-driven; approach; considering; polymer; heterogeneity
Vydáno
01.09.2022
Nakladatel
Italian Association of Chemical Engineering - AIDIC
ISSN
2283-9216
Číslo
94
Strany od–do
1255–1260
Počet stran
6
BIBTEX
@article{BUT179787,
author="Hon Huin {Chin} and Petar Sabev {Varbanov} and Jiří {Klemeš},
title="Plastic Waste Circularity with Data-Driven Approach Considering Polymer Heterogeneity",
year="2022",
number="94",
month="September",
pages="1255--1260",
publisher="Italian Association of Chemical Engineering - AIDIC",
issn="2283-9216"
}