| Title |
Extending Multilevel Statistical Entropy Analysis towards Plastic Recyclability Prediction |
| ID_Doc |
21107 |
| Authors |
Nimmegeers, P; Parchomenko, A; De Meulenaere, P; D'hooge, DR; Van Steenberge, PHM; Rechberger, H; Billen, P |
| Title |
Extending Multilevel Statistical Entropy Analysis towards Plastic Recyclability Prediction |
| Year |
2021 |
| Published |
Sustainability, 13.0, 6 |
| DOI |
10.3390/su13063553 |
| Abstract |
Multilevel statistical entropy analysis (SEA) is a method that has been recently proposed to evaluate circular economy strategies on the material, component and product levels to identify critical stages of resource and functionality losses. However, the comparison of technological alternatives may be difficult, and equal entropies do not necessarily correspond with equal recyclability. A coupling with energy consumption aspects is strongly recommended but largely lacking. The aim of this paper is to improve the multilevel SEA method to reliably assess the recyclability of plastics. Therefore, the multilevel SEA method is first applied to a conceptual case study of a fictitious bag filled with plastics, and the possibilities and limitations of the method are highlighted. Subsequently, it is proposed to extend the method with the computation of the relative decomposition energies of components and products. Finally, two recyclability metrics are proposed. A plastic waste collection bag filled with plastic bottles is used as a case study to illustrate the potential of the developed extended multilevel SEA method. The proposed extension allows us to estimate the recyclability of plastics. In future work, this method will be refined and other potential extensions will be studied together with applications to real-life plastic products and plastic waste streams. |
| Author Keywords |
statistical entropy analysis; recycling; plastic waste; waste management; resource efficiency; circular economy |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000645703300001 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://www.mdpi.com/2071-1050/13/6/3553/pdf?version=1616563167
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