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Extending multilevel statistical entropy analysis towards plastic recyclability prediction
Nimmegeers, P.; Parchomenko, A.; De Meulenaere, P.; D’hooge, D.R.; Van Steenberge, P.H.M.; Rechberger, H.; Billen, P. (2021). Extending multilevel statistical entropy analysis towards plastic recyclability prediction. Sustainability 13(6): 3553. https://dx.doi.org/10.3390/su13063553
In: Sustainability. MDPI: Basel. ISSN 2071-1050, more
Peer reviewed article  

Available in  Authors 

Author keywords
    statistical entropy analysis; recycling; plastic waste; waste management; resource efficiency; circular economy

Authors  Top 
  • Nimmegeers, P.
  • Parchomenko, A., more
  • De Meulenaere, P.
  • D’hooge, D.R.
  • Van Steenberge, P.H.M.
  • Rechberger, H.
  • Billen, P.

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.

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