The recycling of packaging waste is an important part of the EU circular economy package, with a political focus on raising the recycling targets for post-consumer plastic packaging waste (PPW). The recycling of PPW involves at least three steps; collection, sorting and mechanical recycling. In contrast to the first two steps, mechanical recycling is poorly documented, as it is considered a free market activity. In order to provide a complete chain description the mechanical recycling yields were determined. The recovery of mass was determined for the main plastic sorting products from both major collection systems: separate collection (SC) and mechanical recovery (MR) from municipal solid waste. This technical assessment was conducted with a laboratory set-up for a standard mechanical recycling process. This analysis showed that there is a substantial sample-to-sample variation in polymeric composition between similar feedstocks and this variation is also observed in recovered masses. Next, the mechanical recycling of polyethylene feedstocks was studied more in depth. Six PE feedstocks with a gradual increasing level of complexity (from only transparent PE bottle bodies to the complete PE sorting product according to DKR 329), were prepared and mechanical recycled with the laboratory set-up. Since the polymeric composition of both the six feedstocks and the six floating milled goods were known, the net PE recycling yield could be calculated. The net PE yields are close to 100% for such a standard recycling process. Additionally, the compositional analysis revealed that contaminants are only partially removed by the standard mechanical recycling process.
Skip Nav Destination
Article navigation
14 December 2017
PROCEEDINGS OF PPS-32: The 32nd International Conference of the Polymer Processing Society - Conference Papers
25–29 July 2016
Lyon, France
Research Article|
December 14 2017
Efficiency of recycling post-consumer plastic packages
E. U. Thoden van Velzen;
E. U. Thoden van Velzen
a
Wageningen Food & Biobased Research
, Bornse Weilanden 9 6709 WG Wageningen The Netherlands
Search for other works by this author on:
M. Jansen;
M. Jansen
b
Institut für Aufbereitung und Recycling
, RWTH, Wüllnerstrasse 6, 52062 Aachen Germany
Search for other works by this author on:
M. T. Brouwer;
M. T. Brouwer
a
Wageningen Food & Biobased Research
, Bornse Weilanden 9 6709 WG Wageningen The Netherlands
Search for other works by this author on:
A. Feil;
A. Feil
b
Institut für Aufbereitung und Recycling
, RWTH, Wüllnerstrasse 6, 52062 Aachen Germany
Search for other works by this author on:
K. Molenveld;
K. Molenveld
a
Wageningen Food & Biobased Research
, Bornse Weilanden 9 6709 WG Wageningen The Netherlands
Search for other works by this author on:
Th. Pretz, prof.
Th. Pretz, prof.
*
b
Institut für Aufbereitung und Recycling
, RWTH, Wüllnerstrasse 6, 52062 Aachen Germany
Search for other works by this author on:
AIP Conf. Proc. 1914, 170002 (2017)
Citation
E. U. Thoden van Velzen, M. Jansen, M. T. Brouwer, A. Feil, K. Molenveld, Th. Pretz; Efficiency of recycling post-consumer plastic packages. AIP Conf. Proc. 14 December 2017; 1914 (1): 170002. https://doi.org/10.1063/1.5016785
Download citation file:
Citing articles via
Design of a 100 MW solar power plant on wetland in Bangladesh
Apu Kowsar, Sumon Chandra Debnath, et al.
The effect of a balanced diet on improving the quality of life in malignant neoplasms
Yu. N. Melikova, A. S. Kuryndina, et al.
Animal intrusion detection system using Mask RCNN
C. Vijayakumaran, Dakshata, et al.
Related Content
Consumer default risk assessment in a banking institution
AIP Conference Proceedings (December 2016)
Determinants of trust in B2C e-commerce and their relationship with consumer online trust
AIP Conference Proceedings (December 2017)
Mechanical properties of virgin ABS/post-consumer ABS blends
AIP Conference Proceedings (July 2018)
Smart and sustainable building materials: Empirical examination of consumer adoption intentions in Bangalore
AIP Conf. Proc. (October 2024)
Credit scoring to classify consumer loan using machine learning
AIP Conf. Proc. (December 2019)