Optimizing plastics recycling networks

Plastic pollution is a serious sustainability issue facing the global community. Fragments of macroplastics and microplastics pollute terrestrial and aquatic ecosystems, while nanoplastics can also degrade air quality. The recent COVID-19 pandemic also exacerbated the problem. Large-scale commercial use of plastics recycling technologies is hindered by various socio-economic barriers. In particular, cross-contamination of mixed plastic streams is prevalent due to imperfect waste segregation. The concept of Plastics Recycling Networks is intro-duced to facilitate planning of reverse supply chains using optimization models. In this work, basic Linear Programming and Mixed-Integer Linear Programming models are developed for matching sources of waste plastic with plastic recycling plants within Plastics Recycling Networks. These models allocate streams while considering the ability of recycling plants to tolerate contaminants. Two illustrative case studies are analyzed to demonstrate the effectiveness of the models, and policy implications for mitigation of plastic pollution are dis-cussed. These models enable planning of networks with some tolerance for contaminants in plastic waste, and can be the basis for developing new variants to handle additional real world aspects.

Automated summary

Plastic pollution is a serious sustainability issue that affects both terrestrial and aquatic ecosystems, as well as air quality. The COVID-19 pandemic has further worsened the problem. Socio-economic barriers hinder the large-scale commercial use of plastic recycling technologies, with mixed plastic streams often being contaminated due to imperfect waste segregation. This study introduces the concept of Plastics Recycling Networks and develops linear programming and mixed-integer linear programming models to match waste plastic sources with recycling plants. The models consider the tolerance of recycling plants towards contaminants, and two case studies demonstrate their effectiveness. Policy implications for mitigating plastic pollution are also discussed.