Towards optimal trade-offs between material and energy recovery for green waste

Dirk Inghels; Wout Dullaert; El-Houssaine Aghezzaf; Reinout Heijungs

doi:10.1016/j.wasman.2019.05.023

Towards optimal trade-offs between material and energy recovery for green waste

Waste Manag. 2019 Jun 15:93:100-111. doi: 10.1016/j.wasman.2019.05.023. Epub 2019 May 24.

Authors

Dirk Inghels¹, Wout Dullaert², El-Houssaine Aghezzaf³, Reinout Heijungs⁴

Affiliations

¹ Vrije Universiteit Amsterdam, Department of Supply Chain Analytics, De Boelelaan 1105, 1081HV Amsterdam, the Netherlands. Electronic address: Dirk.Inghels@vu.nl.
² Vrije Universiteit Amsterdam, Department of Supply Chain Analytics, De Boelelaan 1105, 1081HV Amsterdam, the Netherlands. Electronic address: Wout.Dullaert@vu.nl.
³ Ghent University, Department of Industrial Systems Engineering and Product Design, Faculty of Engineering and Architecture, Technologiepark 903, 9052 Gent-Zwijnaarde, Belgium, and Flanders Make, Belgium. Electronic address: ElHoussaine.Aghezzaf@ugent.be.
⁴ Vrije Universiteit Amsterdam, Department of Econometrics and Operations Research, De Boelelaan 1105, 1081HV Amsterdam, the Netherlands; Leiden University, Institute of Environmental Sciences, PO Box 9518, 2300RA Leiden, the Netherlands. Electronic address: r.heijungs@vu.nl.

PMID: 31235046
DOI: 10.1016/j.wasman.2019.05.023

Abstract

Green waste is a type of biomass consisting mainly of grass, leaves and fresh prunings originating from gardens and parks. It can be used as feedstock for composting, or for energy recovery. The EU Waste Directive 2008/98/EC advocates composting to prevent waste. This directive allows green waste to be used for (renewable) energy valorization only if a better overall environmental outcome can be demonstrated. In this paper, we propose an assessment procedure based on examining the Pareto front of optimal trade-off combinations for maximizing composting and energy recovery of green waste while minimizing environmental impact and minimizing particulate matter emission. The Pareto optimal front is determined by solving a multi-objective optimization problem using the ε-constraint method. Previous research on green waste valorization using Life Cycle Analysis (LCA) shows that either energy recovery or composting is the preferred option depending on how environmental impact is assessed. In contrast to the full assignment to one of these recovery methods produced by LCA, we demonstrate, using the case of green waste valorization in the Netherlands and Belgium, that the proposed assessment procedure provides optimal solutions in a range between full allocation to compost or energy recovery. The proposed methodology supports the selection of optimal solutions taking the decision makers' preference into account that allows complying with Directives that have opposite goals on green waste valorization. Finally, computational results show that the assessment of the "better environmental outcome" requested by the EU waste Directive 2008/98/EC is influenced by the life cycle impact categories and the policy makers preferences with respect to the valorization options taken into account. Since the EU waste Directive 2008/98/EC does not specify how to execute the outcome assessment of valorization alternatives, this can lead to ambiguity.

Keywords: Decision support tool; Green waste valorization; Material conservation; Multiple objective modeling; Waste-to-energy.

MeSH terms

Belgium
Composting*
Environment
Netherlands
Waste Management*