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Logistic model-based tool for policy-making towards sustainable waste management
Authors:Radovan ?omplák  Martin Pavlas  Ji?í Kropá?  Ond?ej Putna  Vít Procházka
Affiliation:1. Institute of Process and Environmental Engineering, Faculty of Mechanical Engineering, Brno University of Technology (UPEI VUT), Technická 2896/2, 616 69, Brno, Czech Republic
2. Institute of Mathematics, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2896/2, 616 69, Brno, Czech Republic
Abstract:The aim of this paper is to introduce a novel approach which supports facility planning in the field of waste management. Only 23 % of municipal solid waste (MSW) was thermally treated in the EU 27 in 2011. The increased exploitation of its potential for energy recovery must be accompanied by massive investments into highly efficient and reliable incineration technologies. Therefore, the challenge is to be efficient and use the technology to its optimal level. Feasibility studies of all plants providing a service for a region create a large and complex task. Gate fee (the charge for waste processing in the facility) represents one of the most crucial input parameters for the assessment. The gate fee is driven by configuration of the technology, competition, market development, environmental taxation and costs of waste transport to satisfy the plant’s capacity. Valid prediction of the gate fee thus presents a demanding task. In this paper, first, an advanced tool called NERUDA is introduced, which addresses logistic optimization and capacity sizing. The key idea is to focus on the problem of competition modelling among waste-to-energy plants, landfill sites, and mechanical–biological treatment plants producing refuse-derived fuel. Then, the main theoretical concepts are discussed, followed by the development of a suitable mathematical model. The goal is to obtain a minimized cost of MSW treatment for waste producers (municipalities). The application of the developed tool is demonstrated through a case study, where uncertain parameters entering the calculation are handled by a repetitive Monte Carlo simulation based on real-world data.
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