< Terug naar vorige pagina

Publicatie

Benchmarking waste management performance and optimizing waste collection systems in the Brussels Capital Region

Boek - Dissertatie

The question of how to maintain our current level of welfare, while staying within the boundaries of our planet has finally obtained a more prominent place in policy-making, legislation and the academic literature. Achieving this balance will require a systematic change of the economy in which the current linear model (produce - consume - dispose) is replaced by a circular model. The recovery of materials at the end of a product's life and their potential reintroduction into the economy, i.e., waste and materials management, will remain a major aspect of moving towards this circular economy model, and is the main topic of this thesis. The local authorities of the Brussels Capital Region (BCR) have recently stated their vision of moving towards a circular economy in their waste management policies. To offer guidance on how to improve the BCR's waste management, the first part of this thesis compares the BCR's waste management with other European regions. To develop a methodology which takes into account proper performance indicators and exogenous factors, such as population density, income levels or tourism, a thorough literature review of municipal solid waste management (MSWM) benchmarking studies is conducted. The review presents what performance indicators have been used to compare MSWM across different geographical regions, what exogenous factors were taken into account, and how these exogenous factors could possibly affect MSWM performance. Thereafter, a peer selection methodology for singling out best-practice regions is proposed. This methodology is then applied to the case of the BCR for finding best-practice regions that should be subjected to a more in-depth analysis of their local policies and legislation. The second part of this thesis focuses on the collection and treatment of bio-waste (food and garden waste) in the BCR. The impact of alternative future scenarios on collection costs and distance driven is determined by establishing for each scenario the set of collection vehicle routes that minimizes collection costs. This minimization problem is particularly difficult to solve as it contains many specific features and constraints. Therefore, a Mixed Integer Linear Programming model is proposed which is used to solve an aggregated version of the problem and includes an additional constraint that collection vehicles can only visit two consecutive collection locations before dropping off the waste at a processing facility. Furthermore, a heuristic approach, a Hybrid Genetic Algorithm, is developed, which is more appropriate for solving a more detailed version of the bio-waste collection problem and which can be used for solving a large variety of waste collection problems. The determined collection costs and distance driven per scenario can be used to investigate, from a system-wide perspective, the total (collection and treatment) costs and the environmental burdens associated with them. Thus, policy recommendations are provided with respect to alternative treatment facilities and their locations and the separate or joint collection of food and garden waste.
Jaar van publicatie:2021
Toegankelijkheid:Open