Novel approach for optimizing waste management systems based on material flow analysis

Autor: Allesch, Astrid
Jazyk: angličtina
Rok vydání: 2017
Předmět:
DOI: 10.34726/hss.2017.45789
Popis: Decision makers are confronted with the question: Is the current waste management (WM) system the most effective or are there other processes for better reaching set goals? Methods are therefore required that allow for the determination of whether goals are achieved, by evaluating economic, social and environmental aspects. In order to compare the goals and outcomes of any given WM system, it is necessary to adopt an approach that takes a complete set of information into account. This thesis investigates assessment methods that focus on the application of material flow analysis (MFA) for the evaluation of WM systems. Its main goal is to develop a comprehensive novel MFA approach by which to optimize WM systems and support goal-oriented decisions in general. The starting point of this thesis is a survey of assessment methods in order to show their potential and to provide guidance for the application and (future) research into assessment methods. Furthermore, it assesses the potentials of MFA on the level of goods and substances individually, and discusses their differences in view of applicability, effectiveness and data availability. The results reveal the high potential of MFA in supporting goal-oriented WM if the levels of both goods and substances are taken into account. With respect to given goals, these findings lead to the development of a novel approach based on a defined and comprehensive WM system. Material flows beginning with waste input into the system, continuing with collection, transportation and treatment, and ending with recycling, landfilling and emissions are assessed on the levels of both goods and substances. This generalized MFA system and a survey including the value judgment of WM stakeholders is connected to seven criteria which are identified as fulfilling given goals: (i) waste input into the system, (ii) export of waste, (iii) gaseous emissions from waste-treatment plants, (iv) long-term gaseous and liquid emissions from landfills, (v) recycled waste, (vi) waste for energy recovery and (vii) total landfilled waste. A case study demonstrates the applicability of the novel approach and indicates the advantages of including the levels of both goods and substances in optimizing WM systems. Using STAN software, a countrywide material flow system is established and quantified for Austria, comprising all relevant inputs, stocks, outputs of wastes, products, residues and emissions. Material balances on the level of goods and selected substances (C, Cd, Cr, Cu, Fe, Hg, N, Ni, P, Pb and Zn) are developed to characterize this system. The seven criteria are calculated and used for a scenario analysis. The results of the case study indicate potential of higher collection and recycling rates, but also show a limitation regarding `clean�� product cycles as certain hazardous substances are recycled instead of eliminated by waste-to-energy plants, for instance, or disposed of in safe deposits. Discharges to the environment can be decreased by promoting `clean�� recycling and by prolonging landfill aftercare. The results are reproducible with known uncertainties, and indicate dependencies and contradictions between given goals and criteria. In addition, a scenario analysis shows that it is not possible to improve all defined criteria only with a single measure. The novel approach that is developed provides benefits for optimization, design, and decisionmaking in WM through the mass-balance principle and due to redundancy, data consistency and transparency. However, this study also discloses deficits that cannot yet be overcome by this MFA approach, such as the lack of methodical tools by which to take waste exports and long-term effects on recycling-product cycles into account. Furthermore, making comprehensive decisions on how a WM system should develop demands that social and economic issues are taken into account as well.
Databáze: OpenAIRE