Industrial Ecology Approaches to Improve Metal Management : Three Modeling Experiments

Sammanfattning: A linear model of consumption − produce-use-dispose − has constantly increased the pressure on the environment in recent decades. There has been a great belief that technology will solve the problem, but in many cases it is only partly contributing to the solution. For a full solution, the root causes of problems need to be identified. The drivers-pressures-state-impact-response (DPSIR) framework allows the drivers of a specific problem to be identified by structuring the causal relations between humans and the environment. A state/ impact-based approach can help identify pressures and drivers, and make what can be considered an end-of-pipe response. Rather than that mainstream approach, this thesis adopts a pressure-based driver-oriented approach, which could be considered a proactive approach to environmental resource management.In physical resource management, material flow analysis (MFA) is one of the tools used for communication and decision support for policy response on resource productivity and pollution abatement. Here, element flow analysis (EFA), a disaggre- gation of MFA for better mass balance, was applied in pollution control and resource management. The pressure-based driver-oriented approach was used to model element flows and thus identify the drivers of problems in order to improve pollution control and resource management in complex systems.In one case study, a source-storage-transport model was developed and applied in five lakes in the Stockholm region to identify the drivers of copper pollution by monitoring the state of the environment through element flow modeling linking diffuse sources and fate in the lakes. In a second case study, a system dynamics modeling approach was applied in dynamic element flow modeling of the global mobile phone product system to investigate the drivers for closing the material flow loop through a sensitivity analysis. In a third case study, causal loop diagram modeling was used for proactive resource management to identify root causes of a problem in a complex system (product systems of physical consumer goods) by qualitatively analyzing unintended environmental consequences of an improvement action.In the case study on lakes in the Stockholm region, the source-transport-storage model proved capable of predicting copper sources through monitoring the sediment copper content in the heavily copper-polluted lakes. The results also indicated how the model could help guide policy makers in controlling copper pollution. The system dynamics study proposed an eco-cycle model of the global mobile phone product system by tuning the drivers, which could lessen the pressures on resources by decreasing the resource demands for production and increasing resource recovery at product end-of- life. The causal loop diagram study showed that a broader systems approach is required to understand and identify the drivers for proactive resource management in a complex system, where improvement actions can lead to unintended consequences.