Systems Modeling Approaches to Physical Resource Management An Industrial Ecology Perspective

Many of the present problems that we are facing arise as unanticipated side-effects of our own actions. Moreover, the solutions implemented to solve important problems often create new problems. To avoid unintended consequences, understanding complex systems is essential in devising policy instruments and in improving environmental management. Thus, this thesis investigated systems modeling approaches to understand complex systems and monitor the environmental performance of management actions. The overall aim of the work was to investigate the usefulness of different systems modeling approaches in supporting environmental management. A driver based, pressure-oriented approach was adopted to investigate systems modeling tools. Material/substance flow analysis, environmental footprinting, input-output analysis, process-based dynamic modeling, and systems dynamics modeling approaches were applied in different cases to investigate strengths and weaknesses of the tools in generating an understanding of complex systems. Three modeling and accounting approaches were also tested at different systems scales to support environmental monitoring. Static modeling approaches were identified as fundamental to map, account, and monitor physical resource metabolism in production and consumption systems, whereas dynamic modeling showed strengths in understanding complex systems. The results suggested that dynamic modeling approaches should be conducted on top of static analysis to understand the complexity of systems when devising and testing policy instruments. To achieve proactive monitoring, a pressure-based assessment was proposed instead of the mainstream impact/state-based approach. It was also concluded that the LCA community should shift the focus of its assessments to pressures instead of impacts.