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 under- stand 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 mon- itoring. 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. / Många nuvarande miljö- och utvecklingsproblem har uppstått som oförutsedda biverkningar av människans egna handlingar. De lösningar som prövats har i sin tur ofta skapat  nya problem. Det därför viktigt att förstå hur komplexa system fungerar och att utforma styrmedel och ledningssystem som minimerar risken för oönskade bieffekter. Den här avhandling har använt olika modelleringsmetoder för att öka förståelsen för komplexa system och bidra med kunskaper om hur miljöprestanda och förvaltningsåtgärder kan följas upp på ett mer effektivt sätt. Det övergripande syftet med arbetet var att undersöka användbarheten av olika modelleringsmetoder för att effektivisera den fysiska resurshanteringen i samhället. I arbetet har ett flödesbaserat och aktörsinriktat arbetssätt (pressure based and driver oriented approach) använts i modelleringen.  Material- och substansflödesanalys, miljöfotavtryck, input-output analys, processbaserad dynamisk modellering och systemdynamiska modelleringsmetoder studerades för att undersöka styrkor och svagheter hos de olika metoderna/verktygen.  Tre olika modellerings- och redovisningsmetoder för att stödja miljöövervakning testades också i olika systemskalor. Statiska modelleringsmetoder (räkenskaper) identifierades som grundläggande för att kartlägga, kontoföra och övervaka den fysiska resursmetabolismen i produktions- och konsumtionssystem, medan dynamisk modellering visade sin styrka i att skapa förståelse för komplexa system. Resultaten pekar på att dynamiska modelleringsmetoder bör användas som ett komplement till statiska analyser för att förstå komplexiteten i systemen när man utformar och testar styrmedel. För att uppnå proaktiv övervakning bör flödesbaserade räkenskaper utnyttjas i större utsträckning i stället för den vanliga tillstånds- och påverkansövervakningen (state/impact monitoring). En viktig slutsats är därför att LCA-samfundet bör flytta fokus i sina bedömningar från påverkan till flöden. / <p>QC 20160830</p>

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. / <p>QC 20150420</p>