Industrial Ecology Approaches to Improve Metal Management

Three Modeling Experiments

Rajib Sinha

Licentiate Thesis

Industrial Ecology Department of Sustainable Development, Environmental Science and Engineering (SEED) KTH Royal Institute of Technology Stockholm, Sweden

2014 Title: Industrial Ecology Approaches to Improve Metal Management: Three Modeling Experiments

Author: Rajib Sinha

Registration: TRITA-IM-LIC 2014:01 ISBN: 978-91-7595-396-0

Contact information: Industrial Ecology Department of Sustainable Development, Environmental Science and Engineering (SEED) School of Architecture and the Built Environment, KTH Royal Institute of Technology Technikringen 34, SE-100 44 Stockholm, Sweden Email: [email protected] www.kth.se

Printed by: Universitetetsservice US-AB, Stockholm, Sweden, 2014

ii Preface

This licentiate thesis1 attempts to capture specific, but also diverse, research interests in the field of industrial ecology. It therefore has a broader scope than a normal licentiate thesis. Here, I would like to share my academic journey in producing the thesis to guide the reader in understanding the content and the background.

At high school (standard 9−12), I was most interested in mathematics and physics. This led me to study engineering, and I completed my B.Sc. in Civil Engineering at BUET, Dhaka, Bangladesh. During my undergraduate studies, I developed a great interest in structural engineering. As a result, I chose finite element analysis of shear stress as my Bachelor’s degree project. The title of the dissertation was Analysis of Steel-Concrete Composite Bridges with Special Reference to Shear Connectors.

All my close classmates at university and I chose an environmental engineering path for further studies. With my interest in environmental engineering, I completed my M.Sc. in Sustainable Technology at the Division of Industrial Ecology, KTH, Stockholm, Sweden. The title of my Master’s thesis was Modelling Source and Copper Fate in Lake R˚ackstaTr¨ask,Stockholm: Sediment Copper Contents as an Indicator of Urban Metal Emissions. I was then given the opportunity to continue working on the study described in Paper I of this thesis, after which I worked as a research engineer at KTH (for around 2 years) in consecutive small projects on: (i) radionuclide sorption onto soil samples, (ii) reactive transport modeling for radio-nuclide migration, (iii) modeling the effects of mixing and spreading on biodegradable BTEX in groundwa- ter, (iv) household metabolism in a global perspective and (v) energy systems modeling.

During that period, I became interested in research methodologies rather than a specific research topic, in particular, systems analysis, dynamic modeling and computer simulation, especially systems dynamics and agent-based modeling.

I enrolled as a post-graduate student on March 01, 2012. The project focused on modeling a decentralized energy system for future cities and evaluating how the system can respond to different optimization criteria, such as economy, renewables, GHG emissions, low carbon, resilience, etc. An agent-based modeling approach was chosen for the system modeling.

After studying for six months, I moved to another research group − Sustainable Production and Consumption in a broader systems perspective. This group was

1A licentiate degree in Sweden is an academic degree between Master’s and PhD. A licentiate thesis can be written either as a dissertation manuscript (monograph) or as a compilation thesis with a summarizing chapter (kappa) followed by a compendium of articles. I chose the latter version.

iii working with production and consumption systems including a broader systems approach from two different angles: the design perspective and the waste management perspective. Through my interest in systems modeling, I combined the two approaches by modeling energy and material metabolism. During my post-graduate studies, my research specifically focused on the modeling aspects of industrial ecology as described in this thesis.

This summarizing essay is based on the results presented in the three appended papers (Papers I, II, and III) and briefly describes the most important findings of the work. It also reflects my academic journey and interests.

Rajib Sinha August 28, 2014 Stockholm, Sweden

iv Acknowledgments

My deepest gratitude to my supervisor, Professor Bj¨ornM. Frostell, for his inspiration in conducting this research. Without his guidance, I would not have been able to produce this thesis. I am also grateful to my co-supervisor, Maria E. Malmstr¨om,for her guidance and continuous support.

I would like to thank the internal quality reviewer, Professor Josepha Potting, for taking the time to read my cover essay and the appended papers in great detail. Her comments and suggestions helped me enormously to improve the quality of the thesis.

I wish to thank Professor Ronald Wennersten for giving me the opportunity to continue research interest by accepting me as a post-graduate student. In addition, I thank Monika Olsson and Karin Orve for their administrative support during my research. I would also like to thank Nils Brandt, Qing Cui, Rafael Laurenti, and Jagdeep Singh, my co-authors for Papers I-III, and Andrew Bollinger for his support in implementing the mobile phone model.

I am grateful to Industrial Ecology, KTH for the financial support to complete this thesis. I am also very grateful to some of my special friends and colleagues who helped me make this memorable journey: Rafael, Jagdeep, Joseph, Graham, Jiechen, Hossain, Hongling, Guanghong, Mauricio, Jean-Baptiste, Kosta, Daniel, Amit, Ranjan, colleagues at Industrial Ecology, and friends from all over the world who helped and supported me.

On a personal note, it would not possible for me to have my current position without the unconditional love and support of my parents and my younger brother. Finally, I am grateful to my wife for her love and sacrifice during my research.

August 28, 2014 Stockholm, Sweden

v vi Abstract

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.

vii Keywords: system dynamics, element flow analysis, industrial ecology, product systems, end-of-life, DPSIR, pressure-based driver-oriented approach, environmental manage- ment

viii Contents

Preface iii

Acknowledgment v

Abstract vii

List of Papers xi Other Publications ...... xii

List of Abbreviations xiii

1 Introduction 1 1.1 Background ...... 1 1.2 Management practices in the current system ...... 2 1.3 Metal management and tools ...... 2 1.4 Aim and objectives ...... 3

2 Thesis structure 5 2.1 Socio-economic metabolism ...... 5 2.2 Industrial ecology ...... 5 2.3 Industrial ecology and modeling complexity ...... 6 2.4 Complex systems and leverage points ...... 7 2.5 The DPSIR framework ...... 7 2.5.1 Pressure-based driver-oriented approach ...... 9 2.6 Final sinks and clean material cycles ...... 9 2.7 Material flow analysis and resource management ...... 10 2.8 Material, substance and element flow analysis ...... 10 2.9 Physical consumer goods and product systems ...... 11

3 Modeling and methodology 13 3.1 Research design ...... 13 3.1.1 Case selection ...... 13 3.2 Experiments ...... 17 3.2.1 Source-transport-storage model ...... 17 3.2.2 System dynamics model ...... 17 3.2.3 Causal loop diagram ...... 18

4 Results and discussion 21 4.1 State monitoring for pollution control ...... 21 4.2 Drivers for a proactive eco-cycle scenario ...... 21 4.3 Challenges for a resource management ...... 22

ix 4.4 The DPSIR framework and pressure-based driver-oriented approach . . 22 4.5 Application and further studies ...... 24

5 Conclusions 27

References 29

x List of Papers

Paper I Cui, Q., Brandt, N., Sinha, R., & Malmstr¨om, M. E., 2010. Copper content in lake sediments as a tracer of urban emissions: Evaluation through a source-transport-storage model. Science of the Total Environment 408(13), 2714-2725.

The author contributed to development of the model and simulation, data collec- tion, analysis, cross-checking with other type of modeling and results (not included in the paper) specifically for the Lake R˚ackstaTr¨ask.In addition, he cross-checked the calculations for other lakes.

Paper II Sinha, R., Laurenti, R., Singh, J., Malmstr¨om,M. E., & Frostell, B., 2014. Experimenting on closing the metal flow loop in the global mobile phone product system: a system dynamics modeling approach. (Manuscript).

The author was responsible for coming up with the research idea and justification for the research, modeling, data collection, analysis, and drafting the manuscript. Following several discussions with the two advisors, he was responsible for extensive revision of the paper.

Paper III Laurenti, R., Singh, J., Sinha, R., & Frostell, B., 2014. Unintended environmental consequences of purposive improvement actions: a qualitative analysis of systems structure and behaviour. (Submitted).

The author was involved in the research work and contributed to development of the causal loop diagrams, group model building discussions, results analysis, and literature survey.

xi Other publications not included in the thesis Frostell, B., Sinha, R., Assefa, G. & Olsson, L-E., 2014. Modeling both direct and indirect environmental load of purchase decisions: A web-based tool EcoRunner addressing household metabolism. (Submitted).

Singh, J., Laurenti, R., Sinha, R. & Frostell, B. 2014. Progress and challenges to the global waste management system. Waste Management & Research. doi:10.1177/0734242X14537868.

Laurenti, R., Aid, G., Singh, J., Sinha, R. & Frostell, B., 2014. Diverse stakeholder perspectives of selected environmental systems analysis tools in environmental decision-making. (Manuscript).

xii List of Abbreviations ABM agent-based modeling Ag silver Au gold CH4 methane CO2 carbon dioxide Cu copper CLD causal loop diagram DfE design for environment EPA European Protection Agency DPSIR drivers-pressures-state-impact-response EFA element flow analysis EoL end-of-life e-waste electronic waste IE Industrial Ecology MFA material flow analysis LCA life cycle analysis Pd palladium R1 research question 1 R2 research question 2 SD system dynamics SFA substance flow analysis

xiii

1 Introduction

1.1 Background

Rapid population growth, urbanization, and economic growth have given rise to material-intensive production and consumption in modern society (Frosch and Gal- lopoulos, 1989; Fischer-Kowalski and H¨uttler,1998; Fischer-Kowalski and Haberl, 1998; Tukker et al., 2008; Jackson, 2011). As a result, a linear model of consumption (produce-use-dispose) has been endorsed, with constantly increasing pressure on the environment − waste, hazardous pollutant emissions, resource depletion, resource waste, carbon emissions to the atmosphere, and many more (Meadows et al., 1972, 2004; Wenheng and Shuwen, 2008; Jackson, 2011). In response, sustainability efforts focusing on reducing unsustainability have emerged. According to Ehrenfeld and Hoffman (2013), reducing unsustainability is not the same as creating sustainability. Thus there is a need for a profound shift in values in sustainability thinking.

Society and policy makers take necessary measures on a problem when an impact to the human health or ecosystem or economy is perceived (Smeets and Weterings, 1999; Kristensen, 2004). There is a great belief that technology will provide the solution (Ehrenfeld and Hoffman, 2013). However, technology can only solve the symptoms of a problem. The technological solution is not enough. We need to find the root causes of a problem (Ruth and Davidsdottir, 2008, 2009; Jackson, 2011; Ehrenfeld and Hoffman, 2013).

The DPSIR framework (drivers-pressures-state-impact-response) encourages re- searchers to look for the drivers of a problem. The mainstream approaches to find the drivers are generally impact based, i.e., start from observation of environmental and/or biodiversity change impacts by monitoring state changes. Employing the impact-based mainstream approach to combat a problem is considered a reactive response to find the drivers. In addition, the impact-based approach can overlook other problems created by the same drivers to a potential problem. Therefore the ex- isting mainstream approach should be considered a predominantly end-of-pipe response.

Rather than the mainstream approaches mentioned above, this thesis used a proactive response to environmental problems, defined as a pressure-based driver- oriented approach. A pressure-oriented approach derived from the DPSIR frame- work was suggested by Song (2012). The pressure-based driver-oriented approach is similar to the pressure-oriented approach in that both approaches focus on the DPR (Driver-Pressure-Response) model. In addition, they are more cost-effective in terms of information systems than the reactive mainstream responses (Song and Frostell, 2012; Song, 2012). Moreover, they permit a response to both drivers and pressures. However, the pressure-based driver-oriented approach in particular focuses

1 on finding the drivers of a potential problem by modeling the pressures exerted by the socio-economic activities/metabolism. This approach is discussed in greater detail from an industrial ecology perspective in the following sections.

1.2 Management practices in the current system In recent years more attention has been paid to adopting a broader systems approach to analyzing solution strategies for environmental problems. However, little attention has been paid to date to finding the root causes of a problem (Laurenti, 2013; Singh, 2013). In modern society, systems are inter-connected and very complex. Sectoral or compartmental solutions to a problem could lead to creation of another problem. Even some intended improvement actions can lead to unintended consequences, for example energy efficiency improvements can result in rebound effects. A long-term solution to a problem requires a broader systems perspective to address the root causes of the problem. The DPSIR framework encourages the analyst to find the causal relations and understand the drivers of the pressure, the state, and the impact. This framework can also serve as a heuristic device in a resource management system (Singh, 2013). In this thesis, the DPSIR framework is used to discuss the pollution control and resource management issues.

1.3 Metal management and tools In metal management, material flow analysis (MFA) is one of the tools used for under- standing the societal metabolism. Furthermore, MFA is often used as a communication and decision support tool for environmental management (Brunner, 2004; M˚ansson et al., 2009). It supports environmental governance for sustainable polices (Hashimoto and Moriguchi, 2004; Fischer-Kowalski et al., 2011), for example by examining existing systems to support efficient resource management by establishing the mass balances and finding hotspots. In addition, an economy-wide input-output analysis (i.e., incorporating material flows with the national economy) can address national material flows (Fischer-Kowalski et al., 2011). However, economy-wide MFA is very aggregated and requires further disaggregation for actual material balance calculation (Fischer-Kowalski et al., 2011). Furthermore, incorporating economic factors in MFA is not sufficient, and integration of social aspects and identification of a proac- tive way of managing resources in a complex system are also required (Binder, 2007a,b).

Substance flow analysis (SFA) of chemical elements and compounds is based on the same principle as MFA and deals with the actual mass balance of chemical elements and compounds (Ayres and Ayres, 2002; Brunner, 2004). SFA is mainly used in accounting of pollutants (Ayres and Ayres, 2002) and is not a widely used tool for

2 resource management in a broader systems perspective (Ayres and Ayres, 2002; Wrisberg et al., 2002; Brunner, 2004). In addition, SFA represents an aggregated semantic of substance flows (i.e., it does not distinguish between chemical compounds and elements). Chemical compounds may transform into other compounds or elements during different processes in their life cycle stages. Therefore, an SFA focusing on chemical compounds is sometimes not applicable in a broader system. This thesis proposes an element flow analysis (EFA) tool which uses similar principles to SFA, but only considers chemical elements.

In this thesis, EFA is applied in both pollution control and resource management through a dynamic analysis in a broader systems perspective incorporating socio- economic parameters by addressing the following research questions:

R1. How can industrial ecology approaches, especially element flow analysis, contribute to improved control of metal pollution?

R2. In what way can industrial ecology approaches, especially element flow analysis, to examining a complex system contribute to proactive resource management?

1.4 Aim and objectives The main aim of this licentiate thesis was to experiment with industrial ecology approaches, especially EFA and modeling, in complex systems with the intention of contributing to improved pollution control and resource management. EFA was used to identify drivers for environmental management. According to the DPSIR framework, the mainstream state/impact-based approach can address the drivers of an environmental problem.

Considering the DPR model as a proactive approach (Song and Frostell, 2012; Song, 2012), this thesis focuses on a pressure-based driver-oriented approach to a problem (c.f. Figure 1 and subsection Pressure-based driver-oriented approach). In addition, it reflects a progression from a state/impact-based driver-oriented approach (Paper I) to a pressure-based driver-oriented approach (Papers II & III).

Specific objectives of the work were to analyze

• Drivers of pollution by confirming pressures through monitoring the state of the environment, using sediment element (pollutant) content as an indicator of urban diffuse emissions, and to provide a model linking diffuse sources of pollutants and their fate in a recipient, which can be used to help guide abatement of pollution (Paper I)

3 • Drivers of proactive eco-cycling for improved resource management in a complex product system, by conducting a dynamic EFA (focusing on metals used in a phone) in the global mobile phone product system to understand system effects for efficient use of resources by closing the material flow loop (Paper II)

• Root causes of a problem in a complex system for proactive resource management, by qualitatively analyzing unintended environmental consequences and thus iden- tifying underlying major sustainability challenges for physical consumer goods in a complex system (Paper III)

4 2 Thesis structure

The thesis is based on three modeling studies with different scopes in the research field of industrial ecology, conducted using overlapping industrial ecology approaches (Papers I, II, and III). The work describes the change from an impact/state-based approach to a pressure-based approach to environmental problems for improved resource management. The framework approaches are placed within the DPSIR framework. This section describes some terms, concepts, and framework approaches which are essential to understanding the results presented in subsequent sections.

2.1 Socio-economic metabolism The study of societal metabolism (Fischer-Kowalski and H¨uttler, 1998) in socio- technical systems (Pasmore et al., 1982; Clegg, 2000; Geels, 2002, 2005, 2012; Davis et al., 2013) is continuously increasing in sustainable growth discussions, analytical thinking, and policy formulation (Fischer-Kowalski and H¨uttler,1998; Fischer-Kowalski and Haberl, 1998). Research on socio-economic metabolism (e.g., material flow anal- ysis, input-output analysis) investigates physical resource flows in order to identify hot-spots and to provide suggestions for measures promoting sustainability. The sustainable development concept basically comprises the ‘triple bottom line approach’, where three partly overlapping circles (economic, social, ecological aspects) have equal weight. Following Frostell (2013), this thesis argues that ecological sustainability should be the most strongly weighted factor, because of the inter-dependency and physical metabolic interaction of the formal economy and human activities with the global system.

2.2 Industrial ecology Within the sustainability debate, industrial ecology emerged as a study field by asking why industrial systems do not imitate ecosystems?(Frosch and Gallopoulos, 1989; Graedel and Allenby, 2003; Kapur and Graedel, 2004). According to Ehrenfeld (2004a), industrial ecology is a new paradigm which has the potential to act as a game changer by achieving a breakthrough in the science of sustainability. Industrial ecology has been referred to as the science of sustainability (Ehrenfeld, 2004b, 2007; Sharpe and Agarwal, 2014).

Industrial ecology employs a metaphor analogous to the biological ecosystem, where the study focuses on material and energy flows through industrial metabolism (Graedel and Allenby, 2003; Kapur and Graedel, 2004). In ecosystems, trophic level are primary producers, herbivores, carnivores, and detritus decomposers (which

5 receive residues from any other trophic levels and regenerate materials that can again flow out to primary producers). Similarly, industrial trophic levels are extractors, producers, consumers (often at several levels), and decomposers. However, the significant difference between biological and industrial systems is that overall loss in biological system is very low, whereas in industrial systems the losses are enormous. Consequently, industrial systems extract substantial resources outside the industrial system (Graedel and Allenby, 2003, see also Chapter 4). In modern society, people generally use products and discard them, while nature closes the material loop by recycling the resources. In this societal linear consumption model (Frostell, 2013), decomposers could create a circular flow of resources by reuse and recycling. There are (relatively) few decomposers (compared with producers) in the current production and consumption system. By boosting decomposers, economic incentives and policy instruments could play an important role in creating a circular economy (Geng and Doberstein, 2008). However, within modern socio-technical systems it is very difficult to assess the outcome from a deliberate action, since it can lead to unintended consequences, for example, rebound effects (Laurenti, 2013).

Imitating nature or natural ecosystems in an industrial system requires eco-cycling, for instance, closed loop material flows in the industrial system. According to Ravetz (2000) and Eco-Cycle (2014), the concept of eco-cycling illustrates the metabolism in a socio-technical system, whereby substances or resources continuously recirculate within the metabolic industrial system (Fischer-Kowalski and Haberl, 1998; Geels, 2005, 2012). Synonymous concepts in other perspectives are described in the literature, e.g., zero waste (Eco-Cycle, 2014), cradle-to-cradle (Bollinger et al., 2012), closed loop system, industrial symbiosis, eco-park (Graedel and Allenby, 2003), and the circular economy (Geng and Doberstein, 2008). In this thesis, an eco-cycle scenario is synonymously used as a closed loop system, where technical nutrients/resources (e.g., metals) circulate in the socio-economic system without entering the lithosphere (Graedel and Allenby, 2003; Preston, 2012; Ranhagen and Frostell, 2014).

2.3 Industrial ecology and modeling complexity Industrial ecology uses some powerful tools, e.g., life cycle assessment (LCA), design for environment (DfE), MFA, and SFA, and concepts, e.g., eco-efficiency2, dematerial- ization, and decarbonization, to assess and improve products and activities (Graedel and Allenby, 2003; Kapur and Graedel, 2004). In a systems perspective, the traditional tools used in the industrial ecology society (LCA, MFA) mainly account for a defined system. This could be regarded as simply described system modeling, because it cannot include feedback loops in the modeling approach (Ruth and Davidsdottir, 2008;

2Eco-efficiency is synonymous with dematerialization which is analogous to decarbonization in en- ergy systems perspective. All three terminologies simply mean doing more with less.

6 Dijkema and Basson, 2009; Ruth and Davidsdottir, 2009; Davis et al., 2010; Bollinger et al., 2012). Practical systems − whether environmental, economic, technical, cultural, or societal − are complex and change with time and space. DfE and LCA analysis undoubtedly help in making a product or service better for the environment. However, their lack of inclusion of the systems linking technology, society, and the environment may counterbalance the benefits achieved by these analytical approaches.

2.4 Complex systems and leverage points For understanding complex systems, a comparison between simply described system and complex systems could give an insight to system behavior. According to Graedel and Allenby (2003), simply described systems behave in a linear way, while complex systems are generally nonlinear, sometimes show an abrupt response to a minor change (i.e., leverage), and often evolve with time and space. Even though a simple system sometimes behaves non-linearly (e.g., plant growth), description of such a system usually takes a linear approach. In a simply described system, action can easily be detected by following the cause and its associated effects. On the other hand, the link between a cause and its effect is often difficult to establish in complex systems because of their complex interrelations and dynamics (e.g., positive/negative feedback effects).

A leverage point in a complex system can be described as when a small change in a parameter value leads to a large shift towards the goal or a target parameter (Meadows, 1999). A leverage point approach is generally used in systems dynamics modeling and simulation to achieve better performance. In a complex system, this approach explores various possible scenarios and strategies to intervene in the system and is useful in testing policies and investments (Meadows, 1999; Sterman, 2000). In this thesis, the leverage point approach is used to find the most significant potential drivers for proactive resource management.

2.5 The DPSIR framework The DPSIR framework is a conceptual model of a chain of causal relations between human systems and environmental systems (Smeets and Weterings, 1999; Kristensen, 2004). Figure 1 shows the DPSIR framework from a broader systems perspective in resource management and pollution control.

The DPSIR framework can be used to help structure the complexity involved with multilevel modeling of a system (Ness et al., 2010), in order to identify the drivers of a problem. Mainstream DPSIR studies mainly adopt a state/impact-based approach to find the drivers of a problem. In general, the societal and political responses (according to DPSIR) to a problem are elicited from the impact on human health, ecosystems,

7 or the economy. The European Environmental Agency (EEA) uses this framework for monitoring and reporting the state of the environment and for policy measures (Kristensen, 2004). In such work, indicators (physical, biological, or chemical) are used as a communication tool to policymakers (or society), to inform them about the seriousness of an issue (Smeets and Weterings, 1999).

Figure 1: The driver-pressures-state-impact-response (DPSIR) framework from a broader systems per- spective in resource management and pollution control (Smeets and Weterings, 1999; Kristensen, 2004). Dark rectangles represent different DPSIR phases. Thick arrows show the causal links, thin arrows illustrate the political and social responses to different DPSI phases, and dashed arrows (additional recommendations to the DPSIR framework) are proposed to take responses based on different DPS indicators. The lighter background represents a driver-pressure-response (DPR) model − a pressure- oriented approach (Song, 2012).

Although the DPSIR framework is widely used in the environmental domain to find the drivers of a problem and to communicate the results, it faces the following problems (Rekolainen et al., 2003; Carr et al., 2007; Svarstad et al., 2008; Song, 2012; Song and Frostell, 2012):

• The mainstream DPSIR approaches employ static indicators, without considering the dynamics of the systems under discussion.

• DPSIR approaches sometimes demonstrate unclear understanding of the causal relationships in a complex system and drivers for change.

8 • DPSIR approaches mainly focus on measurable indicators for the evaluation of environmental issues and regularly report these.

• Little attention is paid to response to drivers and pressures (proposed dotted arrows in Figure 1) in the DPSIR framework.

Song (2012) distinguished between two environmental management approaches based on the DPSIR framework: (i) state/impact-oriented and (ii) pressure-oriented. According to the state/impact-oriented approach, societal responses are elicited from changes in the environmental state and their impacts through environmental and/or ecological state/impact monitoring. The pressure-oriented approach takes responses based on monitoring pressures exerted by the socio-economic drivers. In other words, the pressure-oriented approach corresponds to the DPR framework, i.e., management efforts focusing on drivers, pressures, and responses to socioeconomic metabolism (see lighter background in Figure 1). According to the latter approach, additional recommendations to the DPSIR framework (dotted arrows in Figure 1) are proposed to understand drivers and pressures which could lead to potential impacts. In principle, the pressure-oriented approach could lead to a proactive policy and decision response by establishing a pressure-oriented monitoring system (Song, 2012; Song and Frostell, 2012).

2.5.1 Pressure-based driver-oriented approach Instead of following the mainstream DPSIR approaches, the pressure-oriented approach was adopted in this thesis work, which was based in principle on modeling pressures to take proactive responses to drivers and pressures rather than reactive responses to states or impacts. However, additional emphasis was placed on identifying drivers based on the pressures. Therefore, a pressure-based driver-oriented approach was employed. This approach is further discussed together with research questions and the results of Papers I-III in Chapter 4.

2.6 Final sinks and clean material cycles The final sinks and clean material cycles concepts (Brunner, 2004; Kral et al., 2013) of a pollutant were taken to represent the concentration of a pollutant which nature can absorb without any side-effects on the environment (i.e., geogenic concentration). Another type of man-made safe sink would be safe storage over time (Brunner, 2004; Kral et al., 2013). On the other hand, clean material cycles (Kral et al., 2013) represent resource circulation in the socio-economic system without emitting hazardous substances. In Papers I-III, the clean material cycles concept was applied in eco-cycle thinking approaches. Brunner (2004) and Kral et al. (2013) propose integrating the

9 final sink and clean material cycles concepts in the design consideration of introducing secondary resources (e.g., physical consumer products) to the anthroposphere.

2.7 Material flow analysis and resource management In this thesis, the term resources refers to physical resources, e.g., materials, energy. Resource management includes systems analysis, planning, and allocation of resources, and optimization and improvement of the technology associated with resource con- servation. MFA plays an important role in analyzing the system to understand the potentially harmful/beneficial sources, draw up priorities for environmental protection and resource conservation, and plan for allocation of resources. Here, MFA served as the backbone for physical resource management by coupling the front (resource deple- tion) and back (disposal) ends of the anthropospheric system through anthropogenic stocks (forecasting resource accumulation from nature to the anthroposphere).

2.8 Material, substance and element flow analysis Material flow analysis is a systematic assessment of the flows and stocks of material within a system defined in space and time (Brunner, 2004). It deals with a combination of different goods, substances and elements, which have positive and negative economic values (Ayres and Ayres, 2002; Brunner, 2004). Substance flow analysis deals with the flows consisting of chemical compounds and elements. Element flow analysis only deals with chemical elements. A comparison of MFA, SFA, and EFA is shown in Table 1.

Table 1: Differences between material flow analysis (MFA), substance flow analysis (SFA), and element flow analysis (EFA)

MFA SFA EFA Goods (e.g., biomass) Compounds (e.g., CO2, CH4) Compounds Elements (e.g., Cu, Au, C) Elements Elements

To be consistent with the semantics, EFA was used here rather than SFA when the analysis focused only on chemical elements (since SFA cannot differentiate between chemical elements and compounds). In addition, an element is generally not destroyed or transformed throughout the whole system and therefore it can be considered a conservative unit. Furthermore, EFA can integrate comprehensive systems by taking a broader systems perspective of an industrial value chain, following the principle of conservation. Thus, EFA enhances the power of MFA and SFA in a complex system

10 aimed at improved resource management by allowing a clearer analysis of industrial metabolism. However, EFA is confined to elements and thus does not cover substances of environmental concern. For example, benzene, toluene, ethylbenzene, and xylenes (BTEX) cannot be accounted for by EFA. In this thesis, EFA was applied in estimating copper pollution in the Stockholm region (Paper I) and in metal management in a physical consumer good product system (Papers II and III).

2.9 Physical consumer goods and product systems Physical consumer goods are vehicles, computers, mobile phones, etc. A product system entails the infrastructure and associated necessary services, but also the activities related to life cycle phases − design, manufacture, transport, consumption, and end-of-life of a product. Physically, the product system includes raw material extraction, production, maintenance and distribution network, utilization, material recycling, and waste treatment. On an intangible level, markets (price and demand elasticity), consumption patterns and user preferences, costs of manufacturing, recovery and export, purposes, function, and objectives, consumer awareness, and economic growth rate are also parts of the product system.

11 12 3 Modeling and methodology

3.1 Research design The overarching research design used in Papers I-III comprised a broad systems approach and consideration of complexity in the cases of pollution control and resource management. On the pollution control side, historical research and practice generally point out the reactive solution to a problem, for instance restoration of a lake by cleaning out the pollutants (Peterson, 1982). In Papers I-III, attempts were made to find solutions in a proactive way by identifying the root causes of a problem. Such proactive resource management encompasses a life cycle thinking approach (Frostell, 2013) that considers design, raw material extraction, production, consumption, and end-of-life, incorporating both social and economic issues.

Figure 2 shows the conceptual research design and the system boundaries of the work described in this thesis. The core of the work was to map element flows in a complex system in order to provide recommendations for pollution abatement and efficient use of resources. For mapping pollutant flows (see Figure 2), the fate of a pollutant was coupled with its sources, focusing on a single pollutant, incorporating both point and diffuse sources of emissions from different products or services or activities (Paper I). For resource management, the work concentrated on physical consumer goods (Paper III; product type 1 in Figure 2), deepening the analysis into a mobile phone product system (Paper II).

Table 2 summarizes Papers I-III and their contributions to answering research questions R1 and R2 and to extending the DPSIR framework. Paper I evaluated a source-transport-storage model by linking point and diffuse sources of a pollutant and its fate in a recipient in order to help guide abatement of the pollution. Papers II and III explored research question R2 on proactive resource management. Paper II examined the drivers and system behaviors for proactive eco-cycling in a mobile phone product system. Paper III qualitatively analyzed the unintended consequences of an improvement action and the sustainability challenges of physical consumer goods through causal loop diagrams. The DPSIR framework was then applied to the results in a proactive approach to identify the root causes of problems. This revealed that Paper I used a mainstream state-based driver-oriented approach to identify drivers by confirming copper emissions through state monitoring as sediment copper concentration. Papers II and III used a pressure-based driver-oriented approach.

3.1.1 Case selection The source-transport-storage model was applied in a subcatchment area of the Stockholm region, where there are elevated levels of copper (Cu) in surface waters,

13 Figure 2: Conceptual research design and system boundaries of the work described in this thesis. The rectangle and square with solid thick lines are the system boundaries for research questions 1 (R1) and 2 (R2), respectively. Dotted lines and dotted lined rectangles were beyond the scope of the thesis. Arrows (straight and curved) represent the flow of resources (with the possibility of recovery, a pollutant is considered a resource) and information. sediment, soil, and groundwater (Sinha, 2009). Every year, the supply of copper to Stockholm is approximately 2300 tonnes and approximately 120 000 tonnes of copper are present in Stockholm as products/materials (Sinha, 2009).

The metal contents in the uppermost sediment layers of lakes around Stockholm are frequently monitored and reported (Stockholm Stad, 2014). Sediment metal levels in these lakes are elevated, despite the fact that local industries have been moved out of the drainage area, for example in the case of Lake Trekanten (Cui, 2010). Sources of copper emissions to the aquatic environment and the fate of the copper emissions in the lakes were analyzed. The aim was to identify the reasons for the high sediment copper content and to test the hypothesis ‘Sediment copper content can predict sources of emission. Therefore, the Stockholm region was selected to apply this model.

14 Table 2: Research questions R1 and R2 and the contribution of Papers I-III to the DPSIR framework and pressure modeling

In Papers II and III, product systems of physical consumer goods were studied in a broader systems perspective to gain insights into challenges to improved resource management. Among various physical consumer goods, a mobile phone product system was selected for further investigation of proactive ecocycling because of the complex processes of production, consumption, and end-of-life. The following aspects also made this system an interesting study object:

• Over 40 elements in the periodic table are present in a mobile phone (Kuehr, 2012; Schluep et al., 2009). Among these elements, on average 23% are metals (Schluep et al., 2009), mostly copper and a small amount of precious metals, e.g., gold (Au), silver (Ag), palladium (Pd) (Paper II). According to Williams et al. (2013), mobile phone circuit boards contain a higher economic value of metals than other types of circuit boards in electronic products, for example video cameras, LED TVs, etc. Table 3 shows the range and abundance (natural reserve) of materials used in mobile phones and the recovery potential from mobile phones relative to global production of virgin materials in 2012. Around 8% of the gold and 16% of the silver produced world-wide were used in mobile phones in that year. Gold and silver are very rare materials and according to Graedel and Allenby (2003), the global reserves may be depleted in less than 25 years with the current consumption rate.

• Due to rapid technological improvements and innovations, the life span of a mobile phone is becoming ever shorter (Basel Convention, 2008; Kuehr, 2012; Tischner, 2012; Herat and Agamuthu, 2012). In the industrialized countries, the working life

15 of a new mobile phone is on average 1.5 years, although the technical lifetime of a phone is approximately 8 years (Bollinger, 2010).

• Discarded mobile phones are rapidly increasing in rich countries (referred to here as industrialized countries) such as the USA, Australia, and European countries (Panambunan-Ferse and Breiter, 2013). In industrialized countries, less than 20% of the phones discarded are properly managed (Bollinger et al., 2012; Umair et al., 2013). Discarded phones from these countries sometimes find a cheap route (some- times illegal; see BBC (2011)) to developing countries, for example Ghana or Pak- istan (Umair et al., 2013). There, they often end in landfill after crude informal recycling, for instance by manual dismantling (often with bare hands) or open burning (Panambunan-Ferse and Breiter, 2013; Umair et al., 2013).

Table 3: Recovery potential of various materials from mobile phones compared with world production of virgin raw materials

Material Annual production Material used in % used Abundance4 (Graedel and (tons) (Basel Con- phones (tons)3 for mobile Allenby, 2003) vention, 2013) phones Steel, iron 1300000000 53000 0.00 Abundant (tD > 100yr) Aluminum 22000000 52000 0.23 Abundant (tD > 100yr) Copper 16000000 95000 0.59 Constrained (tD = 25 − 50yr) Tin 270000 5700 2.20 Plentiful (tD = 50 − 100yr) Silver 20000 3200 16.00 Rare (tD < 25yr) Gold 2500 190 7.60 Rare (tD < 25yr) Palladium 220 280 130.00 Plentiful (tD = 50 − 100yr)

Paper III used physical consumer goods as a case study in identifying root causes of a problem. The mobile phone product system (Paper II) is part of the whole set of physical consumer goods. Paper II used an eco-cycling approach to enhance a circular economy, but only focused on modeling the pressure of resource leakage. Moreover, Paper II did not analyze many important pressures, e.g., emissions, over consumption. Technological advances and innovations sometime make products cheaper. For example, as industrial production becomes more efficient, lower energy or material requirements per unit production make the product cheaper. This frequently results in increased consumption (a rebound effect; Paper III). A similar phenomenon occurs with several other products. Therefore, in Paper III the analysis was extended from specific product to general product level to address unintended consequences of an improvement action. As Paper III illustrates, the product systems of physical consumer goods are very

3Estimated in this study as: Material used in phones = P hone subscriptions in 2012 ∗ Material used in phones∗100 material content in a phone and % used for mobile phones = Annual production 4 tD represents the depletion of resources under the constant current use rate

16 comprehensive and it is highly challenging to identify the root causes of a problem and related pressures.

3.2 Experiments 3.2.1 Source-transport-storage model The source-transport-storage model (Paper I) was developed to identify drivers by confirming pressures through state monitoring. The model was based on EFA and designed to predict the sources of emissions by coupling the urban point and diffuse sources to the sediment copper content in the case study lakes. The EFA covered copper emissions from the urban metabolism and the fate of copper in neighboring lakes. In the study, the geographical system boundary was defined as a lake and its drainage area. The conceptual model focused on various water transport pathways and atmospheric deposition. The model was applied to five lakes and their catchment areas in the Stockholm region.

In the drainage areas of Stockholm lakes, copper is widely used in materials and goods in daily life, for example copper roofs, water pipes, and brake linings of vehicles. Copper is emitted to the environment from these materials and goods during their use period due to weathering and wearing processes. The eroded/emitted copper travels to lakes through different pathways (Paper I). When copper reaches the lake, it is distributed between the dissolved phase and particles. Part of the copper is then transported downstream by the water flow and part of it settles and accumulates in the sediment. A static quantification of copper flows was conducted in Paper I to estimate the source strength. The subsequent fate of copper in the lakes was analyzed by dynamic modeling and simulation. The modeling incorporated the complexity in the aquatic system (e.g., internal loading). In addition, it displayed the outcome in a time series to compare the modeling results with monitored copper concentrations in the sediment over time.

3.2.2 System dynamics model In Paper II, a dynamic element flow model with a life cycle perspective was developed to investigate possibilities for closing the material flow loop by identifying potential drivers in the global mobile phone product system. The starting point was system dynamics modeling and simulation (Sterman, 2000). The elements considered in the study were precious or economically viable (in terms of recovery) metals: copper, gold, silver, and palladium.

The overarching model encompassed the global mobile phone product system, dividing it into two main domains: industrialized countries and developing coun- tries, connected through the export and import of used phones at their end-of-life. Eco-cycling as a principle of industrial ecology, i.e., a symbiotic relationship between

17 different actors, was identified and modeled in the product system. Collection processes for used phones at their end-of-life stage can play an important role in closing the consumption loop by allowing reuse, refurbishment, or recovery of parts, and were therefore included in the model.

In the model, an element/metal (Cu, Ag, Au, Pd) in a phone flows through the product system. In Paper II, economics was considered the driving force for phone flows in the global product system, where the consumer plays a central role in initiating the demand for new phones and for used/refurbished phones at their end-of-life. According to economic principles, investors invest to expand their business when the expected profit from the investment is positive, and vice versa.

In the model, a closed loop is defined by two loop indicators: loop leakage and loop efficiency. Loop leakage indicates the extent to which the loop is closed by determining the amount of resources leaving the product system. Loop efficiency indicates how efficiently the resources are utilized in the system, including the ‘hibernation of resources (for example, putting phones in drawers for a long time without any use).

In the study, a sensitivity analysis was conducted to identify the drivers for closing the material flow loop in the product system by increasing (or decreasing) one parameter by up to 100% while keeping other parameters with their default values. Based on the driving forces (i.e., drivers or leverage points in Paper II), an eco-cycle scenario for the global mobile phone product system was proposed for proactive resource management.

3.2.3 Causal loop diagram The static and dynamic modeling generally used in industrial ecology aims at quanti- fying states and pressures. In contrast, Paper III attempted to qualitatively analyze root causes of unintended consequences from a systems thinking perspective. Causal loop diagram (CLD) modeling was applied to qualitatively determine a problem’s root causes or drivers, terms which are used synonymously in the following. In a CLD, parameters or system state variables are connected by a causal relationship with arrows with a polarity denoting either positive (+) or negative (−) feedbacks, to indicate how the cause (at the arrow tail) changes when the effect (at the arrow point) changes. Forming feedback loops in a CLD is the basis for qualitatively an- alyzing the inter-relationships and finding leverage points by identifying the root causes.

In a broader systems analysis, qualitative analysis with the help of CLD can cover more socio-economic aspects than a quantitative approach, e.g., because of data availability. Therefore, a qualitative approach such as CLD is a preliminary stage of analyzing and framing an issue by addressing important systems and pa- rameters to be considered for further analysis in a quantitative way (if required).

18 In addition, CLD is a prior stage of quantitative system dynamics modeling and simulation (Sterman, 2000). Furthermore, it can illustrate material flows (and element flows as well) throughout the systems. Thus, CLD has the potential to bridge between qualitative and quantitative variables (Laurenti et al., 2014). It also makes for a better understanding of causal relations between material flows and other parameters.

The CLD model used in Paper III illustrated the unintended consequences of an im- provement action (the rebound effect of increased consumption) and the resulting chal- lenges from an overarching systems thinking point of view. Systems thinking method- ology was utilized to find the root causes of the unintended consequences through addressing the engine of economic growth, externalities-consumer costs, and social and environmental ripple effects (Paper III).

19 20 4 Results and discussion

4.1 State monitoring for pollution control Paper I developed and applied the source-transport-storage model in five lakes in the Stockholm region and evaluated whether sediment copper content could be used to identify the diffuse sources of urban copper emission and thus improve pollution control through recipient monitoring. The results showed that the simulated copper concentrations in the sediment agreed reasonably well with the monitoring data on considering the model uncertainty for three lakes (Trekanten, R˚acksta Tr¨ask and L˚angsj¨on). However, for the other two lakes studied (Laduviken and Judarn), predicted sediment copper concentrations were higher than the observed values. This discrepancy was attributed to stormwater management in the lake catchment and the distance of the lake from the urban activities (for more information see Paper I). It was concluded that a source-transport-storage model is applicable to predict the sources of elevated copper concentrations in the sediment of heavily copper-polluted lakes.

Paper I provides some suggestions on how this model could help guide policy makers to control copper pollution in an urban region by assessing the safe sink concept. For Lake Trekanten, the model evaluated the acceptable copper load from urban activity to that specific lake according to the environmental quality standards on lake sediment and recommended a decrease in urban copper emissions of 70% to reach the quality standard. The model also indicated that decreased traffic activities and avoiding the use of copper roofs in the catchment region could be used to achieve acceptable loading in Lake Trekanten (Paper I).

4.2 Drivers for a proactive eco-cycle scenario Paper II identified drivers for closing material flow loops (focusing on economically recoverable metals used in a mobile phone) in the global mobile phone product system from a proactive resource management perspective. The sensitivity analysis showed that the drivers towards closing the metal flow loop and improving loop efficiency were: (i) accessibility of collection pathways, (ii) mobile phone use time in industrialized and developing countries, (iii) gold recovery in developing countries, and (iv) mobile phone hibernation in both industrialized and developing countries. Other parameters, for example, utility of a refurbished phone, manufacturing cost, export cost, displayed very small changes (relative to a huge shift in their default values) towards closing the loop. These parameters achieved a steady state in a very short time. Furthermore, there was a negligible contribution from the parameters towards closing the material flow loops in a long-term perspective (Paper II).

According to the modeling results, current mobile phone product systems are very

21 unsustainable. Approximately 50% of valuable resources leave the system and the loop efficiency is around 30% (see closed loop indicators in section 3.2.2). At the same time, system leakage is continuously increasing and resource efficiency is decreasing. Based on the drivers discussed above, Paper II proposed an eco-cycle model of the global mobile phone product system for closing the material flow loop efficiently. The eco-cycle based scenario indicated that pressure on resources could be lowered by decreasing the resource demands for production and increasing resource recovery at the end-of-life of the product. The study found approx. 5% loop leakage and approx. 95% loop efficiency at steady state by tuning the drivers (Paper II). Based on the analysis, incorporation of a proactive approach was recommended in resource management considering a holistic system for a long-term solution.

4.3 Challenges for a resource management Paper III investigated root causes of unintended environmental consequences to identify underlying major sustainability challenges in a complex product system from a systems thinking perspective. The methods used in industrial ecology for providing decision support do not produce expected outcomes all the time. For ex- ample, dematerialization and increasing energy efficiency of a product, a conventional improvement option for resource management, can have unintended environmental consequences in terms of consumption rebound effects, increased waste, pollution, negative externalities, and other environmental and social negative impacts. These problems are inter-linked within a cause-effect chain and one problem can trigger others.

To find the leverage points for improved management in this complex product system, a broader systems approach was applied to understand and identify the reinforcing and balancing loops towards the expected outcomes. Using the CLD, Paper III showed how unintended environmental consequences could occur as a result of improvement actions. From the analysis, it was possible to conclude that CLD is a powerful tool for achieving a deeper understanding of the long-term consequences of improvement actions (in resource management), by considering complex economic- environmental-social issues and the dynamics among the systems and interventions at multiple levels. In addition, Paper III found that the appropriate approach to intervene in complex systems must combine qualitative and quantitative aspects with systems thinking capabilities in order to identify drivers.

4.4 The DPSIR framework and pressure-based driver- oriented approach Society and policy makers take measures on a problem when judged necessary as a result of monitoring impacts and changes in the state of the environment (Kristensen,

22 2004). This state and impact based approach has developed during the last few decades and is now deeply rooted in practice. A later and more fundamental approach to finding the root causes of a specific problem is the European DPSIR framework. In Papers I-III, the DPSIR framework was used as a decision support and heuristic tool to investigate solutions by identifying drivers both for pollution abatement and resource management. In pollution control (Paper I), state monitoring was linked to catchment metabolism to identify drivers of the pollution. Furthermore, a proactive approach (focused more on drivers /root causes) was applied in resource management (Papers II and III).

With a pressure-based approach, responses are elicited based on the pressures from the societal metabolism. Studies advocating a pressure-based approach have already proven that some state changes arise from increased pressure, for example increasing CO2 emissions to the atmosphere causing climate change (Solomon et al., 2009). Furthermore, some pressures are self-explanatory, for example, nonrenewable resource use. On the other hand, some pressures are invisible until impacts on the environment, economy, or society make it necessary to make a response. In these cases, responses can be delayed until the state of the environment indicates future possible impacts.

Paper I helped identify drivers by confirming pressure through monitoring the state of the environment by applying the source-transport-storage model. More specifically, it showed that sediment copper content of a lake can be used as a tracer of urban point and diffuse sources of emission, as well as an identifier of the driving forces for making a response. Acknowledging the pressure-oriented approach devised by Song (2012), Paper I recommends taking responses by recognizing the pressure beforehand (not waiting for the impact ) for long-term proactive solutions.

According to the DPSIR framework, Paper I used a state/impact-based (or main- stream) approach to find the drivers. This approach is detailed in modeling the specific environmental systems, but lacking in modeling the socio-economic system for interventions to innovate/change in a sustainable way. In addition, the approach is not sufficiently holistic to grasp the whole picture. Such a spatially explicit modeling approach hampers the inclusion of upstream and downstream relations between economic drivers (i.e., between production processes and human behaviors preceding these). Upstream-downstream approaches to life cycle processes are, of course, not new, as they underlie LCA and MFA approaches. However, these typically do not relate to the DPSIR. Paper I attempted to connect the LCA/MFA approaches to the DPSIR in order to recognize the drivers and take action proactively.

In a proactive approach, Papers II and III used the pressure-based driver-oriented method to identify drivers. Understanding the drivers in interrelated systems across different scales and levels is crucial to exploring appropriate responses towards a

23 sustainable solution (Ness et al., 2010; Singh, 2013). When investigating solutions in a complex system, feedback loops (Papers II and III) and internal dynamics over time (Paper II) play the most important roles. Binder (2007a,b) suggested integrating social and economic parameters coupled to material flow modeling in decision support of resource management to investigate the appropriate solution in a complex situation. To that end, Paper II included quantitative dynamic element flow modeling, integrating social and economic parameters, in a complex product system to understand the drivers and system effects for efficient use of resources by closing the material flow loop as a principle of industrial ecology (i.e., eco-cycling). In addition, Paper III qualitatively analyzed unintended environmental consequences of targeted actions for improvement and investigated underlying major sustainability challenges of physical consumer goods in a broader systems perspective.

Modification of identified drivers is essential in the design phase of a product. To decrease the environmental pressures, products or services should be designed to have a predefined final sink for elements and strive for clean material cycles. As an example, if there is no safe sink for an element in a product, it should be replaced by a material which has a safer sink in the end-of-life phase (Brunner, 2004; Kral et al., 2013). Thus, design could be considered a most important top driver in the DPSIR framework for making a response. Therefore, a proactive approach in the design stage of a product or a service is essential for pollution abatement and sustainable resource use.

4.5 Application and further studies Source-transport-storage models could be applicable for other metal pollutants, for predicting diffuse and point sources of emission in an urban area by monitoring aquatic sediment concentrations. The source-transport-storage model could be worth testing in a more complex aquatic system and used for chemicals other than metals.

Causal loop diagrams could be used in system characterization and potential problem identification. This method could be very useful in an early stage of development of a product to proactively design the product and associated services. The CLDs presented in Paper III could also be used in a real case for single products, both qualitatively and quantitatively e.g., system dynamics modeling and simulation. The system dynamics model used here for global mobile phone product systems could be applicable in other e-waste related products and other physical consumer products. However, the proposed eco-cycle model needs to be optimized further as regards its parameter settings, since a semi-optimization method (trial and error methods for tuning the potential drivers) was used in its development (Paper II). Furthermore, the system dynamics model contained some soft parameters, which could be modeled in another type of modeling approach, agent-based modeling (ABM). Due to difficulties in modeling bounded rationality in a system dynamics approach, ABM could model individual stakeholders actions effec-

24 tively. Here, multi-method modeling techniques (i.e., combining SD and ABM) would be an effective tool to implement the soft parameters and bounded rationality of actors, model technological advances, and test the policy instruments towards a goal. Finally, multi-method modeling approaches could be applied for urban metabolism to study symbiotic actions of different stakeholders in order to form a closed material flow loop.

25 26 5 Conclusions

The aim of this licentiate thesis was to identify ways in which industrial ecology approaches, especially element flow analysis and modeling in a complex system, could be used to improve pollution control and proactive resource management. The most essential methodological contribution of the thesis was to conduct element flow analysis in a dynamic way, which was able to demonstrate the issues over time, integrating the dynamics and interrelations between different systems and actors. This analysis was used in the context of pollution control and resource management, incorporating the DPSIR framework as a heuristic and decision support. The following responses were obtained to the two initial research questions (R1, R2)

R1. How can industrial ecology approaches contribute to improved control of metal pollution?

Conventional quantification of pollutants through SFA/EFA focuses either on source estimation or pollutant fate, e.g. in a lake. Paper I bridged this gap by linking the source and fate of a pollutant through EFA and dynamic modeling to identify actions on drivers for improved pollution abatement. A source-storage- transport model was used to determine the origin of pollutants in aquatic sediments by linking two element flow models: (i) an accounting model of the pollutant sources and (ii) a dynamic model of the pollutant fate in a lake. Application of the model to evaluate copper pollution in five lakes in the Stockholm region revealed that the source strength agreed well with simulated sediment copper concentra- tions. This model can be recommended for predicting the sources of pollutants identified by aquatic monitoring and taking action to deal with the sources of the emissions. However, the model results are affected by urban stormwater manage- ment. According to the DPSIR model, the responses to pollution can be applied at source and in the sink (lake). However, taking action at source is recommended to obtain a safe sink.

27 R2. In what way can industrial ecology approaches, especially element flow analysis, to examining a complex system contribute to proactive resource management?

Finding the drivers by monitoring the state of the environment could contribute to proactive pollution control. However, monitoring of state is not enough for proactive resource management, which requires a driver-oriented approach and a broader systems approach to capture scales and levels of interaction. Improved resources management could also lead to improved pollution control.

Element flow analysis mainly deals with the mass balance of elements, while economy wide input-output analysis can capture the material flows within the economy, but does not address the drivers for sustainable production and consumption. This requires the integration of social aspects with the flows. In addition, to find the drivers in a complex system, a dynamic analysis is essential, where feedback loops help identify an effective solution by finding the leverage points and where to intervene in the system.

Paper II investigated the drivers (including socio-economic aspects) through a systems dynamic approach in EFA of the global mobile phone product system, where closing metal flow loops was used as an indicator of proactive eco-cycling for efficient resource management. The analysis showed that the current global mobile phone product system is very unsustainable in terms of resource efficiency (approx. 35%) and resource leakage (approx. 50%). Potential drivers towards closing the material flows in the system include e.g., mobile phone use time and accessibility of collection pathways. An eco-cycle scenario, where loop leakage is approx. 5% and resource efficiency around 95% at steady state, could be achieved by tuning the drivers.

Paper III qualitatively investigated unintended environmental consequences of measures to address underlying major sustainability challenges to efficient resource management in terms of physical consumer goods and their product systems. It incorporated a broader systems approach to identify the root causes of problems.

Based on the overall results, a pressure-based driver-oriented approach can be recommended for proactive resource management. Within the DPSIR framework, design stage of a product could be considered one of the most important drivers for a response.

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