Gerard P.J. Dijkema

Process Knowledge, System Dynamics, and Metal Ecology

A key principle in industrial ecology is the cyclic use of materials, a characteristic of natural ecosystems but a challenge in economic systems. Indeed, in society, metal retention, that is, the ongoing use or ready availability of metal in the economy between the life-cycle stages of resource extraction and final disposal back into the lithosphere, is finite because of the limited grade of secondary (recycled) metals. Currently, the utility of metals is maintained through the addition of high primary (virgin) metals, bringing the concentration of the recycled metals to desired levels. This mixing with high-grade primary metals keeps these recycled metals in the cycle. Long term, this practice of dilution of the undesired substances prevents a closure of the material cycles, whereas recovery without dilution reduces the quality (or quantity) of recycled metals. Metals participate in a system of linked cycles and thus cannot be produced or recovered independently from one another. The metal wheel is introduced in this article as a concise but powerful instrument for the communication of available process knowledge in process metallurgy, the science and technology of producing metals from natural ores and societal raw materials, residues, and end-of-life products. It summarizes the chemical and physical linkages between metals found in ores and the set of metallurgical processes that has been developed to accommodate these linkages. A dynamic mass-flow model is introduced to characterize the global metal cycles. The model facilitates the visualization of the evolution of their structure and technological content. To illustrate the interdependency of metal cycles using the metal wheel and the dynamic model, the transition to lead-free solder is evaluated. Neglect of metal-cycle linkages and dynamics in policy formulation may lead to a shortage of lead substitutes. In case of an extended ban on lead, both the availability and recovery of a range of metals will be affected.

Industrial Ecology 2.0

Industrial ecology (IE) is an ambitious field of study where we seek to understand systems using a wide perspective ranging from the scale of molecules to that of the planet. Achieving such a holistic view is challenging and requires collecting, processing, curating, and sharing immense amounts of data and knowledge. We are not capable of fully achieving this due to the current state of tools used in IE and current community practices. Although we deal with a vastly interconnected world, we are not so good at efficiently interconnecting what we learn about it. This is not a problem unique to IE, and other fields have begun to use tools supported by the World Wide Web to meet these challenges. We discuss these sets of tools and illustrate how community driven data collection, processing, curation, and sharing is allowing people to achieve more than ever before. In particular, we discuss standards that have been created to allow for interlinking of data dispersed across multiple Web sites. This is currently visible in the Linking Open Data initiative, which among others contains interlinked datasets from the U.S. and U.K. governments, biology databases, and Wikipedia. Since the types of technologies and standards involved are outside the normal scope of work by many industrial ecologists, we attempt to explain the relevance, implications, and benefits through a discussion of many real examples currently on the Web. From these, we discuss several best practices, which can be enabling factors for how IE and the community can more efficiently and effectively meet its ambitions - an agenda for Industrial Ecology 2.0.

Understanding the Evolution of Industrial Symbiosis Research: A Bibliometric and Network Analysis (1997-2012)

This study analyzes the evolution of the research field of industrial symbiosis (IS). We elucidate its embedding in industrial ecology (IE), trace the development of research themes, and reveal the evolution of the research network through analysis of the core literature and journals that appeared from 1997 to 2012 by citation analysis, cocitation analysis, and network analysis. In the first period (1997–2005), IS research held a minority share in the IE literature. The research revolved around the concept of IS, the assessment of eco‐industrial park projects, and the establishment of waste treatment and recycling networks. In the second period (2006–2012), diverse research approaches and theories enriched the field, which has led to a maturation in theory building. Our findings clearly illustrate that IS evolved from practice‐oriented research toward coherent theory building through a systematic underpinning and linking of diverse topics. As scientific attention shifted from exploring a phenomenon to elucidating underlying mechanisms, IS knowledge found worldwide practical implementation. The coauthorship network shows that the academic communities of IS are distributed worldwide and that international collaboration is widespread. Through bibliometric and network analysis of IS, we have created a systemic, quantitative image of the evolution of the IS research field and community, which gives IS researchers an underpinned overview of the IS research and may help them to identify new directions and synergy in worldwide research.

MAIA: a Framework for Developing Agent-Based Social Simulations

In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostroms Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experience and knowledge of software development knowledge and skills. MAIA has been developed to help modellers who are unfamiliar with software development to conceptualize and implement agent-based models. It provides the foundation for a conceptualization procedure that guides modellers to adequately capture, analyse, and understand the domain of application, and helps them report explicitly on the motivations behind modelling choices. A web-based application supports conceptualization with MAIA, and outputs an XML file which is used to generate Java code for an executable simulation.

Agent-based modelling of energy infrastructure transitions

Transitions emerge over time as fundamental change of large-scale socio-technical systems such as energy infrastructures that are the backbone of society. To date, however, the body-of-knowledge on energy infrastructure transitions is largely descriptive. Transition management, however, does have a prescriptive character - not only can we understand transitions, we can also shape them. This implies technical system design is augmented with policy, regulation, R&D strategies: some coherent all-inclusive set of transition instruments or transition assemblage. We conjecture a transition management strategy may equate to collaborative design of such a transition assemblage. Using foundations of complex systems theory, agent-based modeling, engineering and policy design scenario analysis, design of experiments and statistical data analysis, a modeling framework has been developed that enables ex-ante assessment of alternative transition assemblage design-alternatives.

Modeling Metal Flow Systems

Substance flow analysis (SFA) is a frequently used industrial ecology technique for studying societal metal flows, but it is limited in its ability to inform us about future developments in metal flow patterns and how we can affect them. Equation‐based simulation modeling techniques, such as dynamic SFA and system dynamics, can usefully complement static SFA studies in this respect, but they are also restricted in several ways. The objective of this article is to demonstrate the ability of agent‐based modeling to overcome these limitations and its usefulness as a tool for studying societal metal flow systems. The body of the article summarizes the parallel implementation of two models - an agent‐based model and a system dynamics model - both addressing the following research question: What conditions foster the development of a closed‐loop flow network for metals in mobile phones? The results from in silico experimentation with these models highlight three important differences between agent‐based modeling (ABM) and equation‐based modeling (EBM) techniques. An analysis of how these differences affected the insights that could be extracted from the constructed models points to several key advantages of ABM in the study of metal flow systems. In particular, this analysis suggests that a key advantage of the ABM technique is its flexibility to enable the representation of societal metal flow systems in a more native manner. This added flexibility endows modelers with enhanced leverage to identify options for steering metal flows and opens new opportunities for using the metaphor of an ecosystem to understand metal flow systems more fully.

Climate adaptation of interconnected infrastructures: a framework for supporting governance

Infrastructures are critical for human society, but vulnerable to climate change. The current body of research on infrastructure adaptation does not adequately account for the interconnectedness of infrastructures, both internally and with one another. We take a step toward addressing this gap through the introduction of a framework for infrastructure adaptation that conceptualizes infrastructures as complex socio-technical “systems of systems” embedded in a changing natural environment. We demonstrate the use of this framework by structuring potential climate change impacts and identifying adaptation options for a preliminary set of cases—road, electricity and drinking water infrastructures. By helping to clarify the relationships between impacts at different levels, we find that the framework facilitates the identification of key nodes in the web of possible impacts and helps in the identification of particularly nocuous weather conditions. We also explore how the framework may be applied more comprehensively to facilitate adaptation governance. We suggest that it may help to ensure that the mental models of stakeholders and the quantitative models of researchers incorporate the essential aspects of interacting climate and infrastructure systems. Further research is necessary to test the framework in these contexts and to determine when and where its application may be most beneficial.

Carbon policies: do they deliver in the long run?

Carbon taxation and emission trading are policy instruments for achieving significant CO2 emission reduction by inducing a shift in technology and fuel choice. Simulations with a quantitative agent-based model of a competitive electricity generation sector show that under both policies CO2 emissions increase for 10-15 years due to the long life cycle of power plants. Dramatic reductions materialize after 20-40 years when a tight cap or sufficient tax level is maintained. When taxes are set equivalent to trading prices, taxation induces earlier investment in CO2 abatement, a better balance between capital and operating costs and lower long-run electricity prices.

Agent-based modeling of energy infrastructure transitions

Transitions emerge over time as fundamental change of large-scale socio-technical systems such as energy infrastructures that are the backbone of society. To date, however, the body-of-knowledge on energy infrastructure transitions is largely descriptive. Transition management, however, does have a prescriptive character - not only can we understand transitions, we can also shape them. This implies technical system design is augmented with policy, regulation, R&D strategies: some coherent all-inclusive set of transition instruments or transition assemblage. We conjecture a transition management strategy may equate to collaborative design of such a transition assemblage. Using foundations of complex systems theory, agent-based modeling, engineering and policy design scenario analysis, design of experiments and statistical data analysis, a modeling framework has been developed that enables ex-ante assessment of alternative transition assemblage design-alternatives.

An Agent Based Model of the System of Electricity Production Systems: Exploring the Impact of CO2 Emission-Trading

To elucidate the impact of CO2 Emission-Trading on the European electricity production system-of-systems an Agent Based Model has been developed. The model emulates the long-term evolution of the European electricity production system-of-systems as a series of investment decisions by independent agents. Simulation results are reported that underpin recommendations for European CO2-policy. A live model will be presented.