Energy and complexity: new ways forward

The purpose of this paper is to review the application of complexity science methods in understanding energy systems and system change. The challenge of moving to sustainable energy systems which provide secure, affordable and low-carbon energy services requires the application of methods which recognise the complexity of energy systems in relation to social, technological, economic and environmental aspects. Energy systems consist of many actors, interacting through networks, leading to emergent properties and adaptive and learning processes. Insights on these type of phenomena have been investigated in other contexts by complex systems theory. However, these insights are only recently beginning to be applied to understanding energy systems and systems transitions. The paper discusses the aspects of energy systems (in terms of technologies, ecosystems, users, institutions, business models) that lend themselves to the application of complexity science and its characteristics of emergence and coevolution. Complex-systems modelling differs from standard (e.g. economic) modelling and offers capabilities beyond those of conventional models, yet these methods are only beginning to realize anything like their full potential to address the most critical energy challenges. In particular there is significant potential for progress in understanding those challenges that reside at the interface of technology and behaviour. Some of the computational methods that are currently available are reviewed: agent-based and network modelling. The advantages and limitations of these modelling techniques are discussed. Finally, the paper considers the emerging themes of transport, energy behaviour and physical infrastructure systems in recent research from complex-systems energy modelling. Although complexity science is not well understood by practitioners in the energy domain (and is often difficult to communicate), models can be used to aid decision-making at multiple levels e.g. national and local, and to aid understanding and allow decision making. The techniques and tools of complexity science, therefore, offer a powerful means of understanding the complex decision-making processes that are needed to realise a low-carbon energy system. We conclude with recommendations for future areas of research and application

Research on Students\u27 Conceptual Understanding of Environmental, Oceanic, Atmospheric, and Climate Science Content

At the interface between atmosphere, hydrosphere, and biosphere, this theme chapter covers content that is societally crucial but publicly controversial and fraught by misconceptions and misinformation. Climate science is an interdisciplinary field that straddles the natural and social sciences; understanding its processes requires system-thinking, understanding mathematical models, and appreciation of its human and societal components. Recent data show that extreme weather and climate events have become more frequent in the past decades. These include extreme temperatures, floods, like the ones associated with the series of very powerful hurricanes that made an unprecedented number of landfalls in August and September 2017 and unusual drought conditions and forest fires across the Western US in the summer of 2017. Studies like these emphasize the complexity of climate science and highlight the importance of climate change adaptation. However, there is a significant disparity in the distribution of vulnerability and readiness to impacts of climate change around the world. In this theme chapter, authors have identified five grand challenges to the conceptual understanding of environmental, oceanic, atmospheric and climate science, and proposed strategies for the geoscience education research community

An alternative to market-oriented energy models : Nexus patterns across hierarchical levels

Unidad de excelencia María de Maeztu MdM-2015-0552From a biophysical perspective, energy is central to the behaviour of social-ecological systems. Its ubiquity means that energy is entangled with nexus elements, including water, land, emissions and labour. At the science-policy interface, large market-oriented energy models dominate as the tool to inform decision-making. The outputs of these models are used to shape policies, but strongly depend on sets of assumptions that are not available for deliberation and gloss over uncertainties. Taking an approach from complexity, we propose an alternative to market-oriented energy models, describing the behaviour of energy systems in relation to patterns of nexus elements across hierarchical levels. Three characteristics are central to the approach: (i) the distinction of the model's building blocks into functional and structural elements; (ii) their hierarchical organisation and (iii) the description of nexus patterns at each level, through the tool of the processor. To illustrate the model, it is applied to Catalonia's energy sector, linking production and consumption patterns. The framework may help inform stakeholder deliberation on pressing energy and nexus issues

Analysis and control of complex collaborative design systems

This paper presents a novel method for modelling the complexity of collaborative design systems based on its analysis and proposes a solution to reducing complexity and improving performance of such systems. The interaction and interfacing properties among many components of a complex design system are analysed from different viewpoints and then a complexity model for collaborative design is established accordingly. In order to simplify complexity and improve performance of collaborative design, a general solution of decomposing a whole system into sub-systems and using unified interface mechanism between them has been proposed. This proposed solution has been tested with a case study. It has been shown that the proposed solution is meaningful and practical

Organizations in the making: Learning and intervening at the science-policy interface

This paper synthesizes recent insights from geography, science and technology studies and related disciplines concerning organizations and organizational learning at the science-policy interface. The paper argues that organizations do not exist and evolve in isolation, but are co-produced through networked connections to other spaces, bodies and practices. Furthermore, organizations should not be studied as stable entities, but are constantly in-the-making. This co-productionist perspective on organizations and organizing has implications for how geographers theorize, study and intervene in organizations at the science-policy interface with respect to encouraging learning and change and in the roles we adopt within and around such organizations

Progressor: Social navigation support through open social student modeling

The increased volumes of online learning content have produced two problems: how to help students to find the most appropriate resources and how to engage them in using these resources. Personalized and social learning have been suggested as potential ways to address these problems. Our work presented in this paper combines the ideas of personalized and social learning in the context of educational hypermedia. We introduce Progressor, an innovative Web-based tool based on the concepts of social navigation and open student modeling that helps students to find the most relevant resources in a large collection of parameterized self-assessment questions on Java programming. We have evaluated Progressor in a semester-long classroom study, the results of which are presented in this paper. The study confirmed the impact of personalized social navigation support provided by the system in the target context. The interface encouraged students to explore more topics attempting more questions and achieving higher success rates in answering them. A deeper analysis of the social navigation support mechanism revealed that the top students successfully led the way to discovering most relevant resources by creating clear pathways for weaker students. © 2013 Taylor and Francis Group, LLC

Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters

Demands on the disaster response capacity of the European Union are likely to increase, as the impacts of disasters continue to grow both in size and frequency. This has resulted in intensive research on issues concerning spatially-explicit information and modelling and their multiple sources of uncertainty. Geospatial support is one of the forms of assistance frequently required by emergency response centres along with hazard forecast and event management assessment. Robust modelling of natural hazards requires dynamic simulations under an array of multiple inputs from different sources. Uncertainty is associated with meteorological forecast and calibration of the model parameters. Software uncertainty also derives from the data transformation models (D-TM) needed for predicting hazard behaviour and its consequences. On the other hand, social contributions have recently been recognized as valuable in raw-data collection and mapping efforts traditionally dominated by professional organizations. Here an architecture overview is proposed for adaptive and robust modelling of natural hazards, following the Semantic Array Programming paradigm to also include the distributed array of social contributors called Citizen Sensor in a semantically-enhanced strategy for D-TM modelling. The modelling architecture proposes a multicriteria approach for assessing the array of potential impacts with qualitative rapid assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema and complementing more traditional and accurate a-posteriori assessment. We discuss the computational aspect of environmental risk modelling using array-based parallel paradigms on High Performance Computing (HPC) platforms, in order for the implications of urgency to be introduced into the systems (Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua

Introduction: Why Should We Study Migration Policies at the Interface between Empirical Research and Normative Analysis?

The text introduces the concept behind the Proceedings of the 2018 ZiF Workshop “Studying Migration Policies at the Interface between Empirical Research and Normative Analysis”. It explains why there is a need to study migration policies across disciplines, includes a short note on the current literature, and provides a look back at the workshop. DOI:10.17879/1519962468