Disaster risk reduction is a major concern of small island developing states. Measures to reduce risk should not only be based on the magnitude of physical hazard, but also on the exposure and vulnerability of communities. In this article, we examine flood risk management policies in the Caribbean island of Sint Maarten using coupled agent-based and flood models. The agent-based model is used to model actors' behaviour in relation to urban building development and policies that are designed to reduce flood hazard and communities' vulnerability and exposure. The policies considered in the model are a Beach Policy, a Building and Housing Ordinance, a Flood Zoning policy and hazard mitigation structural measures. The flood model is used to simulate coastal and pluvial floods on the island. Agent behaviour such as building new houses and implementing hazard reduction measures affect the flood model as these actions affect the rainfall-runoff process. The flood maps generated from the updated flood model simulations are then used to assess the impact and update agents' attributes and behaviour. The simulations results show that low-lying areas are populated, which increases the exposure, and the number of vulnerable houses is also high. Hence, out of the four policies, implementing hazard reduction measures is the most important. Reducing the flood hazard by widening existing drainage channels, constructing new ones and building dykes as coastal flood defence would reduce the hazard, hence reducing the number of flooded houses. As it affects all households on the island, the Building and Housing Ordinance is an important policy to reduce vulnerability. In general, the coupled model outputs can be used to inform policy decision making and provide insights to policymakers on the island.

SummaryIndustrial 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

This paper proposes an approach to facilitate smooth merging of freight trains into a stream of passenger trains with short headways, to help drivers better control freight trains and avoid red signals. An algorithm architecture is proposed for Driver Advisory Systems (DASs) to compute time/speed advice for freight train drivers. The framework includes four parts: buffer stairway prediction, freight train movement prediction, merging window detection and merging optimization. The basic idea is to predict the traffic state in the merging area regularly and find the feasible merging time window. Proper advice can be presented to freight train drivers and help them to merge smoothly, by comparing the freight train movement to the feasible merging window. The performance of the proposed algorithms is illustrated on examples of merging freight trains in the Meteren and Kijfhoek areas on the Dutch railway network. The experimental results show the efficiency and quality of the proposed algorithms on real world size problems. In the Amsterdam Westhaven area, a concept for advising freight trains departing from standstill is now accepted using the

Flood risk emerges from the dynamic interaction between natural hazards and human vulnerability. Methods for the quantification of flood risk are well established, but tend to deal with human and economic vulnerability as being static or changing with an exogenously defined trend. In this paper we present an AgentBased Model (ABM) developed to simulate the dynamical evolution of flood risk and vulnerability, and facilitate an investigation of insurance mechanism in London. The ABM has been developed to firstly allow an analysis of the vulnerability of homeowners to surface water flooding, which is one of the greatest short-term climate risks in the UK with estimated annual costs of £ . bn to £ . bn. These costs have been estimated to increase by -% over the next years due to climate change and urbanisation. Vulnerability is influenced by homeowner's decisions to move house and/or install measures to protect their properties from flooding. In particular, the ABM focuses on the role of flood insurance, simulating the current public-private partnership between the government and insurers in the UK, and the forthcoming re-insurance scheme Flood Re, designed as a roadmap to support the future a ordability and availability of flood insurance. The ABM includes interaction between homeowners, sellers and buyers, an insurer, a local government and a developer. Detailed GIS and qualitative data of the London borough of Camden are used to represent an area at high risk of surface water flooding. The ABM highlights how future development can exacerbate current levels of surface water flood risk in Camden. Investment in flood protection measures are shown to be beneficial for reducing surface water flood risk. The Flood Re scheme is shown to achieve its aim of securing a ordable flood insurance premiums, however, is placed under increasing pressure in the future as the risk of surface water flooding continues to increase.

Keywords:bioenergy complexity industrial ecology matrix network ontology SummaryA method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent-based model (ABM) as distinct instances of technologies with owners capable of making decisions based on economic and environmental information. This simulation setup allows us to explore the dynamics of assembly, disassembly, and use of these systems, which typically span decades, and to analyze the effect of using LCA information in decision making.We were able to integrate a simplified LCA into an ABM by aligning and connecting the data structures that represent the energy infrastructure and the supply chains from source to sink. By using an appropriate database containing life cycle inventory (LCI) information and by solving the scaling factors for the technology matrix, we computed the contribution to global warming in terms of carbon dioxide (CO 2 ) equivalents in the form of a single impact indicator for each instance of technology at each discrete simulation step. These LCAs may then serve to show each agent the impact of its activities at a global level, as indicated by its contribution to climate change. Similar to economic indicators, the LCA indicators may be fed back to the simulated decision making in the ABM to emulate the use of environmental information while the system evolves. A proof of concept was developed that is illustrated for a simplified LCA and ABM used to generate and simulate the evolution of a bioelectricity infrastructure system.