Carbon Capture Clustering: the Case for Coordinated Approaches to Address Freshwater Use Concerns

Carbon capture and storage (CCS) will be a key technology for reducing emissions from fossil-fuelled electricity generation. The UK is developing demonstration plants and UK Government strategy proposes the clustering of CCS facilities, having identified significant cost-savings from shared pipeline infrastructure. However, cooling water use from CCS power plants are almost double those of conventional plants. There are concerns about the volumes of freshwater used and vulnerability to low river flows, particularly in areas identified for CCS clusters. Two innovative approaches may reduce water use in CCS clusters by exploiting synergies with other infrastructures; district heating and municipal wastewater. Our analysis indicates that cooling water reductions from district heating may be feasible in the northwest, but less likely in Yorkshire. We also find that across the UK there are numerous, sufficiently large wastewater treatment plants capable of providing alternative cooling water sources for large power plants. Feasibility of these promising options will be highly contextual, require detailed analysis and may face economic and regulatory barriers. Historically, ad-hoc development of energy infrastructure has struggled to exploit such synergies, but may now be facilitated by the clustering of CCS facilities

A First Step Towards Automatically Building Network Representations

To fully harness Grids, users or middlewares must have some knowledge on the topology of the platform interconnection network. As such knowledge is usually not available, one must uses tools which automatically build a topological network model through some measurements. In this article, we define a methodology to assess the quality of these network model building tools, and we apply this methodology to representatives of the main classes of model builders and to two new algorithms. We show that none of the main existing techniques build models that enable to accurately predict the running time of simple application kernels for actual platforms. However some of the new algorithms we propose give excellent results in a wide range of situations

Mobile Service Clouds: A self-managing infrastructure for autonomic mobile computing services

Abstract. We recently introduced Service Clouds, a distributed infrastructure designed to facilitate rapid prototyping and deployment of autonomic communication services. In this paper, we propose a model that extends Service Clouds to the wireless edge of the Internet. This model, called Mobile Service Clouds, enables dynamic instantiation, composition, configuration, and reconfiguration of services on an overlay network to support mobile computing. We have implemented a prototype of this model and applied it to the problem of dynamically instantiating and migrating proxy services for mobile hosts. We conducted a case study involving data streaming across a combination of PlanetLab nodes, local proxies, and wireless hosts. Results are presented demonstrating the effectiveness of the prototype in establishing new proxies and migrating their functionality in response to node failures.