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

Integrated Infrastructure Modelling — Managing Interdependencies with a Generic Approach

Infrastructure provision is a highly challenging task, especially when accounting for climate change mitigation and adaptation needs. Efforts of making infrastructure more efficient and flexible result in an increasing number of sensitive infrastructure interdependencies. This enforces an integrated infrastructure assessment for planning purposes, in contrast to the traditional independent infrastructure-sector modelling. For the unification of the existing infrastructure-sector models, we propose the implementation of a generic communication interface, which allows the separate sector-models to communicate at the necessarily disaggregate level in order to account for interdependencies appropriately. This approach allows for infrastructure provision modelling under one unified umbrella in a minimally invasive way, while conserving crucial individualities of the separate models. This is achieved through a generic network description, in which we solve the resource allocation through a pragmatic network-flow algorithm that resembles market and consumer behaviour. The developed framework establishes the basis for fully integrated infrastructure evaluation and hence cross-sectorial infrastructure investment decision making — a crucial tool in times of tight governmental budgets

Random quantum correlations and density operator distributions

Consider the question: what statistical ensemble corresponds to minimal prior knowledge about a quantum system ? For the case where the system is in fact known to be in a pure state there is an obvious answer, corresponding to the unique unitarily-invariant measure on the Hilbert sphere. However, the problem is open for the general case where states are described by density operators. Here two approaches to the problem are investigated. The first approach assumes that the system is randomly correlated with a second system, where the ensemble of composite systems is described by a random pure state. Results for qubits randomly correlated with other systems are presented, including average entanglement entropies. It is shown that maximum correlation is guaranteed in the limit as one system becomes infinite-dimensional. The second approach relies on choosing a metric on the space of density operators, and generating a corresponding ensemble from the induced volume element. Comparisons between the approaches are made for qubits, for which the second approach (based on the Bures metric) yields the most symmetric, and hence the least informative, ensemble of density operators.Comment: 13 pages, no figures; a new page of additional notes at end draws attention to 3 new references and their relevanc

Effect of La doping on magnetic structure in heavy fermion CeRhIn5

The magnetic structure of Ce0.9La0.1RhIn5 is measured using neutron diffraction. It is identical to the incommensurate transverse spiral for CeRhIn5, with a magnetic wave vector q_M=(1/2,1/2,0.297), a staggered moment of 0.38(2)Bohr magneton per Ce at 1.4K and a reduced Neel temperature of 2.7 K.Comment: 5 pages, 2 figures, 1 table. Conf. SCES'200

Complications and mortality in hereditary hemorrhagic telangiectasia: a population-based study

OBJECTIVES: Studies report that the risks of significant neurologic complications (including stroke, cerebral abscess, and migraine) and hemorrhagic sequelae are high in patients with hereditary hemorrhagic telangiectasia (HHT), and that life expectancy in this cohort is reduced. However, most published cohorts derive from specialist centers, which may be susceptible to bias. METHODS: We used a population-based approach to estimate the risks of developing neurologic and hemorrhagic complications of HHT, the association of a diagnosis of HHT with common cardiovascular and malignant comorbidities, and also long-term survival of those with the disease. RESULTS: From a UK primary care database of 3.5 million patients (The Health Improvement Network), we identified 675 cases with a diagnosis of HHT and compared them with 6,696 controls matched by age, sex, and primary care practice. Risks of stroke (odds ratio [OR] 1.8, 95% confidence interval [CI] 1.2-2.6), cerebral abscess (OR 30.0, CI 3.1-288), and migraine (OR 1.7, CI 1.3-2.2) were elevated over controls. Bleeding complications including epistaxis (OR 11.6, CI 9.1-14.7) and gastrointestinal hemorrhage (OR 6.1, CI 2.8-13.4) were more common in cases with HHT. Survival of cases with HHT was poorer than controls with a hazard ratio for death of 2.0 (CI 1.6-2.6) and a median age at death 3 years younger. CONCLUSIONS: Patients with HHT are at substantially increased risk of serious neurologic and hemorrhagic complications of the disease. Because a diagnosis of HHT is associated with a significantly poorer survival compared with those who have no disease, evaluation of new strategies to improve clinical management is required

Heart-Kidney Interaction: Epidemiology of Cardiorenal Syndromes

Cardiac and kidney diseases are common, increasingly encountered, and often coexist. Recently, the Acute Dialysis Quality Initiative (ADQI) Working Group convened a consensus conference to develop a classification scheme for the CRS and for five discrete subtypes. These CRS subtypes likely share pathophysiologic mechanisms, however, also have distinguishing clinical features, in terms of precipitating events, risk identification, natural history, and outcomes. Knowledge of the epidemiology of heart-kidney interaction stratified by the proposed CRS subtypes is increasingly important for understanding the overall burden of disease for each CRS subtype, along with associated morbidity, mortality, and health resource utilization. Likewise, an understanding of the epidemiology of CRS is necessary for characterizing whether there exists important knowledge gaps and to aid in the design of clinical studies. This paper will provide a summary of the epidemiology of the cardiorenal syndrome and its subtypes

Completely monotone outer approximations of lower probabilities on finite possibility spaces

Drawing inferences from general lower probabilities on finite possibility spaces usually involves solving linear programming problems. For some applications this may be too computationally demanding. Some special classes of lower probabilities allow for using computationally less demanding techniques. One such class is formed by the completely monotone lower probabilities, for which inferences can be drawn efficiently once their Möbius transform has been calculated. One option is therefore to draw approximate inferences by using a completely monotone approximation to a general lower probability; this must be an outer approximation to avoid drawing inferences that are not implied by the approximated lower probability. In this paper, we discuss existing and new algorithms for performing this approximation, discuss their relative strengths and weaknesses, and illustrate how each one works and performs