All the way to the top! The energy implications of building tall cities

Density of urban form may be achieved under a variety of morphological designs that do not rely on tallness alone. Tall buildings have implications on the broader urban environment and infrastructure that lower buildings would not have, e.g. wind effects, sight-lines, or over-shading. They may also have an impact on energy use for reasons of buildings-physics, construction, and occupant practices. This study uses a statistical approach of neighbourhood level data to analyse the impact of building morphology (e.g. height, volume and density) on energy demand in 12 local authorities in London. The research shows that areas marked by tall buildings use more gas after adjusting for exposures surface area, volume, number of residents and other features. The implication for energy policy and planning is building taller without increasing density may have an energy penalty

Evaluation of the ICT Test Bed project: final report, June 2007

The report describes three strands of evaluation used in the review of the 2006 outcomes from ICT Test Bed and the findings from each strand. a) Quantitative data: Benchmarking of changes in performance on national tests against matched comparator schools and national averages; b) Qualitative data: Site visits including classroom observations, interviews with local authority managers, head teachers, teachers, administrative staff, technicians and students; and c) Document analysis

Getting to net zero: Islington’s social housing stock

This paper describes the development of a detailed plan to get the social housing stock of the Borough of Islington in London, UK, to net zero carbon emissions. This stock is very diverse in form, age and construction, and includes houses, flats and maisonettes. A total of 4500 buildings containing some 33,300 dwellings were modelled using the 3DStock method. Six packages of measures combining fabric improvements, heat pumps and photovoltaic installations were evaluated for each dwelling individually, in terms of costs, the impacts on gas and electricity use, and predicted cuts in carbon emissions. The rollout of measures between 2020 and 2030 was modelled with a specially developed scenario tool, allowing the user to set different criteria and priorities. Fabric measures on their own were shown to achieve only a 13% cut in gas use on average. Heat pumps are the key to displacing gas use. With all measures combined and taking account of the predicted decarbonisation of the electricity supply, it is only possible to achieve an overall 70% cut in emissions by 2030. Policy relevance The development of a detailed practical plan of action is described: an applied case study with the close engagement of the local authority—not a theoretical desk exercise. Each dwelling in Islington’s housing stock was examined and measured separately. The modelling did not rely on ‘archetypes’ as in many such studies. Realistic retrofit options were analysed in each case, using current cost data from practitioners. The same approach could be applied directly to other London boroughs, and for local authorities outside the capital, although different costs and other local factors would apply. For readers outside the UK, the methodology and tools could serve as exemplars. The findings about the respective contributions of heat pumps, solar photovoltaics and fabric measures, and the effects of different priorities in the rollout of retrofits, have relevance for policymaking more generally at local and national levels

Energy use and height in office buildings

The relationship between energy use and height is examined for a sample of 611 office buildings in England and Wales using actual annual metered consumption of electricity and fossil fuels. The buildings are of different ages; they have different construction characteristics and methods of heating and ventilation; and they include both public and commercial offices. When rising from five storeys and below to 21 storeys and above, the mean intensity of electricity and fossil fuel use increases by 137% and 42% respectively, and mean carbon emissions are more than doubled. A multivariate regression model is used to interpret the contributions of building characteristics and other factors to this result. Air-conditioning is important, but a trend of increased energy use with height is also found in naturally ventilated buildings. Newer buildings are not in general more efficient: the intensity of electricity use is greater in offices built in recent decades, without a compensating decrease in fossil fuel use. The evidence suggests it is likely – although not proven – that much of the increase in energy use with height is due to the greater exposure of taller buildings to lower temperatures, stronger winds and more solar gains

kD-STR : a method for spatio-temporal data reduction and modelling

Analysing and learning from spatio-temporal datasets is an important process in many domains, including transportation, healthcare and meteorology. In particular, data collected by sensors in the environment allows us to understand and model the processes acting within the environment. Recently, the volume of spatio-temporal data collected has increased significantly, presenting several challenges for data scientists. Methods are therefore needed to reduce the quantity of data that needs to be processed in order to analyse and learn from spatio-temporal datasets. In this article, we present the -Dimensional Spatio-Temporal Reduction method (D-STR) for reducing the quantity of data used to store a dataset whilst enabling multiple types of analysis on the reduced dataset. D-STR uses hierarchical partitioning to find spatio-temporal regions of similar instances, and models the instances within each region to summarise the dataset. We demonstrate the generality of D-STR with three datasets exhibiting different spatio-temporal characteristics and present results for a range of data modelling techniques. Finally, we compare D-STR with other techniques for reducing the volume of spatio-temporal data. Our results demonstrate that D-STR is effective in reducing spatio-temporal data and generalises to datasets that exhibit different properties

Reducing and linking spatio-temporal datasets with kD-STR

When linking spatio-temporal datasets, the kD-STR algorithm can be used to reduce the datasets and speed up the linking process. However, kD-STR can sacrifice accuracy in the linked dataset whilst retaining unnecessary information. To overcome this, we propose a preprocessing step that removes unnecessary information and an alternative heuristic for kD-STR that prioritises accuracy in the linked output. These are evaluated in a case study linking a road condition dataset with air temperature, rainfall and road traffic data. In this case study, we found the alternative heuristic achieved a 19% improvement in mean error for the linked air temperature features and an 18% reduction in storage used for the rainfall dataset compared to the original kD-STR heuristic. The results in this paper support our hypothesis that, at worse, our alternative heuristic will yield a similar error and storage overhead for linking scenarios as the original kD-STR heuristic. However, in some cases it can give a reduction that is more accurate when linking the datasets whilst using less storage than the original kD-STR algorithm

Second-order phase transition at the phase boundary through the FeRh first-order metamagnetic phase transition

The phase coexistence present through first-order phase transitions implies the presence of phase boundary walls, which can be of finite size. Better understanding of the phase boundary wall properties will provide an insight into the dynamics of first-order phase transitions. Here, by combining x-ray photon correlation spectroscopy investigations with magnetometry measurements of magnetic relaxation through the thermally activated first-order metamagnetic phase transition present in the B2-ordered FeRh alloy, we are able to isolate the dynamic behaviour of the phase boundary wall present in this system. These investigations reveal a change in the nature of the dynamic behaviour and critical scaling of the relaxation time centred around the point of maximum phase coexistence within the phase transition. All of this behaviour can be attributed to the introduction of exchange coupling across the phase boundary wall and raises questions about the role of latent heat in dynamic behaviour of this region

Symptoms associated with victimization in patients with schizophrenia and related disorders

Background: Patients with psychoses have an increased risk of becoming victims of violence. Previous studies have suggested that higher symptom levels are associated with a raised risk of becoming a victim of physical violence. There has been, however, no evidence on the type of symptoms that are linked with an increased risk of recent victimization. Methods: Data was taken from two studies on involuntarily admitted patients, one national study in England and an international one in six other European countries. In the week following admission, trained interviewers asked patients whether they had been victims of physical violence in the year prior to admission, and assessed symptoms on the Brief Psychiatric Rating Scale (BPRS). Only patients with a diagnosis of schizophrenia or related disorders (ICD-10 F20–29) were included in the analysis which was conducted separately for the two samples. Symptom levels assessed on the BPRS subscales were tested as predictors of victimization. Univariable and multivariable logistic regression models were fitted to estimate adjusted odds ratios. Results: Data from 383 patients in the English sample and 543 patients in the European sample was analysed. Rates of victimization were 37.8% and 28.0% respectively. In multivariable models, the BPRS manic subscale was significantly associated with victimization in both samples. Conclusions: Higher levels of manic symptoms indicate a raised risk of being a victim of violence in involuntary patients with schizophrenia and related disorders. This might be explained by higher activity levels, impaired judgement or poorer self-control in patients with manic symptoms. Such symptoms should be specifically considered in risk assessments