A comparative study of benchmarking approaches for non-domestic buildings: Part 1 – Top-down approach

Benchmarking plays an important role in improving energy efficiency of non-domestic buildings. A review of energy benchmarks that underpin the UK’s Display Energy Certificate (DEC) scheme have prompted necessities to explore the benefits and limitations of using various methods to derive energy benchmarks. The existing methods were reviewed and grouped into top-down and bottom-up approaches based on the granularity of the data used. In the study, two top-down methods, descriptive statistics and artificial neural networks (ANN), were explored for the purpose of benchmarking energy performances of schools. The results were used to understand the benefits of using these benchmarks for assessing energy efficiency of buildings and the limitations that affect the robustness of the derived benchmarks. Compared to the bottom-up approach, top-down approaches were found to be beneficial in gaining insight into how peers perform. The relative rather than absolute feedback on energy efficiency meant that peer pressure was a motivator for improvement. On the other hand, there were limitations with regard to the extent to which the energy efficiency of a building could be accurately assessed using the top-down benchmarks. Moreover, difficulties in acquiring adequate data were identified as a key limitation to using the top-down approach for benchmarking non-domestic buildings. The study suggested that there are benefits in rolling out of DECs to private sector buildings and that there is a need to explore more complex methods to provide more accurate indication of energy efficiency in non-domestic buildings

Getting Them There: Removing Barriers to the CPA License

Article Excerpt: An intelligent student chooses to major in accounting. She persists through fraduation with a couble major in accounting and math and meets the 150-hour minimum education requirements….

3DStock: A new kind of three-dimensional model of the building stock of England and Wales, for use in energy analysis

This article describes the development of a new three-dimensional model of the British building stock, called ‘3DStock’. The model differs from other 3D urban and stock models, in that it represents explicitly and in detail the spatial relationships between ‘premises’ and ‘buildings’. It also represents the pattern of activities on different floors within buildings. The geometrical/geographical structure of the model is assembled automatically from two existing national data sets. Additional data from other sources including figures for electricity and gas consumption are then attached. Some sample results are given for energy use intensities. The first purpose of the model is in the analysis of energy use in the building stock. With actual energy data for very large numbers of premises, it is possible to take a completely new type of statistical approach, in which consumption can be related to a range of characteristics including activity, built form, construction and materials. Models have been built to date of the London Borough of Camden and the cities of Leicester, Tamworth and Swindon. Work is in progress to extend the modelling to other parts of Britain. Because of the coverage of the data, this will be limited however to England and Wales

Energy and urban built form: an empirical and statistical approach

The geometrical forms of buildings have important effects on their use of energy. These relationships are explored at the scale of the entire non-domestic building stock of London. A three-dimensional digital model of the city is used to make a series of geometrical measures: building volume, exposed surface area (walls plus roof) and plan depth. These are compared with figures for the consumption of gas and electricity published by the UK Department of Energy and Climate Change (DECC). The comparisons are made at different levels of spatial aggregation, from boroughs to census districts. Strong correlations are demonstrated between exposed surface area and both gas and electricity use. The analysis also provides some evidence of a sharp increase in electricity use in districts with buildings whose depth in plan exceeds 14 m (in which air-conditioning and permanent artificial lighting are typically required). A multiple regression model is used to measure the contribution of these effects to total energy use, as compared with floor area, activities and number of employees

Density and morphology: from the building scale to the city scale

The density of the domestic building stock of London is explored, moving from the scale of individual house and blocks of flats, through larger geographical units, to complete boroughs. The description of the stock is highly detailed and is made using the 3DStock method, which derives building geometry from digital maps and LiDAR (laser measurements from overflying aircraft). This means that accurate estimates of floor areas can be made and used to measure densities as Floor Space Index (FSI) values. Ground coverage or Ground Space Index (GSI) values are calculated from building footprints and land boundaries. The Spacemate tool, devised by Berghauser Pont and Haupt, is used to plot the types and ages of dwellings in terms of FSI, GSI and numbers of storeys. Figures for actual annual gas and electricity consumption are attached to each dwelling. Analysis shows that, in general, energy-use intensities—and especially the intensity of gas use for heating—decrease with increasing density, and with the transition between house types, from detached, to semi-detached, to terraces, to (low-rise) flats

Expanding the plain: using archaeobotany to examine adaptation to the 5.2 kya climate change event during the Anatolian Late Chalcolithic at Çadır Höyük

This study examines how the population at Çadır Höyük on the north central Anatolian plateau modified agricultural and fuel use practices in response to rapid social and environmental change between 3600 and 2900 BCE (Late Chalcolithic and Transitional to Early Bronze periods). Using descriptive and multivariate statistics to explore data from 60 archaeobotanical samples spanning three periods of occupation (3600–3200 BCE, 3300–3100 BCE, and 3100–2900 BCE) the results reveal that the inhabitants of Çadır relied heavily on barley, emmer, lentils, and flax throughout the Late Chalcolithic. Both dung and wood were used as fuel, although dung fuel appears to have been preferentially used. The most significant change throughout this period was a shift from foddering animals to grazing animals on the steppe. This shift corresponded with the 5.2 kya event, a period of increased aridity at the very end of the 4th millennium BCE. By diversifying their agricultural strategies to more risk adverse practices, the population at Çadır demonstrated their ability to be resilient in the face of climate change.1. Introduction 2. Methods 3. Interpretative frameworks 3.1. Sample origin 3.2. Fuel use 4. Results and discussion 4.1. Crops 4.2. Sample origin 4.3. Fuel use 4.4. Change through time 5. Response to climate change 6. Conclusio