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

Using Display Energy Certificates to quantify public sector office energy consumption

This paper explores how internal and external characteristics affect energy use in the public sector office stock in England and Wales, using a database of 2,600 Display Energy Certificates (DECs) combined with other sources of disaggregated office information. The DEC office benchmarks were shown to match the median fossil thermal and electrical consumptions well. Analysis of HVAC, size, occupancy density, building age, location and rateable value were considered. While newer offices were shown to have lower typical fossil-thermal consumption than older offices, this was counterbalanced by higher electrical consumption, resulting in higher typical CO2 emissions. This has implications for the UK's emissions reduction targets for 2050, indicating that while building regulations that focus on thermal performance have been successful, a focus on electrical consumption (both regulated and unregulated) is key. The results were also compared with existing benchmarks for all UK offices, splitting the sample into four generic types, and compared to a similar smaller study of private offices. This indicated that public offices typically used less energy than the general benchmarks had previously predicted, particularly for prestige offices.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) funding for Doctoral Training Studentships, and in association with the EPSRC funded 'ReVISIONS' project [grant number EP/F007566/1].This is the final published version. It first appeared at http://dx.doi.org/10.1080/09613218.2014.97541

Characterising the English school stock using a unified national on-site survey and energy database

The recent commitment towards a net-zero target by 2050 will require considerable improvement to the UK’s building stock. Accounting for over 10% of the services energy consumption of the United Kingdom, the education sector will play an important role. This study aims to improve the understanding of English primary and secondary schools, using national on-site survey data with several large-scale disaggregate data sources. Property Data Survey Programme (PDSP) data on 18,970 schools collected between 2012 and 2014, Display Energy Certificate (DEC) and school census data from the same period were linked and processed to form a unified schools dataset. Statistical analyses were undertaken on 10,392 schools, with a focus on energy performance, and the relationship to several building and system characteristics. The analyses may point to the possibility of assessing operational energy use of schools in a more disaggregate manner. New datasets with detailed and accurate disaggregate information on characteristics of buildings, such as those used in this study, provide opportunities to develop more robust models of the building stock. Such data would provide an opportunity to identify pathways for reducing carbon emissions effectively and provide lessons for other organisations seeking to achieve significant reductions for achieving climate change goals

Window operation behaviour and indoor air quality during lockdown: A monitoring-based simulation-assisted study in London

The Covid-19 outbreak has resulted in new patterns of home occupancy, the implications of which for indoor air quality (IAQ) and energy use are not well-known. In this context, the present study investigates 8 flats in London to uncover if during a lockdown, (a) IAQ in the monitored flats deteriorated, (b) the patterns of window operation by occupants changed, and (c) more effective ventilation patterns could enhance IAQ without significant increases in heating energy demand. To this end, one-year’s worth of monitored data on indoor and outdoor environment along with occupant use of windows has been used to analyse the impact of lockdown on IAQ and infer probabilistic models of window operation behaviour. Moreover, using on-site CO2 data, monitored occupancy and operation of windows, the team has calibrated a thermal performance model of one of the flats to investigate the implications of alternative ventilation strategies. The results suggest that despite the extended occupancy during lockdown, occupants relied less on natural ventilation, which led to an increase of median CO2 concentration by up to 300 ppm. However, simple natural ventilation patterns or use of mechanical ventilation with heat recovery proves to be very effective to maintain acceptable IAQ

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

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

Developing a Data-driven School Building Stock Energy and Indoor Environmental Quality Modelling Method

The school building sector has a pivotal role to play in the transition to a low carbon UK economy. School buildings are responsible for 15% of the country’s public sector carbon emissions, with space heating currently making up the largest proportion of energy use and associated costs in schools. Children spend a large part of their waking life in school buildings. There is substantial evidence that poor indoor air quality and thermal discomfort can have detrimental impacts on the performance, wellbeing and health of schoolchildren and school staff. Maintaining high indoor environmental quality whilst reducing energy demand and carbon emissions in schools is challenging due to the unique operational characteristics of school environments, e.g. high and intermittent occupancy densities or changes in occupancy patterns throughout the year. Furthermore, existing data show that 81% of the school building stock in England was constructed before 1976. Challenges facing the ageing school building stock may be exacerbated in the context of ongoing and future climate change. In recent decades, building stock modelling has been widely used to quantify and evaluate the current and future energy and indoor environmental quality performance of large numbers of buildings at the neighbourhood, city, regional or national level. Building stock models commonly use building archetypes, which aim to represent the diversity of building stocks through frequently occurring building typologies. The aim of this paper is to introduce the Data dRiven Engine for Archetype Models of Schools (DREAMS), a novel, data-driven, archetype-based school building stock modelling framework. DREAMS enables the detailed representation of the school building stock in England through the statistical analysis of two large scale and highly detailed databases provided by the UK Government: (i) the Property Data Survey Programme (PDSP) from the Department for Education (DfE), and (ii) Display Energy Certificates (DEC). In this paper, the development of 168 building archetypes representing 9,551 primary schools in England is presented. The energy consumption of the English primary school building stock was modelled for a typical year under the current climate using the widely tested and applied building performance software EnergyPlus. For the purposes of modelling validation, the DREAMS space heating demand predictions were compared against average measured energy consumption of the schools that were represented by each archetype. It was demonstrated that the simulated fossil-thermal energy consumption of a typical primary school in England was only 7% higher than measured energy consumption (139 kWh/m2/y simulated, compared to 130 kWh/m2/y measured). The building stock model performs better at predicting the energy performance of naturally ventilated buildings,which constitute 97% of the stock, than that of mechanically ventilated ones. The framework has also shown capabilities in predicting energy consumption on a more localised scale. The London primary school building stock was examined as a case study. School building stock modelling frameworks such as DREAMS can be powerful tools that aid decision-makers to quantify and evaluate the impact of a wide range of building stock-level policies, energy efficiency interventions and climate change scenarios on school energy and indoor environmental performance

Energy use intensities in London houses

This research compares domestic metered energy data, for both gas and electricity consumption, against characteristics drawn from a building stock model of Greater London, UK. The energy analyses are limited to houses (single-building, single household) with one standard electricity meter and one mains gas meter as the principal subset. This provides a sample of almost 1.2 million, or 75%, of London’s stock of houses. Energy use was normalised by calculated floor area, providing an energy use intensity (EUI; kWh/m2/yr), which allows properties of all sizes to be compared. Examination of EUIs of each built form versus Energy Performance Certificate (EPC) current energy efficiency (Asset Rating value) indicates weak, or very weak, correlation between the two, particularly for electricity

Modelling platform for schools (MPS): The development of an automated One-By-One framework for the generation of dynamic thermal simulation models of schools

The UK Government has recently committed to achieve net zero carbon status by year 2050. Schools are responsible for around 2% of the UK’s total energy consumption, and around 15% of the UK public sector’s carbon emissions. A detailed analysis of the English school building stock’s performance can help policymakers improve its energy efficiency and indoor environmental quality. Building stock modelling is a technique commonly used to quantify current and future energy demand or indoor environmental quality performance of large numbers of buildings at the neighbourhood, city, regional or national level. ‘Building-by-building’ stock modelling is a modelling technique whereby individual buildings within the stock are modelled and simulated, and performance results are aggregated and analysed at stock level. This paper presents the development of the Modelling Platform for Schools (MPS) – an automated generation of one-by-one thermal models of schools in England through the analysis and integration of a range of data (geometry, size, number of buildings within a school premises etc.) from multiple databases and tools (Edubase/Get Information About Schools, Property Data Survey Programme, Ordanance Survey and others). The study then presents an initial assessment and evaluation of the modelling procedure of the proposed platform. The model evaluation has shown that out of 15,245 schools for which sufficient data were available, nearly 50% can be modelled in an automated manner having a high level of confidence of similarity with the actual buildings. Visual comparison between automatically-generated models and actual buildings has shown that around 70% of the models were, indeed, geometrically accurate

Indoor Air Quality and Overheating in UK Classrooms – an Archetype Stock Modelling Approach

Children spend a large part of their waking lives in school buildings. There is substantial evidence that poor indoor air quality (IAQ) and thermal discomfort can have detrimental impacts on the performance, wellbeing and health of schoolchildren and staff. Maintaining good IAQ while avoiding overheating in classrooms is challenging due to the unique occupancy patterns and heat properties of schools. Building stock modelling has been extensively used in recent years to quantify and evaluate performance of large numbers of buildings at various scales. This paper builds on an archetype stock modelling approach which represents the diversity of the school stock in England through an analysis of The Property Data Survey Programme (PDSP) and the Display Energy Certificates (DEC) databases. The model was used for simulating Indoor-to-Outdoor pollution ratios to estimate indoor air pollution levels (NO2, PM2.5 and CO2) and thermal comfort (overheating) in two climate areas in England: London and the West Pennines. analysis highlighted variations in classrooms' indoor CO2 levels in different seasons and explored the risk of overheating in relation to a classroom's orientation