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.

A brief history is provided of models of energy use in the UK building stock, with the focus on the non-domestic sector. This history leads to an account of the development, since 2009, of the 3DStock method for modelling complete building stocks, both domestic and non-domestic. The paper explains how 3DStock models are built and the data sources used. Special emphasis is placed on the relationship of premises (the floorspace occupied by organisations) to buildings. Energy use may be metered at the level of premises, buildings or groups of buildings. Representing the patterns in which premises relate to buildings is therefore crucial to the modelling process, and in particular to the precise measurement of energy intensities. Applications of 3DStock models in building science and policy tools are reviewed, including the London Building Stock Model (LBSM), delivered to the Greater London Authority (GLA) in 2020. This 'digital twin' can be used for the monitoring, simulation and analysis of the building stock. Implications for research and policy are discussed, particularly for energy epidemiology, density, high-rise buildings, retrofit potential, energy-use intensity and benchmarking. Data are in place to extend 3DStock modelling to the whole of England and Wales. Policy and practice relevance The models can be used to assess energy demand in large numbers of buildings in relation to a range of variables, including built form, age, construction and activities. Poorly performing buildings can be identified, and the potential for retrofit-including renewable technology installations-evaluated using the same variables plus information contained in Energy Performance Certificates (EPCs). Policies for addressing fuel poverty can be evaluated by making links to confidential socioeconomic data on occupants. In conjunction with a dynamic building energy-simulation tool, scenarios can be investigated for retrofit, the potential for renewables and issues in demand-side management. Additional uses are in the precise measurements of density and of the three-dimensional character of the urban fabric. There could be applications in public health, the modelling of indoor and outdoor air pollution, and the tracking of material flows. 3DStock models might also be integrated with digital twins of infrastructure systems and networks.

The UK non-domestic sector accounts for 2 million buildings and 19% of national CO₂ emissions, representing a significant opportunity for emission reductions. However, substantial improvement of the stock requires a greater understanding of current energy performance characteristics. This paper explores energy consumption in English schools, using data from the Display Energy Certificates (DECs) database. DECs are a key step in understanding the non-domestic stock, incorporating national-scale statistical data, covering bottom-up details of the individual buildings. Significant variations in emissions between primary and secondary schools and academies exist, primarily caused by large differences in electricity consumption. Considering pupil numbers is shown to accentuate the differences, revealing a 47% rise in CO₂ emissions per pupil from primary to secondary schools, and a further increase between secondary schools and academies. The extent to which building characteristics, including location, heating, ventilation and air-conditioning (HVAC) and size, influence performance has also been evaluated. Location, HVAC and school density are shown to correlate with variations in energy use. Finally, a comparison of current school performance against past data reveals considerable reductions in fossil-thermal energy consumption over the last decade. However, this has been offset by a significant increase in electricity consumption, resulting in rising typical emissions across the school types. Le secteur non domestique britannique représente 2 millions de bâtiments et 19% des émissions de CO₂ du pays, ce qui constitue une importante opportunité de réduction des émissions. Cependant, une amélioration substantielle du parc exige une plus grande compréhension des caractéristiques actuelles des performances énergétiques. Cet article examine la consommation d'énergie dans les écoles anglaises, en utilisant les données provenant de la base de données des Display Energy Certificates (DEC – Certificats de Performance Energétique à afficher). Les certificats DEC sont une étape clé pour mieux connaître le parc non domestique, intégrant des données statistiques à l'échelle nationale et couvrant en détail selon une approche ascendante les différents bâtiments. D'importantes variations des émissions entre les écoles primaires, les écoles secondaires et les académies existent, principalement dues à de grandes différences dans la consommation électrique. Il est démontré que la prise en compte du nombre d'élèves accentue les différences, révélant une hausse de 47% des émissions de CO₂ par élève entre les écoles primaires et secondaires, une hausse supplémentaire intervenant entre les écoles secondaires et les académies. A également été évalué le degré d'influence sur les performances des caractéristiques des bâtiments, au nombre desquelles l'emplacement, le chauffage, la ventilation mécanique et la climatisation (CVCA), ainsi que la taille. Il est démontré que l'emplacement, la CVCA et la densité des écoles sont en corrélation avec les variations de la consommation d'énergie. Enfin, une comparaison des performances actuelles des écoles par rapport aux données passées révèle des réductions considérables de la consommation d'énergie thermique fossile au cours de la dernière décennie. Cependant, ceci a été contrebalancé par une augmentation importante de la consommation d'électricité, qui s'est traduite par une hausse des émissions moyennes sur l'ensemble des types d'écoles. indicateurs de référence, parc immobilier, émissions de CO₂, Certificats de Performance Energétique (DEC), consommation d'énergie, écoles

The reasons for high carbon emissions from domestic buildings are complex, and have both social and technical dimensions. At the same time, it is costly and very time-consuming to gather reliable data on energy use in the home. The authors had early access to data from the Household Electricity Survey—the most detailed survey of electricity consumption in UK homes ever undertaken—which monitored 250 homes. The data enabled the authors to investigate a series of socio-technical questions drawn up by the UK Government: Why do some households use far more energy than average, whereas others use much less? What potential is there for shifting “peak load” so that electricity demand is more even through the day? Why is base load electricity use so high? The answers were seldom definitive, but statistical tests found significant correlations between high electricity use and social grade, large household size, unemployment and middle age; and between low electricity use and single-person households, small dwellings, and retirement. This paper draws out key findings from the work, and examines how these insights affect our broader understanding of carbon emissions from the built environment.

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 CO ₂ 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 CO ₂ 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. Practical application: This study provides evidence on the deterioration of indoor air quality resulting from homeworking during imposed lockdowns. It also tests and recommends specific ventilation strategies to maintain acceptable indoor air quality at home despite the extended occupancy hours.

The influence of internal and external characteristics on energy use in the public sector office stock in England and Wales is explored using a database of 2600 Display Energy Certificates (DECs) combined with other sources of disaggregated office information. The DEC office benchmarks are shown to match the median fossil thermal and electrical consumptions well. Analyses of heating, ventilation and air-conditioning (HVAC), size, occupancy density, building age, location and rateable value are considered. While newer offices are shown to have lower typical fossil-thermal consumption than older offices, this is 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 are also compared with existing benchmarks for all UK offices, splitting the sample into four generic types, and compared with a similar smaller study of private offices. This indicates that public offices typically used less energy than the general benchmarks had previously predicted, particularly for prestige offices.