This article summarises the findings of a recent BRE Trust funded research project, performed in collaboration with the University of Reading, which analysed the data collected by the Code for Sustainable Homes (the Code) from its inception in 2007 until the end of July 2014 encompassing just over 105,000 post construction stage assessed dwellings. The following interactive graphs depict some of the notable statistics from this work. Click the icons in the legend to exclude/include individual data series.
The first graph shows the distribution of certificates issued at the post construction stage. The distribution is divided first by housing type and then by tenure. Overall there were over 10,000 more flats certified than houses and social tenure was far more common than private.
This next graph shows the distribution of the Code level (0-6) achieved by housing type. As can be seen below it is clear that Code level 3 was the most common in both flats and houses at 76% of total post construction certificates issued, followed by Code level 4 at 21.4%.
The next graph shows the average performance across each of the 9 different assessment categories by Code level achieved at the post construction stage. The total number of credits available in a particular category is given in brackets. As would be expected, the number of credits achieved generally increases as the level increases.
The following series of graphs shows the average scores achieved for each of the Code assessment issues by housing type and tenure. On each of the graphs, the references to each individual issue are given by the “issue ID” which is listed in the Code for Sustainable Homes Technical Guide, in addition, each issue is identified below by the issue description as given in the Technical Guide More detailed information on how each issue is assessed can be found in the Technical Guide. The maximum number of credits available for each assessment issue is shown in brackets after the issue ID. The graphs are presented in the order in which they appear within the Technical Guide.
1. Energy
Ene1 (Dwelling Emission Rate) shows that flats tend to outscore houses by just over a full credit with the private sector outscoring the public sector by around a full credit. Ene2 (Fabric Energy Efficiency) is generally not a heavily targeted issue with averages for both dwelling types and tenures around 2 of a possible 9 credits achieved. Ene3 (Energy Display Devices) and Ene4 (Drying Space) are two issues who’s averages are close to the maximum available of 2 and 1 respectively with both dwelling types and tenures all scoring similarly. Just over 1 of the available 2 credits are achieved in Ene5 (Energy Labelled White Goods). Whilst there is no real discernible difference between houses and flats with flats scoring marginally higher, the private sector does score higher than social. Ene6 (External Lighting) shows that nearly all projects achieved the full 2 credits available for this issue. Ene7 (Low & Zero Carbon Technologies) shows that this issue was rarely targeted in houses and by the social sector as both, on average, score well under 1 credit of the available 2. Of all 4 housing type and tenures, only the private sector scores more than 1 with flats scoring just under 1. Ene8 (Cycle Storage) shows that houses outscore flats and the social sector slightly outscoring private. Finally Ene9 (Home Office) shows a fairly consistent score across all 4 housing type and tenures.
2. Water
Wat1 (Indoor Water Use) shows fairly consistent scoring across all 4 housing categories with houses marginally outscoring flats and the social sector slightly outscoring the private sector. All score around 3.5 out of 5 on average. It is much the same for Wat2 (External Water Use) where houses outscore flats and the social sector outscores the private sector. On average all 4 housing type and tenures score just over half of the 1 available credit.
3. Materials
Mat1 (Environmental Impact of Materials) shows houses outscore flats by some margin with the same being true for social sector properties over the private sector. Mat2 (Responsible Sourcing of Materials – Basic Building Elements) shows a fairly even spread across the four housing type and tenure, with houses marginally outscoring flats. There is no discernible difference between social and private sector dwellings. Lastly Mat3 (Responsible Sourcing of Materials – Finishing Elements) shows a very even distribution across all 4 housing type and tenures with little to no difference in the number of credits achieved.
4. Surface Water Run-off
Sur1 (Management of Surface Water Run-off from Developments) shows almost identical averages for houses and flats with flats outscoring houses by the finest margin. The private sector scores marginally higher than the social sector. Sur2 (Flood Risk) shows a similar picture with averages not differing much between dwelling type or tenure. In this instance, houses marginally outscore flats and social tenures just outscore private.
5. Waste
Was1 (Storage of Non-recyclable Waste and Recyclable Household Waste) shows that all housing categories achieve close to the 4 credit maximum that is available for this issue with houses marginally outscoring flats and the social sector just outscoring the private sector. Was2 (Construction Site Management) also shows a very constant achievement level across all categories. The private sector does slightly outscore social and there is no discernible difference between houses and flats. Finally, Was3 (Composting) sees houses noticeably outscore flats and the social sector just outscoring the private sector.
6. Pollution
Pol1 (Global Warming Potential of Insulants) shows that in all housing type and tenure the full credit available is achieved with the average sitting barely below 1. In Pol2 (NOx Emissions) there is around a ½ credit difference between houses and flats with houses scoring higher. The social sector outscores the private sector by around a quarter of a credit.
7. Health & well-being
None of the housing categories score, on average, half of the available credits in Hea1 (Daylighting). Houses score higher than flats with the private sector just outscoring the social sector. Again in Hea2 (Sound Insulation), houses outscore flats by around ½ a credit and the private sector outscores the social sector. Houses almost achieve the full credit in Hea3 (Private Space) with all housing type and tenure scoring well. The social sector marginally outscores the private sector but both score highly. Hea4 (Lifetime Homes) bucks the trend in this category as flats outscore houses by around ½ a credit. The social sector outscores the private sector but only by a small amount.
8. Management
Man1 (Home User Guide) sees all 4 of the housing type and tenure score nearly all of the 3 available credits for this issue at a fairly consistent rate across the categories. Flats just outscore houses in Man2 (Considerate Constructors Scheme) with neither the social or private sector performing definitively better than the other. In Man3 (Construction Site Impacts), as with Man1, all of the 4 housing type and tenure score evenly although not as close to the maximum as Man1. All average just over 1.5 credits, a little way short of the maximum of 2. Lastly Man4 (Security) sees houses just outscoring flats and the social sector outscoring the private sector by around ½ a credit.
9. Ecology
Eco1 (Ecological Value of Site) sees flats marginally outscoring houses and the private sector scoring slightly more than the social sector. Eco2 (Ecological Enhancement) and Eco3 (Protection on Ecological Features) are very similar to Eco1 with flats outscoring houses and the private sector outscoring the social sector. Eco4 (Change in Ecological Value of Site) sees a similar trend to the first 3 issues but there is greater disparity between flats and houses and the private sector and the social sector. Lastly Eco5 (Building Footprint) shows nearly a full credit’s difference between the average score of houses and the average score of flats, with flats outscoring houses. The private sector also averages nearly half a credit more than the social sector.
The results from the above analysis have been used by BRE during the development of the recently launched Home Quality Mark (HQM). HQM has been created to serve the UK’s house builders and the householders who buy and rent new homes. HQM will help house builders to demonstrate the high quality of their homes and to differentiate them in the marketplace. At the same time, it will give householders the confidence that the new homes they are choosing to buy or rent are well designed and built, and cost effective to run. The Home Quality Mark will do this by providing impartial information from independent experts on a new home’s quality. It clearly indicates to householders the overall expected costs, health and wellbeing benefits, and environmental footprint associated with living in the home. In short, HQM helps everyone to fully understand the quality, performance and attributes of a new-build home.
You can find out more about the Home Quality Mark, download the technical standard and find out how to become an HQM assessor and much more on the HQM website.
BRE would like to thank Professor Martin Sexton, Professor Peter Wyatt, Professor Tim Dixon, Dr Jorn van de Wetering and Whitney Bevan from the University of Reading for their assistance in completing this project. The data used to complete this project was used with permission of the Departments for Communities and Local Government.