Summertime temperatures and thermal comfort in UK homes

Abstract

Internal summertime temperatures measured in 268 homes in Leicester, UK, are reported. The hourly data were collected from living rooms and bedrooms during the summer of 2009. Some household interviews were conducted. The sample of homes was statistically representative of the socio-technical characteristics of the city's housing stock. The data provide insight into the influence of house construction, energy system usage, and occupant characteristics on the incidence of elevated temperatures and thermal discomfort. The warmest homes were amongst the 13% that were heated. Significantly more of these had occupants aged over 70 years who are particularly vulnerable to high temperatures. The national heatwave plan might usefully caution against summertime heating. Temperatures in the 230 free-running homes were analysed using both static criteria and criteria associated with the BSEN15251 adaptive thermal comfort model. These indicated that flats tended to be significantly warmer than other house types. Solid wall homes and detached houses tended to be significantly cooler. It is argued that adaptive criteria provide a valuable and credible framework for assessing internal temperatures in free-running UK homes. However, the temperatures in the Leicester homes were much lower than anticipated by the BSEN15251 model. Numerous possible reasons for this discrepancy are discussed.

Il est rendu compte des températures estivales intérieures mesurées dans 268 logements de Leicester, au Royaume-Uni. Les données horaires ont été recueillies dans les salles de séjour et les chambres pendant l'été 2009. Il a été procédé à des entretiens dans un certain nombre de foyers. L'échantillon de logements était statistiquement représentatif des caractéristiques sociotechniques du parc de logements de la ville. Les données fournissent des enseignements sur l'influence qu'exercent la construction des logements, l'utilisation du système d'énergie et les caractéristiques des occupants sur l'incidence des températures élevées et de l'inconfort thermique. Les logements les plus chauds ont été trouvés dans les 13 % qui étaient chauffés. Un nombre sensiblement plus important de ceux-ci avaient des occupants de plus de 70 ans qui sont particulièrement vulnérables aux températures élevées. Le plan national canicule pourrait utilement mettre en garde contre le chauffage en période estivale. Les températures dans les 230 logements permettant une gestion autonome du chauffage ont été analysées en utilisant à la fois des critères statiques et les critères associés au modèle de confort thermique adaptatif BSEN15251. Ceux-ci ont indiqué que les appartements avaient tendance à être nettement plus chauds que les autres types de logements. Les logements à murs pleins et les maisons individuelles avaient tendance à être sensiblement plus frais. Il est fait valoir que les critères adaptatifs fournissent un cadre utile et crédible pour l'évaluation des températures intérieures dans les logements britanniques permettant une gestion autonome du chauffage. Cependant, les températures des logements de Leicester étaient nettement inférieures à celles anticipées par le modèle BSEN15251. Il est discuté des nombreuses raisons pouvant expliquer cette différence.

Mots clés: adaptation, changement climatique, stress thermique, vague de chaleur, logements, surchauffe, été, mesure de la température, confort thermique, R-U

Keywords:

• adaptation
• climate change
• heat stress
• heatwave
• houses
• overheating
• summer
• temperature measurement
• thermal comfort
• UK

Acknowledgements

The 4M consortium was funded by the Engineering and Physical Sciences Research Council (EPSRC) under its Sustainable Urban Environment programme (Grant Number EP/F007604/1). It was a collaboration between the universities of Loughborough, Newcastle, Sheffield and De Montfort. The authors are grateful to Katherine Irvine who was instrumental in ensuring the Living in Leicester survey was successful. The map shown in Figure 1 is copyright of the Ordnance Survey MasterMap and was provided through EDINA/DigiMap.

Notes

In Leicester, the temperatures in August 2003 reached a peak of 37.0°C (on 9 August) with a maximum daily mean of 25.2°C (on 6 August) and a maximum T _rm value of 21.4°C (on 11 August).

In London, the 97th centile value of the three-day moving average temperature from 1976–1996 was 21.5°C.

The South East and Yorkshire and Humberside experienced the second highest temperature-related death rates with 110 excess deaths (4% above base level) and 100 deaths (6% above base level), respectively.

Hidden in a figure is advice to ‘reduce internal energy and heat’.

This is not surprising as in the UK wintertime space heating energy demands are a major source of greenhouse gas emissions and under heating of homes is a significant health risk. Such studies include, for example, 1600 low-income households (Oreszczyn, Hong, Ridley, and Wilkinson, 2006), 427 homes in the CaRB (Carbon Reduction in Buildings) study (Shipworth et al., 2009), 14 low-energy homes monitored in Milton Keynes (Summerfield et al., 2007), and 25 households in Northern Ireland (Yohanis and Mondol, 2010). The most extensive field survey (Hunt and Gidman, 1982) measured spot temperatures in each room of 100 homes in February and March 1978.

The data points bear no direct relationship to the households surveyed but preserve the number and rough location of those interviewed.

Aerial imagery was used to confirm these responses.

Some homes were inadvertently not offered sensors by the interviewer.

As recorded by Leicester City Council in the middle of Leicester.

The chill of entering air-conditioned spaces on a summer day will be familiar to many.

Authors' underlining.

T _rm = (1 – α).{T _ed–1 + α.T _ed–2 + α ².T _ed–3, …}, where T _ed–1 is the daily mean external temperature the previous day; T _ed–2 is the daily mean external temperature two days ago, etc.; and α has a recommended value of 0.8.

This is the recommended category for spaces ‘occupied by very sensitive and fragile persons with special requirements like handicapped, sick, very young children and elderly persons’.

The standard also offers temperatures for the winter heating season of 21, 20 and 18°C for categories I, II and III, respectively.

In these homes, the non-heated room either did not yield data or it was free floating. However, these free-floating rooms were not, as noted above, included in the free-floating sample, as the flow of heat from the heated room could mean the space was not truly free-running.

Not shown herein.

Data are ordered from left to right by the percentage of time within the Category I boundaries.

Living room figures quoted here are for the period 08.00–22.00 hours; the corresponding values for the evening only (18.00–22.00 hours) are: 116 with more than 5% of hours below Category II and 48 with more than 5% below Category III.

These were estimated from aerial images.

Other isolated significant results can be seen in Tables 2 and 3, but they do not shape into any obvious pattern and they contradict the overall picture painted here.

For example, the work within the European Union SCATS project (McCartney and Nicol, 2002) and a global data base of 21 000 measurements, primarily from office buildings, which underpins the ASHRAE adaptive standard (de Dear, 1998).

One wonders also if the habit might be culturally engrained, originating from ties back to times when creating heat was a time-consuming and messy business (the lighting of coal fires).

Calculation using the Fanger method, as described in ISO 7730 (2005). For activity levels of 1 Met (70 W/m²), sedentary, and 100 Met (100 W/m²) for light domestic work, see INNOVA (2002). The same source gives for summer clothing 0.6 Clo (briefs, thin socks, light shoes, plus normal long-sleeve shirt and trousers) and with a normal sweater (0.9 Clo) and two extra sweaters (one thin and one thick) 1.2 Clo. The calculations assume low air speed (0.1 m/s), 50% relative humidity, and equal radiant and air temperatures.

As are household pets, especially cats.