Current approaches: key debates

This section outlines the key ongoing debates on current approaches and methods for effecting improvements to environmental performance in the existing dwelling stock.

4.5.1 Performance ‘gap’

There is an established and growing body of evidence of a performance gap between building design (and efficiency) and delivery in terms of end use.

Most building assessments are based on information provided during design rather than performance in use. The discrepancy between predicted and actual performance, particularly for energy modelling, is also termed a

credibility gap (Bordass et al., 2004). Recent studies support the existence of a gap between predicted and measured performance in aspects of the building envelope and appliances such as heat pumps and solar thermal systems (Sanders and Phillipson, 2006; Energy Saving Trust, 2010; 2011; Wingfield et al., 2007). Deficient design, defective installation, and behaviour of occupants are amongst the factors that affect predicted performance—but which are brushed aside (Gwilliam, 2011; Lowe et al., 2007; Soebarto et al., 2004). In a study of 1,372 households in the UK by Hong et al. (2006), property and utility data for dwellings ranging in type and age from pre-1900 to post 1976 were analysed before and after intervention. The study found significant differences between modelled and actual heating energy consumption and thus the

energy efficiency improvements did not deliver the reductions in space heating consumption predicted, even after the effects of increased comfort were taken into account. As well as defects in installation, the study noted occupant

117

ventilation practices associated with a new gas central heating system, and preferences of householders for less efficient but familiar room heaters. The reasons for the disparity in performance are related not only to design and construction, but also to the ‘operation’ of buildings—and the fact that they are part of the complexity of everyday life.

This discrepancy in performance has led to questioning of the effectiveness of current approaches and methods of assessment in achieving performance objectives. Several authors underline the importance of using empirical data to assess energy efficiency improvements (for example, Stafford et al., 2011).

Rather than reliance on simulations, they argue there is a need for methods that begin to understand and address actual performance. This is particularly relevant to heritage buildings: a study by Ingram et al. (2011) suggests that a lack of accurate information relating to the design and construction, together with ill-founded assumptions about the activities of occupants, could result in deficient or ineffective retrofits.

In a technical framing, the assumption is that improvements in energy

efficiency will lead to reduced energy demand and greenhouse gas emissions.

However, the presumption that energy efficiency is likely to lead to lower energy consumption is a point of much debate (Caird et al., 2008; Herring, 1999; Hertwich, 2005; Brookes, 2000). The energy efficiency benefits from technological improvements such as increased levels of insulation or a more efficient heating system, may be reduced through rebound effects⁶ (Hertwich, 2005; Sorrell et al., 2009; Brookes, 1990, 2000) whereby some or all of the energy savings are used in increased comfort, or energy efficient appliances are used more often (Herring and Roy, 2007) thereby negating in large part the predicted reduction in energy use (Sanders and Phillipson, 2006). Where

6 The rebound effect was first described in 1865 by Jevons in his famous work The Coal Question where he argued that improved efficiency in coal use would lead not to a reduction in national coal consumption, but rather an increase. If the rebound effect is larger than 100 per cent, all gains from the increased fuel efficiency would be wiped out by increases in demand (the Jevons paradox). Thus technological improvements could not be relied upon to reduce fuel consumption.

118

the efficiency measure leads to increased energy consumption, this is referred to as backfire (Brookes, 2000; Saunders, 2000). Rebound effects have been observed or measured in empirical studies (for example, Caird et al., 2008;

Druckman et al., 2011; 2012; Gram-Hanssen, 2012; Hens et al., 2010; Hong et al., 2006). For households, rebound effects vary depending on the service, whether space heating, cooling, lighting, etc. (Greening et al., 2000).

Published studies reviewed by Sorrell et al. (2009) estimate between 10-30 per cent take-back for household heating, depending on circumstances and method of measurement. Larger take-back is noted in dwellings with lower initial temperatures (Hong et al., 2006; Sanders and Phillipson, 2006).

However, the extent of rebound effects that will occur in a given case, and what determines the extent is uncertain. Such unintentional effects may reduce the ability of a primary policy measure to achieve its goal, or even undermine the validity of efficiency policies. Even so, government holds tightly to the position that in the long term, energy efficiency improvements usually result in large overall energy savings.

The empirical evidence suggests that building solutions, whilst necessary, are not sufficient to reduce energy consumption (Janda, 2011; Stafford et al., 2011). Further work is essential to understand how renovation and energy consumption are intertwined from the occupants’ perspective.

4.5.2 Role of occupants

The energy performance of buildings is highly complex, involving the interaction of many interrelated factors, many of which are not well

understood. The conduct of occupants is increasingly recognised as a critical element in meeting environmental performance aspirations (Stevenson and Leaman, 2010). A need to understand the influence of occupants in

environmental performance within the residential sector has been established.

Firth et al. (2008) found significant variation in heat and electrical energy consumption in similar dwellings. In a separate study, Gill et al. (2010) found a

119

variation of 2.5 to 5 times in energy-related consumption between dwellings of homogeneous design. According to a study by Gram-Hanssen, (2010),

housing occupants living in exactly the same type of dwelling can use three or more times as much energy for heating as their neighbour, suggesting that the inhabitants ultimately determine how energy efficient a home is.

Both ‘technical’ and ‘non-technical’ factors have a critical influence on the total energy requirements of residential dwellings (Gram-Hanssen, 2011b; Schuler et al., 2000). Previous research has tended to focus on the building envelope with inadequate attention given to the occupants (Crosbie and Baker, 2010), although occupant characteristics and patterns of use play a prominent role in the variation in energy consumption in different households (for example, Druckman and Jackson, 2008; Gill et al., 2010; Gram-Hanssen, 2010a; Haas et al., 1998; Sardianou, 2008). Based on statistical analysis of variables from the results of other research, Guerra-Santin et al. (2009) suggest that the technical characteristics of a building account for 42 per cent of the variation in energy consumption, whereas the occupancy characteristics account for some 4.2 per cent. In-depth case study research of 26 dwellings by Gill et al., 2010 found that 51 per cent and 37 per cent respectively of the variation in heat and electrical consumption could be explained by behaviours, indicating that

occupants can have a significant impact on performance and should be accounted for alongside other building mandates. Thus a growing body of evidence indicates that occupants’ practices are at least as important as the efficiency of the building envelope, systems and appliances when seeking to explain household energy consumption.

It is becoming apparent that energy performance depends not only the

technical features of the building but also on the users, although these may be at variance. An energy intensive lifestyle in a very energy efficient residence can lead to higher than expected energy use (Jeeninga et al., 2001 in Guerra-Santin and Itard, 2010). As expressed by Soebarto (in Williamson, 2005: 6):

120

‘ rating the energy (or environmental) performance of a house design will not guarantee that when built the house will actually have a low operating energy. A number of previous studies have shown that actual energy

performance depends on the way the occupants “use” the building and does not necessarily relate to the building design (for example work by Ballinger et al., 1991, Haberl et al. 1998).’

Although a significant determinant of energy use, there is remarkably little data available on the behaviour of building occupants (Productivity Commission, 2005: 134, 219).

There are calls for real world evidence to support policy (Shipworth et al., 2010), qualitative and quantitative studies to improve understanding of domestic energy consumption (Firth et al., 2008), and user-centred

approaches that prioritise understanding of routines, habits, conventions and conceptions of normality over efforts to make individual technologies or behaviours more efficient (Haines et al., 2010; Shove, 2003a). Within

construction research, in the rapid and unpredictable development of energy and buildings, there is a need to examine the processes, understandings and motivations which produce observed patterns and systems in energy and buildings (Schweber and Leiringer, 2012).

4.5.3 Concept of thermal comfort

Existing approaches are founded on a particular conceptualisation of thermal comfort which is aimed at achieving constant temperature set points and standardized conditions. The widely accepted definition of thermal comfort is

‘that condition of mind in which satisfaction is expressed with the thermal environment’ (ASHRAE, 2004; 2010). This is almost identical in wording to the International Standard ISO 7730 (International Organization for

Standardization, 2005)—both of which are based on the physiological understanding and measurement of thermal comfort (Fanger, 1970). This

121

notion of comfort has informed the establishment of universally applied comfort standards and guidelines for the built environment. Although

established codes and standards informing design decisions are underpinned by scientific research (Djongyang et al., 2010), the science of thermal comfort is contested, involving debates about: the cultural and/or physiological nature of comfort; the relative significance of different variables under different climatic conditions; and the possibility of adaptation (Brager and de Dear, 1998; Halawa and van Hoof, 2012; Humphreys and Nicol, 1998; van Hoof et al., 2010). In support of the argument that thermal comfort is socially and culturally constructed, Chappells and Shove (2005) and Humphreys et al., 2007 point to field studies which show how people of different cultures, value and maintain very different indoor conditions and interpretations of comfort (see for example, Wilhite et al., 1996; Isaacs et al., 2010). An alternative conception as an achievement, thermal comfort is seen as ‘personally idiosyncratic, culturally relative, socially influenced and highly dependent on temporality, sequence and activity’ (Jaffari and Matthews, 2009:1). They suggest that individuals may devise their own strategies to manage comfort.

This approach to thermal comfort is supported by a study of six dwellings in Australia (four in Adelaide, one in Brisbane and one in Darwin) by Soebarto et al. (2004) where assessment of the environmental performance revealed some anomalies between actual performance and assessment ratings. Like most heritage buildings, these architect-designed houses were constructed prior to the introduction of energy performance regulations. The indoor and outdoor temperature and relative humidity were monitored for 6-12 months, and records of energy consumption obtained from utility companies. Internal conditions fluctuated with external conditions, and there was no attempt to maintain constant thermal conditions. The occupants used passive design techniques to achieve thermal comfort and they asserted that other benefits associated with living in the dwellings, i.e. openness and connection with the outside, outweighed any minor thermal discomfort. Despite having energy consumption well below the average house in the same location, these

122

buildings were not able to achieve the required rating when evaluated using housing energy rating tools (FirstRate and NatHERS), and so could not have obtained verification using the prescribed software. This study illustrates that a narrow, purely engineering approach is not necessarily the way forward; and designing buildings for a more expanded range of indoor temperature i.e.

accepting a more ‘elastic’ definition of thermal comfort that reflects variation in outdoor conditions, and meets occupants’ aspirations, could significantly reduce energy demand. As Chappells and Shove, (2005: 39) argue:

‘Rather than figuring out more efficient ways of maintaining 21–23 C in the face of issues of sustainable consumption and global warming, society should be embarking on a much more searching debate about the meaning of

comfort and the ways of life associated with it. In this way, it might be possible to exploit existing diversity and variety both in people’s expectations and in the built environment and so avoid a commitment to an unsustainably

standardized future’.