**3. Research development and methodology**

 In developing the research methodology an interview survey was devised, comprising a semi-structured interview. According to [31] there are two types of interviews relevant for subjective surveys. One of them is exploratory or in-depth interviews normally used for surveys. Retrofitting of LCBs was targeted for the survey and adopted for this study. The focus of this study was developed from part of a doctoral study on energy management in the reuse of LCBs. A set of questions was formulated in accordance with the objective of the study and a draft questionnaire was prepared and piloted. Comments were received back from the piloted questionnaire after which a number of redrafts of the questionnaire were undertaken. The final version of the questionnaire contained 85 questions which covered an extensive range of operational issues in retrofitting projects. The questionnaire was designed to address different areas of investigation categorised into six different parts namely: building characteristics, energy using equipment/systems, how the equipment is used, energy used, energy management strategies and user behaviour.

### **3.1 Sampling and selection process**

 Due to the qualitative approach of this study, a non-probability sampling technique was used. Specifically, purposive sampling technique was selected for the retrofitting projects. Zikmund ([32], p. 382) defines purposive sampling as "a non-probability sampling technique in which a researcher selects the sample based on his/her judgment about some appropriate characteristics required of the sample members". Thus, through a process of purposive sampling ([33], pp. 381–385) the researcher selected five case study buildings from the categories of retrofitting projects involving LCBs. The selected projects for this study were chosen from LCB retrofitting projects in the East of England. However, unlike statistical sampling, the sample is not a representative of the entire population of LCBs in England. Although the selected projects have various types of ownership, however, they are used for similar purposes.

#### **3.2 Data collection process**

 The data were collected through phone interviews, site interviews and case study buildings. The researcher conducted some interviews with the building tenants to collect information on how energy is used in the building. Following the phone interview, the researcher conducted six on-site interviews with the building managers/operators to learn more about the management practices being implemented in their building. The purpose was to build on the phone interviews to obtain a more in-depth view of the operational performance of the building and to gain a deeper understanding of the best practices in operating the building. Energy use data collection formed the main focus of the data collection of the selected

*Improving Environmental Sustainability in Reuse of Some of England's Churches: Challenges… DOI: http://dx.doi.org/10.5772/intechopen.81222* 

buildings. According to [34] annual energy use can be estimated either by using top-down approach or a bottom-up approach. The bottom-up approach involves the use of the calculation methods while the top-down approach involves an analysis of measured energy consumption and appropriating it to the elements responsible for energy consumption. The bottom-up approach is mainly founded on theory, the calculated loads, and the rated capacity of energy-using equipment. The limitations of the bottom-up approach lies in the weakness of the calculated results rarely agree with metered data. This leads to overestimating energy consumption and in masking individual elements of energy use. Thus, the top-down approach was preferred for this study because of its advantage of providing a greater degree of accuracy as it is based on factual metered data [35]. In the top-down approach, the actual measured data are obtained from utility companies such as monthly utility bills and meter prints outs and are critically examined. The rational for this is to estimate the annual energy consumption and to determine how energy is being used for the activity within the building. Utility data from the buildings were collected for 12 months and the figures were converted to kg of CO2 and ranked in order of absolute energy consumption.

### **3.3 Data analysis method**

The data analysis method for this study comprise of two approaches. Firstly, benchmarking was adopted as an energy performance tracking strategy. It is a strategy most often use in normalising energy consumption-based metrics such as weather or square footage to promote realistic comparisons with other similar buildings [36]. Benchmarking as used in the analysis of the data in this study is the most prevalent performance tracking approach found in the literature capable of providing a high level picture of energy use. CIBSE TM46 [37] energy benchmarks were adopted to benchmark the performance of the investigated buildings (**Table 2**).

Secondly, the ranking was adopted to categorise higher performing buildings from the lower performing ones. Although the review of literature indicates that numerous ranking and scoring systems have been developed, however, there is no scientific consensus method [38]. The use of ranking will enable the building owners and the facilities managers to be able to compare their building performance to similar building's size and similar pattern of use in order to be adequately informed on the actions to be taken to boost the performance of their buildings. Energy use of the surveyed buildings was converted into CO2 emission using DEFRA [35] CO2 emission conversion factors. It assumes CO2 emission factors of 0.184 kg of CO2/kWh for gas and 0.542 kg of CO2/kWh for electricity. The carbon emissions of the buildings were calculated to determine both 'absolute' and 'relative' terms. The absolute emissions indicate the total footprint while relative emissions refer to the absolute figure indexed to a unit of this per m<sup>2</sup> per performance also referred to as 'intensity indicators'. During the analysis of data, the interpretation and the presentation of results; ethical issues were taken into consideration


by intentional coding the surveyed buildings using an alphabet (**Table 4**) to keep the building's identities and location hidden. This is in line with the suggestion of ([39], p. 89) that the process of data collection should not put participants at risks and that the vulnerable population should be respected by the researcher.
