In analysing the LCA results and in developing further the application and understanding of the new sustainability indicator, the following inter-relations have been addressed, in an attempt to identify best practice office buildings for heating and cooling during different periods of time, for energy and raw-material efficiency.
Overall Long Run Life Cycle Impact Indicator (OLRLCII)
Energy-Efficiency Eco-Efficiency
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Table 4.6: OLRLCII analysis in this thesis Comparison Analysis
Energy efficiency-Winter months
Case study 1 Technology on the sustainable office building (?) compared to the conventional office building
Case Study 2 Technology on the sustainable office building (?) to the conventional office building
OLRLCII for Energy efficiency-Summer months
Case study 1 Technology on the sustainable office building (?) to the conventional office building
Case study 2 Technology on the sustainable office building (?) to the conventional office building
OLRLCII for Material efficiency
Case study 1 Technology on the sustainable office building (?) to the conventional office building
Case study 2 Technology on the sustainable office building (?) to the conventional office building
OLRLCII Overall
Case study 1 Sustainable office building (?) to the conventional office building Case study 2 Sustainable office building (? )to the conventional office building Better Practice Case study 2 (?) Case Study 1
4.4.4 Model 4: Discussion and validation
This model is about providing discussion and validation on the research findings (table 4.8).
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Table 4.7: Model 3, Meta-LCA analysis Heating and cooling system
Contents Discussion-Validation-feedback Philosophical
dimension
Axiology
Kind of data needed Qualitative &quantitative methods
Stakeholders Stakeholders from different backgrounds:
Architects
Mechanical engineers Energy assessors Facility management Building manager
Construction management Energy and power management Data sources Evaluate
Instruments Structured questionnaires, send results via e-mail
Methods Expert advice, sensitivity analysis, online questionnaire survey asking for expert advice-comments on research findings which can be used as validation, research publications (see a list of publications in the first pages of the thesis).
An online questionnaire survey was used to support the discussion on the research findings, sent to different stakeholders from different institutions (appendix 21). The online survey was sent out to (n=10) experts in the field of the built environment. The online survey included 15 questions that focused on:
1. People’s expertise.
2. People’s knowledge on the life span of building services, which helped to consider the long run hypothetical scenarios for refurbishment.
3. People’s perception on the life span of building services to enhance long run energy efficiency.
4. People’s knowledge through rating of influential factors of energy-efficiency for cooling systems, fed by CHP unit during summer.
5. People’s knowledge through rating of influential factors of energy-efficiency for heating systems, fed by CHP unit during summer.
6. People’s knowledge/perception of how to enhance CHP energy efficiency in the long run.
7. People’s perception on possible hypothetical scenarios for increase, decrease or retention of existing embodied raw-material emissions in the long run.
8. People’s perception on the effectiveness of suggested solutions in order to enhance raw-material emission decrease in the long run, through rating.
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9. People’s perception on the importance of using the raw material indicator in the decision-making for choosing sustainable building services and ensuring sustainability in office buildings.
10. People’s perception on the highest significance between energy-efficiency and eco-efficiency, using rating.
11. People’s perception on the most effective combination-optional recommendation in order to achieve zero carbon in non-domestic buildings from 2016, through rating, considering only energy -efficiency.
12. People’s perception on the most effective combination-optional recommendation in order to achieve zero carbon in non-domestic buildings from 2016, through rating, considering both energy efficiency and raw material efficiency.
13. People’s perception on the proposal for raw-material indicator integration in the existing eco-labeling as a medium to enhance the production of low carbon embodied technologies and systems.
14. People’s perception on whether this survey influenced their decision making.
15. People’s feedback and comments for the study.
Validation of the results of the LCA analysis is a significant step to give good reason for the magnitude of the results. Expert advice has been provided by the internal experts (as mentioned, from the University of Central Lancashire). External experts involved in the questionnaire survey are the key stakeholder-contacts; facility managers and architects. The validation process also involves parts of the results discussed in international and national conferences, in peer-reviewed conference proceedings and journals. The following sections explain in detail the data limitation and constraints, assumptions used to overcome limitation and methods used to validate this study.
4.5 Data limitations and constraints
Although the research has achieved its aim there were some unavoidable limitations.
The limitations identified were recorded in parallel with collecting data, practicing SimaPro and analysing data. This section summarises the limitations identified specific to the LCA data inputs, energy and raw-materials. The discussion section provides further explanation on the limitations. Energy data has been collected for the operational years 2009 and 2010 where the raw-material data has been collected since the installation of the existing equipment in office buildings (any raw materials used on equipment before system upgrades and building retrofitting were not considered.)
144 Data limitations were identified in:
Archive data in energy consumption and raw-materials of the equipment studied. The conventional offices do not have mechanical specifications and schematics of the heating-cooling systems. Thus assumptions were used (section 5.3).
On existing data (mechanical specifications, energy metering) on raw-materials and energy consumption. Energy data was not available for all the months for the years 2009-10. Therefore assumptions were used (section 5.3).
Raw-material processes were difficult to collect from the manufacturers even though structured questionnaire were used (appendix 2).
Existing inventory data in SimaPro does not include the exact raw-materials found to be used in the equipment so close alternatives were chosen.
One of the constraints of the research was the case study building access for the fieldwork. Fieldwork data in office buildings was difficult because it was not possible to interrupt office staff for questions. Also all the data providers from all the offices did not want the staff to be contacted directly for questionnaire surveys so office building contacts were limited. This is also due to the fact that there are various stakeholders involved in office building management-development. However data collection responses arrived on time. Another important constraint was to undertake interviews with the occupants of the office buildings. This study intended to collect detailed data on the occupancy level of the office buildings as presented in figure 4.7. The human resources and the building managers were approached to find out this information;
however only an approximate number of building occupancy was provided. Other information on the multi-occupancy of Five Ways House, which is a government building, was found from the internet. The FM manager from Argyle House has only explained which floor areas were unoccupied. The Potterrow building has single type occupancy (students and university staff) and EIIC staff from the Winchester County Council.
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Figure 4.7: Building occupancy factors
Another important constraint that delayed the production of the LCA results was the fact that that initially the LCA SimaPro software was ordered by the university in classroom version so that more people could use it. The issue with that was that only one person could use it at a time. Apart from the networking issues, update authorisation from the IT services and renewal on the license were not happening on time and the software could not operate for a certain period of time. Also the classroom version had limited access to inventory data and it had no uncertainty analysis option.
Due to these constraints the Pre Consultants from the Netherlands were approached to ask for permission to get the PHD version license for free, to be installed on a private laptop. This worked, although it was a trial version and operated only for a month. All the previous results were changed to the current version.
4.5.1 Assumptions
According to the data limitations mentioned in section 5.2 the following assumptions were used: