The above dynamic changes in HVAC systems will result in maintenance and renewal work and contribute to the total life cycle energy. How does this maintenance and renewal influence the life cycle carbon? How can this replacement work be quantified? As Forrester (1961) notes, the SD model is necessary because, while people are good at observing the local structure of a system, they are not good at predicting how complex, interdependent systems will behave.
2.6.1 Empirical SD studies
Feniosky and Michael (2001) developed a dynamics plan and control methodology by integrating the applications of axiomatic design concepts, concurrent engineering concepts, the graphical evaluation and review technique (GERT), and the SD model technique. The authors found that SD model technology can incorporate the causality links between the variables in a construction system and the activity production process. Although a SD model cannot be a true representation of how a real project would evolve over time, it is still a useful technique to establish a benchmark to compare the results of different overlapping strategies developed in the overlapping frame work.
Stave (2003) illustrated the process of building a strategic-level SD model using the case of water management in Las Vegas, Nevada. The purpose of the model was to increase public understanding of the value of water conservation in Las Vegas. The case study demonstrated several benefits of SD for public communication about resource management. The SD model simulation provided immediate feedback and helped participants better understand the basis for management decisions, and also simulated discussion among group members that helped build the consensus and support resource managers needed to implement their decisions.
Chapter 2: Literature Review
Anand et al. (2006) developed a SD model based on the dynamic interactions among a number of system components to estimate carbon emissions from the cement industry in India for a time span of 20 years. The authors set up five SD models to represent the relationship between demand and production, availability of slag and fly ash, and carbon emissions from cement plants and transportation. Quantitative estimates of carbon emissions due to stabilisation of population growth, the curtailment of excess cement production, structural management, energy efficiency management and a combination of all these measures have been worked out. This research successfully identified mitigation strategies for curtailing carbon emissions from this sector.
Matsumoto (1999) presented a method to evaluate the life cycle carbon emissions by the SD method to understand how all the objects in a system interact with one another. The building design strategies to predict and reduce the environmental loads for several types of construction and building materials, and the long-life type, the energy-efficient type and the conventional type of Japanese typical wooden houses were investigated. Matsumoto concluded that: 1) the effectiveness of the method was confirmed by the application of the SD method for the LCI of the residential buildings; 2) building is a complicated system composed of lots of building materials and member subjects and the SD method is suitable to model and simulate the LCA; 3) in the modelling by SD, expansion and change of the system model are possible for simplicity, and sensitivity analysis of various parameters can be easily carried out.
The empirical studies show that the SD model can be applied in studies that (1) are extremely complex and consist of multiple interdependent components, (2) are highly dynamic, (3) involve multiple feedback processes, (4) involve nonlinear relationships, and (5) involve both hard (quantitative) and soft (qualitative) data, (6) are related to time. SD is well suited to the analysis of problems whose behaviour is governed by feedback relationships and that have a long-term horizon (Vennix, 1996).
2.7 Summary
This chapter reviewed the relevant research on LCA methods, energy indicators in the life cycle of HVAC systems, data analysis methods, conventional LCA in buildings or HVAC systems, and existing research related to the integration of the SD model in LCA and applications.
The life span of a HVAC consists of its manufacture, construction, operation and maintenance, and demolition. The categories of energy throughout the HVAC service life are identified as follows: the energy to initially produce the HVAC; the recurring embodied energy required to refurbish and maintain the building over its effective life; the energy to operate the HVAC; and finally the energy consumed for demolition. Data analysis methods in life cycle assessments were then summarized. Before introducing the SD model, the gap in evaluating dynamic changes in conventional life cycle assessments was identified. The important characteristics of the SD method were then highlighted, to provide an idea about evaluating dynamic changes in life cycle assessment.
Chapter 3: Methodology
CHAPTER 3
METHODOLOGY
3.1 Introduction
The research methodology includes the research plan and process and the proposed framework is presented in detail. LCA is a scientific methodology allowing the identification and quantification of the environmental input and output associated with a product in relation to its main function, considering all stages of its life cycle. The generic LCA method requires that all the main inputs to the processes that provide the service are taken into account, as well as the processes and materials that feed into those processes, and so on back up the supply chains of the various materials in the product to the raw resource inputs.
This LCA explores the possibility of using a representative environmental index to compare VAV system, chilled beam system and UAD system. The results are to be integrated in a multi-criteria analysis to provide information to building professionals and clients during the design process. In this research, the LCA analysis is applied to a case study comparing three green technologies, described in more detail in Chapter 4. The functional unit represents a typical air conditioning area with 14337.57m2 in a 13-storey commercial building located in Melbourne, Australia. An expected life span of the building of 50 years has been chosen, considering that in Australia many buildings of this age are demolished or undergo major renovations to reach actual thermal efficiency requirements (Cole and Kernan, 1996). The boundaries of the system include the impacts directly linked to the manufacture of basic materials, products and HVAC components, the related transportation; on-site construction; annual operation energy; regular maintenance work; and the demolition and disposal of waste.