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Occupant behaviour (OB) is impacted by several interdisciplinary factors: environmental, psychosocial, cultural and economic. One of these impacting factors is the climate. In this study, the patterns of OB interactions with heating, cooling, lighting, equipment, windows and shading collected in questionnaire surveys were used as input data in the simulation models of two university buildings. The buildings, a green-rated and a non-rated one, are in Western Sydney University in Sydney, Australia. Then, the models were simulated in eight different climate zones in Australia. Therefore, this research aimed to understand how different climate zones may impact the energy related to OB and compare this impact between a green-rated building and a building without any rating. The results showed that there is no correlation between climate and OB and the levels of discomfort are related to the cooling season. The green building is less subjected to external changes, indicating that in buildings with automatic and properly controlled centralised management systems, the impacts related to the misuse of energy due to OB would be almost irrelevant. The results of this study should not be extended to other occupant behavioural patterns or situations. The results should be confined within the present research and context. [ABSTRACT FROM AUTHOR]

Thermal insulation is a significant factor in building construction. As a result, Green Star in Australia requires building envelopes to be insulated properly. Further, green buildings require at least 15% above the required R-values (which are measured in m2 K/W) for achieving Green Star credit points. Thermal insulation of the roof depends on various factors such as insulation material, sarking material, air films and roof covering. Therefore, there are many options with different combinations available to obtain the required total R-values. This research aims to identify optimum solutions for roofing solutions considering the life-cycle cost. There are ten commonly used roof types in Australia. Therefore, this research calculated the life-cycle costs using the net present value technique for more than 2000 options of roofing solutions and selected optimum solutions for each climate zone in Australia. The outcome shows that the initial cost and the replacement cost significantly influence the life-cycle cost. Further, the maintenance, replacement and disposal costs vary from 47 to 69% of the life-cycle cost. Sensitivity analysis concludes that the discounting rate has a significant influence on the life-cycle cost of the roofing solution. However, the changes in labour rate have only a slight impact on the life-cycle cost of roofing solutions. [ABSTRACT FROM AUTHOR]