Author(s)

K. ALLACKER & F. DE TROYER

Abstract

A four-year project (SuFiQuaD) has started in 2007 to optimise the sustainability of the Belgian dwelling stock, focussing on the environmental impact, the financial cost and the qualities. The whole life cycle of representative housing types is assessed and recommendations for improvement are formulated. The environmental impact is evaluated through a life cycle assessment and is expressed in monetary terms, while a life cycle cost analysis is executed for the financial evaluation. A multi-criteria analysis is used for the quality evaluation considering aspects as for example size of rooms, available wall length for furniture and acoustical performance. For the optimisation the Pareto principle is used, searching for the highest life cycle cost reduction for the smallest investment increase and for the highest quality increase for the lowest life cycle cost increase. This paper elaborates on the developed methodology and the results of the implementation to two dwellings (results of the first phase of the research). The analysis reveals that it is feasible to obtain a large reduction in the life cycle environmental cost for only a minor extra financial investment and life cycle cost. Furthermore, fi nancial-based decisions prove to differ from environmental-based ones. For the case studies, internalisation of the environmental cost leads to an average increase in investment cost of 8%; while the maintenance cost (including cleaning and replacements) increases by 2% and the heating cost by 55%. The life cycle environmental cost is mainly determined by the heating cost, while the financial cost is above all determined by the investment and maintenance costs. Although the environmental and financial cost, or one of both, is higher for a certain option, one may choose for it because of its better quality. This is clearly shown by the inclusion of the quality aspects in the optimisation procedure.

Keywords

life cycle assessment, life cycle costing, monetary valuation, multi-criteria analysis, optimisation,