PARENT SESSION
IP09 - Uncertainties in Life-Cycle and Comparative Risk Assessment
Chair: Pennington, David¹, ¹ GECOS-DGR, EPFL, Lausanne, Vaud, Switzerland
Co-chair: McKone, Tom ², Jones, Kevin³, ² University of California, Berkeley, CA³ Lancaster University, ON, LA1 4YQ
2:10 PM to 5:30 PM - Tuesday, 19 November 2002
Room Room 151 G

(IP71) Environmental Assessment of the Built Environment Under Uncertainty.

Ries, Robert^*,1, ¹ University of Pittsburgh, Pittsburgh, PA, USA

ABSTRACT- Construction and operation of the built environment is a major cause of resource depletion and environmental pollution. Given appropriate models and computational tools, a life cycle analysis (LCA) approach can be advantageously utilized for environmentally informed decision-making. A LCA software tool, Ecologue, has been developed as a part of an integrated building simulation system (SEMPER). This allows the environmental model to include operational effects such as heating, cooling, and lighting in the analysis. The Ecologue model is a combination of a model of the processes occurring in the built environment life cycle, a context model of the physical characteristics of a region, and a sub-regional fate and transport model based on a Mackay fugacity model. Uncertainty is included in the environmental impact indicator model. A recursive pseudo-random Monte Carlo sampling scheme is used to characterize the uncertainty in the impact indicators. The uncertain parameters are described by a mean value, a standard deviation, and a distribution. Probability distributions are primarily log-normal and normal. Uncertain parameters include the properties of the compounds used in the fate and transport model, ambient concentration limits for the compounds, and the characteristics and timing of future processes in the life cycle, i.e., maintenance activities and operational effects. Two alternative building designs were analyzed using this system. The enclosure design for each alternative is different, which effects the environmental performance regarding materials, initial construction, and operation and maintenance. An analysis of the probability density and cumulative distribution functions for the impact indicators show that the deterministic values do not give a true representation of the full range of potential impact. The results indicate that LCA can be a valuable tool for decision-making in the built environment, and that including uncertainty analysis can improve the interpretation and understanding of environmental impact indicator calculations.

Key words: life cycle assessment, uncertainty, built environment