Dynamic life cycle assessment: framework and application to an institutional building

This paper uses a dynamic life cycle assessment (DLCA) approach and illustrates the potential importance of the method using a simplified case study of an institutional building. Previous life cycle assessment (LCA) studies have consistently found that energy consumption in the use phase of a building is dominant in most environmental impact categories. Due to the long life span of buildings and potential for changes in usage patterns over time, a shift toward DLCA has been suggested. We define DLCA as an approach to LCA which explicitly incorporates dynamic process modeling in the context of temporal and spatial variations in the surrounding industrial and environmental systems. A simplified mathematical model is used to incorporate dynamic information from the case study building, temporally explicit sources of life cycle inventory data and temporally explicit life cycle impact assessment characterization factors, where available. The DLCA model was evaluated for the historical and projected future environmental impacts of an existing institutional building, with additional scenario development for sensitivity and uncertainty analysis of future impacts. Results showed that overall life cycle impacts varied greatly in some categories when compared to static LCA results, generated from the temporal perspective of either the building's initial construction or its recent renovation. From the initial construction perspective, impacts in categories related to criteria air pollutants were reduced by more than 50 % when compared to a static LCA, even though nonrenewable energy use increased by 15 %. Pollution controls were a major reason for these reductions. In the future scenario analysis, the baseline DLCA scenario showed a decrease in all impact categories compared with the static LCA. The outer bounds of the sensitivity analysis varied from slightly higher to strongly lower than the static results, indicating the general robustness of the decline across the scenarios. These findings support the use of dynamic modeling in life cycle assessment to increase the relevance of results. In some cases, decision making related to building design and operations may be affected by considering the interaction of temporally explicit information in multiple steps of the LCA. The DLCA results suggest that in some cases, changes during a building's lifetime can influence the LCA results to a greater degree than the material and construction phases. Adapting LCA to a more dynamic approach may increase the usefulness of the method in assessing the performance of buildings and other complex systems in the built environment.