Agent-Based Modeling of Temporal and Spatial Dynamics in Life Cycle Sustainability Assessment

Abstract

Current aggregate and top-down approaches in life cycle sustainability assessment (LCSA) generally fail to account for spatial, temporal, and emergent behavioral dynamics simultaneously during the inventory stage. We discuss the key characteristics captured by complex system approaches (agent-based modeling [ABM] in particular) in the context of LCSA. It is understood that by integrating ABM, temporal, spatial, and behavioral dynamics can be addressed during the life cycle inventory stage. We propose a general concept to integrate ABM into current building life cycle assessment standards. We then use a hypothetical example of green building development to compare the ABM approach with a predefined static policy model. Simulation results from the agent-based model confirm that there are temporal and spatial variations caused by behavioral dynamics. The results are integrated into the calculation of temporally dynamic LCSA indicators on an annual basis. Spatially distributed simulation results can also be used in spatially dynamic LCSA.