Interactive and dynamic insights into environmental impacts of a neighborhood: A tight coupling of multi-agent system and dynamic life cycle assessment

Abstract

Neighborhoods consume large amount of energy and generate substantial pollutant emissions worldwide, and assessment of the environmental impacts (EIs) has garnered particular attention. Nevertheless, the traditional life cycle assessment (LCA) method fails to account for the local variability in non-homogeneous systems due to spatiotemporal dynamics and interactions. Hence, this study integrated the multi-agent system (MAS) with the dynamic LCA (DLCA) model to develop an intelligent EIs assessment model at the neighborhood scale from an interactive and dynamic perspective. MAS was employed to simulate the interactions in neighborhoods and generate foreground elementary flow data considering dynamics. DLCA provides an impact assessment framework. The proposed model was applied to a university campus to demonstrate its operability, and the enhancement effectiveness of integrating MAS with DLCA can be observed. The interactions among the climate, people, and built environment agents on the campus were simulated.10 temporal dynamic factors and four kinds of case-specific dynamic parameters were considered. The effects of several optimization strategies were simulated, and valuable directions, like raising energy conservation awareness, regulating public devices, and improving the campus layout, were proposed. This study established a comprehensive integrated MAS-DLCA model at the neighborhood scale, providing a methodology and practical application process for future studies. It can be used to promote green neighborhood management and sustainable city practices.