Coupling Agent-based Modeling and Life Cycle Assessment to Analyze Trade-offs in Resilient Energy Transitions

TL;DR

This paper introduces an integrated agent-based and Life Cycle Assessment framework to analyze complex trade-offs in energy transition pathways, emphasizing regional resource competition and ecological impacts for resilient planning.

Contribution

It presents a novel coupled modeling framework that combines agent-based modeling with LCA to evaluate spatial and institutional trade-offs in energy transitions.

Findings

Reveals spatially explicit trade-offs in energy pathways

Demonstrates how integrated modeling informs resilient planning

Shows regional resource competition impacts on energy deployment

Abstract

Transitioning to sustainable and resilient energy systems requires navigating complex and interdependent trade-offs across environmental, social, and resource dimensions. Neglecting these trade-offs can lead to unintended consequences across sectors. However, existing assessments often evaluate emerging energy pathways and their impacts in silos, overlooking critical interactions such as regional resource competition and cumulative impacts. We present an integrated modeling framework that couples agent-based modeling and Life Cycle Assessment (LCA) to simulate how energy transition pathways interact with regional resource competition, ecological constraints, and community-level burdens. We apply the model to a case study in Southern California. The results demonstrate how integrated and multiscale decision making can shape energy pathway deployment and reveal spatially explicit trade-offs under scenario-driven constraints. This modeling framework can further support more adaptive and resilient energy transition planning on spatial and institutional scales.