🤖 AI Summary
Energy transitions often trigger regional resource conflicts and unintended adverse outcomes due to insufficient consideration of cross-scale trade-offs among environmental, social, and resource dimensions. To address this, we develop the first integrated spatially explicit multi-agent simulation framework coupling agent-based modeling (ABM) with life cycle assessment (LCA), embedding scenario analysis and regional ecological constraints to jointly quantify impacts across resource competition, ecosystem carrying capacity, and community equity. Our methodological advance lies in uncovering dynamic feedback mechanisms between individual decision-making and system resilience, alongside spatially heterogeneous trade-off patterns. Applied to Southern California, the framework identifies cumulative environmental stress hotspots and critical resource bottlenecks under distinct transition pathways, thereby enabling differentiated deployment optimization and adaptive policy design grounded in empirical ecological and socio-spatial constraints.
📝 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.