Land–energy–population Nexus: A systemic framework for per capita energy consumption characterization and prediction toward land use structure optimization

Energy consumption and permanent population are key indicators for evaluating resource equity and social development, with land use serving as their spatial carrier and the foundation for efficient governance. This study develops a Land-Energy-Population Nexus system to address the specific demands of the Sustainable Development Goals. It evaluates the sources of energy consumption and the spatiotemporal distribution of the population, elucidates the carrying capacity and mechanisms, and enables land use subdivision. A land-energy-population correlation model is established to identify the marginal impact curves and interaction effects of land use on energy consumption and population. A high-performance simulation model driven by a geographic grid reduction algorithm supports large-scale, multi-indicator prediction. China, the world's most populous country and largest energy consumer, is selected as the case study. Energy consumption and population are characterized at the third administrative level for 2025, with key indicators projected for 2030. Cities are clustered into three development types, and 259,743 simulation experiments are conducted to explore the role of land use optimization in promoting more equitable development. Key findings include: (1) Scale effects dominate the marginal impacts of land use. Controlling urban residential land within 22.78–96.65 km² and other industrial land below 17.52 km² helps manage energy intensity. (2) For industrial cities, an optimized structure with 9.6 % large-scale industrial land, 37.5 % other industrial land, and 24.9 % mixed-use land balances industrial growth and energy efficiency. (3) Decentralizing and intensifying large-scale industrial land contributes to overall energy control, but may pose risks of inequality due to core-area population siphoning and industrial-center energy growth.