Regional industrial structure optimization based on water-energy- carbon-economy Multi-Objectives: A case study of Inner Mongolia, China

The water-energy-carbon nexus is fundamentally linked to industrial structure. Research assessing and optimizing regional industrial structures from this integrated perspective is critical. In this study, a comprehensive methodological framework for regional industrial structure evaluation and multi-objective optimization is developed by integrating environmentally extended input-output analysis (EEIOA) with mathematical programming method. This framework is designed to synergize economic growth with water conservation, energy efficiency and carbon reduction. Various single-objective and multi-objective optimization scenarios were developed to accommodate diverse policymaker preferences. Using Inner Mongolia as a case study, we propose differentiated industrial restructuring pathways to support the region's carbon peaking goal by 2030. The results reveal that the primary sector dominates direct water consumption, while the secondary sector acts as the main driver of energy use and carbon emissions. The tertiary sector also demonstrates substantial embodied resource and environmental impacts. Several water-energy-carbon intensive industries were identified. Furthermore, our findings indicate that single-objective optimization struggles to achieve coordination between economic and environmental-resource objectives, whereas multi-objective optimization significantly reduces resource and environmental pressures while maintaining a relatively high average annual GDP growth rate. It is notable that all optimization scenarios promote an increased tertiary industry share, driving a structural shift towards a tertiary-secondary-primary hierarchy. Sensitivity analysis indicates that total energy consumption and carbon emissions fluctuate with input parameter variations. Policy recommendations are finally proposed for decision makers to adjust the industrial structure. These results suggest our approach can help regional decision-makers identify synergistic pathways toward a green transition.