Optimized Resource Allocation for Sustainable Development in Beijing: Integrating Water, Land, Energy, and Carbon Nexus

Chinese megacities face significant challenges in reducing carbon emissions while balancing economic growth and social welfare. This study constructs an innovative multi-objective optimization model, the SD-NSGA-III model, integrated with a System Dynamics (SD) model and using the Non-dominated Sorting Genetic Algorithm III (NSGA-III) to optimize resource allocation in Beijing. The model targets environmental, economic, and social goals by establishing a water-land-energy-carbon (WLEC) nexus for analyzing resource allocation strategies and carbon reduction pathways under various constraints. Scenario simulations under the efficiency-oriented scenario indicated a potential reduction in energy carbon emissions of 81.4% by 2030. The fairness-oriented scenario revealed significant trade-offs between equity and emission reductions, emphasizing the need for balanced strategies. Introducing constraints on resources and economic growth significantly reduced median energy carbon emissions to 80 million tons by 2030. These findings demonstrate the effectiveness of the SD-NSGA-III model in providing actionable strategies for achieving carbon neutrality and sustainable development in cities.