Understanding the current and future net carbon emission trajectories in “Three-Zone Space” is crucial for China to promote the formation of a low-carbon development pattern in territorial space and realize carbon neutrality. Taking Wuhan as the study area, we developed carbon emission and sequestration inventories for “Three-Zone Space”. Key driving factors of net carbon emissions were analyzed using the logarithmic mean division index, and future emissions and sequestration under six scenarios were projected with a system dynamics model. The optimal emission reduction pathway was identified through the intelligent decision-making index analysis. Our results show that Wuhan’s net carbon emission increased from 18.589 Mt in 2000 to 42.794 Mt in 2020. The emissions during this period primarily came from urban production space and urban living space. Economic development is the primary factor contributing to the increase in net carbon emissions (36.412 Mt). The efficiency of territorial space utilization is the strongest mitigator of net carbon emissions, reducing net carbon emissions by 74.341 Mt (accounting for 42.06% of total emissions). The comprehensive scenario is the most effective for net carbon emission reduction in urban and ecological spaces, while the technological progress scenario provides the greatest reduction potential in agricultural spaces. These findings provide actionable insights for optimizing spatial planning, enhancing ecological restoration, and adopting low-carbon agricultural technologies to achieve targeted emissions reductions in “Three-Zone Space”. The results of this study can further provide scientific basis for the formulation of targeted emission reduction measures for “Three-Zone Space” and guide the construction of low-carbon territorial space patterns.

Analyzing the complex dynamics of land use, accurately assessing ecosystem service values (ESVs), and predicting future trends in land use and ESVs alterations within the spatial constraints of policies are essential for policymaking and advancing sustainable development objectives. This study analyzed land use/land cover (LULC) changes in Yunnan Province from 2005 to 2020. Policy constraints were incorporated into the scenario simulations, and an improved equivalent factor method, Markov-PLUS model, global spatial autocorrelation, and the Getis-Ord Gi* method were applied to predict and analyze LULC and ESVs under different scenarios for 2030. The findings revealed the following: (1) Forests and grasslands were the dominant land use categories in YNP, with notable alterations in land use patterns recorded between 2005 and 2020. (2) The total ESVs in the study area increased by CNY 8.152 billion during this period, exhibiting an initial decline followed by gradual recovery. (3) Simulations for 2030 indicated that the natural development scenario would lead to the most extensive urbanization, while the ecological conservation scenario would yield the greatest increase in total ESVs. In contrast, only the farmland conservation scenario led to an increase in food production-related ESVs, but resulted in the lowest total ESVs among the three scenarios. These results contribute to understanding the impacts of land use changes on ESVs, and provide insights for formulating scientifically sound and effective ecological protection and development policies.

Rapid global urbanization has exacerbated the conflict between land expansion and ecosystem carrying capacity, making the enhancement of urban land use efficiency (ULUE), a critical pathway for sustainable development. While the digital economy offers a new engine for green transition, its spatiotemporal mechanisms remain underexplored. Taking China, a representative emerging economy, as a case study, this paper investigates the impact of digital transformation on ULUE from 2013 to 2020. By integrating the Super-EBM model with GTWR, we reveal a dynamic evolution where national efficiency improves while regional polarization intensifies. A key finding challenges traditional agglomeration theory, that population density increasingly exerts a negative impact on ULUE, suggesting that congestion costs and ecological pressures are outweighing agglomeration benefits in the digital era. Furthermore, digital infrastructure demonstrates a consistent positive effect by overcoming geographical barriers, whereas environmental regulation exhibits a J-curve effect that is initially constraining but eventually boosts efficiency. These insights provide a roadmap for developing nations to leverage digital tools for balancing economic growth with ecological sustainability, emphasizing the need for spatially differentiated strategies to manage the digital divide and urban congestion.