RESUMO
Carbon emissions caused by economic growth are the main cause of global warming, but controlling economic growth to reduce carbon emissions does not meet China's conditions. Therefore, how to synergize economic growth and carbon emission reduction is not only a sustainable development issue for China, but also significant for mitigating global warming. The territorial spatial functional pattern (TSFP) is the spatial carrier for coordinating economic development and carbon emissions, but how to establish the TSFP of synergizing economic growth and carbon emission reduction remains unresolved. We propose a decision framework for optimizing TSFP coupled with the multi-objective fuzzy linear programming and the patch-generating land use simulation model, to provide a new path to synergize economic growth and carbon emission reduction in China. To confirm the reliability, we took Qionglai City as the demonstration. The results found a significant spatiotemporal coupling between TSFP and the synergistic states between economic growth and carbon emission reduction (q ≥ 0.8220), which resolves the theoretical uncertainty about synergizing economic growth and carbon emission reduction through the path of TSFP optimization. The urban space of Qionglai City in 2025 and 2030 obtained by the decision framework was 6497.57 hm2 and 6628.72 hm2 respectively, distributed in the central and eastern regions; the rural space was 60,132.92 hm2 and 56,084.97 hm2, concentrated in the east, with a few located in the west; and the ecological space was 71,072.52 hm2 and 74,998.31 hm2, mainly located in the western and southeastern areas. Compared with the TSFP in 2020, the carbon emission intensity of the TSFP obtained by the decision framework was reduced by 0.7 and 4.7 tons/million yuan, respectively, and realized the synergy between economic growth and carbon emission reduction (decoupling index was 0.25 and 0.21). Further confirming that TSFP optimization is an effective way to synergize economic growth and carbon emission reduction, which can provide policy implications for coordinating economic growth and carbon emissions for China and even similar developing countries.
RESUMO
With the exposure of excessive intensive use of urban and agricultural space, the optimization of intensive use of ecological space provides a new way to coordinate the global problem of spatial conflict between ecological protection and economic development. However, the coupling accuracy of the existing structure-spatial coupling optimization model is low, which cannot provide method support for the optimization of intensive use of ecological space. To solve this problem, we propose a new model of ecological spatial intensive use optimization (ESIUO) based on the non-stationarity of the Markov state transition probability of the dominant ecosystem service functions (DESFs) and their suitability, and with the help of the framework of cellular automata (CA). We took Qionglai City as an empirical study area, and compared the results of this model with those of CA-Markov and CLUE-S models with the same parameters. The results show that: (i) The quantitative structure corresponding to the spatial layout of each dominant ecosystem service function (DESF) optimized by the ESIUO model has the smallest relative error (δk≤0.04%) with the optimal quantitative structure. (ii) The layout of DESFs optimized by the ESIUO model maximizes the supply capacity of ecosystem services. The minimum matching degree between the distribution of each DESF and the high-value area of its suitability is 92.06 %, and the spatial distribution is more compact, and the comprehensive effect of spatial layout is the best. Further analysis confirmed that the model can establish the spatial layout of DESFs that can realize the high precision coupling with the optimal quantitative structure of DESFs in terms of quantitative structure, and can support the construction of the layout of intensive use of ecological space to alleviate the pressure of non-ecological space expansion in these areas, and then provide a new way to coordinate ecological protection and economic development.