Synergizing economic growth and carbon emission reduction in China: A path to coupling the MFLP and PLUS models for optimizing the territorial spatial functional pattern

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...

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Veröffentlicht in:The Science of the total environment Jg. 929; S. 171926
Hauptverfasser: Qin, Jing, Ou, Dinghua, Yang, Ziheng, Gao, Xuesong, Zhong, Yuchen, Yang, Wanyu, Wu, Jiayi, Yang, Yajie, Xia, Jianguo, Liu, Yongpeng, Sun, Jun, Deng, Ouping
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Netherlands Elsevier B.V 15.06.2024
Schlagworte:
carbon
Carbon emission reduction
China
emissions factor
environment
issues and policy
land use
Multi-objective fuzzy linear programming
simulation models
sustainable development
Synergistic development path
Territorial space optimization
The patch-generating land use simulation model
uncertainty
China
The patch-generating land use simulation model
Territorial space optimization
Multi-objective fuzzy linear programming
Synergistic development path
Carbon emission reduction
ISSN:0048-9697, 1879-1026, 1879-1026
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Zusammenfassung: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. [Display omitted] •Spatiotemporal coupling exists between TSFP and synergistic states between economic growth and carbon emission reduction.•MFLP and two-stage algorithm obtain the quantitative structure of synergizing economic growth and carbon emission reduction with high robustness.•PLUS model can establish the TSFP of synergizing economic growth and carbon emission reduction.•TSFP Optimization is an effective way to synergize economic growth and carbon emission reduction.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0048-9697
1879-1026
1879-1026
DOI:10.1016/j.scitotenv.2024.171926