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 |
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| Sprache: | Englisch |
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Elsevier B.V
15.06.2024
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| Abstract | 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. |
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| AbstractList | 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 to synergize 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 effect between economic growth and carbon emission reduction (q ≥ 0.8220), which resolves the theoretical uncertainty about synergizing economic growth and carbon emission reduction through optimizing TSFP. The urban space of Qionglai City in 2025 and 2030 obtained by the decision framework was 6497.57 hm
and 6628.72 hm
respectively, distributed in the central and eastern regions; the rural space was 60,132.92 hm
and 56,084.97 hm
, concentrated in the east, with a few located in the west; and the ecological space was 71,072.52 hm
and 74,998.31 hm
, mainly located in the western and southeastern areas. Compared with 2020, the carbon emission intensity of the TSFP that realized the synergy (decoupling index was 0.25 and 0.21, respectively) was reduced by 0.7 and 4.7 tons/million yuan, respectively. Further confirming that optimizing TSFP 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. 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. 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.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. 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. |
| ArticleNumber | 171926 |
| Author | Yang, Wanyu Ou, Dinghua Yang, Ziheng Deng, Ouping Sun, Jun Qin, Jing Gao, Xuesong Wu, Jiayi Zhong, Yuchen Yang, Yajie Xia, Jianguo Liu, Yongpeng |
| Author_xml | – sequence: 1 givenname: Jing surname: Qin fullname: Qin, Jing email: qinjing0724@163.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 2 givenname: Dinghua surname: Ou fullname: Ou, Dinghua email: 14340@sicau.edu.cn organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 3 givenname: Ziheng surname: Yang fullname: Yang, Ziheng email: youngziheng19991222@gmail.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 4 givenname: Xuesong surname: Gao fullname: Gao, Xuesong email: xuesonggao@sicau.edu.cn organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 5 givenname: Yuchen surname: Zhong fullname: Zhong, Yuchen email: 2023206046@stu.sicau.edu.cn organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 6 givenname: Wanyu surname: Yang fullname: Yang, Wanyu email: 13890976966@163.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 7 givenname: Jiayi surname: Wu fullname: Wu, Jiayi email: 19881756625@163.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 8 givenname: Yajie surname: Yang fullname: Yang, Yajie email: vtyy515@yahoo.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 9 givenname: Jianguo surname: Xia fullname: Xia, Jianguo email: xiajianguo@126.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 10 givenname: Yongpeng surname: Liu fullname: Liu, Yongpeng email: 18708442085@163.com organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 11 givenname: Jun surname: Sun fullname: Sun, Jun email: 2019319014@stu.sicau.edu.cn organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China – sequence: 12 givenname: Ouping surname: Deng fullname: Deng, Ouping email: ouping@zju.edu.cn organization: College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China |
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| Keywords | The patch-generating land use simulation model Territorial space optimization Multi-objective fuzzy linear programming Synergistic development path Carbon emission reduction |
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