Proposing carbon reduction strategies for mega-urban agglomerations − a cluster analysis based on carbon emission intensity
[Display omitted] •Probing heterogeneity of CE in mega-urban clusters via new economic geography.•Construction of vector Kaya expansion model based on urban–rural dual structure.•Unifying analysis of production-side and domestic-side carbon emissions.•Framework for stepwise low-carbon policy in mega...
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Published in | Ecological indicators Vol. 166; p. 112336 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
01.09.2024
Elsevier |
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Abstract | [Display omitted]
•Probing heterogeneity of CE in mega-urban clusters via new economic geography.•Construction of vector Kaya expansion model based on urban–rural dual structure.•Unifying analysis of production-side and domestic-side carbon emissions.•Framework for stepwise low-carbon policy in mega-urban agglomerations.
Identifying the causes of heterogeneity in carbon emission (CE) performance among different units of a mega-urban agglomeration is crucial for its low-carbon development. This study examines the impacts of regional industrial transformation, living consumption, and spatial expansion on CE using an extended Kaya identity model, focusing on 26 Yangtze River Delta (YRD) cities from 2006 to 2019. Our study reveals that: (1) The development disparities across YRD cities result in distinct CE reduction trajectories, with advanced urban centers showcasing more effective emission control strategies. (2) Living consumption is the primary driver of CE increases, contributing significantly to the rise with a proportion of 137.2%. This is moderated by industrial transformation, which has implemented efficiency improvements and technological innovations to reduce emissions, contributing to a decrease in CE by 48.9%. Spatial expansion also plays a role, accounting for an 11.7% increase in CE. (3) The YRD’s CE reduction efforts are primarily concentrated in core cities, manifesting a pronounced core-periphery structure that includes spillover effects into transitional and peripheral cities. We propose targeted strategies, including incentivizing green technology in high-emission sectors, developing comprehensive low-carbon public transportation, and encouraging sustainable consumer behaviors through education and incentives. These strategies aim for a balanced advancement in industrial practices, urban planning, and public engagement, providing a roadmap for crafting sustainable urban development strategies in similar global contexts. |
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AbstractList | Identifying the causes of heterogeneity in carbon emission (CE) performance among different units of a mega-urban agglomeration is crucial for its low-carbon development. This study examines the impacts of regional industrial transformation, living consumption, and spatial expansion on CE using an extended Kaya identity model, focusing on 26 Yangtze River Delta (YRD) cities from 2006 to 2019. Our study reveals that: (1) The development disparities across YRD cities result in distinct CE reduction trajectories, with advanced urban centers showcasing more effective emission control strategies. (2) Living consumption is the primary driver of CE increases, contributing significantly to the rise with a proportion of 137.2%. This is moderated by industrial transformation, which has implemented efficiency improvements and technological innovations to reduce emissions, contributing to a decrease in CE by 48.9%. Spatial expansion also plays a role, accounting for an 11.7% increase in CE. (3) The YRD’s CE reduction efforts are primarily concentrated in core cities, manifesting a pronounced core-periphery structure that includes spillover effects into transitional and peripheral cities. We propose targeted strategies, including incentivizing green technology in high-emission sectors, developing comprehensive low-carbon public transportation, and encouraging sustainable consumer behaviors through education and incentives. These strategies aim for a balanced advancement in industrial practices, urban planning, and public engagement, providing a roadmap for crafting sustainable urban development strategies in similar global contexts. [Display omitted] •Probing heterogeneity of CE in mega-urban clusters via new economic geography.•Construction of vector Kaya expansion model based on urban–rural dual structure.•Unifying analysis of production-side and domestic-side carbon emissions.•Framework for stepwise low-carbon policy in mega-urban agglomerations. Identifying the causes of heterogeneity in carbon emission (CE) performance among different units of a mega-urban agglomeration is crucial for its low-carbon development. This study examines the impacts of regional industrial transformation, living consumption, and spatial expansion on CE using an extended Kaya identity model, focusing on 26 Yangtze River Delta (YRD) cities from 2006 to 2019. Our study reveals that: (1) The development disparities across YRD cities result in distinct CE reduction trajectories, with advanced urban centers showcasing more effective emission control strategies. (2) Living consumption is the primary driver of CE increases, contributing significantly to the rise with a proportion of 137.2%. This is moderated by industrial transformation, which has implemented efficiency improvements and technological innovations to reduce emissions, contributing to a decrease in CE by 48.9%. Spatial expansion also plays a role, accounting for an 11.7% increase in CE. (3) The YRD’s CE reduction efforts are primarily concentrated in core cities, manifesting a pronounced core-periphery structure that includes spillover effects into transitional and peripheral cities. We propose targeted strategies, including incentivizing green technology in high-emission sectors, developing comprehensive low-carbon public transportation, and encouraging sustainable consumer behaviors through education and incentives. These strategies aim for a balanced advancement in industrial practices, urban planning, and public engagement, providing a roadmap for crafting sustainable urban development strategies in similar global contexts. |
ArticleNumber | 112336 |
Author | Yan, Xiang Zhou, Qin Cheng, Changgao Fang, Zhou Li, Nan Tang, Yan Tang, Deshan |
Author_xml | – sequence: 1 givenname: Changgao orcidid: 0000-0001-7952-8673 surname: Cheng fullname: Cheng, Changgao email: 1548350004@qq.com organization: Business School, Hohai University, Nanjing 211100, PR China – sequence: 2 givenname: Xiang surname: Yan fullname: Yan, Xiang organization: Business School, Hohai University, Nanjing 211100, PR China – sequence: 3 givenname: Zhou surname: Fang fullname: Fang, Zhou organization: Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla 666303, PR China – sequence: 4 givenname: Qin surname: Zhou fullname: Zhou, Qin organization: Business School, Hohai University, Nanjing 211100, PR China – sequence: 5 givenname: Yan surname: Tang fullname: Tang, Yan organization: College of Computer and Information, Hohai University, Nanjing 211100, PR China – sequence: 6 givenname: Nan surname: Li fullname: Li, Nan organization: College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 211100, PR China – sequence: 7 givenname: Deshan surname: Tang fullname: Tang, Deshan organization: College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 211100, PR China |
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•Probing heterogeneity of CE in mega-urban clusters via new economic geography.•Construction of vector Kaya expansion model based on... Identifying the causes of heterogeneity in carbon emission (CE) performance among different units of a mega-urban agglomeration is crucial for its low-carbon... |
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SubjectTerms | carbon Carbon dioxide emissions citizen participation cluster analysis Driving factors education emissions factor Heterogeneity analysis LMDI public transportation river deltas sustainable technology urban development Yangtze River Yangtze River Delta |
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Title | Proposing carbon reduction strategies for mega-urban agglomerations − a cluster analysis based on carbon emission intensity |
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