Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province
Achieving the dual carbon goals requires profound systemic transformations across the economy and society. Accurately characterizing the spatial correlation network features and mechanisms of carbon emission efficiency (CEE) is critical for promoting regionally coordinated development. This study an...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X24014535 |
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| author | Li Zhang Hongrui Wang Beinan Guo Xuan Liu Caiyun Deng Ziyang Zhao Xin Jiang Yiyang Li |
| author_facet | Li Zhang Hongrui Wang Beinan Guo Xuan Liu Caiyun Deng Ziyang Zhao Xin Jiang Yiyang Li |
| author_sort | Li Zhang |
| collection | DOAJ |
| description | Achieving the dual carbon goals requires profound systemic transformations across the economy and society. Accurately characterizing the spatial correlation network features and mechanisms of carbon emission efficiency (CEE) is critical for promoting regionally coordinated development. This study analyzes 16 prefecture-level cities in Shandong Province, China, from 2006 to 2021, using the Super-SBM model to measure urban CEE. A modified gravity model and social network analysis were combined to explore the spatial network structure, while the Logarithmic Mean Divisia Index and Quadratic Assignment Procedure models investigated its formation mechanisms. The results show that Shandong’s overall CEE has improved but remains spatially imbalanced, characterized by a persistent “higher in the east, lower in the west” pattern. Key cities, such as Jinan and Qingdao, emerge as central nodes in an evolving multi-polarized spatial network, exerting strong influence. Network density has increased over time, enhancing inter-city collaboration in emission reduction. Among driving factors, technological innovation significantly reduces emissions, though economic growth plays a stronger role in shaping network connections. Geographic adjacency further reinforces spatial correlations. While Shandong’s CEE has shown steady progress, targeted efforts in carbon management and technological advancements for less efficient cities are crucial for achieving collaborative emission reduction across the province. |
| format | Article |
| id | doaj-art-b4fe7a143f944d4da5ed13fd5c6ce99d |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-b4fe7a143f944d4da5ed13fd5c6ce99d2025-01-31T05:10:25ZengElsevierEcological Indicators1470-160X2025-01-01170112996Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong ProvinceLi Zhang0Hongrui Wang1Beinan Guo2Xuan Liu3Caiyun Deng4Ziyang Zhao5Xin Jiang6Yiyang Li7College of Water Science, Beijing Normal University, Beijing 100875, ChinaCollege of Water Science, Beijing Normal University, Beijing 100875, China; Corresponding author.School of Government, Beijing Normal University, Beijing 100875, ChinaChina South-to-North Water Diversion Corporation Limited, Beijing 100036, ChinaSchool of Space Science and Technology, Shandong University, Weihai 264209, ChinaSchool of Modern Post, Xi’an University of Posts & Telecommunications, Xi’an 710114, ChinaWater Resources Research Institute of Shandong Province, Jinan 250014, ChinaCollege of Water Science, Beijing Normal University, Beijing 100875, ChinaAchieving the dual carbon goals requires profound systemic transformations across the economy and society. Accurately characterizing the spatial correlation network features and mechanisms of carbon emission efficiency (CEE) is critical for promoting regionally coordinated development. This study analyzes 16 prefecture-level cities in Shandong Province, China, from 2006 to 2021, using the Super-SBM model to measure urban CEE. A modified gravity model and social network analysis were combined to explore the spatial network structure, while the Logarithmic Mean Divisia Index and Quadratic Assignment Procedure models investigated its formation mechanisms. The results show that Shandong’s overall CEE has improved but remains spatially imbalanced, characterized by a persistent “higher in the east, lower in the west” pattern. Key cities, such as Jinan and Qingdao, emerge as central nodes in an evolving multi-polarized spatial network, exerting strong influence. Network density has increased over time, enhancing inter-city collaboration in emission reduction. Among driving factors, technological innovation significantly reduces emissions, though economic growth plays a stronger role in shaping network connections. Geographic adjacency further reinforces spatial correlations. While Shandong’s CEE has shown steady progress, targeted efforts in carbon management and technological advancements for less efficient cities are crucial for achieving collaborative emission reduction across the province.http://www.sciencedirect.com/science/article/pii/S1470160X24014535Urban carbon emission efficiencySpatial correlation networkSocial network analysisFormation mechanismShandong Province |
| spellingShingle | Li Zhang Hongrui Wang Beinan Guo Xuan Liu Caiyun Deng Ziyang Zhao Xin Jiang Yiyang Li Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province Ecological Indicators Urban carbon emission efficiency Spatial correlation network Social network analysis Formation mechanism Shandong Province |
| title | Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province |
| title_full | Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province |
| title_fullStr | Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province |
| title_full_unstemmed | Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province |
| title_short | Characteristics and formation mechanism of carbon emission efficiency spatial correlation network: Perspective from Shandong Province |
| title_sort | characteristics and formation mechanism of carbon emission efficiency spatial correlation network perspective from shandong province |
| topic | Urban carbon emission efficiency Spatial correlation network Social network analysis Formation mechanism Shandong Province |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X24014535 |
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