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Spatiotemporal Evolution and Influencing Factors of Carbon Emission Efficiency in the Yellow River Basin of China: Comparative Analysis of Resource and Non-Resource-Based Cities.
Xu, Yingqi; Cheng, Yu; Zheng, Ruijing; Wang, Yaping.
Afiliação
  • Xu Y; College of Geography and Environment, Shandong Normal University, Jinan 250358, China.
  • Cheng Y; College of Geography and Environment, Shandong Normal University, Jinan 250358, China.
  • Zheng R; College of Geography and Environment, Shandong Normal University, Jinan 250358, China.
  • Wang Y; College of Geography and Environment, Shandong Normal University, Jinan 250358, China.
Article em En | MEDLINE | ID: mdl-36141923
ABSTRACT
Comparing the carbon emission efficiency (CEE) of resource and non-resource-based cities in the Yellow River Basin (YRB) can guide their synergistic development and low-carbon transition. This study used the super-efficiency slacks-based measure (super-SBM) model to measure the CEE of cities in the YRB. Kernel density estimation and Theil index decomposition methods were used to explore the spatiotemporal evolutionary patterns, and a panel regression model was established to analyze the influencing factors of CEE. The research results showed that the CEE of the two types of cities have an overall upward trend in time, with a widening regional gap. Resource-based cities mainly displayed the characteristics of decentralized regional agglomeration, while non-resource-based cities mainly showed the characteristics of convergent regional agglomeration. Panel regression results showed that the levels of economic development, indus-trial structure, and population density are significantly positively correlated with CEE in the YRB, while foreign direct investment and resource endowment are significantly negatively correlated with CEE. Except for economic development and industrial structure, there is some variability in the contribution of the remaining influencing factors to the CEE of the resource and non-resource-based cities. The research results suggest developing classification measures for low-carbon transition in the YRB.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais / Estado_mercado_regulacao Bases de dados: MEDLINE Assunto principal: Carbono / Rios Tipo de estudo: Prognostic_studies País/Região como assunto: Asia Idioma: En Revista: Int J Environ Res Public Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Temas: ECOS / Aspectos_gerais / Estado_mercado_regulacao Bases de dados: MEDLINE Assunto principal: Carbono / Rios Tipo de estudo: Prognostic_studies País/Região como assunto: Asia Idioma: En Revista: Int J Environ Res Public Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China