Green Technology Innovation and Carbon Emission Performance of the Middle Reaches of the Yangtze River Urban Agglomeration: Mechanism and Spatio-Temporal Evolution

Amid the increasingly severe global climate change situation, green technology innovation has become an important means to promote carbon reduction and achieve the transition to a low-carbon economy. This study aims to systematically analyze the relationship between green technology innovation and carbon emission performance in the urban agglomeration of the middle reaches of the Yangtze River, exploring the degree of coupling and coordination between different cities. Utilizing data from 2011 to 2021, we employ methods such as the Coupling Coordination Degree Model and fixed effects model to achieve our objectives. Our findings reveal that both green technology innovation and carbon emission performance in this region are on an upward trend; however, the growth rate of green technology innovation showed a slowdown in 2021. Notably, there are disparities in the coupling coordination degree among cities, with economically developed areas exhibiting a faster growth rate. Moreover, green technology innovation significantly enhances carbon emission performance, and heterogeneity tests indicate that this impact is even more pronounced in cities with weaker environmental regulations. Despite regional differences, the overall trend remains positive.

Authors

Institutions

Publication Details

Journal
Energies
Published
2024-10-23
DOI
https://doi.org/10.3390/en17215274
Citations
2
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.41
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Green Technology Innovation and Carbon Emission Performance of the Middle Reaches of the Yangtze River Urban Agglomeration: Mechanism and Spatio-Temporal Evolution

X.M. Li, Sheyun Li, Yijun Guo
2 citations
Energies
Environmental Impact and Sustainability
0.41
article

Green Technology Innovation and Carbon Emission Performance of the Middle Reaches of the Yangtze River Urban Agglomeration: Mechanism and Spatio-Temporal Evolution

X.M. Li, Sheyun Li, Yijun Guo
article en
2 citations

Abstract

Amid the increasingly severe global climate change situation, green technology innovation has become an important means to promote carbon reduction and achieve the transition to a low-carbon economy. This study aims to systematically analyze the relationship between green technology innovation and carbon emission performance in the urban agglomeration of the middle reaches of the Yangtze River, exploring the degree of coupling and coordination between different cities. Utilizing data from 2011 to 2021, we employ methods such as the Coupling Coordination Degree Model and fixed effects model to achieve our objectives. Our findings reveal that both green technology innovation and carbon emission performance in this region are on an upward trend; however, the growth rate of green technology innovation showed a slowdown in 2021. Notably, there are disparities in the coupling coordination degree among cities, with economically developed areas exhibiting a faster growth rate. Moreover, green technology innovation significantly enhances carbon emission performance, and heterogeneity tests indicate that this impact is even more pronounced in cities with weaker environmental regulations. Despite regional differences, the overall trend remains positive.

EnergiesVol. 17(21)
Central South University of Forestry and Technology (CN), Central South University (CN), Hunan University (CN)
Openalex Percentile: Top 41%
Environmental Impact and Sustainability
0.41
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.