Green bonds and carbon prices: a dynamic relationship revealed DOI
Kai-Hua Wang, Shumei Li

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 10, 2024

Language: Английский

How does corporate digital transformation affect green innovation? Evidence from China's enterprise data DOI
Jian Zhang, Chin‐Hsien Yu, Jinsong Zhao

et al.

Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108217 - 108217

Published: Jan. 1, 2025

Language: Английский

Citations

5

Tracking the provincial energy transition in China: A comprehensive index DOI

Dequn Zhou,

Ting Chen, Hao Ding

et al.

Energy, Journal Year: 2024, Volume and Issue: 304, P. 131879 - 131879

Published: June 7, 2024

Language: Английский

Citations

8

Analysis of the spatial–temporal evolution and driving factors of carbon emission efficiency in the Yangtze River economic Belt DOI Creative Commons
Yanzhi Jin, Kerong Zhang, Dongyang Li

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 165, P. 112092 - 112092

Published: May 27, 2024

As an important economic growth pole and ecological area in China, the urban agglomeration of Yangtze River Economic Belt (YREB) is key to carbon emission reduction. Exploring spatial–temporal evolution driving variables its efficiency (CEE) crucial for realizing goals peaking neutrality. The super-efficiency SBM model, nuclear density method, spatial autocorrelation method were used discuss CEE characteristics 105 cities YREB. On factors emissions, geographic detector Tobit model combined explore differentiation from perspective heterogeneity, concurrently analyze single-factor's effecting intensity impacting direction, as well dual-factors' interaction effects. findings indicated that YREB generally showed a slow upward trend during 2006–2021. From time dynamic evolution, intensified, overall development was toward high level. Furthermore, results pattern presents "downstream areas > midstream upstream areas", "high east low west", "hot cold while clustering effect significant, showing distributions low-low or high-high clustering. Moreover, government intervention, growth, technological progress main factors. In addition, interactions intervention other significantly detected. regression advancement had favorable impact on CEE, but foreign investment, urbanization, involvement negative impacts. future, correlations between provinces should be strengthened amplified promote integrated green development, improve environments.

Language: Английский

Citations

7

Multiscale coupled development and linkage response evaluation of China's carbon neutrality and sustainable development capability–A quantitative analysis perspective DOI
Wei Guo,

Ling Lv,

Xuesheng Zhao

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 200, P. 114569 - 114569

Published: May 21, 2024

Language: Английский

Citations

6

Curbing regional carbon emissions through green technology innovation: an empirical analysis in China DOI
Lingjun Guo, Wenyu Tan, Yi Xu

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: July 17, 2024

Language: Английский

Citations

4

Coupling coordination and spatial network characteristics of carbon emission efficiency and urban green innovation in the Yellow River Basin, China DOI Creative Commons
Keyao Yu, Zhigang Li

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 12, 2024

Carbon emission and sustainable development have attracted global attention. Promoting urban green innovation (UGI) in the Yellow River Basin (YRB) will help lowering intensity of carbon emissions improve safety sustainability. A SBM-DEA model was constructed to measure efficiency (CEE) degree coupling coordination with UGI calculated 73 prefecture-level cities YRB. The spatial association network CEE coupled is by using a modified gravity model, social analysis quadratic assignment procedure (QAP), analyze potential energy, characteristics clustering characteristics. study found that: (1) YRB shows fluctuating growth, mutual promotion continuous coordinated development. (2) linkage between gradually close, energy increases year year, obvious spillover effect, indicating that radiation influence are increasing. In contrast middle stream, upstream downstream regions show higher percentage entire network, their structure more intricate robust. (3) patterns three major clusters examined block exploring positioning functions various these conglomerations, which includes net spillover, benefit, two-way broker plate, so as strengthen connection cities. (4) Factors such adjacency, industrial structure, population density, digital economy urbanization level, significantly impact along temporal regional heterogeneity. Therefore, tailored policies needed collaboration UGI, fostering circular promoting

Language: Английский

Citations

4

Exploring the Impact of Ecological Degradation on the Green Development Efficiency: An Empirical Analysis Using the Novel Epsilon‐Based Measure and Global Malmquist–Luenberger Index DOI Open Access
Mahamane Famanta,

Abid Ali Randhawa,

Bilal Hussain

et al.

Geological Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 29, 2025

ABSTRACT The profound consequences of ecological degradation on humanity's well‐being are a severe matter acknowledged globally. This study examines the impact green development efficiency in less developed countries. A dataset from 1990 to 2020 was used break down impacts efficiency. Green calculated based epsilon‐based measure model, while dynamic change explored with Global Malmquist‐Luenberger Index model. panel‐corrected standard errors (PCSE) and feasible generalised least squares (FGLS) models conducted test influence results show that inhibits efficiency, whereas FDI, urbanisation, economic growth benefit increase In addition, government intervention shows negative correlation spatial Durbin model (SDM) also demonstrate an overall strong spillover effect local neighbouring regions, more significant effects at levels surroundings.

Language: Английский

Citations

0

The impact and spatial externalities of unstable power supply on the low-carbon transition in China DOI
Zhao Chen, Jian Yu, Peng Liu

et al.

Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108306 - 108306

Published: Feb. 1, 2025

Language: Английский

Citations

0

Spatial Effects of Financial Agglomeration and Green Technological Innovation on Carbon Emissions DOI Open Access
Zhijie Hao,

Ziqian Zhao,

Zhiwei Pan

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2746 - 2746

Published: March 19, 2025

Financial agglomeration and green technology innovation are important measures to reduce carbon emissions promote the development of a economy. Based on panel data 30 provinces cities in China from 2011 2020, this paper uses locational entropy method emission coefficient measurement provided IPCC inventory guide establish spatial econometric model explore specific impact financial emission. The results show that (1) both will emissions; (2) when considering effect, effectively (3) influence has regional heterogeneity. Only can significantly eastern region. central region emissions. western emissions, but lead an increase This provides useful suggestions for optimizing industry’s structure, improving level technology, alleviating environmental pollution.

Language: Английский

Citations

0

The key role of digital governance, natural resource depletion, and industrialization in social well-being: A case study of China DOI

Yasong Zhou,

Yuqing Li, Chen Chen

et al.

Resources Policy, Journal Year: 2024, Volume and Issue: 93, P. 104969 - 104969

Published: May 13, 2024

Language: Английский

Citations

2