How does environmental regulation affect the double dividend for energy firms? Evidence from China’s EPT policy DOI

Youyi Deng,

Kangyin Dong, Farhad Taghizadeh‐Hesary

et al.

Economic Analysis and Policy, Journal Year: 2023, Volume and Issue: 79, P. 807 - 820

Published: July 5, 2023

Language: Английский

Co-benefits of policies to reduce air pollution and carbon emissions in China DOI

Botong Xian,

Yalin Xu,

Wei Chen

et al.

Environmental Impact Assessment Review, Journal Year: 2023, Volume and Issue: 104, P. 107301 - 107301

Published: Oct. 2, 2023

Language: Английский

Citations

57
Spatially resolved air quality index prediction in megacities with a CNN-Bi-LSTM hybrid framework DOI

Reza Rabie,

Milad Asghari, Hossein Nosrati

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 109, P. 105537 - 105537

Published: May 18, 2024

Language: Английский

Citations

17
Collaborative governance of carbon reduction in urban agglomerations in the China Yangtze River Economic Belt based on a spatial association network DOI Creative Commons
Feifei Zhao,

Shuai Qian,

Xu Zhao

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 154, P. 110663 - 110663

Published: July 17, 2023

Urban agglomerations are the key areas to promote carbon dioxide (CO2) reduction. Understanding association of CO2 emission urban and their influencing factors is significant synergistic management reduction in Yangtze River Economic Belt (YREB). Based on data three major YREB from 2010 2020, this study summarised characteristics structure agglomerations, explored affecting spatial emissions each agglomeration, proposed countermeasures collaborative accordingly. Results show that correlations increase year by year, have “dense east sparse west,” network correlation differ significantly among agglomerations. The linkage has formed a block division with as boundary, linkages between relatively weak. status role city different, formation paths different agglomerations; therefore, differentiated policies need be formulated for region. above findings provide realistic support constructing strategy first-before-supporting manner.

Language: Английский

Citations

29
Interaction mechanisms of urban ecosystem resilience based on pressure-state-response framework: A case study of the Yangtze River Delta DOI Creative Commons
Changgan Zhang,

Yijing Zhou,

Shanggang Yin

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112263 - 112263

Published: June 22, 2024

Language: Английский

Citations

10
Impact of dual-carbon attention competition from local government on regional carbon emissions in China DOI
Kai Chang, Susheng Wang

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 374, P. 124064 - 124064

Published: Jan. 13, 2025

Language: Английский

Citations

1
Spatiotemporal evolution and driving factors of the synergistic effects of pollution control and carbon reduction in China DOI Creative Commons
Qinggang Meng, Xiaolan Chen, Hui Wang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113103 - 113103

Published: Jan. 1, 2025

Language: Английский

Citations

1
International digital trade and synergetic control of pollution and carbon emissions: Theory and evidence based on a nonlinear framework DOI
Zihao Li, Yue Wang, Tingting Bai

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 376, P. 124450 - 124450

Published: Feb. 10, 2025

Language: Английский

Citations

1
Synergistic effect assessment of pollution and carbon reduction and pathway of green transformation at regional level in China DOI
Ruixi Zhao, Changjun Hu,

Chunlei Du

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145013 - 145013

Published: Feb. 1, 2025

Language: Английский

Citations

1
Evaluation of CO2 and SO2 synergistic emission reduction: The case of China DOI
Qingwei Shi, Qianqian Liang, Tengfei Huo

et al.

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 433, P. 139784 - 139784

Published: Nov. 18, 2023

Language: Английский

Citations

19
Improving the explainability of CNN-LSTM-based flood prediction with integrating SHAP technique DOI Creative Commons
Hao Huang,

Zhaoli Wang,

Yaoxing Liao

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 84, P. 102904 - 102904

Published: Nov. 17, 2024

Language: Английский

Citations

6