
Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 113037 - 113037
Published: Dec. 30, 2024
Language: Английский
Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 113037 - 113037
Published: Dec. 30, 2024
Language: Английский
Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106204 - 106204
Published: Feb. 1, 2025
Language: Английский
Citations
0Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108297 - 108297
Published: Feb. 1, 2025
Language: Английский
Citations
0Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13
Published: March 25, 2025
Industrial carbon emission reduction is not only the need to cope with climate change and environmental pollution, but also an important way achieve sustainable economic development. This paper first constructs evaluation system of urban green development index from four dimensions: economy, society, resources environment. Then, undesirable super-efficiency SBM model used measure static industrial efficiency, spatiotemporal characteristics dynamic efficiency are analyzed by combining Malmquist index. Finally, was incorporated into Tobit regression model, impact energy intensity, structure other factors on considered. cited 18 cities in Sichuan Province 2015 2022 as example for analysis. The results show that overall level shows a downward trend, there great room improvement average 0.740, difference mainly due pure technical efficiency. From 2022, Sichuan’s showed trend stable then decreasing. There significant positive correlation between emissions. Altogether, established this vital magnitude low-carbon regional industry.
Language: Английский
Citations
0Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11006 - 11006
Published: Dec. 15, 2024
To achieve economic resilience and green, low-carbon development are two goals of China’s high-quality development. This paper uses the entropy weight method coupling coordination degree model to estimate level Kernel density estimation, Moran index, Dagum Gini coefficient, Markov chain, obstacle used explore spatiotemporal evolution characteristics factors. The results as follows. (1) between has increased overall. However, eastern region highest, central fastest growth. (2) shows positive spatial autocorrelation, with most provinces exhibiting high–high or low–low aggregation characteristics. (3) contribution imbalance mainly comes from inter-regional differences, but intra-regional differences is increasing. (4) spatio-temporal pattern generally better, probability maintaining initial state largest. neighborhood’s affects transition does not affect that high-level provinces. (5) Innovation capacity main improving resilience, per capita water resources green Finally, this puts forward suggestions for creating a good innovation environment, increasing R&D investment, promoting technology progress, optimizing regional cooperation resource allocation, industrial transformation.
Language: Английский
Citations
1Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 113037 - 113037
Published: Dec. 30, 2024
Language: Английский
Citations
0