Environment Development and Sustainability, Год журнала: 2024, Номер unknown
Опубликована: Дек. 2, 2024
Язык: Английский
Environment Development and Sustainability, Год журнала: 2024, Номер unknown
Опубликована: Дек. 2, 2024
Язык: Английский
Applied Energy, Год журнала: 2024, Номер 363, С. 123081 - 123081
Опубликована: Март 26, 2024
Язык: Английский
Процитировано
35Journal of Environmental Management, Год журнала: 2025, Номер 376, С. 124416 - 124416
Опубликована: Фев. 8, 2025
Язык: Английский
Процитировано
3Ecological Indicators, Год журнала: 2024, Номер 166, С. 112263 - 112263
Опубликована: Июнь 22, 2024
Язык: Английский
Процитировано
10Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144912 - 144912
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1Energy, Год журнала: 2025, Номер unknown, С. 135279 - 135279
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
1Sustainability, Год журнала: 2024, Номер 16(9), С. 3671 - 3671
Опубликована: Апрель 27, 2024
The ecological environment of the Wuling Mountains region has been impacted by climate change and economic development, necessitating immediate reinforcement protection restoration measures. study utilized normalized vegetation index (NDVI) as a proxy for resilience. NDVI data from 2000 to 2020 were employed compute resilience area examine its spatial temporal evolution well factors influencing it. findings indicate that: (1) increased in Guizhou, Chongqing, Hunan sub-areas but decreased Hubei sub-area. (2) varies significantly Hubei, sub-regions, whereas it less Chongqing sub-region. (3) primary elements capability four are conditions socio-economic factors, respectively. can offer scientific foundation conservation efforts area, serve benchmark measuring other environmentally vulnerable regions.
Язык: Английский
Процитировано
5Ecological Indicators, Год журнала: 2024, Номер 166, С. 112352 - 112352
Опубликована: Июль 11, 2024
Язык: Английский
Процитировано
5Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 105933 - 105933
Опубликована: Окт. 1, 2024
Язык: Английский
Процитировано
4Frontiers in Environmental Economics, Год журнала: 2025, Номер 3
Опубликована: Янв. 9, 2025
Artificial intelligence (AI) plays a pivotal role in the development of green economy. This paper examines impact artificial on economic efficiency (GEE) using panel data from 30 provinces China spanning 2011–2020. A multiple linear regression model, alongside various endogeneity and robustness tests, is applied to ensure reliable findings. The empirical results indicate that AI significantly enhances GEE. However, marginal effect GEE influenced by different governance approaches. In terms policy governance, excessive market-based environmental regulation (MER) diminishes AI, while stronger administrative-command regulations (CER) informal (IER) amplify it. Regarding technological substantive innovations (SUG) reduce AI's effect, whereas symbolic (SYG) may increase Notably, threshold SUG surpasses SYG. legal both administrative judicial intellectual property protections though protection (AIP) exhibits more significant than (JIP). These findings offer practical insights for optimizing strategies maximize promoting highlight need balanced sustainable development. Policymakers should tailor encourage regional collaboration harness spatial spillover effects. Enterprises can leverage AI-driven align growth with ecological goals, fostering coordinated
Язык: Английский
Процитировано
0Sustainability, Год журнала: 2025, Номер 17(3), С. 869 - 869
Опубликована: Янв. 22, 2025
This study adopts a sustainable development perspective to examine the economic and ecological coordinated progression spatial disparities across 30 regions in China from 2011 2022. Firstly, detailed analysis of CCD reveals that coordination between ES (economic subsystem) EES (ecological environment has been rising annually. However, overall level remains relatively limited. Second, kernel density estimation (KDE) shows degree various exhibits considerable variability, with disparity becoming increasingly pronounced. Third, trend surface (TS) indicates there exist regional variations EES. Specifically, east experiences an upward trend, while west downward trend. Similarly, south increase, whereas north demonstrates decrease. With ongoing development, it observed stable east–west direction; however, is increasing. Fourth, global Moran’s I pronounced positive autocorrelation. Finally, local Jiangsu, Fujian, Anhui, Jiangxi provinces exhibit significant high–high clusters, three Xinjiang, Gansu, Ningxia have always low–low clusters.
Язык: Английский
Процитировано
0