
Research Square (Research Square), Год журнала: 2024, Номер unknown
Опубликована: Апрель 17, 2024
Язык: Английский
Research Square (Research Square), Год журнала: 2024, Номер unknown
Опубликована: Апрель 17, 2024
Язык: Английский
Journal of Environmental Management, Год журнала: 2024, Номер 353, С. 120174 - 120174
Опубликована: Фев. 1, 2024
Язык: Английский
Процитировано
21Energy, Год журнала: 2025, Номер unknown, С. 134496 - 134496
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
6Resources Policy, Год журнала: 2024, Номер 90, С. 104788 - 104788
Опубликована: Фев. 16, 2024
Язык: Английский
Процитировано
14Renewable Energy, Год журнала: 2024, Номер 232, С. 121025 - 121025
Опубликована: Июль 26, 2024
Язык: Английский
Процитировано
12Clean Technologies and Environmental Policy, Год журнала: 2024, Номер unknown
Опубликована: Авг. 1, 2024
Abstract The increase in energy intensity and depletion may lead to faster of natural resources increased environmental impacts. green transition can improve quality by reducing the pressure on carbon footprint. At this point, public regulations are significant for sustainability. On one hand, policy stringency imposes high taxes polluting activities and, other provides R&D support clean technologies. This study examines impact intensity, depletion, transition, load capacity factor G7 countries from 1990–2020 using common correlated effects mean group augmented panel long run estimators. study's robust results show that i) has a negative sustainability Germany, Italy, USA, ii) Canada France, iii) positive Japan. must reverse adverse accelerating energy. These with fiscal should use instruments include taxes. Graphical abstract
Язык: Английский
Процитировано
12Journal of Environmental Management, Год журнала: 2024, Номер 365, С. 121549 - 121549
Опубликована: Июль 1, 2024
Язык: Английский
Процитировано
11Energy, Год журнала: 2024, Номер 307, С. 132540 - 132540
Опубликована: Июль 26, 2024
Язык: Английский
Процитировано
11Resources Policy, Год журнала: 2024, Номер 95, С. 105198 - 105198
Опубликована: Июнь 28, 2024
Язык: Английский
Процитировано
10Sustainable Development, Год журнала: 2024, Номер unknown
Опубликована: Окт. 6, 2024
Abstract Artificial intelligence (AI) and environmental points are equally important components within the response to local weather change. Therefore, based on efforts of reducing carbon emissions more efficiently effectively, this study tries focus AI integration with capture technology. The urgency tackling climate change means we need advanced capture, is an area where can make a huge impact in how these technologies operated managed. It will minimize manufacturing improve both resource efficiency as well our planet's footprint by turning waste into something value again. could be leveraged analyze data sets from plants, searching for optimal system settings efficient ways identifying patterns available information at larger scale than currently possible. In addition, incorporated sensors monitoring mechanisms supply chain identify any operational failure reception itself allowing timely action protect those areas. also helps generative design materials, which allows researchers explore new types carbon‐absorbing material, including metal–organic frameworks polymeric materials that industrial CO 2 , such moisture. it increases accuracy reservoir simulations controls injection systems storage or enhanced oil recovery. Through applying algorithms geology, production performance real‐time would like facilitate optimization processes while assuring maximum efficiency. integrates renewable‐based employed AI‐driven smart grid methods.
Язык: Английский
Процитировано
9Energy & Environment, Год журнала: 2024, Номер unknown
Опубликована: Сен. 26, 2024
This study explored the ecological footprint in South Korea, and it lacks substantial research on its footprint, which illustrates environmental impact of economic growth, adherence to rule law, adoption renewable energy, exportation petroleum. To this end, examined relationship between GDP petroleum exports Korea using dataset spanning 1990 2022. The employed Autoregressive Distributed Lag (ARDL), robustness tests (fully modified ordinary least squares, dynamic canonical cointegrating regression) including Granger Causality. Based outcomes ARDL method (i) law use energy sources dampens (ii) upsurges long run, (iii) fuel improved short-run. Causality test shows that there is unidirectional consumption, means causes all explanatory variables investigated. findings highlight importance well-coordinated policy implementation by policymakers order stop Korea's notable degradation. Policy makers should invest sector; actively support execution strict legal guidelines growth sources.
Язык: Английский
Процитировано
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