人工智能驱动的绿色创新促进可持续发展:来自印度可再生能源转型的经验见解。

IF 8.4 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Journal of Environmental Management Pub Date : 2025-08-01 Epub Date: 2025-06-19 DOI:10.1016/j.jenvman.2025.126285
Biswanath Behera, Puspanjali Behera, Ugur Korkut Pata, Litu Sethi, Narayan Sethi
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引用次数: 0

摘要

本文探讨了人工智能(AI)、绿色技术创新(GTI)和可再生能源发电(REG)对印度可持续发展的贡献,并特别关注了它们与可持续发展目标(sdg)的一致性。利用1987 - 2020年的数据,运用动态ARDL模拟方法,分析了人工智能对绿色增长的直接和调节作用。结果表明,虽然REG单独对绿色增长的影响不显著(0.073%),但AI和GTI显著促进了长期绿色增长。具体而言,人工智能对长期绿色增长的贡献率为0.241%,GTI为0.163%,支持可持续发展目标8(体面劳动和经济增长)和可持续发展目标9(产业、创新和基础设施)。此外,交互效应表明,人工智能显著增强了REG的有效性(交互系数为0.017%),促进了符合可持续发展目标7(负担得起的清洁能源)的清洁能源转型。同样,人工智能增强了GTI的贡献(相互作用系数为0.041%),加强了环境质量,以支持可持续发展目标13(气候行动)。通过KRLS估计器进行鲁棒性检查确认了这些关系。政策影响表明,将人工智能纳入能源和创新政策可以扩大可持续性成果。因此,印度要实现可持续发展目标,向低碳、创新驱动型经济转型,就必须制定一项包括数字化转型、技术融资和机构支持在内的协调战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence-driven green innovation for sustainable development: Empirical insights from India's renewable energy transition.

This paper explores the contribution of artificial intelligence (AI), green technology innovation (GTI), and renewable energy generation (REG) to sustainable development in India, with a specific focus on their alignment with the Sustainable Development Goals (SDGs). Employing data from 1987 to 2020 and applying the Dynamic ARDL simulation approach, the study analyzes both direct and moderating effects of AI on green growth. The outcomes illustrate that while REG alone has a statistically insignificant impact on green growth (0.073 %), AI and GTI significantly promote long-term green growth. Specifically, AI contributes 0.241 % and GTI 0.163 % to long-term green growth, supporting SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). Moreover, interaction effects show that AI significantly enhances the effectiveness of REG (with an interaction coefficient of 0.017 %), facilitating a cleaner energy transition in line with SDG 7 (Affordable and Clean Energy). Similarly, AI enhances the contribution of GTI (with an interaction coefficient of 0.041 %), reinforcing environmental quality in support of SDG 13 (Climate Action). Robustness checks via the KRLS estimator confirm these relationships. Policy implications suggest that integrating AI into energy and innovation policies can amplify sustainability outcomes. Hence, a coordinated strategy encompassing digital transformation, technology financing, and institutional support is essential for India to meet its SDG targets and transition toward a low-carbon, innovation-driven economy.

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来源期刊
Journal of Environmental Management
Journal of Environmental Management 环境科学-环境科学
CiteScore
13.70
自引率
5.70%
发文量
2477
审稿时长
84 days
期刊介绍: The Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made.Critical review articles are also welcome; submission of these is strongly encouraged.
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