Does artificial intelligence promote energy transition and curb carbon emissions? The role of trade openness

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 447, P. 141298 - 141298

Published: Feb. 15, 2024

Language: Английский

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Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)

Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 14, 2024

Abstract This study examines the multifaceted impact of artificial intelligence (AI) on environmental sustainability, specifically targeting ecological footprints, carbon emissions, and energy transitions. Utilizing panel data from 67 countries, we employ System Generalized Method Moments (SYS-GMM) Dynamic Panel Threshold Models (DPTM) to analyze complex interactions between AI development key metrics. The estimated coefficients benchmark model show that significantly reduces footprints emissions while promoting transitions, with most substantial observed in followed by footprint reduction reduction. Nonlinear analysis indicates several insights: (i) a higher proportion industrial sector diminishes inhibitory effect but enhances its positive transitions; (ii) increased trade openness amplifies AI’s ability reduce promote (iii) benefits are more pronounced at levels development, enhancing (iv) as transition process deepens, effectiveness reducing increases, role further transitions decreases. enriches existing literature providing nuanced understanding offers robust scientific foundation for global policymakers develop sustainable management frameworks.

Language: Английский

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How does geopolitical risk affect carbon emissions?: An empirical study from the perspective of mineral resources extraction in OECD countries

Resources Policy, Journal Year: 2023, Volume and Issue: 85, P. 103983 - 103983

Published: July 30, 2023

Language: Английский

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Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy

Energy Economics, Journal Year: 2024, Volume and Issue: 131, P. 107403 - 107403

Published: Feb. 12, 2024

Language: Английский

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Rethinking the environmental Kuznets curve hypothesis across 214 countries: the impacts of 12 economic, institutional, technological, resource, and social factors

Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)

Published: Feb. 21, 2024

Abstract Research over the past three decades has provided rich empirical evidence for inverted U-shaped EKC theory, but current problems facing advancing climate mitigation actions require us to re-examine shape of global rigorously. This paper examined N-shaped in a panel 214 countries with 12 traditional and emerging variables, including institutions risks, information communication technology (ICT), artificial intelligence(AI), resource energy use, selected social factors. The two-dimensional Tapio decoupling model based on group homogeneous is developed explore inter-group heterogeneous carbon emission effects each variable. Global research results show that linear cubic terms GDP per capita are significantly positive, while quadratic term negative, regardless whether additional variables added. means robust existence an EKC. Geopolitical risk, ICT, food security confirmed positively impact emissions, composite institutional quality, digital economy, transition, population aging negative. AI, natural rents, trade openness, income inequality insignificant. inflection points considering all 45.08 73.44 thousand US dollars, respectively. Combining turning calculated coefficients, categorized into six groups model. subsequent regression heterogeneity direction magnitude impacts most variables. Finally, differentiated reduction strategies stages proposed.

Language: Английский

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Artificial intelligence and sustainable development during urbanization: Perspectives on AI R&D innovation, AI infrastructure, and AI market advantage

Sustainable Development, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 27, 2024

Abstract This study explores the impact of artificial intelligence (AI) on sustainable development across 51 countries during urbanization. Using panel data, examines AI's effects through three dimensions: R&D innovation, infrastructure, and market advantage. The results demonstrate that AI promotes development, with innovation exerting strongest influence, followed by whereas advantage has smallest impact. Additionally, uncovers regional heterogeneity in impacts. In upper middle levels (60%–70% quantiles), promoting effect is strongest. Moreover, urbanization plays a threshold role relationship between development. When below threshold, infrastructure promote inhibit it. Conversely, when exceeds this inhibits becomes insignificant, begin to recommends governments should consider level crafting policies utilizing AI.

Language: Английский

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Assessing the synergistic effects of artificial intelligence on pollutant and carbon emission mitigation in China

Energy Economics, Journal Year: 2024, Volume and Issue: 138, P. 107829 - 107829

Published: Aug. 12, 2024

Language: Английский

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Impact of artificial intelligence on renewable energy supply chain vulnerability: Evidence from 61 countries

Energy Economics, Journal Year: 2024, Volume and Issue: 131, P. 107357 - 107357

Published: Feb. 19, 2024

Language: Английский

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Unveiling the role of artificial intelligence in influencing enterprise environmental performance: Evidence from China

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 440, P. 140934 - 140934

Published: Jan. 24, 2024

Language: Английский

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Evaluating the synergistic effects of digital economy and government governance on urban low-carbon transition

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 105, P. 105337 - 105337

Published: March 11, 2024

Language: Английский

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