Can artificial intelligence technology innovation boost energy resilience? The role of green finance

Energy Economics, Journal Year: 2024, Volume and Issue: 142, P. 108159 - 108159

Published: Dec. 25, 2024

Language: Английский

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Can Intelligent Manufacturing Drive Green Development in China’s Pharmaceutical Industry? -- Evidence from Listed Enterprises

Energy, Journal Year: 2024, Volume and Issue: 308, P. 132953 - 132953

Published: Aug. 23, 2024

Language: Английский

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Towards Sustainable Development: Can Industrial Intelligence Promote Carbon Emission Reduction

Sustainability, Journal Year: 2025, Volume and Issue: 17(1), P. 370 - 370

Published: Jan. 6, 2025

The realization of intelligent transformation is an important path for the industry to move towards low-carbon development. Based on panel data from 30 provinces in China, this study utilizes intermediate effect model and spatial econometric analyze influence industrial intelligence carbon emissions. research reveals that helps with reduction, result still valid after undergoing various tests. Industrial relies green technological innovation, structure upgrading, energy intensity realize reduction. There a spillover role emissions, which has positive reduction local adjoining regions. emissions exhibits heterogeneity regional dimension, time level dimension. provides empirical evidence implications using artificial achieve

Language: Английский

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Building a Sustainable Future: The Nexus Between Artificial Intelligence, Renewable Energy, Green Human Capital, Geopolitical Risk, and Carbon Emissions Through the Moderating Role of Institutional Quality

Sustainability, Journal Year: 2025, Volume and Issue: 17(3), P. 990 - 990

Published: Jan. 25, 2025

Countries worldwide are focusing on energy efficiency, economic sustainability, and responsible resource management to address climate change meet sustainable development goals (SDGs). This study investigates how factors such as artificial intelligence, renewable energy, green human capital, geopolitical risk, natural rent, information communication technology influenced CO2 emissions in 36 countries between 2000 2021. The also explores institutional quality moderates these relationships. We employed advanced econometric techniques this gap, including panel-correlated standard errors (PCSE) the Driscoll–Kraay estimations (DKSE) models. A two-step system GMM approach was used strengthen robustness of our findings. findings reveal that consumption, can significantly reduce emissions. Conversely, contribute increased Institutional enhances positive impact capital emission reduction. However, it has opposite effect leading an even greater increase These underscore importance policies achieving goals. recommend policymakers prioritize investing clean while strengthening effectively mitigate carbon SDGs. They regulate AI ICT footprints risks through diversification international cooperation.

Language: Английский

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Accounting carbon emission responsibility on China's ICT sector under different principles based on the EE-MRIO model

Environmental Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: March 4, 2025

The purpose of this study is to investigate and compare the ICT sector's carbon emission responsibility under production-based (PBA), consumption-based (CBA), income-based accounting principle (IBA) shared-responsibility approach (SRA), focusing on case China. We utilise environmentally extended multiregional input-output (EE-MRIO) model based China's 2012 2017 provincial MRIO table. empirical finding demonstrate that responsibilities assigned sector CBA greater than those SRA, IBA PBA. Regional emissions are highly concentrated PBA IBA. absolute amount increased all method, but increase in national share varied significantly. inter-sectoral transfer pattern, shows exhibits dual lock-in effects, demonstrates strong supply-chain dependencies, upstream procurement anchored energy-intensive sectors (S23, S14, S13), while downstream consumption path-dependent concentration S23, S29. Inter-regional significant regional heterogeneity. In economically developed provinces like Guangdong, Beijing Zhejiang, has a downstream-pushing effect notable upstream-pulling other regions. Conversely, less northeastern northwestern provinces, sector, mainly serving local consumption, leads minimal effect. These results provide supportive references for China develop more integrated policies, supporting common differentiated reduction targets.

Language: Английский

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Artificial intelligence and enterprise pollution emissions: From the perspective of energy transition

Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108349 - 108349

Published: March 1, 2025

Language: Английский

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Evaluating the energy-saving and efficiency-enhancing potential of data factor marketization: Empirical evidence from 270 cities in China

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 378, P. 124686 - 124686

Published: March 5, 2025

Language: Английский

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Reducing carbon emission at the corporate level: Does artificial intelligence matter?

Environmental Impact Assessment Review, Journal Year: 2025, Volume and Issue: 114, P. 107911 - 107911

Published: March 11, 2025

Language: Английский

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Artificial Intelligence and Climate Change

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 355 - 362

Published: April 8, 2025

Deep in the depths of analytics and big data, AI can play a vital role understanding impacts climate change. This digital world is increasingly using technology to collect analyze environmental sift through this data highly granular way, seeking uncover trends patterns that help guide change efforts. In context challenge, scientists engineers are working together design powerful predictive models enable analysis future scenarios. advance necessary step towards better determining how humans adapt provide effective solutions.

Language: Английский

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Unleashing the Power of Artificial Intelligence: A Game Changer for Urban Energy Efficiency in China

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106372 - 106372

Published: April 1, 2025

Language: Английский

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