Achieving pollution abatement and carbon reduction synergistically: How can industrial robots play a role? DOI
Chongchong Xu,

Helen Lv Zhang,

Boqiang Lin

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123816 - 123816

Published: Dec. 24, 2024

Language: Английский

How does Energy Quota Trading Affect the Corporate Pollution Gap? Evidence from China DOI
Zhaoxuan Qiu, Jincheng Li, Bei Liu

et al.

Economic Modelling, Journal Year: 2025, Volume and Issue: unknown, P. 107025 - 107025

Published: Jan. 1, 2025

Language: Английский

Citations

1
Achieving the synergy of pollution and carbon emission reductions: Can artificial intelligence applications work? DOI
Jie Dian, Shanmin Li,

Song Tian

et al.

China Economic Review, Journal Year: 2025, Volume and Issue: unknown, P. 102389 - 102389

Published: March 1, 2025

Language: Английский

Citations

1
How public environmental appeals affect the collaborative governance in pollution and carbon reduction: Evidence from spatial effects across Chinese cities DOI
Ning Zhao,

Meilin Jin,

Zhaoxuan Qiu

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 256, P. 119249 - 119249

Published: May 27, 2024

Language: Английский

Citations

8
Does Income Inequality Undermine the Carbon Abatement Benefits of Artificial Intelligence? DOI
Zequn Dong,

Lingran Zhang,

C. P.-P. Tan

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 472, P. 143437 - 143437

Published: Aug. 18, 2024

Language: Английский

Citations

6
How does financial openness affect pollution emission of industrial enterprises?—Empirical evidence from the entry of foreign banks in China DOI
Bei Liu,

Xing Bao,

Zhaoxuan Qiu

et al.

Sustainable Development, Journal Year: 2023, Volume and Issue: 32(4), P. 2910 - 2930

Published: Nov. 13, 2023

Abstract Currently, the effects of financial openness (FO) on environment have not been assessed at micro level enterprises. This article uses difference‐in‐differences method to explore pollution abatement effect FO. The results show that FO can effectively promote with a significant environmental performance enhancement effect. In addition, is stronger in large, heavy industrial, and state‐owned Besides, significantly alleviates financing constraints promotes by driving R&D investment strengthening intensity end‐of‐pipe treatment. Policy recommendations are given steadily expand pattern, improve disclosure system small medium‐sized enterprises, optimize subsidies for increased stimulate abatement. A reference other emerging economies, especially transitioning provided fully utilize under construction or improvement realize value control.

Language: Английский

Citations

13
Information consumption city and carbon emission efficiency: Evidence from China's quasi-natural experiment DOI
Xujun Liu, Yuanqing Luo,

Shengtie Guo

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 255, P. 119182 - 119182

Published: May 19, 2024

Language: Английский

Citations

5
The Non-linear Impact of Digital Trade Development on Carbon Emissions: Evidence from Chinese Cities DOI Creative Commons

Xiangxiang Zhou,

Hui Guo

Energy Nexus, Journal Year: 2025, Volume and Issue: unknown, P. 100390 - 100390

Published: Feb. 1, 2025

Language: Английский

Citations

0
Industrial Robotics, Resource Efficiency, Energy Transition, and Environmental Quality: Designing a Sustainable Development Goals Framework for G7 Countries in the Presence of Geopolitical Risk DOI Open Access

Yuhan Xia,

Mahmood Ahmad

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 1960 - 1960

Published: Feb. 25, 2025

In recent years, the integration of industrial robotics has emerged as a powerful tool in reshaping industries by enhancing production efficiency, reducing waste generation, and optimizing resource utilization. However, robotics, particularly manufacturing production, require significant energy that can potentially impact on environmental quality. Despite growing adoption artificial intelligence (AI)-based there is paucity literature ecological footprint (EF), context advanced economies. this context, study aims to investigate transition, geopolitical risk EF G7 countries from 1993 2021. The employed econometric techniques, including Kernel-based Regularized Least Squares (KRLS) Artificial Neural Network (ANN) machine learning methods. results unveiled significantly curtail degradation impeding EF. Resource efficiency transition posed negative Geopolitical risks economic growth exacerbate Based results, proposes important policy implications for achieving sustainable development.

Language: Английский

Citations

0
Artificial intelligence and enterprise pollution emissions: From the perspective of energy transition DOI

Youcai Yang,

Xiaotong Niu,

Changgui Lin

et al.

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

Published: March 1, 2025

Language: Английский

Citations

0
Reducing carbon emission at the corporate level: Does artificial intelligence matter? DOI
Yanchao Feng, Yuying Yan, Ke Shi

et al.

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

Published: March 11, 2025

Language: Английский

Citations

0