Harnessing artificial intelligence for environmental protection: Smart air quality management under oil price fluctuations

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics Pub Date : 2025-09-10 DOI:10.1016/j.eneco.2025.108892

Meng Qin , Xuefeng Shao , Yujie Zhu , Cheng-To Lin

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Abstract

Investigating the capacity of artificial intelligence (AI) to enhance air quality represents a critical research area for achieving sustainable development goals. This study employs a mixed-frequency vector autoregression (MF-VAR) model to examine the impact of AI on U.S. carbon emission (CE) from the first week of June 2018 through the fourth week of July 2024, while controlling for oil market dynamics. The MF-VAR impulse responses reveal that AI has an initial positive impact on CE, which subsequently transitions to an adverse effect, and it turns positive again at the fifth or sixth period. The increase-decrease-rebound effect of AI on CE indicates that harnessing AI for cleaner air presents both opportunities and challenges. Furthermore, the analyses based on seasonally adjusted CE, expanded control variables, and an alternative mixed-frequency model confirm the robustness of our empirical analyses. In the context of escalating climate risks, our findings underscore the need for an integrated policy framework that harnesses the potential of AI for cleaner air while mitigating its environmental footprint.

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利用人工智能保护环境：油价波动下的智能空气质量管理

研究人工智能（AI）改善空气质量的能力是实现可持续发展目标的一个关键研究领域。本研究采用混合频率向量自回归（MF-VAR）模型，在控制石油市场动态的情况下，研究了2018年6月第一周至2024年7月第四周人工智能对美国碳排放（CE）的影响。MF-VAR脉冲响应表明，AI对CE具有初始的积极影响，随后转变为不利影响，并在第五或第六个周期再次变为积极影响。人工智能对碳排放的增加-减少-反弹效应表明，利用人工智能清洁空气既有机遇，也有挑战。此外，基于季节调整CE、扩展控制变量和替代混合频率模型的分析证实了我们的实证分析的稳健性。在气候风险不断升级的背景下，我们的研究结果强调需要一个综合政策框架，利用人工智能清洁空气的潜力，同时减轻其环境足迹。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Energy Economics ECONOMICS-

CiteScore

18.60

自引率

12.50%

发文量

524

期刊介绍： Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.