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Other's shoes also fit well: AI technologies contribute to China's blue skies as well as carbon reduction.
Chu, Zhongzhu; Chen, Pengyu; Zhang, Zihan; Chen, Zitao.
Affiliation
  • Chu Z; School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200030, China. Electronic address: zhongzhu_chu@sjtu.edu.cn.
  • Chen P; School of Economics and Management, Inner Mongolia University, Inner Mongolia, 010021, China.
  • Zhang Z; School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200030, China; School of Emergency Management, Shanghai Jiao Tong University, Shanghai, 200030, China.
  • Chen Z; School of Media and Communication, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address: ztchen24@foxmail.com.
J Environ Manage ; 353: 120171, 2024 Feb 27.
Article in En | MEDLINE | ID: mdl-38278110
ABSTRACT
Artificial intelligence (AI) technology represents a disruptive innovation that has garnered significant interest among researchers for its potential applications in ecological and environmental management. While many studies have investigated the impact of AI on carbon emissions, relatively few have delved into its relationship with air pollution. This study sets out to explore the causal mechanisms and constraints linking AI technologies and air pollution, using provincial panel data collected from 2007 to 2020 in China. Furthermore, this study examines the distinct pathways through which AI technology can ameliorate air pollution and reduce carbon emissions. The findings reveal the following key insights (1) AI technologies have the capacity to significantly reduce air pollution, particularly in terms of PM2.5 and SO2 levels. (2) AI technologies contribute to enhanced air quality by facilitating adjustments in energy structures, improving energy efficiency, and strengthening digital infrastructure. Nonetheless, it is important to note that adjusting the energy structure remains the most practical approach for reducing carbon emissions. (3) The efficacy of AI in controlling air pollution is influenced by geographical location, economic development level, level of information technology development, resource dependence, and public attention. In conclusion, this study proposes novel policy recommendations to offer fresh perspectives to countries interested in leveraging AI for the advancement of ecological and environmental governance.
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Full text: 1 Database: MEDLINE Main subject: Air Pollutants / Air Pollution Type of study: Guideline Country/Region as subject: Asia Language: En Journal: J Environ Manage Year: 2024 Type: Article

Full text: 1 Database: MEDLINE Main subject: Air Pollutants / Air Pollution Type of study: Guideline Country/Region as subject: Asia Language: En Journal: J Environ Manage Year: 2024 Type: Article