空气污染
空气质量指数
环境治理
温室气体
环境经济学
公司治理
中国
业务
污染
资源(消歧)
高效能源利用
自然资源经济学
环境规划
环境资源管理
环境科学
工程类
政治学
计算机科学
地理
经济
生态学
气象学
计算机网络
电气工程
财务
法学
生物
作者
Zhongzhu Chu,Pengyu Chen,Zihan Zhang,Zitao Chen
标识
DOI:10.1016/j.jenvman.2024.120171
摘要
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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