数字赋能、技术创新与空气污染治理——来自专利文本挖掘的证据

Abstract

The rapid development of digital technology and the diversification of its application scenarios have greatly changed traditional economic governance models, but the environmental effects of such technological innovation remain unclear. This paper uses text mining analysis techniques to construct refined national digital technology patent data and systematically studies the impact of digital technology innovation on China's ambient air quality, its channels of action, and its heterogeneous effects. The study finds that digital technology innovation significantly reduces China's air pollution levels, especially in the application of digital technologies such as artificial intelligence, big data, and 5G communication. Estimates show that the growth of digital technology patents reduces the national annual average PM2.5 concentration by 1.013 μg/m3, reducing losses in statistical life value by approximately 16.6 billion yuan. Mechanism analysis finds that digital technology innovation improves industrial enterprises' air pollution control effectiveness through the technological effect at the green innovation end and the governance effect at the production management end. Further analysis shows that the empowerment effect of digital technology differs significantly across technology categories, regions, and enterprise types. The conclusions of this paper have important policy implications for digital technology to empower air pollution control in a focused and categorized manner, improve the implementation of precise and differentiated control measures, and jointly promote high-level environmental protection and high-quality economic development.