How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology

Wei Zhou, Yan Zhuang and Yan Chen

Energy Economics, 2024, vol. 131, issue C

Abstract: Artificial intelligence (AI) can revolutionize production process by improving energy efficiency, reducing costs, and developing green technology. Among the most important applications of AI technology, industrial robots are increasingly being used in production and have become significant feature of high-quality ecinomic development. Concerning this issue, this study uses the provincial panel data from China from 2010 to 2019 to explore how adopting industrial robots affects regional pollution emissions. We find that industrial robots significantly reduce the pollution emissions intensity in various provinces of China, and this conclusion holds following a series of robustness tests. Mechanism analysis shows that industrial robots reduce pollutant emissions intensity by improving energy efficiency and enhancing pollution reduction technologies. Heterogeneity analyses reveal that industrial robots significantly reduce pollution emissions intensity in the eastern and western regions of China, as well as in regions outside the Yangtze River Economic Belt, while this effect is significant for the central region and the Yangtze River Economic Belt. Industrial robots primarily promote pollution reduction in the eastern region, rather than enhancing regional energy efficiency. For the western region and regions outside the Yangtze River Economic Belt, the reduction in pollution emissions intensity appears to be attributable to both mechanisms. The above findings enrich the study on the impact of industrial robots on green production behavior and provide insights into pollution emissions control for some provinces of China.

Keywords: Artificial intelligence; Pollution emissions; Energy efficiency; Artificial intelligence (AI) technology; Industrial robots (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:131:y:2024:i:c:s014098832400063x

DOI: 10.1016/j.eneco.2024.107355

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