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Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms

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  • Yang Shen

    (Institute of Quantitative Economics, Huaqiao University, Xiamen 361021, China)

  • Zhihong Yang

    (School of Economics and Management, Northwestern University, Xi’an 710127, China)

Abstract

The coordinated promotion of pollution control and carbon reduction is intended to build a more beautiful China. Intelligent industrial technology plays an important role in the fight against climate change and in improving the ecological environment. Based on panel data from 30 provinces in China from 2006 to 2020, we used a two-way fixed effects model to evaluate the synergistic effects of industrial intelligent transformation on pollution control and carbon reduction and its mechanisms. The results showed that the introduction and installation of industrial robots by enterprises significantly reduced carbon emissions and the concentration of fine particles in the air, as well as having the synergistic effect of reducing pollution and carbon. This conclusion was still robust after using instrumental variable methods to perform endogenous tests. The study also showed that industrial intelligence reduced pollution and carbon through mechanisms that promoted green technological innovation and improved energy efficiency. The conclusions of this study could provide evidence for the use of digital technologies to promote environmental protection and achieve the goal of carbon neutrality, as well as play a significant role in the promotion of economic and societal green transformation.

Suggested Citation

  • Yang Shen & Zhihong Yang, 2023. "Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms," Sustainability, MDPI, vol. 15(8), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6401-:d:1118968
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    as
    1. Daron Acemoglu & Philippe Aghion & Leonardo Bursztyn & David Hemous, 2012. "The Environment and Directed Technical Change," American Economic Review, American Economic Association, vol. 102(1), pages 131-166, February.
    2. Wang, Linhui & Wang, Hui & Cao, Zhanglu & He, Yongda & Dong, Zhiqing & Wang, Shixiang, 2022. "Can industrial intellectualization reduce carbon emissions? — Empirical evidence from the perspective of carbon total factor productivity in China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    3. Keyong Zhang & Sulun Li & Peng Qin & Bohong Wang, 2022. "Spatial and Temporal Effects of Digital Technology Development on Carbon Emissions: Evidence from China," Sustainability, MDPI, vol. 15(1), pages 1-16, December.
    4. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    5. Cai, Jinyang & Zheng, Huanyu & Vardanyan, Michael & Shen, Zhiyang, 2023. "Achieving carbon neutrality through green technological progress: evidence from China," Energy Policy, Elsevier, vol. 173(C).
    6. Li, Yaya & Zhang, Yuru & Pan, An & Han, Minchun & Veglianti, Eleonora, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Technology in Society, Elsevier, vol. 70(C).
    7. Du, Kerui & Cheng, Yuanyuan & Yao, Xin, 2021. "Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities," Energy Economics, Elsevier, vol. 98(C).
    8. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Impacts of GDP, Fossil Fuel Energy Consumption, Energy Consumption Intensity, and Economic Structure on SO 2 Emissions: A Multi-Variate Panel Data Model Analysis on Selected Chinese Provinces," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
    9. Yaling Lu & Yuan Wang & Yujie Liao & Jiantong Wang & Mei Shan & Hongqiang Jiang, 2023. "Public Concern about Haze and Ozone in the Era of Their Coordinated Control in China," IJERPH, MDPI, vol. 20(2), pages 1-13, January.
    10. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    11. Pingguo Xu & Leyi Chen & Huajuan Dai, 2022. "Pathways to Sustainable Development: Corporate Digital Transformation and Environmental Performance in China," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    12. Jing-Wen Huang & Yong-Hui Li, 2017. "Green Innovation and Performance: The View of Organizational Capability and Social Reciprocity," Journal of Business Ethics, Springer, vol. 145(2), pages 309-324, October.
    13. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    14. Kwok Tai Chui & Miltiadis D. Lytras & Anna Visvizi, 2018. "Energy Sustainability in Smart Cities: Artificial Intelligence, Smart Monitoring, and Optimization of Energy Consumption," Energies, MDPI, vol. 11(11), pages 1-20, October.
    15. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    16. J. Jason West & Steven J. Smith & Raquel A. Silva & Vaishali Naik & Yuqiang Zhang & Zachariah Adelman & Meridith M. Fry & Susan Anenberg & Larry W. Horowitz & Jean-Francois Lamarque, 2013. "Co-benefits of mitigating global greenhouse gas emissions for future air quality and human health," Nature Climate Change, Nature, vol. 3(10), pages 885-889, October.
    17. Ben Arfi, Wissal & Hikkerova, Lubica & Sahut, Jean-Michel, 2018. "External knowledge sources, green innovation and performance," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 210-220.
    18. Yuanfang Du & Shibing You, 2022. "Interaction among Air Pollution, National Health, and Economic Development," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    19. Adam Jaffe & Richard Newell & Robert Stavins, 2002. "Environmental Policy and Technological Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(1), pages 41-70, June.
    20. Brian Arthur, W. & Ermoliev, Yu. M. & Kaniovski, Yu. M., 1987. "Path-dependent processes and the emergence of macro-structure," European Journal of Operational Research, Elsevier, vol. 30(3), pages 294-303, June.
    21. Shrestha, Ram M. & Pradhan, Shreekar, 2010. "Co-benefits of CO2 emission reduction in a developing country," Energy Policy, Elsevier, vol. 38(5), pages 2586-2597, May.
    22. Zhou, Xiaoyan & Zhang, Jie & Li, Junpeng, 2013. "Industrial structural transformation and carbon dioxide emissions in China," Energy Policy, Elsevier, vol. 57(C), pages 43-51.
    23. Hao Lv & Beibei Shi & Nan Li & Rong Kang, 2022. "Intelligent Manufacturing and Carbon Emissions Reduction: Evidence from the Use of Industrial Robots in China," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
    24. Ping Chen & Jiawei Gao & Zheng Ji & Han Liang & Yu Peng, 2022. "Do Artificial Intelligence Applications Affect Carbon Emission Performance?—Evidence from Panel Data Analysis of Chinese Cities," Energies, MDPI, vol. 15(15), pages 1-16, August.
    25. van Vuuren, D.P. & Cofala, J. & Eerens, H.E. & Oostenrijk, R. & Heyes, C. & Klimont, Z. & den Elzen, M.G.J. & Amann, M., 2006. "Exploring the ancillary benefits of the Kyoto Protocol for air pollution in Europe," Energy Policy, Elsevier, vol. 34(4), pages 444-460, March.
    26. Yu-Ying Lin, Eugene & Chen, Ping-Yu & Chen, Chi-Chung, 2013. "Measuring green productivity of country: A generlized metafrontier Malmquist productivity index approach," Energy, Elsevier, vol. 55(C), pages 340-353.
    27. Xuan Chang & Jinye Li, 2022. "Effects of the Digital Economy on Carbon Emissions in China: A Spatial Durbin Econometric Analysis," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
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    Cited by:

    1. Mingyue Chen & Shuting Wang & Xiaowen Wang, 2024. "How Does Artificial Intelligence Impact Green Development? Evidence from China," Sustainability, MDPI, vol. 16(3), pages 1-23, February.
    2. Yang Shen & Xiuwu Zhang, 2024. "The impact of artificial intelligence on employment: the role of virtual agglomeration," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    3. Ping Han & Tingting He & Can Feng & Yihan Wang, 2024. "Research on Whether Artificial Intelligence Affects Industrial Carbon Emission Intensity Based on the Perspective of Industrial Structure and Government Intervention," Sustainability, MDPI, vol. 16(21), pages 1-19, October.
    4. Liu, Yajun & Zhang, Xiuwu & Shen, Yang, 2024. "Technology-driven carbon reduction: Analyzing the impact of digital technology on China's carbon emission and its mechanism," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    5. Yang Shen, 2024. "Future jobs: analyzing the impact of artificial intelligence on employment and its mechanisms," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-33, April.

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