Application Status, Hotspots, and Future Trends of Artificial Intelligence in the Field of Sustainable Environmental Governance
DOI:
https://doi.org/10.63333/eem.v1n13Keywords:
Artificial Intelligence, Environmental Governance, Sustainable DevelopmentAbstract
Amidst the increasingly severe global environmental crisis, the application of artificial intelligence (AI) in the fields of environmental governance and sustainable development has become a hot topic in current scientific research and practice. The complexity and urgency of environmental issues have made the integration of AI technology particularly important and pressing. To comprehensively understand the research status, hotspots, and future trends in this field, this study employed Citespace and VOSviewer literature analysis tools to construct a knowledge map based on data from 2004 to 2024. The analysis results reveal that, in terms of research regions, Asia (especially China) has made the most significant contributions, while North America and Europe (particularly the United States and some EU countries) have closely collaborated, forming the core research regions. The top five authors in terms of publication volume are Liu J, Vinuesa R, Nishant R, Bag S, and Benzidia S. Regarding research hotspots, the current themes in this field focus on four clusters: intelligent management and green innovation for performance lifecycle assessment, smart cities and sustainable development, and AI-enabled environmental management. These highlight the vast potential of AI in enhancing environmental governance efficiency and promoting sustainable development. As for future trends, the number of publications in this field has shown a continuous upward trend in recent years, with predictions indicating that future research will continue to concentrate on keywords such as AI, life cycle, assessment, and the Internet of Things. In summary, AI is forming an active and expanding field within environmental governance, and future research will deepen understanding of the topic, explore the integration of AI with environmental science, address global challenges, and drive environmental governance towards a smart, efficient, and sustainable direction.
References
[1]Liu, J., Liu, L., Qian, Y., & Song, S. (2022). The effect of artificial intelligence on carbon intensity: Evidence from China’s industrial sector. Socio-Economic Planning Sciences, 83(101002), 101002. https://doi.org/10. 1016/j.seps.2020.101002
[2] Ding, C., Ke, J., Levine, M., & Zhou, N. (2024). Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale. Nature Communications, 15(1), 5916. https://doi.org/10. 1038/s41467-024-50088-4
[3]Bibri, S. E., Huang, J., & Krogstie, J. (2024). Artificial intelligence of things for synergizing smarter eco-city brain, metabolism, and platform: Pioneering data-driven environmental governance. Sustainable Cities and Society, 108(105516), 105516. https://doi.org/10.1016/j.scs.2024.105516
[4]Guo, Y.-M., Huang, Z.-L., Guo, J., Li, H., Guo, X.-R., & Nkeli, M. J. (2019). Bibliometric analysis on smart cities research. Sustainability, 11(13), 3606. https://doi.org/10.3390/su11133606
[5] Chen, Y., Lin, M., & Zhuang, D. (2022). Wastewater treatment and emerging contaminants: Bibliometric analysis. Chemosphere, 297(133932), 133932. https://doi.org/10.1016/j.chemosphere.2022.133932
[6]Ma, D., Yang, B., Guan, B., Song, L., Liu, Q., Fan, Y., Zhao, L., Wang, T., Zhang, Z., Gao, Z., Li, S., & Xu, H. (2021). A bibliometric analysis of pyroptosis from 2001 to 2021. Frontiers in Immunology, 12, 731933. https://doi.org/10.3389/fimmu.2021.731933
[7]Tang, R., Lin, L., Liu, Y., & Li, H. (2024). Bibliometric and visual analysis of global publications on kaempferol. Frontiers in Nutrition, 11, 1442574. https://doi.org/10.3389/fnut.2024.1442574
[8]Yang, L., Li, Z., Lei, Y., Liu, J., Zhang, R., Lei, W., & Anita, A. R. (2024). Research hotspots and trends in healthcare workers ’ resilience: A bibliometric and visualized analysis. Heliyon, 10(15), e35107. https://doi.org/10. 1016/j.heliyon.2024.e35107
[9]Wong, C., Papageorgiou, S. N., Seehra, J., & Cobourne, M. T. (2022). Prolific authorship in orthodontic scientific publishing. Orthodontics & Craniofacial Research, 25(3), 416–428. https://doi.org/10.1111/ocr.12551
[10]Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 233. https://doi.org/10.1038/s41467-019-14108-y
[11]Huang, T., Zhong, W., Lu, C., Zhang, C., Deng, Z., Zhou, R., Zhao, Z., & Luo, X. (2022). Visualized analysis of global studies on cervical spondylosis surgery: A bibliometric study based on Web of Science database and VOSviewer. Indian Journal of Orthopaedics, 56(6), 996–1010. https://doi.org/10. 1007/s43465-021-00581-5
[12] Ligozat, A.-L., Lefevre, J., Bugeau, A., & Combaz, J. (2022). Unraveling the hidden environmental impacts of AI solutions for environment life cycle assessment of AI solutions. Sustainability, 14(9), 5172. https://doi.org/10.3390/su14095172
[13]Xu, X., & Song, Y. (2023). Is there a conflict between automation and environment? Implications of artificial intelligence for carbon emissions in China. Sustainability, 15(16),12437. https://doi.org/10.3390/su151612437
[14]Lin, J., Zeng, Y., Wu, S., & Luo, X. (robert). (2024). How does artificial intelligence affect the environmental performance of organizations? The role of green innovation and green culture. Information & Management, 61(2), 103924. https://doi.org/10.1016/j.im.2024.103924
[15]Wu, X. (2021). Analysis of environmental governance expense prediction reform with the background of Artificial Intelligence. Journal of organizational and end user computing: an official publication of the Information Resources Management Association, 34(5), 1–19. https://doi.org/10.4018/joeuc.287874
[16]Wang, H., Qin, F., & Zhang, X. (2019). A spatial exploring model for urban land ecological security based on a modified artificial bee colony algorithm. Ecological Informatics, 50, 51–61. https://doi.org/10. 1016/j.ecoinf.2018.12.009
[17]Saxena, A., Singh, R., Gehlot, A., Akram, S. V., Twala, B., Singh, A., Montero, E. C., &
Priyadarshi, N. (2022). Technologies empowered environmental, social, and governance (ESG): An Industry 4.0 landscape. Sustainability, 15(1),309.https://doi.org/10.3390/su15010309.
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