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Ways to Improve China's Ecological Governance Effectiveness through Artificial Intelligence

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DOI: 10.23977/erej.2024.080120 | Downloads: 12 | Views: 232

Author(s)

Hongwei Zhan 1, Wei Liao 1

Affiliation(s)

1 School of Marxism, Chongqing Technology and Business University, Chongqing, China

Corresponding Author

Wei Liao

ABSTRACT

Although China has made remarkable achievements in ecological governance, it is imperative to acknowledge the persisting challenges. Firstly, the ecological monitoring and early warning system exhibit noteworthy imperfections, and access to information is delayed. Secondly, data integration and analysis are slow, and management decision-making lacks timeliness and accuracy. Thirdly, the ecological governance model implemented by the government's central authority is not energetic, and cross-sectoral cooperation is insufficient. China's efforts to improve the effectiveness of ecological governance are hindered by these obstacles. As one of the most important technological developments in the digital age, research indicates that artificial intelligence can expand the coverage of ecological monitoring, increase the speed of information acquisition and processing in ecological governance, improve the timeliness and scientificity of ecological decision-making, and strengthen multi-party cooperation to promote innovation in ecological governance models. Applying artificial intelligence to China's ecological governance will definitely improve its effectiveness and promote sustainable development goals.

KEYWORDS

China's Ecological Governance; Artificial Intelligence; Environmental Development; Sustainable Development

CITE THIS PAPER

Hongwei Zhan, Wei Liao, Ways to Improve China's Ecological Governance Effectiveness through Artificial Intelligence. Environment, Resource and Ecology Journal (2024) Vol. 8: 160-169. DOI: http://dx.doi.org/10.23977/erej.2024.080120.

REFERENCES

[1] Wang W, Sun Y, Wu J. Environmental warning system based on the DPSIR model: A practical and concise method for environmental assessment [J]. Sustainability, 2018, 10(6): 1728.
[2] Sun, Y. P. The theoretical contribution of Xi's ecological civilization thought to environmental economics [J]. Journal of Nanjing University, 2019, 3: 1-9.
[3] Xi, J. P. Notes on the Resolution of the Central Committee of the Communist Party of China on the Major Achievements and Historical Experience of the Party's Centennial Struggle[J]. People's Weekly, 2021: 4-8
[4] McCarthy, J. Artificial Intelligence, Logic, and Formalizing Common Sense. Machine Learning and the City: Applications in Architecture and Urban Design, 2022: 69-90. https://doi.org/10.1002/9781119815075.ch6
[5] Morelli J. Environmental sustainability: A definition for environmental professionals[J]. Journal of environmental sustainability, 2011, 1(1): 2. http://doi.org/10.14448/jes.01.0002
[6] Shi, Y. G., Meng, Q. County ecological governance capacity: concept, elements and system construction[J]. Journal of Sichuan University (Philosophy and Social Science Edition), 2018, 5-13.
[7] Mol A P J, Carter N T. China's environmental governance in transition[M]//Environmental governance in China. Routledge, 2013: 1-22.
[8] Hays G C, Bailey H, Bograd S J, et al. Translating marine animal tracking data into conservation policy and management [J]. Trends in ecology & evolution, 2019, 34(5): 459-473. 
[9] Maskin E, Qian Y, Xu C. Incentives, information, and organizational form[J]. The review of economic studies, 2000, 67(2): 359-378.
[10] He G, Lu Y, Mol A P J, et al. Changes and challenges: China's environmental management in transition[J]. Environmental Development, 2012, 3: 25-38. 
[11] Fan, X. S. Progress of Research on International Early Warning System and Its Implications for Domestic Early Warning Research on Ecological Environment[J]. Acta Ecologica Sinica, 2021, 41: 7454-7463.
[12] Hino M, Benami E, Brooks N. Machine learning for environmental monitoring[J]. Nature Sustainability, 2018, 1(10): 583-588.
[13] Xu K. Artificial intelligence unlocks ecological environment governance—smart statistical monitoring based on meteorology [J]. Multimedia Tools and Applications, 2023: 1-13.
[14] Duan Y, Edwards J S, Dwivedi Y K. Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda[J]. International journal of information management, 2019, 48: 63-71.  https://doi.org/10.1016/j.ijinfomgt.2019.01.021
[15] Alam J R, Sajid A, Talib R, et al. A review on the role of big data in business[J]. International Journal of Computer Science and Mobile Computing, 2014, 3(4): 446-453.
[16] Lindenmayer D B, Likens G E. The science and application of ecological monitoring[J]. Biological conservation, 2010, 143(6): 1317-1328. https://doi.org/10.1016/j.biocon.2010.02.013
[17] Cullen‐Knox C, Eccleston R, Haward M, et al. Contemporary Challenges in Environmental Governance: Technology, governance and the social licence [J]. Environmental policy and governance, 2017, 27(1): 3-13. https://doi.org/10.1002/eet.1743
[18] Cortès U, Sànchez-Marrè M, Ceccaroni L, et al. Artificial intelligence and environmental decision support systems[J]. Applied intelligence, 2000, 13: 77-91. https://doi.org/10.1023/A:1008331413864
[19] Siddig A A H. Why is biodiversity data-deficiency an ongoing conservation dilemma in Africa?[J]. Journal for Nature Conservation, 2019, 50: 125719. https://doi.org/10.1016/j.jnc.2019.125719
[20] Overpeck J T, Meehl G A, Bony S, et al. Climate data challenges in the 21st century[J]. Science, 2011, 331(6018): 700-702. http://doi.org/10.1126/science.1197869
[21] Denning D E. Is Quantum Computing a Cybersecurity Threat? Although quantum computers currently don't have enough processing power to break encryption keys, future versions might[J]. American Scientist, 2019, 107(2): 83-86.

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