Research on Spatiotemporal Analysis and Prediction of China's Carbon Emissions Based on LSTM Model
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Keywords

Carbon emission efficiency
Time series analysis
Super-SBM model
Cluster analysis

How to Cite

Liang, Y., & Yang, Y. (2025). Research on Spatiotemporal Analysis and Prediction of China’s Carbon Emissions Based on LSTM Model. International Theory and Practice in Humanities and Social Sciences, 2(9), 19–32. https://doi.org/10.70693/itphss.v2i9.1347

Abstract

Since becoming the world's largest emitting economy in 2014, China's carbon emission issue has become increasingly prominent. In 2020, China's carbon emission intensity decreased by 48.4% compared to 2005, representing a major breakthrough; however, the differences in carbon emissions among provinces and cities have become more apparent. Based on carbon emission data from 30 Chinese provinces and cities from 2000 to 2019, this study employs time series analysis, the Super-SBM model, and cluster analysis to examine carbon emission efficiency, carbon emission intensity, and their characteristics. The results indicate that imbalanced development and insufficient utilization between carbon emissions and energy consumption persist across provinces and cities. While carbon emission efficiency in most provinces and cities has shown a steady annual increase, it remains volatile in a few regions. Accordingly, the following policy recommendations are proposed: (1) Tailor energy-saving and emission reduction targets according to the actual conditions of each province and city; (2) Continuously promote the development of new energy industries and accelerate the research and development of energy-saving and emission reduction technologies. 

https://doi.org/10.70693/itphss.v2i9.1347
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Copyright (c) 2025 Yuhan Liang (Author); Ye Yang (Co-Authors)

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