Chengdu carbon emission analysis and emission reduction countermeasure research in the context of the Double Carbon

Authors

  • Haizhou Liang
  • Sitong Chen
  • Yang Yan
  • Shutian Li
  • Mengting Qin

DOI:

https://doi.org/10.54097/e3d2qx54

Keywords:

Carbon emissions, TOPSIS, Holt model, Gray Forecast Model.

Abstract

In the context of global warming, low -carbon has become the focus of long -term concern for governments and all walks of life from all over the country. China proposed in 2020 to achieve the two goals of "carbon neutrality" and "carbon peaks". In recent years, it has achieved remarkable results in carbon emission reduction low carbon work. This study comprehensively evaluated the important carbon emissions indicators of Chengdu through the use of the TOPSIS Entropy Method and used the Gray Forecast Model and the Holt model to predict the total carbon emissions of Chengdu from 2023 to 2027. The largest weight of urban activities in various types of carbon emissions indicators in Chengdu is 0.3165. The total carbon emissions in Chengdu have increased in index before the 20th century, and it did not fluctuate slowly until recent years. The government should pay attention to the development and utilization of new energy and the transformation of energy efficiency. This study provides a reference for the direction of energy conservation and emission reduction policies of the Chengdu Municipal Government, and provides reference and samples for other cities around the world in promoting green low -carbon transformation.

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References

[1] Jiang Yu, Tan Yaoyao, Li Dong, et al. Carbon Emission Reduction Analysis of Sanitation Vehicles Using Clean Energy under the Background of Carbon Peaking and Carbon Neutrality [J]. Construction Machinery Technology & Management,2024,37(03):46-48.DOI:10.13824/j.cnki. cmtm.2024.03.016.

[2] Wang Tao, Zhao Lei. Carbon Reduction Benefits and Evaluation of Park City Construction——Taking the Built-up Area of Chengdu Park City as an Example [J]. Journal of Green Science and Technology,2024,26(11):43-47.DOI:10.16663/j.cnki.lskj.2024.11.036.

[3] Xia Wei, Chen Xunbo. Research on carbon emission effect and efficiency of land use in Chengdu city [J]. Natural Resources Information,2024,(03):19-28.

[4] Cheng Jianwei, Yan Jiahui, Liang Haibin. The space -time pattern and influencing factor of carbon emissions in the prefecture -level city in Shanxi Province [J]. Shanxi Agricultural Economy,2024,(16):76-79+88.DOI:10.16675/j.cnki.cn14-1065/f.2024.16.022.

[5] Wang Shaojian, Huang Yongyuan. Spatial spillover effect and driving forces of carbon emission intensity at city level in China [J]. Acta Geographica Sinica,2019,74(06):1131-1148.

[6] Liu Chao, Zhang Hongbo, Huang Yuyan. Temporal and Spatial Dynamic Characteristics, Influencing Factors and Corresponding Planning Strategies of Carbon Emissions by Sectors in the Yangtze River Delta [J]. Shanghai Urban Planning Review,2024,(04):40-47.

[7] Yu Shuyu, Zhu Guangyan, Liu Keiliang, et al., Time -and -space differential analysis of transportation of transportation in the city [J]. Highways & Automotive Applications,2024,40(05):26-32+36.DOI:10.20035/j.issn.1671-2668.2024.05.004.

[8] Tang Jiangwei, Huang Yanfen. Research on the Impact of Carbon Emissions on High-quality Economic Development:Empirical Analysis based on the Data of 284 Prefecture-level and above Cities in China [J]. Journal of Technical Economics & Management,2024,(09):55-61.

[9] Zhang Zilong, Wang Dandan, Zhang Juan, et al., Analyze the factors of direct carbon emissions based on the LMDI model [J]. Anhui Architecture,2024,31(10):78-80.DOI:10.16330/j.cnki.1007-7359.2024.10.26.

[10] Hao Yaxing, Wang Jian. Research on Driving Factors of Carbon Emission in Chinese Automobile Manufacturing Industry [J]. Environmental Science Survey,2024,43(05):1-6+19.DOI:10.13623/j.cnki.hkdk.2024.05.001.

[11] Li Huiyun, Chen Gang, Yu Zongbao. Impact of New Quality Productivity on Carbon Emissions in Sporting Goods Manufacturing Industry: Based on Panel Data of 30 Provinces (Autonomous Regions and Municipalities) in China [J]. Journal of Shandong Sport University,2024,40(05):57-66.DOI:10.14104/j.cnki.1006-2076.2024.05.007.

[12] Huang Ruxia, Zhong Qiumeng, Wu Xiaohui, et al. Impacts of Economic Structural Transition on Synergetic Control of CO2 and Air Pollutants in Guangdong Province [J]. Research of Environmental Sciences,2022,35(10):2303-2311.DOI:10.13198/j.issn.1001-6929.2022.02.30.

[13] Zhang Zhengfeng, Zhang Dong. Spatial relatedness of CO2 emission and carbon balance zoning in Beijing Tianjin Hebei counties [J]. China Environmental Science,2023,43(04):2057-2068.DOI:10.19674/j.cnki.issn1000-6923. 20221011.002.

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Published

18-02-2025

How to Cite

Liang, H., Chen, S., Yan, Y., Li, S., & Qin, M. (2025). Chengdu carbon emission analysis and emission reduction countermeasure research in the context of the Double Carbon. Highlights in Science, Engineering and Technology, 125, 434-444. https://doi.org/10.54097/e3d2qx54