Calculation and Influencing Factors of Carbon Emissions in Countries along the Belt and Road Based on the LMDI Method

Authors

  • Jingyuan Cui
  • Yumeng Wu

DOI:

https://doi.org/10.54097/hset.v11i.1372

Keywords:

Carbon emissions; LMDI; The Belt and Road Initiative.

Abstract

In order to study the carbon emissions of countries along the Belt and Road and its influencing factors, this paper calculates the energy carbon emissions of six major regions from 2013 to 2020 from the national level based on the LMDI index decomposition method and divides the driving factors into population, economy, industrial structure, energy intensity and carbon emission intensity, analyzing the contribution rate of each factor and regional differences. The results show that the carbon emissions of countries along the Belt and Road have shown an overall upward trend at present. The main influencing factors are economy and industrial structure, as well as reducing energy consumption intensity has also contributed more to the suppression of carbon emissions. Population and carbon emission intensity vary slightly by region. Therefore, governments should guide reasonable population growth, formulate reasonable carbon emission reduction policies according to local conditions, optimize the energy structure and accelerate the establishment of carbon markets.

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References

[One Belt One Road Observation] Carbon Emission Pressures and Challenges in Countries Along the "One Belt One Road" Tencent News [EB/OL]. /2022-04-14. https://new.qq.com/omn/20210514/20210514A07RUG00.html.

Ang B W, Zhang F Q. Handling zero values in the logarithmic mean Divisa index decomposition approach [J]. Energy Policy, 2007: 238–246.

Wang Fengting, Fang Kai, Yu Chang. Decoupling Elasticity and Driving Factors of Industrial Energy Carbon Emissions and Economic Growth in Beijing-Tianjin-Hebei Region——Empirical Based on Tapio Decoupling and LMDI Model[J]. Industrial Technology Economy, 2019, 38(08): 32–40.

Wang Jie, Li Zhiguo, Gu Jijian. Decoupling Elasticity and Driving Factors of Carbon Emissions and Economic Growth in BRICS Countries: An Analysis Based on Tapio Decoupling and LMDI Model[J]. World Geographic Research, 2021, 30(03): 501–508.

Victor M, Mara M, Roula I-L, 等. Factors affecting CO2 emissions in Top countries on Renewable Energies: A LMDI decomposition application [D]. Campus de Santiago: University of Aveiro.

PF G, M L, M.J. P. Tracking European Union CO2emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach[J]. Energy, 2014, Volume 73: 741–750.

Yu Jinping, Zhang Yanyan. The Influence of "One Belt, One Road" National Railway Connectivity on China's Exports[J]. World Economic and Political Forum, 2021(1).

Zhang Hui, Yan Qiangming, Tang Yuxuan. Research on the Industrial Structure Height and Cooperation Path of “One Belt, One Road” related countries[J]. Learning and Exploration, 2019(282).

BP_Stats_2021.pdf [J].

IPCC — Intergovernmental Panel on Climate Change [J].

Homepage - U.S. Energy Information Administration (EIA) [EB/OL]. /2022-04-17. https://www.eia.gov/index.php.

World Bank Open Data | Data [EB/OL]. /2022-04-17. https://data.worldbank.org.cn/.

Ang B W, Pandiyan G. Decomposition of energy-induced CO2 emissions in manufacturing [J]. Energy Economics, 1997: 363–374.

Birdsall N. Another see population and global warning[J]. Population, health, and nutrition policy research,

Wang Yanan, Xie Yanqi, Xie Liqin, et al. Factor decomposition analysis of China's urban living carbon emissions based on LMDI model and Q-type clustering[J]. Environmental Science Research, 2019, 32(04): 539–546.

G.O-R,A.M-N,J.E.G-R. Is India on the right pathway to reduce CO2 emissions? Decomposing an enlarged Kaya identity using the LMDI method for the period 1990-2016[J]. Science of The Total Environment, 2020, 737(1).

Chin H C, Wei X T, Zhao J T. The driving factors of energy-related CO2 emission growth in Malaysia: The LMDI decomposition method based on energy allocation analysis[J]. Renewable and Sustainable Energy Reviews, 2019, 115.

Zhang Jifeng, Liu Qichao. Space-time evolution and influencing factors of China's direct investment in countries along the "One Belt One Road"[J]. Public Governance Research,, 2022, 34(1): 89–98.

Zhao Liping, Li Yuan. The impact of industrial structure on carbon emission intensity [J]. City Problems, 2018(6).

Song Xiaohui, Zhang Yufen, Wang Yimei, et al. Analysis of the impact of population factors on carbon emissions based on IPTA extended model[J]. Environmental Science Research, 2012, 25(1): 109–115.

Zhang Cuiju, Zhang Zongyi. The Impact of Industrial and Population Spatial Agglomeration on China's Regional Carbon Emission Intensity[J]. Technological Economy, 2016, 35(1): 71–77.

Lamini D. Factors affecting CO2 emissions and environmental efficiency: evidence from different regions in Africa[D]. Jiangsu University, 2020.

Ma Ying, Shao Changxiu. Analysis of Influencing Factors and Decoupling Effect of Energy Consumption Carbon Emissions in Beishang and Tianjin Based on LMDI[J]. Journal of Gansu Science, 2022, 34(01): 124–132.

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Published

23-08-2022

How to Cite

Cui, J., & Wu, Y. (2022). Calculation and Influencing Factors of Carbon Emissions in Countries along the Belt and Road Based on the LMDI Method. Highlights in Science, Engineering and Technology, 11, 167-176. https://doi.org/10.54097/hset.v11i.1372