Decomposition Analysis and Trend Prediction of Energy-Consumption CO 2 Emissions in China’s Yangtze River Delta Region

Yue Yuan and Sunhee Suk ()
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Yue Yuan: Graduate School of Fisheries and Environmental Sciences, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521, Japan
Sunhee Suk: Graduate School of Fisheries and Environmental Sciences, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521, Japan

Energies, 2023, vol. 16, issue 11, 1-18

Abstract: This study calculated CO 2 emissions related to the consumption of primary energy by five sectors in the Yangtze River Delta region over 2000 to 2019. The Logarithmic Mean Divisia Index (LMDI) decomposition method was used to establish the factor decomposition model of CO 2 emissions change. The LMDI model was modified to assess the impact of five influencing factors, namely energy structure, energy intensity, industrial structure, economic output, and population size, on CO 2 emissions in the Yangtze River Delta region over the study period. The empirical results show that economic output has the largest positive effect on the growth in CO 2 emissions. Population size is the second most important factor promoting the growth in CO 2 emissions. Energy intensity is the most inhibitory factor to restrain CO 2 emissions, with a significant negative effect. Energy structure and industrial structure contribute insignificantly to CO 2 emissions. Using data on CO 2 emissions in the Yangtze River Delta region from 2000 to 2019, the GM (1, 1) model was applied for future forecasts of primary energy consumption and CO 2 emissions. Specific policy suggestions to mitigate CO 2 emissions in Yangtze River Delta region are provided.

Keywords: Yangtze River Delta region; CO 2 emissions; LMDI method; grey prediction GM (1, 1) model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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