Decomposition Analysis and Trend Prediction of Energy-Consumption CO2 Emissions in China’s Yangtze River Delta Region

Abstract

This study calculated CO2 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 CO2 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 CO2 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 CO2 emissions. Population size is the second most important factor promoting the growth in CO2 emissions. Energy intensity is the most inhibitory factor to restrain CO2 emissions, with a significant negative effect. Energy structure and industrial structure contribute insignificantly to CO2 emissions. Using data on CO2 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 CO2 emissions. Specific policy suggestions to mitigate CO2 emissions in Yangtze River Delta region are provided.