TY - GEN
T1 - LMDI-ARIMA Model for Carbon Emissions Analysis and Prediction in High Energy Consuming Industries with Emission Reduction Measures
AU - Zhou, Mingyue
AU - Chu, Wen
AU - Xu, Xu
AU - Xu, Xiangmin
AU - Zheng, Bowen
AU - Yao, Weitao
AU - Liu, Chang
AU - Wang, Xuchen
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In this paper, starting from the specific perspective of enterprises, the carbon emission calculation model is first used to calculate and organize the carbon emission data of three typical high energy consuming industries. Secondly, the Logarithmic Mean Divisia Index (LMDI) decomposition analysis method is used to calculate the contribution of fossil fuels in the carbon emissions of enterprise fuel combustion. After comparison, it is found that steel enterprises are most affected by this factor. At the same time, time series analysis is used to predict the future carbon emissions of different enterprises by Autoregressive Integrated Moving Average (ARIMA) model. Finally, with the help of the established LMDI-ARIMA model, hypothetical adjustments were made to the proportion of fossil fuels in steel enterprises and carbon emissions predictions were made, obtaining the expected carbon reduction that the steel industry can achieve by changing the proportion of clean energy use.
AB - In this paper, starting from the specific perspective of enterprises, the carbon emission calculation model is first used to calculate and organize the carbon emission data of three typical high energy consuming industries. Secondly, the Logarithmic Mean Divisia Index (LMDI) decomposition analysis method is used to calculate the contribution of fossil fuels in the carbon emissions of enterprise fuel combustion. After comparison, it is found that steel enterprises are most affected by this factor. At the same time, time series analysis is used to predict the future carbon emissions of different enterprises by Autoregressive Integrated Moving Average (ARIMA) model. Finally, with the help of the established LMDI-ARIMA model, hypothetical adjustments were made to the proportion of fossil fuels in steel enterprises and carbon emissions predictions were made, obtaining the expected carbon reduction that the steel industry can achieve by changing the proportion of clean energy use.
KW - carbon emission calculation
KW - carbon emission prediction
KW - clean energy
KW - energy conservation and emission reduction
KW - High energy consuming industries
UR - http://www.scopus.com/inward/record.url?scp=105007606590&partnerID=8YFLogxK
U2 - 10.1109/EI264398.2024.10990805
DO - 10.1109/EI264398.2024.10990805
M3 - Conference Proceeding
AN - SCOPUS:105007606590
T3 - 2024 IEEE 8th Conference on Energy Internet and Energy System Integration, EI2 2024
SP - 4047
EP - 4053
BT - 2024 IEEE 8th Conference on Energy Internet and Energy System Integration, EI2 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE Conference on Energy Internet and Energy System Integration, EI2 2024
Y2 - 29 November 2024 through 2 December 2024
ER -
