TY - JOUR
T1 - An empirical study on the evolution and driving factors of energy-related carbon emissions in the Yangtze River Economic Belt
AU - Zhu, Yi
AU - Liu, Xieqihua
AU - Feng, Chao
AU - Zhang, Tao
AU - Wang, Xi
N1 - Publisher Copyright:
Copyright © 2025 Zhu, Liu, Feng, Zhang and Wang.
PY - 2025
Y1 - 2025
N2 - This study analyzes energy-related carbon emissions in the Yangtze River Economic Belt (YREB) from 2000 to 2022 using regional energy consumption data and IPCC guidelines. The Mann-Kendall trend test and mutation point detection methods are applied to examine emission trends and structural shifts. The Kaya identity and Logarithmic Mean Divisia Index (LMDI) approach are used to decompose the impacts of energy structure, economic activity, population, and energy intensity on carbon emissions across subregions. The results show that since 2000, the growth rate of carbon emissions across the YREB has slowed significantly, with annual growth remaining below 2.5% since 2012. The energy mix has improved, with coal’s share decreasing from 77% to 69%, while natural gas and electricity’s combined share grew from 1% to 4%. Regionally, emissions in the Midstream reaches have peaked and are declining, while the Upstream reaches are nearing their peak. Although the Downstream reaches have not yet peaked, their emission growth has markedly decelerated. Overall, energy intensity and structural optimization have suppressed emissions, while economic growth and population expansion remain the dominant drivers. These findings highlight the need for continued optimization of both energy and industrial structures, with differentiated carbon reduction strategies tailored to each subregion’s unique characteristics and development stages within the YREB.
AB - This study analyzes energy-related carbon emissions in the Yangtze River Economic Belt (YREB) from 2000 to 2022 using regional energy consumption data and IPCC guidelines. The Mann-Kendall trend test and mutation point detection methods are applied to examine emission trends and structural shifts. The Kaya identity and Logarithmic Mean Divisia Index (LMDI) approach are used to decompose the impacts of energy structure, economic activity, population, and energy intensity on carbon emissions across subregions. The results show that since 2000, the growth rate of carbon emissions across the YREB has slowed significantly, with annual growth remaining below 2.5% since 2012. The energy mix has improved, with coal’s share decreasing from 77% to 69%, while natural gas and electricity’s combined share grew from 1% to 4%. Regionally, emissions in the Midstream reaches have peaked and are declining, while the Upstream reaches are nearing their peak. Although the Downstream reaches have not yet peaked, their emission growth has markedly decelerated. Overall, energy intensity and structural optimization have suppressed emissions, while economic growth and population expansion remain the dominant drivers. These findings highlight the need for continued optimization of both energy and industrial structures, with differentiated carbon reduction strategies tailored to each subregion’s unique characteristics and development stages within the YREB.
KW - Yangtze River Economic Belt
KW - carbon emissions
KW - energy consumption
KW - energy structure
KW - influencing factors
UR - https://www.scopus.com/pages/publications/105012730879
U2 - 10.3389/fenvs.2025.1596713
DO - 10.3389/fenvs.2025.1596713
M3 - Article
AN - SCOPUS:105012730879
SN - 2296-665X
VL - 13
JO - Frontiers in Environmental Science
JF - Frontiers in Environmental Science
M1 - 1596713
ER -