TY - GEN
T1 - A Spatio-Temporal Evolution Model of Carbon Productivity in Large Regions for Dual Carbon Target
AU - Sun, Yige
AU - Tang, Xiaonan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Reaching the double carbon target can be accomplished through carbon productivity. In the setting of carbon neutrality, this paper establishes an analytical model for the spatio-temporal evolution of carbon productivity in large regions, and takes the Yellow River Basin as a case study to analyze the spatio-temporal evolution of carbon productivity in nine provinces and regions during 2012–2022 from multiple perspectives, and puts forward suggestions that can be generalized to promote carbon neutrality. The findings indicates that: (1) The model established can well analyze the change of the proportion of energy consumption in large regions. It is concluded that although fossil energy consumption accounts for a large proportion in China at present, the proportion is gradually decreasing, while the proportion of clean energy consumption such as wind energy and solar energy is constantly increasing. Therefore, China should strengthen the adjustment of energy structure and encourage the vigorous development of clean energy. (2) The established model can completely and accurately analyze the spatio-temporal variation characteristics of carbon productivity in large regions. It is concluded that although China's carbon productivity has been steadily increasing over time in recent years, there remains a significant disparity among various regions, and the lower reaches of rivers are generally higher than the middle and upper reaches of rivers. China should strengthen monitoring of areas where carbon productivity is lagging behind.
AB - Reaching the double carbon target can be accomplished through carbon productivity. In the setting of carbon neutrality, this paper establishes an analytical model for the spatio-temporal evolution of carbon productivity in large regions, and takes the Yellow River Basin as a case study to analyze the spatio-temporal evolution of carbon productivity in nine provinces and regions during 2012–2022 from multiple perspectives, and puts forward suggestions that can be generalized to promote carbon neutrality. The findings indicates that: (1) The model established can well analyze the change of the proportion of energy consumption in large regions. It is concluded that although fossil energy consumption accounts for a large proportion in China at present, the proportion is gradually decreasing, while the proportion of clean energy consumption such as wind energy and solar energy is constantly increasing. Therefore, China should strengthen the adjustment of energy structure and encourage the vigorous development of clean energy. (2) The established model can completely and accurately analyze the spatio-temporal variation characteristics of carbon productivity in large regions. It is concluded that although China's carbon productivity has been steadily increasing over time in recent years, there remains a significant disparity among various regions, and the lower reaches of rivers are generally higher than the middle and upper reaches of rivers. China should strengthen monitoring of areas where carbon productivity is lagging behind.
KW - Carbon neutral
KW - Carbon productivity
KW - Energy structure
UR - http://www.scopus.com/inward/record.url?scp=105000454778&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-1965-8_75
DO - 10.1007/978-981-96-1965-8_75
M3 - Conference Proceeding
AN - SCOPUS:105000454778
SN - 9789819619641
T3 - Lecture Notes in Electrical Engineering
SP - 782
EP - 788
BT - Proceedings of 2024 International Conference on Smart Electrical Grid and Renewable Energy, SEGRE 2024 - Volume 2
A2 - Wen, Fushuan
A2 - Liu, Haoming
A2 - Wen, Huiqing
A2 - Wang, Shunli
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Smart Electrical Grid and Renewable Energy, SEGRE 2024
Y2 - 9 August 2024 through 12 August 2024
ER -