Assessing annual carbon emissions and its peak year in the Yangtze river economic belt (2021-2035) through land use/land cover analysis

被引:1
作者
Du, Lin [1 ]
Peng, Chuanjing [1 ]
Ren, Hangxing [1 ]
Wu, Zhiyuan [1 ]
Gao, Wei [1 ]
机构
[1] China Univ Geosci, Sch Geog & Informat Engn, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
Carbon emissions; STIRPAT model; PLUS model; Carbon peak; LAND use changes; Spatialization; DRIVING FORCES; CO2; EMISSIONS; CHINA; MODEL; SIMULATION; STIRPAT; IMPACT; URBANIZATION; DETERMINANTS; SCENARIOS;
D O I
10.1016/j.scs.2025.106453
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
As a major carbon emitting country, China is committed to peak carbon emissions before 2030. The Yangtze River Economic Belt (YREB), a key economic region in China, plays a significant role in national carbon emissions, making it crucial to study its emissions. This study uses the STIRPAT model and the Grey Model (GM) to analyze the carbon emissions of building land from 2021 to 2035; then the Patch-generating Land Use Simulation model (PLUS) is employed to predict the land-use changes over next 15 years, and future emissions from cropland, forest, grassland, water area, and unused land estimated using emission coefficients. Finally, carbon emissions across the YREB are calculated and mapped. The projections reveal that carbon emissions from building land increase and then decrease in the baseline scenario from 2021 to 2035. However, carbon emissions from cropland decline annually. Furthermore, this study identifies 2028 as carbon peak year in YREB area, totaling 8.278 x 108t. Additionally, diminishing total energy consumption and the proportion of some industries may be beneficial for regional carbon reduction. The results of this study are instructive for carbon emission reduction and peak carbon attainment in China.
引用
收藏
页数:12
相关论文
共 75 条
[2]   The Global Stocktake at COP28 [J].
不详 .
NATURE CLIMATE CHANGE, 2023, 13 (11) :1146-1147
[3]   Impact of energy consumption patterns on peak emissions in China's carbon neutralisation process [J].
Cai, Xinyu ;
Xiang, Hua ;
Zheng, Haotian .
ENERGY STRATEGY REVIEWS, 2024, 55
[4]   Regional policy options for carbon peaking in the Yangtze River Delta under uncertainty [J].
Cui, Lianbiao ;
Wang, Jiaxue ;
Chen, Xueli ;
Song, Malin .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2024, 364
[5]   Examining the uncertainty of carbon emission changes: A systematic approach based on peak simulation and resilience assessment [J].
Cui, Xuezhu ;
Zhao, Kuokuo ;
Zhou, Zhanhang ;
Huang, Peixuan .
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW, 2021, 91
[6]   A review on historical trajectories and spatially explicit scenarios of land-use and land-cover changes in China [J].
Deng, Xiangzheng ;
Li, Zhihui .
JOURNAL OF LAND USE SCIENCE, 2016, 11 (06) :709-724
[7]   Determinants of CO2 emissions in the European Union: The role of renewable and non-renewable energy [J].
Dogan, Eyup ;
Seker, Fahri .
RENEWABLE ENERGY, 2016, 94 :429-439
[8]   IMPACT OF POPULATION GROWTH [J].
EHRLICH, PR ;
HOLDREN, JP .
SCIENCE, 1971, 171 (3977) :1212-&
[9]   China's pathways to peak carbon emissions: New insights from various industrial sectors [J].
Fang, Kai ;
Li, Chenglin ;
Tang, Yiqi ;
He, Jianjian ;
Song, Junnian .
APPLIED ENERGY, 2022, 306
[10]   Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces [J].
Fang, Kai ;
Tang, Yiqi ;
Zhang, Qifeng ;
Song, Junnian ;
Wen, Qi ;
Sun, Huaping ;
Ji, Chenyang ;
Xu, Anqi .
APPLIED ENERGY, 2019, 255