Spatiotemporal Variation and Development Stage of CO2 Emissions of Urban Agglomerations in the Yangtze River Economic Belt, China

被引:5
|
作者
Lu, Qikai [1 ,2 ,3 ]
Lv, Tiance [1 ,4 ]
Wang, Sirui [4 ,5 ]
Wei, Lifei [1 ,3 ]
机构
[1] Hubei Univ, Fac Resources & Environm Sci, Wuhan 430062, Peoples R China
[2] Wuhan Univ, Key Lab Digital Mapping & Land Informat Applicat, Minist Nat Resources, Wuhan 430079, Peoples R China
[3] Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China
[4] Hubei Univ, Chucai Honors Coll, Wuhan 430062, Peoples R China
[5] Hubei Univ, Sch Publ Adm, Wuhan 430062, Peoples R China
关键词
carbon emission; Yangtze River Economic Belt; urban agglomeration; influencing factor; multiscale geographically weighted regression; GEOGRAPHICALLY WEIGHTED REGRESSION; DECOMPOSITION ANALYSIS; ENERGY-CONSUMPTION; IMPACT; POLICIES; GROWTH; REGION; POWER;
D O I
10.3390/land12091678
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As the world's largest developing country, China has played an important role in the achievement of the global CO2 emissions mitigation goal. The monitoring and analysis of CO2 emissions in the Yangtze River Economic Belt (YREB) urban agglomerations is strategic to the carbon peak and carbon neutrality in China. In this paper, we revealed the spatial and temporal variations of CO2 emissions in Cheng-Yu urban agglomeration (CY-UA), Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and Yangtze River Delta urban agglomeration (YRD-UA) in YREB and investigated the carbon emission development stage of YREB urban agglomerations. Particularly, a carbon emission development stage framework that considered the relationship between economic growth and carbon emissions was built based on Environmental Kuznets Curves (EKCs). Meanwhile, multiscale geographically weighted regression (MGWR) was used to analyze the impact of different influencing factors, including population (POP), GDP per capita (GDPPC), the proportion of secondary industry (SI), carbon emission intensity (CI), and urbanization (UR), on the CO2 emissions of three urban agglomerations. The results illustrate the following: (1) The CO2 emissions of YREB urban agglomerations decreased, with YRD-UA having the highest CO2 emissions among the three urban agglomerations and contributing 41.87% of YREB CO2 emissions in 2017. (2) CY-UA, YRMR-UA, and YRD-UA reached the CO2 emissions peak in 2012, 2011, and 2020, respectively, all of which are at the low-carbon stage. (3) POP and GDPPC show the greatest impact on the CO2 emissions of the three YREB urban agglomerations.
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页数:20
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