Spatial–temporal pattern evolution and influencing factors of coupled coordination between carbon emission and economic development along the Pearl River Basin in China

被引:0
作者
Bin Zhang
Jian Yin
Hongtao Jiang
Yuanhong Qiu
机构
[1] Guizhou University of Finance and Economics,Center for China Western Modernization
[2] Guizhou University of Finance and Economics,College of Big Data Application and Economics
[3] Guizhou Key Laboratory of Big Data Statistical Analysis,undefined
来源
Environmental Science and Pollution Research | 2023年 / 30卷
关键词
Carbon emission; Economic development; Coupling coordination; Influencing factors; The Pearl River Basin;
D O I
暂无
中图分类号
学科分类号
摘要
The Pearl River Basin (PRB) is a significant area for economic development (ED) and ecological protection in China. Studying the relationship between carbon emission (CE) and ED is crucial for China and the world to cope with climate change and achieve CO2 reduction. For 48 cities in the PRB, we used the coupling coordination model and geographically weighted regression model to analyze the coupling coordination degree (CCD) between CE and ED and investigate the main influencing factors. The results suggested that (1) the CCD presents spatial heterogeneity, with the Pearl River Delta having the highest value and the middle reaches having the lowest value; (2) the coupling coordination type between CE and ED changes from incoordination to coordination in general; and (3) the resident income and population size have a positive influence on the CCD of the cities in the lower reaches, while the secondary industry scale has a beneficial impact on the upstream. Finally, we put forward corresponding policy suggestions to achieve sustainable development in terms of reducing economic inequities, enhancing public expenditure and innovation capability, and streamlining the industrial structure.
引用
收藏
页码:6875 / 6890
页数:15
相关论文
共 238 条
[1]  
Alam MM(2016)Relationships among carbon emissions, economic growth, energy consumption and population growth: Testing Environmental Kuznets Curve hypothesis for Brazil, China, India and Indonesia Ecol Ind 70 466-479
[2]  
Murad MW(2021)Using quantile regression to analyze the relationship between socioeconomic indicators and carbon dioxide emissions in G20 countries Sustainability 13 7011-145
[3]  
Noman A(2022)Global perspectives on environmental Kuznets curve: a bibliometric review Gondwana Res 103 135-524
[4]  
Ozturk I(2021)Spatial analysis of urban smart growth and its effects on housing price: the case of Isfahan Iran Sustain Cities Soc 68 497-32
[5]  
Alotaibi AA(1999)Some notes on parametric significance tests for geographically weighted regression J Reg Sci 39 23-1280
[6]  
Alajlan N(2019)Promoting sustainability of manufacturing industry through the lean energy-saving and emission-reduction strategy Sci Total Environ 665 1269-569
[7]  
Anwar MA(2021)Driving factors for coordinating urbanization with conservation of the ecological environment in China Ambio 50 557-455
[8]  
Zhang QY(2021)China’s climate ambition: Revisiting its First Nationally Determined Contribution and centering a just transition to clean energy Energy Policy 155 431-420
[9]  
Asmi F(2019)A spatial-temporal decomposition analysis of China’s carbon intensity from the economic perspective J Clean Prod 215 414-192
[10]  
Hussain N(2021)Spatiotemporal patterns of industrial carbon emissions at the city level Resour Conserv Recycl 169 2712-63