Spatial-Temporal Characteristics and Influencing Factors on Carbon Emissions from Land Use in Suzhou, the World's Largest Industrial City in China

被引:1
|
作者
Han, Yue [1 ]
Ge, Xiaosan [1 ]
机构
[1] Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Peoples R China
基金
中国国家自然科学基金;
关键词
land use; carbon emissions; carbon emission risk; pressure index; LMDI model; DECOMPOSITION ANALYSIS; ENERGY-CONSUMPTION; DIOXIDE EMISSIONS; CO2; EMISSIONS; DRIVERS; LMDI; INTENSITY; PROVINCES; FOOTPRINT; LEVEL;
D O I
10.3390/su151813306
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Exploring carbon emissions in Suzhou, a city with a significant heavy industry presence, and understanding the factors that influence these emissions are crucial in achieving China's dual-carbon goals within the framework of global climate governance. This study utilized land use data and statistical data from 2008 to 2020 in Suzhou. The carbon emission coefficient method was employed to calculate carbon emissions, while GIS technology was used to analyze their temporal and spatial distribution, as well as carbon emission risk. Additionally, the LMDI model was applied to investigate the contribution of influencing factors and TAPIO was used to analyze the decoupling relationship between the main influencing factors and carbon emissions. The study yielded the following findings: (1) From 2008 to 2020, land use changes in all regions of Suzhou are obvious, and there are mutual transformations among different land types. (2) The overall carbon emission in Suzhou showed an upward trend, with a spatial distribution characterized by higher emissions in the northern regions and lower emissions in the southern regions. (3) The risk and pressure index of carbon emission in all regions of Suzhou are too large, and the amount of carbon emission and carbon absorption is seriously out of balance, resulting in an overall carbon imbalance. (4) Among the influencing factors on land use carbon emissions in Suzhou, energy intensity exerted the strongest negative effect, and economic growth showed the strongest positive effect. (5) Decoupling analysis showed that economic growth and carbon emissions are generally shifting towards a strong decoupling and, except for Zhangjiagang, other regions have a good development model. Based on the research findings, this paper proposes specific suggestions for reducing carbon emissions, aiming to provide actionable recommendations for Suzhou and other urban areas in achieving low-carbon and environmentally sustainable cities.
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页数:18
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