长江流域资源与环境 >> 2025, Vol. 34 >> Issue (08): 1811-.doi: 10.11870/cjlyzyyhj202508014

• 生态环境 • 上一篇    下一篇

长三角地区碳排放时空特征与影响因素研究

张宁1,邓清晨1,茹泓凯2   

  1. (1. 杭州电子科技大学管理学院,浙江 杭州 310018;2. 杭州电子科技大学经济学院,浙江 杭州 310018)
  • 出版日期:2025-08-20 发布日期:2025-09-01

Spatial and Temporal Characteristics and Influencing Factors of Carbon Emissions in Yangtze River Delta Region

ZHANG Ning1, DENG Qing-chen1, RU Hong-kai2   

  1. (1. School of Management, Hangzhou Dianzi University, Hangzhou 310018, China;2. School of Economics, Hangzhou Dianzi University, Hangzhou 310018, China)
  • Online:2025-08-20 Published:2025-09-01

摘要: 长三角是我国经济社会发展水平最高且最具活跃性的地区,对其碳排放时空特征及影响因素的分析有助于为中国其他区域同类问题的思考提供重要参考。研究基于2006~2021年长三角地区41个城市的夜间灯光数据,利用空间自相关分析、标准差椭圆等方法分析长三角地区碳排放的时空特征,并利用地理时空加权回归模型(GTWR)实证考察长三角地区碳排放影响因素的时空异质性。结果显示:(1)2006~2021年长三角地区碳排放量呈上升态势,并具有显著的空间正自相关性。长三角东部江浙沪交界地带呈现高-高集聚,而低-低集聚地区主要位于长三角西部安徽省境内。(2)标准差椭圆结果显示,碳排放增长在长三角的西部地区表现的更为显著,且重心有向西转移的发展趋势。(3)环境规制、绿化水平、研发投入与低碳试点政策对碳排放呈负向抑制作用,而人口规模、经济水平、产业结构、对外开放度则呈正向促进作用,且各因素对长三角地区碳排放的影响存在时空差异。研究结果对长三角地区制定差异化的碳减排策略提供了有价值的参考作用。

Abstract: The Yangtze River Delta (YRD) is the region with the highest level of economic and social development and the most active region in China. Analyses of the spatial and temporal characteristics of the carbon emissions and the associated affecting factors can provide important references for other regions of China. This study employed spatial autocorrelation analysis and standard deviation ellipse, based on nighttime lighting data from 41 cities in the YRD region from 2006 to 2021, to analyse the spatial and temporal characteristics of carbon emissions. Furthermore, this study used the geographically and temporally weighted regression (GTWR) model to empirically examine the spatial and temporal heterogeneity of the factors influencing carbon emissions in the YRD region. The findings indicated that: (1) The data demonstrated a clear upward trajectory in carbon emissions in the YRD region from 2006 to 2021, with evidence of significant spatial positive autocorrelation. The junction zone of Jiangsu, Zhejiang and Shanghai in the eastern part of the YRD exhibited a high-high agglomeration, whereas the low-low agglomeration area was predominantly situated in the western part of the YRD within Anhui Province. (2) The standard deviation ellipse results indicated that the growth of carbon emissions was more pronounced in the western part of the YRD, with a tendency for the centre of gravity of shifting towards the west. (3) Environmental regulations, greening level, R&D investment and low-carbon pilot policies exerted a negative inhibitory effect on carbon emissions, whereas population size, economic level, industrial structure and openness to the outside world exerted a positive promotional effect. Furthermore, the impact of each factor on carbon emissions in the YRD region exhibited spatial and temporal differences. These results may provide valuable references for the development of differentiated carbon emission reduction strategies in the YRD region.

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