县域尺度下长株潭地区城市化与碳排放的关系

Relationship Between Urbanization and Carbon Emissions in the Chang-Zhu-Tan Region at the County Level

基于碳代谢模型核算了1995~2020年长株潭县域碳排放,采用Tapio脱钩模型探讨了长株潭各县域碳排放与城市用地之间的脱钩关系,并用时空地理加权回归(GTWR)模型分析了城市空间形态对碳排放的影响机制.结果表明:①研究区县域碳排放总体上形成了以市辖区为中心的聚集分布,且呈逐年扩散趋势.2020年相比1995年新增7个高碳排放区,均为长沙市区县.②1995~2020年,研究区整体由以强脱钩为主转变为以扩张负脱钩为主,空间上脱钩状态在脱钩和负脱钩之间来回波动;除7个县域脱钩状态在倒退外,2020年其余均达到脱钩状态或向脱钩状态靠近.③城市斑块面积(CA)、城市斑块数量(NP)和斑块结合度(COHESION)与城市碳排放之间呈正相关效应,而景观形状指数(LSI)、最大斑块指数(LPI)和欧氏距离均值(ENN_MN)与城市碳排放则呈负相关效应,不同城市形态指标对碳排放的影响具有显著空间异质性.

Urbanization is a major source of carbon emissions.A quantitative study on the dynamic relationship between urbanization and its morphological characteristics and carbon emissions is crucial for formulating urban carbon emission reduction policies.Based on the carbon metabolism model,the carbon emissions at the country level in Chang-Zhu-Tan from 1995 to 2020 were calculated.The Tapio decoupling model was used to explore the decoupling relationship between the carbon emissions of Chang-Zhu-Tan and urban land,and a geographically and temporally weighted regression(GTWR)model was used to analyze the impact mechanism of urban spatial morphology on carbon emissions.The following conclusions were drawn:①carbon emissions at the county level in the study area formed a clustered distribution centered on the city jurisdiction and showed a trend of diffusion from year to year.Compared with those in 1995,there were seven new high carbon emission districts in 2020,all of which belonged to Changsha.②From 1995-2020,the research area as a whole changed from mainly strong decoupling to mainly dilated negative decoupling,and the spatial decoupling state fluctuated back and forth between the decoupling and negative decoupling.By 2020,except for the seven regions with the uncoupling state regressing,all of them reached the uncoupling state or were close to the uncoupling state.③Urban patch area(CA),urban patch number(NP),and patch combination degree(COHESION)were positively correlated with urban carbon emissions,whereas landscape shape index(LSI),maximum patch index(LPI),and Euclidean distance mean(ENN_MN)were negatively correlated with urban carbon emissions,and the impact of different urban form indicators on carbon emissions had significant spatial heterogeneity.