长江流域资源与环境 >> 2024, Vol. 33 >> Issue (5): 937-948.doi: 10.11870/cjlyzyyhj202405003

• 区域可持续发展 • 上一篇    下一篇

县域土地城镇化与碳排放的互动演化及驱动机理研究 ——以江西省为例

牛曙晨,罗翔,秦井井,程超*   

  1. (华中师范大学公共管理学院,湖北 武汉 430079)
  • 出版日期:2024-05-20 发布日期:2024-05-29

 Interactive Evolution and Driving Mechanism of County Land Urbanization and Carbon Emissions: Taking Jiangxi Province as An Example

NIU Shu-chen,LUO Xiang,QIN Jing-jing,CHENG Chao   

  1. (Collage of Public Administration,Central China Normal University,Wuhan 430079,China)
  • Online:2024-05-20 Published:2024-05-29

摘要:  县域是生态文明建设的基本单元,探究县域土地城镇化与碳排放的互动演化机理,对于促进绿色高质量发展,实现“双碳”目标具有重要意义。基于DMSP-OLS和NPP-VIIRS夜间灯光数据、栅格数据和能源消费数据,分析了2011~2020年江西省县域土地城镇化与碳排放的互动演化特征,并借助空间面板Tobit模型分析其驱动机理。研究结果表明:(1)2011~2020年江西省土地城镇化率、碳排放量以及两者耦合协调度均呈持续上升态势,但仍以低耦合协调类型为主。(2)江西省县域土地城镇化和碳排放耦合协调度存在空间自相关,局域空间以H-H和L-L类型为主,且时空格局较为稳定,其中H-H类型集中分布在南昌市、九江市和景德镇市下辖区县,而L-L类型主要集中于南部山地丘陵区县。(3)两者互动演化的驱动因素中,人口集聚水平、经济发展水平、政府治理能力和工业发展水平对二者耦合协调发展具有显著促进作用,而生态绿化水平则存在抑制作用。

Abstract: County is the basic unit of ecological civilization construction. Exploring the interactive evolution county land urbanization and carbon emissions is of great significance for promoting green and high-quality development and achieving the goal of "double carbon.". Based on DMSP-OLS and NPP-VIIRS nighttime light data, raster data and energy consumption data, this paper analyzed the interactive evolution characteristics of land urbanization and carbon emissions in Jiangxi Province from 2011 to 2020. The driving mechanism was explored with the help of spatial panel Tobit model. The results showed that: The land urbanization rate, carbon emissions and the coupling coordination degree of the two showed a continuous upward trend, but the degree was still low. The LISA agglomeration map was dominated by H-H and L-L types, and the spatial and temporal pattern was relatively stable. The H-H type was concentrated in the districts and counties under the jurisdiction of Nanchang City, Jiujiang City and Jingdezhen City, while the L-L type was mainly located in the southern mountainous and hilly areas. Among the driving factors, the level of population agglomeration, the level of economic development, the ability of government governance and the level of industrial development played a significant role in promoting the coordinated development, while the level of ecological greening demonstrated an inhibitory effect.

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