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江苏省城市交通碳排放的时空演变特征与驱动因素分析

Spatial and temporal evolution characteristics and driving factors of urban traffic carbon emissions in Jiangsu Province

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【作者】 黄蕾刘俊豪刘榆欣鞠小玉王鹏

【Author】 HUANG Lei;LIU Jun-hao;LIU Yu-xin;JU Xiao-yu;WANG Peng;State Key Laboratory of Pollution Control and Recycling Research,School of Environment,Nanjing University;Nanjing University (Suzhou) Research Institute of Advanced Technology;School of Economics and Management,China University of Petroleum(Beijing);School of Civil Engineering and Mechanics,Jiangsu University;

【通讯作者】 王鹏;

【机构】 南京大学环境学院污染控制与资源化研究国家重点实验室南京大学(苏州)高新技术研究院中国石油大学(北京)经济管理学院江苏大学土木工程与力学学院

【摘要】 基于江苏省各城市2001—2021年的面板数据,结合IPCC碳排放测算方案运用“自下而上”方法完整测度了江苏省城市交通运输部门碳排放量,运用两级LMDI加法分解模型分析了8个因素对碳排放的影响机制和影响异质性。结果表明:关于时序变化趋势,江苏省交通碳排放经历了3个阶段,2001—2005年为高速增长阶段,2006—2013年为中速增长阶段,2014年至今为低速增长阶段,增长率持续稳定在10%以下;关于空间变化趋势,江苏省交通碳排放量呈现“南高北低”的分布特点,苏州碳排放量约占江苏全省的1/3;关于驱动因素,江苏省交通碳排放的促增因素为能源效率、经济水平、公共交通饱和度、绿色植被覆盖率、人口规模,促降因素主要为产业结构、公共交通参与度、土地利用结构,其中经济水平是首要的促增因素,公共交通参与度是主要的促降因素。

【Abstract】 Based on the panel data of cities in Jiangsu Province from 2001 to 2021,combined with the IPCC carbon emission calculation scheme, the carbon emissions of urban transportation departments in Jiangsu Province were measured completely by the “bottom-up” method, and the influence mechanism and influence heterogeneity of eight factors on carbon emissions were analyzed by using the two-level LMDI addition decomposition model.The results show that the traffic carbon emission in Jiangsu Province has experienced three stages: the high-speed growth stage from 2001 to 2005,the medium-speed growth stage from 2006 to 2013,and the low-speed growth stage from 2014 to now, and the growth rate has remained stable below 10%.As for the spatial change trend, the traffic carbon emissions in Jiangsu Province are characterized by “high in the south and low in the north”,and Suzhou’s carbon emissions account for about 1/3 of Jiangsu Province.As for the driving factors, energy efficiency, economic level, public transport saturation, green vegetation coverage and population size are the driving factors, while industrial structure, public transport participation and land use structure are the main driving factors, among which economic level is the primary driving factor and public transport participation is the main driving factor.

【基金】 苏州市科技计划项目-碳达峰碳中和科技支撑重点专项(ST202218)资助
  • 【文献出处】 环境生态学 ,Environmental Ecology , 编辑部邮箱 ,2024年01期
  • 【分类号】X73
  • 【下载频次】181
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