摘要
基于数据融合的夜间灯光数据构建中国西部地区省市县三级多尺度碳排放模型,利用分数阶灰色模型估算2025年省市县三级碳排放数据,采用莫兰指数进行空间聚集性分析,运用LMDI因素分解方法探究能源消费碳排放的影响因素。结果表明:西部地区地市级和区县级碳排放整体水平呈显著正相关关系,内部存在高(低)聚类。各省会城市处于高碳排第一方阵,并各自形成省会城市包围圈,辐射周边城市。经济发展是西部地区能源消费碳排放增长的最大“推手”;能源强度下降是降低能源消费碳排放的重要因素;人口规模和能源结构对能源消费碳排放有着微弱的正向影响。
A multi-scale carbon emission model based on night light data of long time series is constructed for western China at provincial,municipal and county levels,and a fractional-order grey model is used to estimate carbon emission data for 2025 at provincial,municipal and county levels.The Moran index is used for spatial aggregation analysis,and the LMDI factor decomposition method is applied to explore the influencing factors of carbon emission from energy consumption.Economic development is the biggest "driver" of the growth of carbon emissions from energy consumption in the western region;decreasing energy intensity is an important factor in reducing carbon emissions from energy consumption;population size and energy structure have a weak positive influence on carbon emissions from energy consumption.
作者
冉光圭
杨宣
RAN Guang-gui;YANG Xuan(School of Managment,Guizhou University,Guiyang,Guizhou 550025,China)
出处
《贵州民族研究》
CSSCI
北大核心
2022年第6期56-61,共6页
Guizhou Ethnic Studies
基金
国家自然科学基金项目“碳中和背景下中国发电行业碳排放配额分配方法及其应用研究”(72104062)
贵州省2018年十大创新团队(公司治理与公司金融)项目(省社科通[2017] 29号)
贵州大学文科重点学科及特色学科重大科研项目(GDZT201707号)的阶段性成果。
关键词
西部地区
夜间灯光数据
多尺度能源碳排放
空间聚集性分析
LMDI因素分解
China’s western region
Night light data
Multi scale carbon emission from energy consumption
Spatial aggregation analysis
LMDI factor decomposition
