基于GWR的中国居民生活能源消费驱动因素时空演变研究

摘要

借助地理加权回归模型(GWR)揭示中国30个省份、直辖市、自治区2011—2014年人均生活能源消费量受人均可自由支配收入、产业结构、能源消费结构、城镇化率、老龄化率、受教育程度各驱动因素作用的空间差异性.通过研究各省市生活能源消费的驱动因素的空间分布状态,为国家制定差异化的区域生活节能目标和寻找多元化的节能途径提供有益参考.结果表明:人均可自由支配收入、城镇化及受教育程度对人均生活能源消费量产生正向作用,产业结构、能源消费结构及老龄化率对人均生活能源消费产生抑制作用,且生活能源消费各影响因素的回归系数表现为:受教育程度>城镇化率>人均可自由支配收入>产业结构>能源消费结构>老龄化率.因此,政府在进行政策制定时,需根据各影响因素的驱动作用及其空间差异,针对不同区域采取差别化的能源政策,不断调整和优化产业结构和能源消费结构,减少城镇化中能源回弹效应的消极影响,引导和激励居民绿色能源消费,缓解人口规模增加、消费水平提升和城镇化对生活节能的压力.%Geographical Weighted Regression method (GWR) was used to study the impact of per capita disposable income, industrial structure, household energy consumption structure, urbanization rate, aging rate and educational level on the per capita household energy consumption of30 provinces, municipalities and autonomous regions of China to reveal the spatial differences of each driving factor in 2011—2014 respectively. The study of the driving factors spatiotemporal disparity of residential energy consumption provides references for the development of differential regional objectives of energy conservation and multiple energy conservation strategies in the next period to Chinese government. The results showed that the per capita disposable income, urbanization rate and educational level had a positive effect on per capita household energy consumption. The industrial structure, household energy consumption structure and aging rate had an inhibitory effect on per capita household energy consumption. These six influential factors of residential energy consumption in a descending order were: educational level>urbanization rate>per capita disposable income>industrial structure> household energy consumption structure>aging rate. Therefore, the government needs to adopt differentiated energy policies for different regions during policy formulation according to the driving effects of each influencing factor and their spatial differences, while adjusting and optimizing industrial structure and household energy consumption structure, minimizing the negative impact of energy rebound effect under urbanization, guiding and encouraging green residential energy consumption to ease the increasing population, consumption level and the pressure of urbanization on residential energy conservation.