资源科学 ›› 2017, Vol. 39 ›› Issue (12): 2247-2257.doi: 10.18402/resci.2017.12.04

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中国能源消费结构地域分布的时空分异及影响因素

周彦楠1,2,3(), 何则1,2,3, 马丽1,2,3, 杨宇1,2,3(), 张天媛4, 陈力原4   

  1. 1. 中国科学院地理科学与资源研究所,北京 100101
    2. 中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
    3. 中国科学院大学资源与环境学院,北京 100049
    4. 北京林业大学林学院,北京 100083
  • 收稿日期:2017-09-07 修回日期:2017-11-25 出版日期:2017-12-31 发布日期:2017-12-31
  • 作者简介:

    作者简介:周彦楠,女,河南信阳人,硕士生,从事能源地理与区域发展研究。E-mail:zhouyn.17s@igsnrr.ac.cn

  • 基金资助:
    中华人民共和国科学技术部国家重点研发项目(2016YFA0602800);国家自然科学基金项目(41401132;41371141)

Spatial and temporal differentiation of China's provincial scale energy consumption structure

Yannan ZHOU1,2,3(), Ze HE1,2,3, Li MA1,2,3, Yu YANG1,2,3(), Tianyuan ZHANG4, Liyuan CHEN4   

  1. 1. Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China
    2. The Key Laboratory of Regional Sustainable Development Analysis and Simulation,Beijing 100101,China
    3. College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China
    4. College of Forestry,Beijing Forestry University,Beijing 100083,China
  • Received:2017-09-07 Revised:2017-11-25 Online:2017-12-31 Published:2017-12-31

摘要:

能源碳排放是全球温室效应最主要的贡献因素,要实现低碳发展,必须调整能源消费结构。本文基于分省能源终端消费数据,采用K-means聚类法和STIRPAT模型,对中国省级层面四大类能源的消费比重、时空分异、演化及其影响因素的研究结果表明:①1990—2014年间,各省煤炭消费比重不断降低,不同省区在不同时段石油消费比重变化呈现多样性特征,各省天然气消费比重整体仍处在较低水平上,电力与热力消费比重整体保持着持续增加的趋势;北京、天津、上海、江苏、广东、海南、甘肃、青海和宁夏处于相对较优的低碳能源消费结构;②1990—2014年期间,中国能源终端消费结构呈现出不断改善的趋势,其地域分布一方面呈现出明显的地带性分布特征,同时也表现出一定的产地消费导向特征;③能源消费强度、第二产业比重、能源生产结构和资本投入等依次对以煤炭为主的能源消费结构有正向促进作用;土地城市化、能源自给度、科技进步和进出口贸易等具有反向抑制作用;而人均GDP、人口城市化和实际利用外商直接投资的作用不显著。建议在省区层面着力调整能源消费结构,关注河北、山西和贵州等地能源产地消费导向问题,并通过加快推进产业结构高级化进程、合理安排城市化进程、提升科技创新能力和增强对外开放水平,以有效改善各省能源消费结构、降低碳排放,实现低碳发展。

关键词: 能源消费结构, 地域分布, K-means, STRIPAT, 时空分异, 影响因素, 中国

Abstract:

Energy-related carbon emissions are the most important contributor to the global greenhouse effect. Low-carbon development must begin with the adjustment of the energy consumption structure(ECT). Based on four categories of provincial level energy terminal consumption data,using the K means clustering method and the STIRPAT model,we researched the geographical distribution pattern of ECT and spatial and time differentiation,evolution and influence factors. We found that from 1990 to 2014,the provincial coal consumption ratio decreased;oil consumption ratio changed in different periods in different provinces;natural gas consumption was at a low level and showed regional diversity;and power and heat consumption increased. Beijing,Tianjin,Shanghai,Jiangsu,Guangdong,Hainan,Gansu,Qinghai and Ningxia provinces are in a relatively low carbon ECT. China’s energy terminal consumption structure showed a trend of continuous improvement over 1990 to 2014. On the one hand,the geographical distribution of ECT shows obvious zonal distribution,while also showing certain characteristic of in-situ consumption orientation. The energy consumption intensity,industrial structure,energy production structure and capital input,in turn,have positive promoting effects on ECT dominated by coal. The urbanization of land,rate of energy self-sufficiency,technology progress and import and export trade,have an inhibiting effect on ECT. GDP per capita,population urbanization and FDI of actual usage are not significant for ECT. In order to effectively ameliorate the provincial energy consumption structure,reduce carbon emissions and achieve low carbon development,China should adjust ECT at the provincial level,focusing on Hebei,Shanxi and Guizhou energy in-situ consumption status,and speed up the process of the fundamentals of industrial structure,advancing urbanization,enhancing the level of science and technology innovation and promoting an international focus.

Key words: energy consumption structure, geographical distribution, K-means, STRIPAT, spatiotemporal differentiation, influencing factor, China