| 摘要: |
| 加强地市碳减排、提高地市碳排放效率是山东省碳减排的重要途径。构建考虑能源替代效应的RAM模型对山东省地市碳排放效率进行测度,并进行差异性分析和聚类分析,运用Moran’s I自相关指数进行空间相关性检验,构建基于面板数据的空间计量模型进行影响因素分析。结果表明:17地市碳排放效率呈现空间聚集效应,多数地市表现为空间依赖性;能源消费结构、产业结构、城镇化对碳排放效率有负向影响,对外开放与科技支持水平对其有正向影响;各地市可通过优化能源消费结构、发展低碳产业、合理推进城市化、鼓励发展对外贸易、增加科技投入、完善区域碳减排合作机制等提升碳排放效率。 |
| 关键词: 碳排放效率 RAM模型 测度 影响因素 提升对策 山东省 |
| DOI：10.13216/j.cnki.upcjess.2018.01.0003 |
| 分类号:F124.5;F224 |
| 基金项目:教育部人文社会科学研究规划基金项目(16YJAZH054);山东省自然科学基金项目(ZR2015GM008);中央高校基本科研业务费专项资金资助项目(15CX04101B) |
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| Evaluation, Influencing Factors and Promotion Countermeasures of Cities Carbon Emissions Efficiencies in Shandong Province |
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SONG Jiekun, LIANG Lulu, NIU Danping, CAO Zijian, ZHANG Kaixin
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(School of Economics and Management, China University of Petroleum, Qingdao, Shandong 266580, China)
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| Abstract: |
| It is an important way to strengthen cities carbon emissions reduction and increase carbon emissions efficiencies for Shandong province. A RAM model considering the energy substitution effect is constructed to evaluate the cities carbon emissions efficiencies, and the difference analysis and cluster analysis are carried out. Moran 's I self-correlation indexes are applied to conduct spatial correlation test, and the spatial measurement model based on panel data is constructed to analyze the influencing factors.The results show as follows:17 cities carbon emissions efficiencies show the spatial aggregation effect, and most of them present spatial dependence.Energy consumption structure, industrial structure and urbanization have negative impact on carbon emissions efficiencies, and the external opening-up and technology support level have positive impacts. 17 cities can optimize energy consumption structure, develop low-carbon industries, promote reasonable urbanization,encourage the development of foreign trade, increase investment in science and technology, and improve the regional cooperation mechanism of carbon emissions reduction, so as to promote carbon emission sefficiencies. |
| Key words: carbon emissions efficiencies RAM model evaluation influencing factors promotion countermeasures Shandong province |
