文章摘要
中国省域能源消费碳排放及其 驱动因素分解分析
Carbon Emissions of Energy Consumption and Its DrivingFactors Decomposition in China's Provinces
  
DOI:
中文关键词: 碳排放  LMDI方法  能源消费  因素分解  中国省域
英文关键词: carbon emissions  LMDI method  energy consumption  factors decomposition  China's provinces
基金项目:教育部人文社会科学资助项目(14YJAZH050);湖南省社科基金资助项目(14YBA170)
作者单位
刘贤赵,高长春,张勇,余光辉,宋焱,田艳林 湖南科技大学 资源环境与安全工程学院湖南 湘潭 411201 
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中文摘要:
      在利用IPCC提供的参考方法对中国大陆30个省区(不包括西藏)1997~2012年能源消费碳排放量估算、分析的基础上,采用LMDI分解模型将碳排放的影响因子分解为人口规模效应、经济发展效应、能源强度效应、能源结构效应以及城乡人口结构效应和人均能源消费效应,并对江苏、河南、内蒙古和重庆4省区的碳排放驱动因素进行了实证分解.结果表明:中国各省域碳排放量和人均碳排放量均呈上升趋势,但增加幅度各省区明显不同;CO2排放强度存在明显的省区差异,表现为东部省份<中部省份<西部省份,除青海、宁夏和海南3省碳排放强度仍在增加外,其他各省区均呈下降趋势;经济发展、人口规模、城市化水平对碳排放表现为正向效应,能源强度、能源结构则表现为负向效应,其中经济发展对4省区能源消费碳排放正向效应最大,而能源强度对4省区碳排放负向效应最大;乡村人口比例、城乡人均能源消费量对4省区碳排放量的影响有限且存在较弱的正负波动.
英文摘要:
      The CO2 emissions of energy consumption were calculated and analyzed according to the reference approach provided by IPCC in China’s thirty provinces (excluding Tibet) from 1997 to 2012. Based on this, using the method of LMDI decomposition, the effects of CO2 emission in China’s provinces were decomposed into six influencing effects, namely population size effect, economic development effects, energy intensity effect, energy structure effect, urban-rural population structure effect and per capita energy consumption effect. Also the driving forces of carbon emissions from energy consumption in the four provinces of Jiangsu, Henan, Inner Mongolia and Chongqing were empirically decomposed. The results showed that: Both the amount of carbon emissions and per capita carbon emissions in China’s provinces exhibite an upward trend over the period from 1997 to 2012, but the increase ranges in China’s provinces are significantly different; The obvious differences in CO2 emissions intensities are found in China’s provinces. The provinces in descending order of carbon emission intensity are the western provinces, the central provinces and the eastern provinces. The intensities of carbon emissions in other provinces of China showed a declining trend except in three provinces of Qinghai, Ningxia and Hainan; Economic development, population size and urbanization level had the positive effect on carbon emissions, and energy intensity and energy structure are negative effect. Among them, economic development had the strongest positive impact on carbon emissions; energy intensity effect had the strongest negative effect on carbon emissions. The proportion of rural population, the energy consumption per capita of urban and rural areas had limited impacts on the increase of CO2 emission and exhibited weak positive and negative fluctuation effects on carbon emissions. Keywords: carbon emissions; LMDI method; energy consumption; factors decomposition; China's provinces
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