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作 者:张晓平[1]
机构地区:[1]中国科学院研究生院资源与环境学院,北京100049
出 处:《资源科学》2008年第6期883-889,共7页Resources Science
基 金:国家科技支撑计划(课题批准号:2007BAC03A11)
摘 要:能源消费强度反映国民经济发展中对能源的利用效率,其变动方向及影响因素受到学术界广泛关注。但研究中大多以我国总体能源消费强度的变化为对象,对地域差异关注不足。本文选取多项指标,构建能源消费规模份额指数、能耗强度指数、增长速度指数、综合消费指数,从不同角度刻画中国能源消费的区域差异。在此基础上,利用回归分析法,定量研究了地区能源消费强度的影响因素。结果表明,我国地区间能源消费强度的差异与地区总体经济发展水平、地区工业化程度、地区经济重型化程度存在直接关系,尤其是地区经济重型化程度的提高将会显著增加地区经济能耗强度。现阶段,控制高耗能重化工业的重复建设与盲目投资,对于减小能源消耗强度具有重要的意义。同时,经济发展水平和经济结构的地域差异性,要求我国能源战略的推进与实施必须制定相应的地区政策才能确保国家宏观战略的顺利实施。China is currently the second largest energy consumer in the world after the US, and energy consumption will likely continue to rise due to industrialization and urbanization. Energy-saving initiatives are not only a response to international carbon emission reduction requirements, but also an international responsibility. To implement the national energy strategy, it is necessary to research the factors that heavily impact energy intensity in China. Many scholars have studied China' s energy intensity changes (measured by energy consumption per unit of GDP), and the impact of factors such as industrial structure, technology improvement and energy efficiency changes. Compared with national-scale studies on energy intensity, regional-level analysis of disparities in energy intensity at the provincial scale is not well developed. This paper briefly introduces China's energy situation and previous empirical studies, and describes the regional disparities in energy intensity using several provincial-level indicators, including total energy consumption and its proportion of national consumption, energy intensity, and growth rate. Eastern provinces such as Shandong, Hebei, Jiangsu, Guangdong and Liaoning make up a large proportion of China's total energy consumption and growth. In terms of energy intensity, the northern provinces, in particular Inner Mongolia, Shanxi and Ningxia, have relatively higher levels. The paper offers a qualitative analysis of the main factors affecting regional energy intensity, with an emphasis on regional economic development level, economic structure and industrial structure. To quantify the impact of industrial composition, this study used a heavy-degree index (HI) for the regional economies, calculated as the proportion of industrial value-added to gross regional production multiplied by the ratio of heavy to light industry at the provincial level. Results from regression analysis show that regional energy intensity is statistically correlated with regional development l
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