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2011 , Vol. 26 >Issue 5: 814 - 824

DOI: https://doi.org/10.11849/zrzyxb.2011.05.009

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基于STIRPAT模型的能源消费碳足迹变化及影响因素——以江苏省苏锡常地区为例

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  • 南京农业大学 公共管理学院,南京 210095
卢娜(1982- ),女,河北正定人,博士研究生,主要研究方向为资源经济与可持续发展。E-mail: lunaluckyforever@163.com

收稿日期: 2010-09-12

  修回日期: 2010-11-20

  网络出版日期: 2011-05-20

基金资助

国家自然科学基金重点项目"农村发展中生态环境管理研究"(70833001);江苏省"青蓝工程"资助。

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Trends and Determining Factors of Energy Consumption Carbon Footprint —An Analysis for Suzhou-Wuxi-Changzhou Region Based on STIRPAT Model

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  • College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China

Received date: 2010-09-12

  Revised date: 2010-11-20

  Online published: 2011-05-20

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摘要

定量研究经济社会发展对地区能源消费碳足迹的影响对区域实现低碳发展具有重要意义。论文计算了江苏省苏锡常地区1991—2008年能源消费碳足迹,采用岭回归函数对STIRPAT模型进行了拟合,采用脱钩指数分析了经济发展与能源消费碳足迹之间的关系。结果表明:①1991—2008年能源消费碳足迹平均增长速度为15.30%,能源消费碳足迹分配率以煤炭为主,石油所占比例呈波动下降趋势,天然气所占比例上升较快,能源消费碳足迹产值总体呈波动下降趋势;②经济增长是能源消费碳足迹的主要影响因素,两者关系模型拟合未出现环境库兹涅茨曲线;③经济增长与能源消费碳足迹之间处于相对脱钩与复钩的波动状态,从另一侧面验证了目前两者之间不存在库兹涅茨曲线假说的结论。

关键词： 工业经济; 能源消费碳足迹; STIRPAT模型; 脱钩指数; 苏锡常

本文引用格式

卢娜, 曲福田, 冯淑怡, 邵雪兰 . 基于STIRPAT模型的能源消费碳足迹变化及影响因素——以江苏省苏锡常地区为例[J]. 自然资源学报, 2011 , 26(5) : 814 -824 . DOI: 10.11849/zrzyxb.2011.05.009

Abstract

Improving the understanding of the impact of socio-economic development on energy consumption carbon footprint is of great importance for developing low-carbon economy. This paper calculated and analyzed the trend of energy consumption carbon footprint of Suzhou-Wuxi-Changzhou region during the period of 1991—2008. Applying ridge regression method, the STIRPAT model was estimated to explore the relationships between population, per capita GDP, technological development and energy consumption carbon footprint. The decoupling index was adopted to further analyze the relationship between economic growth and energy consumption carbon footprint. Results indicated that: 1) For Suzhou-Wuxi-Changzhou region, energy consumption carbon footprint has increased from 0.05 hm2 per capita in 1991 to 0.58 hm2 per capita in 2008. The annual average increasing rate was 15.30%. Coal consumption accounted for the largest share in energy consumption carbon footprint. The share in 2008 was 96.18%. Petroleum consumption fluctuated and showed a downward trend, the share decreased from 18.71% to 3.42% from 1991 to 2008. Different from petroleum, natural gas consumption rose very fast. Even though the share was only 0.40% in 2008, the annual average increasing rate was 45.40% since the extension of natural gas in 2002. The value of carbon footprint showed an overall fluctuating downward tendency, indicating a large space for energy efficiency improvement. 2) Economic development was the main driving factor for energy consumption carbon footprint. 1% increase of per capita GDP has resulted in 0.73% increase in energy consumption carbon footprint. The relationship between per capita GDP and energy consumption carbon footprint, however, did not prove the environmental Kuznets curve (EKC), indicating that with the socio-economic development, environmental pressure caused by energy consumption will continuously increasing. 3) The decoupling index was fluctuating, either in the state of relative decoupling or in re-coupling, indicating that economic growth was highly dependent on energy consumption, and verifying that EKC hypothesis does not exist. Compared with Suzhou and Wuxi, Changzhou has displayed a decoupling state between economic growth and energy consumption carbon footprint since 1998.

Key words： industrial economy; energy consumption carbon footprint; STIRPAT model; decoupling index; Suzhou-Wuxi-Changzhou region

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