| 中国火电企业碳排放测算及预测分析 |
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| 引用本文： | 米国芳,赵涛.中国火电企业碳排放测算及预测分析[J].资源科学,2012,34(10):1825-1831. |
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| 作者姓名： | 米国芳 赵涛 |
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| 作者单位： | 1. 天津大学管理与经济学部,天津300072 内蒙古财经学院统计与数学学院,呼和浩特010070
2. 天津大学管理与经济学部,天津,300072 |
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| 基金项目： | 国家自然科学基金(编号:71162015);天津大学自主创新基金资助项目(编号:60304002)。 |
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| 摘 要： | 如何预测和分析火力发电企业的碳排放成为低碳经济研究领域中十分重要的问题。本文分析了我国火电企业的发展现状,并与世界主要发达国家进行了对比研究;根据政府间气候变化专门委员会（IPCC）2006年版碳排放计算指南和不同能源品种的碳排放系数,计算出了1997年-2009年中国火力发电企业碳排放;运用含误差修正的改进的GM（1,1）模型对中国火力发电企业的碳排放进行预测分析,并根据碳排放现状和预测结果总结了我国火电企业碳排放特征。分析结果表明：在保持过去发展规律不变的情况下,中国火力发电企业碳排放量成增长的趋势,并且火电企业的碳排放趋势可以划分为5个阶段。总之,必须通过技术进步来提高能源利用效率和降低单位能耗,使中国火力发电企业实现低碳经济发展。
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| 关 键 词： | 碳排放 低碳经济 改进的GM(1 1)模型 周期性残差 |
Evaluation and Prediction of Carbon Emissions from Thermal Power Enterprises in China |
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| MI Guofang and ZHAO Tao.Evaluation and Prediction of Carbon Emissions from Thermal Power Enterprises in China[J].Resources Science,2012,34(10):1825-1831. |
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| Authors: | MI Guofang and ZHAO Tao |
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| Institution: | Department of Management and Economics, Tianjin University, Tianjin 300072, China;School of Statistics and Mathematical, Inner Mongolia Finance and Economics College, Hohhot 010070, China;Department of Management and Economics, Tianjin University, Tianjin 300072, China |
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| Abstract: | China discharges the most carbon in the world and coal-fired thermal power enterprises are one of the main sources of carbon emissions. How to predicate and analyze carbon emissions is important when discussing the low-carbon economy development of the thermal power sector. This paper analyzed the current thermal power situation in China, and compares major developed countries. Carbon emissions from thermal power enterprises were calculated according to the Intergovernmental Panel on Climate Change’s 2006 guide to the calculation of carbon emissions and carbon emission coefficient of different energy sources from 1997-2009 across China. A GMv (1,1) model was improved by logarithmic and power function transformations on original sample data and substituting the albino responsive for connotation type. Carbon emissions from thermal power enterprises in China were predicted and analyzed using this improved GM (1,1) model (denoted hereafter as IGM). We found that prediction residual errors showed cyclical fluctuation and an appropriate model and cycle were selected according to the broken line graph of residual error. The IGM was modified by cyclic residual error, and the average prediction residual error was reduced to 1.96% from 4.23%, and the precision of the prediction model was equal to first grade. The results showed that the simulation precision of the model was greatly improved. It has a better reaction for carbon emissions with stochastic volatility and accurately fits the predication of carbon emissions from thermal power enterprises. Under the model, carbon emissions grow under current Chinese development laws and trends in carbon emission can be divided into four stages. Maintaining technical progress to improve energy efficiency and reduce energy consumption is essential to fully realize a low-carbon economy and thermal power enterprise in China. |
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| Keywords: | Carbon emissions Low-carbon economy Improved GM model Cyclic residual error |
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