中国碳排放强度预测与煤炭能源比重检验分析  

Forecast of the Carbon Emission Intensity and Analysis of Coal Energy’s Proportion in China

作　　者：刘广为[1] 赵涛[1] 米国芳[1,2] 

机构地区：[1]天津大学管理与经济学部,天津300072 [2]内蒙古财经学院统计与数学学院,呼和浩特010070

出　　处：《资源科学》2012年第4期677-687,共11页Resources Science

基　　金：天津大学自主创新基金(编号:60304002)

摘　　要：本文首先对国内外碳排放强度影响因素研究动态进行系统论述,随后对碳排放强度的预测研究现状做出整体概述。将DDEPM与现有的碳排放预测方法进行比较,说明其优越性。应用DDEPM,用Matlab编程,基于1980年-2009年的碳排放数据和GDP数据,对2020年碳排放和GDP进行预测,通过计算得出降低中国碳排放强度的潜力巨大。基于中国能源以煤炭为主的现状,应用向量自回归模型(VAR),从煤炭能源消耗比重的角度,分析其对中国碳排放强度的影响。随后整合碳排放强度、煤炭消耗比重的预测数据和实际数据,将其整合数据进行向量自回归处理,其结果与碳排放强度与煤炭消耗比重实际数据的向量自回归进行比较,得出了两组模型结论的一致性,从变化规律的角度检验DDEPM预测的准确度;最后应用脉冲响应函数,分析碳排放相度与煤炭消耗比重的相关性。As the largest developing country in the world, China has attracted the attentions of the world for carbon emission problem. The research on carbon emission has become a new hot spot all over the world. As for this study, firstly, we discussed the research situation of influence factors of carbon emission intensity and then systematically summarized the present situation of carbon emission forecast study both at home and at abroad. After discussing the derivation process of the Discrete Difference Equation Prediction Model （DDEPM） and comparing it with the present prediction methods, we found that the DDEPM has great superiority. Therefore, based on the DDEPM, the Matlab programming and the data of carbon emission and GDP during 1980-2009, this paper has forecasted the data of carbon emission and GDP in 2020. At the same time, by calculating we found that there is great potential to reduce the carbon emission intensity. In addition, the paper has analyzed the impact of China’s situation of taking coal as the main energy on the carbon emission intensity based on the Vector Autoregression model （VAR） and the proportion of coal consumption. After that, we integrated the carbon emission intensity, the prediction data of the proportion of coal consumption and the actual data and then dealt with the integration data by VAR model. Through comparing the integration data model with the actual data model, we got the conclusion that the two models are similar to each other. We also checked the accuracy of DDEPM prediction in terms of the variation law. At last, we have analyzed the correlation between carbon emission intensity and the proportion of coal consumption by applying the Impulse Response Function.

关 键 词：碳排放强度 DDEPM 煤炭能源比重 VAR 脉冲响应函数 

分 类 号：F224[经济管理—国民经济] F205F426.21