%0 Journal Article
%T Evaluation and Prediction of Carbon Emissions from Thermal Power Enterprises in China<br>中国火电企业碳排放测算及预测分析
%A MI Guofang
%A ZHAO Tao
%A <br>米国芳
%A 赵涛
%J 资源科学
%D 2012
%I 
%X 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.
%K Carbon emissions
%K Low-carbon economy
%K Improved GM model
%K Cyclic residual error<br>碳排放
%K 低碳经济
%K 改进的GM(1
%K 1)模型
%K 周期性残差
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=9DEEAF23637E6E9539AD99BE6ABAB2B3&aid=619BC47B47C1F3B485E45455BF2CE46F&yid=99E9153A83D4CB11&vid=339D79302DF62549&iid=F3090AE9B60B7ED1&sid=BD667367F07B7EA7&eid=A7D9E4E50C1328C9&journal_id=1007-7588&journal_name=资源科学&referenced_num=0&reference_num=16