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江苏省能源消费趋势预测及其碳排放研究 被引量:4

Jianshu province energy consumption trend prediction and carbon emission research
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摘要 能源是江苏未来经济健康发展的物质基础,科学预测江苏未来的能源消费对于能源资源严重缺乏的江苏而言具有举足轻重的意义。文章借助趋势外推模型和ARMA模型相结合,对江苏2014~2023年的能源消费进行了预测,结果表明江苏省2020年能源消费量大约为4.5亿吨标煤;利用马尔科夫预测模型对江苏未来能源消费结构进行了预测,并在此基础上预测了江苏2014~2023年的碳排放量,结果表明,未来江苏的碳排放量呈明显上升趋势,至2020年左右,其碳排放量约为3.7亿吨,这意味着江苏将面临严峻的减排形势。因此江苏未来必须大力调整能源消费结构,使能源结构朝着清洁化、优质化方向发展,为江苏社会经济的健康发展奠定基础。 Energy is the material basis for the fu- ture healthy development of the economy in Jiangsu, so it is very important for Jiangsu to scientifically forecast its future energy consumption, which is ~ack of energy resource. This article forecasts the energy consumption of Jiangsu in 2014-2023 by the combination of trend extrapolation model and ARMA model, the re- sults show that the energy consumption in 2020 in jiangsu province ~s about 450 million tons of tce; then the paper forecasts the future energy consumption structure in jiangsu province by the markov prediction model, predicting its the carbon emissions in 2014- 2023 on the basis of above the forecast ,the results shows that there is clearly ascendant trend in the fu- ture carbon emissions and its carbon emissions will rise to about 370 million tons in 2020, which means Jiangsu will face the severe situation of emissions re- duction. So it is necessary for Jiangsu to vigorously adjust its future structure energy consumption in or- der to make it develop towards clean and varieties and lay the foundation for the healthy development of so- cial economy in Jiangsu province.
作者 邢红 赵媛
出处 《特区经济》 2013年第9期39-42,共4页 Special Zone Economy
关键词 能源消费预测 碳排放 江苏 prediction of energy consumption carbonemissions jiangsu province
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  • 1侯丹丹,杨俊杰.我国“十二五”能源消费预测及影响因素分析[J].中外能源,2012,17(6):1-7. 被引量:7
  • 2Global Carbon Emissions [ EB/OL]. C2014. http://co2now, org/ Current-CO2/CO2 -Now/global-carbon-emissions. html.
  • 3AUFFHAMMER M, CARSON R T. Forecasting the path of China's CO2 emissions using province-level information [ J]. Journal of Envi- ronmental Economics and Management. 2008,55 (3) :229-247.
  • 4江苏统计年鉴_2013[EB/OL].2014.http://www.jssb.gov.cn/2013nj/indexc.htm.
  • 52013年江苏省国民经济和社会发展统计公报[EB/OL].2014-02-20.http://3snews.1schina.tom.cn/system/2014/02/20/020314904.shtml.
  • 6KAYA Y. Impact of carbon dioxide emission on GNP growth : inter- pretation of proposed scenarios [ C ]. Paris:IPCC Energy and Indus- try Subgroup, Response Strategies Working Group, 1989.
  • 7Cai Zhenhua, Liao Xinwei. The trend of China ener gy structure: Forecast natural gas consumption [J] . Energy Education Science and Technology Part A: Energy Science and Research, 2014 (1).
  • 8Bai Yan, Ren Qingchang, Jiang Hongmei. The anal- ysis of combined prediction model of building energy consumption with grey theory and RBF neural net- work [J] . Advanced Materials Research, 2012 (10).
  • 9郭菊娥,柴建,吕振东.我国能源消费需求影响因素及其影响机理分析[J].管理学报,2008,5(5):651-654. 被引量:51
  • 10周丹丹,李蜀庆.重庆市能源消费影响因素分析[J].环境科学与管理,2009,34(3):192-194. 被引量:5

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