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全球CO_2排放研究趋势及其对我国的启示
引用本文:刘红光,刘卫东,范晓梅,唐志鹏.全球CO_2排放研究趋势及其对我国的启示[J].中国人口.资源与环境,2010,20(2).
作者姓名:刘红光  刘卫东  范晓梅  唐志鹏
作者单位:1. 中国科学院地理科学与资源研究所,北京,100101;中国科学院研究生院,北京,100049
2. 中国科学院地理科学与资源研究所,北京,100101
摘    要:近几年,全球气候变暖已经成为国际社会的共识,由此而引发的温室气体减排计划也陆续在主要发达国家开始实施,有关CO_2排放问题的研究也成为全球的学术焦点.通过对全球CO_2排放研究趋势的总结发现:首先,国际社会有关CO_2排放的核算方法不断完善,从IPCC(1995)到IPCC(2006),内容更加完善,方法更趋合理;其次,排放责任的区分日益公平合理,随着"碳转移"和"碳泄露"问题研究的深入,有关排放责任区分方法的研究逐渐在从生产视角向消费视角转变;第三,排放因素分解逐步深入,分解公式包括KAYA公式和投入产出公式,分解方法从指数法到平均对数法再到微积分法,分解模型日趋成熟和多元化;第四,排放预测模型也不断综合化、长期化,自上而下模型和自下而上模型逐渐相互借鉴和融合.在此基础上,笔者对我国CO_2排放研究提出了几点启发,即加快排放因子数据库建设,重视责任排放和结构分析研究,提高自主建模的水平和完善我国技术环境数据库等.以期提高我国对温室气体排放现状和历史的认识,在国际气候变化领域发挥积极的作用.

关 键 词:CO_2排放  研究趋势  启示

Global Research Trends related to CO_2 and Enlightment to China
LIU Hong-guang,LIU Wei-dong,FAN Xiao-mei,TANG Zhi-peng.Global Research Trends related to CO_2 and Enlightment to China[J].China Polulation.Resources and Environment,2010,20(2).
Authors:LIU Hong-guang  LIU Wei-dong  FAN Xiao-mei  TANG Zhi-peng
Abstract:Given the growing awareness on the likely catastrophic effects of climate change and the close association of climate change with global emission of greenhouse gases (of which carbon dioxide is more prominent), considerable research efforts have been devoted to the analysis of carbon dioxide (CO_2) emissions and its relationship to sustainable development. Now GHG deduction programs had been coming into effect in many developed countries whose have more responsibility for history CO_2 emissions, as well as the studies has been mature. First, the GHG emission accounting system is more all-inclusive and the methods is more reasonable with the effort of IPCC from 1995 and all other researchers related. Second, the responsibility location is more reasonable and fair. Along with the clarity of "carbon transfer" or" carbon leakage", the perspective and methodology for parting regional CO_2 emission responsibility is turning from production base to consumption base. Third, the decomposition method is deeper and more complexe. For example, the decomposition formulas are including KAYA expression and Input-output expression and the decomposition techniques are developed from Index analysis to Sample Average Division and then Adaptive-weighting Division.Fourth, the prediction model is more integrated and long-term. The top-down model and bottom-up model are both inter-embedded and synergetic. Trends above give some advices for the research of CO_2 in our country, such as emission factors database construction, deeper research on emission responsibility and structure analysis, promotion of modeling technology and technology-environment database.
Keywords:CO_2 emission  research trends  enlightment
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