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中国生物质燃气产能及碳减排潜力
引用本文:赵晓,常化振,彭思洋,王伟,王书肖,马中.中国生物质燃气产能及碳减排潜力[J].中国环境科学,2018,38(8):3151-3159.
作者姓名:赵晓  常化振  彭思洋  王伟  王书肖  马中
作者单位:1. 中国人民大学环境学院, 北京 100872; 2. 清华大学环境学院, 北京 100084
基金项目:国家重点研发计划项目(2016YFC0203900,2016YFC0203901)及国家自然科学基金项目(51778619,21577173)
摘    要:基于回归分析预测模型和来源分类预测模型对2020~2050年生物质燃气产量和能源结构占比进行预测,并对碳减排潜力进行了情景分析.结果表明,回归分析预测偏差较小,其中逐步回归预测偏差值为9.34%,略小于多元线性回归的13.99%.来源分类模型的准确度高于回归模型.到2050年,沼气增幅约为176%.在低碳情景中提高生物质燃气应用比例最高可降低未来情景中10%的碳排放量,表明大力发展生物质燃气对于碳减排和碳循环有较为明显的正面效应.结合现状对经济,技术,市场等方面提出政策建议.为下一步发掘生物质燃气产品市场潜力提供理论指导.

关 键 词:生物质燃气  回归预测  情景分析  碳减排潜力计算  
收稿时间:2018-01-23

The analysis of biomass gas production capacity and carbon emission reduction potential in China
ZHAO Xiao,CHANG Hua-zhen,PENG Si-yang,WANG Wei,WANG Shu-xiao,MA Zhong.The analysis of biomass gas production capacity and carbon emission reduction potential in China[J].China Environmental Science,2018,38(8):3151-3159.
Authors:ZHAO Xiao  CHANG Hua-zhen  PENG Si-yang  WANG Wei  WANG Shu-xiao  MA Zhong
Institution:1. School of Environment and Natural Resources, Renming University of China, Beijing 100872, China; 2. School of Environment, Tsinghua University, Beijing 100084, China
Abstract:Based on the regression analysis prediction model and the source classification prediction model, the biomass gas production and the energy structure proportion between 2020 and 2050 were predicted. And the scenarios of carbon emission reduction potential were analyzed. The results showed that the regression analysis had a smaller prediction error, which stepwise regression prediction was 9.34%, slightly less than 13.99% of the multiple linear regression. The source classification model was more accurate. By 2050, biogas would increase by about 176%. And increasing the application of biomass gas in the low-carbon scenario can reduce the carbon emission by 10% in the future scenario, indicating that the vigorous development of biomass gas has a significant positive effect on carbon emission reduction and carbon cycle. Based on the status, we put forward several policy suggestions on economy, technology and market to provide theoretical guidance for further exploring of market potential on biomass gas.
Keywords:biogas  regression forecast  scenario analysis  carbon emission reduction potential  
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