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吴  剑,许嘉钰. 碳约束下的京津冀2035年能源消费路径分析[J]. 科学技术与工程, 2020, 20(24): 10089-10096.
wujian,许嘉钰.Study on Beijing-Tianjin-Hebei Zone Energy Consumption Pathway in 2035 under Carbon Emission Constrain[J].Science Technology and Engineering,2020,20(24):10089-10096.
碳约束下的京津冀2035年能源消费路径分析
Study on Beijing-Tianjin-Hebei Zone Energy Consumption Pathway in 2035 under Carbon Emission Constrain
投稿时间:2019-07-08  修订日期:2020-06-04
DOI:
中文关键词:  碳排放,神经网络,排放系数法,能源消费路径,能源结构优化
英文关键词:carbon dioxide emission, artificial neural network, emission factor method, energy consumption pathway, energy consumption optimization
基金项目:国家大气攻关项目(DQGG0302-04);中国工程院重大咨询项目(2016-ZD-07-01,2017-ZD-09-02-01)资助
     
作者单位
吴  剑 清华大学环境学院
许嘉钰 清华大学环境学院
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中文摘要:
      化石能源消费产生二氧化碳,二氧化碳排放量增加导致气候变化,因此,京津冀地区能源消费将会受到二氧化碳(CO2)排放量(碳排放)的制约。首先,利用经典的时间序列模型预测了驱动因素,如国内生产总值(GDP) 、人口、城市化率、产业结构和能耗强度等。然后将驱动因素预测值作为自变量,能源消费作为因变量,采用神经网络方法计算出北京、天津和河北的能源消费量。并利用排放系数法计算实际碳排放量作为约束量,根据内增原理对煤炭、石油、天然气和其它能源消费量进行优化,优化结果作为京津冀在应对气候变化的能源消费可行路径。研究表明:经济和社会是驱动能源消费量增长的主要驱动因素,碳约束下的能源消费路径核心在于控制煤炭和石油消费,天然气和电力供应是能源结构调整的关键。
英文摘要:
      Carbon dioxide is produced by fossil energy consumption, and the growth of carbon dioxide emissions contributes to climate change,so the Beijing-Tianjin-Hebei zone energy consumption is under carbon dioxide emissions constrain. Firstly, all driving factors (such as gross domestic product (GDP) , population, urbanization rate, industrial mixture, energy consumption intensity) were predicted by classical time series models. And these prediction values were substituted into artificial neural network (ANN) as Independent input variables, the energy consumption as the output variable, and then all total energy consumption were respectively predicted in the Beijing-Tianjin-Hebei region. And their carbon dioxide emissions calculated by emission factor method was regarded as the constrain, then coal, oil, natural gas, other energy consumption were optimized by increase principle, the optimization results were the Beijing-Tianjin-Hebei region energy consumption pathway for climate change . The research results show: economy and society are dominating driving factors for energy consumption growth, the coal and oil energy consumption control is a core measure for the pathway of energy consumption under the carbon dioxide emissions constrain , the supply of natural gas and electricity is the key of energy consumption structure optimization.
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