王京京, 卫佳佳. 时间序列下北京市建筑运行碳排放变化特征与情景模拟[J]. 北京工业大学学报, 2022, 43(3): 220-229. DOI: 10.11936/bjutxb2021060015
    引用本文: 王京京, 卫佳佳. 时间序列下北京市建筑运行碳排放变化特征与情景模拟[J]. 北京工业大学学报, 2022, 43(3): 220-229. DOI: 10.11936/bjutxb2021060015
    WANG Jingjing, WEI Jiajia. Temporal Variation Characteristics and a Scenario Analysis of Carbon Emissions in the Operation of Buildings in Beijing[J]. Journal of Beijing University of Technology, 2022, 43(3): 220-229. DOI: 10.11936/bjutxb2021060015
    Citation: WANG Jingjing, WEI Jiajia. Temporal Variation Characteristics and a Scenario Analysis of Carbon Emissions in the Operation of Buildings in Beijing[J]. Journal of Beijing University of Technology, 2022, 43(3): 220-229. DOI: 10.11936/bjutxb2021060015

    时间序列下北京市建筑运行碳排放变化特征与情景模拟

    Temporal Variation Characteristics and a Scenario Analysis of Carbon Emissions in the Operation of Buildings in Beijing

    • 摘要: 根据联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change,IPCC)统计,建筑业是温室气体的主要来源之一,约占32%,而运行阶段的碳排放占建筑整个生命周期的60%~80%.北京市的碳排放远超全国大部分城市,为了解决北京市建筑运行碳排放研究不足的问题,首先,在传统排放系数法的基础上进行改进,建立时间序列下北京市建筑运行碳排放计算模型,并对北京区域的直接和间接碳排放因子进行修正.通过模拟和分析2005—2019年北京市建筑运行碳排放数据,编制了分行业能源法的建筑运行碳排放清单.其次,利用Kaya恒等式和LMDI模型分析碳排放各个驱动因素的贡献度,运用情景模拟预测北京市建筑运行碳排放在高碳、中碳和低碳下的变化趋势.结果表明:北京的电力和热力碳排放因子均在逐年降低;整体上建筑运行碳排放在2012年达到历史最高值,已初步具备达峰的条件;在未来碳排放仍能呈现整体下降的态势.研究成果将为预测北京的建筑运行碳排放量提供科学依据.

       

      Abstract: According to Intergovernmental Panel on Climate Change (IPCC) statistics, the construction industry is one of the main sources of greenhouse gases emissions, accounting for about 32%. The carbon emissions of buildings in the operation stage accounts for 60%-80% of the whole life cycle. According to previous research, the carbon emissions in Beijing are far higher than those in most other cities in China, but there are still some deficiencies in the research on the carbon emissions of the operation of buildings in Beijing. First, based on the traditional emission coefficient method, the operation calculation model of carbon emissions in the operation of buildings in Beijing was established in time series, and the direct and indirect carbon emission factors of Beijing were modified. By simulating and analyzing the carbon emissions data in the operation of buildings in Beijing from 2005 to 2019, the carbon emission of operation inventory was compiled based on the energy method of different industries. Second, Kaya identity and LMDI models were used to analyze the contribution of various driving factors of carbon emissions, and three scenarios, i.e., high carbon, medium carbon and low carbon were used to predict the changes of carbon emissions in the operation of buildings in Beijing. Results show that the heat and electricity carbon emission factors in Beijing decrease year by year. The carbon emissions in the operation of buildings reaches the highest value in 2012, indicating it has met the goal of peak. The overall carbon emissions demonstrates a trend of decrease in the future. The research results provides a scientific basis for the prediction of the carbon emissions in the operation of buildings in Beijing.

       

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