北京市居民消费间接碳排放测算及影响因素

    Calculation and Driving Forces of Indirect Carbon Emissions from Household Consumption in Beijing

    • 摘要: 利用北京市2002-2012年的统计数据,基于投入产出模型分别测算北京市农村和城市低、中、高3个收入居民群组的消费间接碳排放量,利用结构分解分析(SDA)方法对北京市居民消费间接碳排放的影响因素进行分析。结果表明:2002-2012年,城乡居民消费间接碳排放总量从2002年的3 131.81万吨增加至2012年的3 857.67万吨,年均增长率为2.11%。分收入群组看,农村低、中、高3个收入群组的居民间接碳排放随着收入上升而下降,城市低、中、高3个收入群组的居民间接碳排放随着收入上升而上升。SDA结果显示,2002-2012年,平均消费水平变动是城乡居民消费间接碳排放增加的主要驱动因素,碳排放强度变动则是主要抑制因素,消费结构和城镇化水平的变动则影响有限。因此,在研究结论的基础上提出如下减排建议:进一步降低产业部门碳排放强度和优化产业结构;严控人口规模,提升城镇化的水平和质量;在增加居民收入的基础上优化消费结构,鼓励低碳消费、绿色消费。

       

      Abstract: Using statistical data of Beijing City from 2002 to 2012, this study calculated the indirect carbon emissions from rural and urban household consumption in Beijing by 3 income groups based on input-output analysis, and analyzed the influencing factors of indirect carbon emissions from rural and urban household consumption employing Structural decomposition analysis(SDA). The results show that from 2002 to 2012, the indirect carbon emissions from rural and urban household consumption in Beijing increased from 3131.81(104t CO2)in 2002 to 3857.67(104t CO2)in 2012 with an annual growth rate of 2.11%. Indirect carbon emissions from low, medium, and high income rural household groups decreased with the increase of income, while indirect emissions from low, medium, and high income urban household groups increased with the increase of income. The SDA results show that, the booming average consumption level was the most important driving force for the increase of indirect carbon emissions of household consumption in Beijing from 2002 to 2012;while the change of carbon emissions intensity was the major factor in restraining the increase of indirect carbon emissions, the impact of consumption structure and urbanization was limited. Policy implications about carbon reduction in Beijing are as follows:further reduce carbon emissions intensity of industries and optimize industrial structure, strictly control the population scale and improve the quality and level of urbanization, and optimize consumption structure based on the increase of income and encourage low carbon & green consumption.

       

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