城镇化进程中家庭碳排放变化趋势、驱动因素和减排对策

发布时间：2018-04-08 13:41

本文选题：家庭直接碳排放　切入点：家庭间接关联碳排放　出处：《浙江大学》2017年博士论文

【摘要】：研究背景全球变暖已成为国家非传统安全问题,而二氧化碳排放是长期气候变化的最大贡献因素。中国碳排放规模已列全球第一,我国政府在巴黎协定等国际协议中承诺碳排放在2030年左右达到峰值。随着城镇化发展、家庭小型化与核心化的人口转型以及消费升级,家庭碳排放逐渐成为未来碳排放的新增长点,因而有必要以家庭为研究单位,探讨城镇化进程中城乡家庭碳排放变动趋势及其驱动因素、影响机理,为制定相应的家庭节能减排政策提供参考。研究方法与内容本研究建立“人口-家庭-消费-碳排放-环境”的理论框架和脉络,着眼于家庭消费引起的直接碳排放和间接关联碳排放,使用IPCC推荐的碳排放计算方法、投入-产出模型,分别计算家庭直接、间接关联碳排放。从家庭户城镇化的视角,引入对数平均迪氏指数分解(LMDI)模型,从人口、经济、技术等宏观层面解释家庭碳排放的驱动因素。从家庭户异质性的微观角度分析家庭消费结构的影响因素,在消费者生活方式框架下分析不同类型家庭的碳排放规模及结构,建立线性回归分析模型,研究城乡属性、收入、户主年龄、性别、教育程度、家庭规模等家庭户异质性特征对家庭碳排放的影响。应用LMDI双层完全分解,分析家庭碳排放占全国碳排放比重变动的影响因素,并进行国际比较,以明晰我国当前家庭碳排放的发展阶段。结合我国经济发展新常态、社会人口发展趋势与减排目标的多重约束条件,在IPAT模型基础上建立IHAT-IDA预测模型,估算2017～2050年我国的家庭碳排放变化,最后从家庭消费消费需求侧、行业供给侧角度分别提出减排建议。研究结论(1)城乡家庭直接能源消费结构逐步趋向低碳化,且存在明显差异,与发达国家相比较,我国家庭直接能源消费和碳排放处于较低水平,未来减排空间有限,减排空间更多存在于相关的供给侧生产部门。(2)家庭间接关联碳排放对应的行业部门从满足基本生活保障的农业、食品制造业等部门逐渐过渡到与居住、医疗保健相关的服务型部门。(3)宏观层面上,城乡家庭户数和收入水平是家庭碳排放增长的重要正向驱动因素,家庭户城镇化水平促进间接关联碳排放增长,城乡家庭消费结构具有不同程度的高碳化特征,碳排放强度抑制家庭碳排放的增长。(4)微观层面上,家庭收入、家庭规模、户主教育水平、性别、年龄均对家庭碳排放规模和结构有不同程度的影响。(5)城乡最高收入组的家庭分别对城乡家庭碳排放贡献46.8%、33.2%,具有较大的碳排放责任,政策制定者可针对不同收入组的家庭户实行有区别的消费引导和政策工具。(6)2017～2050年,我国家庭直接碳排放、间接关联碳排放占全国碳排放的比重分别从3.48%、46.15%升至5.6～7.1%、48.8～49.8%。(7)家庭碳排放峰值将出现于2028～2031年,约为50.5～55.7tC02,环境库兹涅茨假说适用于中国家庭部门的碳排放。
[Abstract]:Background Global warming has become a national non-traditional safety problem, and carbon dioxide emissions are the biggest contributors to climate change in the long term.China has already ranked first in the world in terms of carbon emissions, and the Chinese government has promised to peak carbon emissions around 2030 in international agreements such as the Paris Agreement.With the development of urbanization, the population transformation and consumption upgrading of household miniaturization and core, household carbon emissions gradually become a new growth point of future carbon emissions, so it is necessary to take the family as the research unit.This paper probes into the changing trend of carbon emissions of urban and rural households in the process of urbanization, the driving factors and the influencing mechanism, and provides a reference for formulating the corresponding policies of household energy saving and emission reduction.Research methods and contents this study establishes the theoretical framework and context of population-household-consumption-carbon emitter-environment, focuses on the direct and indirect related carbon emissions caused by household consumption, and uses the carbon emission calculation method recommended by IPCC.The input-output model is used to calculate the direct and indirect carbon emissions of households.From the perspective of household urbanization, the LMDI model is introduced to explain the driving factors of household carbon emission from population, economy, technology and so on.This paper analyzes the influencing factors of household consumption structure from the microcosmic perspective of household heterogeneity, analyzes the scale and structure of carbon emissions of different types of households under the framework of consumer lifestyle, establishes a linear regression model, studies the attributes of urban and rural areas and income.The influence of household heterogeneity such as head of household age, sex, education level and household size on household carbon emissions.By using LMDI double layer complete decomposition, this paper analyzes the influencing factors of the change of household carbon emissions in the whole country, and makes an international comparison in order to clarify the development stage of household carbon emissions in China.Combined with the new normal of China's economic development, the trend of social and population development and the multiple constraints of emission reduction targets, a IHAT-IDA prediction model is established on the basis of IPAT model to estimate the changes of household carbon emissions in China from 2017-2050. Finally, the demand side of household consumption is analyzed.Industry supply-side angle respectively put forward emission reduction recommendations.Conclusion 1) the consumption structure of direct energy in urban and rural households tends to be decarbonized gradually, and there are obvious differences. Compared with developed countries, household direct energy consumption and carbon emissions in China are at a lower level, and the future emission reduction space is limited.Emission reduction space exists more in the relevant supply-side production sector. 2) households indirectly associated with carbon emissions corresponding to the industry sectors from agriculture, food manufacturing and other sectors that meet basic living security gradually transition to housing.At the macro level, the number of households and income levels of urban and rural households are the important positive drivers of the growth of household carbon emissions, and the urbanization level of households promotes the growth of indirectly correlated carbon emissions.The consumption structure of urban and rural households has different degree of high carbonization characteristics, carbon emission intensity inhibits the growth of household carbon emissions.) on the micro level, household income, household size, head of household education level, gender,Age has different effects on the scale and structure of household carbon emissions. (5) households of the highest income groups in urban and rural areas contribute 46.833. 2 to the carbon emissions of urban and rural households, respectively, and have greater responsibility for carbon emissions.Policy makers can implement differentiated consumption guidance and policy tools for households in different income groups from 20172050 to 2050, with direct carbon emissions from households in our country.The proportion of indirectly correlated carbon emissions to national carbon emissions increased from 3.48% to 5.6%, respectively.) the peak value of household carbon emissions will appear in 2028 ~ 2031, about 50.5 ~ 55.7 t C 02.The environmental Kuznets hypothesis is applicable to the carbon emissions of Chinese household sector.
【学位授予单位】：浙江大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：X321

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