中国城乡居民生活碳排放驱动因素分析

An Analysis on Driving Factors of China's Urban and Rural Household Carbon Emissions

本文基于时间序列数据从生活消费视角定量评估居民人均生活碳排放的驱动因素。基于Kaya恒等式基本原理,采用LMDI分解法构建一个包括消费碳排放强度、消费结构、城乡消费比重、消费水平、经济水平和城乡结构在内的居民人均生活碳排放驱动因素分解模型,对我国1995-2012年的城乡居民人均生活碳排放影响因素进行分解分析。研究结果表明:消费水平、经济水平、消费结构、城乡结构、城乡消费比重各因素效应对我国城镇居民人均生活碳排放的影响均大于对我国农村居民人均生活碳排放的影响;消费水平、经济水平、消费结构因素对我国城乡居民人均生活碳排放的影响最为明显;城镇人口效应对城镇居民人均生活碳排放量的减排意义重大,而农村人口效应导致农村居民人均生活碳排放量的增加;城乡结构变化会带动居民人均生活碳排放的变化,随着时间推移,城乡结构达到一定程度,我国城乡居民人均生活碳排放的变化也相对稳定。在此基础上,提出我国家庭生活消费节能减排的对策及建议,引导居民低碳生活,绿色消费。

Using time series data, the driving factors of household carbon emissions were estimated from consumption perspective. Based on the basic principles of Kaya identity, a decomposition model on the driving factors of household carbon emissions per capita using the Logarithmic Mean Divisia Index （LMDI） method was established, which included the carbon intensity of consumption, consumption structure, urban-rural consumption ratio, consumption level, economic level and urban-rural structure. The affecting factors of per capita carbon emissions from urban and rural households from 1995 to 2012 were analyzed. The results indicated that the contributions of the consumption level, economic level, consumption structure, urban-rural structure and the urban-rural consumption ratio＇ s effect to urban household carbon emissions per capita were greater than that of rural household carbon emissions per capita. Consumption level, economic level and consumption structure had the most obvious impact on the urban and rural household carbon emissions per capita. Urban population＇ s effect had great significance on the urban household carbon emissions per capita reduction, rural population＇ s effect led to the increase of rural household carbon emissions per capita. Changes in urban-rural structure would result in changes in household carbon emissions per capita. Over time, urban-rural structure will reach a certain level that the changes in China＇s urban and rural household carbon emissions per capita tend to relatively stable. On this basis, the countermeasures and suggestions for energy conservation and pollution reduction from household consumption were put forward to guide residents towards low- carbon living, green consumption.