城镇居民生活能源碳排放的省域差异及影响因素

Provincial Differences and Influencing Factors of Carbon Emissions in Urban Residents' Energy Consumption

利用碳排放系数法,对中国及各省份城镇居民生活能源碳排放进行估算,并利用LMDI模型进行因素分解。结果表明,城镇居民生活能源碳排放从2000年的27 784万吨CO_2增加到2014年的91 336万吨CO_2,其中内蒙古碳排放增量最大。从全国层面看,收入水平和人口规模是刺激因素,分别增加碳排放78 229万吨CO_2和31 998万吨CO_2;节能技术、消费倾向和能源结构是抑制因素,分别减少碳排放31 122万吨CO_2、9 636万吨CO_2和5 917万吨CO_2。从省域层面看,能源结构效应最大的是辽宁省,共减少碳排放793万吨CO_2;节能技术效应最大的是辽宁省,共减少碳排放3 146万吨CO_2;消费倾向效应最大的是山东省,共减少碳排放907万吨CO_2;收入水平效应最大的是辽宁省,共增加碳排放6 153万吨CO_2;人口规模效应最大的是广东省,共增加碳排放4 006万吨CO_2。

Using carbon emission coefficient method,this paper estimated carbon emissions in energy consumption by urban residents in each province in China,and made factorization using LMDI model.The results showed that urban residents’carbon emissions increased from 27 784×10~4 t CO2in the year 2000 to 91 336×10~4 t CO2 in 2014,with Inner Mongolia ranking the first in terms of the carbon emission increment.At the national level,income and population scale are stimulating factors,contributing to the increase of carbon emissions with 78 229×10~4 t CO2 and 31 998×10~4 t CO2 respectively.Energy-saving technology,consumption tendency and energy structure are restraining factors,contributing to the reduction of carbon emissions with 31 122×10~4 t CO2,9 636×10~4 t CO2and 5 917×10~4 t CO2 respectively.At the provincial level,Liaoning Province ranks the first both in terms of the effect of energy structure,reducing 793×10~4 t CO2,and in terms of the effect of energy-saving technology,reducing 3 146×10~4 t CO2;Shandong Province ranks the first in terms of the effect of consumption tendency,reducing 907×10~4t CO2;Meanwhile,Liaoning province ranks the first in terms of the effect of income,increasing 6 153×10~4 t CO2,and Guangdong province ranks the first in terms of the effect of population scale,increasing 4 006×10~4 t CO2.