摘要
文章利用政府宏观统计数据,基于投入产出模型测算了上海居民消费产生的间接碳排放,并利用扩展的投入产出模型,使用结构分解分析法分析了居民消费间接碳排放的影响因素。结果表明:1997-2010年,上海市石油加工炼焦及燃烧加工业、金属加工制品、交通运输仓储及信息服务3个部门的碳排放强度、碳排放乘数因子均处于各部门前列,是能源消耗高度密集型部门;上海市居民间接能源消费产生的碳排放总量、城镇居民间接能源消费产生的碳排放呈上升趋势,农村居民间接能源消费产生的碳排放总体呈下降趋势。结构分解结果显示,上海市居民消费水平的提高是居民消费间接碳排放增加的主要驱动力;城镇人口规模的增加也是影响上海城镇居民消费间接碳排放总量增加的重要因素。调整居民消费结构、降低部门碳排放强度是现阶段居民消费碳减排的有效措施。
Based on the input-output model,this study calculated the indirect carbon emissions of Shanghai’s residents con sumption with the government macroscopic statistic data.In addition influencing factors of carbon emission were analyzed with the improved input-output model and structure decomposition analysis method.The results as follows,first of all,during the years from 1997 to 2010,oil processing coking and burning processing industry carbon emissions intensity and carbon emis sions multiplier factor is the biggest,and they are energy-consumption-intensive sectors.Secondly,carbon emission from residents indirect energy consumption of Shanghai’s whole city and urban area increased year by year,while carbon emission from rural residents indirect energy consumption decreased.Furthermore,the structure decomposition results showed that the main driving force for the increasing of the indirect carbon emission from residents consumption was the improved consumption level.Besides,the rapid urban population growth was also a key factor for the increase of the indirect carbon emission from residents’consumption.It is important to correctly handle contradictions among the development of low-carbon economy and the improvement of level of household consumption and population urbanization.At the present,adjusting residents’con sumption structure and reducing carbon emission intensity are the most effective measures to reduce carbon emission caused by residents’consumption.
出处
《华东经济管理》
CSSCI
2013年第1期1-7,共7页
East China Economic Management
基金
国家社会科学基金重大项目(10ZD&032)
国家自然科学基金项目(71173047)
教育部人文社会科学研究规划基金项目(09YJA790045)
关键词
居民消费
间接碳排放
投入产出
上海市
residents’consumption
indirect carbon emissions
input-output
Shanghai