安徽省1995年-2009年能源消费碳排放驱动因子分析及趋势预测——基于STIRPAT模型  

Trend Prediction and Analysis of Driving Factors of Carbon Emissions from Energy Consumption during the Period 1995-2009 in Anhui Province Based on the STIRPAT Model

作　　者：张乐勤[1,2] 李荣富[3] 陈素平[3] 祝亚雯[2] 许信旺[2] 

机构地区：[1]安徽农业大学资源环境学院,合肥230036 [2]池州学院资源环境与旅游系,池州247000 [3]池州学院资源经济贸易系,池州247000

出　　处：《资源科学》2012年第2期316-327,共12页Resources Science

基　　金：安徽省教育厅重点研究课题(编号:2010sk502zd);国家自然基金项目(编号:41071337);池州学院自然重点课题(编号:2012zrz006)

摘　　要：能源消费碳排放驱动因子的定量分析能揭示出碳排放的影响因素。依据IPCC碳排放计算方法,对安徽省1995年-2009年能源消费碳排放量及碳排放强度进行了动态测度,结果表明:1995年-2009年,安徽省能源消费碳排放量由1995年的4420.58万t增加到2009年的10919.11万t,呈持续增长态势,年平均增幅为10.48%,碳排放强度由1995年的2.44t/万元降至2009年的1.09t/万元,呈持续下降态势,平均年降幅9.69%,煤炭类碳排放量占绝对优势,年平均为93.77%。基于STIRPAT模型,揭示了人口、人均GDP、第二产业贡献值、全社会固定资产投资、单位GDP能耗等驱动因子的边际弹性系数分别为0.1582、0.2329、0.2424、0.2688、-0.1176。运用灰色GM(1,1)模型,预测2015年、2020年的碳排放量将分别达到15686.25万t、22519.10万t,碳排放强度将分别降至0.81t/万元、0.62t/万元。根据安徽省能源消费碳排放量现状特点及发展趋势,结合碳排放驱动因子的边际贡献,提出了减少能源消费的政策建议,可为安徽省节能减排政策的制定提供科学依据,有利于安徽省的生态建设及可持续发展,也可为中尺度(省级行政区)碳排放驱动因子研究及预测提供示范。Quantitative analysis of driving factors of carbon emissions from energy consumption can show influential factors of carbon emissions.By restricting one or some of the factors that can effectively reduce carbon emissions,it is a commonly used method to reduce carbon emissions and climate change.Based on the approach of IPCC for carbon emissions,this study performed an investigation into dynamic measurement of the total carbon emission from energy consumption and carbon emission intensity from 1995 throughout 2009 in Anhui Province.Results indicate an increase in carbon emissions from energy consumption in Anhui Province from 4420.58 ten thousands tons in 1995 to 10 919.11 ten thousands tons in 2009,a yearly increase of 10.48%on average,and a decrease in carbon emission intensity from 0.244 kg/RMB in 1995 to 0.109 kg/ RMB in 2005,a yearly decrease of 9.69%.The carbon emission resulted mostly from coal, accounting for 93.77%.Based on the STIRPAT model,the study revealed that marginal elasticity coefficients of driving factors such as population,per capita GDP,the value contribution of the secondary industry,total fixed asset investment,and energy consumption per unit of GDP are 0.1582,0.2329,0.2424,0.2688,and-0.1176,respectively.Then the grey GM（1,1）model was applied.Carbon emissions in 2015 and 2020 will be expected to expand to 15 686.25 and 22 519.10 ten thousands tons,and the carbon emission intensity will reduce to 0.081kg/RMB and 0.062kg/RMB,respectively.Finally,according to the current characteristics and development trends of carbon emissions from energy consumption,combined with the marginal contribution of driving factors of carbon emissions,some policy recommendations were given to reduce energy consumption,i.e.,1）adjusting economic structure and accelerating the pace of economic restructuring to an energy-saving and intensive one;2）utilizing resources and tools such as economy,law,administration,and media,and strongly promoting the energy saving six high-energy heavy chemical industries;3）cont

关 键 词：能源消费 碳排放 测度 驱动因子 预测 安徽省 

分 类 号：X24[环境科学与工程—环境科学]