中国居民能源消费碳排放现状分析及预测研究
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摘要
当前,居民能源需求不断增加,生活部门已经成为我国第二大能耗部门,随着居民生活条件逐步改善,居民能源消费碳排放还将持续增长。文章对1997—2015年中国居民能源消费碳排放现状进行分析,并基于ARIMA模型对2016—2025年居民能源消费碳排放进行预测研究,结果表明:1997—2015年,中国居民能源消费碳排放整体呈上升趋势,城市碳排放增速和占比于2005年超过农村;城市煤品碳排放波动下降,油品碳排放比2005年增速加快,到2015年与煤炭碳排放相差0.073 5亿吨。农村居民煤品碳排放仍然较高,油品和气品碳排放增幅远低于城市;到2025年,居民能源消费碳排放达到7.87亿吨,年均增长率7.13%;煤品碳排放持续下降,但减速较缓,油品碳排放自2016年起超过煤炭呈现快速上升趋势。
Recently,the energy demand of residents is increasing,and life department has become the second largest energy consumption department.The improvement of living standards will inevitably promote the growth of energy and carbon emissions of residents.In this paper,the current situation of energy consumption carbon emission in Chinese household is calculated using China energy statistical yearbook from 1997 to 2015.And then,the energy consumption carbon emissions of residents in 2016-2025 are predicted by the autoregressive integrated moving average model.The results suggest that overall energy carbon emissions are on the rise from 1997 to 2015,and after 2005,the growth rate and proportion of urban emissions are higher than rural areas;The coal carbon emission of urban illustrates a fluctuating decline trend;Oil carbon emissions increased rapidly since 2005,and compared with coal carbon emissions by 7.35 million tons at 2015;the coal carbon emissions from rural residents are still high,and the increased amplification of oil and natural gas carbon emissions are awfully lower than the urban;The results of the prediction indicate that the energy carbon emissions of residents will reach 787 million tons,and the percentage of average annual growth rate is 7.13% by 2025.The coal carbon emissions continue to decline with a slower rate,since 2016,oil carbon emissions have surpassed the coal which reveals a trend of rapid increase.
Recently,the energy demand of residents is increasing,and life department has become the second largest energy consumption department.The improvement of living standards will inevitably promote the growth of energy and carbon emissions of residents.In this paper,the current situation of energy consumption carbon emission in Chinese household is calculated using China energy statistical yearbook from 1997 to 2015.And then,the energy consumption carbon emissions of residents in 2016-2025 are predicted by the autoregressive integrated moving average model.The results suggest that overall energy carbon emissions are on the rise from 1997 to 2015,and after 2005,the growth rate and proportion of urban emissions are higher than rural areas;The coal carbon emission of urban illustrates a fluctuating decline trend;Oil carbon emissions increased rapidly since 2005,and compared with coal carbon emissions by 7.35 million tons at 2015;the coal carbon emissions from rural residents are still high,and the increased amplification of oil and natural gas carbon emissions are awfully lower than the urban;The results of the prediction indicate that the energy carbon emissions of residents will reach 787 million tons,and the percentage of average annual growth rate is 7.13% by 2025.The coal carbon emissions continue to decline with a slower rate,since 2016,oil carbon emissions have surpassed the coal which reveals a trend of rapid increase.
引文
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[17]孙涵,周丽娜,郭海湘.中国城镇居民生活完全能源消费的测算及趋势分析[J].中国能源,2014(4):40-44.
[18]张德政,王磊,赵玉平.汽车“油改气”市场需求分析[J].科技创新导报,2015(7):14.
[2]王文超.中国省区能源消费与二氧化碳排放量驱动因素分析及预测研究[D].大连:大连理工大学,2013.
[3]汪臻.中国居民消费碳排放量的测算及影响因素研究[D].合肥:中国科学技术大学,2012.
[4]Dietz T,Gardner G T,Gilligan J,et al.Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions[J].Proceedings of the National Academy of Sciences,2009,106(44):18452-18456.
[5]Bin S,Dowlatabadi H.Consumer lifestyle approach to USenergy use and the related CO2 emissions[J].Energy Policy,2005,33(2):197-208.
[6]Liu L C,Wu G,Wang J N,et al.China's carbon emissions from urban and rural households during 1992-2007[J].Journal of Cleaner Production,2011,19(15):1754-1762.
[7]Wang Y,Shi M J.CO2 emission induced by household consumption in China[J].Chinese Journal of Population Resources and Environment,2009,7(3):11-19.
[8]Weber C,Perrels A.Modelling lifestyle effects on energy demand and related emissions[J].Energy Policy,2000,28(8):549-566.
[9]邓荣荣.惯性发展情景下湖南省能否实现2020年减排目标--基于GM(1,1)模型预测[J].资源开发与市场,2017(7):802-806.
[10]常亮.基于时间序列分析的ARIMA模型分析及预测[J].计算机时代,2011(2):8-10.
[11]肖枝洪,王明浩.中国碳排放量的组合模型及预测[J].重庆工商大学学报(自然科学版),2016(1):9-15.
[12]许丽勤.居民直接生活碳排放量及其影响因素分析[D].昆明:云南财经大学,2015.
[13]Box G E P,Jenkins G M,Reinsel G C.时间序列分析:预测与控制[M].北京:中国统计出版社,2011.
[14]李桢业,虞晓芬.“能源危机”对浙江经济发展和居民福利影响的投入产出模型分析[J].浙江工业大学学报(社会科学版),2006(2):27-32.
[15]黄小丽.我国城镇居民直接生活能源消费碳排放量空间差异及影响因素研究[D].杭州:杭州电子科技大学,2013.
[16]李振宇,卢红,任文坡,等.我国未来石油消费发展趋势分析[J].化工进展,2016(6):1739-1747.
[17]孙涵,周丽娜,郭海湘.中国城镇居民生活完全能源消费的测算及趋势分析[J].中国能源,2014(4):40-44.
[18]张德政,王磊,赵玉平.汽车“油改气”市场需求分析[J].科技创新导报,2015(7):14.
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