京津冀区域公路客运交通碳排放时空特征与调控预测

doi:10.18402/resci.2017.07.13

摘要/Abstract

摘要：

运用机动车燃料消耗的碳排放直接测算方法,对京津冀区域2005-2014年公路客运交通碳排放进行了测算和时空分析;并借助LEAP模型,设定了基准增长、比例控制和总量控制三种调控情景,对区域未来的公路客运交通碳排放进行了预测和调控设想。结果表明：①从时间演变来看,虽然单位乘客碳排放强度大大降低,但区域总体公路客运交通碳排放绝对量却在稳步快速增长,区域碳减排压力持续增加;②从空间分异来看,京津二市碳排放一直处于领先地位,但河北11市碳排放的稳步提升也使河北省碳排放在京津冀区域中的比重大大抬升;③预测发现总量控制情景较比例控制情景有更大碳减排幅度,但两种控制情景的区域碳排放总量至2030年都会保持增长态势,因此区域公路客运交通的调控需要科学设计并加大力度。本研究可为区域交通管治政策制定和碳减排提供参考。

关键词: 公路客运交通, 碳排放, LEAP模型, 情景预测, 京津冀

Abstract:

In the 21st century,China entered an era of highway passenger transport,which is bound by regional energy supply and that strongly impacts carbon emissions. With the rapid increase in the number of private cars,road passenger transport has made a significant contribution to carbon emissions,and future contributions to regional carbon emissions will increase further. This is undoubtedly a huge challenge for China's carbon reduction goals. By using the bottom-up approach for estimating carbon emissions,the Beijing-Tianjin-Hebei region （hereafter,ereafte Jing-Jin-Ji）of highway passenger transport carbon emissions were estimated and analyzed from 2005 to 2014. With the help of a LEAP model,we set three kinds of regulations including benchmark growth,proportional control and total amount of control. The future of regional highway passenger transport carbon emissions is forecasted. We found that from the evolution of time,although per capita carbon emission intensity is greatly reduced,regional overall highway passenger transport carbon emissions grow steadily,and regional carbon reduction pressure increases. From a spatial differentiation perspective,the carbon emissions of the two cities Beijing and Tianjin is leading. The steady rise of carbon emissions in the 11 cities of Hebei also meant that the proportion of carbon emissions in the Jing-Jin-Ji region in Hebei increased. We predict that the total quantity control scenario is a proportional control situation and more carbon emissions,but no matter the regional carbon emission reductions, carbon emissions will keep rising until 2030. The design of highway passenger transport control requires scientific areas and greater effort. These data should be used to improve highway passenger transport policy and regional carbon reduction in China.

Key words: road transport, carbon emissions, LEAP Model, forecast, Beijing-Tianjin-Hebei region

马海涛, 康雷. 京津冀区域公路客运交通碳排放时空特征与调控预测[J]. 资源科学, 2017, 39(7): 1361-1370.

Haitao MA, Lei KANG. Spatial and temporal characteristics and prediction of carbon emissions from road traffic in the Beijing-Tianjin-Hebei Region[J]. Resources Science, 2017, 39(7): 1361-1370.

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参考文献 31

[1]	池熊伟. 中国交通部门碳排放分析[J]. 鄱阳湖学刊,2012,(4):56-62.
	[Chi X W.Carbon pool economists China's transportation sector analysis[J]. Journal of Poyang Lake,2012,(4):56-62.]
[2]	Wang R,Liu W,Xiao L,et al.Path towards achieving of China's 2020 carbon emission reduction target a discussion of low-carbon energy policies at province level[J]. Energy Policy,2011,39(5):2740-2747.
[3]	Shabbir R,Ahmad S S.Monitoring urban transport air pollution and energy demand in Rawalpindi and Islamabad using leap model[J]. Energy,2010,35(5):2323-2332.
[4]	He K,Huo H,Zhan Q,et al.Oil consumption and CO2 emissions in China's road transport:current status,future trends,and policy implications[J]. Energy Policy,2005,33(12):1499-1507.
[5]	李琳娜. 中国客运交通的碳排放地理特征与展望[J]. 地理研究,2016,35(7):1230-1242.
	[Li L N.China's carbon emissions geographical characteristics and prospect of passenger transport[J]. Journal of Geographical Research,2016,35(7):1230-1242.]
[6]	黄晓燕,刘夏琼,曹小曙,等. 广州市三个圈层社区居民通勤碳排放特征-以都府小区、南雅苑小区和丽江花园为例[J]. 地理研究,2015,34(4):751-761.
	[Huang X Y,Liu X Q,Cao X S,et al.Guangzhou three spheres of community residents commuting carbon features[J]. Journal of Geographical Research,2015,34(4):751-761.]
[7]	徐昔保,陈爽,杨桂山. 长三角地区城市居民出行交通碳排放特征与影响机理[J]. 长江流域资源与环境,2014,23(8):1064-1071.
	[Xu X B,Chen S,Yang G S.Yangtze river delta urban residents travel transport carbon emissions characteristics and effect mechanism[J]. Journal of Resources and Environment in Yangtze River Basin,2014,23(8):1064-1071.]
[8]	宁晓菊,张金萍,秦耀辰,等. 郑州城市居民交通碳排放的时空特征[J]. 资源科学,2014,36(5):1021-1028.
	[Ning X J,Zhang J P,Qin Y C,et al.Zhengzhou urban traffic carbon emission characteristics of space and time[J]. Resources Science,2014,36(5):1021-1028.]
[9]	邓小乐,孙慧. 基于STIRPAT模型的西北五省区碳排放峰值预测研究[J]. 生态经济,2016,32(9):36-41.
	[Deng X L,Sun H.Based on the northwest five provinces of carbon emissions peak STIRPAT model prediction research[J]. Ecological Economy,2016,32(9):36-41.]
[10]	李志鹏. 基于系统动力学的天津市城市交通能源消耗与碳排放预测[J]. 价值工程,2012,31(7):308-310.
	[Li Z P.Based on system dynamics of Tianjin urban transportation energy con-sumption and carbon emissions prediction[J]. Value Engi-neering,2012,31(7):308-310.]
[11]	杨花,杜斌,吕锋骅,等. 基于IPCC排放清单和LEAP模型的山西省CO2排放研究[J]. 环境污染与防治,2014,36(3):103-109.
	[Yang H,Du B,Lv F H,et al.Based on the IPCC emissions inventory and LEAP model of CO2 emissions of Shanxi Province[J]. Journal of Environmental Pollution and Prevention,2014,36(3):103-109.]
[12]	童抗抗,马克明. 居住-就业距离对交通碳排放的影响[J]. 生态学报,2012,32(10):2975-2984.
	[Tong K K,Ma K M.Living-employment distance on the influence of traffic emissions[J]. Acta Ecologicasinica,2012,32(10):2975-2984.]
[13]	张金萍,秦耀辰,张艳,等. 城市CO2排放结构与低碳水平测度-以京津沪渝为例[J]. 地理科学,2010,30(6):874-879.
	[Zhang J P,Qin Y C,Zhang Y,et al.The urban structure and low carbon level measure CO2 emissions-in the Beijing and Tianjin only,for example[J]. Journal of Geographical Science,2010,30(6):874-879.]
[14]	国家统计局城市社会经济调查司. 中国城市统计年鉴2013[M]. 北京:中国统计出版社,2013.
	[National Bureau of Statistics of China. China City Statistics Yearbook 2013[M]. Beijing:China Statistics Press,2013.]
[15]	海德堡能源与环境研究所. 中国交通:不同交通方式的能源消耗与排放研究报告[R]. 海德堡:海德堡能源与环境研究所,2008.
	[Institute of Energy and Environment. Transport in China:Different Transport Modes Energy Consumption and Emission[R]. Heidelberg:Institute of Energy and Environment,2008.]
[16]	IPCC国家温室气体清单特别工作组. 2006年IPCC国家温室气体清单指南[M]. 神奈川:日本全球环境战略研究所,2006.
	[IPCC National Greenhouse Gas Inventory Task Force. 2006 IPCC Guidelines for National Greenhouse Gas Inventories[M]. Kanagawa:Japan Global Environmental Strategy Institute,2006.]
[17]	冀丰渊. 京津冀协同发展规划纲要[R]. 廊坊:对接京津-解题京津冀一体化与推动区域经济协同发展(对接京津与环首都沿渤海第13次论坛)论文集,2016.
	[Ji F Y.The Integration of Beijing -Tianjin-Hebei Cooperation and the Development of Regional Economy(the 13th Forum of Beijing -Tianjin and Central Capital along the Bohai Sea),2016.]
[18]	北京交通委员会,北京发展和改革委员会. 北京市十二五时期交通发展建设规划[EB/OL].(2012-08-20)[2017-01-21]. .
	[Beijing Transportation Commission, Beijing Develop-ment and Reform Commission. Beijing 12th Five-Year Transpor-tation De-velopment and Construction Planning[EB/OL].(2012-08-20)[2017-01-21]. .]
[19]	北京市人民政府.北京市城市总体规划(2004-2020)[EB/OL]. (2005-04-25)[2017-01-21]. .
	[Beijing Municipal People's Govern-ment. Beijing Urban Master Plan (2004-2020)[EB/OL]. (2005-04-25)[2017-01-21]. .]
[20]	河北省人民政府. 河北省国民经济和社会发展第十三个五年规划纲要[EB/OL]. (2016-08-02)[2017-01-21]. .
	[Hebei Province People's Government. Outline of the 13th Five-Year Plan for the National Economic and Social Development of the Hebei Province [EB/OL]. (2016-08-02)[2017-01-21]. .]
[21]	张秀媛,杨新苗,闫琰. 城市交通能耗和碳排放统计测算方法研究[J]. 中国软科学,2014,(6):142-150.
	[Zhang X Y,Yang X M,Yan Y.Urban transportation energy consumption and carbon emissions statistic method research[J]. China Soft Science,2014,(6):142-150.]
[22]	王会芝. 交通能源消费碳排放情景预测研究-以天津市为例[J]. 干旱区资源与环境,2016,30(7):37-41.
	[Wang H Z.The transportation energy consumption carbon emissions scenario prediction research-in Tianjin,for example[J]. Journal of Re-sources and Environment in Arid Areas,2016,30(7):37-41.]
[23]	柯水发,王亚,陈奕钢,等. 北京市交通运输业碳排放及减排情景分析[J]. 中国人口·资源与环境,2015,25(6):81-88.
	[Ke S F,Wang Y,Chen Y G,et al.The Beijing transport carbon emis-sions and emissions scenario analysis[J]. China Population Resources and Environment,2015,25(6):81-88.]
[24]	马丽,刘立涛. 基于发达国家比较的中国能源消费峰值预测[J]. 地理科学,2016,36(7):980-988.
	[Ma L,Liu L T.Based on the developed country compare peak of China's energy con-sumption prediction[J]. Journal of Geographical Science,2016,36(7):980-988.]
[25]	周健,崔胜辉,林剑艺,等. 基于LEAP模型的厦门交通能耗及大气污染物排放分析[J]. 环境科学与技术,2011,34(11):164-170.
	[Zhou J,Cui S H,Lin J Y,et al.Based on the LEAP model of Xiamen transportation energy consumption and air pollutants emission analysis[J]. Journal of Environmental Science and Technology,2011,34(11):164-170.]
[26]	王长建,张小雷,张虹鸥,等. 基于IO-SDA模型的新疆能源消费碳排放影响机理分析[J]. 地理学报,2016,71(7):1105-1118.
	[Wang C J,Zhang X L,Zhang H O,et al.Based on the IO-SDA model of energy consumption in Xinjiang carbon impact mecha-nism analysis[J]. Journal of Geography,2016,71(7):1105-1118.]
[27]	林晓丹,吕彬,田良,等. 基于LCA的北京市公交车节能及温室气体减排潜力分析[J]. 环境科学学报,2015,35(2):576-584.
	[Lin X D,Lv B,Tian L,et al.Based on LCA of Beijing bus energy saving and greenhouse gas emission reduction potential analysis[J]. Journal of Environmental Science,2015,35(2):576-584.]
[28]	王宇飞,李惠民,齐晔. 交通出行需求对碳排放的影响及贡献[J]. 生态经济,2016,32(9):32-35.
	[Wang Y F,Li H M,Qi Y.The influence of the transportation demand of carbon emissions and contribute[J]. Ecological Economy,2016,32(9):32-35.]
[29]	董洁芳,王强,王兴民,等. 山西省煤炭消费需求影响因素的实证研究[J]. 中国科学院大学学报,2016,33(5):641-650.
	[Dong J F,Wang Q,Wang X M,et al.Shanxi coal:An empirical study of factors influencing consumer demand[J]. Journal of Univer-sity of Chinese Academy of Sciences,2016,33(5):641-650.]
[30]	苏涛永,张建慧,李金良,等. 城市交通碳排放影响因素实证研究-来自京津沪渝面板数据的证据[J]. 工业工程与管理,2011,16(5):134-138.
	[Su T Y,Zhang J H,Li J L,et al.The urban traffic carbon emission factors affecting the empirical research,the evidence from the Beijing,Tianjin,Shanghai,and Chong-qing only panel data[J]. Journal of Industrial Engineering and Management,2011,16(5):134-138.]
[31]	刘建翠. 中国交通运输部门节能潜力和碳排放预测[J]. 资源科学,2011,33(4):640-646.
	[Liu J C.China's transportation and energy saving potential and carbon emissions prediction[J]. Resource Science,2011,33(4):640-646.]

交通工具	年平均行驶里程/km	平均燃料消耗	燃料	碳排放系数/（tCO₂/t）
出租汽车	71 175	15.07km/kg	汽油	2.93
出租汽车		0.07m³/km	天然气	2.16
公共汽车	34 000	3.91km/kg	汽油	2.93
公共汽车		0.15m³/km	天然气	2.16
私人汽车	18 000	15.07km/kg	汽油	2.93
摩托车	10 000	50.23km/kg	汽油	2.93

情景设定	具体内容
基准增长情景	未来没有任何减排措施,机动车总量依旧维持现在的增长水平,私家车、公交车也维持既有增长水平
比例控制情景	私家车、摩托车数量2020年在基准情景基础上减少10%,2025年、2030年分别减少15%、20%;公交车到2020年出行比例达到40%左右,公交车年平均行驶里程到2020年比2010年增加10%,2030年比2010年增加20%。公交车、出租车的新能源车（CNG、电动）2020年达到总量的40%,2030年达到总量的50%
总量控制情景	私家车总量到2020年北京市不超过600万辆,天津市不超过350万辆,河北省不超过1 000万辆,2030年北京市不超过700万辆,天津市不超过500万辆,河北省不超过1 500万辆,公交车和出租车的数量维持原有的增长水平。技术减排,2020年机动车平均汽油消耗在2010年基础上减少5%,2030年减少10%。