中国“一带一路”节点城市CO_2排放特征分析
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摘要
"一带一路"节点城市的CO_2排放特征分析是绿色"一带一路"建设的关键和重要支撑。本文以我国"一带一路"沿线37个节点城市作为研究对象,基于国际上较为成熟和应用广泛的城市CO_2排放核算方法,编制了节点城市在2005、2012、2015三年的CO_2排放清单,包含工业能源排放、工业过程排放、农业排放、服务业排放、城镇生活排放、农村生活排放、交通排放7个部门的直接排放和外调电力引起的间接排放。本研究分别从时间和空间维度,从CO_2排放总量及结构、排放强度、空间聚类三个方面,对37个节点城市的CO_2排放特征进行了系统分析。结果表明,中国"一带一路"节点城市CO_2排放在数量上呈现出较大的差异性,排放前5的城市几乎比排放后5的城市的CO_2排放量高出两个数量级。2005—2015年间,"一带一路"节点城市CO_2直接排放总量以年均4. 71%的增长率快速增加,以西北地区节点城市增长最快,以服务业增幅最大。而在空间上始终保持沿海、内陆、东北、西北、西南节点城市的CO_2直接排放量由大到小的顺序不变,其中沿海地区节点城市占到45. 31%。工业能源消耗是"一带一路"节点城市CO_2直接排放的主要来源,占比在71%～78%之间。我国"一带一路"节点城市的人均CO_2排放及单位GDP的CO_2排放,均低于节点城市所在区域的平均水平。"一带一路"倡议实施以来,西南和内陆地区节点城市单位GDP的CO_2排放水平逐渐提升,2015年呈现出内陆-西南-沿海-东北-西北节点城市的单位GDP的CO_2排放水平逐渐递增趋势。在人均CO_2排放和人均GDP二维空间上的城市聚类结果表明,近1/2节点城市处于"低排放、低经济"组,以西南地区节点城市为典型; 1/3节点城市处于"低排放、高经济"组,以沿海地区节点城市为典型,是比较理想的城市发展模式;仅3个西北地区节点城市位于"高排放、低经济"组;"高排放、高经济"组仅有舟山、宁波、呼和浩特3个节点城市。本研究结果为"一带一路"各节点城市找出各自的低碳发展路径和模式,因地制宜地提出相关的低碳政策建议提供了依据和支撑。
Systematic characteristic analysis for carbon emissions in node cities is of great importance the implement tation of green‘Belt and Road Initiative'development strategy. In this paper,37 node cities along ‘Belt and Road'in China were selected as research objects. For which,the urban carbon emission inventory of those node cities in the year 2005,2012 and 2015,based on the international urban carbon accounting scpes and method. It provided emission data from 7 sectors including industrial energy,industrial process,agriculture,service,urban household,rural household,and transportation,and indirect emissions caused by( purchased)electricity systematic characteristic analysis of carbon emissions 37 node cities had been conducted in this study from the CO_2 emissions and structure,emission intensity and spatial clustering aspeets. Results revealed that large discrepancies existed between cities in terms of both CO_2 emission quantity and spatial pattern. The emissions of top 5 cities were substantially higher than those of the bottom 5cities( almost by two orders of magnitude). Between 2005 and 2015,the total direct CO_2 emissions of all the ‘Belt and Road Initiative'node cities increased rapidly with an average annual growth rate of 4. 71%,with the fastest growth in the northwestern area and the largest increase in the service industry. For spatial distribution,the direct CO_2 emissions were always maintain the same order from large to small in the year 2005,2012 and 2015: coastal,inland,northeast,northwest,and southwest. In which,direct carbon emissions from coastal note cities accounted for 45. 31%. Industrial energy consumption was the main source of direct CO_2 emissions in the node cities,accounting for 71% ～ 78%. The per capita CO_2 emissions and the CO_2 emissions per unit of GDP in node cities were both lower than the average level of the area where the node cities were located. Since the ‘Belt and Road Initiative ' was implemented,the CO_2 emission levels per unit of GDP in the cities of the southwest and inland regions had gradually increased. In2015,the CO_2 emission levels per unit of GDP showed an increasing trend in the order: inland,southwest,coastal to northeast and northwest. The node cities could be categorized into groups based on both CO_2 emissions per capita and GDP per capita. Nearly half of the node cities were in the‘low emission,low economy'group,which was typical of the node cities in the southwest area. In ‘lowemission,high-economy'group,which was identified as an ideal urban development model,1/3 of the node cities were included with coastal cities as typical representative. Only three northwestern node cities belonged to the ‘high-emission,low-economy'group.There were only three nodes in ‘high-emission,high-economy'group,Zhoushan,Ningbo and Hohhot. The results of this study provided the basis and support for each of the‘Belt and Road Initiative'node cities to find their own low-carbon development paths,and made it possible for node cities to propose low-carbon policy recommendations according to local conditions.
Systematic characteristic analysis for carbon emissions in node cities is of great importance the implement tation of green‘Belt and Road Initiative'development strategy. In this paper,37 node cities along ‘Belt and Road'in China were selected as research objects. For which,the urban carbon emission inventory of those node cities in the year 2005,2012 and 2015,based on the international urban carbon accounting scpes and method. It provided emission data from 7 sectors including industrial energy,industrial process,agriculture,service,urban household,rural household,and transportation,and indirect emissions caused by( purchased)electricity systematic characteristic analysis of carbon emissions 37 node cities had been conducted in this study from the CO_2 emissions and structure,emission intensity and spatial clustering aspeets. Results revealed that large discrepancies existed between cities in terms of both CO_2 emission quantity and spatial pattern. The emissions of top 5 cities were substantially higher than those of the bottom 5cities( almost by two orders of magnitude). Between 2005 and 2015,the total direct CO_2 emissions of all the ‘Belt and Road Initiative'node cities increased rapidly with an average annual growth rate of 4. 71%,with the fastest growth in the northwestern area and the largest increase in the service industry. For spatial distribution,the direct CO_2 emissions were always maintain the same order from large to small in the year 2005,2012 and 2015: coastal,inland,northeast,northwest,and southwest. In which,direct carbon emissions from coastal note cities accounted for 45. 31%. Industrial energy consumption was the main source of direct CO_2 emissions in the node cities,accounting for 71% ～ 78%. The per capita CO_2 emissions and the CO_2 emissions per unit of GDP in node cities were both lower than the average level of the area where the node cities were located. Since the ‘Belt and Road Initiative ' was implemented,the CO_2 emission levels per unit of GDP in the cities of the southwest and inland regions had gradually increased. In2015,the CO_2 emission levels per unit of GDP showed an increasing trend in the order: inland,southwest,coastal to northeast and northwest. The node cities could be categorized into groups based on both CO_2 emissions per capita and GDP per capita. Nearly half of the node cities were in the‘low emission,low economy'group,which was typical of the node cities in the southwest area. In ‘lowemission,high-economy'group,which was identified as an ideal urban development model,1/3 of the node cities were included with coastal cities as typical representative. Only three northwestern node cities belonged to the ‘high-emission,low-economy'group.There were only three nodes in ‘high-emission,high-economy'group,Zhoushan,Ningbo and Hohhot. The results of this study provided the basis and support for each of the‘Belt and Road Initiative'node cities to find their own low-carbon development paths,and made it possible for node cities to propose low-carbon policy recommendations according to local conditions.
引文
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[17]CAI B, WANG J, HE J, et al. Evaluating CO2, emission performance in China’s cement industry:an enterprise perspective[J]. Applied energy,2016,166:191-200.
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[20]MENG FX,LIU G Y,HU Y C,et al. Urban carbon flow and structure analysis in a multi-scales economy[J]. Energy policy,2018,121:553-564.
[2]祁悦,樊星,杨晋希,等.“一带一路”沿线国家开展国际气候合作的展望及建议[J].中国经贸导刊(理论版),2017(17):40-43.
[3]赵春明.“一带一路”战略与我国绿色产业发展[J].学海,2016(1):137-142.
[4]傅京燕,司秀梅.“一带一路”沿线国家碳排放驱动因素、减排贡献与潜力[J].热带地理,2017,37(1):1-9.
[5]李清如.中日对“一带一路”沿线国家贸易隐含碳的测算及影响因素分析[J].现代日本经济,2017,214:69-84.
[6]郭兆晖,马玉琪,范超.“一带一路”沿线区域绿色发展水平评价[J].福建论坛(人文社会科学版),2017(7):25-31.
[7]李小平,王洋.“一带一路”沿线主要国家碳生产率收敛性及其影响因素分析[J].武汉大学学报(哲学社会科学版),2017,70(3):58-76.
[8]雷原,张武林,曲亮.“一带一路”战略下中国经济增长与碳减排协同研究[J].河海大学学报(哲学社会科学版),2016,18(1):23-29.
[9]CAI B F,LIANG S,ZHOU J,et al. China high resolution emission database(CHRED)with point emission sources,gridded emission data, and supplementary socioeconomic data[J]. Resources,conservation and recycling,2018,129:232-239.
[10]UNEP,UN-HABITAT,Bank the World. International standard for determining greenhouse gas emissions for cities[R]. 2010.
[11]World Resources Institute(WRI),C40 Cities Climate Leadership Group,ICLEI Local Governments for Sustainability. Global protocol for community-scale greenhouse gas emission inventories:an accounting and reporting standard for cities[R]. 2014.
[12]国家发展和改革委员会应对气候变化司. 2005中国温室气体清单研究[M].北京:中国环境科学出版社,2014.
[13]蔡博峰,刘晓曼,陆军,等. 2005年中国城市CO2排放数据集[J].中国人口·资源与环境,2018,28(4):1-7.
[14]蔡博峰,王金南,杨姝影,等.中国城市CO2排放数据集研究——基于中国高空间分辨率网格数据[J].中国人口·资源与环境,2017,27(2):1-4.
[15]林剑艺,孟凡鑫,崔胜辉,等.城市能源利用碳足迹分析——以厦门市为例[J].生态学报,2012,32(12):3782-3794.
[16]中国城市经济学会中小城市经济发展委员会.中国中小城市发展报告(2010):中小城市绿色发展之路[M].北京:社会科学文献出版社,2010.
[17]CAI B, WANG J, HE J, et al. Evaluating CO2, emission performance in China’s cement industry:an enterprise perspective[J]. Applied energy,2016,166:191-200.
[18]MENG F X,LIU G Y,YANG Z F,et al. Structural analysis of embodied greenhouse gas emissions from key urban materials:a case study of Xiamen City of China[J]. Journal of cleaner production,2017,163:212-223.
[19]MI Z F,MENG J,GUAN D B,et al. Chinese CO2emission flows have reversed since the global financial crisis[J]. Nature communications,2017,8(1):1712.
[20]MENG FX,LIU G Y,HU Y C,et al. Urban carbon flow and structure analysis in a multi-scales economy[J]. Energy policy,2018,121:553-564.