基于配额指标重要性视角的中国碳排放配额再分配

周迪; 王文捷; 陈梓佳

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中国环境科学 ›› 2020, Vol. 40 ›› Issue (12) : 5551-5560.

环境影响评价与管理

基于配额指标重要性视角的中国碳排放配额再分配

周迪, 王文捷, 陈梓佳

作者信息 +

Research on the redistribution of carbon emission quotas in China based on the importance of indicators to carbon emissions

ZHOU Di, WANG Wen-jie, CHEN Zi-jia

Author information +

文章历史 +

摘要

提出用与碳排放“同步变化程度”来衡量配额指标重要性的思想，对中国各省份碳排放配额进行再分配.首先在公平和效率原则基础上选取碳排放的影响因素作为分配指标，其次采用灰色关联分析法分别测算出各地区各指标与碳排放量的同步变动程度，以得到各地区各指标在配额分配中的比重.最后测算出我国29个省区2020~2030年的碳排放配额与排放空间.结果表明，人口基数及经济发展指标对各地碳排放有较强的同步变动关联性，因此应该被赋予更高的权重；配额最多的地区包括广东、北京、江苏、山东、上海，最少的地区则包括宁夏、贵州、青海、吉林、新疆.盈余分析发现，北京地区的碳排放空间有较多盈余；浙江等5个省区已达较饱和状态；山东等4个省区则处于较严重的溢出状态，在未来10年内需承担较重的减排压力.

Abstract

This paper puts forward the idea of using the "synchronous trend of change" in carbon emissions to measure the importance of quota indicators that distributes carbon emission quotas in various provinces of China. Firstly, based on the principles of fairness and efficiency, the influence factors of carbon emissions are selected as allocation indicators. Secondly, the grey correlation method is adopted to calculate the "synchronous trend" of each indicator and carbon emissions in each region, so as to obtain the weight of each indicator in quota allocation. Finally, the carbon emission quota and emission space of 29provinces from 2020 to 2030 are calculated. The results show that indicators such as population and economic are strongly correlated with local carbon emissions. Therefore, they should be attached more importance to. Guangdong, Beijing, Jiangsu, Shandong and Shanghai have the largest quotas, while Ningxia, Guizhou, Qinghai, Jilin and Xinjiang have the fewest ones. According to our analysis, Beijing has surplus carbon emission space; the space for Zhejiang and other four provinces is quite saturated.; and the situation faced by Shandong and other three provinces and regions is more severe because of spillover, where the pressure to reduce emissions will be extremely heavy in the next decade.

导出引用

周迪, 王文捷, 陈梓佳. 基于配额指标重要性视角的中国碳排放配额再分配[J]. 中国环境科学. 2020, 40(12): 5551-5560

ZHOU Di, WANG Wen-jie, CHEN Zi-jia. Research on the redistribution of carbon emission quotas in China based on the importance of indicators to carbon emissions[J]. China Environmental Science. 2020, 40(12): 5551-5560

中图分类号： X196

参考文献

[1] Zhou P, Wang M. Carbon dioxide emissions allocation:A review[J]. Ecological economics, 2016,125:47-59.
[2] Grubb M. The greenhouse effect:negotiating targets[J]. International Affairs, 1990,66(1):67-89.
[3] Janssen M, Rotmans J. Allocation of fossil CO₂ emission rights quantifying cultural perspectives[J]. Ecological Economics, 1995, 13(1):65-79.
[4] Hepburn C, Stern N. A new global deal on climate change[J]. Oxford Review of Economic Policy, 2008,24(2):259-279.
[5] Höhne N, Blok K. Calculating historical contributions to climate change-discussing the ‘Brazilian Proposal’[J]. Climatic change, 2005, 71(1/2):141-173.
[6] 丁仲礼,段晓男,葛全胜,等.2050年大气CO₂浓度控制:各国排放权计算[J]. 中国科学(D辑:地球科学), 2009,39(8):1009-1027. Ding Z L, Duan X N, Ge Q S, et al. Control of atmospheric CO₂ concentrations by 2050:A calculation on the emission rights of different countries[J]. Science in China Series D:Earth Sciences, 2009,39(8):1009-1027.
[7] 李钢,廖建辉.基于碳资本存量的碳排放权分配方案[J]. 中国社会科学, 2015,(7):66-81. Li G, Liao J H. A scheme for allocating carbon emission permits on the basis of carbon capital stocks[J]. Social Sciences in China, 2015,(7):66-81.
[8] 王慧慧,刘恒辰,何霄嘉,等.基于代际公平的碳排放权分配研究[J]. 中国环境科学, 2016,36(6):1895-1904. Wang H H, Liu H C, He X J, et al. Allocation of carbon emissions right based on the intergenerational equity[J]. China Environmental Science, 2016,36(6):1895-1904.
[9] 方恺,张琦峰,叶瑞克,等.巴黎协定生效下的中国省际碳排放权分配研究[J]. 环境科学学报, 2018,38(3):1224-1234. Fang W F, Zhang W F, Ye R K, et al. Allocating China's carbon emission allowance to the provincial quotas in the context of the Paris Agreement[J]. Journal of Environmental Science, 2018,38(3):1224-1234.
[10] Kong Y, Zhao T, Yuan R, et al. Allocation of carbon emission quotas in Chinese provinces based on equality and efficiency principles[J]. Journal of Cleaner Production, 2019,211:222-232.
[11] Chiu Y H, Lin J C, Su W N, et al. An efficiency evaluation of the EU's allocation of carbon emission allowances[J]. Energy Sources, Part B:Economics, Planning, and Policy, 2015,10(2):192-200.
[12] An Q, Wen Y, Xiong B, et al. Allocation of carbon dioxide emission permits with the minimum cost for Chinese provinces in big data environment[J]. Journal of Cleaner Production, 2017,142:886-893.
[13] Cai W, Ye P. A more scientific allocation scheme of carbon dioxide emissions allowances:The case from China[J]. Journal of Cleaner Production, 2019,215:903-912.
[14] Ma C Q, Ren Y S, Zhang Y J, et al. The allocation of carbon emission quotas to five major power generation corporations in China[J]. Journal of Cleaner Production, 2018,189:1-12.
[15] 王勇,程瑜,杨光春,等.2020和2030年碳强度目标约束下中国碳排放权的省区分解[J]. 中国环境科学, 2018,38(8):3180-3188. Wang Y, Cheng Y, Yang G C, et al. Provincial decomposition of China's carbon emission rights under the constraint of 2020 and 2030 carbon intensity targets[J]. China Environmental Science, 2018,38(8):3180-3188.
[16] Qin Q, Lu Y, Li X, et al. A multi-criteria decision analysis model for carbon emission quota allocation in China's east coastal areas:efficiency and equity[J]. Journal of Cleaner Production, 2017,168:410-419.
[17] 王文举,陈真玲.中国省级区域初始配额分配方案研究——基于责任与目标、公平与效率的视角[J]. 管理世界, 2019,35(3):81-98. Wang W J, Chen Z L. Study on the initial carbon quota allocation scheme in China's provincial areas:a perspective based on responsibility and objectives, equity and efficiency[J]. Management World, 2019,35(3):81-98.
[18] 陈建宏,王文哲,熊汉富.湖南省CO₂排放因素的灰色关联分析[J]. 地域研究与开发, 2010,29(4):131-134. Chen J H, Wang W Z, Xiong H F. Gray relational analysis on factors of CO₂ emission in Hunan Province[J]. Areal Research and Development, 2010,29(4):131-134.
[19] 田立新,封录.实证分析二氧化碳排放量主要影响因素[J]. 北京理工大学学报(社会科学版), 2013,15(2):23-27,59. Tian L X, Feng L. An empirical analysis of the main factors influencing carbon dioxide emissions[J]. Journal of Beijing Institute of Technology (Social Sciences Edition), 2013,15(2):23-27,59.
[20] Fang K, Zhang Q, Long Y, et al. How can China achieve its intended nationally determined contributions by 2030? A multi-criteria allocation of China's carbon emission allowance[J]. Applied energy, 2019,241:380-389.
[21] 杜立民.我国二氧化碳排放的影响因素:基于省级面板数据的研究[J]. 南方经济, 2010,(11):20-33. Du L M. Impact factors of China's carbon dioxide emissions:provincial panel data analysis[J]. South China Journal of Economics, 2010,(11):20-33.
[22] 中华人民共和国国家统计局.中国统计年鉴[M]. 北京:中国统计出版社, 2007-2017. National Bureau of Statistics of the People's Republic of China. China statistical yearbook[M]. Beijing:China Statistics Press, 2007-2017.
[23] 中国国家统计局能源统计司.中国能源统计年鉴[M]. 中国统计出版社, 2007-2017. Department of Energy Statistics of the National Bureau of Statistics of the People's Republic of China. China Energy statistical yearbook[M]. Beijing:China Statistics Press, 2007-2017.
[24] 深圳国泰安教育技术股份有限公司.CSMAR区域经济数据库[Z]. (2019-08-12)[2019-08-26]. http://cndata1.csmar.com/#/datacenter/singletable/search?databaseId=18. Guotaian Shenzhen Education Technology Limited by Share Ltd. CSMAR Regional Economic Database[Z]. (2019-08-12)[2019-08-26]. http://cndata1.csmar.com/#/datacenter/singletable/search?databaseId=18.
[25] Tone K. Dealing with Undesirable Outputs in DEA:A slacks based measure (SBM) approach[R]. GRIPS Research Report Seires I, 2003-0005.
[26] 周迪,郑楚鹏,华诗润,等.公平与效率协调视角下的中国碳减排潜力与路径[J]. 自然资源学报, 2019,34(1):80-91. Zhou D, Zheng C P, Hua S R, et al. The potentialities and paths of China's carbon emission reduction based on the coordination of fairness and efficiency[J]. Journal of Natural Resources, 2019,34(1):80-91.
[27] 单豪杰.中国资本存量K的再估算:1952~2006年[J]. 数量经济技术经济研究, 2008,25(10):17-31. Shan H J. Reestimating the capital stock of China:1952~2006[J]. The Journal of Quantitative & Technical Economics, 2008,25(10):17-31.
[28] 深圳国泰安教育技术股份有限公司.CSMAR区域经济数据库[Z]. (2019-08-12)[2019-08-26].http://cndata1.csmar.com/#/datacenter/singletable/search?databaseId=20&tbid=1182&field=. Guotaian Shenzhen Education Technology Limited by Share Ltd. CSMAR regional economic database[Z]. (2019-08-12)[2019-08-26]. http://cndata1.csmar.com/#/datacenter/singletable/search? databaseId=20&tbid=1182&field=.
[29] 柴建,杜孟凡,周晓阳,等.中国省际差异化能源转型背景下的CO₂排放预测[J]. 系统工程理论与实践, 2019,39(8):2005-2018. Chai J, Du M F, Zhou X Y, et al. The prediction of CO₂ emission in the background of China's provincial differentiated energy transformation[J]. Systems Engineering-Theory & Practice, 2019,39(8):2005-2018.
[30] 新华社.中华人民共和国国民经济和社会发展第十三个五年规划[EB/OL]. (2016-03-17)[2018-05-28]. http://www.xinhuanet.com/politics/2016lh/2016-03/17/c_1118366322.htm. Xinhua News Agency. Outline of the 13th Five-Year Plan for national economic and social development of the People's Republic of China[EB/OL]. (2016-03-17)[2018-05-28]. http://www.xinhuanet.com/politics/2016lh/2016-03/17/c_1118366322.htm.