[1]袁长伟,彭琛.城市公交碳排放效率评价及驱动因素分析[J].长安大学学报(自然科学版),2024,44(4):139-148.[doi:10.19721/j.cnki.1671-8879.2024.04.013]
　YUAN Chang-wei,PENG Chen.Carbon emission efficiency and driving factors analysis of urban bus transportation[J].Journal of Chang’an University (Natural Science Edition),2024,44(4):139-148.[doi:10.19721/j.cnki.1671-8879.2024.04.013]
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城市公交碳排放效率评价及驱动因素分析()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第44卷
期数:
2024年4期
页码:
139-148
栏目:
交通工程
出版日期:
2024-07-10

文章信息/Info

Title:
Carbon emission efficiency and driving factors analysis of urban bus transportation
文章编号:
1671-8879(2024)04-0139-10
作者:
袁长伟; 彭琛
(长安大学 运输工程学院,陕西 西安 710064)
Author(s):
YUAN Chang-wei;  PENG Chen
(College of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China)
关键词:
交通工程;  碳排放效率;  super-SBM模型;  城市公交;  驱动因素
Keywords:
traffic engineering;  carbon emission efficiency;  super-SBM model;  urban bus transport;  driving factor
分类号:
U491.1
DOI:
10.19721/j.cnki.1671-8879.2024.04.013
文献标志码:
A
摘要:
近年来,交通碳排已成为城市发展过程中的重要碳排放源之一,为促进城市公交低碳高效发展,对城市公交二氧化碳排放效率及其驱动因素进行量化分析。以陕西省城市公交系统为例,利用2017～2021年公交能源消耗数据,考虑电网碳排放因子的时间变化特性,采用“自上而下”法测算出公交二氧化碳排放量,选取公交标准运营车辆数、运营线路总长度、能源消耗总量作为投入变量,客运量与碳排放量作为产出变量,建立基于松驰变量的超效率测度模型(super-efficiency slack-based measurement, super-SBM)分析城市公交碳排放效率。此外,运用对数平均迪氏指数法(logarithmic mean Divisia index, LMDI)分析各驱动因素对公交碳排放量的影响程度。并根据研究结果为陕西省公交行业提出了节能减排政策建议。结果表明:陕西省城市公交碳排放效率均值为0.65,还有较大的投入和产出空间,其中,延安、西安和铜川碳排放效率较高,渭南、汉中、安康碳排放效率靠后,陕西省各地区间公交碳排放效率差异明显,呈陕北地区>陕西省均值>关中地区>陕南地区的格局。研究期内,陕西省城市公交碳排放量总体呈下降趋势,运输强度因素对公交碳排放影响效应最为显著,且体现为抑制作用,其他各影响因素对公交碳排放起促进作用,效应值由强到弱依次为能源结构强度、经济发展、能源消耗和人口规模因素,其影响效应值分别为10.48×104、9.89×104、4.35×104、3.42×104 t。
Abstract:
In recent years, transport carbon emissions have become one of the important sources of carbon emissions in the process of urban development. In order to promote the development of urban public transport in a low-carbon and efficient manner, the efficiency of carbon dioxide emissions from urban public transport and its driving factors was quantitatively analyzed. The urban public transport system in Shaanxi Province was taken as an example, using the data of public transport energy consumption from 2017 to 2021, and the temporal and spatial characteristics of the carbon emission factor of the power grid was considered, the top-down method was used to measure the carbon dioxide emission of public transport. The number of standard operating vehicles, total length of operating routes, and total energy consumption of public transport were selected as input variables, and passenger traffic and carbon emissions as output variables, and the super-SBM model was established to analyse the carbon emission efficiency of urban public transport. In addition, the LMDI was used to analyse the influence of each driving factor on the carbon emissions of public transport.Based on the results of the study, energy-saving and emission reduction policy recommendations were proposed for the public transport industry in Shaanxi Province. The results show that the average value of urban public transport carbon emission efficiency in Shaanxi Province is 0.65, and there is still a large input and output space, of which, Yan'an, Xi'an and Tongchuan have higher carbon emission efficiency, and Weinan, Hanzhong and Ankang have backward carbon emission efficiency, and the differences in public transport carbon emission efficiency among different regions in Shaanxi Province are obvious, the northern region is larger than the northern region, and the Guanzhong region is larger than the southern region of Shaanxi Province. In the study period from 2017 to 2021, urban public transport carbon emissions in Shaanxi Province in general showed a downward trend, the transport intensity factor has the most significant effect on the impact of public transport carbon emissions, and embodied in the inhibition, the other influencing factors on the public transport carbon emissions to promote the role of the effect of the value of the strongest to the weakest in order of intensity of the energy structure, economic development, energy consumption and the population size factor, the effect of the value of the impact of the effect of the value of the following, respectively 104 800, 98 900, 43 500 and 34 200 t.4 tabs, 2 figs, 26 refs.

参考文献/References:

[1] 金 昱.国际大城市交通碳排放特征及减碳策略比较研究[J].国际城市规划,2022,37(2):25-33.
JIN Yu.Comparative study on characteristic and planning strategies of transportation carbon emissions in global megacities[J].Urban Planning International,2022,37(2):25-33.
[2]KAYA Y,YOKOBORI K.Global environment,energy and economic development[R].New York:United Nations University,1993.
[3]卢建锋,傅 惠,王小霞.区域交通运输业碳排放效率影响因素研究[J].交通运输系统工程与信息,2016,16(2):25-30.
LU Jian-feng,FU Hui,WANG Xiao-xia.Research on the impact of regional transportation emissions efficiency factors[J].Journal of Transportation Systems Engineering and Information Technology,2016,16(2):25-30.
[4]SOW O,OUKIL A,NDIAYE B M,et al.Efficiency analysis of public transportation subunits using DEA and bootstrap approaches-Dakar Dem Dikk case study[J].Journal of Mathematics Research,2016,8(6):114-127.
[5]USTADI M N,SHOPI N A M.A study towards the efficiency of public transportation hub characteristics:A case study of northern region,Peninsular Malaysia[J].Procedia Economics and Finance,2016,35:612-621.
[6]李 琼,朱士卜,朱文英.城市公交运营效率评价研究——基于三阶段DEA方法的分析[J].价格理论与实践,2022(6):152-155,195.
LI Qiong,ZHU Shi-bu,ZHU Wen-ying.Research on evaluation of urban public transport operation efficiency-Base on the analysis of the three stage DEA method[J].Price:Theory & Practice,2022(6):152-155,195.
[7]TONE K.A slacks-based measure of efficiency in data development analysis[J].European Journal of Operational Research,2001,130(3):498-509.
[8]TONE K.A slacks-based measure of super-efficiency in data envelopment analysis[J].European Journal of Operational Research,2002,143(1):32-41.
[9]吴 茜,刘菊梅,叶士琳.福建省城市公交效率测度及时空演化特征——基于超效率SBM模型和Malmquist指数法[J].福建师范大学学报(自然科学版),2022,38(2):71-80.
WU Qian,LIU Ju-mei,YE Shi-lin.Measurement and temporal and spatial evolution characteristics of urban public transport efficiency in Fujian Province:Based on super efficiency SBM model and Malmquist index method[J].Journal of Fujian Normal University(Natural Science Edition),2022,38(2):71-80.
[10]章 玉.考虑非期望产出的大中城市公交营运效率评价[J].交通运输研究,2016,2(6):32-37.
ZHANG Yu.Operation efficiency evaluation for public transport of large and medium-sized cities based on undesirable output[J].Transportation Research,2016,2(6):32-37.
[11]陈 丹,于 慧,汤 程,等.城市公共客运交通碳排放及其大气环境影响的实证研究[J].交通运输系统工程与信息,2023,23(4):1-10.
CHEN Dan,YU Hui,TANG Cheng,et al.Empirical study on carbon dioxide emissions and atmospheric environment impact of urban public passenger transportation[J].Transport Systems Engineering and Information,2023,23(4):1-10.
[12]王 超,武丽敏.基于“双碳”视角的丝绸之路经济带交通碳减排驱动因素分析[J].干旱区资源与环境,2024,38(2):9-19.
WANG Chao,WU Li-min.Factors driving the carbon emission reduction in transport along the Silk Road Economic Belt:An analysis from the perspective of “double carbon”[J].Journal of Arid Land Resources and Environment,2024,38(2):9-19.
[13]王智琦,李建国,彭彬彬,等.西部地区交通碳排放的驱动因素与脱钩效应分析[J].环境工程,2023,41(10):213-222.
WANG Zhi-qi,LI Jian-guo,PENG Bin-bin,et al.Driving factors and decoupling effects analysis of transportation carbon emissions in western China[J].Environmental Engineering,2023,41(10):213-222.
[14]刘俊豪,刘榆欣,黄 蕾.中国华东地区旅游交通碳排放测度与驱动因素分析[J].环境科学研究,2024,37(3):626-636.
LIU Jun-hao,LIU Yu-xin,HUANG Lei.Measurement and driving factor analysis of carbon emissions from tourism transportation in East China[J].Research of Environmental Sciences,2024,37(3):626-636.
[15]张国兴,苏钊贤.黄河流域交通运输碳排放的影响因素分解与情景预测[J].管理评论,2020,32(12):283-294.
ZHANG Guo-xing,SU Zhao-xian.Analysis of influencing factors and scenario prediction of transportation carbon emissions in the Yellow River Basin[J].Management Review,2020,32(12):283-294.
[16]杨绍华,张宇泉,耿 涌.基于LMDI的长江经济带交通碳排放变化分析[J].中国环境科学,2022,42(10):4817-4826.
YANG Shao-hua,ZHANG Yu-quan,GENG Yong.An LMDI-based investigation of the changes in carbon emissions of the transportation sector in the Yangtze River economic[J].China Environmental Science,2022,42(10):4817-4826.
[17]周 琪,梁 肖,黄俊生,等.城市轨道交通碳排放效率与影响因素研究[J].交通运输系统工程与信息,2023,23(1):30-38,85.
ZHOU Qi,LIANG Xiao,HUANG Jun-sheng,et al.Carbon emission efficiency and influencing factors analysis of urban rail transit[J].Journal of Transportation Systems Engineering and Information Technology,2023,23(1):30-38,85.
[18]戈艳艳,王姗姗.考虑碳排放的港口全要素生产率及影响因素分析[J].交通运输系统工程与信息,2021,21(2):22-29.
GAO Yan-yan,WANG Shan-shan.Total factor productivity and influencing factors analysis for ports considering carbon emissions[J].Journal of Transportation Systems Engineering and Information Technology,2021,21(2):22-29.
[19]郑 琰,贲宇姝,王康得,等.物流企业的碳排放效率评价及驱动因素分析[J].交通运输系统工程与信息,2023,23(2):11-21.
ZHENG Yan,BEN Yu-shu,WANG Kang-de,et al.Carbon emission efficiency evaluation and driving factors analysis of logistics enterprises[J].Journal of Transportation Systems Engineering and Information Technology,2023,23(2):11-21.
[20]袁振洲,袁晓敬,杨 洋,等.城市轨道交通二氧化碳排放量化及其影响因素分析[J].城市轨道交通研究,2023,26(10):97-102.
YUAN Zhen-zhou,YUAN Xiao-jing,YANG Yang,et al.Quantification of carbon dioxide emissions in urban rail transit and its influencing factor analysis[J].Urban Mass Transit,2023,26(10):97-102.
[21]CHARNES A,COOPER W W,RHODES E.Measuring the efficiency of decision making units[J].European journal of operations research,1978,2(6):429-444.
[22]KAYA Y.Impact of carbon dioxide emission control on GNP growth:Interpretation of proposed scenarios[R].Paris:IPCC Energy and Industry Subgroup,1989.
[23]李学文,徐丽群.中国城市公共交通行业运营效率评价——基于改进的SE-DEA-Gini方法的研究[J].管理现代化,2014(2):90-92.
LI Xue-wen,XU Li-qun.Evaluation of operational efficiency in China's urban public transport industry-A study based on the improved SE-DEA-Gini method[J].Modernization of Management,2014(2):90-92.
[24]李金培,徐丽群,姚 迪.公共交通效率衡量及无效率解析[J].系统管理学报,2020,29(4):684-697.
LI Jin-pei,XU Li-qun,YAO Di.Efficiency measurement and inefficiency analysis of public transportation[J].Journal of Systems & Management,2020,29(4):684-697.
[25]SHARMA M G,DEBNATH R M,OLORUNTOBA R,et al.Benchmarking of rail transport service performance through DEA for Indian railways[J].International Journal of Logistics Management,2016,27(3):629-649.
[26]王白雪,郭 琨.北京市公共交通碳排放效率研究——基于超效率SBM模型和ML指数[J].系统科学与数学,2018,38(4):456-467.
WANG Bai-xue,GUO Kun.The efficient of carbon emissions efficiency of Beijing public transportation system:Based on super-efficiency SBM model using Malmquist-Luenberger index[J].Journal of Systems Science and Mathematical Sciences,2018,38(4):456-467.

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备注/Memo

备注/Memo:
收稿日期:2024-03-01
基金项目:陕西省杰出青年科学基金项目(2021JC-27); 陕西省重点科技创新团队项目(2023-CX-TD-11)
作者简介:袁长伟(1981-),男,湖南邵阳人,教授,博士研究生导师,E-mail:changwei@chd.edu.cn。
更新日期/Last Update: 2024-07-10