Volume 12 Issue 3
May  2022
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LIU Y,ZHANG H.Evaluation of provincial carbon emission efficiency based on partial order set[J].Journal of Environmental Engineering Technology,2022,12(3):937-942 doi: 10.12153/j.issn.1674-991X.20210199
Citation: LIU Y,ZHANG H.Evaluation of provincial carbon emission efficiency based on partial order set[J].Journal of Environmental Engineering Technology,2022,12(3):937-942 doi: 10.12153/j.issn.1674-991X.20210199

Evaluation of provincial carbon emission efficiency based on partial order set

doi: 10.12153/j.issn.1674-991X.20210199
  • Received Date: 2021-05-24
  • Accepted Date: 2021-08-30
  • Available Online: 2022-06-07
  • To address the problematic time weights of panel data in the evaluation of carbon emission efficiency, a partial-order set evaluation model was used to evaluate the carbon emission efficiency of China. In this model, it was not necessary to know the specific weight values of the indicators, but only the weight order was needed. By collecting the panel data of 30 Chinese provinces (autonomous regions and municipalities) from 2000 to 2017, calculating each year′s carbon emission efficiency, and sequencing the weight values in time reverse order, the carbon emission efficiency was evaluated. The results showed that the carbon emission efficiency was the highest in East China, followed by the Central China, and the worst in Northwest. The factors affecting the carbon emission efficiency in each region were different, which required that specific carbon emission policies should be developed according to local conditions. The carbon emission efficiency of each region tended to be aggregated, and the local carbon emission policy would not only affect the carbon emission effect of the region, but also affect the carbon emission of the adjacent areas, so, it was necessary to strengthen the cooperation of carbon emission reduction among all the regions.

     

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  • [1]
    ZHOU P, ANG B W. Linear programming models for measuring economy-wide energy efficiency performance[J]. Energy Policy,2008,36(8):2911-2916. doi: 10.1016/j.enpol.2008.03.041
    [2]
    PAN X F, PAN X Y, LI C Y, et al. Effects of China's environmental policy on carbon emission efficiency[J]. International Journal of Climate Change Strategies and Management,2019,11(3):326-340. doi: 10.1108/IJCCSM-12-2017-0206
    [3]
    ZHOU P, ANG B W, HAN J Y. Total factor carbon emission performance: a Malmquist index analysis[J]. Energy Economics,2010,32(1):194-201. doi: 10.1016/j.eneco.2009.10.003
    [4]
    DONG F, LONG R Y, BIAN Z F, et al. Applying a Ruggiero three-stage super-efficiency DEA model to gauge regional carbon emission efficiency: evidence from China[J]. Natural Hazards,2017,87(3):1453-1468. doi: 10.1007/s11069-017-2826-2
    [5]
    李涛, 傅强.中国省际碳排放效率研究[J]. 统计研究,2011,28(7):62-71. doi: 10.3969/j.issn.1002-4565.2011.07.008

    LI T, FU Q. Study on China's carbon dioxide emissions efficiency[J]. Statistical Research,2011,28(7):62-71. doi: 10.3969/j.issn.1002-4565.2011.07.008
    [6]
    刘亦文, 胡宗义.中国碳排放效率区域差异性研究: 基于三阶段DEA模型和超效率DEA模型的分析[J]. 山西财经大学学报,2015,37(2):23-34.

    LIU Y W, HU Z Y. Research on regional difference about carbon emission efficiency in China: based on three stage DEA model and super efficiency DEA model[J]. Journal of Shanxi University of Finance and Economics,2015,37(2):23-34.
    [7]
    李艳红.山东省碳减排系统仿真及政策优化研究[J]. 环境工程技术学报,2020,10(1):150-159. doi: 10.12153/j.issn.1674-991X.20190063

    LI Y H. System simulation and policy optimization of carbon emission reduction in Shandong Province[J]. Journal of Environmental Engineering Technology,2020,10(1):150-159. doi: 10.12153/j.issn.1674-991X.20190063
    [8]
    孙少勤, 郭琴琴, 邵青.基于超效率DEA模型的中国省际碳排放效率研究[J]. 阅江学刊,2014,6(6):41-51.

    SUN S Q, GUO Q Q, SHAO Q. Study on provincial carbon emission's efficiency in China based on super-efficiency DEA model[J]. Yuejiang Academic Journal,2014,6(6):41-51.
    [9]
    王缃韵.我国省际碳排放效率及其动态特征分析[J]. 现代经济信息,2016(4):17-18.
    [10]
    宋雅静, 万安位, 黄珂婧.基于超效率模型的中国省际碳排放效率研究[J]. 北方经贸,2020(7):30-32.
    [11]
    岳瑞锋, 朱永杰.1990—2007年中国能源碳排放的省域聚类分析[J]. 技术经济,2010,29(3):40-45. doi: 10.3969/j.issn.1002-980X.2010.03.009

    YUE R F, ZHU Y J. Provincial cluster analysis on China's energy carbon emission from 1990 to 2007[J]. Technology Economics,2010,29(3):40-45. doi: 10.3969/j.issn.1002-980X.2010.03.009
    [12]
    马大来, 陈仲常, 王玲.中国省际碳排放效率的空间计量[J]. 中国人口·资源与环境,2015,25(1):67-77. doi: 10.3969/j.issn.1002-2104.2015.01.010

    MA D L, CHEN Z C, WANG L. Spatial econometrics research on inter-provincial carbon emissions efficiency in China[J]. China Population, Resources and Environment,2015,25(1):67-77. doi: 10.3969/j.issn.1002-2104.2015.01.010
    [13]
    王莉, 白彦.中国工业能源效率的空间交互效应识别与分析[J]. 西南民族大学学报(人文社会科学版),2021,42(6):152-161.
    [14]
    李铭泓, 黄羿, 朱伟俊, 等.中国交通运输业碳排放全要素生产率研究: 基于Global Malmquist-Luenberger指数[J]. 科技管理研究,2021,41(9):203-211. doi: 10.3969/j.issn.1000-7695.2021.09.027

    LI M H, HUANG Y, ZHU W J, et al. Research on the carbon emission total factor productivity of the transportation industry in China based on the global Malmquist-Luenberger index[J]. Science and Technology Management Research,2021,41(9):203-211. doi: 10.3969/j.issn.1000-7695.2021.09.027
    [15]
    张德钢.市场分割对碳排放效率的影响研究: 基于固定效应面板随机前沿模型[J]. 软科学,2018,32(9):94-97.

    ZHANG D G. Study on the impact of market segmentation on carbon emission efficiency: based on fixed-effect panel stochastic frontier models[J]. Soft Science,2018,32(9):94-97.
    [16]
    金英君, 刘晓峰, 王义源.政府调控碳排放路径研究: 基于金融效率的视角[J]. 中国软科学,2021(5):135-144. doi: 10.3969/j.issn.1002-9753.2021.05.013

    JIN Y J, LIU X F, WANG Y Y. Government research on the path to regulating carbon emissions: based on a financial efficiency perspective[J]. China Soft Science,2021(5):135-144. doi: 10.3969/j.issn.1002-9753.2021.05.013
    [17]
    岳立柱, 张志杰, 闫艳.蕴含权重的偏序集多准则决策法[J]. 运筹与管理,2018,27(2):26-31.

    YUE L Z, ZHANG Z J, YAN Y. Multi criteria decision making method of poset with weight[J]. Operations Research and Management Science,2018,27(2):26-31.
    [18]
    范懿.一个有关哈斯图的解析方法[J]. 上海第二工业大学学报,2003,20(1):17-22. doi: 10.3969/j.issn.1001-4543.2003.01.003

    FAN Y. An analytic methord about Hasse Chart[J]. Journal of Shanghai Second Polytechnic University,2003,20(1):17-22. doi: 10.3969/j.issn.1001-4543.2003.01.003
    [19]
    黄亮, 王会敏, 岳立柱, 等.基于偏序集的采空区塌陷危险性评价研究[J]. 中国安全生产科学技术,2019,15(4):134-140.

    HUANG L, WANG H M, YUE L Z, et al. Study on risk assessment of goaf collapse based on partial order set[J]. Journal of Safety Science and Technology,2019,15(4):134-140.
    [20]
    李世豪. 基于随机前沿模型的京津冀地区碳排放效率研究[D]. 北京: 华北电力大学(北京), 2020.
    [21]
    LI H Z, GUO S, CUI L Y, et al. Review of renewable energy industry in Beijing: development status, obstacles and proposals[J]. Renewable and Sustainable Energy Reviews,2015,43:711-725. doi: 10.1016/j.rser.2014.11.074
    [22]
    XIONG S Q, MA X M. Regional carbon efficiency in China: a super-SBM model with undesirable outputs[J]. DEStech Transactions on Environment, Energy and Earth Sciences, 2017. doi: 10.12783/dteees/ese2017/14347.
    [23]
    李健, 马晓芳, 苑清敏.区域碳排放效率评价及影响因素分析[J]. 环境科学学报,2019,39(12):4293-4300.

    LI J, MA X F, YUAN Q M. Evaluation and influencing factors' analysis of regional carbon emission efficiency[J]. Acta Scientiae Circumstantiae,2019,39(12):4293-4300.
    [24]
    张翱祥, 邓荣荣.中部六省碳排放效率与产业结构优化的耦合协调度及影响因素分析[J]. 生态经济,2021,37(3):31-37.

    ZHANG A X, DENG R R. Coupling coordination degree of carbon emission efficiency and industrial structure optimization in six provinces of central China and research on its influencing factors[J]. Ecological Economy,2021,37(3):31-37.
    [25]
    姜博, 马胜利.区域经济增长与碳排放影响因素研究: 以东北三省为例[J]. 企业经济,2020,39(11):122-131.
    [26]
    马远, 刘真真.黄河流域土地利用碳排放的时空演变及影响因素研究[J]. 生态经济,2021,37(7):35-43.

    MA Y, LIU Z Z. Study on the spatial-temporal evolution and influencing factors of land use carbon emissions in the Yellow River Basin[J]. Ecological Economy,2021,37(7):35-43. ⊕
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