CO2 emissions integrated fuzzy model: A case of seven emerging economies

被引:12
作者
Dincer, Hasan [1 ]
Yuksel, Serhat [1 ]
Mikhaylov, Alexey [2 ]
Muyeen, S. M. [3 ]
Chang, Tsangyao [4 ]
Barykin, Sergey [5 ]
Kalinina, Olga [5 ]
机构
[1] Istanbul Medipol Univ, Sch Business, Istanbul, Turkiye
[2] Financial Univ, Financial Fac, Govt Russian Federat, Moscow, Russia
[3] Qatar Univ, Dept Elect Engn, Box 2713, Doha, Qatar
[4] Feng Chia Univ, Dept Finance, Taichung, Taiwan
[5] Peter Great St Petersburg Polytech Univ, St Petersburg, Russia
基金
俄罗斯科学基金会;
关键词
CO2; emission; Emerging economies model; TOPSIS method; Quantum spherical fuzzy; Fiscal policy; Taxation; DECISION-MAKING; ENERGY PRODUCTIVITY; CONVERGENCE; OPERATORS; ENTROPY; DEMATEL;
D O I
10.1016/j.egyr.2023.05.008
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper proposes a new model to study carbon emission issues in seven emerging (E7) economies (China, Mexico, Turkey, Russia, Brazil, Indonesia and India). It employs weighted Quantum Spherical fuzzy DEMATEL model with golden cut using 18 years data, which was ranked for carbon emission evaluation via Quantum Spherical fuzzy TOPSIS method. The data includes macroeconomic variables for the period from 2003 to 2020. Paper observes that (i) CO2 emissions from fossil fuels is the most significant factor distressing the carbon emission problem of E7 economies. It suggests that these countries need to explore alternatives to fossil fuels to handle the carbon emission problem. (ii) The CO2 emission problem in energy production can be minimized by renewable energy and nuclear energy, suggesting some financial incentives to the investors in energy explorations areas. (iii) It is also observed that due to high volatility of CO2 emissions, a negative market factor exists in consumer sentiment in consumption of oil and petroleum products. This can be compensated via energy consumption fiscal policy in taxation and encourage of extractive industries and producers of petroleum products, as well as the uneven spatial development to have a significant impact on the reduction of CO2 emission. The paper gives recommendation that E7 countries need to find alternatives to fossil fuels in order to deal effectively with the carbon emission problem.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页码:5741 / 5751
页数:11
相关论文
共 56 条
  • [31] Interval-valued intuitionistic hesitant fuzzy entropy based VIKOR method for industrial robots selection
    Narayanamoorthy, S.
    Geetha, S.
    Rakkiyappan, R.
    Joo, Young Hoon
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2019, 121 (28-37) : 28 - 37
  • [32] Hybrid Allocation of Capacitor and Distributed Static Compensator in Radial Distribution Networks Using Multi-Objective Improved Golden Ratio Optimization Based on Fuzzy Decision Making
    Noori, Alireza
    Zhang, Yiming
    Nouri, Negar
    Hajivand, Mohammad
    [J]. IEEE ACCESS, 2020, 8 : 162180 - 162195
  • [33] Impact of digital finance on financial inclusion and stability
    Ozili, Peterson K.
    [J]. BORSA ISTANBUL REVIEW, 2018, 18 (04) : 329 - 340
  • [34] Ozimek A, 2020, FUTURE REMOTE WORK, DOI DOI 10.2139/SSRN.3638597
  • [35] Dynamics and drivers of per capita CO2 emissions in Asia
    Parker, Steven
    Bhatti, M. Ishaq
    [J]. ENERGY ECONOMICS, 2020, 89
  • [36] Economy-wide and manufacturing energy productivity transition paths and club convergence for OECD and non-OECD countries
    Parker, Steven
    Liddle, Brantley
    [J]. ENERGY ECONOMICS, 2017, 62 : 338 - 346
  • [37] Pham T. A., 2020, Applied Sciences, V10
  • [38] Phoumin H., 2014, ERIA DISCUSSION PAPE
  • [39] Occupant-based energy upgrades selection for Canadian residential buildings based on field energy data and calibrated simulations
    Rana, Anber
    Perera, Piyaruwan
    Ruparathna, Rajeev
    Karunathilake, Hirushie
    Hewage, Kasun
    Alam, M. Shahria
    Sadiq, Rehan
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 271
  • [40] Raza N., 2019, J COMPUT COMMUN, V7, P19, DOI [10.4236/jcc.2019.73003, DOI 10.4236/JCC.2019.73003]