PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2018 | 27 | 6 |

Tytuł artykułu

How carbon emission quotas can be allocated fairly and efficiently among different industrial sectors: The case of Chinese industry

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Emissions trading schemes (ETS) have been treated as a cost-effective mitigation measure to effectively control carbon emissions. Industrial carbon emission quota allocation is prior to the implementation of ETS. This study takes industrial sectors in China as a case to apportion carbon emission quotas. An informational entropy and multiple-factor mixed weighting allocation model (IEMMA) was established by considering fairness, efficiency, and feasibility from 4 aspects, i.e., emission reduction responsibility, emission reduction potential, emission reduction capacity, and industrial features. The allocation results among industrial sectors present many differences, and averaging a weighting allocation scheme is more feasible than other allocation schemes considering the fairness, efficiency, and feasibility. This study not only advances the existing literature on the issue of sectoral carbon emission quota allocation, but also provides a significant reference for China’s policymaking in ETS implementation.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

27

Numer

6

Opis fizyczny

p.2883-2891,fig.,ref.

Twórcy

autor
  • School of Management, China University of Mining and Technology, Xuzhou, China
autor
  • School of Management, China University of Mining and Technology, Xuzhou, China
autor
  • School of Management, China University of Mining and Technology, Xuzhou, China
autor
  • School of Management, China University of Mining and Technology, Xuzhou, China
autor
  • School of Management, China University of Mining and Technology, Xuzhou, China

Bibliografia

  • 1. GUMULA S., PYTEL K., PIASKOWSKA-SILARSKA M. Polemical Remarks to the Claim that Carbon Dioxide Strengthens the Greenhouse Effect in the Atmosphere. Pol. J. Environ. Stud. 23 (6), 2321, 2014.
  • 2. MFA. U.S.-China Joint Announcement on Climate Change. Ministy of Foreign Affairs of People’s Republic of China, Beijing, 2015.
  • 3. CHANG X., LI Y., ZHAO Y., WU J. Effects of carbon permits allocation methods on remanufacturing production decisions. J. Clean. Prod. 152, 281, 2017.
  • 4. RINGIUS L, TORVANGER A, UNDERDAL A. Burden Sharing and Fairness Principles in International Climate Policy. Int. Environ. Agreem-P. 2 (1), 1, 2002.
  • 5. ZHANG Y.J., WANG A.D., DA Y.B. Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method. Energ. Policy. 74 (C), 454, 2014.
  • 6. KANDER A., JIBORN M. A new way of allocating responsibility for carbon emissions: Swedish consumption based emissions adjusted for NEGA-emissions. Soc. Sci. 2014.
  • 7. HAN R., TANG B.J., FAN J.L., LIU L.C., WEI Y.M. Integrated weighting approach to carbon emission quotas: an application case of Beijing-Tianjin-Hebei region. J. Clean. Prod. 131, 448, 2016.
  • 8. ZHANG Y.J., HAO J.F. Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles. Ann. Oper. Res. 255 (1-2), 117, 2017.
  • 9. FILAR J.A., GAERTNER P.S. A sectoral allocation of world CO₂, emission reductions. Math. Comput.Simulat. 43 (3-6), 269, 1997.
  • 10. YU S., WEI Y.M., WANG K. Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition. Energ. Policy. 66 (7), 630, 2014.
  • 11. CHIU Y.H., LIN J.C., HSU C.C., JIA W.L. Carbon emission allowances of efficiency analysis: Application of super SBM ZSG-DEA model. Pol. J. Environ. Stud. 22 (3), 653, 2013.
  • 12. SUN J., WU J., LIANG L., ZHONG R.Y., HUANG G.Q. Allocation of emission permits using DEA: centralized and individual points of view. Int. J. Prod. Res. 52 (2), 419, 2014.
  • 13. LIU Z., GENG Y., LINDER S, GUAN D. Uncovering China’s greenhouse gas emission from sectoral and sectoral perspectives. Energy, 45 (1), 1059, 2012.
  • 14. ZHANG Y.J., DA Y.B. Decomposing the changes of energy-related carbon emissions in China: evidence from the PDA approach. Nat. Hazards. 69 (1), 1109, 2013.
  • 15. YI W.J., ZOU L.L., GUO J., WANG K., WEI Y.M. How can China reach its CO₂, intensity reduction targets by 2020? A sectoral allocation based on equity and development. Energ. Policy. 39 (5), 2407, 2011.
  • 16. ZHOU P., ZHANG L., ZHOU D.Q., XIA W.J. Modeling economic performance of interprovincial CO₂, emission reduction quota trading in China. Appl. Energy. 112 (16), 1518, 2013.
  • 17. YU S., WEI Y.M., FAN J., ZHANG X., WANG K. Exploring the sectoral characteristics of inter-provincial CO₂, emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization. Appl. Energy. 92 (4), 552, 2012.
  • 18. WU H., DU S., LIANG L., ZHOU Y. A DEA-based approach for fair reduction and reallocation of emission permits. Math. Comput. Model. 58 (5-6), 1095, 2013.
  • 19. BROEK M.V.D., HOEFNAGELS R., RUBIN E., RUBIN E., FAAIJ A. Effects of technological learning on future cost and performance of power plants with CO₂, capture. Prog. Energ. Combust. 35 (6), 457, 2009.
  • 20. KUNNAS J., MYLLYNTAUS T. Anxiety and technological change - Explaining the inverted U-curve of sulphur dioxide emissions in late 20th century Finland. Ecol. Econ. 69 (7), 1587, 2010.
  • 21. HAN Y.F. Research on the Potential of Resource Saving and Emission Reducing of Papermaking Industry in China: Based on Environment Learning Curve. Adv. Mat. Res. 361-363, 1013, 2012.
  • 22. HAN Y.F. Analysis of environment learning curve and the inter-province emission reducing potential in china. Shaanxi Normal University, 2008.
  • 23. China’s National Bureau of Statistics (CNBS). Industrial classification for national economic activities (GB/T 4754-2011); China Statistical Press: Beijing, 2011.
  • 24. China’s National Bureau of Statistics (CNBS). China Statistic Yearbook; China Statistical Press: Beijing, 2015.
  • 25. China’s National Bureau of Statistics (CNBS). China Energy Statistic Yearbook; China Statistical Press: Beijing, 2015.
  • 26. China’s National Bureau of Statistics (CNBS). China Industry Statistic Yearbook; China Statistical Press: Beijing, 2015.
  • 27. DONG F., YU B.L., HADACHIN T., Dai Y.J., WANG Y., ZHANG S.N., LONG R.Y. Drivers of carbon emission intensity change in China. Resour. Conserv. Recycl. 129, 187, 2018.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.agro-a7240de8-adae-4a55-8aef-e16dbc667018
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.