Natural Hazards

, Volume 85, Issue 2, pp 1189–1208 | Cite as

Research on the initial allocation of carbon emission quotas: evidence from China

  • Yu-Jie Hu
  • Rong Han
  • Bao-Jun TangEmail author
Original Paper


In November 2015, China government announced that the national carbon emissions trading market is expected to start in 2017. Carbon emission trading system is a raising concern from day to day, in which the allocation of carbon quotas has the closest relationship with trading units directly determining the cost of carbon trading. Initial allowance allocation is fundamental, but it proposes difficulty in terms of the trading mechanism design. This paper is based on the total control principle of national layout, in which the government sets up the cap of emissions in the carbon emissions trading system and focuses on the historical emission allocation concept from the perspective of fairness and history responsibility meaning that the allocation of quota in the future is based on the historical emissions. Firstly, we carry out comparative analysis based on the economy development and the emissions of 31 provinces and cities in China and select the sign-post province, Hebei. Secondly, we take the sign-post province as benchmarking and compare the benchmarking with the other provinces on the economy to set three quota situations of different initial years. Finally, we conduct quota calculation of residual carbon dioxide of various provinces by the end of 2020 and provide the specific quota calculation plans under different situations. The result of quota indicates: Most provinces still have more or less surplus to reallocate by the end of 2020; some provinces and cities have developing economy at expense of large emission and old industrial area with high energy consumption and high coal demand are in the shortage of future emission space; for the developed areas, the earlier emissions accounting is not good for their owning surplus; the earlier the years we select as the starting to account the quota, the greater the reductions space we will have. Meanwhile, we carry out testing of the feasibility of self-providing quota plans. These results may provide corresponding policy advice for China.


Carbon emissions trading Total control Initial allocation Long-term fair 



We gratefully acknowledge the financial support from the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 71521002), the National Natural Science Foundation of China (Grant Nos. 71273031 and 71573013), the Beijing Natural Science Foundation of China (Grant No. 9152014) and National Key R&D Program (Grant No. 2016YFA0602603), Joint Development Program of Beijing Municipal Commission of Education.


  1. Cazorla M, Toman M (2000) International equity and climate change policy. Res Future Clim 27:1–20Google Scholar
  2. Cramton P, Kerr S (2002) Tradeable carbon permit auctions: how and why to auction not grandfather. Energy Policy 30(4):333–345CrossRefGoogle Scholar
  3. Demailly D, Quirion P (2006) C02 abatement, competitiveness and leakage in the European cement industry under the EU ETS: grandfathering versus output-based allocation. Clim Policy 6(1):93–113CrossRefGoogle Scholar
  4. Ding ZL, Duan XN, Ge QS et al (2009) Control of atmospheric CO2 concentration by 2050: an allocation on the emission rights of different countries. Sci China Seri D Earth Sci 39(8):1009–1027Google Scholar
  5. Han R, Tang BJ, Fan JL et al (2016) Integrated weighting approach to carbon emission quotas: an application case of Beijing–Tianjin–Hebei region. J Clean Prod 131:448–459CrossRefGoogle Scholar
  6. Hepburn C, Grubb M, Neuhoff K et al (2006) Auctioning of EU ETS phase II allowances: how and why. Clim Policy 6(1):137–160CrossRefGoogle Scholar
  7. Hu M (2007) Price of sewage’s discharge right analysis of the shadow price model. Prices Mon 2:19–22Google Scholar
  8. Huang T-C, Wu B-T (2004) Appraisal models of emission permits deals based on costs and profits. Shanghai Manag Sci 6:34–36Google Scholar
  9. IPCC (2006) 2006 IPCC guidelines for national greenhouse gas inventories. IPCC National Greenhouse Gas Inventories ProgrammeGoogle Scholar
  10. Li SD, Wang JQ (2004) Initial perm it right of pollutant discharge: impact to market structure under different allocation. J Wuhan Univ Technol Transp Sci Eng 28(1):40–43CrossRefGoogle Scholar
  11. Lin YH (2009a) The research on shadow price model of tradable permits. Environ Sci Manag 34(2):16–19Google Scholar
  12. Lin YH (2009b) The theory of emissions trading market pricing mechanism and influence factors. Contemp Econ Manag 31(20):1–4Google Scholar
  13. Matthes FC, Neuhoff K (2007) Auctioning in the European Union Emissions Trading Scheme. Öko-Institution & University of Cambridge. A report to WWFGoogle Scholar
  14. Mi Z, Pan S, Yu H, Wei Y (2015a) Potential impacts of industrial structure on energy consumption and CO2 emission: a case study of Beijing. J Clean Prod 103:455–462CrossRefGoogle Scholar
  15. Mi Z, Wei Y, He C, Li H, Yuan X, Liao H (2015b) Regional efforts to mitigate climate change in China: a multi-criteria assessment approach. Mitig Adapt Strateg Glob Change. doi: 10.1007/s11027-015-9660-1 Google Scholar
  16. Mi Z, Zhang Y, Guan D et al (2016) Consumption-based emission accounting for Chinese cities. Appl Energy. doi: 10.1016/j.apenergy.2016.06.094 Google Scholar
  17. Provisional Regulation on Carbon Emissions Trading Management National Development and Reform Commission (NDRC) (2014) China: People’s Republic of ChinaGoogle Scholar
  18. Ringius L, Torvanger A, Holtsmark B (1998) Can multi-criteria rules fairly distribute climate burdens? OECD results from three burden sharing rules. Energy Policy 26(10):777–793CrossRefGoogle Scholar
  19. Stavins RN (1997) Policy instruments for climate change: how can national governments address a global problem. The University of Chicago Law School. Discussion Paper 97–11:1–36Google Scholar
  20. Sun M, Tao YW (2011) Research on energy saving goal decomposition model. Stat Decis 329(5):51–54Google Scholar
  21. Tang BJ, Sheng C, Gao C (2013a) The efficiency analysis of the European CO2 futures market. Appl Energy 112(1):1544–1547CrossRefGoogle Scholar
  22. Tang BJ, Shi XP, Gao C (2013b) Analysis on embodied energy of China’s export trade and the energy consumption trends of key industries. Int J Energy Res 37:2019–2028Google Scholar
  23. Wei Y-M, Zou L-L, Wang K et al (2013) Review of proposals for an agreement on future climate policy: perspectives from the responsibilities for GHG reduction. Energy Strategy Rev 2(2):161–168CrossRefGoogle Scholar
  24. Wei Y-M, Wang L, Liao H et al (2014) Responsibility accounting in carbon allocation: a global perspective. Appl Energy 130:122–133CrossRefGoogle Scholar
  25. Wei Y, Mi Z, Huang Z (2015) Climate policy modeling: an online SCI-E and SSCI based literature review. OMEGA Int J Manag Sci 57:70–84CrossRefGoogle Scholar
  26. Yan L, Wu TF (2010) Initial distribution and trading model of shadow price-based emission permit. J Chongqing Univ Technol Soc Sci 24(2):53–56Google Scholar
  27. Yu H, Tang BJ, Yuan XC, Wang SY, Wei YM (2015a) How do the appliance energy standards work in China? Evidence from room air conditioners. Energy Build 86:833–840CrossRefGoogle Scholar
  28. Yu H, Pan S, Tang B, Mi Z, Zhang Y, Wei Y (2015b) Urban energy consumption and CO2 emissions in Beijing: current and future. Energy Effic 8(3):527–543CrossRefGoogle Scholar
  29. Zhang D-F, Wu Y-Z, Jiang L-P et al (2009) The initial allocation of emission rights for free and paid distribution of the comparative study. J Anhui Agric Sci 37(10):4707–4709Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Center for Energy and Environmental Policy ResearchBeijing Institute of TechnologyBeijingChina
  2. 2.School of Management and EconomicsBeijing Institute of TechnologyBeijingChina
  3. 3.Collaborative Innovation Center of Electric Vehicles in BeijingBeijingChina
  4. 4.Sustainable Development Research Institute for Economy and Society of BeijingBeijingChina

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