In this study we used the Gini coefficient optimization model to optimize the allocation of carbon emission quotas in history basing on data of population, GDP and carbon emissions from 132 countries by 1901 to 2005, taking the equity of historical intergenerational and intra-generational into account. We also allocated a equitable distribution of carbon emission permits for various countries in the future. The Gini coefficient value of carbon emission quotas in history were lower than the actual value based on GDP and population from various countries, and were below 0.4 of warning value, and obtained an optimal carbon emission quotas allocation that comprehensively considered the history of various countries' GDP and population. The analysis of carbon emissions remaining quantity and the deficit quantity in history from various countries showed that the United States had the largest historical carbon deficit, India and China had the largest historical carbon remaining quantity. Meanwhile, considering the history of carbon emissions, the future carbon emission permits of various countries showed that China, India and other countries had the largest population, the economic proportion of the world were higher, and thus can get the most carbon emission permits in the future.
王慧慧, 刘恒辰, 何霄嘉, 曾维华. 基于代际公平的碳排放权分配研究[J]. 中国环境科学, 2016, 36(6): 1895-1904.
WANG Hui-hui, LIU Heng-chen, HE Xiao-jia, ZENG Wei-hua. Allocation of carbon emissions right based on the intergenerational equity. CHINA ENVIRONMENTAL SCIENCECE, 2016, 36(6): 1895-1904.
Heil M T, Wodon Q T. Inequality in CO2Emissions Between Poor and Rich Countries [J]. Journal of Environment & Development, 1997,6(4):426-452.
[4]
Heil M T, Wodon Q T. Future Inequality in CO2Emissions and the Impact of Abatement Proposals [J]. Environmental & Resource Economics, 2000,17(2):163-181.
[5]
Hedenus F, Azar C. Estimates of trends in global income and resource inequalities [J]. Ecological Economics, 2005,55(3):351-364.
[6]
Duro J A, Padilla E. International inequalities in per capita CO2emissions: A decomposition methodology by Kaya factors [J]. Energy Economics, 2006,28(2):170-187.
[7]
Groot L. Carbon Lorenz curves [J]. Resource & Energy Economics, 2010,32(1):45-64.
[8]
Golombek R, Kittelsen S A C, Rosendahl K E. Price and welfare effects of emission quota allocation [J]. Energy Economics, 2013, 36(3):568-580.
[9]
Paloheimo E, Salmi O. Evaluating the carbon emissions of the low carbon city: A novel approach for consumer based allocation [J]. Cities, 2013,30(30):233-239.
[10]
Chin A T H, Zhang P. Carbon emission allocation methods for the aviation sector [J]. Journal of Air Transport Management, 2013,28(5):70-76.
Bohm P, Larsen B. Fairness in a tradeable-permit treaty for carbon emissions reductions in Europe and the former Soviet Union [J]. Environmental and Resource Economics, 1994,4(3): 219-239.
[24]
Kverndokk S. Tradeable CO2Emission Permits: Initial Distribution as a Justice Problem [J]. Environmental Values, 1992,4(2):129-148.
Baer P. The greenhouse development rights framework for global burden sharing: reflection on principles and prospects [J]. Wiley Interdisciplinary Reviews: Climate Change, 2013,4(1):61-71.