This dissertation applies one new carbon burden-sharing scheme to China at the regional and provincial
levels. The major principle of this scheme is to allocate the carbon mitigation burden based on
individual emissions instead of average or total national/regional emissions. Only high emitting
individuals at the right end of the carbon distributions are included in the mitigation accounting.
To simulate the carbon distribution across individuals, a number of assumptions need to be made. The
key parameter to determine is the carbon elasticity of income. Through an analysis of the consumption
data from household surveys for 2002, chapter 2 calculates the carbon footprints of Chinese
households, analyzes their patterns of consumption and carbon emissions, and estimates the carbon
elasticity of income. The results of this study show that the average per capita household CO2
emissions of urban and rural households in China were 3.2 tons and 0.9 tons, respectively, in 2002. In
terms of carbon inequality, China’s overall inequality, as measured by its Gini coefficient across
individuals, was 0.51 in 2002, approximately the same level as that of the world as a whole (0.52 in
2004). Simulation results indicate that income (expenditure on consumption is used in the models) is
the most important factor causing inequality in carbon emissions. With all the other available
conditions controlled, the income elasticity was 0.92 for rural households, 0.61 for urban households,
and 0.84 for all households together.
Carbon mitigation allocation is performed under different hypothetical national CO2 emissions targets
for 2020 and 2030. The allocation results show that there are three tiers of provinces with a heavy
mitigation burden to bear. For 2020, the data are very clear. Both the first tier and the second contain
five provinces each. These are mainly provinces from the northeast, northwest, and coastal regions,
plus Tianjin and Shanghai. The third tier is composed of seven provinces from six regions. For 2030,
the three-tier system changes to a small extent and inter-tier differences are relatively vague. The top
burden bearers are featured with heavy coal endowments, the extraction of electricity from coal,
energy-intensive economic structures, high-income-related high-emission lifestyles, low-income
related low productivity and efficiency, and an energy-demanding climate. Allocation results are also
compared with other mainstream schemes of burden-sharing. This new burden-sharing does allocate a
greater share of the mitigation burden to relatively rich provinces. However, it cannot shift the
burden-sharing pattern among provinces and regions. The heavy burden bearers are always those
provinces and regions with high carbon intensities and/or high per capita CO2 emissions. Other factors
considered in different schemes are as well always secondary. Therefore, no matter what allocation
scheme is to be applied in China, I recommend, on the basis of this study, linking the development
priorities with regional features and adjusting the burden-sharing results accordingly.