Based On Income Angle Of The Empirical Analysis On The Allocation Of The Burden Of Co2 Emission Reduction In Various Provinces

Global climate change is hitherto the most seriousenvironmental problem，and is also one of the most complicatedchallenges in the21st century. The international negotiations aiming tomitigate global climate warming not only to the people’s surviving, butalso influence directly the modernization and sustainable developmentof developing countries. Now the scientific community has reached aconsensus that people’s activities should be responsible for the part ofglobal climate warming at least，and international negotiations havebeen also underway to try to reach a consensus on cutting the CO2emissions worldwide in order to solve it at all. As the largest developingcountry and the most CO2emissions source in the world, China’s CO2emissions reductions have been one of the hottest problems discussedby academe， environmental administers and all governments in theworld. It is of great importance to analyze China’s CO2emissions, whichis beneficial to China’ s sustainable development, but also cancontribute to mitigate the global climate warming.This dissertation applies one new carbon burden-sharingscheme to China at the regional and provincial levels. The majorprinciple of this scheme is to allocate the carbon mitigation burdenbased on individual emissions instead of average or totalnational/regional emissions. Only high emitting individuals at the rightend of the carbon distributions are included in the mitigationaccounting. To simulate the carbon distribution across individuals, anumber of assumptions need to be made. The key parameter todetermine is the carbon elasticity of income. Through an analysis of theconsumption data from household surveys, chapter2calculates thecarbon footprints of Chinese households, analyzes their patterns ofconsumption and carbon emissions,and estimates the carbon elasticity of income. The results of this study show that the average per capitahousehold CO₂emissions of urban and rural households in China were3.2tons and0.9tons, respectively,. In terms of carbon inequality,China’s overall inequality, as measured by its Gini coefficient acrossindividuals, was0.51, approximately the same level as that of the worldas a whole （0.52）. Simulation results indicate that income （expenditureon consumption is used in the models） is the most important factorcausing inequality in carbon emissions. With all the other availableconditions controlled, the income elasticity was0.92for rural households,0.61for urban households, and0.84for all households together.Carbon mitigation allocation is performed under differenthypothetical national CO2emissions targets for2020and2030. Theallocation results show that there are three tiers of provinces with aheavy mitigation burden to bear. For2020, the data are very clear. Boththe first tier and the second contain five provinces each. These aremainly provinces from the northeast, northwest, and coastal regions,plus Tianjin and Shanghai. The third tier is composed of seven provincesfrom six regions. For2030, the three-tier system changes to a small extentand inter-tier differences are relatively vague. The top burden bearersare featured with heavy coal endowments, the extraction of electricityfrom coal, energy-intensive economic structures, high-income-relatedhigh-emission lifestyles, low-income related low productivity andefficiency, and an energy-demanding climate. Allocation results arealso compared with other mainstream schemes of burden-sharing. Thisnew burden-sharing does allocate a greater share of the mitigationburden to relatively rich provinces. However, it cannot shift theburden-sharing pattern among provinces and regions. The heavyburden bearers are always those provinces and regions with highcarbon intensities and/or high per capita CO2emissions. Therefore, nomatter what allocation scheme is to be applied in China, I recommend, on the basis of this study, linking the development priorities with regionalfeatures and adjusting the burden-sharing results accordingly.