Allocation Of Reduction Target Based On Carbon Dioxide Emission Variation And Equity In China

The international community has reached a consensus that global warming poses a serious threat. Consequently, greenhouse gas reduction plans have been successively promulgated in the major developed and developing countries. China, as the largest developing country, announced its program to reduce future carbon dioxide ?CO₂? emissions during the 15th International Climate Conference held in Copenhagen in 2009. Moreover, achieving a national reduction target of CO₂ emissions depends on how intra-national units implement their own reduction targets. Therefore, China announced its 12th five-year ?2011-2015? plan to reduce emissions in 2012, which explicitly stipulated the reduction target for each provincial unit in mainland China. Both of these announcements emphasized the decrease of CO₂ emission intensity. The first target, which was announced in Copenhagen, stated that the emission intensity in 2020 should be reduced by 40%-45% compared with the 2005 level. Study on reduction targets allocation of carbon dioxide emission in provincial-level will help to accomplish intensity reduciton target of carbon dioxide emission which the country has promised. At the same time, China has carried out the pilot project for carbon emission trading in seven provincial-level regions, and the initial allocation of reduction target in emission intensity is the basis of carbon emission trading.At the beginning of this study, the literature review about history and current status of greenhouse gas reduction and carbon dioxide emission reduction were given. The existing studies focused on allocation of reduction responsibility among the country-level. Based on mess status of allocation principles, standards, methods in carbon emission reduction within country, the study identified research ideas and processes are "set base, measure variations, construct system, use methods and assess allocation results". Take the allocation of carbon dioxide reduction targets within China at the provincial-level as an example for empirical research. The main research processes and conclusions can be summarized as below.At the first section of the study, regional net carbon dioxide emissions were calculated to set the base for reduction target allocation as a starting point. A new computing model of regional carbon dioxide emissions was configured by considering the carbon emission sources of energy consumption and cement production process, as long as the carbon sequestration of major land use types include forest and green lands. The model was applied to calculated inter-provincial carbon dioxide emissions in China.The carbon dioxide emissions of thirty provinces from year 1995 to year 2013 were carried out by using national statistical data. In order to reflect the emission variations among provinces directly, this section selected some indexes including regional total emissions, per capita emissions, emission intensity, emission density to illustrate the temporal and spatial variations and geographic distribution in provincial carbon dioxide emission. The typical distribution in emission variations, such as, the total emissions and per capita emissions showed significant differences from east to west China procinves, emission intensity had great differences between south with north China provinces. In order to measure these emission differences, the Theil entropy index method was adopted to estimate the overall differences in per capita emissions and emission intensity. At the same time, according to the common rules of the provincial partition, as we all known 3 and 8 divisions in accordance with partition by per capita Gross Domestic Product, respectively. The internal differences of carbon dioxide emission in partition and the contribution to the overall differences were all measured by Theil index and its decomposition. From the results, we figured out some northern and western provinces, as well as coastal provinces had a very significant impact on the formation of overall differences in carbon dioxide emission of China. The provinces in these regions and partitions should be assigned more reduction burden and given more consideration when draw up a scheme of reduction target allocation.At the second section of the study, on the basis of analyzing the allocation principles and allocation methods of emission reduction burden sharing among countries, this study carried on internal allocation of carbon dioxide reduction by using selective allocation principles, standards and methods within a country. The selective principles were historical responsibility, capacity, efficiency and equality. Based on the analysis of regional emission variations, under the principles of emission reduction allocation within country, the different indicators were selected to reflect the allocation principles, respectively. The framework of "targets, principles, indicators" in carbon dioxide reduction allocation was built by the thought of allocation process. Based on decision-making process by reduction policy makers, this study designed a multi-criteria comprehensive index allocation model by considering choice preferences and decision scenarios. The mathematical methods included traditional proportional method, abatement cost consideration method, improvement proportional method were employed for calculating regional reduction targets of carbon dioxide emission. Take the allocation of provincial-level carbon dioxide reduction targets from 2014 to 2020 as an example, the constructed multi-criteria scenario allocation model was carried out and got the allocation results of reduction targets in all participating provinces. These results satisfied the overall national emission reduction targets to achieve emissions intensity in 2020 compare with 2013 level by 20.01% decrease, achieved emissions intensity in 2020 compare with 2005 level by 45% decrease which was national carbon dioxide reduction commitment of China. By comparing the reduction targets assigned in all provinces and classified the targets for high, middle and low level on spatial distribution. The distribution also showed that the assigned high-level reduction targets were concentrated in some northern and western provinces, as well as coastal provinces. In any of allocation scenarios and methods, these provinces need to undertake more reduction responsibility in the future. This conclusion was reflected by all allocation results. There were some big differences and gaps among the allocation results by using different mathematical methods in particular provinces, and also big differences between provincial-level allocation targets and national overall reduction target. According to the discrete degree between the provincial-level reduction targets and national target, the logarithmic function allocation method by considering abatement cost could be better in reflecting the variations of regional emission.At the last section of the study, the measurement methods of equity in regional carbon dioxide emission was cited to calculate the unfairness degree in per capita carbon dioxide emissions and emission intensity. The measurement methods or indicators included carbon Gini coefficient, coefficient of variation, Kakwani index and Theil index. From the perspective of future equity in carbon dioxide emission, the study calculated the carbon equity in 2020 for all provinces, assessed all allocation results of carbon dioxide reduction. The allocation result which had better change of carbon equity was chosen for the solution of reduction targets among all provinces. Base on this assumption, this study thought that the allocation result calculated by efficiency preference and logarithmic function method in decision-making scenario model was the solution. In this solution, the emission intensity decrease targets, total emissions control target and emissions change permission were given out for all provinces. Even if emission intensity of all provinces were determined to decrease, but the targets they got had big differences by each other. Shanxi, Ningxia, Qinghai, Xinjiang, Inner Mongolia, Shandong, Guangdong, Liaoning, Jiangsu and other provinces got higher reduction targets of emission intensity. At the same time, high emissions provinces in the base year 2013 still got more emissions increase and high emissions permission.Based on historical data of carbon dioxide emissions in all provinces, this study designed two different reduction pressure indexes by using time series forecasting and same time interval in emissions change. At the last of this section, the pressure of emission reduction that each province will face, was evaluated in the selected solution allocation result.