Study On Driving Factors And Control Strategy Of Carbon Emission Growth In China

Globa lclimate changes makes global sustainable development face severe challenges.China as an energy superpower, especially in the rapid economic development in recent years, the surge in China’s energy demand, leading to increased CO2 emissions. In November 2009, the Chinese government announced that in 2005 on the basis of gross domestic product(GDP) CO2 emissions(carbon intensity), will drop 40% ~ 40% by 2020, that is the Chinese government commitment to the international community, which has the certain legal restraint. Therefore, how to realize the target of the carbon intensity of our country, for China’s energy saving and emission reduction, environmental conservation and economic harmony, stability, sustainable development is of great significance. Revolving around the prediction of China’s CO2 emission, The identification of driving factors and measurements, control strategies, this innovative work is as follows:1. Through the historical data of 1953-2013, using CO2 emissions measurement recommended by the time-varying parameter state space model, markov chain model and "2006 IPCC Guidelines for National Greenhouse Gas Inventories ", forecasting China’s CO2 emissions in 2014-2020. Results show that China’s carbon emissions show upward trend in high speed from 2014, China’s energy conservation and emissions reduction is still face greater pressure and challenges.2. Combining of logarithmic mean Divisia index method of Kaya equation(LMDI) and STIRPAT development model, and carrying out the research on the measure of recognition of China’s CO2 emissions driving factors from1953 to 2013. The results indicate that the economic development, industrial structure and population scale factor play a stimulating effect on CO2 emissions. The output value of energy consumption and energy structure has a negative effect on carbon emissions.3. Using scenario analysis, which control the scene settings on driving factors of CO2 emissions in the energy consumption,energy structure and economic development, set up China’s carbon intensity prediction model and calculate carbon intensity under different scenarios of the "decline" and "potential " contribution.The results of different scenarios had vary results.4. The use of the decomposition model of development and the weight decision preference settings, analyzes the control of China’s total energy consumption, in 2020 the provinces(municipalities and autonomous regions, excluding Hong Kong, Macao and Taiwan and Tibet) of the total energy consumption. The results show that, in the scenario decomposition model and different weight setting, Hebei, Jiangsu, Shandong, and Guangdong’s energy consumption are at the forefront, and Shandong account for the largest proportion. In the context of no preference, preferent efficiency and preferent the endowment of regional, the amount of inter provincial energy consumption in China is similar to the results,the feasibility of the model and decomposition of preference scenarios,the fairness preference scenarios,there is a big difference between the provincial energy consumption results and other results of scene.