Research On Driving Forces And Attribution Analysis Of China’ S Energy-related GHG Emissions

The energy, environmental and climate problems caused by the greenhouse gas(GHG) emissions have received increasing attention nowadays. Since the agreement of Tokyo protocol in 1997, how to deal with the various challenges of GHG emissions has gradually become a priority for countries all over the world. In order to fulfill the promises that the CO2 emissions intensity will be decreased by 40-45% in 2020 compared with the 2005 level, and that the CO2 emissions of China will reach the peak point in 2030, the entire economic sector and the various industries of China need to play an active role in emissions reduction. This study first explored the driving forces of the energy-related GHG emissions in China from the national and sectoral perspectives. Then, the study moved a step further to explore the contributions of various sectors made to the change of each driving factor. The findings of this study provided some implications for emission reduction policies. The main research contents are given as follows.(1) The study mainly focused on three types of GHG emissions, including CO2, CH4 and N2 O. The emission coefficients of 18 types of fuels were calculated. Of which, the emission coefficients of electricity and heat were analyzed in detail. The GHG estimations of each industrial sector and the whole economy were calculated. Then, we used STIRPAT model and Partial Least Squares Regression to analyze the influence of population, per capita GDP, shares of secondary and tertiary industry, urbanization rate, and energy intensity on GHG emissions. At the same time, we built a GM(1,1) model to predict the values of GHG emissions, the share of secondary industry, per capita GDP, urbanization rate and energy intensity from 2012 to 2020.The prediction accuracy of each variable was quite high.(2) The study utilized a logarithmic mean Divisia index(LMDI) decomposition analysis to study GHG emission changes from a sectoral perspective. The influencing factors were classified into five groups, including emissions coefficient, energy structure, energy intensity, structure(economic structure and population structure) and scale(economic scale and population scale). The results showed that the expansion of economic scale was the dominant factor in increasing emissions in the four economic sectors, the increase in per capita energy consumption was primary responsible for the increasing resident GHG emissions, and the energy structure change was the major contributor to GHG emission growth in all sectors. Based on the decomposition results, we evaluated the policies and measures recently implemented in China for emissions mitigation.(3) In order to explore the contributions of the individual sectors to the reduction of GHG emissions, the study applied a Sato–Vartia LMDI-II to disentangle the GHG emissions in four economic sectors into three factors, including the emission coefficient effect, the structure effect and energy intensity effect. In addition, we quantified the contributions of each influencing factor in both single-period method and multi-period method. Then, a recently proposed attribution analysis was used to attribute the three influencing factors of the pre-defined four economic sectors to quantify the contributions of each sector. Combined with relative state and sectoral policies, the findings obtained were interpreted. Finally, implications for emission reduction policies were discussed.