Based on the international community's analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI) decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China's contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a) economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China's current actual policy; (b) the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c) considering the regional protectionism, regional actual situation need to be considered at the same time; (d) in the study of the industrial structure, the contribution value of industry is the most prominent factor for China's carbon productivity, while the industrial restructuring has not been done well enough.
Abstract:Energy efficiency improvement is essential for China's sustainable development of its social economy. Based on the provincial panel data of China's three economic regions from 1990 to 2013, this research uses the data envelopment analysis (DEA) model to measure the total-factor energy efficiency, and the Tobit regression model to explore the driving factors of efficiency changes. Empirical results show: (1) Energy efficiency, energy consumption structure, and government fiscal scale are significantly positively correlated. (2) Industrial structure and per capita income level have negative correlation to energy efficiency; the impact of industrial structure on energy efficiency is relatively small. (3) The increase of carbon dioxide emissions will decrease the energy efficiency. Furthermore, with people becoming less conscious of energy conservation and emission reduction, energy efficiency will also decrease. (4) Specific energy policies will improve energy efficiency, and greater openness in coastal areas will also have the similar effect.
As an essential measure to mitigate the CO2 emissions, China is constructing a nationwide carbon emission trading (CET) market. The electric power industry is the first sector that will be introduced into this market, but the quota allocation scheme, as the key foundation of market transactions, is still undetermined. This research employed the gross domestic product (GDP), energy consumption, and electric generation data of 30 provinces from 2001 to 2015, a hybrid trend forecasting model, and a three-indicator allocation model to measure the provincial quota allocation for carbon emissions in China′s electric power sector. The conclusions drawn from the empirical analysis can be summarized as follows: (1) The carbon emission peak in China′s electric power sector will appear in 2027, and peak emissions will be 3.63 billion tons, which will surpass the total carbon emissions of the European Union (EU) and approximately equal to 2/3 of the United States of America (USA). (2) The developed provinces that are supported by traditional industries should take more responsibility for carbon mitigation. (3) Nine provinces are expected to be the buyers in the CET market. These provinces are mostly located in eastern China, and account for approximately 63.65% of China′s carbon emissions generated by the electric power sector. (4) The long-distance electric power transmission shifts the carbon emissions and then has an impact on the quotas allocation for carbon emissions. (5) The development and effective utilization of clean power generation will play a positive role for carbon mitigation in China′s electric sector.
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