Keywords: carbon emissions, energy consumption, factors decomposition, logarithmic mean weight Divisia index, LMDI, mean–rate–of–change index, MRCI, Shapley value, STIRPAT model, Shandong Province, carbon dioxide, CO2, China, per capita GDP, population, consumption intensity, consumption structure, industrial structure
Study on influencing factors of carbon emissions from energy consumption of Shandong Province of China from 1995 to 2009
LMDI, MRCI and Shapley value models are employed for decomposing carbon emissions from energy consumption of Shandong province from 1995 to 2009. Based on the results, an optimal weighted combination model is put forward. By applying STIRPAT model, the impact of each factor on carbon emissions is evaluated. The results show that the cumulative effects of population, per capita GDP and industrial structure are positive, and those of energy consumption intensity and energy consumption structure are negative. Per capita GDP is the largest driver of the increasing carbon emissions and has the most significant impact on carbon emissions; population plays a weak driving role, but its impact is great; energy consumption intensity and energy consumption structure are important inhibition factors, and the former has a great impact, while the latter has a weak impact; industrial structure has played a weak inhibitory role since 2005, and its impact is weak.