Study on influencing factors of carbon emissions from energy consumption of Shandong Province of China from 1995 to 2009

Jiekun Song,Dong Zhang,Qing Song

doi:10.1504/ijgei.2013.061819

Jiekun Song, Dong Zhang + Show 1 more

Open Access

https://doi.org/10.1504/ijgei.2013.061819

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Abstract

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.

Highlights

In recent years, Shandong province of China has achieved remarkable performance in economic development
According to equality expression of carbon emissions, decomposition models can be categorized into additive decomposition and multiplicative decomposition models; according to the decomposition with residual or not, decomposition models can be categorized into residual decomposition and zero-residual decomposition models; according to the principle of method, decomposition models can be categorized into index decomposition and structural decomposition models [1]
Since the above models are suitable for the decomposition of carbon emissions and have no unexplained residuals, whose result is most objective and credible, or can we combine them to get the better result? This paper proposes a combination method and applies it to decompose carbon emissions from energy consumption of Shandong province

Summary

Introduction

Shandong province of China has achieved remarkable performance in economic development. By using LMDI, Guo et al [14] decomposed carbon emissions of Shanghai city into four factors including population, per capita GDP, energy intensity, and energy structure. This paper proposes a combination method and applies it to decompose carbon emissions from energy consumption of Shandong province. Energy consumption intensity of the secondary industry was the highest among three industries, and it was always more than 1.1 ton standard coal per 10 thousand Yuan, which was much higher than those of the primary and tertiary industries. Carbon emissions have increased significantly from 68.3809 million tons in 2002 to 232.4380 million ton in 2012, and the annual average growth rate was 13.02%

Factors Decomposition Model of Carbon Emissions from Energy Consumption

Findings

Conclusions