Using LMDI Method to Analyze the Energy-Related CO2 Emissions in Guangdong Province, China

In recent years, Guangdong has achieved remarkable performance in economic development; meanwhile it is being faced with problems of increasing CO2 emissions. Following the IPCC Guidelines for National Greenhouse Gas Inventories, we estimated the energy-related CO2 emissions in Guangdong during the...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 291-294; pp. 1556 - 1561
Main Authors Zhu, Bang Zhu, Wang, Ping, Wu, Wan Shui
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.01.2013
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Summary:In recent years, Guangdong has achieved remarkable performance in economic development; meanwhile it is being faced with problems of increasing CO2 emissions. Following the IPCC Guidelines for National Greenhouse Gas Inventories, we estimated the energy-related CO2 emissions in Guangdong during the period of 1980-2010. We employed the logarithmic mean divisia index (LMDI) method to decompose the CO2 emissions into energy intensity, energy structure, per capita GDP and population scale effects. Besides, we deduced the calculation methods for the year by year effects, the accumulated effects and the contribution degrees. Using 1980 as the base year, the empirical results show that the accumulated effects of energy intensity and energy structure in 2010 are negative, while those of per capita GDP and population scale are positive. Per capita GDP is the chief positive influence on the CO2 emissions. Energy intensity is becoming more significant; however, its direction is instability. Population scale has a significant positive effect on the CO2 emissions. Energy structure has a negligible negative impact on the CO2 emissions. Some suggestions on CO2 emissions reduction in Guangdong are given based on the analysis.
Bibliography:Selected, peer reviewed papers from the 2012 International Conference on Sustainable Energy and Environmental Engineering (ICSEEE 2012), December 29-30, 2012, Guangzhou, China
ISBN:9783037856345
3037856343
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.291-294.1556