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Sustainability 2017, 9(2), 274;

Decomposition Analysis of Carbon Emission Factors from Energy Consumption in Guangdong Province from 1990 to 2014

Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, School of Geography Science and Tourism, Xinjiang Normal University, Urumqi 830054, China
Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, China
School of Geographical Science, Nanjing Normal University, Nanjing 210046, China
Authors to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 19 January 2017 / Revised: 8 February 2017 / Accepted: 12 February 2017 / Published: 15 February 2017
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Carbon emissions research based on regional perspective is necessary and helpful for China to achieve its reduction targets. This research aims at analyzing the energy-related carbon emissions and finding out the most important driving forces for the carbon emissions increments in Guangdong province. LMDI (Logarithmic Mean Divisia Index) method based on the extended Kaya identity has been used to explore the main driving factors for energy-related carbon emissions in Guangdong province annually between 1990 and 2014. Research results show that the impacts and influences of various factors on carbon emissions are different in the different development stages. Economic growth effect and population size effect are the two most important driving factors for the increased carbon emissions. Energy intensity effect played the dominant role in curbing carbon emissions. Energy structure effect and technical progress effect had different but relatively minor effects on carbon emissions during the five different development stages. View Full-Text
Keywords: carbon emissions; LMDI; Guangdong province carbon emissions; LMDI; Guangdong province

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Wang, F.; Wang, C.; Su, Y.; Jin, L.; Wang, Y.; Zhang, X. Decomposition Analysis of Carbon Emission Factors from Energy Consumption in Guangdong Province from 1990 to 2014. Sustainability 2017, 9, 274.

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