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Abstract The DEA-Shephard distance function of energy input was taken into a seven-factor LMDI decomposition model, which was built of carbon emissions from the energy consumption of six major industries in China from 1995to 2010.The empirical results revealed that industrial structure, economic output, population size, and energy efficiency had a pulling effect on industrial carbon emissions from energy consumption, and the cumulative effect of economic output had the maximum contribution of 135%. The cumulative effects of industrial structure, population scale, and energy efficiency on carbon emissions were 10.74%, 9.39%, and 0.65% respectively. Energy intensity with a cumulative contribution of 54.6% has the largest potential to reduce carbon emissions, which meant industrial energy intensity had larger room for improvement, and the inhibitory effect was increasing; the cumulative contributions of energy structure and energy technological progress to China's carbon emissions reduction were 0.2% and 1.04%, they had weak contributions, so needed to be improved; In terms of the industrial carbon reduction, agriculture, forestry, animal husbandry and fishery, construction, wholesale and retail and catering industry and other industries had been better in reducing carbon emissions. Transportation, storage and postal industry had been lagging behind in carbon reduction. Industrial carbon emissions had always been the major source of carbon emissions in China.
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Received: 22 December 2012
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