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Using the logarithmic mean Divisia index (LMDI) method, we decomposed the factors that affect carbon emissions at a multi-regional level. Based on a comparative analysis of the regional contributions to carbon emissions in China from 1995 to 2012, we found that economic growth is a major factor that increases carbon emissions. Excluding Hainan, Guangxi, Ningxia, and Xinjiang, the energy intensity effects of other provinces and municipalities inhibited carbon emissions clearly. The energy structure effect in Beijing and Shanghai inhibited carbon emissions most obviously, whereas the energy structure effect in Xinjiang promoted carbon emissions to the greatest extent. The energy structure effect in most regions had little influence on carbon emissions. The output proportion effect enhances carbon emissions on the whole, which indicates China's regional economic development is not coordinated from the perspective of carbon emission reductions. Overall, Shandong, Inner Mongolia, and Hebei made the biggest contributions to national carbon emissions. Policy implications in terms of our study results are discussed. [ABSTRACT FROM AUTHOR]

This study analyzes carbon emissions due to energy consumption based on different stages and sectors in China, and by applying the logarithmic mean Divisia index decomposition method, carbon emissions were decomposed into energy structure, energy intensity, economic structure, and economic output effects. The study period was divided into “high efficiency and high output”, “low efficiency and low output”, “high efficiency and low output” and “low efficiency and high output” considering different carbon emission characteristics and economic development. Carbon emissions exhibit different characteristics at different stages. The degree of increase in carbon emissions at these stages depends on the combined effect of the energy efficiency and the economic output. The main factor driving carbon emissions was the economic output effect in each stage and the main factor inhibiting carbon emissions was the energy intensity effect. The economic and energy structures had only a modest effect on carbon emissions at each stage. The industry sector was the top contributor to carbon emissions, followed by the transport sector. The policy implications in terms of economic growth, the economic structure, and energy consumption are discussed in relation to the different stages. [ABSTRACT FROM AUTHOR]

Using the logarithmic mean Divisia index (LMDI) method, we decomposed factors affecting the national carbon intensity (NCI) in China at a multi-regional level. A comparative analysis of regional contributions in different Five-Year Plan (5YP) periods revealed that the energy structure had inhibitory effects on NCI during the 9th and 10th 5YP periods, but had promoting effects during the 11th and start of the 12th 5YP periods. The energy structure had a strong inhibitory impact in eastern, north-eastern, and northern regions of China, but only a slight impact in central, northern, south-western, and north-western regions. Energy intensity is a major factor and had a strong inhibitory effect on NCI except during the 10th 5YP period. Energy intensity had a strong inhibitory effect in eastern and northern regions, but only a slight impact in north-western and southern regions, especially in Hainan, Ningxia, Xinjiang, and Qinghai provinces. Overall, proportional output in China had a promoting effect on NCI, which indicates regional economic development was not coordinated. The combined effects of regional carbon intensity (RCI) and proportional output determined changes in NCI, and RCI had a strong effect on NCI. Regions with high proportional output and large carbon emissions had a great impact on NCI. The total effect in developed areas such as eastern, northern, and north-eastern regions was strongly inhibitory, while the impact was slight in relatively less developed areas such as northwestern and southern regions. Some policy implications arising from our study results are discussed. [ABSTRACT FROM AUTHOR]