Abstract
China’s economy has been highly reliant on exports in recent years, with Guangdong its biggest province in export trade volume. Despite the global financial crisis of 2008, exports from Guangdong continued to increase significantly; however, the energy consumption embodied in exports is unknown. In this study, we investigate the changes of energy embodied in exports from 2007 to 2012 in Guangdong Province. We use EIO (Environmental Input-Output) and LMDI (Logarithmic Mean Divisia Index) method to find out the drivers of such changes embodied in total exports and export of each sector. Our results show: Firstly, from 2007 to 2012, the export structure in Guangdong has changed, reflecting in low energy intensity industry experiencing faster growth in exports than high energy intensity industry. Secondly, the growth rate of embodied energy consumption in Guangdong’s exports is slowing, with average annual growth from 2007 to 2012 of 6.8%. Thirdly, though Guangdong’s exports grew significantly, the energy consumption embodied therein decreased by 23% from 2007 to 2012, representing a drop of 50.51 Mtce. Finally, the most prominent change driver differed across sectors: For low value-added industries, such as metal smelting and rolling, the main contributor was export structure change, whereas for high value-added industries, such as communications, computers, and other electronic equipment, the main contributor was technical change. Guangdong is playing a leading role in industrial upgrading in China, and this has made the embodied energy consumption decreased obviously in Guangdong. It will be interesting to further investigate the trends of embodied energy consumption of other provinces in China, as this would give us deeper understanding of Chinese resource and environment problems.
Highlights
It is important to identify the trend of energy consumption embodied in Guangdong’s exports, as well as the main factors contributing to changes therein
Thereby, avoids the shortcomings of classical MDI (Mean Divisia Index) this method has been widely used in analyzing the drivers of environmental problems change in national level [14,42,43] Provincial-level changes in the energy consumption embodied in exports have rarely been studied
One appropriate method to capture energy consumption flows in the economy is the environmental input–output (EIO) model, which is extended from the standard Leontief input–output model [45,46]
Summary
Thereby, avoids the shortcomings of classical MDI (Mean Divisia Index) (which does not consider indirect effects on carbon emissions, and the non-uniqueness problem of SDA [41]) this method has been widely used in analyzing the drivers of environmental problems change in national level [14,42,43] Provincial-level changes in the energy consumption embodied in exports have rarely been studied. It details the decomposition approach, which combines the input-output technique and the LMDI to analyze the drivers of change in embodied energy consumption.
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