Abstract
In response to global climate change, China has voluntarily assumed responsibility and has pledged to reach its peak in carbon emissions by 2030. Industrial structure and urbanization have important impacts on energy consumption. This paper empirically analyzes the dynamic influence of industrial structure and urbanization on energy consumption in the Zhejiang Province of China by constructing a structural vector auto regressive model using impulse response function and variance decomposition. The results show a positive impact of urbanization on energy consumption, which increases and then gradually decreases, and an impact of industrial structure on energy consumption. The results also indicate that it will take a certain period of time for an increase in the proportion of tertiary industry to curb the growth of energy consumption. Urbanization has a greater impact on energy consumption than does industrial structure.
Highlights
China is a developing country, it has assumed responsibility for addressing the problem of global climate change
One target is that China will reduce its carbon dioxide emissions per unit of GDP by 60–65% of 2005 levels, and non-fossil energy will account for 20% of primary energy consumption [1]
How do industrial structure optimization and urbanization development affect energy consumption, especially in Zhejiang Province of China, where carbon emissions from energy activities account for approximately 78–80% of total carbon emissions? [29]
Summary
China is a developing country, it has assumed responsibility for addressing the problem of global climate change. How do industrial structure optimization and urbanization development affect energy consumption, especially in Zhejiang Province of China, where carbon emissions from energy activities account for approximately 78–80% of total carbon emissions? The growth rate of urbanization in Zhejiang ranks third out of 34 provinces in China, and it is one of the few provinces in China where tertiary industry has surpassed secondary industry All of these new challenges have a profound impact on energy consumption and make it much more difficult to realize energy-saving potential. We focus on Zhejiang Province and measure the impact of urbanization and industrial structure on energy consumption separately by impulse response function and variance decomposition using a structural vector auto regression (SVAR) model. In 2016, energy consumption in Zhejiang reached 2.03 million tons of consumptiocnoailn, aZndhtehjeiagnrogwrthearacthe ewdas23..043%,mwihlilcihownatsosnigsniofifcacnotlaylh, iagnhedr tthhaen tghreoowvetrhallrlaevteelwofa1s.4%3.4in%, which was significantlyChiingah. er than the overall level of 1.4% in China
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