4.7 Article

Testing the impact of renewable energy and oil price on carbon emission intensity in China's transportation sector

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SPRINGER HEIDELBERG
DOI: 10.1007/s11356-023-28053-3

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Autoregressive distributed lag model; Oil price; Economic complexity; Renewable energy; Transport sector

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As the world's largest carbon emitter, China needs to transition to a low-carbon economy, particularly in its transportation sector, to achieve carbon neutrality by 2050. A study utilizing the bootstrap autoregressive distributed lag model found that increasing oil prices reduce carbon emission intensity in both the short and long run. Additionally, higher levels of renewable energy and economic complexity contribute to a decrease in carbon emission intensity, while non-renewable energy has a positive impact on carbon emission intensity.
As the largest carbon emitter in the world, with its transportation sector contributing the largest shares of its emission, the need for a low-carbon transition economy has become a policy agenda for China because in order to reach carbon neutrality by 2050, lowering the intensity of carbon emissions in the transportation sector will be crucial. In this regard, we used the bootstrap autoregressive distributed lag model to explore the impact of clean energy and oil prices on the intensity of carbon emissions in China's transportation sector. The study found that an increase in oil prices decreases the intensity of carbon emissions in the short and long run. Similarly, an increase in the level of renewable energy and economic complexity declines the intensity of carbon emissions in the transportation sector. On the contrary, the research demonstrates that non-renewable energy contributes positively to carbon emission intensity. Therefore, the authorities must promote green technology to neutralize the transportation system's detrimental effects on China's environmental quality. The implications for successfully promoting carbon emission intensity mitigation in the transportation sector are examined in the conclusion.

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