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.
Keywords: Autoregressive distributed lag model; Economic complexity; Oil price; Renewable energy; Transport sector.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.