Exploring the link between CO2 emissions, economic growth, urbanization and transportation infrastructure in China: Evidence from the ARDL model

As the challenge of global climate change becomes increasingly severe, carbon emissions have become a key constraint on sustainable development. This study aims to explore the impact of economic growth, urbanization, and transportation infrastructure on carbon emissions in China. Using time-series data from 1977 to 2022, the study employs the Autoregressive Distributed Lag (ARDL) model to analyze the short-term and long-term dynamic relationships between these variables, and the Vector Error Correction Model (VECM) to assess the causal relationships. The ARDL regression results show that, in the short run, economic growth has an immediate significant positive effect on carbon emissions, while urbanization exhibits mixed lagged effects—initially increasing and later reducing emissions. Transportation infrastructure has no immediate impact but shows a significant emission-reducing effect through its lagged terms. In the long run, economic growth exhibits an insignificant negative impact on emissions, urbanization has an insignificant positive effect, and the expansion of transportation infrastructure is positively associated with increased carbon emissions. Granger causality analysis reveals that carbon emissions and urbanization exhibit a bidirectional causal relationship in the short run. In the long run, carbon emissions are mutually causal with economic growth, and are also unidirectionally influenced by transportation infrastructure. This study emphasizes the importance of developing an integrated policy framework to balance economic growth, urbanization, and transportation infrastructure with environmental sustainability.