Simulation of transit-oriented development impacts on travel carbon and air pollutant emissions

Rapid motorization poses challenges to transport decarbonization and air quality in China. The built environment shapes travel behavior, and transit-oriented development (TOD) has emerged as a key strategy for low-carbon mobility. This study develops a predictive model that links built environment indicators to travel modal shares and associated emissions. The model identifies the effects of 14 indicators on six travel modes: private cars, buses, metros, electric bikes, shared bikes, and walking, and simulates a level of integration (LOI) to represent the built environment attractiveness for different travel modes. Based on the LOI, travel modal shares are predicted and translated into carbon and air pollutant emissions using a bottom-up approach. The model is applied to three metro-centered precincts with distinct urban forms in Nanjing. The results reveal substantial differences in travel emissions across urban forms: in the car-dependent suburban precinct, the private car modal share reaches 38.7%, while in the transit-rich historic core it is 15.0%, leading to per capita annual carbon dioxide (CO₂) emissions of 857 kg and 429 kg, respectively. Most air pollutant emissions follow trends similar to CO₂, except for sulfur dioxide (SO₂), which exhibits higher per capita emissions in the historic core due to larger shares of electricity-based modes. A TOD retrofitting scenario for the suburban precinct indicates that targeted interventions can reduce travel CO₂ emissions by 6.1%, and air pollutant emissions by 2.8%–6.4%. Overall, the proposed model provides a tool to assess travel-related emissions across contrasting urban forms and identify TOD pathways for low-carbon travel and improved air quality.