Mining travel carbon emission patterns and evaluating equity in public transportation based on smart card data

Against rapid urbanization, ensuring carbon emission equity is critical for inclusive sustainable development. Using Beijing's smart card data, we develop a bottom-up accounting model to quantify travel carbon emissions in public transportation at the Traffic Analysis Zone scale, assessing equity through three dimensions: vertical (Palma ratio), horizontal (Gini coefficient), and spatial (Carbon Burden Index). Results show that the stratification and efficiency differences in public transportation services drive emission characteristics. Subway travel time is approximately twice that of buses, and the travel distance is 2.5–3.4 times longer, resulting in 80.9% higher per capita emissions. Weekdays, weekends, and holidays reflect distinct carbon emission patterns driven by ‘commute-driven,’ ‘mixed demand,’ and ‘leisure-oriented’ travel behaviors, respectively. During weekday peak periods, low-income groups bear nearly half of the travel emission burden, with per capita emissions 69% higher than those of high-income groups. Marginalized groups bear hidden environmental costs for urban economic efficiency. Commuting demand and jobs-housing spatial mismatches exacerbate equity disparities. Substituting short trips with shared bikes reduces emissions by 2%. The study reveals the socioeconomic and spatial differentiation mechanisms of urban public transportation travel carbon emissions. These findings provide a scientific basis for formulating low-carbon transportation policies that balance equity and efficiency.