Pathway analysis of private car CO2 emissions: an individual car-use perspective - Zheng, Ji (Frontiers in Future Transportation, 2025)
How to reduce CO2 emissions from private vehicles with low efficiency and excessive growth is a global challenge for big cities. This study conducted a questionnaire survey for private cars in Beijing in 2019 and developed a path analysis model to uncover the influencing mechanisms of vehicle attributes and driver socio-demographics, travel patterns, and driving behaviors on private car CO2 emissions. The results show that fuel consumption per 100 km (FC), engine displacement (Engine), and annual mileage (Mileage_y) have a positive direct effect on CO2 emissions (E). Driver’s characteristics, including age (Age_d), education level (Edu_d), monthly personal income (Income_p), family size (Pop), whether there are elderly people or children in the family (EK), and eco-driving behaviors (Eco) influence E completely indirectly. The total influence in absolute value is, in order, Mileage_y (0.934) > Engine (0.224) > FC (0.185) > Pop (0.078) > EK (0.032) > Income_p (0.018) > Eco (−0.010) > Edu_d (0.002) > Age_d (−0.001). Higher income and education levels are associated with higher emissions, warranting targeted policy interventions for carbon mitigation.