Pathway analysis of private car CO2 emissions: an individual car-use perspective

How to reduce CO 2 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 CO 2 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 CO 2 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.