Assessing the effectiveness of demand-management-technology in reducing CO

Urban passenger transportation, as a pivotal element of the transportation system, accounts for over 40% of total carbon emissions from road transport. Consequently, mitigating carbon emissions in this sector is a crucial strategy for attaining carbon peak targets. This study centers on Lanzhou, a representative transportation hub city in China, and develops a dynamic model based on the Passenger Urban Transportation Carbon Emission System (PCES) framework to simulate emissions under three categories of interventions: Demand, Management, and Technology (DMT). The investigation analyzes the temporal trends and underlying mechanisms influencing these emissions. Results reveal that total carbon emissions from passenger transportation in Lanzhou are projected to rise until 2030, with a marked deceleration in growth rate anticipated after 2028. The carbon reduction efficacy among different interventions varies significantly, with fuel vehicle restrictions and management policies demonstrating the greatest effectiveness in conserving energy and reducing emissions. Nevertheless, continuous technological innovation and strategic policy guidance remain indispensable, especially to enhance public transportation usage and reduce overall energy consumption. Furthermore, the integration of multiple strategies accelerates progress toward achieving the 'carbon peak' objective within the passenger transportation sector. Simulation outcomes from the combined DMT scenario exhibit superior explanatory power regarding carbon reduction effects within the PCES framework compared to individual measures. Moreover, this research substantiates the utility of the PCES framework in steering the low-carbon development pathway of urban passenger transportation.