Modeling and Analysis of Carbon Emissions Throughout Lifecycle of Electric Vehicles Considering Dynamic Carbon Emission Factors

Amidst the global strategic transition towards low-carbon energy systems, electric vehicles (EVs) are pivotal for achieving deep decarbonization within the transportation sector. Consequently, enhancing the scientific rigor and precision of their life-cycle carbon footprint assessments is of paramount importance. Addressing the limitations of existing research, notably ambiguous assessment boundaries and the omission of dynamic coupling characteristics, this study develops a dynamic regional-level life-cycle carbon footprint assessment model for EVs that incorporates time-variant carbon emission factors. The methodology first delineates system boundaries based on established life-cycle assessment (LCA) principles, establishing a comprehensive analytical framework encompassing power battery production, vehicle manufacturing, operational use, and end-of-life recycling. Subsequently, inventory analysis is employed to model carbon emissions during the production and recycling phases. Crucially, for the operational phase, we introduce a novel source–load synergistic optimization approach integrating dynamic carbon intensity tracking. This is achieved by formulating a low-carbon dispatch model that accounts for power grid security constraints and the spatiotemporal distribution of EVs, thereby enabling the calculation of dynamic nodal carbon intensities and consequential EV emissions. Finally, data from these distinct stages are integrated to construct a holistic life-cycle carbon accounting system. Our results, based on a typical regional grid scenario, reveal that indirect carbon emissions during the operational phase contribute 75.1% of the total life-cycle emissions, substantially outweighing contributions from production (23.4%) and recycling (1.5%). This underscores the significant carbon mitigation leverage of the use phase and validates the efficacy of our dynamic carbon intensity model in improving the accuracy of regional-level EV carbon accounting.