Quantifying the impact of U.S. electric vehicle sales on light-duty vehicle fleet CO_2 emissions using a novel agent-based simulation

摘要

When understanding the effect of new technology on any sector, it is essential to have a quantitative understanding of the sector's "turnover rate": the sector-wide inertia based on buying and scrappage rates of existing products. To assess sector-wide inertia in the transportation sector, this paper develops an agent-based stochastic simulation for characterization of the U.S. light-duty (LD) vehicle fleet, applying the output to quantifying the effect of electric vehicles sales on the greenhouse gas (GHG) emissions of the fleet as a whole. Such a model framework allows us to study transportation policies that might affect scrappage rates, vehicle types, and car sharing adoption and comparing them to different exogenous electric vehicle adoption scenarios. Overall, we find that the impact of scrappage rate on emissions is small but could have synergistic interactions with our exogenous electric vehicle adoption scenarios. Furthermore, the impact of restricting vehicle type is negligible. Grid decarbonization has a large effect, roughly the same as doubling EV saturation. Lastly, mandating shared fleet electrification could have the same effect as decarbonization.