Spatiotemporal Operational Emissions Associated With Light-, Medium-, and Heavy-Duty Transportation Electrification

The spatiotemporal distribution of pollutants plays a significant role on their impact on ecosystems and human health. This article presents a strategy for calculating spatiotemporal operational emissions (OEs) of road transportation and the electric grid to quantify the impact of transportation electrification. Emissions from internal combustion engine vehicles and offset emissions from electric vehicles (EVs) are considered using actual transportation networks and travel data. The spatiotemporal charging demand for light-, medium-, and heavy-duty EVs is estimated in a behaviorally informed way and mapped to electrical buses within the power grid and an ac optimal power flow with unit commitment is solved. The methodology is demonstrated with ten scenarios simulated on a grid with 7000 electrical buses geographically sited in Texas, created with actual generator data for the 2020 grid, and a future case, including anticipated generator updates by 2030. Results show overall transportation emission reductions in daily OEs of up to 20%–30% for all pollutants studied, outweighing the increase in emissions from the electric grid. Considering emissions on an hourly basis, up to approximately 1000% reduction in CO emissions is observed.