Air Quality Benefits and Tradeoffs from 30% Light-Duty Vehicle Electrification over the Midwest-Great Lakes Region

With the recent advent of automaker production commitments, increasing consumer options, greater affordability, and policy incentives and mandates the United States vehicle fleet is becoming increasingly electric. From an environmental sustainability perspective, the appeal of electric vehicles (EVs) is multifaceted, but largely contingent on the assumption that the net usage of an EV emits less greenhouse gas and fewer air pollutants than an internal combustion engine (ICE) vehicle. Studies have largely borne out this assumption for greenhouse gases, but the net effect of widespread EV adoption on air quality depends on numerous complicating nonlinear factors including the source of electricity used to charge EV batteries, the type, magnitude, and proximity of other emission sources, local-to-regional scale meteorology, and season. With this motivation in mind, we use a chemical transport model, the two-way coupled Community Multi-Scalar Air Quality and Weather Research and Forecasting (CMAQ-WRF) modeling system, to simulate the changes in air quality that result from the instantaneous replacement of 30% of the ICE light-duty vehicle fleet with EVs. We scale tailpipe, refueling infrastructure, and power plant emissions according to ICE vehicle fractional replacement and EV battery charging demands using an open-source emissions remapping algorithm that determines which power plants meet marginal demand needs using a series of weights designed to emulate U.S. grid behavior. Our simulations are run at neighborhood-scale (i.e., 1.3 km2) over a Midwest-Great Lakes domain, and are facilitated by high resolution emission surrogates produced by the Lake Michigan Air Directors Consortium (LADCO) which we process using the Sparse Matrix Operator Kernel Emissions (SMOKE) model. We compare our sensitivity experiments to baseline simulations to determine the changes in both primary and secondary pollutant concentrations. We contextualize these changes by computing the exposure and public health impacts across health endpoints using community standard health response functions. Analyzing the geospatial shift in pollutants provides a better understanding of the benefits and tradeoffs of an EV transition, and provides decision-makers with context on how EV adoption impacts local air quality.