Optimal Vehicle Trips (Cache County)

This paper develops a conceptual model of optimal vehicle trips in a region plagued by weather-dependent, mobile-source air pollution, and numerically estimates optimal trips for one of the nation's perennially worst air quality regions in terms of short-term particulate matter. Based upon data-driven parameters and damage estimates, our numerical model generates steady-state values for region-wide vehicle trips and associated PM2.5 concentrations along with their corresponding optimal time paths. Our dataset includes a host of pertinent weather variables that determine PM2.5 concentrations both independently as well as interacted with vehicle trips. As a result, our empirical model enables us to isolate the conditions under which vehicle travel most affects air pollution levels. Our results suggest that maximizing net social welfare in the presence of mobile-source pollution requires substantial reductions in traditional, emissions-generating vehicle usage on days experiencing critical weather conditions - in the case of our study area, temperature inversions. Because they are socially optimal and targeted solely for days with temperature inversions, the estimated reductions in vehicle usage are substantially larger than those proposed by Moscardini and Caplan (2017) to attain the USEPA's daily standard for particulate matter on an average basis.