Towards high-resolution first-best air pollution tolls: An evaluation of regulatory policies and a discussion on long-term user reactions

Abstract

In this paper, we present an approach to calculate high-resolution first-best air pollution tolls with respect to emission cost factors provided by [1]. We link dynamic traffic flows of a multi-agent transport simulation to detailed air pollution emission factors. The monetary equivalent of emissions is internalized in a policy which is then used as a benchmark for evaluating the effects of a regulatory measure — a speed limitation to 30 km/h in the inner city of Munich. The calculated toll, which is equal to simulated marginal costs in terms of individual vehicle attributes and time-dependent traffic states, results in average air pollution costs that are very close to values in the literature. Furthermore, we find that the regulatory measure is considerably less successful in terms of total emission reduction. It reduces emissions of urban travelers too strongly while even increasing the emissions of commuters and freight, both leading to a increase in deadweight loss. That is, the regulatory measure leads to higher market inefficiencies than a “do-nothing” strategy: too high generalized prices for urban travelers, too low generalized prices for commuters and freight. Finally, we discuss the implications of long-term changes in the vehicle fleet as a reaction to the internalization policy. The estimations indicate, however, that the price signal of this policy is not strong enough to significantly change long-term behavior.