Demonstrates reduced traffic density and PM2.5 levels in an Italian road corridor, suggesting effective management strategies.
Dynamic congestion pricing is emerging as a potential approach to contemporarily manage traffic congestion and air quality. However, most toll road pricing strategies tend to rely on traditional solutions such as fixed or variable pricing, leading to suboptimal results in terms of traffic demand or pollution. In this paper, we propose a dynamic congestion pricing algorithm enabling to deal with both traffic congestion and PM2.5 levels reduction. Through a case study based on the SS36 road corridor connecting Milan to Bormio, we show that the proposed approach activates an extra toll fee on 28.26% of observations in 2022, leading to a total charge cost of 14.9€ million. This approach determines a reduction in road traffic density equal to 11.2%, contributing to a percentage drop of PM2.5 levels equal to 0.01%. The results remain robust across alternative specifications, including sensitivity analyses on air quality and traffic speed thresholds, as well as demand price elasticity assumptions. Overall, the paper shows that the dynamic congestion pricing strategy may provide insights for policymakers aiming to target both air quality and traffic management issues.
No takes yet. Share an insight, caveat, or question.
Carenini et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: