In this paper, a novel modeling framework is proposed for the estimation of optimal CO2 emission taxes for urban traffic. The framework is based on a bi-level model comprising a combined equilibrium model with elastic demand and a \\\\pollution taxes\\\\ (PTs) estimation model based on vehicle kilometers traveled and emissions produced. A bi-level optimization problem is proposed for the PT estimation model (PTM) in order to provide the minimum price which reduces emissions generated in an urban area to a desired value dependent on the environmental goals. To solve this problem, the Regula Falsi method is proposed
and it exhibits a high enough rate of convergence. Two tests using the Nguyen and Dupuis network and Barcelona network (Spain) have been performed to test the convergence of our resolution method and the applicability of the proposal over networks with different sizes. The results are very promising and allow the implicit definition of the behavior of users against different PT prices
