This article compares the potential of four transportation policies designed to reduce greenhouse gases and pollutant emissions in urban areas. The policies analyzed include both pricing policies aimed to increase car costs and fleet renovation. The study applies a land-use and transportation interaction model combined with an optimization algorithm that provides the optimal design of each policy. The results show how each policy, or combination of policies, affects long-term modal share, trip length, trip times, and vehicle kilometers traveled. Those are the explanatory variables for modeling the emissions at a city level. The policies are tested in the metropolitan area of Madrid (Spain). The evaluation framework allows testing the effectiveness of these policies for various future policy measures at two different geographical scales. The impact of a fuel tax and a major vehicle fleet renewal are simulated for the whole Madrid region. Policy packages including a congestion (road) charge and increased parking fees are tested only in the central business district of the city. The results of the study show that of all the policy packages tested involving higher fuel prices are expected to have the greatest effect on achieving the environmental targets. They also show that technological improvements in the vehicle fleet are insufficient to reduce CO2 emissions levels per se, although they do contribute to a decrease in pollutant emissions owing to improved engine performance and reduced gas consumption and emissions when used together with other policy instruments. Finally, local measures such as road pricing and parking fees fulfill local objectives in the central area of the city but cause negative externalities on the surrounding areas.