The global transition towards electric mobility presents both opportunities and challenges for public finance and urban transport systems. One critical concern is the projected decline in energy tax revenues, which have traditionally been a major source of government funding. In Germany, the tax revenue per kilometre driven is expected to drop from €0.03/km for internal combustion engine vehicles to €0.005/km for electric vehicles. This shift translates into an estimated loss of €12.5 billion in fuel tax revenue nationwide by 2030. Simultaneously, traffic congestion remains a persistent issue in urban centres, imposing economic and environmental costs. This paper investigates whether congestion pricing can serve as a sustainable and welfare-enhancing alternative to compensate for the declining revenues from fuel taxation, while also addressing traffic inefficiencies and emissions.

Using the greater Berlin area as a case study, we estimate regional energy tax losses under dynamic electric vehicle adoption scenarios by 2030. We then simulate a dynamic congestion toll using the multi-agent transport simulation software MATSim. The simulation analyses three scenarios: a Reference case without tolls, a Congestion case with pricing based on real-time traffic, and a Congestion+ case combining tolls with expanded road capacity and subsidised public transport.

Our findings show that congestion tolls generate substantial revenues—€784 million in the Congestion scenario and €615 million in Congestion+—effectively compensating the simulated energy tax loss of €671.6 million in the studied region. From a mobility perspective, around 3% of car trips are dropped or shifted to public transport, and about 60% of drivers adjust departure times to avoid peak-hour tolls, resulting in a 28% reduction in traffic delays and over 5% lower CO₂ emissions.

Beyond fiscal and environmental gains, the policy also delivers a welfare surplus. The population’s aggregate utility loss due to the introduction of the toll is estimated at €191 million, significantly lower than the toll revenue, creating space for redistribution. Our distributional analysis shows the policy can be progressive: high-income groups contribute disproportionately to toll revenue, while investments in infrastructure and public transport benefit lower-income residents. Regarding the horizontal distribution effects, residents in outer boroughs face higher utility losses, indicating the need for targeted redistribution measures such as lump-sum transfers or improved public transport connectivity.

This study confirms that congestion pricing can play a vital role in offsetting fiscal losses from e-mobility transitions while delivering broad societal benefits. Given its replicable methodology and the relevance of its findings to many countries facing similar fiscal and transport challenges, our approach provides a valuable blueprint for policymakers and stakeholders.