This dataset provides the simulation-based results for Figures 8 and 9 of the discussion paper "Urban Transport Policies and Emission Reduction Strategies in Riyadh: Insights from a Multi-Agent Simulation" (2026). Using the METROPOLIS2 multi-agent model, the dataset compares uniform vs. distance-targeted EV incentives at 30% fleet penetration, aligned with Riyadh's 2030 targets. Targeted adoption achieves a 44.8% CO₂ reduction compared to 30.1% under uniform adoption. Results also show that the same reduction can be achieved with up to 34.4% fewer vehicle switches through distance-based targeting.