Urban Transport Policies and Emission Reduction Strategies in Riyadh:Insights from a Multi-Agent Simulation

Rapid urban growth in Riyadh is expected to intensify congestion, energy demand, and transport-related emissions, raising the stakes for policy choices that deliver quantifiable results. We develop and apply a calibrated multi-agent model of Riyadh (METROPOLIS2) to compare three levers—targeted electric-vehicle incentives, improved metro accessibility, and telework adoption—and to quantify their effects on traffic, emissions, and traveler welfare. Beyond CO₂, we estimate local pollutants (NOₓ and PM₂.₅) using speed-dependent emission factors, and find that distance-targeted incen􀆟ves yield larger simulated reductions than uniform EV uptake. At 20% EV share in 2030, targeted incentives reduce CO₂ by 32.3% (vs 20.1% under uniform incentives). For the local pollutants, the corresponding reduction is 26% for NOₓ and 26% for PM₂.₅ (vs 15% for each under uniform incentives). Enhancing first–lastmile metro access cuts annual CO₂ emissions by just over 1 million tonnes and travel times by about 20 percent, while reducing NOₓ by 16.5% (≈4,451 kg) and PM₂.₅ by 16.6 percent (≈451 kg) per weekday across the network. Telework at 20 percent adoption lowers car use by 5.8 percent and per-trip emissions by 4.6 percent, though non-work trip rebound can erode gains. While these estimates are simulation-based and should be treated as indicative, the results suggest a portfolio logic: concentrate electrification among the city’s highest-mileage drivers, treat metro accessibility as an emissions and air-quality instrument, and pair telework with demand management to preserve environmental gains.