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. In this paper, 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 we find that distance-targeted incentives 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- and last-mile metro access cuts annual CO2 emissions by just over 1 million tonnes and travel times by about 20%, while reducing NOx by 16.5% (≈4,451 kg) and PM2.5 by 16.6% (≈451 kg) per weekday across the network.
