Urban mobility-related emissions are an increasing concern in rapidly expanding cities, highlighting the need for robust methods to assess and mitigate their environmental impact. This study develops a multi-agent model to estimate emissions in Riyadh city, which serves as the primary case study. Specifically, it employs the dynamic traffic simulator METROPOLIS2 to examine mobility-related emissions and their environmental implications. The framework integrates a cleaned road network, an origin-destination matrix covering 162 zones with node-zone assignment, and a simplified metro layer. The model is calibrated to replicate observed congestion patterns and validated through day-to-day dynamics, including convergence in departure and arrival times, route reallocation under congestion, and the co-movement of distance and emissions under a homogeneous fleet. Generalized cost and emissions indicators are reported at both the trip and network levels. The contribution is methodological: a transparent, reproducible baseline for Riyadh that supports credible scenario evaluation.
