Estimating Worst-Case Carbon Monoxide Exposure Uncertainty Using Deterministic and Monte Carlo Methods Southward from UPN Seturan Intersection, Yogyakarta - Yusuf, Yusmardhany; Dwi Amalia; Alfiana Adhitasari; Kadek Chelsy Zahra; Anggita Nur Widyastuti (Jurnal Serambi Engineering, 2026)
Carbon Monoxide (CO) is a critical urban pollutant with severe health implications, primarily driven by vehicular emissions in high-density traffic zones. This study investigates the spatial dispersion of CO along the main road located towards the south of the Universitas Pembangunan Nasional (UPN) Seturan Depok intersection, extending 150 meters to the south (Jalan Seturan Raya) in Condongcatur Sleman Yogyakarta, aligning with specific sampling positions located directly amidst the traffic stream to capture immediate exposure levels. This research addresses the limitations of deterministic approaches based on the advection-diffusion equation, which often fail to fully account for the random fluctuations of atmospheric turbulence inherent in complex urban environments. To address this, the study integrates direct field measurements with a probabilistic algorithm that treats the diffusivity coefficient as a random variable governed by the Peclet number. The results demonstrate that the Monte Carlo simulation achieves a predictive accuracy (R2 = 0.9393) which, while slightly lower than the analytical model (R2 = 0.9522), remains highly robust as it successfully accounts for the chaotic, random nature of real world atmospheric turbulence. Furthermore, the simulation identifies a critical high-risk zone within 40 meters of the source where concentrations consistently exceed 35 mg/m³ due to diffusion-dominated transport.