Field Evaluation of CALINE4-Based Carbon Monoxide Dispersion Modeling at a Signalized Intersection in Ulaanbaatar, Mongolia

Abstract

Urban intersections are important hot spots of traffic–related air pollution, particularly in places where signal delays and idling increase vehicle emissions. This study evaluates near–road carbon monoxide (CO) concentrations at a signalized four–leg intersection in Ulaanbaatar, Mongolia, by combining field measurements with CALINE4 dispersion modeling. CO concentrations were measured at four receptor locations during two observation periods, 9:00–10:00 and 15:00–16:00. Hourly traffic volume, fleet composition, microclimatic conditions, and receptor geometry were used as model inputs. A fleet-weighted CO emission factor of 12.5 g veh−1 mile−1, adjusted for vehicle age and local stop-and–go traffic conditions, was applied as the base case, while 11.5 and 13.5 g veh−1 mile−1 were tested as sensitivity scenarios. The base case CALINE4 results reproduced the measured spatial pattern reasonably well, with overall performance indicators of r2 = 0.759, FB = −0.006, NMSE = 0.010, RMSE = 0.400 ppm, and MAE = 0.325 ppm. Sensitivity analysis showed that higher emission factors increased predicted CO concentrations, although differences among scenarios were limited. The results suggest that the MOVES–CALINE4 modeling chain is suitable for preliminary screening level CO hot–spot assessment at congested intersections in Ulaanbaatar.