This study addresses the challenge of efficient monitoring of ship exhaust emissions in inland waterways by proposing an optimized approach to selecting bridge-based monitoring points. A micro-scale Computational Fluid Dynamics (CFD) model was developed to simulate interactions between ship exhaust plumes and river-crossing bridges, enabling precise predictions of dispersion patterns and concentrations. A numerical model incorporating pre-defined monitoring points and local environmental data was used to evaluate the influence of wind, water levels, and ship dynamics on plume behavior. The model's feasibility was validated through on-site UAV experiments. Results showed that plume dispersion is significantly affected by wind direction, wind speed, water level, and ship speed. Under extreme low water levels, the proposed three-point monitoring setup achieved a detection probability of 61.47 %, with performance improving as water levels increased. This study enhances monitoring accuracy and efficiency for riverine areas, providing a valuable tool for precise regulation of ship-emitted pollutants and supporting sustainable inland waterway management.