Global shipping generates substantial emissions that can adversely affect air quality in port cities, yet the detectability of ship-related pollution by urban monitoring locations remains insufficiently understood. This study aims to identify the meteorological conditions under which ship exhaust plumes can be detected at a stationary air-quality monitoring station located 1.4 km from the Port of Klaipeda. Night-time particulate matter and NO measurements from an AQMesh station were synchronized with Automatic Identification System (AIS) ship-tracking data, and an artificial neural network was applied to determine the environmental parameters most strongly associated with detectable pollution peaks. Kernel Density Estimation (KDE) was used to map the spatial patterns of ship activity by vessel type. The results indicate that plume detection is most likely to be detected with moderate wind speeds (8–12.5 m/s for PM and 7.5–9.6 m/s for NO), elevated humidity (>84%), and higher-pressure ranges for particulate matter. Warmer night-time conditions further enhance pollutant transport by reducing atmospheric stability. KDE analysis shows that potential pollutant accumulation zones differ by vessel type, with the most intense hotspots forming near anchorage locations rather than along transit routes. Overall, the findings demonstrate that ship-related pollution can be detected at distances exceeding 1 km under specific meteorological conditions and highlight the parameters that most strongly govern plume penetration into the urban environment.