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Shipping is a major source of carbon emissions and faces an urgent need for decarbonization. Research on vessel carbon emissions not only characterizes regional emission patterns but also provides critical evidence for targeted mitigation policies and optimized maritime management. This study quantifies vessel carbon emissions in the Port of New York and New Jersey from February to November 2023 using Automatic Identification System (AIS) data combined with the STEAM model. An activity-weighted spatial allocation method was applied to distribute emissions across 100 m × 100 m grids. Emission characteristics were analyzed across four dimensions: vessel type, operational state, temporal variation, and spatial distribution. Results show that total emissions during the study period reached approximately 136,701.8 t, with container ships contributing 62.3% of the total. Berthing operations were identified as the dominant emission source, accounting for 73.4% of total emissions, followed by tugboats and cargo vessels. Temporally, emissions peaked in October (10.8%) and were lowest in February (8.8%), reflecting variations in trade intensity and seasonal weather conditions. Spatially, emissions exhibited strong clustering around terminal berths. A sensitivity analysis was performed to assess the robustness of the emission estimates. When the load factor (LF) varied by ±10%, total emissions changed by only ±1.85%, indicating that the results are highly stable and robust. This limited variation arises from the dominance of berthing operations with relatively steady auxiliary loads and the application of the constraint LF ≤ 1, which prevents unrealistic overloading. These findings offer indicative insights that can inform port-level emission management and serve as a reference for future low-carbon policy development. Full article