Bottom-up modelling is used frequently to estimate emissions produced by seagoing vessels, and the accuracy of modelling is dependent on the data the model is trained with. Observational studies can be used to increase the model accuracy. Here we compared data from two measuring campaigns conducted on board ships that use Liquefied Natural Gas (LNG) as primary fuel in internal combustion engines (ICE) in a diesel-electric setup with values obtained from the Ship Traffic Emission Assessment Model (STEAM).The power demand for propulsion calculated using Automatic Identification System (AIS) data matched observations reasonably. The root mean square error between the modelled and observed power demand was 759–914 kW (28.6–34.5%) for the measured ropax vessel and 1869–1916 kW (16.7–17.1%) for the large cruise vessel over four voyages while the ships were underway. The discrepancy is largely explained by the auxiliary power demand, which was 4 times higher on the large cruise vessel than the model prediction.Using meteorological data to estimate the increase of resistance did not improve the goodness of fit between modelled and observed engine power demand. STEAM model's base-specific fuel consumption calculation method fits observed values reasonably when the engine load is over 50%, but ICEs used in constant speed mode have increased consumption at lower engine loads compared to variable speed ICEs.The share of pilot fuel of total energy consumption was found to play a significant role in the emission factors for measured exhaust gas compounds. More accurate functions to model fuel consumption and emissions were derived using the observed data.