Accurately estimating ship emissions inventories in port areas provides scientific assurance for the building of green ports.
Ship emissions inventories using automated identification system (AIS) data are widely used to predict and estimate ship pollutant emissions in the seas and rivers for their high spatiotemporal resolution, but they still have considerable uncertainties.
Over the past decade, many studies have focused on addressing these uncertainties, and improving the accuracy of ship emissions inventories has constantly been a hot issue. The most notable sources of uncertainty in the ship emissions inventories using AIS data are the uncertainties related to model input data, prediction of propulsion power, emission factor and fuel information.
Yun Un Hyok, a section head at the Faculty of Shipbuilding and Ocean Engineering, has proposed an improved load-factor-based power model considering the impact of hull shape on the ship’s resistance, and applied it to the estimation of ship pollutant emissions in a certain port area.
The total ship emissions estimated using the proposed method were 1.27×104, 6.33×104, 1.91×103, 1.76×103, 3.11×103 and 7.52×103t of SO2, NOx, PM10, PM2.5, HC and CO, respectively.
According to the results of comparison with traditional power models, the total emissions from ocean going vessels (OGVs) in the sailing mode was 89% and 104% of those using Propeller Law and Admiralty Law power models, respectively. These differences were greater for NOx than for other pollutant species and also greater for bulk carriers and tankers than for other subtypes of vessels.
Although the proposed improved load-factor-based power model still has some uncertainties, it is believed to be worth employing to estimate regional ship emissions inventories in the future, because it can accurately estimate ship emissions inventories by analyzing the impact of hull shape on ship resistance with few ship parameters.