Improved Ship Emission Model Considering Load Factor‐Based Power and Hull Shape: Implication in a Chinese Port Cluster

Abstract Shipping emissions are a major source of atmospheric pollutants globally. Accurate ship emission inventories are the key for developing pollution control strategies, but simulating the operating power of a ship under different navigational conditions is a challenge in ship emission estimation. Here, to improve the accuracy of the traditional power model and to establish framework for ship emissions in the port area, an improved load factor‐based power model considering the impact of hull shape on the ship's resistance was proposed and applied to estimate the ship pollutant emissions. A series of data preprocessing methods were constructed based on automated identification system (AIS) high‐precision measured data, including filling gaps and outliers, identifying vessel's operating mode with geofencing, and assigning fuel information by navigation area. The proposed power model and the AIS data preprocessing method were applied to estimate the ship pollutant emissions within Qingdao Port, China, in 2020. The total ship emissions were 1.27 × 10 4 , 6.33 × 10 4 , 1.91 × 10 3 , 1.76 × 10 3 , 3.11 × 10 3 , and 7.52 × 10 3 tone for SO 2 , NO X , PM 10 , PM 2.5 , HC, and CO, respectively. As for emissions from ocean‐going vessels, the proposed power model estimation was 3.9% lower than the propeller law power model and 2.4% higher than the admiralty law power model. We highlight that the proposed power model could be of large benefit in accurately evaluating regional ship emissions in the future, which can provide scientific assurance for ship emission inventory construction and green port development.