A ship emission modeling system with scenario capabilities. (December 2021)

• Record Type: Journal Article
• Authors: Schwarzkopf, Daniel A.; Petrik, Ronny; Matthias, Volker; Quante, Markus; Majamäki, Elisa; Jalkanen, Jukka-Pekka
• Is Part Of: Atmospheric environment. Volume 12(2021)
• Publication Date: 2021-12
• Subjects: Shipping emissions -- Emission inventory -- AIS -- MoSES -- Emission modeling
• DOI: 10.1016/j.aeaoa.2021.100132
• Languages: English
• ISSNs: 2590-1621

Abstract

Abstract: A bottom-up modular ship emission modeling system (MoSES) is presented that calculates highly spatiotemporally resolved ship exhaust emissions, based on ship position data recorded from the automatic identification system. MoSES is built in a modularized architecture, which guarantees good expandability. Several ship-type specific methods have been developed for estimating missing ship characteristics that are important for ship emission modeling, such as the gross tonnage, main or auxiliary engine power, engine rating or the service speed, since these characteristics are often not available in present data. Additionally, most recent emission factors for sulfate and black carbon were derived from literature that cover formerly neglected low-sulfur fuels. MoSES is demonstrated by the creation of an emissions inventory for the North and Baltic Sea region, but it may readily be applied to other regions as well. The results were evaluated and compared to ship emission data calculated with the established Ship Traffic Assessment Model (STEAM 3). A good agreement with the daily shipping activity and CO2 emissions was found, although fewer emissions were calculated with MoSES for SO2, SO4 and NOX due to differences in the method for calculating the power consumption, the assumed fuel sulfur content, and applied emission factors. Furthermore, the impact of different emissions factors and uncertainties due to missing ship characteristics has been investigated. Additionally, extensive functionalities for scenario generation were implemented that allow the modification of a ship fleet in a model run. A filtering algorithm was developed to support scenario generation by the creation of sub-emission inventories. These contain only emissions of ships moving between two specific harbors or points of interest. This feature is demonstrated for the ship traffic between the five busiest harbors in the North Sea among each other, and between the English Channel. The scenario capability of the model is exemplified on a case based on sub-emission inventories, that investigates a decreased trade volume between representative ports of mainland Europe and the United Kingdom. Highlights: This new ship emission model has a particular versatility for scenario generation. Several Ship-type specific methods for estimating ship characteristics were developed. Most recent ship emission factors for sulfate and mineral ash were derived. In a comparison with the established Ship Traffic Assessment Model (STEAM), a good agreement between both models was found.