Abstract
Abstract. Estimating the impact of ship emissions on local air quality is a topic of high relevance, especially in large harbor cities. For chemistry-transport modeling studies, the initial plume rise and dispersion play a crucial role for the distribution of pollutants into vertical model layers. This study aims at parameterizing the vertical downward dispersion in the near field of a prototype cruise ship, depending on several meteorological and technical input parameters. By using the microscale chemistry, transport and stream model (MITRAS), a parameterization scheme was developed to calculate the downward dispersion, i.e., the fraction of emissions, which will be dispersed below stack height. This represents the local concentration in the vicinity of the ship. Cases with and without considering the obstacle effect of the ship have been compared. Wind speed and ship size were found to be the strongest factors influencing the downward dispersion, which can reach values up to 55 % at high wind speed and lateral wind. This compares to 31 % in the case where the obstacle effect was not considered and shows the importance of obstacle effects when assessing the ground-level pollution situation in ports.
Highlights
Ship emissions are among the harmful anthropogenic influences on air quality and human health, especially in big harbor cities
The following subsections describe the results of singleand multi-parameter regressions that were performed in order to describe the relationship between the downward dispersion and the input parameters
A ship plume modeling study was performed with the microscale numerical model (MITRAS) to investigate the downward dispersion of the exhaust in close proximity to a modeled cruise ship
Summary
Ship emissions are among the harmful anthropogenic influences on air quality and human health, especially in big harbor cities. Many ship plume modeling studies focus on global- or regional-scale plume dispersion, chemistry and their parametrization (e.g., Aksoyoglu et al, 2016; Huszar et al, 2010; Vinken et al, 2011). For emission calculation, they can make use of global (Corbett et al, 2007; Wang et al, 2008) or regional (Aulinger et al, 2016; Jalkanen et al, 2009, 2012) shipping emission inventories. Increasing trends in ship emissions in northern Europe have been modeled for the North Sea (Matthias et al, 2016) and Baltic Sea (Karl et al, 2019), and the efficiency of emission reduction measures has been evaluated
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