The purpose of this paper is to design a route and speed optimization method to simultaneously reduce sailing cost and time, considering Emission Control Areas (ECAs) regulations and weather conditions. To solve it, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was used to find the Pareto-optimal set, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to find the trade-off solution from the Pareto-optimal set. The proposed model was then applied to a service route around the US Coast, based on different fuel prices in ECAs. The results show that the proposed method can reduce the total sailing cost and time compared with other methods, and can help shipping companies effectively cope with fuel price fluctuations. Moreover, we also determined the best time interval for changing ship route and speed in terms of minimizing the sailing cost.

Ship exhaust gas has become an essential source of air pollution in recent years. To assess the impact of ship exhaust gas on the atmospheric environment and human health, this paper studies the problem of ship exhaust gas diffusion in the port area. According to automatic identification system (AIS) data, ship exhaust gas is estimated based on the bottom-up method, and the result of emission calculation is entered into a Gaussian puff model to calculate the superposition of the diffusion of gaseous pollutants from multiple ships. In addition, the results of a case study of the diffusion of ship exhaust gas in the western area of Shenzhen Port in China show that the distribution of the NO₂ concentration in the studied area is not stable, the diffusion of exhaust gas from multiple ships mainly affects some areas near large ship berths at night, and there is a small impact on the whole study area. This lays a foundation for monitoring and treating the atmospheric environment in the port area.