A Calculation Algorithm for Ship Pollutant Gas Emissions and Diffusions Based on Real-Time Meteorological Conditions and Its Application

Xianhua Wu ()
Additional contact information
Xianhua Wu: Shanghai Maritime University, School of Economics and Management

Chapter 3 in Environmental Disaster in China, 2026, pp 53-77 from Springer

Abstract: Abstract Most literature focusing on the issue of ship pollutant emission and diffusion is based on static meteorological conditions. The relevant literature seldom analyzes the emission and diffusion of ship pollutant gas according to real-time meteorological data when wind direction, wind speed and other meteorological conditions have changed. This paper proposes a fast translational diffusion algorithm and a model by the algorithm, verified with the ships and meteorological data of Huangpu River in Shanghai. First, CO2 emissions were estimated using the actual speed of the ship engine changed under the influence of variable wind, and simulation analysis was performed to the scenario of hourly diffusions. The research findings are as follows: (1) In comparison with the traditional algorithms, the fast algorithm can significantly improve calculation efficiency, save calculation time and achieve the long-distance and long-time parallel calculation of multiple ships. (2) As proven by the empirical research using the ships on Huangpu River in Shanghai, the maximum difference of CO2 emissions is 34.5%, 36.85% and 19.97% respectively after upwind, downwind and real-time meteorological conditions are taken into account. The research finding indicates that wind direction changes have a greater impact on the carbon emission of ships.

Keywords: Variable wind direction; Ship; Emission and diffusion; Fast algorithm; Huangpu River; AIS data (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-92-0910-1_3

Ordering information: This item can be ordered from
http://www.springer.com/9789819209101

DOI: 10.1007/978-981-92-0910-1_3

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().