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Rulent, J, James, MK, Rameshwaran, P, Jardine, JE, Katavouta, A, Wakelin, S, Jayathilaka, R, Arulananthan, K, Holt, J, Sutton, MA and Artioli, Y 2024 Modelling pollutants transport scenarios based on the X-Press Pearl disaster. Marine Pollution Bulletin, 209. 117129. https://doi.org/10.1016/j.marpolbul.2024.117129
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Rulent et al. - 2024 - Modelling pollutants transport scenarios based on .pdf - Published Version Available under License Creative Commons Attribution. Download (11MB) | Preview |
Abstract/Summary
The MV X-Press Pearl accident near Sri Lanka in May 2021 released several pollutants into the ocean, including 1843.3 t of urea, raising concerns about the impact on the region. This study uses a coupled ocean (NEMO)– biogeochemistry (ERSEM) model to simulate urea dispersion under various scenarios. While it doesn't directly reflect the real accident, it provides insights into the potential impact of similar chemical spills. By adjusting tracer release rates and timing, we assessed their impact on the distribution of the chemical plume. Findings show slower release rates prolong higher urea concentrations, potentially causing phytoplankton blooms, while monsoon conditions significantly affect dispersal patterns. Due to a lack of publicly available urea observations, we used particle tracking experiments validated with data on plastic nurdle beaching. This research shows how a simpler, affordable scenario approach could inform the management of chemical spills without a fully developed operational oceanographic system.
| Item Type: | Publication - Article |
|---|---|
| Additional Keywords: | Passive tracer modelling High resolution Coastal pollution Shipwreck |
| Divisions: | Plymouth Marine Laboratory > National Capability categories > National Capability Modelling Plymouth Marine Laboratory > National Capability categories > Single Centre NC - CLASS (expired) Plymouth Marine Laboratory > Science Areas > Marine System Modelling |
| Depositing User: | S Hawkins |
| Date made live: | 19 Nov 2024 11:19 |
| Last Modified: | 19 Nov 2024 11:19 |
| URI: | https://plymsea.ac.uk/id/eprint/10327 |
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