A generic operational tool for early warning oil spills - applications to Cartagena bay (Colombia) and the coast of Algarve

• Main Author: Moreira, Diogo Mendes
• Publication Date: 2023
• Format: Master thesis
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10400.1/20609
• topic: Modelação oceânica; Modelação de hidrocarbonetos; Modelos operacionais; Basic; Soma; Baía de Cartagena; Algarve

Over the past 10 years, the record of oil spills per year has decreased, with the majority being of a medium size (between 7 and 700 tonnes) followed by larger scale events, with volumes greater than 700 tonnes. Even though the frequency of spill events has been decreasing, the size and quantity of oil tanker ships have been growing, which will increase the hazard level of a spill. These issues, highly motivate the creation of projects focused on dealing with ocean pollution. This thesis was developed in accordance with two of these projects: "BASIC-Building Resilience in Cartagena Bay" and "ASTRiiS-Atlantic Sustainability Through Remote and In-situ Integrated Solutions". The BASIC project focuses on monitoring water quality and creating a mathematical model to predict hydrodynamic conditions and identify pollution in Cartagena Bay. The resulting product will be used by CARDIQUE Corporation and local authorities. The ASTRiiS Project, involving organizations like the Technical Institute of Lisbon and CIMA at the University of the Algarve, seeks to develop customizable information services and products to be implemented in key sectors of the blue economy with growth potential. Thus, spill predictions are a crucial component of monitoring because they enable a more effective response to the accident by assessing the impact beforehand and better developing a strategy to mitigate the environmental impact. The most important oil weathering processes in seawater are most commonly computed by Lagrangian models, which provide these predictions. These processes, which represent the interaction of hydrocarbons with seawater, are: Spreading, Evaporation, Dispersion, Dissolution and Emulsification. The models are able to forecast the geographical and temporal propagation of the oil spill slick with the support of the hydrodynamic and atmospheric forcing from external numerical models, which are required to compute these processes. The three most crucial factors out of these are wind, currents, and water temperature, which are all applied to calculate how spills behave in different parts of the world. The objective of the thesis is to create a generic Python-based program that will serve as the link between the user and the oil spill model, serving as an Early Warning System Tool (EWS-Tool) in response to oil spills, adaptable to any region of the globe. The MOHID Lagrangian module will be adapted to the region of Cartagena Bay, Colombia, and, the Coastal Region of Algarve to assess the oil spill events. Furthermore, the operational models BASIC, SOMA, CMEMS, AMSEAS, SKIRON and GFS will supply the hydrodynamic and atmospheric variables, which will serve as the foundation for the simulation forcing. Essentially, the EWS-Tool must read the user simulation information from a web form and send the results for the user email with a report of the simulation results. Furthermore, the EWS Tool entered a testing phase where different users tested it in order to find improvements. The results showed that, by adapting the tool to two different regions, the tool can be easily used in different scenarios and adapted to other pollutants in any other region of the globe. Additionally, the base created in this work will allow the development in the future of new models capable of further reducing hydrocarbon pollution in the environment, track other types of pollution, including microplastics, and even assist in search and rescue operations.