Offshore oil spills in Brazil: An extensive review and further development.

The present study offers an extensive overview on the evolution and current state of marine oil spill research in Brazil and then discusses further directions. Given the historical and current relevance of this issue, this paper also aims to summarize the exploration, geological background, design of oil spills timeline and assessment of the most important of them. Moreover, it includes a critical comparison of Brazilian oil spill models in terms of their simulation abilities, real-time field data assimilation, space and time forecasts and uncertainty evaluation. This study also presents the perspectives of the Multi-User System for Detection, Prediction, and Monitoring of Oil Spills at Sea (SisMOM) the largest and most important Brazilian project to face the offshore oil spills.

Oil reaching the coast: Is Brazil on the route of international oceanic dumping?

After the oil spill disaster occurred in 2019, various events of tar balls reaching the Brazilian coast and archipelagos have been reported. The hypothesis here is that the oil/waste dumped in international waters by ships on-route to Cape of Good Hope is reaching the Brazilian coast. On that account, 30-year probabilistic simulations were used to estimate the probability of dumped oil residue reaching the Brazilian coast. The simulations considered three Zones following the South Atlantic route. The results have shown that up to 28.5 % of large ships could dump oil on-route. Inside the Brazilian Exclusive Economic Zone, the probability of dumped oil/waste reaching the coastline is about 62 % and quickly decreases for Dumping Zones 2 and 3. Equatorial and Northeast shores of Brazil are the most vulnerable to oceanic dumping when compared to other regions.

Mysterious oil spill on the Brazilian coast - Part 2: A probabilistic approach to fill gaps of uncertainties.

Over 5000 tons of spilled oil reached the northeast coast of Brazil in 2019. The Laboratory for Computational Methods in Engineering (LAMCE/COPPE/UFRJ) employed time-reverse modeling and identify multiple potential source areas. As time-reverse modeling has many uncertainties, this article carried out a methodology study to mitigate them. A probabilistic modeling using Monte Carlo approach was developed to test these source areas with the Spill, Transport, and Fate Model (STFM) and a scenario tree methodology was used to select possible spill scenarios. To estimate the performance of Lagrangian models, two new model performance evaluations were added to Chang and Hanna (2004). The combination of probabilistic simulations, scenario tree analysis, and model performance evaluation proved to be a powerful tool for mitigating the uncertainties of time-reverse modeling, yielding good results and simple implementation.