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.

Oil spill in northeastern Brazil: Application of fluorescence spectroscopy and PARAFAC in the analysis of oil-related compounds.

Between November 2019 and February 2020, 53 water samples were collected along 430 km of coastline in northeastern Brazil, which was the location of an oil spill that occurred in August 2019. Synchronous fluorescence matrices (SFMs) were acquired to avoid regions affected by Raman Stokes scatterings and second harmonic signals, and then, the SFMs were converted into excitation-emission matrices (EEM) by shear transformation. The matrix coupled with parallel factor analysis (PARAFAC) was used in the study of fluorescent components present in the collected waters. A sample collected before the oil spill and another from Florianópolis-SC, 2000 km from the incident, were used as references for nonimpacted waters. In the postspill samples, 4 components were determined, with component 1 (λexc = 225 nm, λem = 475 nm) being associated with humic-like organic matter (terrestrial), component 2 (λexc = 230 nm, λem = 390 nm) being associated with humic-like organic matter (marine), component 3 (λexc = 225/295 nm, λem = 345 nm) being associated with dibenzothiophene-like components also observed in tests with crude oil samples, and component 4 (λexc = 220/280 nm, λem = 340 nm) being associated with a naphthalene-like substance. Principal component analysis (PCA) was performed on the PARAFAC scores. The distribution of samples along the 4 components was observed and compared with the reference samples.