Dispersion analysis of the 2017 Persian Gulf oil spill based on remote sensing data and numerical modelling.

Oil spills, detected by SAR sensors as dark areas, are highly effective marine pollutants that affect the ocean surface. These spills change the water surface tension, attenuating capillary gravitational waves and causing specular reflections. We conducted a case study in the Persian Gulf (Arabian Sea to the Strait of Hormuz), where approximately 163,900 gal of crude oil spilled in March 2017.

Analysis of thermal discomfort associated with synoptic conditions in the city of Pelotas, southernmost region of Brazil.

Here, we evaluated the influence of outdoor environmental conditions (synoptic weather conditions) on human thermal discomfort in the five macro-regions of Pelotas city, located in the southernmost region of Brazil. To do this, meteorological sensors (HOBO MX2301A) were installed outside the residences to measure the air temperature, dew point temperature, and relative humidity between 18 January and 20 August 2019. Two well-established simplified biometeorological indices were examined seasonally: (i) humidex for the summer months and (ii) effective temperature as a function of wind for the autumn and winter months.

Absorbed dose rate for marine biota due to the oil spilled using ICRP reference animal and Monte Carlo simulation.

The current study aimed to obtain dose conversion coefficients for marine animals due to an oil spill accident using two variables: crude oil activity concentration and organism depth. Thorium series presented a dose contribution twice that uranium series for similar conditions. Bi-214 and Tl-208 stood out for delivering a higher dose rate for uranium and thorium series, respectively.

Comparison between oil spill images and look-alikes: an evaluation of SAR-derived observations of the 2019 oil spill incident along Brazilian waters.

Three SAR-derived observations of dark surface patches along the Northeastern Brazilian coastline by the end of 2019 were misreported in the Brazilian media as oil spill-related. Unfortunately, these observations were misled by false positives or look-alikes. Therefore, this paper aims to technically evaluate these look-alike classes by analyzing image attributes found to be helpful to the identification of ocean targets, including oil spills, rain cells, biofilms, and low wind conditions.