Search Results (4)

Trinidad and Tobago is the largest producer of oil and natural gas in Central America and the Caribbean. Natural crude oil seeps, in addition to leaking petroleum pipelines, have resulted in chronic contamination of the surrounding terrestrial environments since the time of petroleum discovery, production, and refinement in Trinidad. In this study, we isolated microbes from soils chronically contaminated with crude oil using a culture-dependent approach with enrichment. The sampling of eight such sites located in the southern peninsula of Trinidad revealed a diverse microbial composition and novel oil-degrading filamentous fungi and yeast as single-isolate degraders and naturally occurring consortia, with specific bacterial species not previously reported in the literature. Multiple sequence comparisons and phylogenetic analyses confirmed the identity of the top degraders. The filamentous fungal community based on culturable species was dominated by Ascomycota, and the recovered yeast isolates were affiliated with Basidiomycota (65.23%) and Ascomycota (34.78%) phyla. Enhanced biodegradation of petroleum hydrocarbons is maintained by biocatalysts such as lipases. Five out of seven species demonstrated extracellular lipase activity in vitro. Our findings could provide new insights into microbial resources from chronically contaminated terrestrial environments, and this information will be beneficial to the bioremediation of petroleum contamination and other industrial applications. Full article

Our research focuses on refining the ability to discriminate two petrogenic oil-slick categories: the sea surface expression of naturally-occurring oil seeps and man-made oil spills. For that, a long-term RADARSAT-2 dataset (244 scenes imaged between 2008 and 2012) is analyzed to investigate oil slicks (4562) observed in the Gulf of Mexico (Campeche Bay, Mexico). As the scientific literature on the use of satellite-derived measurements to discriminate the oil-slick category is sparse, our research addresses this gap by extending our previous investigations aimed at discriminating seeps from spills. To reveal hidden traits of the available satellite information and to evaluate an existing Oil-Slick Discrimination Algorithm, distinct processing segments methodically inspect the data at several levels: input data repository, data transformation, attribute selection, and multivariate data analysis. Different attribute selection strategies similarly excel at the seep-spill differentiation. The combination of different Oil-Slick Information Descriptors presents comparable discrimination accuracies. Among 8 non-linear transformations, the Logarithm and Cube Root normalizations disclose the most effective discrimination power of almost 70%. Our refined analysis corroborates and consolidates our earlier findings, providing a firmer basis and useful accuracies of the seep-spill discrimination practice using information acquired with space-borne surveillance systems based on Synthetic Aperture Radars. Full article

An Exploratory Data Analysis (EDA) aims to use Synthetic Aperture Radar (SAR) measurements for discriminating between two oil slick types observed on the sea surface: naturally-occurring oil seeps versus human-related oil spills—the use of satellite sensors for this task is poorly documented in scientific literature. A long-term RADARSAT dataset (2008–2012) is exploited to investigate oil slicks in Campeche Bay (Gulf of Mexico). Simple Classification Algorithms to distinguish the oil slick type are designed based on standard multivariate data analysis techniques. Various attributes of geometry, shape, and dimension that describe the oil slick Size Information are combined with SAR-derived backscatter coefficients—sigma-(σ_o), beta-(β_o), and gamma-(γ_o) naught. The combination of several of these characteristics is capable of distinguishing the oil slick type with ~70% of overall accuracy, however, the sole and simple use of two specific oil slick’s Size Information (i.e., area and perimeter) is equally capable of distinguishing seeps from spills. The data mining exercise of our EDA promotes a novel idea bridging petroleum pollution and remote sensing research, thus paving the way to further investigate the satellite synoptic view to express geophysical differences between seeped and spilled oil observed on the sea surface for systematic use. Full article

Seeps are the expression of the migration of hydrocarbons from subsurface accumulations to the surface in sedimentary basins. They may represent an important indication of the presence of petroleum (gas and oil) reservoirs and faults, and are a natural source of greenhouse gas (methane) and atmospheric pollutants (ethane, propane) to the atmosphere. Romania is one of the countries with the largest number of seeps in the world, due to the high petroleum potential and active tectonics. Based on a review of the available literature, and on the field surveys performed by the authors during the last 17 years, we report the first comprehensive GIS-based inventory of 470 seeps in Romania (HYSED-RO), including gas seeps (10.4% of the total), oil seeps (11.7%), mud volcanoes (50.4%), gas-rich springs (12.6%), asphalt (solid) seeps (4.3%), unclassified manifestations (4.0%), and uncertain seeps (6.6%). Seeps are typically located in correspondence with major faults and vertical and fractured stratigraphic contacts associated to petroleum reservoirs (anticlines) in low heat flow areas, and their gas-geochemistry reflects that of the subsurface reservoirs. The largest and most active seeps occur in the Carpathian Foredeep, where they release thermogenic gas, and subordinately in the Transylvanian Basin, where gas is mainly microbial. HYSED-RO may represent a key reference for baseline characterization prior to subsurface petroleum extraction, for environmental studies, and atmospheric greenhouse gas emission estimates in Romania. Full article