Modelling an expert GIS system based on knowledge to evaluate oil spill environmental sensitivity

Oil spills cause great damage to coastal habitats, especially when rapid and suitable response measures are not taken. Establishing high priority areas is fundamental for the operation of response teams. Under this context and considering the need for keeping all geographical information up-to-date for emergencial use, the present study proposes employing a decision tree coupled with a knowledge-based approach using GIS to assign oil sensitivity indices to Brazilian coastal habitats. The modelled system works based on rules set by the official standards of Brazilian Federal Environment Organ. We tested it on one of the littoral regions of Brazil where transportation of petroleum is most intense: the coast of the municipalities of Sao Sebastiao and Caraguatatuba in the northern littoral of São Paulo state, Brazil. The system automatically ranked the littoral sensitivity index of the study area habitats according to geographical conditions during summer and winter; since index ranks of some habitats varied between these seasons because of sediment alterations. The obtained results illustrate the great potential of the proposed system in generating ESI maps and in aiding response teams during emergency operations. (C) 2009 Elsevier Ltd. All rights reserved.

Integrated assessment for establishing an oil environmental vulnerability map: Case study for the Santos Basin region, Brazil

The growth of maritime transport and oil exploitation activities may increase the risk of oil spills. Thus, plans and actions to prevent or mitigate impacts are needed to minimize the effects caused by oil. However, tools used worldwide to support contingency plans have not been integrated, thus leading to failure in establishing priority areas. This investigation aimed to develop indices of environmental vulnerability to oil (IEVO), by combining information about environmental sensibility to oil and results of numerical modeling of spilled oil. To achieve that, a case study concerning to oil spills scenarios in a subtropical coastal area was designed, and IEVOs were calculated and presented in maps, in order to make the information about the areas' vulnerability more easily visualized. For summer, the extension of coastline potentially affected by oil was approximately 150. km, and most of the coastline presented medium to high vulnerability. For winter, 230. km coastline would be affected, from which 75% were classified as medium to high vulnerability. Thus, IEVO maps allowed a rapid and clearer interpretation of the vulnerability of the mapped region, facilitating the planning process and the actions in response to an oil spill. © 2013 Elsevier Ltd.

Mapeamento de sensibilidade ambiental ao óleo do arquipélago de Ilha Bela - SP

Pós-graduação em Geociências e Meio Ambiente - IGCE

Mapeamento de sensibilidade ao derrame de óleo dos ambientes costeiros dos municípios de São Vicente, Santos e Guarujá - SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mapeamento de sensibilidade ambiental a derramentos de petróleo do sistema estuarino de Santos, estado de São Paulo

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mapeamento de sensibilidade ambiental a derramamentos de óleo na região costeira de Bertioga - SP

Pós-graduação em Geociências e Meio Ambiente - IGCE

Mapa de vulnerabilidade ambiental ao óleo e cartas SAO: trecho Praia Grande - Ilha Comprida, litoral paulista

Pós-graduação em Geociências e Meio Ambiente - IGCE

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.