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1.
Mar Pollut Bull ; 129(2): 623-632, 2018 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-29102071

RESUMO

In case of an oil spill, dispersant application represents a response option, which enhances the natural dispersion of oil and thus reduces coating of seabirds and coastal areas. However, as oil is transferred to the water phase, a trade-off of potential harmful effects shifted to other compartments must be performed. This paper summarizes the results of a workshop on the current knowledge on risks and benefits of the use of dispersants with respect to specific conditions encountered at the German sea areas. The German North Sea coast is a sensitive ecosystem characterised by tidal flats, barrier islands and salt marshes. Many prerequisites for a potential integration of dispersants as spill response option are available in Germany, including sensitivity maps and tools for drift modelling of dispersed and undispersed oil. However, open scientific questions remain concerning the persistence of dispersed oil trapped in the sediments and potential health effects.


Assuntos
Conservação dos Recursos Hídricos/métodos , Poluição por Petróleo/prevenção & controle , Petróleo/análise , Tensoativos/química , Poluentes Químicos da Água/análise , Tomada de Decisões , Alemanha , Guias como Assunto , Poluição por Petróleo/efeitos adversos , Áreas Alagadas
2.
Environ Monit Assess ; 110(1-3): 291-9, 2005 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-16308793

RESUMO

Environmental Sensitivity Indices (ESI) composed of many field-data are essential for monitoring and control systems. At the beginning of the last decade an ESI of the German Wadden Sea was developed for use by the relevant authorities. This ESI was derived by experts semi-manually analysing the extensive field data-set. An algorithm is presented here which emulates human expert-decisions on the classification of sensitivity classes. This will permit the necessary regular updates of ESI-determination when new field data become available using automated classifications procedures. After tuning the algorithm parameters it generates decisions identical to those of human experts in about 97% of all locations tested. In addition, the algorithm presented also enables erroneous or extremely seldom field data to be identified.


Assuntos
Meio Ambiente , Redes Neurais de Computação , Algoritmos , Animais , Tomada de Decisões , Monitoramento Ambiental , Fucus , Invertebrados , Oceanos e Mares , Zosteraceae
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