A probabilistic model of decision making regarding the use of chemical dispersants to combat oil spills in the German Bight.

Oil spills are one of the major threats to the marine environment in the German Bight (North Sea). In case of an accident, application of chemical dispersants would be one response option among others. Dispersion breaks oil slicks into small droplets which get then mixed into the water column. Removal of the oil from the water surface may reduce contamination of the coast. However, the window of opportunity for effective dispersant application is short and there are concerns about potential effects to the marine life. We propose a Bayesian network (BN) as an interactive and intuitive tool for responders to justify decisions on using chemical dispersants and possibly the provision of appropriate assets. The BN combines detailed sub-BNs for different criteria that govern the decision process. Expected drift trajectories are estimated based on comprehensive numerical ensemble simulations of hypothetical oil spills. Ecological impacts are represented prototypically, focusing on vulnerability of seabird concentrations to pollution in coastal areas. Dispersant effectiveness is estimated considering oil properties and weather conditions. Decision making is supposed to be based on expected satisfaction. The definition of what is considered satisfactory is of central importance for the whole analysis.

The potential for dispersant use as a maritime oil spill response measure in German waters.

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.

Model-based long-term reconstruction of weather-driven variations in chronic oil pollution along the German North Sea coast.

Lagrangian passive tracer transport simulations covering the 46-year period 1958-2003 were utilized to compare the exposures of different parts of the German North Sea coast to ship-related chronic oil pollution. Assuming the spatial distribution of oil releases to be proportional to estimated ship traffic density, detailed drift reconstructions allowed for the reconstruction of wind-induced inter-annual variations in coastal pollution. For the winter months, a statistical relationship between simulated advective transports and prevailing sea surface pressure fields was established via Canonical Correlation Analysis. Wind effects were found to be more important for the northern (Schleswig-Holstein) than for the southern (Lower Saxony) part of the German North Sea coast. For Schleswig-Holstein, simulations showed consensus with beached bird survey data from this region. Proper identification of weather-driven inter-annual and spatial variations in monitoring data helps to avert misjudgments with regard to trends in the general level of chronic oil pollution.