Implications of using chemical dispersants to combat oil spills in the German Bight - Depiction by means of a Bayesian network

Environ Pollut. 2019 May:248:609-620. doi: 10.1016/j.envpol.2019.02.063. Epub 2019 Feb 23.

Abstract

Application of chemical dispersants is one option for combatting oil spills, dispersing oil into the water column and thereby reducing potential pollution to coastal areas. Efficiency of dispersant application depends on oil characteristics, sea and weather conditions. Potential environmental impacts must also be taken into account. Referring to the German Bight region (North Sea), we show how probabilistic Bayesian network (BN) technology can integrate all these aspects to support contingency planning. Expected effects of chemical dispersion on oil spill drift paths are quantified based on comprehensive numerical ensemble simulations. Ecological impacts are represented just in simplified terms focusing on nearshore seabird distributions. The intuitive and interactive BN summarizes expected benefits from chemical dispersion depending on where and under which weather conditions a hypothetical pollution occurs.

Keywords: Bayesian network; Chemical dispersant; German Bight; Oil spill; Risk assessment.

MeSH terms

  • Bayes Theorem
  • Environmental Restoration and Remediation / methods*
  • Hydrodynamics
  • Models, Theoretical*
  • North Sea
  • Petroleum Pollution / analysis*
  • Seawater / chemistry
  • Surface-Active Agents / chemistry*
  • Water Pollutants, Chemical / analysis*

Substances

  • Surface-Active Agents
  • Water Pollutants, Chemical