@misc{liu_implications_of_2019, 
author={Liu, Z., Callies, U.},
title={Implications of using chemical dispersants to combat oil spills in the German Bight – Depiction by means of a Bayesian network},
year={2019},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.envpol.2019.02.063},
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.},
note = {Online available at: \url{https://doi.org/10.1016/j.envpol.2019.02.063} (DOI). Liu, Z.; Callies, U.: Implications of using chemical dispersants to combat oil spills in the German Bight – Depiction by means of a Bayesian network. Environmental Pollution. 2019. vol. 248, 609-620. DOI: 10.1016/j.envpol.2019.02.063}}