Optimizing the Recovery Efficiency of Finnish Oil Combating Vessels in the Gulf of Finland Using Bayesian Networks

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

Kuvaus

Oil transport has greatly increased in the Gulf of Finland
over the years, and risks of an oil accident occurring have risen. Thus, an
effective oil combating strategy is needed. We developed a Bayesian
Network (BN) to examine the recovery efficiency and optimal
disposition of the Finnish oil combating vessels in the Gulf of Finland
(GoF), Eastern Baltic Sea. Four alternative home harbors, five accident
points, and ten oil combating vessels were included in the model to find
the optimal disposition policy that would maximize the recovery
efficiency. With this composition, the placement of the oil combating
vessels seems not to have a significant effect on the recovery efficiency.
The process seems to be strongly controlled by certain random factors
independent of human action, e.g. wave height and stranding time of the
oil. Therefore, the success of oil combating is rather uncertain, so it is
also important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this type
of multidecision optimization. The methodology, results, and practices are further discussed.
Alkuperäiskielienglanti
LehtiEnvironmental Science & Technology
Vuosikerta2013
Numero47
Sivut1792 - 1799
Sivumäärä8
ISSN0013-936X
DOI - pysyväislinkit
TilaJulkaistu - 17 tammikuuta 2013
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

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title = "Optimizing the Recovery Efficiency of Finnish Oil Combating Vessels in the Gulf of Finland Using Bayesian Networks",
abstract = "Oil transport has greatly increased in the Gulf of Finlandover the years, and risks of an oil accident occurring have risen. Thus, aneffective oil combating strategy is needed. We developed a BayesianNetwork (BN) to examine the recovery efficiency and optimaldisposition of the Finnish oil combating vessels in the Gulf of Finland(GoF), Eastern Baltic Sea. Four alternative home harbors, five accidentpoints, and ten oil combating vessels were included in the model to findthe optimal disposition policy that would maximize the recoveryefficiency. With this composition, the placement of the oil combatingvessels seems not to have a significant effect on the recovery efficiency.The process seems to be strongly controlled by certain random factorsindependent of human action, e.g. wave height and stranding time of theoil. Therefore, the success of oil combating is rather uncertain, so it isalso important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this typeof multidecision optimization. The methodology, results, and practices are further discussed.",
keywords = "1172 Environmental sciences",
author = "Annukka Lehikoinen and Emilia Luoma and Samu M{\"a}ntyniemi and Sakari Kuikka",
year = "2013",
month = "1",
day = "17",
doi = "10.1021/es303634f",
language = "English",
volume = "2013",
pages = "1792 -- 1799",
journal = "Environmental Science & Technology",
issn = "0013-936X",
publisher = "American Chemical Society",
number = "47",

}

Optimizing the Recovery Efficiency of Finnish Oil Combating Vessels in the Gulf of Finland Using Bayesian Networks. / Lehikoinen, Annukka; Luoma, Emilia; Mäntyniemi, Samu; Kuikka, Sakari.

julkaisussa: Environmental Science & Technology, Vuosikerta 2013, Nro 47, 17.01.2013, s. 1792 - 1799.

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - Optimizing the Recovery Efficiency of Finnish Oil Combating Vessels in the Gulf of Finland Using Bayesian Networks

AU - Lehikoinen, Annukka

AU - Luoma, Emilia

AU - Mäntyniemi, Samu

AU - Kuikka, Sakari

PY - 2013/1/17

Y1 - 2013/1/17

N2 - Oil transport has greatly increased in the Gulf of Finlandover the years, and risks of an oil accident occurring have risen. Thus, aneffective oil combating strategy is needed. We developed a BayesianNetwork (BN) to examine the recovery efficiency and optimaldisposition of the Finnish oil combating vessels in the Gulf of Finland(GoF), Eastern Baltic Sea. Four alternative home harbors, five accidentpoints, and ten oil combating vessels were included in the model to findthe optimal disposition policy that would maximize the recoveryefficiency. With this composition, the placement of the oil combatingvessels seems not to have a significant effect on the recovery efficiency.The process seems to be strongly controlled by certain random factorsindependent of human action, e.g. wave height and stranding time of theoil. Therefore, the success of oil combating is rather uncertain, so it isalso important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this typeof multidecision optimization. The methodology, results, and practices are further discussed.

AB - Oil transport has greatly increased in the Gulf of Finlandover the years, and risks of an oil accident occurring have risen. Thus, aneffective oil combating strategy is needed. We developed a BayesianNetwork (BN) to examine the recovery efficiency and optimaldisposition of the Finnish oil combating vessels in the Gulf of Finland(GoF), Eastern Baltic Sea. Four alternative home harbors, five accidentpoints, and ten oil combating vessels were included in the model to findthe optimal disposition policy that would maximize the recoveryefficiency. With this composition, the placement of the oil combatingvessels seems not to have a significant effect on the recovery efficiency.The process seems to be strongly controlled by certain random factorsindependent of human action, e.g. wave height and stranding time of theoil. Therefore, the success of oil combating is rather uncertain, so it isalso important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this typeof multidecision optimization. The methodology, results, and practices are further discussed.

KW - 1172 Environmental sciences

U2 - 10.1021/es303634f

DO - 10.1021/es303634f

M3 - Article

VL - 2013

SP - 1792

EP - 1799

JO - Environmental Science & Technology

JF - Environmental Science & Technology

SN - 0013-936X

IS - 47

ER -