An ecological risk assessment model for Arctic oil spills from a subsea pipeline

There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of...

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Published in:Marine Pollution Bulletin
Main Authors: Arzaghi, Ehsan, Abbassi, Rouzbeh, Garaniya, Vikram, Binns, Jonathan, Khan , Faisal
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
Online Access:https://researchers.mq.edu.au/en/publications/ef432ab9-6a09-4e7d-91ff-da7eb10a8577
https://doi.org/10.1016/j.marpolbul.2018.08.030
http://www.scopus.com/inward/record.url?scp=85052468761&partnerID=8YFLogxK
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author Arzaghi, Ehsan
Abbassi, Rouzbeh
Garaniya, Vikram
Binns, Jonathan
Khan , Faisal
author_facet Arzaghi, Ehsan
Abbassi, Rouzbeh
Garaniya, Vikram
Binns, Jonathan
Khan , Faisal
author_sort Arzaghi, Ehsan
collection Macquarie University Research Portal
container_start_page 1117
container_title Marine Pollution Bulletin
container_volume 135
description There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of released oil, taking into account the uncertainty of input variables. This assists in predicting the 95th percentile Predicted Exposure Concentration (PEC 95% ) of pollutants in different media. The 5th percentile Predicted No Effect Concentration (PNEC 5% ) is obtained from toxicity data for 19 species. A model based on Dynamic Bayesian Network (DBN) is developed to assess the ecological risk posed to the aquatic community. The model enables accounting for the occurrence likelihood of input parameters, as well as analyzing the time-variable risk profile caused by seasonal changes. It is observed through the results that previous probabilistic methods developed for ERA can be overestimating the risk level.
format Article in Journal/Newspaper
genre Arctic
Arctic
Arctic Ocean
genre_facet Arctic
Arctic
Arctic Ocean
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
id ftmacquarieunicr:oai:https://researchers.mq.edu.au:publications/ef432ab9-6a09-4e7d-91ff-da7eb10a8577
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language English
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op_doi https://doi.org/10.1016/j.marpolbul.2018.08.030
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op_source Arzaghi , E , Abbassi , R , Garaniya , V , Binns , J & Khan , F 2018 , ' An ecological risk assessment model for Arctic oil spills from a subsea pipeline ' , Marine Pollution Bulletin , vol. 135 , pp. 1117-1127 . https://doi.org/10.1016/j.marpolbul.2018.08.030
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spelling ftmacquarieunicr:oai:https://researchers.mq.edu.au:publications/ef432ab9-6a09-4e7d-91ff-da7eb10a8577 2025-05-04T14:14:41+00:00 An ecological risk assessment model for Arctic oil spills from a subsea pipeline Arzaghi, Ehsan Abbassi, Rouzbeh Garaniya, Vikram Binns, Jonathan Khan , Faisal 2018-10 https://researchers.mq.edu.au/en/publications/ef432ab9-6a09-4e7d-91ff-da7eb10a8577 https://doi.org/10.1016/j.marpolbul.2018.08.030 http://www.scopus.com/inward/record.url?scp=85052468761&partnerID=8YFLogxK eng eng info:eu-repo/semantics/closedAccess Arzaghi , E , Abbassi , R , Garaniya , V , Binns , J & Khan , F 2018 , ' An ecological risk assessment model for Arctic oil spills from a subsea pipeline ' , Marine Pollution Bulletin , vol. 135 , pp. 1117-1127 . https://doi.org/10.1016/j.marpolbul.2018.08.030 Bayesian network Fugacity Ecological Risk Assessment Oil spill Arctic article 2018 ftmacquarieunicr https://doi.org/10.1016/j.marpolbul.2018.08.030 2025-04-09T00:15:35Z There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of released oil, taking into account the uncertainty of input variables. This assists in predicting the 95th percentile Predicted Exposure Concentration (PEC 95% ) of pollutants in different media. The 5th percentile Predicted No Effect Concentration (PNEC 5% ) is obtained from toxicity data for 19 species. A model based on Dynamic Bayesian Network (DBN) is developed to assess the ecological risk posed to the aquatic community. The model enables accounting for the occurrence likelihood of input parameters, as well as analyzing the time-variable risk profile caused by seasonal changes. It is observed through the results that previous probabilistic methods developed for ERA can be overestimating the risk level. Article in Journal/Newspaper Arctic Arctic Arctic Ocean Macquarie University Research Portal Arctic Arctic Ocean Marine Pollution Bulletin 135 1117 1127
spellingShingle Bayesian network
Fugacity
Ecological Risk Assessment
Oil spill
Arctic
Arzaghi, Ehsan
Abbassi, Rouzbeh
Garaniya, Vikram
Binns, Jonathan
Khan , Faisal
An ecological risk assessment model for Arctic oil spills from a subsea pipeline
title An ecological risk assessment model for Arctic oil spills from a subsea pipeline
title_full An ecological risk assessment model for Arctic oil spills from a subsea pipeline
title_fullStr An ecological risk assessment model for Arctic oil spills from a subsea pipeline
title_full_unstemmed An ecological risk assessment model for Arctic oil spills from a subsea pipeline
title_short An ecological risk assessment model for Arctic oil spills from a subsea pipeline
title_sort ecological risk assessment model for arctic oil spills from a subsea pipeline
topic Bayesian network
Fugacity
Ecological Risk Assessment
Oil spill
Arctic
topic_facet Bayesian network
Fugacity
Ecological Risk Assessment
Oil spill
Arctic
url https://researchers.mq.edu.au/en/publications/ef432ab9-6a09-4e7d-91ff-da7eb10a8577
https://doi.org/10.1016/j.marpolbul.2018.08.030
http://www.scopus.com/inward/record.url?scp=85052468761&partnerID=8YFLogxK