Response planning for accidental oil spills in persian gulf: a decision support system (DSS) based on consequence modeling

Amir Heidari, P ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1016/j.marpolbul.2018.12.053
  3. Publisher: Elsevier Ltd , 2019
  4. Abstract:
  5. Different causes lead to accidental oil spills from fixed and mobile sources in the marine environment. Therefore, it is essential to have a systematic plan for mitigating oil spill consequences. In this research, a general DSS is proposed for passive and active response planning in Persian Gulf, before and after a spill. The DSS is based on NOAA's advanced oil spill model (GNOME), which is now linked with credible met-ocean datasets of CMEMS and ECMWF. The developed open-source tool converts the results of the Lagrangian oil spill model to quantitative parameters such as mean concentration and time of impact of oil. Using them, two new parameters, emergency response priority number (ERPN) and risk index (RI), are defined and used for response planning. The tool was tested in both deterministic and probabilistic modes, and found to be useful for evaluation of emergency response drills and risk-based prioritization of coastal areas. © 2019 Elsevier Ltd
  6. Keywords:
  7. Oil spill ; Probabilistic risk analysis (PRA) ; Response drills ; Response planning ; Artificial intelligence ; Decision support systems ; Drills ; Emergency services ; Infill drilling ; Oil spills ; Risk analysis ; Risk assessment ; Consequence modeling ; Decision support system (dss) ; Emergency response ; Marine environment ; Mean concentrations ; Probabilistic mode ; Quantitative parameters ; Marine pollution ; Coastal zone ; Concentration (composition) ; Data set ; Oil spill response ; Probability ; Emergency ; Quantitative analysis ; Sea ; Seashore ; Accident ; Analysis ; Prevention and control ; Procedures ; Theoretical model ; Water pollution ; Arabian sea ; Indian ocean ; Persian gulf ; Accidents ; Disaster planning ; Humans ; Models, theoretical ; Petroleum pollution
  8. Source: Marine Pollution Bulletin ; Volume 140 , 2019 , Pages 116-128 ; 0025326X (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0025326X18309044