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Improving Oil Spill Models to Support Environmental Emergency Response and Chemical Dispersant use Policy Development


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    Haibo Niu Dalhousie University

Increased oil and gas activity in Canada raises the risk of marine oil spills. The recent Deepwater Horizon disaster has shown that it is vital that a reliable deep-water oil spill model be available to predict the trajectory of oil.

This research helps to fill a major research gap on the modeling of subsurface oil spills by providing essential data and improved mathematical formulae for oil droplet size distribution. The findings will result in a new tool which provides more accurate information on when, where and how much oil, will surface and what the thickness of the oil slick will be. The proposed preliminary study on dispersant use, if expanded in the future, could eventually lead to a pre-approval policy that would facilitate rapid oil spill response, and reduce environmental, social, and economic impacts in the event of a spill.

This project promotes international cooperation in marine environmental prediction through the collaboration of Dalhousie (Canada) with the Technical University of Lisbon (Portugal). The adoption of Portuguese best expertise on oil spill modeling would greatly benefit Canada. The improved oil spill model will help to advance spill modeling and response world-wide. 

Partners:

  • Fisheries and Oceans Canada - BIO - Maritimes

Investigators:

  • Rodrigo Fernandes
  • Glen Herbert
  • Thomas King
  • Keith Thompson Dalhousie University

MEOPeers:

  • Pu Li Dalhousie University
  • Shihan Li Dalhousie University
  • Linlu Weng Dalhousie University

Publications:

  • Niu,Haibo,Conmy, R.N., King, T., Robinson, B., Ryan, S., Lu, Y., Abercrombie, M., Boufadel, M.. 2016, Dispersant Effectiveness, In-Situ Droplet Size Distribution and Numerical Modeling to Assess Subsurface Dispersant Injection as a Deepwater Blowout Oil Spill Response Option and Evaluation of Oil Fluorescence Characteristics, US Environmental Protection Agency,
  • Li,Pu,Niu,Haibo,Weng,Linlu,. 2015, Experimental and Modeling Study of Droplet Size Distributionfrom Subsurface Oil Releases, Report to Fisheries and Oceans Canada and US Environmental Protection Agency,
  • Niu,Haibo,et al. 2014, Modeling the Effects of Chemical Dispersant on the Fate of Spilled Oil: Case Study of a Hypothetical Spill near Saint John, NB, Water Quality Journal of Canada,
  • Perrie,William,Li, Haiyan. 0, Sea Ice Characterization and Classification Using Hybrid Polarimetry SAR, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10.1109/JSTARS.2016.2584542.
  • Li,Pu,Niu,Haibo,. 2016, The influence of Spatial and Temporal Resolutions of Hydrodynamic Model on the Deepwater Oil Spill Model Predictions, 2016 Gulf of Mexico Oil spill and Ecosystem Conference.,

The end product deep-water oil spill Modelling tool could be used by government agencies (such as Fisheries and Oceans Canada, the Canadian Coast Guard, and oil and gas producers) to assess the potential environmental impacts of subsurface oil spills, and to allocate the limited response resources more effectively during spill cleanup. The results will also help regulatory agencies, such as CNLOPB and CNSOPB to improve their dispersant use policy.