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Mar Pollut Bull. 2016 Dec 15;113(1-2):332-342. doi: 10.1016/j.marpolbul.2016.10.005. Epub 2016 Oct 11.

Reynolds number scaling to predict droplet size distribution in dispersed and undispersed subsurface oil releases.

Author information

Department of Engineering, Dalhousie University (Truro Campus), Truro, NS, Canada B2N 5E3. Electronic address: Pu.Li@Dal.Ca.
Department of Civil Engineering, Dalhousie University (Sexton Campus), Halifax, NS, Canada B3H 4R2.
Department of Engineering, Dalhousie University (Truro Campus), Truro, NS, Canada B2N 5E3.
Centre for Offshore Oil, Gas and Energy Research (COOGER), Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS, Canada B2Y 4A2.
US Environmental Protection Agency (US EPA), Office of Research and Development, Cincinnati, OH, USA 45220.
Oceans and Atmosphere Flagship, CSIRO, Bentley, WA, Australia 6102.


This study was aimed at testing the applicability of modified Weber number scaling with Alaska North Slope (ANS) crude oil, and developing a Reynolds number scaling approach for oil droplet size prediction for high viscosity oils. Dispersant to oil ratio and empirical coefficients were also quantified. Finally, a two-step Rosin-Rammler scheme was introduced for the determination of droplet size distribution. This new approach appeared more advantageous in avoiding the inconsistency in interfacial tension measurements, and consequently delivered concise droplet size prediction. Calculated and observed data correlated well based on Reynolds number scaling. The relation indicated that chemical dispersant played an important role in reducing the droplet size of ANS under different seasonal conditions. The proposed Reynolds number scaling and two-step Rosin-Rammler approaches provide a concise, reliable way to predict droplet size distribution, supporting decision making in chemical dispersant application during an offshore oil spill.


Chemical dispersant; Dispersant to oil ratio; Modified Weber number scaling; Oil droplet size distribution; Reynolds number scaling; Rosin-Rammler

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