Department of Earth Sciences, University of New Hampshire, 105 Main Street, Durham, New Hampshire 03824, USA.
Norwegian Research Centre, P.O. Box 6031, Bergen 5892, Norway.
J Acoust Soc Am. 2019 Aug;146(2):1176. doi: 10.1121/1.5121699.
Improved in situ quantification of oil in the marine environment is critical for informing models of fate and transport and evaluating the resiliency of marine communities to oil spills. Broadband acoustic backscatter has been used to quantify a variety of targets in the water column; from fish and planktonic organisms to gas bubbles and oceanic microstructure, and shows promise for use in quantifying oil droplets. Quantifying water column targets with broadband acoustic backscatter relies on accurate models of a target's frequency dependent target strength (TS), a function of the target's acoustic impedance, shape, and size. Previous acoustic quantification of oil droplets has assumed that droplets were spheres. In this study, broadband (100.5-422 kHz) acoustic backscatter from individual oil droplets was measured, and the frequency dependent TS compared to a model of acoustic scattering from fluid spheres and two models for more complex shapes. Droplets of three different crude oils, two medium oils, and one heavy oil were quantified and all droplets were oblate spheroids. The impact of the deviation from sphericity on the accuracy of each model was determined. If an inversion of the model for spherical droplets was used to estimate flux from acoustic observations, errors in the predicted volume of a droplet were between 30% and 50%. The heavy oil also showed deviations in predicted volume of 20%-40% when using the two models for more complex shapes.
改进海洋环境中石油的原位定量分析对于为命运和迁移模型提供信息以及评估海洋群落对溢油的恢复能力至关重要。宽带声波反向散射已被用于定量测量水柱中的各种目标；从鱼类和浮游生物到气泡和海洋微观结构，并且有望用于定量测量油滴。利用宽带声波反向散射定量测量水柱目标需要准确的目标频率相关目标强度（TS）模型，该模型是目标声阻抗、形状和大小的函数。以前对油滴的声学定量假设油滴是球体。在这项研究中，测量了单个油滴的宽带（100.5-422 kHz）声波反向散射，并将频率相关的 TS 与流体球体的声学散射模型以及两个更复杂形状的模型进行了比较。对三种不同的原油、两种中质油和一种重质油的液滴进行了量化，所有液滴均为扁长球体。确定了从球形偏离对每个模型准确性的影响。如果使用球形液滴的模型反转来估计声观测的通量，则预测液滴体积的误差在 30%至 50%之间。当使用两个更复杂形状的模型时，重质油的预测体积也会出现 20%-40%的偏差。
