De Padova Diana, Mossa Michele, Adamo Maria, De Carolis Giacomo, Pasquariello Guido
Department of Civil, Environmental, Building Engineering and Chemistry, Technical University of Bari, via Orabona 4, 70125, Bari, Italy.
National Research Council of Italy, Institute of Intelligent Systems for Automation (CNR-ISSIA), via Amendola 122/D, 70126, Bari, Italy.
Environ Sci Pollut Res Int. 2017 Feb;24(6):5530-5543. doi: 10.1007/s11356-016-8214-8. Epub 2016 Dec 27.
In case of oil spills due to disasters, one of the environmental concerns is the oil trajectories and spatial distribution. To meet these new challenges, spill response plans need to be upgraded. An important component of such a plan would be models able to simulate the behaviour of oil in terms of trajectories and spatial distribution, if accidentally released, in deep water. All these models need to be calibrated with independent observations. The aim of the present paper is to demonstrate that significant support to oil slick monitoring can be obtained by the synergistic use of oil drift models and remote sensing observations. Based on transport properties and weathering processes, oil drift models can indeed predict the fate of spilled oil under the action of water current velocity and wind in terms of oil position, concentration and thickness distribution. The oil spill event that occurred on 31 May 2003 in the Baltic Sea offshore the Swedish and Danish coasts is considered a case study with the aim of producing three-dimensional models of sea circulation and oil contaminant transport. The High-Resolution Limited Area Model (HIRLAM) is used for atmospheric forcing. The results of the numerical modelling of current speed and water surface elevation data are validated by measurements carried out in Kalmarsund, Simrishamn and Kungsholmsfort stations over a period of 18 days and 17 h. The oil spill model uses the current field obtained from a circulation model. Near-infrared (NIR) satellite images were compared with numerical simulations. The simulation was able to predict both the oil spill trajectories of the observed slick and thickness distribution. Therefore, this work shows how oil drift modelling and remotely sensed data can provide the right synergy to reproduce the timing and transport of the oil and to get reliable estimates of thicknesses of spilled oil to prepare an emergency plan and to assess the magnitude of risk involved in case of oil spills due to disaster.
在因灾害导致石油泄漏的情况下，环境方面的一个担忧是油的轨迹和空间分布。为应对这些新挑战，溢油应急计划需要升级。此类计划的一个重要组成部分将是能够模拟石油在深水意外泄漏时其轨迹和空间分布行为的模型。所有这些模型都需要用独立观测数据进行校准。本文的目的是证明通过协同使用油漂移模型和遥感观测，可以为浮油监测提供重要支持。基于输运特性和风化过程，油漂移模型确实可以根据水流速度和风力作用，预测溢油在油位置、浓度和厚度分布方面的归宿。2003年5月31日发生在瑞典和丹麦海岸附近波罗的海的溢油事件被视为一个案例研究，目的是生成海流循环和油污染物输运的三维模型。高分辨率有限区域模型（HIRLAM）用于大气强迫。通过在卡尔马松德、西姆里斯哈姆和昆斯霍尔姆斯福特站进行的为期18天17小时的测量，对流速和水面高程数据的数值模拟结果进行了验证。溢油模型使用从环流模型获得的流场。将近红外（NIR）卫星图像与数值模拟进行了比较。该模拟能够预测观测到的浮油的溢油轨迹和厚度分布。因此，这项工作展示了油漂移建模和遥感数据如何能够提供恰当的协同作用，以再现油的时间变化和输运情况，并获得溢油厚度的可靠估计值，从而制定应急计划并评估因灾害导致溢油时所涉及的风险程度。
