Ability to estimate the recovery potential of countermeasures is vital in establishing a rational response solution for oil spills at sea. This requires estimation of how much oil can be recovered and the determination of the rational quantities and operating conditions of the response equipment. In this study, a constant loss rate model and a variable loss rate model were developed to estimate the recovery potential of a mechanical oil recovery system, while considering the escape of oil containment booms. The latter model could calculate the speed at which oil loss began to occur and the volume of oil lost. A case study was performed to analyze the significance of oil loss and to calculate changes in recovery potential with respect to adjustable vital variables. The developed model was able to estimate the best operating situation, which optimizes the recovery potential for different response times and environmental conditions. After the oil is spilled offshore, it quickly undergoes spreading and weathering processes, including evaporation, dispersion, and emulsification [11][12][13]. The properties of the oil are strongly influenced by the weathering process, which is governed by environmental conditions. For example, as the weathering process progresses, the evaporation changes the composition of the spilled oil, and the emulsification alters the water fraction of the emulsion. As a consequence, the viscosity increment due to evaporation and emulsification causes degradation of mechanical recovery efficiency. Therefore, the spreading and weathering process should be considered in evaluating recovery performance. Spaulding [12,13] reviewed and analyzed oil transport and fate models, including spreading, evaporation, dissolution, entrainment, emulsification, biodegradation, and sedimentation. Among them, several spreading and weathering models were used in this study to simulate the oil behavior on the sea surface.The purpose of recovery potential estimation is not to predict the exact recovery volume in the given environmental conditions, but to ascertain that the oil recovery volume depends on various factors and to reflect these factors when establishing response strategies [14]. To make a reasonable decision based on the response strategy, it is required to evaluate mechanical recovery capacity. Several previous studies have focused on the recovery potential estimation of skimmers [15][16][17][18].The effective daily recovery capacity (EDRC) is a planning method that estimates the required daily oil recovery capacity for the skimmer to respond to a given spill. The EDRC is calculated by considering the total nameplate capacity of the skimmer, its operating time, and its mobilization efficiency. The performance change due to variations in oil properties and characteristics of the recovery equipment is solely described with the mechanical efficiency, which is considered to be a constant value (0.2) in EDRC. The advantage of EDRC is that it can quickly estimate the capacity of the skimmer required for mobiliza...

Recovery modeling and countermeasures for oil spilled at sea have been extensively researched, but research remains insufficient on recovery potential estimation methods. It is required to access the mechanical recovery potential by considering the relationship between oil behavior, environmental conditions, and the performance of clean-up activities. Two response-planning models were developed in this study. One is a spatially uniform recovery model for estimating recovery potential that reflects weathering, oil properties, and equipment efficiency. The other is a spatially nonuniform recovery model that considers not only the above characteristics but also local thickness reduction by skimming. A comparison between the two models and an analysis of their effects on response was carried out through the calculation using an accident scenario. It is possible to analyze the effect of the thin slicks, natural dissipation, and the quantification of deployable skimming systems with the spatially nonuniform recovery model. Finally, we analyzed interrelationships among residual oil volume on the sea, response time, and the number of skimming systems.