Oil spill on sea surfaces, which mainly produced by the oil leakage accident happened on tankers, offshore platforms, drilling rigs and wells, has bring irreversible damage to marine environments and ecosystems. Among various spill oil handling methods, using sorbents to absorb and recover spill oils is a perspective method because they are cost-effective and enable a high recovery and without secondary pollution to the ecosystem. Currently, sorbents based on biomass materials have aroused extensively attention thanks to their features of inexpensive, abundant, biodegradable, and sustainable. Herein, we comprehensively review the state-of-the-art development of biomass-based sorbents for spill oil cleanup in the recent five years. After briefly introducing the background, the basic theory and material characteristics for the separation of oil from water and the adsorption of oils is also presented. Various modification methods for biomass materials are summarized in section three. Section four discusses the recent progress of biomass as oil sorbents for oil spill cleanup, in which the emphasis is placed on the oil sorption capacity and the separation efficiency. Finally, the challenge and future development directions is outlined.

The microwave scatterometer is one of the most effective instruments in ocean remote sensing, which urges the need for some theoretical models to accurately estimate the scattering coefficient of the sea surface. For the simulation of the scattering from an ocean surface, the sea spectrum, or its inverse Fourier transform, autocorrelation function is essential. Currently, many sea spectral models have been proposed for describing sea waves. However, which spectrum should be adopted during electromagnetic (EM) computations? A systematic comparison of these models is needed to evaluate their accuracies. In this paper, we focus on numerical simulations of scattering from a rough sea surface in monostatic and bistatic configurations by using six different sea spectral models and the first-order small slope approximation (SSA-1). First, sea spectral models proposed by Elfouhaily et al., Hwang et al., Romeiser et al., Apel et al., Fung et al., and Pierson et al., are compared with each other from different points of view, e.g., the omnidirectional parts, the angular spreading functions, the autocorrelation functions, and the slope variances. We find that the spectra given by Elfouhaily and Hwang could reflect realistic wind sea waves more accurately. Then, the scattering coefficients are simulated in fully monostatic and bistatic configurations. Regarding the monostatic scattering, the results simulated using EM scattering models are compared with those obtained from the measured UAVSAR data in the L band and the empirical model CMOD5 in the C band. Comparisons are made for various incident angles, wind speeds, and wind directions. Meanwhile, special attention is paid to low to moderate incident angles. The comparisons show that, it is difficult to find one certain spectral model to simulate scattering coefficient accurately under all wind speeds or wind directions. Accurate estimations will be obtained using different methods according to different situations.

To assist in the detection of ship targets in complex sea conditions, a numerical simulation method is proposed to obtain synthetic aperture radar (SAR) images of time-varying ocean ship wakes under various radar, ship, and sea surface parameters. This method addresses the limitations of recent simulations, which failed to simultaneously incorporate different types of time-varying ship wakes, simulate based on the echo data, and discuss the velocity bunching (VB) effect on the image results. To address these issues, firstly, the time-varying wave height and velocity fields of the sea surface, Kelvin wakes, and turbulence wakes are simulated using the linear filtering method, classic fluid dynamics models, and attenuation function method, respectively. Secondly, raw data of the ocean ship wakes are obtained by calculating the backscattering fields using geophysical model functions (GMFs), as well as by determining the changing slant range varying with the elevation and velocity fields. Thirdly, by applying the Range-Doppler algorithm (RDA) for pulse compression and range cell migration correction (RCMC) on the echo data, SAR images with and without the VB effect are generated. Our simulation also accounts for the influence of speckle noise. The SAR imaging results indicate that whether the VB effect is considered or not, the radar electromagnetic wavebands, polarization modes, wind speeds, and the relative wind directions have distinct impacts on the SAR image intensity, and the texture and morphology of ship wakes vary significantly with the wind speeds, ship speeds, and the relative radar looking directions. When considering the VB effect, the azimuthal offset and blur in the images caused by the more intense wave motion also increase with the wave speeds.

Retrieving the oil-water mixture ratio (M, the proportion of oil in an oil-water mixture) of the marine oil spill is of vital importance for the emergency treatment of oil pollution, which can be achieved by a copolarization ratio (PR) method. In the framework of the PR method, it is assumed that Bragg scattering dominates at moderate incidence angles, and the relative contribution of non-Bragg scattering to total scattering (RCNT) is typically neglected. However, in this work, it is found that the RCNT cannot be neglected for L-band, especially for HH polarization at higher wind speeds (the RCNT is approximately 0.6~0.8 for wind speeds of 10~12 m/s). The significant impact of non-Bragg scattering results in the PR method not being accurate enough for retrieving M. After separately investigating the influences of the damping effect and effective dielectric constant reduction on the RCNT, a novel approach is proposed for more accurately estimating the M of marine oil spills by eliminating the impact of non-Bragg scattering. The proposed method was applied to UAVSAR images collected during the Deepwater Horizon (DWH) oil spill accident. The inversion results of our approach show that the M of most oil spill areas ranges from approximately 0.3 to 0.6, which matches the reality better than that of a traditional PR method (ranging from approximately 0.6 to 0.8).

This paper is devoted to investigating the electromagnetic (EM) backscattering from slick-free and slick-covered sea surfaces at various bands (L-band, C-band, X-band, and Ku-band) by using the second-order small slope approximation (SSA-2) and the measured synthetic aperture radar (SAR) data. It is known that the impact of slick on sea surface is mainly caused by two factors: the Marangoni damping effect and the reduction of friction velocity. In this work, the influences induced by these two factors on the sea curvature spectrum, the root mean square (RMS) height, the RMS slope, and the autocorrelation function of sea surfaces are studied in detail. Then, the slick-free and slick-covered sea surface profiles are simulated using the Elfouhaily spectrum and the Monte-Carlo model. The SSA-2 with the tapered incident wave is employed to simulate the normalized radar cross-sections (NRCSs) of sea surfaces. Furthermore, for slick-free sea surfaces, the NRCSs simulated with the SSA-2 at various bands are compared with those obtained by the first-order small slope approximation (SSA-1), the classic two-scale model (TSM), and the geophysical model functions (GMFs) at various bands, respectively. For slick-covered sea surfaces, the SSA-2-simulated NRCSs are compared with those obtained from C-band Radarsat-2 images and L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) images, respectively. The numerical simulations illustrate that the SSA-2 can be used to study the EM backscattering from slick-free and slick-covered sea surfaces, and it has more advantages than the SSA-1 and the TSM. The works presented in this paper are helpful for understanding the EM scattering from the sea surface covered with slick, in theory.