The terminal settling velocity of microplastics plays a vital role in the physical behavior of microplastics, and is related to the migration and fate of these microplastics in the ocean. At present, the terminal settling velocity is mostly calculated by formulae, which also leads to a fewer studies on the use of machine-learning models to predict its settling velocity in this field. This study fills this gap by studying the prediction of the settling velocity by machine-learning models and compares it with the traditional formula calculation method. This study evaluates three machine-learning models, namely, random forest, linear regression, and the back propagation neural network. The results of this study show that the prediction results of the three machine-learning models are more accurate than those of traditional formula calculations, with an accuracy increase of 12.79% (random forest), 9.3% (linear regression), and 13.92% (back propagation neural network), respectively. At the same time, according to the results of this study, random forest is better than the other models in the mean absolute error and root mean square error evaluation indicators, which are only 0.0036 and 0.0047. This paper proposes three machine-learning methods to prove that the prediction effect of machine learning is much better than traditional formula calculations, thereby improving the shortcomings in this field. At the same time, it also provides reliable data support for studying the migration behavior of microplastics in water bodies.

With the development of renewable energy and the utilization of marine resources, large-scale offshore floating photovoltaics have gradually attracted widespread attention. In order to develop offshore floating photovoltaics and promote sustainable development, it has become necessary to explore the hydrodynamic characteristics of floating photovoltaic units and floating arrays. In this work, based on the viscous flow theory, the Computational Fluid Dynamics (CFD) and the discrete element method (DEM) methods are used to analyze the hydrodynamics of the floating body unit of offshore floating photovoltaics. The influencing factors include mooring length, mooring radius, and floating unit length. In addition, the hydrodynamic performance of the floating body unit and the floating body array under different wave heights and periods is also discussed to explore the influence of environmental loads on the floating body unit and the floating body array. The results indicate that the mooring tension exhibits an opposite trend with the surge and heave motions when the mooring line length and radius are varied. The motion is found to be more pronounced when the floating body unit length is 0.4 times the wavelength. The heave motion of the floating body unit exhibits a strong linear relationship with wave height, increasing by 0.01 m for every 0.015 m increase in wave height. The motion of the floating body units on both sides connected to the mooring lines decreases as the array length increases.

Sun, Z.-l.; Gao, Y.; Xu, D.; Hu, C.-h.; Fang, H.-w., and Xu, Y.-p., 2019. A new formula for the transport capacity of nonuniform suspended sediment in estuaries. Journal of Coastal Research, 35(3), 684–692. Coconut Creek (Florida), ISSN 0749-0208.A new formula for calculating the sediment transport capacity is developed as a function of the time-dependent Froude number and the particle Reynolds number. Considering the relation between suspension and transport of sediment, a critical condition for suspension is introduced into the formula. The proposed formula provides a consistent formulation for the fractional and total transport capacity of nonuniform sediments and leads to an expression for the mean fall velocity that makes physical sense. The coefficients in the proposed formula were determined with laboratory data of uniform sediment, and it is verified by field data measured from alluvial rivers. The concept of instantaneous equilibrium was proposed so that applicability of the formula extended to estuaries. The results show that the present formula performs well in conditions of laboratories, rivers, and estuaries. This can provide a key parameter or bottom boundary condition for two-dimensional/three-dimensional mathematical models of nonuniform sediment.

This study investigates the pollution characteristics and environmental risks of crushed microplastics (MPs) generated during plastic recycling, emphasizing their adsorption capacity for heavy metals, particularly lead (Pb). SEM-EDS analysis revealed that crushed MPs exhibit significantly higher adsorption capacity than primary MPs due to their larger surface area and more available adsorption sites, including oxygen-containing functional groups. The adsorption behavior of MPs was influenced by key factors such as MP size, MP quantity, pH, salinity, and biofilm formation. Smaller MPs demonstrated higher adsorption efficiency, while elevated pH enhanced Pb adsorption. Conversely, increased salinity reduced adsorption due to competition for adsorption sites. Increasing MP concentrations improved Pb removal efficiency, but higher MP quantities led to a decrease in maximum adsorption capacity, demonstrating a trade-off between removal efficiency and adsorption capacity. Isothermal adsorption experiments revealed that Pb adsorption on MPs follows a multi-layer mechanism, best characterized by the Freundlich model. The adsorption capacity increased nonlinearly with Pb concentration and stabilized as surface sites became saturated. The formation of biofilms on MPs further enhanced their adsorption capacity by providing additional functional groups and facilitating multi-layer adsorption, increasing ecological risks. Adsorption kinetics were best described by pseudo-second-order and intra-particle diffusion models, indicating chemical adsorption and boundary layer diffusion as dominant mechanisms. Magnetic Fe₃O₄ nanoparticles demonstrated a high recovery efficiency of 99.3% for MPs, highlighting their potential for environmental remediation. However, the presence of adsorbed Pb slightly reduced recovery performance, emphasizing the need to optimize recovery conditions for maximum efficiency. These findings underscore the dual threat posed by crushed MPs: their capacity to adsorb and concentrate harmful substances, increasing ecological toxicity, and the challenges associated with their recovery. This research provides critical insights into mitigating MP pollution and developing effective recovery strategies under realistic environmental conditions.

The tidal asymmetry under the action of sea level rise in Hangzhou Bay. Coastlines dominated by the tide are not only directly affected by the rise of the mean sea level but also by the tidal dynamics. The computational domain of the hydrodynamic model covers the entire Hangzhou Bay and takes into account the feedback between the tidal motion and the erodible bottom. Its main application fields include: the simulation of different sea level rise (SLR) rates, the interaction between tidal duration and skewness and the interaction between tidal range and astronomical tide. The results on tidal asymmetry in Hangzhou Bay is a systematic process consisting of four aspects: Firstly, the tide increase, which is affected by the sea level rise, is between 25% and 50%. Secondly, the value of the sea level rise is about two times the added value of the tidal range, and the tidal range increased to the left side of the tidal wave propagation direction, which accelerated the propagation velocity. Thirdly, the sea level rise amplified the M₂ tidal amplitude and delayed the M₂ tidal phase in the inner bay, which reduced about 50%. Finally, the change of the tidal range caused by tide level had the same magnitude as the change caused by the mean sea level rise. The purpose of this study was to emphasize the importance of the predictions of the response area affected by tidal asymmetry based on the action of the sea level rise in Hangzhou Bay.