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In estuaries and coastal waters, the flocculation of cohesive sediments is significantly affected by extracellular polymeric substances secreted by microalgae. In this study, laboratory experiments are carried out to explore the role of two typical microalgae (Skeletonema costatum and Cyclotella meneghiniana) on suspended fine‐grained sediments under various turbulent shear and environmental conditions. The results show that the shear rate is a dominant factor in controlling the biomineral flocculation processes, and the existence of microalgae generally enhances the aggregation of mineral sediments with microalgae. It is also found that floc size distributions (FSDs) and mean sizes are clearly influenced by different algal species and concentrations, especially under intensive turbulent environments. Moreover, a quasi‐Monte Carlo (QMC) based bivariate population balance model is developed to simulate the FSDs of sediment‐algae flocs. This model is reasonably validated by two analytical solutions and laboratory observations, and indicates a potential extension for tracking the properties of microalgae‐associated fine sediment flocs due to the discrete nature of the QMC method. Plain Language Summary: The transportation of fine‐grained suspended sediments in estuaries and coastal environments is a factor in many engineering and environmental issues (e.g., siltation, dredging, bed morphology, and water quality). One important characteristic that affects the transport and fate of cohesive sediment particles is flocculation, which is the tendency of particles to aggregate and breakup sequentially to form clusters (flocs) of various sizes, densities, and settling velocities. Since they are abundant in the natural environment, microalgae and their sticky secretions play important roles in the flocculation of cohesive sediment as biological glues. However, few studies have been carried out to reveal the correlation between microalgae and sediment flocculation. Thus, this study aims to investigate the influences of microalgae on the flocculation of cohesive sediment particles in various turbulent environments. We find turbulent shear is dominant in the biomineral flocculation and that biomineral flocs are generally larger than pure sediment flocs. In addition, we develop a bivariate flocculation model to simulate the floc size distribution of biomineral flocs, which is well validated by theoretical solutions and laboratory results. This innovative model offers a preliminary application for multivariate models in biomineral flocculation, which promotes a prospect of future research to develop advanced transportation models. Key Points: The influence of microalgae on the flocculation of cohesive sediments is investigated by laboratory experiments and numerical modelsThe existence of microalgae and their secreted extracellular polymeric substances generally enhances the aggregation of biomineral flocsThe quasi‐Monte Carlo based bivariate population balance model can mimic the biomineral flocculation processes with reasonable accuracy [ABSTRACT FROM AUTHOR]

Abstract The time evolutions of local Particle Size Distributions (PSDs) of suspended kaolinite are explored under different hydrodynamic conditions. A setup that uses oscillating grids is adopted to generate a nearly isotropic turbulence in a settling column, and the results at the observation location show that the initial unimodal PSDs change to bimodal distributions due to flocculation processes. The first peak of the bimodal PSD, which represents primary particles (0.1–4 µm) and flocculi (4–20 µm), remains similar in size to the median size of the initial PSD. The second peak, which represents the flocs (> 50 µm), however, is size-varying under different experimental durations and shear rates. For low shear rates, the size of the second peak increases with time and reaches an equilibrium state; for high shear rates, it first increases and then decreases. Moreover, the two PSD peaks are reasonably simulated by a two-class population balance equation, with the experimental and predicted results comparing well. The results of this study also indicate that the optimum shear rate to boost flocculation is approximately 20 s−1. Highlights • Bimodal Particle Size Distributions (PSDs) were observed in a settling column with oscillating grids; • The first peak of the PSD, which represents the flocculi, remains close in size; • The second peak of the PSD, which represents the flocs, is size-varying under different environments; • The bimodal PSDs are reasonably predicted by the two-class population balance model; • The optimal shear rate to promote flocculation is around 20 s−1 in this experiment. [ABSTRACT FROM AUTHOR]

The population balance equation has been used to describe the evolution of particle populations caused by aggregation and breakup processes for several decades. Only recently has it been used to efficiently and directly predict the temporal variation of particle size distribution (PSD) for cohesive sediments by using the quadrature method of moments (QMOM). In this study, an extension of that effort carries out additional validations that compare with analytical solutions for pure coagulation systems, pure breakup systems, and combined coagulation and breakup systems. Besides, a laboratory experiment is conducted in a five liter mixing chamber to provide steady state PSD of suspended kaolinite with a chamber-averaged kaolinite concentration 0.52 g/L and shear rate 45 s − 1 . The model results match reasonably well with both of those from analytical solutions and kaolinite flocculation experiment results. Sensitivities regarding the selecting of different model input parameters (such as fractal dimensions, primary particle sizes, aggregation and breakage fitting parameters, and fragmentation distribution functions) are also checked. The results further confirm the capability of QMOM to predict PSD using its quadrature nodes and the corresponding weights. [ABSTRACT FROM AUTHOR]

The observation of floc size distribution (FSD) for quantitative description of its properties over a sufficient size range, from a few microns to a few millimeters, is still a challenge in most marine environments. In this study, an inexpensive image acquisition and processing system is developed for achieving this objective. Images are acquired by using a Sony Alpha NEX-5R camera body with a CMOS sensor, a Sony E-mount to Nikon F-mount adaptor, extension tubes, a Nikon macro lens, and a close-up lens that can identify flocs with a minimum size of 5 μm. The light source and camera trigger are controlled by a micro-controller that was assembled for this project. These images are analyzed by using MATLAB Image Processing Toolbox. The processed floc size and their statistical distributions are confirmed with two available sample sets. The validated process is then applied to measure the steady state FSDs of kaolinite suspensions for different shear rates, suspended sediment concentrations, salinities, and a selected organic matter, guar gum. Although the presence of salt promotes flocculation of suspended kaolinite, only a small amount of salt, around 0.5 ppt, is needed to reach the saturation status. Thus for the test salinities (0.5, 1, 2, 3, 5, and 9 ppt), the measured FSDs show little difference among each other. On the other hand, guar gum affects kaolinite flocculation significantly and the maximum effect happens at a guar gum concentration around 15 mg/L when the kaolinite concentration is around 0.52 g/L. At this dosage the characteristic floc size is the largest. [ABSTRACT FROM AUTHOR]

An enhanced Quadrature Method Of Moments (QMOM) is employed to solve the population balance model (PBM) with a maximum of eight size classes for the purpose of describing the evolution of floc size distribution (FSD) of kaolinite suspension and colloidal montmorillonite. This approach can be used to estimate many representative sizes, e.g., d 32 (Sauter mean size), d 43 (De Broukere mean size), d 60 (hydrodynamic mean size), and D 50 (median size). The following three considerations are adopted to enhance the QMOM approach: (1) An adjustable factor, which is selected based on its ability to track up to eight size classes, is implemented; (2) moments higher than the third order are not necessarily simulated directly; (3) a restriction on the ratio between the minimum and maximum weights is used to exclude unreliable nodes. The above enhancements have been proposed by others, but are integrated for the first time in this study. Model results are verified by comparison with available experimental data. The results of this study suggest that the quadrature nodes and weights in the QMOM are the characteristic sizes and corresponding characteristic number densities to effectively predict the FSD of cohesive sediments. This study also demonstrates that the possible range of the correction factor (also sometimes referred to as “collision efficiency”) for the Euclidean collision frequency could be larger than one because of both the difference in floc structure represented by fractal dimension as well as the impacts of organic matter. [ABSTRACT FROM AUTHOR]