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Abstract Estuarine and coastal regions are often characterized by a high variability of suspended sediment concentrations in their waters, which influences dredging projects, contaminant transport, aquaculture and fisheries. Although various three-dimensional open source software are available to model the hydrodynamics of coastal water with a sediment module, the prediction of the fate and transport of cohesive sediments is still far from satisfied due to the lack of an efficient and robust flocculation model to estimate the floc settling velocity and the deposition rate. Single-class and sometimes two-class flocculation models are oversimplified and fail to examine complicated floc size distributions, while quadrature-based or multi-class based flocculation models may be too complicated to be coupled with large scale estuarine or ocean models. Therefore, a three-class population balance model was developed to track the sizes and number concentrations of microflocs, macroflocs and megaflocs, respectively. With the assumption of a fixed size of microflocs and megaflocs, only four tracers are needed when coupled with the open-source TELEMAC system. It enables better settling flux estimates and better addresses the occurrence and concentration of larger megaflocs. This tri-modal flocculation model was validated with two experimental data sets: (1) 1-D settling column tests with the Ems mud and (2) in-situ measurements at the WZ Buoy station on the Belgian coast. Results show that the flocculation properties of cohesive sediments can be reasonably simulated in both environments. It is also found that the number of macroflocs created, when a larger macrofloc breaks up, is a statistical mean value and may not be an integer when applying the model in the field. Graphical abstract Image Highlights • The sizes of flocs are dynamically altered because of particle aggregation and breakage. • A three-class population balance flocculation model was developed. • This flocculation model has been successfully implemented in the open source TELEMAC. • Four tracer variables, representing the floc size distributions, were included in TELEMAC. • The model was validated with settling column tests and field measurements. [ABSTRACT FROM AUTHOR]

Although spectroscopic methods provide a fast and cost-effective means of monitoring dissolved organic carbon (DOC) in natural and engineered water systems, the prediction accuracy of these methods is limited by the complex relationship between optical properties and DOC concentration. In this study, we developed DOC prediction models using multiple linear/log-linear regression and feedforward artificial neural network (ANN) and investigated the effectiveness of spectroscopic properties, such as fluorescence intensity and UV absorption at 254 nm (UV 254), as predictors. Optimum predictors were identified based on correlation analysis to construct models using single and multiple predictors. We compared the peak-picking and parallel factor analysis (PARAFAC) methods for selecting appropriate fluorescence wavelengths. Both methods had similar prediction capability (p-values >0.05), suggesting PARAFAC was not necessary for choosing fluorescence predictors. Fluorescence peak T was identified as a more accurate predictor than UV 254. Combining UV 254 and multiple fluorescence peak intensities as predictors further improved the prediction capability of the models. The ANN models outperformed the linear/log-linear regression models with multiple predictors, achieving higher prediction accuracy (peak-picking: R2 = 0.8978, RMSE = 0.3105 mg/L; PARAFAC: R2 = 0.9079, RMSE = 0.2989 mg/L). These findings suggest the potential to develop a real-time DOC concentration sensor based on optical properties using an ANN for signal processing. [Display omitted] • We developed an ANN model to measure DOC concentration in wastewater samples. • We identified most suitable predictors among the optical properties. • ANN models outperformed the linear/log-linear models in terms of R2 and RMSE values. • ANN model can be applied to the development of in situ optical DOC sensor devices. • Integrating UV 254 and fluorescence peak intensities enhanced ANN model performance. [ABSTRACT FROM AUTHOR]

• The effects of anionic, cationic and neutral organic matters on the aggregation of microplastics are investigated. • All of the organic matters show positive effects on the growth of biofilm-coated microplastic aggregates. • The two-class population balance model is used to track the small and large microplastic subgroups under turbulence. Biofilm-coated microplastics are omnipresent in aquatic environments, carrying different organic matter (OM) that in turn influences the flocculation and settling of microplastic aggregates. In this study, the effects of chitosan, guar gum, humic acid, and xanthan gum on the flocculation of anthropogenic microplastics are examined under controlled shear through the mixing chamber experiments. The results show that all of the selected OMs have positive effects on biofilm culturing and thus enhance the growth of microplastic flocs, with more evident promoting effects for cationic and neutral OMs (i.e., chitosan and guar gum) than anionic OMs (i.e., humic acid and xanthan). No critical shear rate is observed in the size vs. shear relationship based on our measurements. In addition, the quadrature-based two-class population balance model is employed to track the development of bimodal floc size distributions (FSDs) composed of small and large microplastic flocs. The model predictions show reasonable agreement with the observed FSDs. The largest error of settling flux from the two-class model is 7.8% in contrast with the reference value measured by the camera-based FSDs with 30 bins. This study highlights the role of different OMs on microplastic flocculation and indicates that a two-class model may be sufficient to describe microplastic transport processes in estuaries. [Display omitted] [ABSTRACT FROM AUTHOR]

• We studied flocculation of microalgae- and clay-containing suspensions. • Investigations were done in different microalgal growth phases. • A two-class flocculation kinetic model and Bayesian calibration were applied. • Effect of organic matter secreted by algae on flocculation kinetics was evaluated. • Distinct flocculation mechanisms were identified in different microalgal growth phases. Interplays between microalgae and clay minerals enhance biologically mediated flocculation, thereby affecting the sedimentation and transportation of suspended particulate matter (SPM) in water and benthic environments. This interaction forms larger flocs with a higher settling velocity and enhances SPM sinking. The aim of this study was to investigate the flocculation kinetics of microalgae and clay in suspension and to elucidate the mechanisms associated with such interactions. Standard jar test experiments were conducted using various mixtures of kaolinite and microalgal samples from batch cultures (Chlorella vulgaris) to estimate biologically mediated flocculation kinetics. The organic matter (OM) composition secreted by the microalgae was characterized using a liquid chromatography - organic carbon detection system, and quantitative analysis of transparent exopolymer particles was conducted separately. A two-class flocculation kinetic model, based on the interaction between flocculi and flocs, was also adopted to quantitatively analyze the experimental data from flocculation. Results from the flocculation kinetic tests and OM analyses, in association with other data analyses (i.e., floc size distribution and flocculation kinetic model), showed that flocculation increased with OM concentration during the growth phase (10–20 d). However, on day 23 during the early stationary phase, flocculation kinetics started decreasing and substantially declined on day 30, even though the amount of OM (mainly biopolymers) continued to increase. Our results indicate that an adequate quantity of biopolymers produced by the microalgal cells in the growth phase enhanced floc-to-floc attachment and hence flocculation kinetics. In contrast, an excessive quantity of biopolymers and humic substances in the stationary phase enhanced the formation of polymeric backbone structures and flocculation via scavenging particles but simultaneously increased steric stabilization with the production of a large number of fragmented particles. [Display omitted] [ABSTRACT FROM AUTHOR]

• The current findings of the heterogeneous composition of flocs are summarized. • The effect of the composition of flocs on their structure and dynamics is reviewed. • The interaction among heterogeneous components within flocs is explained. • Human activities affecting the heterogeneous composition of flocs are also summarized. Flocculation is a key process for controlling the fate and transport of suspended particulate matter (SPM) in water environments and has received considerable attention in the field of water science (e.g., oceanography, limnology, and hydrology), remaining an active area of research. The research on flocculation has been conducted to elucidate the SPM dynamics and to diagnose various environmental issues. The flocculation, sedimentation, and transportation of SPM are closely linked to the compositional and structural properties of flocs. In fact, flocs are highly heterogeneous in terms of composition. However, the lack of comprehensive research on floc composition and structure has led to misconceptions regarding the temporal and spatial dynamics of SPM. This review summarizes the current understanding of the heterogeneous composition of flocs (e.g., minerals, organic matter, metals, microplastic, engineered nanoparticles) and its effect on their structure and on their fate and transport within aquatic environments. Furthermore, the effects of human activities (e.g., pollutant discharge, construction) on floc composition are discussed. Graphical abstract [Display omitted]. [ABSTRACT FROM AUTHOR]