Flocculant Dosage Research Articles

The effects of water quality on the filtration performance of coal flotation product

Low-quality water is frequently used in coal preparation plants to conserve freshwater resources and lower operational costs. In the present work, a series of laboratory filtration experiments and subsequent μCT imaging of the filter cakes were conducted to link the effect of water quality on filtration performance and cake structure. Filtration experiments were carried out with three selected variables, including the slurry pH, salt concentration, which are the most important parameters of water quality, and the flocculant dosage. Filtration flowrate and cake moisture, the two most critical parameters, while examining filtration performance, were evaluated based on the filtration results. The slurry pH, salt concentration, and flocculant dosage were all found to significantly impact the flowrate, while the cake moisture was mainly affected by flocculant and salt concentration. These observed interactions were correlated with the results from filter cake µCT imaging. An increase in either salt concentration or the flocculant dosage was observed, which can cause a change in the pore structure of the cake, altering porosity, pore size, and specific surface area within the cake. Such changes in the pore structure resulted in changes in the specific cake resistance and the available water adsorption area, ultimately leading to changes in flowrate and moisture retention.

Coupling coagulation-flocculation-sedimentation with adsorption on biosorbent (Corncob) for the removal of textile dyes from aqueous solutions

This study evaluated the efficacy of combining the coagulation-flocculation-sedimentation (CFS) process with adsorption onto corncob biosorbent for the removal of textile dyes from aqueous solutions. The synthetic dyes tested were Bemacron Blue RS 01 (BB-RS01), a disperse dye, and Bemacid Marine N-5R (BM-N5R), an acid dye. Aluminum sulfate (Al₂ (SO₄)₃·18H₂O) was used as the coagulant, followed by superfloc 8396 as the flocculant. During coagulation, optimal parameters included coagulant doses (50-600 mg/L), flocculant doses (30-125 mg/L), and pH (2-11). For the adsorption phase, factors such as pH (2-11), temperature (25-45°C), contact time (0-480 min), and initial dye concentration (15-100 mg/L) were investigated. The corncob was characterized using FTIR, SEM, and pHpzc. Both Langmuir and Freundlich isotherm models were applied, with the Langmuir model demonstrating the best fit (0.92 < R² < 0.96). The CFS process achieved dye removal rates of 95.1% for BB-RS01 at pH 8 and 92.3% for BM-N5R at pH 6.5. Adsorption efficiency varied with solution pH, yielding removal rates of 26.19% for BB-RS01 at pH 6 and 7.69% for BM-N5R at pH 4. Maximum adsorption capacities were 99.5 mg/g for BB-RS01 and 46.08 mg/g for BM-N5R. This study demonstrates the effectiveness of coupling CFS with corncob adsorption for economical dye removal, utilizing agricultural waste as a biosorbent.

Turbidity removal from surface water using Cactus opuntia

Coagulation and flocculation are critical processes in water treatment facilities and typically precede the more intricate secondary and tertiary treatment stages. Currently, the most commonly used coagulants in water treatment are aluminum sulfate (alum) and ferric chloride. In developing countries, synthetic coagulants can be neither economical nor health-friendly. Consequently, natural coagulants have garnered significant research attention over the past decade. This study explored the use of cactus as a natural coagulant to decrease turbidity in surface water from the Sekak dam in Tlemcen, Algeria. Various jar tests were performed to optimize parameters such as coagulant and flocculant dosages, mixing speed, rapid mixing duration, and the pH of the water. The initial turbidity level of 5.45 NTU was reduced by up to 84.03%. The turbidity removal capacity observed in this study suggests that Opuntia cactus has considerable potential for application in surface water treatment.

Turbidity Removal Efficiency of Tannin Based Flocculants Derived from Different Agricultural Waste

Tannin-based flocculants have been investigated, produced, and commercialized as a promising product in water supply and wastewater treatment. This study compared turbidity removal efficiency of tannin-based flocculants produced from different agricultural waste. Tannin was extracted using ultrasonic method (ethanol 50%, 2 h, 500 kHz) and modified according to Mannich reaction using HCHO and NH4Cl. The coagulation and flocculation efficiencies were determined using Jar-tests on artificial wastewater with initial turbidity of 200 NTU. The results showed that at pH 7 and alum dosage of 5 ppm, turbidity removal efficiency of flocculants derived from longan pericarp, mimosa bark, green tea waste, and green banana peel were 93%, 92.7%, 92%, and 89.8%, respectively; corresponding to flocculant dosages of 10 ppm, 12 ppm, 8 ppm and 8 ppm. Production efficiency for green tea waste (9.4%), mimosa bark (7.1%), longan pericarp (4.6%) were much higher than that for green banana peel (0.5%). Based on the turbidity removal and production efficiencies as well as the optimal dosages of tannin-based flocculants, green tea waste was found to be the most potential material of all four agricultural waste to produce tannin-based flocculants.

Role of Organic Matter Present in the Water Column on Turbidity Flows

Turbidity flows are known to be affected by the density difference between sediment plumes and the surrounding water. However, besides density, other factors could lead to changes in flow propagation. Such a factor is the presence of suspended organic matter. Recently, it was found that flocculation does occur within plumes upon release of a sediment/organic matter mixture in a lock exchange flume. In the present study, mineral sediment (illite clay) was released into the outflow compartment containing water and synthetic organic matter (polyacrylamide flocculant). Even though the density of water was barely affected by the presence of flocculant, flow head velocity was observed to be larger in the presence of flocculant than without. Samples taken at different positions in the flume indicated that flocs were created during the small current propagation time (about 30–60 s) and that their sizes were larger with higher flocculant dosage. The size of flocs depended on their positions in the flow: flocs sampled in the body part of the flow were larger than the ones sampled at the bottom. All these properties are discussed as a function of sediment–flocculant interactions.

The effect of flocculant anionicity on the resistance of quartz flocs to mechanical treatment

Five polyacrylamide (PAM)-based flocculants of similar molecular weights but different degrees of anionicity were selected to investigate the effect of physicochemical properties of the tested polymers on resistance of quartz flocs to mechanical treatment. The flocculated quartz suspension was prepared at two different flocculant dosages and each sample was subjected to either ultrasonication or screening to break the flocs. The tests were performed as a function of ultrasonication duration and screen size while settling rate of flocs, turbidity of supernatant and adsorption density of flocculants were measured as indices of strength of flocs. Adsorption studies showed that adsorption density of flocculants on fine quartz surface remained unaffected by ultrasonication and screening tests, indicating that the observed changes in floc sizes was not a result of desorption. It was found that ultrasonication not only breaks the flocs but also affects the polymer chain, while screening as a strength measurement technique only breaks the flocs. In relation to dewatering applications that rely on floc strength to allow water to flow freely, such as pressure filtration, it was found that at the same adsorption density of the flocculants, PAMs with flexible chains produced the most resistant flocs. These results are attributed to the ability of these flocculants to conform to the shape and size of the flocs.

Integrating ANSYS Fluent Simulation and Aspen Plus for efficient heavy metal ion removal with de-oiled cake

In this study bio-flocculant extracted from the de-oiled cake, a common waste generated while producing oil was used to treat an electroplating industrial effluent. A comprehensive analysis of flocculation efficiency in a simulated reactor using ANSYS Workbench - Fluent, with a focus on optimizing impeller position was carried out. The findings reveal that the optimal impeller position is 2 cm from the tank base, where maximum turbulent kinetic energy (0.02577 m2/s2) and dissipation rate (22.19 m2/s3) were achieved at 200 RPM, enhancing flocculation efficacy. Furthermore, the study identifies 0.5 g L−1 as the optimal flocculant dosage, resulting in 72.70 % and 89.38 % removal of Ni(II) and Cr(VI), respectively. The flocculation process was determined to follow second-order kinetics, with significant improvements in collision efficiency and particle aggregation at the optimized dosage. Fourier Transform Infrared spectroscopy analysis confirmed chemical interactions leading to flocculation, while zeta potential and particle size distribution studies corroborated the stability and effectiveness of the process. A techno-economic analysis was conducted, estimating the total capital investment required for pilot and industrial-scale implementations, highlighting the feasibility and scalability of the proposed treatment method. A holistic framework for enhancing industrial effluent treatment processes by integrated computational fluid dynamics, kinetic studies, and economic evaluation, is the novelty of this research.

Development and evaluation of amine-functionalized β-cyclodextrin grafted starch as a natural flocculant for turbidity removal in water treatment

Recently, biopolymers have been used as coagulants/flocculants due to their biodegradability, low cost, and renewability. In this study, an environmentally friendly amine-functionalized starch-based flocculant was successfully prepared. Initially, β-cyclodextrin was grafted onto the starch backbone to increase the number of hydroxyl groups, and this composite was named CD-starch. Subsequently, in order to introduce cationic properties and enhance effective flocculation, CD-starch was modified using amine functional groups. The surface functional groups were engineered by introducing different amine to CD-starch ratios (0.5:1, 1:1, 2:1 w/w), named A-CD-starch 0.5, 1 and 2, respectively. Following the characterization of the synthesized substrate, its performance in the flocculation process of a kaolin suspension was investigated. The effects of different parameters, including pH, flocculant dosage, and initial turbidity on wastewater turbidity removal, was investigated. The results showed that a higher ratio of amine to CD-starch leads to a better amination reaction due to the greater availability of nitrogen for alkylation. Jar experiments showed that for initial turbidities of 50, 150 and 300 NTU, the appropriate doses of flocculant were 0.070, 0.085 and 0.130 mg/mL, respectively. For these initial turbidities, the maximum turbidity removal was achieved 80.1 %, 92 %, and 97.8 %, respectively. This work provides an innovative natural flocculant based on starch which can effectively treat turbid wastewaters.

Innovative Treatment of Urban Wastewater by Flocculation Combined with Ozone Pre-Oxidation and Denitrification

In this study, urban wastewater was treated by flocculation, ozone pre-oxidation and denitrification for efficient purification. Polymeric aluminum chloride (PAC) and polymeric aluminum ferric sulfate (PAFS) were added to the wastewater at different levels to remove the COD, turbidity, TP and TN of the wastewater. A better flocculant was selected and its optimum ozone pre-oxidation concentration was determined by changing the ozone concentration and measuring the effluent quality. Denitrification was further enhanced by varying the C/N ratio of the wastewater. The results show that, with the increase in flocculant dosage, the removal rates of COD, turbidity, TP and TN by PAC and PAFS were improved. The purification effect of PAC was better than that of PAFS and the optimum removal of COD, turbidity, TP and TN was obtained at a dosage of 80 mg L−1 by PAC, at 55.9%, 55.6%, 90.0% and 13.3%, respectively. Ozone pre-oxidation enhanced the removal of COD, turbidity and TN by PAC, and the optimal ozone dosage was 1.2 mg L−1, which resulted in 64.8%, 57.1% and 24.8% removal of COD, turbidity and TN, respectively. With the increase in the C/N ratio from 2.0 to 4.0, the NO3−-N concentration of PAC-treated water gradually decreased, but when the C/N ratio was 4.0, the COD concentration increased, so the optimal C/N ratio should be 3.5. Overall, the combination of ozone pre-oxidation, denitrification and flocculation was an effective method to treat urban wastewater, which has a strong application prospect.

Development of bioflocculants for mineral processing

Mining and minerals processing are essential to modern society, and the demand for metals and minerals is increasing due to the rapid development of clean energy technologies, such as electric vehicles, solar panels, wind turbines, etc. The mining industry, however, is facing significant challenges in meeting sustainability and environmental goals. As more minerals are extracted, the use of water increases, leading to greater wastewater and tailings production. To tackle this issue, flocculants are commonly used across mining sites to dewater waste streams by binding and settling particles, to allow for improved solid-liquid separation. While conventional flocculants (synthetic polymers often derived from petrochemicals) are effective in rapidly settling particles, they present several issues, such as high levels of entrapped water, ineffective fine particle separation, and environmental and health concerns. To address these challenges, bioflocculants have been proposed as alternative flocculants. This review explores three main bioflocculant research directions, including plant based, graft copolymers, and microbial flocculants, discussing the advantages and disadvantages of each. The ratio of flocculant dose to suspended solids (i.e. flocculant dose ratio) and the flocculation efficiency in these studies related to mineral and mining wastewater solid-liquid separation are evaluated. Finally, the review proposes future opportunities and directions to mitigate issues that have historically made bioflocculants less appealing. These include enhancing the recyclability of flocculants as well as advancing protein design and modification.

Using a novel bio-based cationic flocculant for food industry wastewater treatment

Wastewater from the food industry is considered harmful to human health and aquatic life, as well as polluting water and soil. This research is centered around finding an affordable and easy physicochemical method for dealing with waste generated by the food industry. To accomplish this goal, a new bio-based flocculant called 4-benzyl-4-(2-oleamidoethylamino-2-oxoethyl) morpholin-4-ium chloride was created using sustainable sources, specifically crude olive pomace oil. Its chemical structure was confirmed using various spectroscopic techniques such as FTIR, 1H-NMR, mass spectra, and 13C-NMR. This new bio-based cationic flocculant was combined with alum to act as a coagulant in the waste treatment process. Also, a study was conducted to determine the optimal conditions for the coagulation-flocculation process parameters, namely, pH and alum dosage, on COD and removal efficiency. The results showed that the optimal conditions for flocculation were achieved at pH 5.8, with 680 mg/L alum and 10 mg/L of commercial flocculant dose compared to only 5 mg/L of a new bio-based cationic flocculant. A comparison was made between the new bio-cationic flocculant and a commercial CTAB one for treating wastewater in the food industry. The study found that the new bio-based cationic flocculant was more effective in reducing the chemical oxygen demand, achieving a reduction of 61.3% compared to 54.6% for using a commercial cationic flocculant. Furthermore, using a new bio-based cationic flocculant costs only 0.49 $/g, which is less than the present cationic flocculant, which costs 0.93 $/g. The adoption of this new flocculant provides a sustainable alternative to existing industrial wastewater treatment processes

Study on Demulsification Pre-Treatment of Emulsified Wastewater

In this paper, the flocculation effect of single flocculants and compound flocculants on emulsified wastewater under different conditions was studied. The effect of flocculant type, dose, settling time and composite ratio of flocculant on the treatment of emulsified wastewater were investigated through single-factor condition tests, and then the optimal conditions of flocculants for treating emulsified wastewater were obtained. The results showed that the single inorganic flocculant could break the stable state of the emulsion when the pH was adjusted to 7 and formed tiny flocs, but it took a long time to settle down. The single organic flocculant had no flocculation effect. The inorganic–organic composite flocculants could effectively solve the problem of emulsion breaking and flocculation, and could form large flocs and alum flower formations at the same time, with mud and water effectively separated. The best conditions for the composite flocculants were as follows: under the condition of room temperature and pH 7, the dose of PFC was 2250 mg/L and APAM was 5 mg, the homogeneous stirring time was 10 min, and the settling time was 0.5 h. The removal rate of COD and turbidity reached 84.75% and 99.86%. The study could provide a new treatment idea and method for the pretreatment of stabilized high-turbidity wastewater.

Mechanical properties and microscopic analysis of water-castable engineered cementitious composites (WECC)

To address the difficulties in repairing underwater concrete panels and the unsatisfactory results of existing repair methods and materials, water-castable engineered cementitious composites (WECC) are developed. The effects of flocculant dosage on anti-dispersibility, fluidity, tensile behaviors, flexural behaviors, and fracture behaviors were investigated. XRD, MIP, and SEM tests were conducted on the WECC. Excellent tensile properties, flexural energy absorption capacity, and crack resistance are exhibited by the WECC. The increase in flocculant dosage decreases the dispersion degree during the underwater casting process of WECC, reduces the early hydration reaction rate, increases the internal porosity, resulting in a decrease in various mechanical properties. By comparing the tensile properties of WECC and WECC(L), while integrating microscopic analysis results, the performance loss mechanism of WECC and the tensile constitutive model have been identified. Additionally, the effects of (washed sea sand) sand-colloid ratio on workability and mechanical properties were investigated. When the sand-colloid ratio is 0.25, a higher level of compatibility between the fibers and the matrix is observed, and good ductility is demonstrated. Considering various performance factors, two mixed proportions have been established. The time, resources, and labor required for the repair process can be significantly reduced by using WECC for repairing underwater components, and the hydraulic structures can operate normally. The externally generated complex stress can be effectively released by WECC. The tested results provide crucial references for the underwater reinforcement of WECC.

Predictive Insight into Tailings Flowability at Their Disposal Using Operating Data-Driven Artificial Neural Network (ANN) Technique

This study investigates the application of artificial neural networks (ANNs) in predicting the flowability of mining tailings based on operational variables. As the mining industry seeks to enhance operations with complex ores, the constant improvement and optimization of mineral waste management are crucial. The flowability of tailings was investigated with data driven by properties such as particle-size distribution, water content, compaction capacity, and viscoelastic characteristics that can directly affect stacking, water recovery capabilities, and stability at disposal, influencing storage capacity, operational continuity, and work safety. There was a strong correlation between water content and tailings flowability, emphasising its importance in operational transport and deposition. Three ANN models were evaluated to predict tailings flowability across three and five categories, where a model based on thickening operational variables, including yield stress and turbidity, demonstrated the highest accuracy, achieving up to 94.4% in three categories and 88.9% in five categories. Key variables such as flocculant dosage, water content, yield stress, and solid concentration were identified as crucial for prediction accuracy The findings suggest that ANN models, even with limited datasets, can provide reliable flowability predictions, supporting tailings management and operational decision-making.

Experimental investigation on sedimentation characteristics of coastal slurry by flocculation

Coastal waste slurry has a negative impact on the environment due to its slow, natural settling characteristics. In this study, the organic, inorganic, and composite flocculants were applied to improve the mud-water separation performance. A series of experiments with sedimentation columns and particle size analysis were conducted to investigate the effects of flocculant type, dosage and combination on slurry settling rates and its associated mechanisms. The experimental results show that different types of flocculants varied in improving the settling efficiency of slurry, while the flocculation effect of inorganic flocculants is relatively poor. The settling efficiency of organic polymer flocculants on slurry is in order of anionic polyacrylamide (APAM) > cationic polyacrylamide (CPAM) > nonionic polyacrylamide (PAM), with their optimal dosage 0.2%, 0.1%, and 0.1%, respectively. Moreover, the combination of APAM and Solid Polymeric Ferric Sulfate (SPFS) can further improve the efficiency of mud-water separation by enhancing electro-neutralization and net sweeping capability. Subsequently, the change in the particle size distribution of the slurry demonstrates that flocculation causes the aggregation of fine particles in slurry to form coarse particles. These findings have implications for improving the sedimentation characteristics of waste slurry to reduce environmental pollution.

Integrating selective flocculation techniques for enhanced efficiency in manufacturing processes: A novel approach through artificial neural network modeling

The use of medium and low-grade iron ore is gradually becoming more important due to the depletion of high-grade iron ore reserves and stringent environmental acts/rules. Slimes from iron ore washing were discarded in tailing dams; however, there is currently consideration for recovering iron values from ultra-fines as well. There are enormous fine dumps that are still unutilised. Hence, this study attempt to delve the optimization of iron ore slimes an indeed requirement for manufacturing and design in industries. Leveraging a flocculation process, coupled with the implementation of an Artificial Neural Network (ANN) predictive model, the Kiriburu processing plant serves as the primary source for iron ore slime samples. Chemical analyses of the collected iron samples reveal a composition featuring 58.24 % iron content, 3.47 % Al2O3, 4.72 % SiO2, and 5.18 % LOI (Loss on Ignition). The investigation explores the performance of the flocculation technique under varying pH levels, different pulp densities, and diverse flocculant dosages. Furthermore, the varying parameters selected are pH from 6 to 11, pulp density from 1 % to 15 %, and flocculant dose from 0.03 to 0.27 mg/g. The study's findings showcase a substantial improvement in the Fe grade of iron ore, escalating from 58.24 % to 66.12 %, with an impressive recovery rate of 82.54 % achieved using a flocculant dosage of 0.09 mg/g at pH 10. Additionally, a performance assessment of the selective flocculation method for iron ore slimes is conducted using an ANN predictive model, with recovery as the pivotal parameter. The input parameters for this model encompass pH, pulp density, and flocculant dosages. Employing a three-layer ANN model with a 3–3–1 architecture and utilizing feed-forward back propagation, the study demonstrates a close alignment between predicted values and experimental data, confirming the model's effectiveness for practical manufacturing applications. Information regarding the potential applications of the model's iron ore slime beneficiation efficacy for the manufacturing sector should be considered. This could entail lower waste, more effectiveness, or cost savings. Emphasise any possible ramifications for sustainability or the environment that would make the study pertinent in a larger perspective.

Energy-saving analysis of desalination equipment based on a machine-learning sequence modeling

Abstract To control water quality and seawater desalination dosage, modeling the coagulation process of saltwater is crucial. With a focus on the features of seawater coagulation with a long lag, a machine-learning sequence-based modeling approach is suggested. The link between influent and effluent turbidities, flow rates, flocculant and coagulant dosages, and other parameters is modeled using structured units such as a gate recurrent unit encoder and a linear network decoder. The model’s validity is confirmed by numerical experiments based on real operating data, which also offer a solid foundation for managing flocculant and coagulant assistance reduction.

Research on concentration dosing control based on the ISSA-LSTM model and dynamic concentration detection

ABSTRACT During the thickening process, the dosage of flocculant has a great influence on the overflow concentration and filter cake moisture. The dosage of flocculant cannot be automatically updated according to the feeding situation, especially when the properties of the concentrated feeding material change, and the overflow concentration detection feedback cannot be adjusted in time. To address these problems, a dynamic concentration detection device was designed. In addition, a dosage of flocculant correction model based on dynamic concentration detection was constructed, and a feed-forwards flocculant additioncontrol model based on the ISSA-LSTM neural network was proposed. The results showed that the relationship between the linear slope of the dynamic concentration and the dosage of flocculant was in line with that obtained using the ExpAssoc model. Then, a double-layer LSTMslime water feedforward flocculant addition control model was proposed based on the multistrategy jointly improved Sparrow SearchAlgorithm (SSA). This model can determine the optimal dosage according to the condition of the infeeding during the thickening process. This new method can improve the intelligence of coal preparation plants and reduce the cost of washing. The scientific application of these research results will help to realize intelligent solid – liquid separation.

Optimization of the coagulation-flocculation process using response surface methodology for wastewater pretreatment generated by vegetable oil refineries: A path towards environmental sustainability

Treating complex and variable wastewater, mainly from refineries with diverse pollutants, presents multifaceted challenges. However, through diligent management and the implementation of efficient treatment strategies, the effectiveness of wastewater treatment can be maintained, ensuring the protection of the environment and public health. This study aims to enhance the coagulation-flocculation process for pretreated wastewater from vegetable oil refineries (VORW). Findings reveal that pretreatment through gravity separation influences coagulation-flocculation efficiency for oil-containing wastewater. Employing a central composite design (CCD), the study examines the effects of pH, coagulant/flocculant dosage, and settling time on turbidity and chemical oxygen demand removal (COD). Each factor significantly impacts results, with pH exerting the most substantial influence. ANOVA results validate the statistical significance of the selected models, aligning with experimental data for each response. The study demonstrates a satisfactory model fit, supported by high adjusted coefficients of determination (R2Adj = 96.59 % for turbidity and R2Adj = 93.61 % for COD). Optimal parameters—pH 7.5, coagulant dose 110 mg/L, flocculant dose 0.55 ml/L, and settling time 15 min—yield a 96 % reduction in turbidity and a 95 % reduction in COD. Furthermore, the combined treatment of flotation followed by coagulation-flocculation proves highly effective in achieving significant pollutant removal, showcasing the practical application of the design of experiments (DOE) in optimizing wastewater treatment processes.

Deep learning-based flocculation sensor for automatic control of flocculant dose in sludge dewatering processes during wastewater treatment

In sludge dewatering of most wastewater treatment plants (WWTPs), the dose of polymer flocculant is manually adjusted through direct visual inspection of the flocs without the aid of any instruments. Although there is a demand for the development of automatic control of flocculant dosing, this has been challenging owing to the lack of a reliable flocculation sensor. To address this issue, this study developed a novel image sensor for measuring the degree of flocculation (DF) based on deep learning. Two types of sludge samples were used in the laboratory-scale flocculation tests: excess sludge and mixtures of excess sludge and raw wastewater. To search for a deep learning regression model suitable for DF inference, ten models, including convolutional neural networks, vision transformers, and a multilayer perceptron MLP mixer, were comparatively analysed. The ConvNeXt and MLP mixer models showed the highest accuracies with coefficients of determination (R2) greater than 0.9. The region contributing to the DF inference in the flocculation images was visualised using a modulus-weighted, gradient-weighted regression activation map. A prototype of the flocculation sensor was constructed using an inexpensive EdgeAI device. This device comprises a single-board computer and an integrated graphical processing unit (GPU) and is equipped with a quantised ConvNeXt model. The maximum inference speed of the sensor was 12.8 frames per second (FPS). The flocculation control tests showed that the sensor could control the DF to the target value by adjusting the polymer flocculant dose. Therefore, the flocculation sensor can provide a data-driven approach to the management of the flocculation process, thereby facilitating the automation of WWTPs.