Effect of shear rate on floc characteristics and concentration factors for the harvesting of Chlorella vulgaris using coagulation-flocculation-sedimentation

Machine learning framework for modeling flocculation kinetics using non-intrusive dynamic image analysis

The implementation of a machine learning (ML) model to improve both the effectiveness and sustainability of the water treatment system is a significant challenge in the water sector, with the optimization of flocculation processes being a major setback. The objective of this study was to develop a ML model for predicting flocs evolution of the flocculation process in water treatment. Furthermore, we have devised a framework for its potential adoption in large-scale water treatment. Therefore, the paper can be split into two parts. In the first one, flocculation evolution has been studied from an experimental setup, using a non-intrusive image acquisition method. Subsequently, the ML framework has been implemented. Batch assay data of two velocity gradients (Gf 20 and 60 s-1) and flocculation time of three hours were partitioned into five groups for flocs length range 0.27-3.5 mm and upscaled using linear method. Multilayer Perceptron (MLP) and Long-Short Term Memory (LSTM) models, and traditional time series model, Auto Regressive Integrated Moving Average (ARIMA) were explored to predict floc length evolution data. The experiments illustrate the kinetics of flocculation, where the initial stage is characterized by a rapid floc growth followed by a plateau during which floc length fluctuates within a narrow range. Results demonstrate that ML is sensitive to flocculation; however, the model should be selected with care. ARIMA model is not suitable for predicting number of flocs with negative test accuracy (R2). In contrast, MLP recorded R2 of 0.86-1.0 for training and 0.92-1.0 for testing, across Gf 20 s-1 and Gf 60 s-1. LSTM model has the best prediction R2 of 0.92-1.00 for Gf 20 s-1 and accurately predicts the number of flocs across all groups and Gfs. Our study has proven that the developed framework could be replicated for water treatment modeling and promotes the application of smart technology in water treatment.

Enhancing floc size and strength with a hybrid polymer of zinc oxide, acrylamide, and tannin in textile wastewater

This study involved synthesising new hybrid polymers called ZOPAT, made up of zinc oxide, acrylamide, and tannin, using a blended technique. The effectiveness of ZOPAT in treating textile wastewater was then tested by measuring floc growth rate, flocculation index, strength factor, and recovery factor under optimised conditions. The study also identified the zeta potential, morphology, elemental composition, and functional groups of the polymers. Response surface methodology determines the optimal pH and ZOPAT dose, resulting in 93% colour, 80% chemical oxygen demand (COD), 100% turbidity, and suspended solids (SS) removal at pH 9.22 and 737 mg/L ZOPAT. The study found that ZOPAT was more effective than commercial Polyaluminium chloride in reducing colour and COD, producing larger and stronger flocs, and requiring a shorter coagulation time of 17.5 min. ZOPAT was also easy to homogenise and operate due to its one-unit dosing system. The study attributes the success of ZOPAT to the presence of Zn, N, and K, which create electrostatic attraction with opposite charged particles, and the formation of dye-particle-dye with amide, hydroxyl, and carboxyl groups in ZOPAT, which remove colour, turbidity, COD, and SS. Overall, the study concludes that ZOPAT has significant potential for textile wastewater treatment.

Monitoring effects of hydrodynamic cavitation pretreatment of sodium oleate on the aggregation of fine diaspore particles through small-angle laser scattering

Hydrodynamic cavitation (HC) enhanced fine particle aggregation could be largely due to the generation of tiny bubbles and their role in bridging particles. However, the lack of adequate characterizations of aggregates severally limits our further understanding of the associated aggregation behaviors. In this study, the aggregation of fine diaspore particles was comparatively investigated in sodium oleate (NaOl) solutions with and without HC pretreatment through the small-angle laser scattering (SALS) technique in a shear-induced aggregation (SIA) system. Results showed that HC pretreatment caused the formation of bulk nanobubbles (BNBs), which significantly modified the particle interactions and thereby modified the size and mass fractal dimension (Df) of aggregates under different SIA conditions. Although HC pretreatment did not noticeably alter the gradual change trend of aggregate size and structure characteristics under specific variables, BNBs bridging facilitated the aggregation process towards the diffusion-limited cluster aggregation model, resulting in the formation of larger but looser aggregates. This effect was more pronounced under relatively high NaOl concentrations. Apart from BNBs, the aggregation was also affected by cavitation bubbles formed during shear cavitation, which was more significant under high stirring intensity conditions (i.e., 1800 rpm) than the low stirring intensity conditions (i.e., 600 rpm).

A critical review on phycoremediation of pollutants from wastewater-a novel algae-based secondary treatment with the opportunities of production of value-added products

Though the biological treatment employing bacterial strains has wide application in effluent treatment plant, it has got several limitations. Researches hence while looking for alternative biological organisms that can be used for secondary treatment came up with the idea of using microalgae. Since then, a large number of microalgal/cyanobacterial strains have been identified that can efficiently remove pollutants from wastewater. Some researchers also found out that the algal biomass not only acts as a carbon sink by taking up carbon dioxide from the atmosphere and giving oxygen but also is a renewable source of several value-added products that can be extracted from it for the commercial use. In this work, the cleaning effect of different species of microalgae/cyanobacteria on wastewater from varied sources along with the value-added products obtained from the algal biomass as observed by researchers during the past few years are reviewed. While a number of review works in the field of phycoremediation technology was reported in literature, a comprehensive study on phycoremediation of wastewater from different industries and household individually is limited. In the present review work, the efficiency of diverse microalgal/cyanobacterial strains in treatment of wide range of industrial effluents along with municipal wastewater having multi-pollutants has been critically reviewed.

A new bin size index method for statistical analysis of multimodal datasets from materials characterization

This paper presents a normalized standard error-based statistical data binning method, termed "bin size index" (BSI), which yields an optimized, objective bin size for constructing a rational histogram to facilitate subsequent deconvolution of multimodal datasets from materials characterization and hence the determination of the underlying probability density functions. Totally ten datasets, including four normally-distributed synthetic ones, three normally-distributed ones on the elasticity of rocks obtained by statistical nanoindentation, and three lognormally-distributed ones on the particle size distributions of flocculated clay suspensions, were used to illustrate the BSI's concepts and algorithms. While results from the synthetic datasets prove the method's accuracy and effectiveness, analyses of other real datasets from materials characterization and measurement further demonstrate its rationale, performance, and applicability to practical problems. The BSI method also enables determination of the number of modes via the comparative evaluation of the errors returned from different trial bin sizes. The accuracy and performance of the BSI method are further compared with other widely used binning methods, and the former yields the highest BSI and smallest normalized standard errors. This new method particularly penalizes the overfitting that tends to yield too many pseudo-modes via normalizing the errors by the number of modes hidden in the datasets, and also eliminates the difficulty in specifying criteria for acceptable values of the fitting errors. The advantages and disadvantages of the new method are also discussed.

Enhanced Microcystis Aeruginosa removal and novel flocculation mechanisms using a novel continuous co-coagulation flotation (CCF)

Co-coagulation flotation (CCF) is a novel flotation technology that renders more efficient algal removal compared to traditional mechanical coagulation flotation (MCF) due to a short residence time (< 30 s) and fast rising behavior of algal flocs (> 250 m·h^-1). This study compared the algal removal performance using continuous CCF and MCF using water samples taken from Lake Dianchi with severe Microcystis aeruginosa blooms. Removal efficiency, dosage of coagulant/flocculant, rising velocity and structural characteristics of the resulting flocs in the two processes were systematically compared. The results show that CCF could save >50 % polyaluminum chloride (PAC) and polyacrylamide (PAM) compared with MCF when the removal efficiency was both over 95 %. The average rising velocity of flocs in CCF could reach 254.3 m·h^-1, much higher than that in MCF (154.5 m·h^-1). In the respective optimal coagulation conditions, the flocs formed in CCF (G = 164.8 s^-1) were larger (1843 ± 128 μm) and more spherical with a higher fractal dimension (D_f = 1.85 ± 0.01) than those generated in MCF (G = 34.1 s^-1). The Stokes's Law was found to correctly predict the rising velocity of spherical flocs with large fractal dimensions (D_f > 1.7). In contrast, the Haarhoff and Edzwald's extended equation was more suitable for calculating the rising velocity of irregular flocs with small fractal dimension. This study provides new insights into the mechanisms of the enhanced algal removal by CCF and lays foundation for developing cost-efficient algal mitigation processes.

Predicting the flocculation kinetics of fine particles in a turbulent flow using a Budyko-type model

Through an analogy with the Budyko curves in catchment hydrology science, this study defines the supply and demand limits for the flocculation system of cohesive particles (the supply limit can be represented by the potential floc size growth, whereas the demand limit can be represented by the steady-state floc size) and attempts to adopt Budyko-type models to estimate the temporal evolution of floc size during flocculation. Seventeen experimental datasets are collected to test the accuracy of the Budyko model with an average high correlation coefficient of 0.9784 and average low relative error and root mean squared error values of 0.1304 and 0.0605, respectively. Either the potential floc size growth or the steady-state floc size is a monotonic function of the flow shear rate, and a simple empiric power law function can be used to describe them. Other Budyko-type models are also found to show good prediction accuracies against the experimental datasets. This study indicates that Budyko-type models have potential as a good addition to existing flocculation models for predicting the temporal variation in the size population of flocs in a turbulent flow, provided that some coefficients have been calibrated by limited data points prior.

Nano magnetite assisted flocculation for efficient harvesting of lutein and lipid producing microalgae biomass

For commercial scale algal biorefining, harvesting cost is a major bottleneck. Thus, a cost-effective, less-energy intensive, and efficient harvesting method is being investigated. Among several harvesting methods, magnetic flocculation offers the benefits of modest operation, energy savings and quick separation. This study aims to develop novel magnetite-(Fe₃O₄) nanoparticles (MNPs) of 20 nm average size and their high reusability potential to reduce the harvesting cost of microalgae biomass. The MNPs were synthesized and characterized using FTIR, Zeta analyzer, and SEM before performing on Chlorella sorokiniana Kh12 and Tu5. For maximum harvesting efficiency >99%, the optimal culture pH, MNPs concentration, and agitation speed were 3, 200 mg/L, and 450 rpm, respectively. Subsequently, MNPs were recovered via alkaline treatment and reused up to 5 cycles as they retained their reactivity and harvesting efficiency. The studied MNPs-based harvesting method could be adopted at a commercial scale for cost-effective algae biorefinery in the future.

Harvesting of Microcystis flos-aquae using dissolved air flotation: The inhibitory effect of carboxyl groups in uronic acid-containing carbohydrates

Harvesting algal biomass reduces nutrient loading in eutrophicated lakes and the protein-rich microalgal biomass could be recycled as feedstocks of feed and fertilizer. Due to the complexity of algogenic organic matter (AOM), the key components and functional groups in AOM that inhibit coagulation-based microalgal harvesting have not been disclosed thus far. This study quantitatively analysed the responsive compositions and functional groups of AOM involved in the dissolved air flotation (DAF) harvesting of M. flos-aquae with 1 × 10⁹ cell L^-1 density at coagulation pH 6.2. The results showed that harvesting efficiency dropped drastically from 95.5 ± 0.7% to 43 ± 0.7% in the presence of AOM (26.77 mg L^-1) at the coagulant dosage of 0.75 mg L^-1 and further deteriorated with increasing AOM concentration. Carbohydrates contributed 81% of the total composition of substances involved in the DAF, while the contribution of protein and humic-like substances were only 18% and 1%, respectively. Stoichiometric analysis of functional groups in carbohydrates, proteins, and humic-like substances using model components revealed that carboxyl groups in uronic acid-containing carbohydrates accounted for 76% of the total reduction in carboxyl groups, which was much higher than that in proteins (23%) and humic-like substances (1%), indicating that carboxyl groups in uronic acids containing carbohydrates were the major inhibitors. A conceptual model of charge competition was proposed to explain the inhibition mechanism of carboxyl functional groups in uronic acid-containing carbohydrates on microalgal DAF. Strategies such as preventing carboxyl deprotonation by pH reduction and employment of sweeping/bridging polymeric coagulants/flocculants were proposed for the to reduce the inhibitory effect of carboxyl functional groups.

Nannochloropsis oceanica harvested using electrocoagulation with alternative electrodes - An innovative approach on potential biomass applications

Electrocoagulation is a promising technology to harvest microalgal biomass. However, the commonly used aluminum electrodes release undesired salts that decrease biomass value. In this study, alternative iron, zinc, and magnesium electrodes and operational parameters pH, time and current density were studied to harvest Nannochloropsis oceanica. For recovery efficiency and concentration factor the initial pH was most important using iron electrodes, while time and current density were more relevant using zinc and magnesium electrodes. Optimal parameters resulted in biomass recovery efficiencies > 95%, biomass was concentrated 2.8-7.2 times and contained 15.7-29.1% ashes. Elemental analysis revealed metal salts in harvested biomass resulting from electrode corrosion. Finally, ash contents could be reduced by 65% using EDTA as a chelating agent. The electrocoagulation harvested microalgal biomass enriched in essential metals may be a promising bioresource for agricultural growth inducers, or functional ingredients for feed.

A comprehensive review on the synthesis and applications of ion exchange membranes

Ion exchange membranes (IEMs) are undergoing prosperous development in recent years. More than 30,000 papers which are indexed by Science Citation Index Expanded (SCIE) have been published on IEMs during the past twenty years (2001-2020). Especially, more than 3000 papers are published in the year of 2020, revealing researchers' great interest in this area. This paper firstly reviews the different types (e.g., cation exchange membrane, anion exchange membrane, proton exchange membrane, bipolar membrane) and electrochemical properties (e.g., permselectivity, electrical resistance/ionic conductivity) of IEMs and the corresponding working principles, followed by membrane synthesis methods, including the common solution casting method. Especially, as a promising future direction, green synthesis is critically discussed. IEMs are extensively applied in various applications, which can be generalized into two big categories, where the water-based category mainly includes electrodialysis, diffusion dialysis and membrane capacitive deionization, while the energy-based category mainly includes reverse electrodialysis, fuel cells, redox flow battery and electrolysis for hydrogen production. These applications are comprehensively discussed in this paper. This review may open new possibilities for the future development of IEMs.

Effects of Co-culture on Improved Productivity and Bioresource for Microalgal Biomass Using the Floc-Forming Bacteria Melaminivora Jejuensis

Bacterial and algal floc formation was induced by inoculating three species of wastewater-derived bacteria (Melaminivora jejuensis, Comamonas flocculans, and Escherichia coli) into algal cultures (Chlorella sorokiniana). Bacterial and algal flocs formed in algal cultures inoculated with M. jejuensis and C. flocculans, and these flocs showed higher sedimentation rates than pure algal culture. The floc formed by M. jejuensis (4988.46 ± 2589.81 μm) was 10-fold larger than the floc formed by C. flocculans (488.60 ± 226.22 μm), with a three-fold higher sedimentation rate (M. jejuensis, 91.08 ± 2.32% and C. flocculans, 32.55 ± 6.33%). Biomass and lipid productivity were improved with M. jejuensis inoculation [biomass, 102.25 ± 0.35 mg/(L·day) and 57.80 ± 0.20 mg/(L·day)] compared with the productivity obtained under pure algal culture conditions [biomass, 78.00 ± 3.89 mg/(L·day) and lipids, 42.26 ± 2.11 mg/(L·day)]. Furthermore, the fatty acid composition of the biomass produced under pure algal culture conditions was mainly composed of C_16:0 (43.67%) and C_18:2 (45.99%), whereas the fatty acid composition of the biomass produced by M. jejuensis was mainly C_16:0 (31.80%), C_16:1 (24.45%), C_18:1 (20.23%), and C_18:2 (16.11%). These results suggest the possibility of developing an efficient method for harvesting microalgae using M. jejuensis and provide information on how to improve biomass productivity using floc-forming bacteria.

The role of ballast specific gravity and velocity gradient in ballasted flocculation

This study investigated the concealed interaction between applied velocity gradient (G value) and ballast specific gravity (SG) in ballasted flocculation (BF). The objective was to unravel the participation of applied surface concentration (SC: 0.005 m²L^-1-0.02 m²L^-1) of high specific gravity ballasts (SG: 2.9-5.57) in BF aggregation phenomenon at varied velocity gradients (G value: 750s^-1-1250s^-1). Static mixer was used to perform the BF experiments, and aggregated flocs were characterized using charge coupled device (CCD) camera. The results revealed that conventionally adopted velocity gradient (G value: 150s^-1 - 300s^-1) in BF studies was insufficient for efficient floc development due to inadequate suspension of denser ballasts during mixing. This resulted in poor turbidity removal (< 40 %) and immature slow settling flocs (< 25 mh^-1) despite higher ballast consumption. However, appropriate optimization of G value (1250s^-1) corresponding to high specific gravity ballast (SG: 5.57) resulted in 99.5 % turbidity removal (residual turbidity: 1NTU) achieved in a shorter settling interval of 30 s consuming significantly less ballast concentration. This expeditious settling phenomenon was also evident in CCD camera observations of the ballasted flocs achieving superficial settling velocity (105mh^-1). Therefore, it was concluded that appropriate optimization of the G value corresponding to the pertinent concentration of denser ballasts can exhibit rapid elimination of micropollutants, and superficial sedimentation with efficient material and energy use. This can lead to efficient BF design with a short HRT, compact footprint, and ability to handle highly turbid influent.

Algal cells harvesting using cost-effective magnetic nano-particles

Innovative iron-based nanoparticles were synthesized, characterized and tested for the first time for harvesting single and mixed algal culture from real wastewater. The tailor-made magnetic nanoparticles (MNPs; Fe-MNP-I and Fe-MNP-II) achieved a percentage algae harvesting efficiency (%AHE) higher than 95% using a concentration of MNPs (C_MNP) of 25 ± 0.3 (std. dev = 0.08) mg.L^-1, mixing speed (M_speed) of 120 ± 2 (std. dev = 0.10) rpm, short contact time (C_t) of 7 ± 0.1 (std. dev = 0.05) min and separation time (SP_t) of 3 ± 0.1 (std. dev = 0.09) min. The optimum operational conditions for harvesting of Chlorella vulgaris (C.v) were determined at (C_MNP = 40 ± 0.4 (std. dev = 0.5) g_MNPs.L^-1, SP_t = 2.5 ± 0.4 (std. dev = 0.1) min, M_speed = 145 ± 3 (std. dev = 1.50) rpm and C_t = 5 ± 0.3 (std. dev = 0.10) min using surface response methodology. Langmuir model describes better the adsorption behavior of algae-Fe-MNP-I system, while both Langmuir and Freundlich fit well the adsorption behavior of algae-Fe-MNP-II. The maximum adsorption capacity of Spirulina platensis (SP.PL) (18.27 ± 0.07 (std. dev = 0.19) mg_DWC.mg_particles^-1) was higher than that for Chlorella vulgaris (C.v) (11.52 ± 0.01 (std. dev = 0.34) mg_DWC.mg_particles^-1) and mixed algal culture (M.X) (17.20 ± 0.07 (std. dev = 0.54) mg_DWC.mg_particles^-1) over Fe-MNP-I. Zeta potential measurements revealed that the adsorption mechanism between MNPs and algal strains is controlled by electrostatic interaction. The synthesized MNPs were recycled 10 times using alkaline-ultrasonic regeneration procedure.

Effects of Fe3O4 nanoparticle fabrication and surface modification on Chlorella sp. harvesting efficiency

Harvesting is a critical step in microalgae-based biodiesel production. Oleaginous microalgae harvesting by magnetic nanomaterials has gained attention because of the advantages of higher efficiency, lower cost, and convenient operation. In the present study, Fe₃O₄ magnetic nanoparticles (MNPs) were fabricated using two different methods (chemical coprecipitation and thermal decomposition), modified with amino acid using three different approaches (ultrasonic, long-time mixing, and "one-step" approaches), and utilized for oleaginous microalgae Chlorella sp. HQ harvesting. The results showed that the Fe₃O₄ MNPs synthesized by the chemical coprecipitation method achieved superior performance when considering both harvesting efficiency and fabrication cost. For the amino-acid modification, the one-step approach outcompeted the other approaches. At a dosage of 200 mg/L, the optimized Fe₃O₄@Arginine MNPs could achieve a harvesting efficiency of 95% with a low cost of only 347 USD/t of harvested algal biomass. Both the amino-acid content on the NPs and the number of amino groups in the amino acid molecules played a role in improving the harvesting performance.