Response Surface Methodology for Optimization of Rotating Biological Contactor Combined with External Membrane Filtration for Wastewater Treatment

Co-metabolic degradation and metabolite detection of hexabromocyclododecane by Shewanella oneidensis MR-1

Hexabromocyclododecane (HBCD) is a widely used brominated flame retardant; however, it is a persistent organic pollutant as well as affects the human thyroid hormones and causes cancer. However, the degradation of HBCD has received little attention from researchers. Due to its bioaccumulative and hazardous properties, an appropriate strategy for its remediation is required. In this study, we investigated the biodegradation of HBCD using Shewanella oneidensis MR-1 under optimized conditions. The Box-Behnken design (BBD) was implemented for the optimization of the physical degradation parameters of HBCD. S. oneidensis MR-1 showed the best degradation performance at a temperature of 30 °C, pH 7, and agitation speed of 115 rpm, with an HBCD concentration of 1125 μg/L in mineral salt medium (MSM). The strain tolerated up to 2000 μg/L HBCD. Gas chromatography-mass spectrometry analysis identified three intermediates, including 2-bromo dodecane, 2,7,10-trimethyldodecane, and 4-methyl-1-decene. The results provide an insightful understanding of the biodegradation of HBCD by S. oneidensis MR-1 under optimized conditions and could pave the way for further eco-friendly applications. KEY POINTS: • HBCD biodegradation by Shewanella oneidensis • Optimization of HBCD biodegradation by the Box-Behnken analysis • Identification of useful metabolites from HBCD degradation.

Modelling and optimization of membrane process for removal of biologics (pathogens) from water and wastewater: Current perspectives and challenges

As one of the 17 sustainable development goals, the United Nations (UN) has prioritized "clean water and sanitation" (Goal 6) to reduce the discharge of emerging pollutants and disease-causing agents into the environment. Contamination of water by pathogenic microorganisms and their existence in treated water is a global public health concern. Under natural conditions, water is frequently prone to contamination by invasive microorganisms, such as bacteria, viruses, and protozoa. This circumstance has therefore highlighted the critical need for research techniques to prevent, treat, and get rid of pathogens in wastewater. Membrane systems have emerged as one of the effective ways of removing contaminants from water and wastewater However, few research studies have examined the synergistic or conflicting effects of operating conditions on newly developing contaminants found in wastewater. Therefore, the efficient, dependable, and expeditious examination of the pathogens in the intricate wastewater matrix remains a significant obstacle. As far as it can be ascertained, much attention has not recently been given to optimizing membrane processes to develop optimal operation design as related to pathogen removal from water and wastewater. Therefore, this state-of-the-art review aims to discuss the current trends in removing pathogens from wastewater by membrane techniques. In addition, conventional techniques of treating pathogenic-containing water and wastewater and their shortcomings were briefly discussed. Furthermore, derived mathematical models suitable for modelling, simulation, and control of membrane technologies for pathogens removal are highlighted. In conclusion, the challenges facing membrane technologies for removing pathogens were extensively discussed, and future outlooks/perspectives on optimizing and modelling membrane processes are recommended.

Wastewater treatment using moving bed biofilm reactor technology: a case study of ceramic industry

Biological approaches and coagulation are frequently used to reduce the chemical oxygen demand (COD) for treatment of ceramic effluent water. The technology known as the moving bed biofilm reactor (MBBR) can accomplish this goal. Further, the process of emulsification-aided innovative MBBR using biosurfactants can be proposed for ceramic effluent treatment. In a step-by-step upgrading scheme, biosurfactants and a consortia of halophilic and halotolerant microbial culture was utilized for the treatment of the effluent water. Over the course of 21 days, a progressive decrease in COD of up to 95.79% was achieved. Over the next 48 h period, the biochemical oxygen demand (BOD) was reduced by 98.3%, while total suspended solids (TSS) decreased by 79.41%. With the use of this innovative MBBR technology, biofilm formation accelerated, lowering the COD, BOD, and TSS levels. This allows treated water to be used for further research on recycling it back into the ceramics sector and repurposing it for agricultural purposes. PRACTITIONER POINTS: Implementation of modified MBBR technology for the treatment of effluent water. Biosurfactants could reduce in the organic and inorganic loads. Increase in MLSS values with COD removal observed. The plant operations without the use of chemical coagulants was effective with biosurfactants. Biofilm formation on carriers was scraped and the presence of surfactin and rhamnolipid was confirmed.

Optimization of operational parameters using RSM, ANN, and SVM in membrane integrated with rotating biological contactor

Membrane fouling is a critical bottleneck to the widespread adoption of membrane separation processes. It diminishes the membrane permeability and results in high operational energy costs. The current study presents optimizing the operating parameters of a novel rotating biological contactor (RBC) integrated with an external membrane (RBC + ME) that combines membrane technology with an RBC. In the RBC + ME, the membrane panel is placed external to the bioreactor. Response surface methodology (RSM) is applied to optimize the membrane permeability through three operating parameters (hydraulic retention time (HRT), rotational disk speed, and sludge retention time (SRT)). The artificial neural networks (ANN) and support vector machine (SVM) are implemented to depict the statistical modelling approach using experimental data sets. The results showed that all three operating parameters contribute significantly to the performance of the bioreactor. RSM revealed an optimum value of 40.7 rpm disk rotational speed, 18 h HRT and 12.4 d SRT, respectively. An ANN model with ten hidden layers provides the highest R2 value, while the SVM model with the Bayesian optimizer provides the highest R2. RSM, ANN, and SVM models reveal the highest R-square values of 0.97, 0.99, and 0.99, respectively. Machine learning techniques help predict the model based on the experimental results and training data sets.

Response of biofilm-based systems for antibiotics removal from wastewater: Resource efficiency and process resiliency

Biofilm-based systems have efficient stability to cope-up influent shock loading with protective and abundant microbial assemblage, which are extensively exploited for biodegradation of recalcitrant antibiotics from wastewater. The system performance is subject to biofilm types, chemical composition, growth and thickness maintenance. The present study elaborates discussion on different type of biofilms and their formation mechanism involving extracellular polymeric substances secreted by microbes when exposed to antibiotics-laden wastewater. The biofilm models applied for estimation/prediction of biofilm-based systems performance are explored to classify the application feasibility. Further, the critical review of antibiotics removal efficiency, design and operation of different biofilm-based systems (e.g. rotating biological contactor, membrane biofilm bioreactor etc.) is performed. Extending the information on effect of various process parameters (e.g. hydraulic retention time, pH, biocarrier filling ratio etc.), the microbial community dynamics responsible of antibiotics biodegradation in biofilms, the technological problems, related prospective and key future research directions are demonstrated. The biofilm-based system with biocarriers filling ratio of ∼50-70% and predominantly enriched with bacterial species of phylum Proteobacteria protected under biofilm thickness of ∼1600 μm is effectively utilized for antibiotic biodegradation (>90%) when operated at DO concentration ≥3 mg/L. The C/N ratio ≥1 is best suitable condition to eliminate antibiotic pollution from biofilm-based systems. Considering the significance of biofilm-based systems, this review study could be beneficial for the researchers targeting to develop sustainable biofilm-based technologies with feasible regulatory strategies for treatment of mixed antibiotics-laden real wastewater.

Effect of Operating Parameters on the Performance of Integrated Fixed-Film Activated Sludge for Wastewater Treatment

Integrated fixed-film activated sludge (IFAS) is a hybrid wastewater treatment process that combines suspended and attached growth. The current review provides an overview of the effect of operating parameters on the performance of IFAS and their implications for wastewater treatment. The operating parameters examined include hydraulic retention time (HRT), solids retention time (SRT), dissolved oxygen (DO) levels, temperature, nutrient loading rates, and aeration. Proper control and optimization of these parameters significantly enhance the treatment efficiency and pollutant removal. Longer HRT and appropriate SRT contribute to improved organic matter and nutrient removal. DO levels promote the growth of aerobic microorganisms, leading to enhanced organic matter degradation. Temperature influences microbial activity and enzymatic reactions, impacting treatment efficiency. Nutrient loading rates must be carefully managed to avoid system overload or inhibition. Effective aeration ensures uniform distribution of wastewater and biofilm carriers, optimizing contact between microorganisms and pollutants. IFAS has been used in water reuse applications, providing a sustainable and reliable water source for non-potable uses. Overall, IFAS has proven to be an effective and efficient treatment process that can provide high-quality effluent suitable for discharge or reuse. Understanding the effects of these operating parameters helps to optimize the design and operation for efficient wastewater treatment. Further research is needed to explore the interactions between different parameters, evaluate their impact under varying wastewater characteristics, and develop advanced control strategies for improved performance and sustainability.

Response Surface Methodology for the Synthesis and Characterization of Bio-Oil Extracted from Biomass Waste and Upgradation Using the Rice Husk Ash Catalyst

Rice husk ash (RHA), a low-cost biomaterial, was utilized to form bio-oil from pyrolysis in a batch-stirred reactor, followed by its upgradation using the RHA catalyst. In the present study, the effect of temperature (ranging from 400 to 480 °C) on bio-oil production produced from RHA was studied to obtain the maximum bio-oil yield. Response surface methodology (RSM) was applied to investigate the effect of operational parameters (temperature, heating rate, and particle size) on the bio-oil yield. The results showed that a maximum bio-oil output of 20.33% was obtained at 480 °C temperature, 80 °C/min heating rate, and 200 μm particle size. Temperature and heating rate positively impact the bio-oil yield, while particle size has little effect. The overall R² value of 0.9614 for the proposed model proved in good agreement with the experimental data. The physical properties of raw bio-oil were determined, and 1030 kg/m³ density, 12 MJ/kg calorific value, 1.40 cSt viscosity, 3 pH, and 72 mg KOH/g acid value were obtained, respectively. To enhance the characteristics of the bio-oil, upgradation was performed using the RHA catalyst through the esterification process. The upgraded bio-oil stemmed from a density of 0.98 g/cm³, an acid value of 58 mg of KOH/g, a calorific value of 16 MJ/kg, and a viscosity 10.5 cSt, respectively. The physical properties, GC-MS and FTIR, showed an improvement in the bio-oil characterization. The findings of this study indicate that RHA can be used as an alternative source for bio-oil production to create a more sustainable and cleaner environment.

Biofilm-based technology for industrial wastewater treatment: current technology, applications and future perspectives

The microbial community in biofilm is safeguarded from the action of toxic chemicals, antimicrobial compounds, and harsh/stressful environmental circumstances. Therefore, biofilm-based technology has nowadays become a successful alternative for treating industrial wastewater as compared to suspended growth-based technologies. In biofilm reactors, microbial cells are attached to static or free-moving materials to form a biofilm which facilitates the process of liquid and solid separation in biofilm-mediated operations. This paper aims to review the state-of-the-art of recent research on bacterial biofilm in industrial wastewater treatment including biofilm fundamentals, possible applications and problems, and factors to regulate biofilm formation. We discussed in detail the treatment efficiencies of fluidized bed biofilm reactor (FBBR), trickling filter reactor (TFR), rotating biological contactor (RBC), membrane biofilm reactor (MBfR), and moving bed biofilm reactor (MBBR) for different types of industrial wastewater treatment. Besides, biofilms have many applications in food and agriculture, biofuel and bioenergy production, power generation, and plastic degradation. Furthermore, key factors for regulating biofilm formation were also emphasized. In conclusion, industrial applications make evident that biofilm-based treatment technology is impactful for pollutant removal. Future research to address and improve the limitations of biofilm-based technology in wastewater treatment is also discussed.

Nanofiltration Treatment of Industrial Wastewater Doped with Organic Dye: A Study of Hydrodynamics and Specific Energy

This study was conducted to eliminate the ions and molecules present in the industrial wastewater received by the municipal wastewater treatment plant (WWTP) of Reghaia, which is located east of Algiers, Algeria. The process was developed for two different study matrices: (a) the wastewater from WWTP and (b) wastewater mixed with Brilliant Blue FCF (BBF) dye to show the influence of the strength of the ionic solution on the treatment. The most effective operating parameters were determined by assessing the residence time distribution applied to the reactor flow regime. Energy analysis showed the viability of a nanofiltration membrane, improving the permeate flux. The nanofiltration process consumed 1.94 kWh/m3 to reduce the chemical oxygen demand (COD) of 63.58% and 48.35% for raw wastewater and doped BBF wastewater, respectively. The results demonstrated that nanofiltration performance with a volume dilution ratio of 1/2 showed the reduction of the COD of 87.2% after 15 min for undoped wastewater, whereas the retention rate decreases to 64% with an increase of dilution ratio to 4/5 for the same water matrix. The influence of a pH of 5 has a significant influence on the composition of the wastewater matrix by the reduction of COD of 49.8% and 59.68% for doped wastewater and raw wastewater, respectively. This could be explained by the isolated points of the membrane in the order of 4.5.

Homogeneously and heterogeneously structured biofilm models for wastewater treatment

Biofilm, a layer comprising extracellular polymeric substances, is the platform where the embedded living cells degrade the substances in the wastewaters. Biofilm models have been developed as part of the comprehensive models for the wastewater treatment process. This review summarizes the biofilm models applied in contemporary literature based on the spatial dimensions adopted for model build-up. The most commonly applied biofilm models are null-dimensional, considering the biofilm active biomass for the substrate sink's biological reaction. The one-dimensional, multi-species models are the second standard models for contemporary studies, providing transport and reaction resistances of substrates in the biofilm matrix and the interactions of competing or collaborating strains in the biofilm. The structural homogeneity of the biofilm challenges the validity of the uniformly structured models, highlighting the need to re-examine the validity of the uniformly structured models. The challenges and prospects of biofilm model developments and applications are outlined.

Utilization of Response Surface Methodology in Optimization and Modelling of a Microbial Electrolysis Cell for Wastewater Treatment Using Box–Behnken Design Method

A vast quantity of untreated wastewater is discharged into the environment, resulting in contamination of receiving waters. A microbial electrolysis cell (MEC) is a promising bioelectrochemical system (BES) for wastewater treatment and energy production. However, poor design and control of MEC variables may lead to inhibition in the system. This study explored the utilization of Response Surface Methodology (RSM) on the synergistic aspects of MEC and magnetite nanoparticles for wastewater treatment. Influences of temperature (25–35 °C), voltage supply (0.3–1.3 V) and magnetite nanoparticle dosage (0.1–1.0 g) on the biochemical methane potentials (BMPs) were investigated with the aim of optimizing biogas yield, chemical oxygen demand removal and current density. The analysis of variance (ANOVA) technique verified that the quadratic models obtained were substantial, with p-values below 0.05 and high regression coefficients (R2). The optimum biogas yield of 563.02 mL/g VSfed, chemical oxygen demand (COD) removal of 97.52%, and current density of 26.05 mA/m2 were obtained at 32.2 °C, 0.77 V and 0.53 g. The RSM revealed a good comparison between the predicted and actual responses. This study revealed the effective utilization of statistical modeling and optimization to improve the performance of the MEC to achieve a sustainable and eco-friendly situation.

SVM and ANN Modelling Approach for the Optimization of Membrane Permeability of a Membrane Rotating Biological Contactor for Wastewater Treatment

Membrane fouling significantly hinders the widespread application of membrane technology. In the current study, a support vector machine (SVM) and artificial neural networks (ANN) modelling approach was adopted to optimize the membrane permeability in a novel membrane rotating biological contactor (MRBC). The MRBC utilizes the disk rotation mechanism to generate a shear rate at the membrane surface to scour off the foulants. The effect of operational parameters (disk rotational speed, hydraulic retention time (HRT), and sludge retention time (SRT)) was studied on the membrane permeability. ANN and SVM are machine learning algorithms that aim to predict the model based on the trained data sets. The implementation and efficacy of machine learning and statistical approaches have been demonstrated through real-time experimental results. Feed-forward ANN with the back-propagation algorithm and SVN regression models for various kernel functions were trained to augment the membrane permeability. An overall comparison of predictive models for the test data sets reveals the model’s significance. ANN modelling with 13 hidden layers gives the highest R2 value of >0.99, and the SVM model with the Bayesian optimizer approach results in R2 values higher than 0.99. The MRBC is a promising substitute for traditional suspended growth processes, which aligns with the stipulations of ecological evolution and environmentally friendly treatment.

Kenics Static Mixer Combined with Gas Sparging for the Improvement of Cross-Flow Microfiltration: Modeling and Optimization

The use of membrane filtration as a downstream process for microbial biomass harvesting is hampered due to the low permeate flux values achieved during the microfiltration of fermentation broths. Several hydrodynamic methods for increasing permeate flux by creating turbulent flow patterns inside the membrane module are used to overcome this problem. The main goal of this study was to investigate the combined use of a Kenics static mixer and gas sparging during cross-flow microfiltration of Bacillus velezensis IP22 cultivation broth. Optimization of the microfiltration process was performed by using the response surface methodology. It was found that the combined use of a static mixer and gas sparging leads to a considerable increase in the permeate flux, up to the optimum steady-state permeate flux value of 183.42 L·m−2·h−1 and specific energy consumption of 0.844 kW·h·m−3. The optimum steady-state permeate flux is almost four times higher, whilst, at the same time, the specific energy consumption is almost three times lower compared to the optimum results achieved using gas sparging alone. The combination of Kenics static mixer and gas sparging during cross-flow microfiltration is a promising technique for the enhancement of steady-state permeate flux with simultaneously decreasing specific energy consumption.

Confounding Effect of Wetting, Compaction, and Fouling in an Ultra-Low-Pressure Membrane Filtration: A Review

Ultra-low-pressure membrane (ULPM) filtration has emerged as a promising decentralized water and wastewater treatment method. It has been proven effective in long-term filtration under stable flux without requiring physical or chemical cleaning, despite operating at considerably lower flux. The use of ultra-low pressure, often simply by hydrostatic force (often called gravity-driven membrane (GDM) filtration), makes it fall into the uncharted territory of common pressure-driven membrane filtration. The applied polymeric membrane is sensitive to compaction, wetting, and fouling. This paper reviews recent studies on membrane compaction, wetting, and fouling. The scope of this review includes studies on those phenomena in the ULPM and how they affect the overall performance of the system. The performance of GDM systems for water and wastewater treatment is also evaluated. Finally, perspectives on the future research direction of ULPM filtration are also detailed.

Effect of Operating Parameters and Energy Expenditure on the Biological Performance of Rotating Biological Contactor for Wastewater Treatment

The rotating biological contactor (RBC) is resistant to toxic chemical and shock loadings, and this results in significant organic and nutrient removal efficiencies. The RBC system offers a low-energy footprint and saves up to 90% in energy costs. Due to the system’s low-energy demand, it is easily operable with renewable energy sources, either solar or wind power. An RBC was employed to degrade pollutants in domestic wastewater through biodegradation mechanisms in this study. The high microbial population in the RBC bioreactor produced excellent biological treatment capacity and higher effluent quality. The results showed that the RBC bioreactor achieved an average removal efficiency of 73.9% of chemical oxygen demand (COD), 38.3% of total nitrogen (TN), 95.6% of ammonium, and 78.9% of turbidity. Investigation of operational parameters, disk rotational speed, HRT, and SRT, showed the biological performance impact. Disk rotational speed showed uniform effluent quality at 30–40 rpm, while higher values of disk rotational speed (>40 rpm) resulted in lower effluent quality in COD, TN, and turbidity. The longer hydraulic retention time and sludge retention time (SRT) facilitated higher biological performance efficiency. The longer SRTs enabled the higher TN removal efficiency because of the higher quantity of microbial biomass retention. The longer SRT also resulted in efficient sludge-settling properties and reduced volume of sludge production. The energy evaluation of the RBC bioreactor showed that it consumed only 0.14 kWh/m3, which is significantly lower than the conventional treatment methods; therefore, it is easily operable with renewable energy sources. The RBC is promising substitute for traditional suspended growth processes as higher microbial activity, lower operational and maintenance costs, and lower carbon foot print enhanced the biological performance, which aligns with the stipulations of ecological evolution and environment-friendly treatment.

Response Surface Methodology and Artificial Neural Network Modelling of Membrane Rotating Biological Contactors for Wastewater Treatment

Membrane fouling is a major hindrance to widespread wastewater treatment applications. This study optimizes operating parameters in membrane rotating biological contactors (MRBC) for maximized membrane fouling through Response Surface Methodology (RSM) and an Artificial Neural Network (ANN). MRBC is an integrated system, embracing membrane filtration and conventional rotating biological contactor in one individual bioreactor. The filtration performance was optimized by exploiting the three parameters of disk rotational speed, membrane-to-disk gap, and organic loading rate. The results showed that both the RSM and ANN models were in good agreement with the experimental data and the modelled equation. The overall R² value was 0.9982 for the proposed network using ANN, higher than the RSM value (0.9762). The RSM model demonstrated the optimum operating parameter values of a 44 rpm disk rotational speed, a 1.07 membrane-to-disk gap, and a 10.2 g COD/m² d organic loading rate. The optimization of process parameters can eliminate unnecessary steps and automate steps in the process to save time, reduce errors and avoid duplicate work. This work demonstrates the effective use of statistical modeling to enhance MRBC system performance to obtain a sustainable and energy-efficient treatment process to prevent human health and the environment.