Biochar/layered double hydroxide (LDH) composites have gained considerable attention in recent times as low-cost sustainable materials for applications in water treatment. This paper critically evaluates the latest development in applications of biochar/LDH composites in water treatment with an emphasis on adsorption and catalytic degradation of various pollutants. The adsorption of various noxious contaminants, i.e., heavy metals, dyes, anions, and pharmaceuticals onto biochar/LDH composites are described in detail by elaborating the adsorption mechanism and regeneration ability. The synergistic effect of LDH with biochar exhibited significant improvement in specific surface area, surface functional groups, structure heterogeneity, stability, and adsorption characteristics of the resulting biochar/LDH composites. The major hurdles and challenges associated with the synthesis and applications of biochar/LDH composites in water remediation are emphasized. Finally, a roadmap is suggested for future research to assure the effective applications of biochar/LDH composites in water purification.
This paper elucidates the capability of isolated indigenous bacteria to remove aluminium from wastewater and soil. Two indigenous species of Brochothrix thermosphacta and Vibrio alginolyticus were isolated from an aluminium-contaminated site. These two species were used to treat aluminium-containing wastewater and contaminated soil using the bioaugmentation method. B. thermosphacta showed the highest aluminium removal of 57.87 ± 0.45% while V. alginolyticus can remove aluminium up to 59.72 ± 0.33% from wastewater. For aluminium-contaminated soil, B. thermosphacta and V. alginolyticus, showed a highest removal of only 4.58 ± 0.44% and 5.48 ± 0.58%, respectively. The bioaugmentation method is more suitable to be used to treat aluminium in wastewater compared to contaminated soil. The produced biomass separation after wastewater treatment was so much easier and applicable, compared to the produced biomass handling from contaminated soil treatment. A 48.55 ± 2.45% and 40.12 ± 4.55% of aluminium can be recovered from B. thermosphacta and V. alginolyticus biomass, respectively, with 100 mg/L initial aluminium concentration in wastewater.
The coexistence of algae and bacteria in nature dates back to the very early stages when life came into existence. The interaction between algae and bacteria plays an important role in the planet ecology, cycling nutrients, and feeding higher trophic levels, and have been evolving ever since. The emerging concept of algal-bacterial consortia is gaining attention, much towards environmental management and protection. Studies have shown that algal-bacterial synergy does not only promote carbon capture in wastewater bioremediation but also consequently produces biofuels from algal-bacterial biomass. This review has evaluated the optimistic prospects of algal-bacterial consortia in environmental remediation, biorefinery, carbon sequestration as well as its contribution to the production of high-value compounds. In addition, algal-bacterial consortia offer great potential in bloom control, dye removal, agricultural biofertilizers, and bioplastics production. This work also emphasizes the advancement of algal-bacterial biotechnology in environmental management through the incorporation of Industry Revolution 4.0 technologies. The challenges include its pathway to greener industry, competition with other food additive sources, societal acceptance, cost feasibility, environmental trade-off, safety and compatibility. Thus, there is a need for further in-depth research to ensure the environmental sustainability and feasibility of algal-bacterial consortia to meet numerous current and future needs of society in the long run.
Methylene blue is a refractory pollutant commonly present in textile wastewater. This study tests the feasibility of TiO2/graphene oxide (GO) composite in enhancing photocatalytic degradation of MB in synthetic wastewater with respect to scientific and engineering aspects. To enhance its removal, we vary the composition of the composite based on the TiO2 weight. Under UV-vis irradiation, the effects of photocatalyst's dose, pH, and reaction time on MB removal by the composites are evaluated under optimum conditions, while any changes in their physico-chemical properties before and after treatment are analyzed by using TEM, SEM, XRD, FTIR and BET. The photodegradation pathways of the target pollutant by the composite and its removal mechanisms are also elaborated. It is found that the same composite with a 1:2 wt ratio of GO/TiO2 has the largest surface area of 104.51 m2/g. Under optimum reactions (0.2 g/L of dose, pH 10, and 5 mg/L of pollutant's concentration), an almost complete MB removal could be attained within 4 h. This result is higher than that of the TiO2 alone (30%) under the same conditions. Since the treated effluents could meet the strict discharge standard limit of ≤0.2 μg/L set by China's regulation, subsequent biological treatments are unnecessary for completing biodegradation of remaining oxidation by-products in the wastewater effluents.
There is a pressing need for efficient biological treatment systems for the removal of organic compounds in greywater given the rapid increase in household wastewater produced as a consequence of rapid urbanisation. Moreover, proper treatment of greywater allows its reuse that can significantly reduce the demand for freshwater supplies. Herein, we demonstrate the possibility of enhancing the removal efficiency of solid contaminants from greywater using MHz-order surface acoustic waves (SAWs). A key distinction of the use of these high frequency surface acoustic waves, compared to previous work on its lower frequency (kHz order) bulk ultrasound counterpart for wastewater treatment, is the absence of cavitation, which can inflict considerable damage on bacteria, thus limiting the intensity and duration, and hence the efficiency enhancement, associated with the acoustic exposure. In particular, we show that up to fivefold improvement in the removal efficiency can be obtained, primarily due to the ability of the acoustic pressure field in homogenizing and reducing the size of bacterial clusters in the sample, therefore providing a larger surface area that promotes greater bacteria digestion. Alternatively, the SAW exposure allows the reduction in the treatment duration to achieve a given level of removal efficiency, thus facilitating higher treatment rates and hence processing throughput. Given the low-cost of the miniature chipscale platform, these promising results highlight its possibility for portable greywater treatment for domestic use or for large-scale industrial wastewater processing through massive parallelization.
To ensure the safe discharge of treated wastewater to the environment, continuous efforts are vital to enhance the modelling accuracy of wastewater treatment plants (WWTPs) through utilizing state-of-art techniques and algorithms. The integration of metaheuristic modern optimization algorithms that are natlurally inspired with the Fussy Inference Systems (FIS) to improve the modelling performance is a promising and mathematically suitable approach. This study integrates four population-based algorithms, namely: Particle swarm optimization (PSO), Genetic algorithm (GA), Hybrid GA-PSO, and Mutating invasive weed optimization (M-IWO) with FIS system. A full-scale WWTP in South Africa (SA) was selected to assess the validity of the proposed algorithms, where six wastewater effluent parameters were modeled, i.e., Alkalinity (ALK), Sulphate (SLP), Phosphate (PHS), Total Kjeldahl Nitrogen (TKN), Total Suspended Solids (TSS), and Chemical Oxygen Demand (COD). The results from this study showed that the hybrid PSO-GA algorithm outperforms the PSO and GA algorithms when used individually, in modelling all wastewater effluent parameters. PSO performed better for SLP and TKN compared to GA, while the M-IWO algorithm failed to provide an acceptable modelling convergence for all the studied parameters. However, three out of four algorithms applied in this study proven beneficial to be optimized in enhancing the modelling accuracy of wastewater quality parameters.
This study investigated acclimation ability of native Chlorella sorokiniana (CS-N) and commercial Chlorella sorokiniana (CS-C) in palm oil mill effluent (POME), their metabolic profile and feasibility of effluent recycling for dilution purpose. Maximum specific growth rate, µmax and lag time, λ of the microalgae were evaluated. Result shows both strains produced comparable growth in POME, with µmax of 0.31 day-1 and 0.30 day-1 respectively, albeit longer λ by the CS-C. However, three cycles of acclimation was able to reduce λ from eight days to two days for CS-C. Metabolic profiling using principal component analysis (PCA) shows clear cluster of acclimatized strains to suggest better stress tolerance of CS-N. Finally, a remarkable µmax of 0.57 day-1 without lag phase was achieved using acclimatized CS-N in 40% POME concentration. Acclimation has successfully shortened the λ and dilution with final effluent was proved to be feasible for further improvement of the microalgae growth.
This study was conducted to examine the production of bioflocculants using agricultural wastewater as a fermentation feedstock under different temperatures and incubation times. The mechanism of flocculation was studied to gain a detailed understanding of the flocculation activity. The highest bioflocculant yield (2.03 g/L) at a temperature of 40 °C was produced in a palm oil mill effluent medium (BioF-POME). Bioflocculant produced from a fermented SME medium (BioF-SME) showed the highest activity. The flocculation tests for colour and turbidity removal from lake water indicated that BioF-SME and BioF-POME performed comparably to commercial alum. Analyses of the bioflocculants using liquid chromatography-mass spectrometry (LC-MS) found that the bioflocculants contained xylose and glucose. The mechanism study showed that flocculation occurred through charge neutralization and interparticle bridging between the bioflocculant polymer and the particles in the lake water. Thus, agricultural wastewater can be used as a fermentation feedstock for high-quality bioflocculants.
The biodegradability and safety of the bioflocculants make them a potential alternative to non-biodegradable chemical flocculants for wastewater treatment. However, low yield and production cost has been reported to be the limiting factor for large scale bioflocculant production. Although the utilization of cheap nutrient sources is generally appealing for large scale bioproduct production, exploration to meet the demand for them is still low. Although much progress has been achieved at laboratory scale, Industrial production and application of bioflocculant is yet to be viable due to cost of the production medium and low yield. Thus, the prospects of bioflocculant application as an alternative to chemical flocculants is linked to evaluation and utilization of cheap alternative and renewable nutrient sources. This review evaluates the latest literature on the utilization of waste/wastewater as an alternative substitute for conventional expensive nutrient sources. It focuses on the mechanisms and metabolic pathways involved in microbial flocculant synthesis, culture conditions and nutrient requirements for bioflocculant production, pre-treatment, and also optimization of waste substrate for bioflocculant synthesis and bioflocculant production from waste and their efficiencies. Utilization of wastes as a microbial nutrient source drastically reduces the cost of bioflocculant production and increases the appeal of bioflocculant as a cost-effective alternative to chemical flocculants.
Currently, research trends on aerobic granular sludge (AGS) have integrated the operating conditions of extracellular polymeric substances (EPS) towards the stability of AGS systems in various types of wastewater with different physical and biochemical characteristics. More attention is given to the stability of the AGS system for real site applications. Although recent studies have reported comprehensively the mechanism of AGS formation and stability in relation to other intermolecular interactions such as microbial distribution, shock loading and toxicity, standard operating condition control strategies for different types of wastewater have not yet been discussed. Thus, the dimensional multi-layer structural model of AGS is discussed comprehensively in the first part of this review paper, focusing on diameter size, thickness variability of each layer and diffusion factor. This can assist in facilitating the interrelation between disposition and stability of AGS structure to correspond to the changes in wastewater types, which is the main objective and novelty of this review.
The growing prevalence of new toxins in the environment continues to cause widespread concerns. Pharmaceuticals, organic pollutants, heavy metal ions, endocrine-disrupting substances, microorganisms, and others are examples of persistent organic chemicals whose effects are unknown because they have recently entered the environment and are displaying up in wastewater treatment facilities. Pharmaceutical pollutants in discharged wastewater have become a danger to animals, marine species, humans, and the environment. Although their presence in drinking water has generated significant concerns, little is known about their destiny and environmental effects. As a result, there is a rising need for selective, sensitive, quick, easy-to-handle, and low-cost early monitoring detection systems. This study aims to deliver an overview of a low-cost carbon-based composite to detect and remove pharmaceutical components from wastewater using the literature reviews and bibliometric analysis technique from 1970 to 2021 based on the web of science (WoS) database. Various pollutants in water and soil were reviewed, and different methods were introduced to detect pharmaceutical pollutants. The advantages and drawbacks of varying carbon-based materials for sensing and removing pharmaceutical wastes were also introduced. Finally, the available techniques for wastewater treatment, challenges and future perspectives on the recent progress were highlighted. The suggestions in this article will facilitate the development of novel on-site methods for removing emerging pollutants from pharmaceutical effluents and commercial enterprises.
Rhodamine B (RhB) dye used in the textile industries is associated with carcinogenic and neurotoxic effects with a high potential to cause a variety of human diseases. Semiconductor photocatalysts synthesised through agriculture waste extracts exhibited high efficiency for RhB removal. The current review aimed to explore the efficiency and mechanism of RhB degradation using different photocatalysts that have been used in recent years, as well as the effect of various factors on the removal process. Zinc oxide nanoparticles (ZnO NPs) synthesised from plant extract is the most effective for the RhB degradation with the efficiency reaching 100% after 210 min. The photocatalysis process depends on the pH because pH changes the balance of water dissociation, which impacts the formation of hydroxyl radicals and the surface load of the catalyst. Analysis using Jupyter Notebook revealed a strong correlation between the concentration of ZnO NPs and the photocatalysis efficiency (R = 0.72). These findings reveal that man-sized photocatalysts have a high potential for removing RhB from the wastewater.
Microalgae are drawing attentions among researchers for their biorefinery use or value-added products. The high production rate of biomasses produced are attractive for conversion into volatile biochar. Torrefaction, pyrolysis and hydrothermal carbonization are the recommended thermochemical conversion techniques that could produce microalgal-based biochar with desirable physiochemical properties such as high surface area and pore volume, abundant surface functional groups, as well as functionality such as high adsorption capacity. The characterizations of the biochar significantly influence the mechanisms in adsorption of pollutants from wastewaters. Specific adsorption of the organic and inorganic pollutants from the effluent are reviewed to examine the adsorption capacity and efficiency of biochar derived from different microalgae species. Last but not least, future remarks over the challenges and improvements are discussed accordingly. Overall, this review would discuss the synthesis, characterization and application of the microalgal-based biochar in wastewater.
Conventional wastewater treatment technologies have difficulties in feasibly removing persistent organics. The photocatalytic oxidation of these contaminants offers an economical and environmentally friendly solution. In this study, TiO2 membranes and Ag/TiO2 membranes were prepared and used for the decomposition of dissolved formic acid in wastewater. The photochemical deposition of silver on a TiO2 membrane improved the decomposition rate. The rate doubled by depositing ca. 2.5 mg of Ag per 1 g of TiO2. The influence of salinity on formic acid decomposition was studied. The presence of inorganic salts reduced the treatment performance of the TiO2 membranes to half. Ag/TiO2 membranes had a larger reduction of ca. 40%. The performance was recovered by washing the membranes with water. The anion adsorption on the membrane surface likely caused the performance reduction.
This research aims to evaluate the performance of PolyCera® Titan membrane for different wastewater treatment. Membrane filtration of several cycles was conducted in understanding the fouling mechanism, fouling propensity, and defouling potential of the PolyCera® Titan which had not been studied by any other researcher before. The PolyCera® Titan membrane is effective for the treatment of textile industry wastewater, palm oil mill effluent (POME), leachate, and semiconductor-industry wastewater. Rejection of methylene blue (MB) and Congo red (CR) was in the range of 78.76-86.04% and 88.89-93.71%, respectively; 94.72-96.50% NaCl, 96.07-97.62% kaolin, and 97.26-97.73% glucose were rejected from synthetic leachate indicating the removal of TDS, TSS, and COD from the leachate, respectively. Standard blocking and complete model were the best models used to explain the PolyCera® Titan membrane fouling mechanism in all types of wastewater treatment processes with a high R2 value. Physical cleaning with the use of distilled water was able to recover the permeate flux with the flux recovery ratio (FRR) value in the range of 79.2-95.22% in the first cycle, 81.20-98.16% in the second cycle, and 86.09-95.96% in the third cycle.
One-time ultrasonication pre-treatment of Rhodobacter sphaeroides was evaluated for improving biohydrogen production via photofermentation. Batch experiments were performed by varying ultrasonication amplitude (15, 30, and 45%) and duration (5, 10, and 15 min) using combined effluents from palm oil as well as pulp and paper mill as a single substrate. Experimental data showed that ultrasonication at amplitude 30% for 10 min (256.33 J/mL) achieved the highest biohydrogen yield of 9.982 mL H2/mLmedium with 5.125% of light efficiency. A maximum CODtotal removal of 44.7% was also obtained. However, when higher ultrasonication energy inputs (>256.33 J/mL) were transmitted to the cells, biohydrogen production did not improve further. In fact, 20.6% decrease of biohydrogen yield (as compared to the highest biohydrogen yield) was observed using the most intense ultrasonicated inoculum (472.59 J/mL). Field emission scanning electron microscope images revealed the occurrence of cell damages and biomass losses if ultrasonication at 472.59 J/mL was used. The present results suggested that moderate ultrasonication pre-treatment was an effective technique to improve biohydrogen production performances of R. sphaeroides.
Researchers have broadly studied textile waste, but the research topics development and performance trends in this study area are still unclear. A bibliometric analysis was conducted to explore the global scientific literature to determine state of the art on textile waste over the past 16 years. Data of publications output are identified based on the Web of Science (from 2015 to 2020). This study used VOSviewer to analyse collaboration networks among authors, countries, institutions, and author's keywords in identifying five main clusters. A total of 3296 papers in textile waste research were identified. In this study, a total of 10451 authors were involved in textile waste research, and 36 authors among them published more than ten research publications in the period of this study. China has been in a top position in textile waste research moving from 3 output publications in 2005 to 91 output publications in 2020. Indian Institute of Technology System IIT System was ranked first in terms of the total publication number (85 publications, 2.45%). Textile wastewater and adsorption are the most commonly used keywords that reflect the current main research direction in this field and received more attention in recent years. Based on keyword cluster analysis outputs, textile waste research can be categorized into five types of clusters, namely (1) pollutant compositions, (2) component of textile wastewater, (3) treatment methods for textile wastewater, (4) effect mechanism of textile wastewater, and (5) recyclability of textile waste.
Water pollution and depletion of natural resources have motivated the utilization of green organic solvents in solvent extraction (SX) and liquid membrane (LM) for sustainable wastewater treatment and resource recovery. SX is an old and established separation method, while LM, which combines both the solute removal and recovery processes of SX in a single unit, is a revolutionary separation technology. The organic solvents used for solute removal in SX and LM can be categorized into sole conventional, mixed conventional-green, and sole green organic solvents, whereas the stripping agents used for solute recovery include acids, bases, metal salts, and water. This review revealed that the performance of greener organic solvents (mixed conventional-green and sole green organic solvents) was on par with the sole conventional organic solvents. However, some green organic solvents may threaten food security, while others could be pricey. The distinctive extraction theories of various sole green organic solvents (free fatty acid-rich oils, triglyceride-rich oils, and deep eutectic solvents) affect their application suitability for a specific type of wastewater. Organic liquid wastes are among the optimal green organic solvents for SX and LM in consideration of their triple environmental, economic, and performance benefits.
Photo-Fenton oxidation is one of the most promising processes to remove recalcitrant contaminants from industrial wastewater. In this study, we developed a novel heterogeneous catalyst to enhance photo-Fenton oxidation. Multi-composition (Fe-Cu-Zn) on aluminosilicate zeolite (ZSM-5) was prepared using a chemical process. Subsequently, the synthesized catalyst was characterized by using X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), high-resolution transmission electron microscopy (HRTEM), energy dispersive X-ray (spectroscopy) (EDX), and Brunauer-Emmett-Teller (BET). Activity of the synthesized catalyst is analysed to degrade an azo dye, methyl orange. Taguchi method is used to optimize color removal and total carbon content (TOC) removal. The dye completely degraded, and 76% of TOC removal was obtained at optimized process conditions. The amount of catalyst required for the desired degradation of dye significantly reduced up to 92% and 30% compared to conventional homogenous and heterogeneous Fenton oxidation processes, respectively.
Accurate prediction of inlet chemical oxygen demand (COD) is vital for better planning and management of wastewater treatment plants. The COD values at the inlet follow a complex nonstationary pattern, making its prediction challenging. This study compared the performance of several novel machine learning models developed through hybridizing kernel-based extreme learning machines (KELMs) with intelligent optimization algorithms for the reliable prediction of real-time COD values. The combined time-series learning method and consumer behaviours, estimated from water-use data (hour/day), were used as the supplementary inputs of the hybrid KELM models. Comparison of model performances for different input combinations revealed the best performance using up to 2-day lag values of COD with the other wastewater properties. The results also showed the best performance of the KELM-salp swarm algorithm (SSA) model among all the hybrid models with a minimum root mean square error of 0.058 and mean absolute error of 0.044.