The utilization of natural zeolite (NZ) as an adsorbent for NH4+ removal was investigated. Three types of NZ (i.e., NZ01, NZ02, and NZ03) were characterized, and their NH4+ adsorption process in aqueous solution was evaluated. The effect of pH towards NH4+ adsorption showed that the NZ01 has the highest NH4+ adsorption capacity compared with other natural zeolites used. The application of NZ01 for a simultaneous removal of NH4+ and turbidity in synthetic NH4+-kaolin suspension by adsorptive coagulation process for treating drinking water was studied. The addition of NZ01 into the system increased the NH4+ removal efficiency (ηNH4+) from 11.64% without NZ01 to 41.86% with the addition of 0.2 g L-1 of NZ01. The turbidity removal (ηT), however, was insignificantly affected since the ηT was already higher than 98.0% over all studied parameter's ranges. The thermodynamic and kinetic data analyses suggested that the removal of NH4+ obeyed the Temkin isotherm model and pseudo-second-order kinetic model, respectively. Generally, the turbidity removal was due to the flocculation of destabilized solid particles by alum in the suspension system. The ηNH4+ in surface water was 29.31%, which is lower compared with the removal in the synthetic NH4+-kaolin suspension, but a high ηT (98.65%) was observed. It was found that the addition of the NZ01 could enhance the removal of NH4+ as well as other pollutants in the surface water.
Due to the rapid growth in the heavy metal-based industries, their effluent and local dumping have created significant environmental issues. In the past, typically, removal of heavy metals was handled by reverse osmosis and ion exchange techniques, but these methods have many disadvantages. Therefore, extensive work into the development of improved techniques has increased, especially for heavy metal removal. Many countries are currently researching new materials and techniques based on nanotechnology for various applications that involve extracting heavy metals from different water sources such as wastewater, groundwater, drinking water and surface water. Nanotechnology provides the possibility of enhancing existing techniques to tackle problems more efficiently. The development in nanotechnology has led to the discovery of many new materials such as magnetic nanoparticles. These nanoparticles demonstrate excellent properties such as surface-volume ratio, higher surface area, low toxicity and easy separation. Besides, magnetic nanoparticles can be easily and efficiently recovered after adsorption compared with other typical adsorbents. This review mainly emphasises on the efficiency of heavy metal removal using magnetic nanoadsorbent from aqueous solution. In addition, an in-depth analysis of the synthesis, characterisation and modification approaches of magnetic nanoparticles is systematically presented. Furthermore, future opportunities and challenges of using magnetic particles as an adsorbent for the removal of heavy metals are also discussed.
The textile industry consumes a large volume of organic dyes and water. These organic dyes, which remained in the effluents, are usually persistent and difficult to degrade by conventional wastewater treatment techniques. If the wastewater is not treated properly and is discharged into water system, it will cause environmental pollution and risk to living organisms. To mitigate these impacts, the photo-driven catalysis process using semiconductor materials emerges as a promising approach. The semiconductor photocatalysts are able to remove the organic effluent through their mineralization and decolorization abilities. Besides the commonly used titanium dioxide (TiO2), manganese dioxide (MnO2) is a potential photocatalyst for wastewater treatment. MnO2 has a narrow bandgap energy of 1~2 eV. Thus, it possesses high possibility to be driven by visible light and infrared light for dye degradation. This paper reviews the MnO2-based photocatalysts in various aspects, including its fundamental and photocatalytic mechanisms, recent progress in the synthesis of MnO2 nanostructures in particle forms and on supporting systems, and regeneration of photocatalysts for repeated use. In addition, the effect of various factors that could affect the photocatalytic performance of MnO2 nanostructures are discussed, followed by the future prospects of the development of this semiconductor photocatalysts towards commercialization.
The performance of local plants was tested using synthetic turbid water resembling real wastewater by measuring their ability to remove turbidity. The selected plants were A. indica, S. palustris, D. linearis, S. polyanthum, M. esculenta, P. sarmentosum, and M. malabathricum which can easily be found locally. The experiment was run based on coagulant dosages varied from 0 to 10 g/L for each plant with a rapid mixing speed at 180 rpm for 3 min, slow mixing speed at 10 rpm for 20 min, and settling time for 30 min. The results demonstrated that each plant has been capable of reducing turbidity by different amounts, with an increase in the coagulant dosage. The optimum coagulant dosages achieved for A. indica, S. palustris, S. polyanthum, and D. linearis were 10 g/L with turbidity removal at 26.9%, 24.9%, 24.9%, and 17.5%, respectively. P. sarmentosum and M. esculenta attained optimum coagulant dosages at 5 g/L with turbidity removal at 24.2% and 22.2%, and lastly M. malabathricum at 0.1 g/L (12.2%). P. sarmentosum was suggested to the best natural coagulant which achieved the highest removal of turbidity with a low dosage used.
As clean water can be considered among the essentials of human life, there is always a requirement to seek its foremost and high quality. Water primarily becomes polluted due to organic as well as inorganic pollutants, including nutrients, heavy metals, and constant contamination with organic materials. Predicting the quality of water accurately is essential for its better management along with controlling pollution. With stricter laws regarding water treatment to remove organic and biologic materials along with different pollutants, looking for novel technologic procedures will be necessary for improved control of the treatment processes by water utilities. Linear regression-based models with relative simplicity considering water prediction have been typically used as available statistical models. Nevertheless, in a majority of real problems, particularly those associated with modeling of water quality, non-linear patterns will be observed, requiring non-linear models to address them. Thus, artificial intelligence (AI) can be a good candidate in modeling and optimizing the elimination of pollutants from water in empirical settings with the ability to generate ideal operational variables, due to its recent considerable advancements. Management and operation of water treatment procedures are supported technically by these technologies, leading to higher efficiency compared to sole dependence on human operations. Thus, establishing predictive models for water quality and subsequently, more efficient management of water resources would be critically important, serving as a strong tool. A systematic review methodology has been employed in the present work to investigate the previous studies over the time interval of 2010-2020, while analyzing and synthesizing the literature, particularly regarding AI application in water treatment. A total number of 92 articles had addressed the topic under study using AI. Based on the conclusions, the application of AI can obviously facilitate operations, process automation, and management of water resources in significantly volatile contexts.
Chemical coagulants like alum, ferric salts, and polyacrylamide derivatives are helpful in water treatment. However, the long-term detrimental effects of chemical coagulants on humans and the environment require alternative research for natural coagulants. This study used novel leguminous (green beans (GB), pigeon pea (PP)), fruit seeds (Tamarind indica (TI), and date palm (DS)) as coagulants to remove turbidity. The seeds were powdered, and the crude active coagulants were extracted with distilled water and a 1 M NaCl solution. The result showed that PP's distilled water extract had the highest turbidity removal of 81.12%, while DS had the least performance of 62.54%. The NaCl extract of PP had the highest removal (94.62%), followed by TI (76.08%). This study found the optimum doses for GB, TI, PP, and DS to be 50, 40, 10, and 70 mL/L, with their optimum pH at 3, 1, 3, and 1, respectively. The FTIR spectra confirmed the existence of -OH, -NH, COOH, C = O, C-C, and C-H peaks, indicating the presence of protein-specific functional groups supporting their potential use as coagulants. Therefore, PP would have been used based on turbidity performance; however, due to their nutritional value, TI and DS are suitable seeds for the coagulation-flocculation treatment of turbid water because they are waste materials.
17α-methyltestosterone (MT) hormone is a synthetic androgenic steroid hormone utilized to induce Nile tilapia transitioning for enhanced production yield. This study specifically focuses on the removal of MT through the utilization of photocatalytic membrane reactor (PMR), which employs an in-house polyvinylidene fluoride (PVDF) ultrafiltration membrane modified with 1% nanomaterials (either TiO2 or α-Fe2O3). The molecular weight cut-off (MWCO) of the in-house membrane falls within the ultrafiltration range. Under UV95W radiation, the PMR with PVDF/TiO2 and PVDF/α-Fe2O3 membranes achieved 100% MT removal at 140 and 160 min, respectively. The MT removal by the commercial NF03 membrane was only at 50%. In contrast, without light irradiation, the MT removal by all the membranes remained unchanged after 180 min, exhibiting lower performance. The incorporation of TiO2 and α-Fe2O3 enhanced water flux and MT removal of the membrane. Notably, the catalytic activity was limited by the distribution and concentration of the catalyst at the membrane surface. The water contact angle did not correlate with the water flux for the composited membrane. The degradation of MT aligned well with Pseudo-first-order kinetic models. Thus, the in-house ultrafiltration PMR demonstrated superior removal efficiency and lower operational costs than the commercial nanofiltration membrane, attributable to its photocatalytic activities.
This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as fresh water production and vapor temperatures. Evaluation metrics reveal the integrated ANN-ICA model outperforms the classic ANN, achieving a remarkable 20% reduction in mean squared error (MSE). The emotional artificial neural network (EANN) demonstrates superior accuracy, attaining an impressive 99% coefficient of determination (R2) in predicting freshwater production and vapor temperatures. The comprehensive comparative analysis extends to environmental assessments, displaying the solar desalination system's compatibility with renewable energy sources. Results highlight the potential for the proposed system to conserve water resources and reduce environmental impact, with a substantial decrease in total dissolved solids (TDS) from over 6,000 ppm to below 50 ppm. The findings underscore the efficacy of machine learning models in optimizing solar-driven desalination systems, providing valuable insights into their capabilities for addressing water scarcity challenges and contributing to the global shift toward sustainable and environmentally friendly water production methods.
The adsorption of ammonium from water was studied on an activated carbon obtained using raw oil palm shell and activated with acetic acid. The performance of this adsorbent was tested at different operating conditions including the solution pH, adsorbent dosage, and initial ammonium concentration. Kinetic and equilibrium studies were carried out, and their results were analyzed with different models. For the adsorption kinetics, the pseudo-first order equation was the best model to correlate this system. Calculated adsorption rate constants ranged from 0.071 to 0.074 g/mg min. The ammonium removal was 70-80% at pH 6-8, and it was significantly affected by electrostatic interaction forces. Ammonium removal (%) increased with the adsorbent dosage, and neutral pH condition favored the adsorption of this pollutant. The best ammonium adsorption conditions were identified with a response surface methodology model where the maximum removal was 91.49% with 2.27 g/L of adsorbent at pH 8.11 for an initial ammonium concentration of 36.90 mg/L. The application of a physical monolayer model developed by statistical physics theory indicated that the removal mechanism of ammonium was multi-ionic and involved physical interactions with adsorption energy of 29 kJ/mol. This activated carbon treated with acetic acid is promising to depollute aqueous solutions containing ammonium.
Synthetic dyes play a crucial role in our daily lives, especially in clothing, leather accessories, and furniture manufacturing. Unfortunately, these potentially carcinogenic substances are significantly impacting our water systems due to their widespread use. Dyes from various sources pose a serious environmental threat owing to their persistence and toxicity. Regulations underscore the urgency in addressing this problem. In response to this challenge, metal oxide nanoparticles such as titanium dioxide (TiO2), zinc oxide (ZnO), and iron oxide (Fe3O4) have emerged as intriguing options for dye degradation due to their unique characteristics and production methods. This paper aims to explore the types of nanoparticles suitable for dye degradation, various synthesis methods, and the properties of nanoparticles. The study elaborates on the photocatalytic and adsorption-desorption activities of metal oxide nanoparticles, elucidating their role in dye degradation and their application potential. Factors influencing degradation, including nanoparticle properties and environmental conditions, are discussed. Furthermore, the paper provides relevant case studies, practical applications in water treatment, and effluent treatment specifically in the textile sector. Challenges such as agglomeration, toxicity concerns, and cost-effectiveness are acknowledged. Future advancements in nanomaterial synthesis, their integration with other materials, and their impact on environmental regulations are potential areas for development. In conclusion, metal oxide nanoparticles possess immense potential in reducing dye pollution, and further research and development are essential to define their role in long-term environmental management.
Using bone char for contaminated wastewater treatment and soil remediation is an intriguing approach to environmental management and an environmentally friendly way of recycling waste. The bone char remediation strategy for heavy metal-polluted wastewater was primarily affected by bone char characteristics, factors of solution, and heavy metal (HM) chemistry. Therefore, the optimal parameters of HM sorption by bone char depend on the research being performed. Regarding enhancing HM immobilization by bone char, a generic strategy for determining optimal parameters and predicting outcomes is crucial. The primary objective of this research was to employ artificial neural network (ANN) technology to determine the optimal parameters via sensitivity analysis and to predict objective function through simulation. Sensitivity analysis found that for multi-metals sorption (Cd, Ni, and Zn), the order of significance for pyrolysis parameters was reaction temperature > heating rate > residence time. The primary variables for single metal sorption were solution pH, HM concentration, and pyrolysis temperature. Regarding binary sorption, the incubation parameters were evaluated in the following order: HM concentrations > solution pH > bone char mass > incubation duration. This approach can be used for further experiment design and improve the immobilization of HM by bone char for water remediation.
Adsorption is one of the most efficient methods for remediating industrial recalcitrant wastewater due to its simple design and low investment cost. However, the conventional adsorbents used in adsorption have several limitations, including high cost, low removal rates, secondary waste generation, and low regeneration ability. Hence, the focus of the research has shifted to developing alternative low-cost green adsorbents from renewable resources such as biomass. In this regard, the recent progress in the modification of biomass-derived adsorbents, which are rich in cellulosic content, through a variety of techniques, including chemical, physical, and thermal processes, has been critically reviewed in this paper. In addition, the practical applications of raw and modified biomass-based adsorbents for the treatment of industrial wastewater are discussed extensively. In a nutshell, the adsorption mechanism, particularly for real wastewater, and the effects of various modifications on biomass-based adsorbents have yet to be thoroughly studied, despite the extensive research efforts devoted to their innovation. Therefore, this review provides insight into future research needed in wastewater treatment utilizing biomass-based adsorbents, as well as the possibility of commercializing biomass-based adsorbents into viable products.
A circular gravity-phase separator using coalescing medium with cross flow was developed to remove oil and suspended solids from wastewaters. Coalescence medium in the form of inclined plates promotes rising of oil droplets through coalescence and settling of solid particles through coagulation. It exhibits 22.67% higher removal of total suspended solids (TSS) compared to separators without coalescing medium. Moreover, it removed more than 70% of oil compared to conventional American Petroleum Institute separators, which exhibit an average of 33% oil removal. The flowrate required to attain an effluent oil concentration of 10 mg/L (Q(o10)) at different influent oil concentrations (C(io)) can be represented by Q(o10) x 10(-5) = -0.0012C(io) + 0.352. The flowrate required to attain an effluent TSS concentration of 50 mg/L (Q(ss50)) at different influent TSS concentrations (C(iss)) can be represented by Q(ss50) x 10(-5) = 1.0 x 10(6) C(iss)(-2.9576). The smallest removable solid particle size was 4.87 microm.
Matched MeSH terms: Water Purification/instrumentation; Water Purification/methods*; Water Purification/standards
The main aim of this study is to investigate the performance of organic oxidation and denitrification of the system under long-term operation. The MFC reactor was operated in continuous mode for 180 days. Nitrate was successfully demonstrated as terminal electron acceptor, where nitrate was reduced at the cathode using electron provided by acetate oxidation at the anode. The removal efficiencies of chemical oxygen demand (COD) and nitrate were higher in the closed circuit system than in open circuit system. Both COD and nitrate reduction improved with the increase of organic loading and subsequently contributed to higher power output. The maximum nitrate removal efficiency was 88 ± 4 % (influent of 141 ± 14 mg/L). The internal resistant was 50 Ω, which was found to be low for a double chambered MFC. The maximum power density was 669 mW/m(3) with current density of 3487 mA/m(3).
Mesoporous carbon is a promising material having multiple applications. It can act as a catalytic support and can be used in energy storage devices. Moreover, mesoporous carbon controls body's oral drug delivery system and adsorb poisonous metal from water and various other molecules from an aqueous solution. The accuracy and improved activity of the carbon materials depend on some parameters. The recent breakthrough in the synthesis of mesoporous carbon, with high surface area, large pore-volume, and good thermostability, improves its activity manifold in performing functions. Considering the promising application of mesoporous carbon, it should be broadly illustrated in the literature. This review summarizes the potential application of mesoporous carbon in many scientific disciplines. Moreover, the outlook for further improvement of mesoporous carbon has been demonstrated in detail. Hopefully, it would act as a reference guidebook for researchers about the putative application of mesoporous carbon in multidimensional fields.
Increasing demands in palm oil industry hence resulting the production of palm oil to increase. It is then creating a major problem in disposing the waste to be treat in appropriate ways. The governments are forced to look for alternative technology for the palm oil mill effluent (POME) treatment because the demand of oil increases with the awareness on increasing environmental issue. Therefore, a new technology must be found in order to reduce energy consumption, to meet legal requirements on emission and for cost reduction and also increased quality of water treatment. Membrane Anaerobic System (MAS) is a promising alternative way to overcome these issues. In this study, the efficiency of the MAS performance increases to 99.03% in ten days operation. The application of Monod, Contois and Chen & Hashimoto models were used to analyze the performance of MAS for treating POME. The results from the experiment show the substrate removal model is well fits for estimation of kinetics membrane anaerobic system. Amongst them, the Contois and Monod models predicted the bio-kinetic reactions of the MAS very well with coefficient of determination (R2>97%) values. The MAS bioreactor was creating to be an improvement method as well as successful biological treatment since the graph shows linearized which is good agreement with reported in literature.
This paper studies the use of gamma irradiation for textile waste water treatment. Prior to irradiation, the raw wastewa ter was diluted using tap water to targeted concentration of COD 400 mg/l. The sample was irradiated at selected dose between the ranges of 2kGy to 100kGy. The results showed that Irradiation was effective in removing the highly colored refractory organic pollutants. The COD removal at lowest dose, 2kGy is about 310 mg/l. Meanwhile, at highest dose, 1 00kGy the COD reduced to 100mg/l. The degree of removal influenced by the dose introduced during the treatment pro cess. As the dose increased, higher removal of organic pollutant was recorded. On the other hand, other properties of t he wastewater such as pH, turbidity, suspended solid, BOD and color shows tremendous changes as the dose increases. This shows the concentration of pollutants and dose of irradiation applied are directly proportional to each other.
The present study reported for the first time covalent immobilization of protocatechuate 3,4-dioxygenase (3,4-POD) onto functionalized multi-walled carbon nanotubes (F-MWCNT) for degrading the toxic 3,4-dihydroxybenzoic acid (3,4-DHBA) pollutant in water. The F-MWCNTs had a maximum 3,4-POD loading of 1060 μg/mg. Immobilized 3,4 POD had 44% of relative structural changes to its free configurations. Nevertheless, >90% of relative activity and about 50% of catalytic efficiency were retained to the free enzyme. Immobilized 3,4-POD demonstrated higher alkaline stability and thermostability than the free 3,4-POD. The free and immobilized 3,4-POD lost 82% and 66% of relative activities, respectively after 180 min of incubations at 90 °C. Excellent shelf-life was observed for the immobilized 3,4-POD with residual activity of 56% compared with 41% and 39% of the free 3,4-POD at 4 °C and 25 °C over 30 days storage. Immobilized 3,4-POD showed >60% of catalytic activity retention even after ten-cycle uses, defraying the expenses of free 3,4-POD productions for long term uses. Finally, the immobilized 3,4-POD removed 71% of 3,4-DHBA from water in <4 h, paving its future application for water purification with reduced costs and time.
Treated palm oil mill effluents (POME) is of great concern as it still has colour from its dissolved organics which may pollute receiving water bodies. In this study, the removal of colour from treated palm oil mill effluent were investigated through adsorption studies using carbon derived from wastewater sludge (WSC). Sludge from activated sludge plants were dried and processed to produce WSC. In this study, three different bed depths of WSC were used: 5 cm, 10 cm, and 15 cm. For each bed depth, the flowrate was varied at three different values: 100 mL/hr, 50 mL/hr and 25 mL/hr. It was found that at bed depth of 5 cm, the breakthrough curves were occurred at 360 min, 150 min and 15 min for flowrates of 25, 50 and 100 mL/hr respectively. It was observed that at a particular depth the exhaustion time for column reduced as flow rate increases. Kinetic models, Adams-Bohart and Yoon-Nelson were used to analyze the performance of the adsorption. It was found that rate constant for Adams Bohart model decreased with the increase in bed depth. Adsorption capacity obtained from Adams-Bohart model ranged from 2676.19 mg/L up to 8938.78 mg/L. The maximum adsorption capacity increases with smaller bed depth. For Yoon-Nelson model, the rate constant decreases with increase in bed depth. The required time for 50% breakthrough obtained from the models ranged from 17.01 to 104.17 minutes for all three bed depths. The reduction of colour was found to be effective at all bed depths. The experimental data was best described by both models as with higher values of correlation coefficient (R2).
This review is aimed to present an in-depth review of several methodologies on magnetic
water treatment (MWT) that are employed as scale treatment in water pipeline and to
critically discuss each method in order to determine the best outcome of MWT. The
magnetically assisted water in pipeline in various applications are presented, argued and
best variables are listed according to the performance of each MWT. The advantages and
limitations of MWT are discussed and the main outcome from the review summarize the
best method in MWT, especially in effectiveness of treating scale in terms of sustained
environment benefits. Magnetic field application in water treatment has the potential to
improve the water pipeline performance and lifetime. The application is also significant in
controlling the growth of scale in upcoming system. Both of these benefits lead to healthier
water treatment, increasing and maintaining the lifetime and performance of water system.