Water treatment is necessary to ensure the availability of clean and safe water for various uses. Integrating Internet of Things (IoT) technology with water purification systems has shown enormous potential in recent years for enhancing the efficiency and efficacy of the treatment process. Monitoring the disposal of sewage in treatment facilities is the primary obstacle. As a result, a Supervisory Control And Data Acquisition (SCADA) system, including the IoT, has been proposed to ensure the proper operation of these sewer systems and limit the risk of overflow and malfunction. In this paper, we suggest a novel approach that blends Deep Belief Networks (DBNs) with an IoT-based water treatment system equipped with a SCADA system for increased monitoring and control. An IoT–SCADA system can be implemented at various wastewater collection and treatment phases. Secondly, incorporating DBNs enhances the system's predictive capabilities, enabling proactive maintenance and decision-making to prevent potential failures and optimize resource allocation. The proposed technique computes the efficacy of the effluent treatment facility and ensures that chemical emissions do not exceed permissible limits. Furthermore, Complex Event Processing (CEP) can be utilized to evaluate and analyze the massive influx of real-time data sets provided by IoT sensors.
In this work, Phragmites australis and Vallisneria natans were selected as the research objects and were cultured for 10 d under 0.10 μg L−1 sulfadiazine (SD) stress in a simulated surface flow wetland reactor. SD degradation was conducted at pH = 7 and 25 °C for 96 h. Each plant group conformed to the first-order kinetic model of degradation, and the degradation rate increased with time, reaching the maximum at 96 h. At 96 h, the degradation rate of P. australis communities was higher than that of V. natans. SD metabolites showed that the degradation pathways in the plant rhizosphere were mainly hydroxylation, aminolation, and S–N bond cleavage. In the analysis of rhizosphere bacterial community structure, the bacterial phyla that could degrade antibiotics accounted for a large proportion. Compared with before degradation, the dominant phylum and genus did not change after degradation (96 h), but their abundance changed to varying degrees, and new genera appeared in the P. australis group. This research provides a reference for the degradation of antibiotics in karst areas and new information on the mechanism of SA degradation in the plant rhizosphere.
One way to improve the infrastructure, operations, monitoring, maintenance, and management of wastewater treatment systems is to use machine learning modelling to make smart forecasting, tracking, and failure prediction systems. This method aims to use industry data to treat the wastewater treatment model. Gradient-Boosted Decision Tree (GBDT) algorithms were used gradually to predict wastewater plant parameters. In addition, we used the Slime Mould Algorithm (SMA) for feature extraction and other acceptable tuning procedures. The input and effluent Chemical Oxygen Demand (COD) prediction for effluent treatment systems applies to the GBDT approaches employed in this study. GBDT-SMA employs artificial intelligence to provide precise method modelling for complex systems. Several training and model testing techniques were used to determine the best topology for the neural network models and decision trees. The GBDT-SMA model performed best across all methods. With 500 data, GBDT-SMA achieved an accuracy of 96.32%, outperforming other models like Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Deep Convolutional Neural Network (DCNN), and K-neighbours RF, which reached an accuracy of 82.97, 87.45, 85.98, and 91.45%, respectively.
Recycling treated greywater (GW) for onsite, non-potable applications can reduce the potable water demand typically used for non-potable purposes. The conventional methods for GW treatment are limited in their ability to remove wide-ranging pollutants that are inexpensive and use low energy. For this reason, effective and low-cost onsite treatment options are in demand. This study examines the effectiveness of sand filtration (SF), granulated blast furnace slag (GBFS), and activated carbon (AC) in the treatment of GW from a residential apartment building in Sharjah, United Arab Emirates. The study relies on four different pilot-scale experimental setups to investigate the effectiveness of SF, AC, and GBFS in treating microorganisms from GW and evaluate the microbial risk reduction using these treatment processes. A quantitative microbial risk assessment (QMRA) approach is used for risk assessment. Results show that GBFS achieves a higher reduction of total coliform (TC) (0.54-2.05 log removal) and fecal coliform (FC) (1.96-2.30 log removal) than AC. SF improves reduction by 0.13-3.39 log removal and 1.11-3.68 log removal for TC and FC, respectively. The study also reveals substantial FC and Escherichia coli risk reduction by SF, AC and GBFS.
Water scarcity is a worldwide problem, which leads to unprecedented pressure on water supply in arid and semi-arid regions. Treating wastewater is an alternative water resource, therefore, its reuse for agricultural irrigation has been growing worldwide since the beginning of the 21st century. In several regions of wine-producing countries (e.g., Australia, California - USA, Spain), wastewater reuse appears to be the most accessible alternative, both financially and technically, for agricultural uses that notably do not require drinking water. From the summer of 2022, vine irrigation full-scale implementation will start with tertiary treated municipal wastewater in the French Languedoc region. This was made possible thanks to a collaborative research project conducted between 2013 and 2018 to address all potential health and environmental risks associated with this process. This research project was conducted in the south of France, with experimental and control plots both equipped with drip irrigation systems. All the results produced during the research project demonstrated the feasibility of applying this process for vine drip irrigation while effectively managing health and environmental risks and complying with the regulation (treated water microbiological quality). A social acceptance and economic study were also performed in order to broaden the scope of the project scalability evaluation.
The Bouzareah in northern Algeria's province and Ghardaia in southern Algeria's province are particularly vulnerable to drought and water scarcity, even if apparent differences in climatic conditions mark each region. Though it may seem counterintuitive, Ghardaia has considerable water resources that could be tapped for agriculture. Our study aimed to design a prototype of a desalination unit coupled with a solar collector for these two provinces using the TRNSYS 16. The desalination unit is composed of vacuum membrane distillation (VMD) coupled with a solar collector, and the photovoltaic has been designed according to the climatic conditions of each region. In this work, the approach adopted is to integrate a model developed in the literature into a simulation environment (TRNSYS) coupled with the CODE-BLOCKS compiler and FORTRAN programming language to create a new component (i.e., VMD process). The permeation flux and the power to load reached their maximum values with the charge of solar irradiation 48 kg/h m2 and 6,300 kJ/h, respectively, for Ghardaia at the sun irradiation value 800 W/m2 and temperature of 34 degrees C. Results showed that Ghardaia had a higher GOR value than Bouzareah over the year (10.947 vs. 8.3389).
The reaction of p-carboxy phenyl amino maleimide (CHM) with cellulose acetate (CA), led to the formation of a modified cellulose acetate polymer (MCA), which was characterized by UV/Vis, 1H NMR, and 13C NMR. The active sites of the reaction were the –NH group of (CHM) and the OAc of CA. CA was grafted with (CHM) to build branches on its main chains, using benzoyl peroxide as an initiator. The results of 1H NMR and 13C NMR revealed the presence of (CHM) moieties inside the polymeric matrix. The (CA-g-CHM) ZrO2 was fabricated into a membrane, using a phase inversion technique. The effect of ZrO2 content on the water flux was discussed. The SEM/EDS was also used to characterize the membrane contents and morphology. The morphology of the membrane showed the grafted parts and the EDS confirmed the presence of nitrogen atoms in the polymeric matrix. The thermogravimetry (TGA) results showed that the membrane exhibited high thermal stability which would adjust the membrane for the desalination process. The desalination test indicated the removal of NaCl salt by the membrane, as shown by the EDS and 1H NMR spectroscopy results. The membrane exhibited good antibacterial and antifungal properties.
China is the largest steel producer in the world. Effective methods to alleviate the contradiction between water supply and water demand of the iron and steel industry in China are to implement the recycling of wastewater from the iron and steel industry and develop unconventional water resources. This paper reviews the development of wastewater recycling in the iron and steel industry in China in the past 40 years (1980–2020). During this period, steel output has increased from 36 to 1,053 million tons, freshwater consumption per ton of steel has decreased from 35.9 to 2.45 tons, and water resources reuse has soared from 61.2 to 98.02%. Four typical cases, including the Anyang Steel Group, the Tangshan Steel Group, the Tianjin Steel Group, and the Taihang Steel Group, were analyzed. In addition, a water efficiency research project of iron and steel enterprises in China was carried out in 2019. Statistical analyses on wastewater recycling rate, reuse rate, direct cooling water circulation rate, and other indicators were performed. The recycling of wastewater in the iron and steel industry would be continuously improved by policy drivers, economic drivers, and technical drivers.
Zinc is one of the heavy metals present in textile wastewater with high concentrations. However, the chronic toxic effects of zinc on aquatic vertebrates are still ambiguous. Zinc accumulation in zebrafish after chronic zinc exposure and toxic effects on the intestines, muscles, and gills were investigated in this study. The results showed that a significant accumulation of zinc in the intestine, muscle, and gill was observed after 25 d of zinc exposure. The toxic effects of zinc were mainly in the form of zinc-induced oxidative stress in zebrafish, potential neurotoxicity, and changes in intestinal microbes. Significant changes in the levels of superoxide dismutase, catalase, metallothionein, glutathione, and malondialdehyde indicated that zinc damaged the antioxidant system of adult zebrafish. Zinc exposure resulted in a significant decrease in acetylcholinesterase activity and abnormal neural signaling. Furthermore, zinc exposure resulted in increased intestinal microbial richness and decreased the Simpson index in adult zebrafish. At the phylum and genus levels, the predominant microbes in the intestine are altered by zinc. In summary, this study provides an analysis of the toxic effects of chronic zinc exposure on adult zebrafish and the potential mechanisms, which are important for assessing the dual effects of zinc on aquatic organisms.
Reverse osmosis desalination facilities operating on microgrids (MGs) powered by renewable energy are becoming more significant. A leader-follower structured optimization method underlies the suggested algorithm. The desalination plant is divided into components, each of which can be operated separately as needed. MGs are becoming an important part of smart grids, which incorporate distributed renewable energy sources (RESs), energy storage devices, and load control strategies. This research proposes novel techniques in economic saline water treatment based on MG architecture integrated with a renewable energy systems. This study offers an optimization framework to simultaneously optimize saline as well as freshwater water sources, decentralized renewable and conventional energy sources to operate water-energy systems economically and efficiently. The radial Boltzmann basis machine is used to analyse the salinity of water. Data on water salinity were used to conduct the experimental analysis, which was evaluated for accuracy, precision, recall, and specificity as well as computational cost and kappa coefficient. The proposed method achieved 88% accuracy, 65% precision, 59% recall, 65% specificity, 59% computational cost, and 51% kappa coefficient.
The use of biochar as an additive material in various compositions to the anaerobic digestion of the tannery wastewater was investigated. Pyrolytic biochar made from Khat waste with different compositions was added to anaerobic batch digesters in laboratory-scale biogas experiments. Biogas digesters with volume of 500 ml were used to explore the effects of biochar on anaerobic digestion in the ratios of 5, 10, 15, and 20% (w/w) at constant mesophilic temperature (38 degrees C). The results show that for five experimental tests in digesters (D0, D1, D2, D3, and D4), which contains 0, 5, 10, 15, and 20% of biochar, the cumulative methane and volume of biogas yields were, respectively, 17.04, 41.2, 43.8, 51.6, 48.6% and 150, 520, 680, 760, 690. Comparing the cumulative methane production efficiency of the digester containing zero biochar (D0) with the addition of 5, 10, 15, and 20% biochar had more favorable effects and increased by 58.6, 61.1, 66.98, and 64.94%, respectively. From these results, adding 15% of biochar to anaerobic digestion causes a three-fold increase in methane compared to the control and more positive effects than all other biochar e compositions. According to this result, the right dose of biochar must be added to maximize biogas production.
In the current scenario of the need for cost-effective remediation, our study aimed to assess the remedial potential of bacteria obtained from metal-rich wastewater. To simulate the conditions, we prepared wastewater containing five toxic metals (Cu, Cr, Ni, Fe, and Pb). Two types of metal-resistant bacteria were isolated from a prominent wastewater drain in Lahore, Pakistan. These isolated bacteria were thoroughly characterized, both phenotypically and genotypically. Subsequently, the isolated bacteria were exposed to the wastewater solution containing each of the aforementioned metals at a concentration of 250 ppm. The exposed isolates were then incubated for a duration of 15 days. After 5 days, we measured the uptake of metals by the bacterial isolates. Following the 15-day incubation period, we observed that the bacterial isolates demonstrated the maximum efficiency in removing metals, with approximately 47.5% of Fe, 77% of Ni, 75.75% of Cu, 64% of Cr, and 82.5% of Pb being removed. These findings have significant implications for the development of environmentally friendly and cost-effective strategies for metal ion remediation.
Adsorption is vital for the elimination of Cr6+ and Pb2+ ions in the contaminated solution medium. A ternary blend made up of chitosan, nylon 6 and polyurethane foam (CS/Ny 6/PUF) blend in the ratio of 2:1:1 has been investigated. These blends are used as an adsorbent due to the insoluble nature in acidic and basic medium. The adsorption efficacy was analyzed by modifying pH, contact time, and adsorbent dosage. The maximum uptake of metal ions has been exhibited in the pH range 5. An equilibrium adsorption statistic indicated that adsorption isotherm follows the Freundlich model. The adsorption kinetic parameters specified that the adsorption of chromium has shown pseudo-second-order and lead pseudo-first-order reaction.
In membrane filtration technology, membrane fouling is the primary obstacle to optimizing efficiency and results in a short membrane lifetime and high operating costs. By incorporating nanomaterials into the membrane synthesis process, a mixed-matrix membrane with significantly enhanced characteristics and performance may be obtained. Graphene oxide (GO), aluminum oxide (Al2O3), tin oxide (SnO2), and titanium oxide (TiO2) were incorporated into a polyethersulfone (PESU) membrane. The water permeability of the modified membranes showed improvements when compared with the pure membrane. It increased from 65 L/m2 h bar for the pristine membrane (PES-1) to 143.6, 83.68, 92.12, 75.43 L/m2 h bar for Al2O3 (PES-2), TiO2 (PES-3), SnO2 (PES-4), and GO (PES-5) membranes, respectively. It was discovered that the membrane's surface hydrophilicity was significantly and directly affected by the incorporation of nanoparticles. Fouling parameters include Rr (Reversible fouling ratio), Rir (irreversible fouling ratio), Rt (total fouling ratio), and Frr (flux recovery ratio) and were measured to determine the membrane's fouling tendency. The results showed that the membrane's propensity for fouling could be reduced when nanoparticles were incorporated into it. The experimental results are best explained by the cake layer and both standard and intermediate blocking mechanism models, as determined by the traditional single fouling models.
Around the world, it is growing harder to provide clean and safe drinking water. In wastewater treatment, sensors are employed, and the Internet of Things (IoT) is used to transmit data. Chemical oxygen demand (COD), biochemical demand (BOD), total nitrogen (T-N), total suspended solids (TSS), and phosphorous (T-P) components all contribute to eutrophication, which must be avoided. The wastewater sector has lately made efforts to become carbon neutral; however, the environmental impact and the road to carbon neutrality have received very little attention. The challenges are caused by poor prediction. This research proposes deep learning modified neural networks (DLMNN) with Binary Spotted Hyena Optimizer (BSHO) for modeling and calculations to address this challenge. All efforts for resource recovery, water reuse, and energy recovery partially attain this objective. In contrast to previous modeling techniques, the DLMNN-training BSHOs and validation demonstrated outstanding accuracy shown by the model's high coefficient (R2) for both training and testing. Also covered are recent developments and problems with nanomaterials made from sustainable carbon and graphene quantum dots, as well as their uses in the treatment and purification of wastewater. The proposed model DLMNN-BSHO achieved 95.936% precision, 95.326% recall, 93.747% F-score, and 99.637% accuracy.
The growing population and increasing water demand necessitate exploring alternative sources of water, including saline water. Saline water treatment technologies have undergone significant advancements in recent years, enabling the production of potable water from seawater and brackish water. This review provides an overview of the current state of saline water treatment technologies, including desalination and membrane-based processes. The advantages and limitations of each technology and their suitability for different applications are discussed. Recent advancements in materials and techniques that have led to improvements in energy efficiency, productivity, and cost-effectiveness of these technologies are highlighted. Finally, the future directions and challenges in the field of saline water treatment are outlined.
Closed circuit reverse osmosis (CCRO) and forward osmosis-RO (FO-RO) were evaluated at a pilot scale to generate additional permeate from RO concentrate - achieving a recovery of 61% for CCRO and 35% for FO-RO - at a full-scale advanced water purification facility. This study assessed permeate water quality, suitability of the permeate for treatment by an ultraviolet-advanced oxidation process (UV-AOP), and cost/ footprint for a conceptual 10- or 20-mgd system. Both technologies demonstrated inorganic, organic, and microbiological constituent removal suitable for blending with primary RO permeate. Virus challenge testing with MS coliphage demonstrated greater than 5-log removal by both technologies. Pilot-scale UV/hydrogen peroxide AOP treatment of CCRO or FO-RO permeate yielded similar performance (similar to 1.4-log N-nitrosodimethylamine removal and similar to 0.5-log 1,4-dioxane removal) as the full-scale UV-AOP that treats the RO permeate from the purification facility. The estimated full-scale total unit cost (capital plus operation and maintenance costs) of product water produced by the two technologies was estimated to range from $0.91 to $1.12 per cubic meter, depending on the design flow rate of RO concentrate treated, and is estimated to be similar between the two technologies given the +50%/-30% expected accuracy of the Class 5 cost estimate.
Antibiotics are a large group of emerging organic pollutants with low concentration levels in the water. The presence of antibiotics will affect the ecological environment and human health. The removal of trace organic compounds by graphene oxide (GO) membranes has attracted extensive attention. This study investigated the removal of three differently charged antibiotics by GO membranes and the influence of water quality on the removal of antibiotics. It showed that a crosslinked ethylenediamine-GO (EDA-GO) membrane had better stability and higher antibiotic removal performance than a non-crosslinked GO membrane. Among the three antibiotics, penicillin (PNC) was negatively charged and had the highest removal efficiency due to steric effect and electrostatic repulsion. A low concentration (10 mmol L−1) of Na+ in water could increase the membrane flux but had no significant effect on the removal of antibiotics. Ca2+ could reduce the membrane flux and improve the removal of chloramphenicol (CAP) and PNC. The removal efficiencies of low-concentration antibiotics (500 μg L−1) were higher than those of high-concentration antibiotics (10 mg L−1). Furthermore, the removal of antibiotics under the condition of actual wastewater quality was higher than those in solutions prepared with ultrapure water. The EDA-GO membrane has great potential in the removal of antibiotics in wastewater.
Capacitive deionization (CDI) is an emerging technology which is being developed as a promising desalination alternative for charged species from salt water, being electrode materials as key drivers for highly efficient process. Here, we describe synthesis of highly porous activated carbons from chicken feathers using pyrolysis followed by chemical activation with potassium hydroxide in a 1:4 ratio to produce sustainable, scalable, and sustainable carbon electrodes for CDI. Poly (vinyl alcohol) (PVA) was used as binder to modify chicken feather activated carbons (CF-AC), which were subsequently crosslinked with glutaraldehyde (GA) to produce CF-AC-PVA-GA polymers through acetylation reaction. This resulted from improving hydrophilicity of CF-AC-PVA-GA polymers to raise the electrodes' resistance. Prepared materials were characterized using scanning electron microscopy, Fourier transform infrared, X-ray diffraction, Brunauer-Emmett-Teller and cyclic voltammetry. Fabricated CDI electrodes were used to investigate their performance for desalination, and exhibited different electrosorption capacity at different applied potentials. Modified electrodes possessed good stability in shear conditions and CDI process was stable and reproducible around 16 electrosorption cycles. Salt removal capacity of the modified electrodes (CF-AC-PVA-GA) was found to be 3.89 mg g−1. The obtained outcomes offer important considerations of ions electrosorption and help advancing CDI system for water treatment and desalination.
A multi-stage anoxic/oxic (A/O) moving-bed biofilm reactor (MBBR) system with multiple chambers was established for municipal wastewater treatment. The active biomass quantity, bioactivity, and biomass yield of a pilot-scale multi-stage MBBR were investigated in this study. The microbial activity and heterotrophic yield coefficients (YH) were measured using respirometric techniques in each chamber at different temperature conditions. Meanwhile, the growth, nitrification, and denitrification rates of functional biomass were also quantified as specific respiration rates (SOURs). The total active biomass in the multi-stage A/O-MBBR system was 0.71-1.68 g COD/m(2) for the aerobic reactor and 0.39-1.44 g COD/m2 for the anoxic reactor at 10-19 degrees C. The YH values for the anoxic reactors were 0.61-0.69, which were comparable to the recommended value of the activated sludge model (ASM1). The correlation coefficient between Nitrospira and the autotrophic specific respiration rate (SOURA) was 0.82. Meanwhile, denitrifying genera showed a significant correlation with the heterotrophic specific respiration rate (SOURH) and the active heterotrophic biomass (XH). This study provided insights into biomass distribution and the corresponding kinetic parameters for the multi-stage MBBR systems, which may serve as a reference for process design and troubleshooting.
