Performance of a polymerization-based electrochemically assisted persulfate process on a real coking wastewater treatment.

Industrial wastewater should be treated with caution due to its potential environmental risks. In this study, a polymerization-based cathode/Fe3+/peroxydisulfate (PDS) process was employed for the first time to treat a raw coking wastewater, which can achieve simultaneous organics abatement and recovery by converting organic contaminants into separable solid organic-polymers. The results confirm that several dominant organic contaminants in coking wastewater such as phenol, cresols, quinoline and indole can be induced to polymerize by self-coupling or cross-coupling. The total chemical oxygen demand (COD) abatement from coking wastewater is 46.8% and the separable organic-polymer formed from organic contaminants accounts for 62.8% of the abated COD. Dissolved organic carbon (DOC) abatement of 41.9% is achieved with about 89% less PDS consumption than conventional degradation-based process. Operating conditions such as PDS concentration, Fe3+ concentration and current density can affect the COD/DOC abatement and organic-polymer yield by regulating the generation of reactive radicals. ESI-MS result shows that some organic-polymers are substituted by inorganic ions such as Cl-, Br-, I-, NH4+, SCN- and CN-, suggesting that these inorganic ions may be involved in the polymerization. The specific consumption of this coking wastewater treatment is 27 kWh/kg COD and 95 kWh/kg DOC. The values are much lower than those of the degradation-based processes in treating the same coking wastewater, and also are lower than those of most processes previously reported for coking wastewater treatment.

Effects of two fillers and process conditions on the water treatment efficiency of a continuous packed bed biofilm reactor.

This study evaluated the treatment efficiency of two selected fillers and their combination for improving the water quality of aquaculture wastewater using a packed bed biofilm reactor (PBBR) under various process conditions. The fillers used were nanosheet (NS), activated carbon (AC), and a combination of both. The results indicated that the use of combined fillers and the hydraulic retention time (HRT) of 4 h significantly enhanced water quality in the PBBR. The removal rates of chemical oxygen demand, NO2-─N, total suspended solids（TSS）, and chlorophyll a were 63.55%, 74.25%, 62.75%, and 92.85%, respectively. The microbiota analysis revealed that the presence of NS increased the abundance of microbial phyla associated with nitrogen removal, such as Nitrospirae and Proteobacteria. The difference between the M1 and M2 communities was minimal. Additionally, the microbiota in different PBBR samples displayed similar preferences for carbon sources, and carbohydrates and amino acids were the most commonly utilized carbon sources by microbiota. These results indicated that the combination of NS and AC fillers in a PBBR effectively enhanced the treatment efficiency of aquaculture wastewater when operated at an HRT of 4 h. The findings provide valuable insights into optimizing the design of aquaculture wastewater treatment systems.

Efficiency of aerobic biodegradation of sugar beet distillery stillage under dissolved oxygen tension-controlled conditions.

The efficiency of aerobic biodegradation of distillery wastewater using various microbial cultures is intricately linked to process conditions. The study aimed to examine the aerobic biodegradation by a Bacillus bacteria under controlled dissolved oxygen tension (DOT) conditions as a novel approach in the treatment of sugar beet distillery stillage. The processes were conducted in a 2-L Biostat®B stirred-tank reactor (STR), at a temperature of 36°C, with aeration of 1.0 L/(L·min), and uncontrolled pH of the medium (an initial pH of 8.0). Each experiment was performed at a different DOT setpoint: 75%, 65% and 55% saturation, controlled through stirrer rotational speed adjustments. The study showed that the DOT setpoint did not influence the process efficiency, determined by the pollutant load removal expressed as COD, BOD5 and TOC. In all three experiments, the obtained reduction values of these parameters were comparable, falling within the narrow ranges of 78.6-78.7%, 97.3-98.0% and 75.0-76.4%, respectively. However, the DOT setpoint did influence the rate of process biodegradation. The removal rate of the pollutant load expressed as COD, was the lowest when DOT was set at 55% (0.48 g O2/(L•h)), and the highest when DOT was set at 65% (0.55 g O2/(L•h)). For biogenic elements (nitrogen and phosphorus), a beneficial effect was observed at a low setpoint of controlled DOT during biodegradation. The maximum extent of removal of both total nitrogen (54%) and total phosphorus (67.8%) was achieved at the lowest DOT setpoint (55%). The findings suggest that conducting the batch aerobic process biodegradation of sugar beet stillage at a relatively low DOT setpoint in the medium might achieve high efficiency pollutant load removal and potentially lead to a reduction in the process cost.

Online soft measurement method for chemical oxygen demand based on CNN-BiLSTM-Attention algorithm.

The measurement of chemical oxygen demand (COD) is very important in the process of sewage treatment. The value of COD reflects the effectiveness and trend of sewage treatment to a certain extent, but obtaining accurate data requires high cost and labor intensity. To1 solve this problem, this paper proposes an online soft measurement method for COD based on Convolutional Neural Network-Bidirectional Long Short-Term Memory Network-Attention Mechanism (CNN-BiLSTM-Attention) algorithm. Firstly, by analyzing the mechanism of the aerobic tank stage in the Anaerobic-Anoxic-Oxic (A2O) wastewater treatment process, the selection range of input variables was preliminarily determined, and the collected sample dataset was subjected to correlation analysis. Finally, pH, dissolved oxygen (DO), electrical conductivity (EC), and water temperature (T) were determined as input variables for soft measurement prediction of COD.Then, based on the feature extraction ability of CNN and the advantage that BiLSTM is able to capture the backward and forward dependencies in time series data, combined with the attention mechanism that can assign higher weights to the key data, a CNN-BiLSTM-Attention algorithm model was established to soft measure COD in the effluent from the aerobic zone of the A2O wastewater treatment process. At the same time, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) were utilized Three indicators were used to evaluate the model, and the results showed that the model can accurately predict the value of COD and has a high accuracy. At the same time, compared with models such as CNN-LSTM-Attention, CNN-BiLSTM, CNN-LSTM, LSTM, RNN, BP, SVM, XGBoost, and RF etc., the results showed that the CNN-BiLSTM Attention model performed the best, proving the superiority of the algorithm model.The Wilcoxon signed-rank test indicates significant differences between the CNN-BiLSTM-Attention model and other models.

Batch and semi-continuous treatment of cassava wastewater using microbial fuel cells and metataxonomic analysis.

The treatment of agroindustrial wastewater using microbial fuel cells (MFCs) is a technological strategy to harness its chemical energy while simultaneously purifying the water. This manuscript investigates the organic load effect as chemical oxygen demand (COD) on the production of electricity during the treatment of cassava wastewater by means of a dual-chamber microbial fuel cell in batch mode. Additionally, specific conditions were selected to evaluate the semi-continuous operational mode. The dynamics of microbial communities on the graphite anode were also investigated. The maximum power density delivered by the batch MFC (656.4 µW m - 2 ) was achieved at the highest evaluated organic load (6.8 g COD L - 1 ). Similarly, the largest COD removal efficiency (61.9%) was reached at the lowest organic load (1.17 g COD L - 1 ). Cyanide degradation percentages (50-70%) were achieved across treatments. The semi-continuous operation of the MFC for 2 months revealed that the voltage across the cell is dependent on the supply or suspension of the organic load feed. The electrode polarization resistance was observed to decreases over time, possibly due to the enrichment of the anode with electrogenic microbial communities. A metataxonomic analysis revealed a significant increase in bacteria from the phylum Firmicutes, primarily of the genus Enterococcus.

Decolorization enhancement of basic fuchsin by UV/H2O2 process: optimization and modeling using Box Behnken design.

The present work deals with the optimization of basic fuchsin dye removal from an aqueous solution using the ultraviolet UV/H2O2 process. Response Surface Modeling (RSM) based on Box-Behnken experimental design (BBD) was applied as a tool for the optimization of operating conditions such as initial dye concentration (10-50 ppm), hydrogen peroxide dosage (H2O2) (10-20 mM/L) and irradiation time (60-180 min), at pH = 7.4 under ultra-violet irradiation (254 nm and 25 W intensity). Chemical oxygen demand (COD abatement) was used as a response variable. The Box-Behnken Design can be employed to develop a mathematical model for predicting UV/H2O2 performance for COD abatement. COD abatement is sensitive to the concentration of hydrogen peroxide and irradiation time. Statistical analyses indicate a high correlation between observed and predicted values (R2 > 0.98). In the BBD predictions, the optimal conditions in the UV/H2O2 process for removing 99.3% of COD were found to be low levels of pollutant concentration (10 ppm), a high concentration of hydrogen peroxide dosage (20 mM/L), and an irradiation time of 80 min.

Anaerobic digestion of herbal waste: a waste to energy option.

Herbal waste produced during the manufacturing of herbal products is a potential feedstock for anaerobic digestion due to high amount of organic matter that can be transformed into biogas as an energy resource. Therefore, the present study was undertaken to convert herbal waste produced during the manufacturing of common of Ayurveda products into biogas through anaerobic digestion process using batch test study under controlled mesophilic temperature conditions of 35 °C with food to inoculum ratio of 0.75. The maximum biomethane potential (BMP) of 0.90 (gCH4COD/g CODfed) and sludge activity of 0.70 (gCH4-CD/gVSS) was exhibited by WS herbal waste owing to its high chemical oxygen demand (COD) of 4 g/g and better solubilization potential of the organic matter showing change in volatile suspended solids (ΔVSS) of 79%. On the other hand, the waste derived from the TA herb, exhibited the least biogas yield of 0.55 (gCH4COD/g CODfed) and sludge activity of 0.40 (gCH4-CD/gVSS), albeit with higher organic matter present. This was due to the possible hindrance of waste solubilization by the presence of lignin. The waste derived from VVL and PE showed intermediate BMP and sludge activity. The methane generation rate constant (k), a key indicator of the biodegradation potential, was also evaluated. The k values showed similar trend as of BMP values ranging from 0.081 to 0.15 d-1 thus indicating the influence of presence of lignin and the change in ΔVSS. The present study proves anaerobic digestion to be an alternative treatment method to be a milestone for management of herbal wastes and can be successfully implemented on real-scale systems.

Enhancing membrane bioreactors for dairy effluent treatment with a mixed mobile bed application.

This study examines the impact of incorporating a mobile bed into a membrane bioreactor (MBR) system on the treatment efficiency of dairy industry effluents. Initially, a conventional MBR system was operated for 60 days, followed by a modification that included a support material and ran for another 60 days under identical conditions. Performance was evaluated based on the removal efficiencies for soluble chemical oxygen demand (CODs), phenolic compounds, and oils and greases (OG), alongside measurements of solid content, dissolved oxygen, temperature, mixed liquor pH, and transmembrane pressure (TMP). The introduction of the mobile bed led to an increase in removal efficiencies for COD and phenolic compounds from 94.4 and 92.7% to 98 and 94.4%, respectively, marking statistically significant improvements (p < 0.05), while OG removal remained the same in both strategies (87.7%) (p > 0.05). Moreover, the modified system showed a more stable TMP profile, reducing the need for cleaning interventions compared to the conventional system, which experienced a notable TMP increase requiring cleaning at a 0.6 bar threshold. The findings suggest that integrating a mobile bed into MBR systems significantly enhances the treatment of dairy effluents, presenting an interesting solution for the upgrade of this type of system.

Comprehensive study on the selection and performance of the best electrode pair for electrocoagulation of textile wastewater using multi-criteria decision-making methods (TOPSIS, VIKOR and PROMETHEE II).

The accelerating environmental impact of the textile industry, especially in water management, requires efficient wastewater treatment strategies. This study examines the effectiveness of various electrode pairs in the Electrocoagulation (EC) process for treating textile wastewater, focusing on removing of Total Suspended Solids (TSS), turbidity, Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC). A comprehensive analysis was conducted using thirty-six electrode pair combinations, consisting of six materials: Aluminium (Al), Zinc (Zn), Carbon (C), Copper (Cu), Mild Steel (MS), and Stainless Steel (SS). The results demonstrated that different electrode pairs yielded varying removal efficiencies for various pollutants, with the highest efficiencies being 92.09% for COD (Al-C pair), 99.66% for TSS (Al-Cu pair), 99.17% for turbidity (Al-MS pair), and 70.99% for TOC (SS-SS pair). However, no single electrode pair excelled in removing all pollutant categories. To address this, three Multi-Criteria Decision Making (MCDM) methods such as TOPSIS, VIKOR, and PROMETHEE II were used to assess the most effective electrode pair. The results indicated that the Al-Zn combination was the most efficient, exhibiting high removal efficiencies for various pollutants (99.32% for TSS, 98.88% for turbidity, 68.62% for COD, and 57.96% for TOC). This study demonstrates that the EC process can effectively treat textile effluent and emphasizes the importance of selecting suitable electrode materials. Furthermore, pollutant removal was optimal with the Al-Zn electrode pair, offering a balanced and efficient approach to textile wastewater treatment. Thus, MCDM methods offer a robust framework for assessing and optimizing electrode selection, providing valuable insights for sustainable environmental management practices.

Remotely sensed estimates of long-term biochemical oxygen demand over Hong Kong marine waters using machine learning enhanced by imbalanced label optimisation.

In many coastal cities around the world, continuing water degradation threatens the living environment of humans and aquatic organisms. To assess and control the water pollution situation, this study estimated the Biochemical Oxygen Demand (BOD) concentration of Hong Kong's marine waters using remote sensing and an improved machine learning (ML) method. The scheme was derived from four ML algorithms (RBF, SVR, RF, XGB) and calibrated using a large amount (N > 1000) of in-situ BOD5 data. Based on labeled datasets with different preprocessing, i.e., the original BOD5, the log10(BOD5), and label distribution smoothing (LDS), three types of models were trained and evaluated. The results highlight the superior potential of the LDS-based model to improve BOD5 estimate by dealing with imbalanced training dataset. Additionally, XGB and RF outperformed RBF and SVR when the model was developed using log10(BOD5) or LDS(BOD5). Over two decades, the BOD5 concentration of Hong Kong marine waters in the autumn (Sep. to Nov.) shows a downward trend, with significant decreases in Deep Bay, Western Buffer, Victoria Harbour, Eastern Buffer, Junk Bay, Port Shelter, and the Tolo Harbour and Channel. Principal component analysis revealed that nutrient levels emerged as the predominant factor in Victoria Harbour and the interior of Deep Bay, while chlorophyll-related and physical parameters were dominant in Southern, Mirs Bay, Northwestern, and the outlet of Deep Bay. LDS provides a new perspective to improve ML-based water quality estimation by alleviating the imbalance in the labeled dataset. Overall, the remotely sensed BOD5 can offer insight into the spatial-temporal distribution of organic matter in Hong Kong coastal waters and valuable guidance for the pollution control.

The performance of quaternary-ammonium chitosan in wastewater treatment: The overlooked role of solubility.

Quaternary-ammonium chitosan (CT-CTA) is a popular water treatment agent, and its electropositivity and cation strength are improved compared with chitosan. The use of CT-CTA is widely advocated to remove suspended particles and organic matter from wastewater. However, the solubility of CT-CTA is an important factor affecting the performance of CT-CTA, which is a neglected problem in previous studies. In the study, CT-CTA with different solubilities were prepared by adjusting pH from 2 to 7 in preparation, and their applications were explored in wastewater. When the pH was 2, 2.5, or 3, the obtained CT-CTA was a dissolved state. The turbidity and color removal were 95 % - 98 % and 60 % - 74 %, respectively. When the pH was 4, 5, 6, or 7, the obtained CT-CTA was a solid state. The turbidity and color removal were 30 % - 63 % and 90 % - 97 %, respectively. For domestic-wastewater treatment, CT-CTA in a dissolved state removed 92 % of turbidity and 50 % of chemical oxygen demand (COD). CT-CTA in a solid state removed 86 % of turbidity and 64 % of COD with poly aluminum chloride (PAC). The results illustrated the performance of CT-CTA with different solubilities, which can broaden its application in wastewater treatment.

Prediction of COD in industrial wastewater treatment plant using an artificial neural network.

In this investigation, the modeling of the Aksaray industrial wastewater treatment plant was performed using artificial neural networks with various architectures in the MATLAB software. The dataset utilized in this study was collected from the Aksaray wastewater treatment plant over a 9-month period through daily records. The treatment efficiency of the plants was assessed based on the output values of chemical oxygen demand (COD) output. Principal component analysis (PCA) was applied to furnish input for the Feedforward Backpropagation Artificial Neural Networks (FFBANN). The model's performance was evaluated using the Mean Squared Error (MSE), the Mean Absolute Error (MAE) and correlation coefficient (R2) parameters. The optimal architecture for the neural network model was determined through several trial and error iterations. According to the modeling results, the ANN exhibited a high predictive capability for plant performance, with an R2 reaching up to 0.9997 when comparing the observed and predicted output variables.

Spatio-temporal variation in water quality due to the anthropogenic impact in Rudrasagar Lake, a Ramsar site in India.

Rudrasagar Lake, a vital habitat for diverse flora and fauna, supports over 2000 households to sustain their daily livelihoods. The current study attempts to examine the impact of human activities on spatio-temporal variation in the water quality of the study area. The study integrates extensive field surveys, sample processing, and statistical analysis to assess the recent status of wetland health. Latin Square Matrix (LSM) was employed to select the sampling sites while the Inverse Distance Weighting (IDW) interpolation technique was used for spatial variation mapping. Modified Weighted Arithmetic Water Quality Index (MWAWQI) and Comprehensive Pollution Index (CPI) were utilized for assessing seasonal variation water quality and pollution loads, respectively. The results showed that dissolved oxygen (DO) was strongly influenced by the tributaries, and recreational activities have substantially influenced the highest concentrations of biochemical oxygen demand (BOD), and total suspended solids (TSS). The central portion of the lake is particularly susceptible to pollution from extensive fishing and recreational activities while peripheral sites are strongly influenced by agricultural run-offs, seepages from brick industries, and municipal wastes characterized by high concentrations of pH, total hardness (TH), oxidation-reduction potential (ORP). The findings reveal remarkable spatio-temporal fluctuations and highlight the areas within the lake susceptible to anthropogenic activities. The study proposed a sustainable management model to ameliorate anthropogenic threats. Moreover, the study contributes to the scientific understanding of the challenges and ensures the long-term viability of wetland health as a vital ecological and socio-economic resource.

Performance evaluation of a new sponge-based moving bed biofilm reactor for the removal of pharmaceutical pollutants from real wastewater.

Pharmaceutical pollutants, a group of emerging contaminants, have attracted outstanding attention in recent years, and their removal from aquatic environments has been addressed. In the current study, a new sponge-based moving bed biofilm reactor (MBBR) was developed to remove chemical oxygen demand (COD) and the pharmaceutical compound Ibuprofen (IBU). A 30-L pilot scale MBBR was constructed, which was continuously fed from the effluent of the first clarifier of the Southern Tehran wastewater treatment plant. The controlled operational parameters were pH in the natural range, Dissolved Oxygen of 1.5-2 mg/L, average suspended mixed liquor suspended solids (MLSS), and mixed liquor volatile suspended solids (MLVSS) of 1.68 ± 0.1 g/L and 1.48 ± 0.1 g/L, respectively. The effect of hydraulic retention time (HRT) (5 h, 10 h, 15 h), filling ratio (10%, 20%, 30%), and initial IBU concentration (2 mg/L, 5 mg/L, 10 mg/L) on removal efficiencies was assessed. The findings of this study revealed a COD removal efficiency ranging from 48.9 to 96.7%, with the best removal efficiency observed at an HRT of 10 h, a filling ratio of 20%, and an initial IBU concentration of 2 mg/L. Simultaneously, the IBU removal rate ranged from 25 to 92.7%, with the highest removal efficiency observed under the same HRT and filling ratio, albeit with an initial IBU concentration of 5 mg/L. An extension of HRT from 5 to 10 h significantly improved both COD and IBU removal. However, further extension from 10 to 15 h slightly enhanced the removal efficiency of COD and IBU, and even in some cases, removal efficiency decreased. Based on the obtained results, 20% of the filling ratio was chosen as the optimum state. Increasing the initial concentration of IBU from 2 to 5 mg/L generally improved COD and IBU removal, whereas an increase from 5 to 10 mg/L caused a decline in COD and IBU removal. This study also optimized the reactor's efficiency for COD and IBU removal by using response surface methodology (RSM) with independent variables of HRT, filling ratio, and initial IBU concentration. In this regard, the quadratic model was found to be significant. Utilizing the central composite design (CCD), the optimal operating parameters at an HRT of 10 h, a filling ratio of 21%, and an initial IBU concentration of 3 mg/L were pinpointed, achieving the highest COD and IBU removal efficiencies. The present study demonstrated that sponge-based MBBR stands out as a promising technology for COD and IBU removal.

Electroactive Brevundimonas diminuta consortium mediated selenite bioreduction, biogenesis of selenium nanoparticles and bio-electricity generation.

In this study, highly selenite-resistant strains belonging to Brevundimonas diminuta (OK287021, OK287022) genus were isolated from previously operated single chamber microbial fuel cell (SCMFC). The central composite design showed that the B. diminuta consortium could reduce selenite. Under optimum conditions, 15.38 Log CFU mL-1 microbial growth, 99.08% Se(IV) reduction, and 89.94% chemical oxygen demand (COD) removal were observed. Moreover, the UV-visible spectroscopy (UV) and Fourier transform infrared spectroscopy (FTIR) analyses confirmed the synthesis of elemental selenium nanoparticles (SeNPs). In addition, transmission electron microscopy (TEM) and scanning electron microscope (SEM) revealed the formation of SeNPs nano-spheres. Besides, the bioelectrochemical performance of B. diminuta in the SCMFC illustrated that the maximum power density was higher in the case of selenite SCMFCs than those of the sterile control SCMFCs. Additionally, the bioelectrochemical impedance spectroscopy and cyclic voltammetry characterization illustrated the production of definite extracellular redox mediators that might be involved in the electron transfer progression during the reduction of selenite. In conclusion, B. diminuta whose electrochemical activity has never previously been reported could be a suitable and robust biocatalyst for selenite bioreduction along with wastewater treatment, bioelectricity generation, and economical synthesis of SeNPs in MFCs.

Tannery effluent treatments with mangrove fungi, grass root biomass, and biochar.

Tannery effluents contain high amounts of polluting chemicals, such as salts and heavy metals released often to surface waters. New economic and eco-friendly purification methods are needed. Two adsorbing materials and five salt-tolerant fungal isolates from mangrove habitat were studied. Purification experiments were carried out using the pollutant adsorbents biochar and the biomass of vetiver grass (Chrysopogon zizanioides) roots and the fungi Cladosporium cladosporioides, Phomopsis glabrae, Aspergillus niger, Emericellopsis sp., and Scopulariopsis sp., which were isolated from mangrove sediment. They efficacy to reduce pollutants was studied in different combinations. Salinity, turbidity, total dissolved solids, total suspended solids, phenols, nitrogen, ammonia. Biological and chemical oxygen demand (BOD, COD) and several heavy metals were measured. The adsorbents were efficient reducing the pollutants to 15-50% of the original. The efficiency of the combination of biochar and roots was generally at the same level as the adsorbents alone. Some pollutants such as turbidity, COD and ammonium were reduced slightly more by the combination than the adsorbents alone. From all 14 treatments, Emericellopsis sp. with biochar and roots appeared to be the most efficient reducing pollutants to < 10-30%. BOD and COD were reduced to ca 5% of the original. The treatment was efficient in reducing also heavy metals (As, Cd, Cr, Mn Pb, Zn). The fungal species originating from the environment instead of the strains present in the tannery effluent reduced pollutants remarkably and the adsorbents improved the reduction efficiency. However, the method needs development for effluents with high pollutant concentrations to fulfil the environmental regulations.

Long-term evaluating the strengthening effects of iron-carbon mediator for coking wastewater treatment in EGSB reactor.

Coking wastewater (CWW) treatment is difficult due to its complex composition and high biological toxicity. Iron-carbon mediators was used to enhance the treatment of CWW through iron-carbon microelectrolysis (ICME). The results indicated that the removal rate of COD and phenolic compounds were enhanced by 24.1 % and 23.5 %, while biogas production and methane content were promoted by 50 % and 7 %. Microbial community analysis indicated that iron-carbon mediators had a transformative impact on the reactor's performance and dependability by enriching microorganisms involved in direct and indirect electron transfer, such as Anaerolineae and Methanothrix. The mediator also produced noteworthy gains in LB-EPS and TB-EPS, increasing by roughly 109.3 % and 211.6 %, respectively. PICRISt analysis demonstrated that iron-carbon mediators effectively augment the abundance of functional genes associated with metabolism, Citrate cycle, and EET pathway. This study provides a new approach for CWW treatment.

Treatment of pharmaceutical industry wastewater for water reuse in Jordan using hybrid constructed wetlands.

Developing cost-efficient wastewater treatment technologies for safe reuse is essential, especially in developing countries simultaneously facing water scarcity. This study developed and evaluated a hybrid constructed wetlands (CWs) approach, incorporating tidal flow (TF) operation and utilising local Jordanian zeolite as a wetland substrate for real pharmaceutical industry wastewater treatment. Over 273 days of continuous monitoring, the results revealed that the first-stage TFCWs filled with either raw or modified zeolite performed significantly higher reductions in Chemical Oxygen Demand (COD, 58 %-60 %), Total Nitrogen (TN, 32 %-37 %), and Phosphate (PO4, 46 %-64 %) compared to TFCWs filled with normal sand. Water quality further improved after the second stage of horizontal subsurface flow CWs treatment, achieving log removals of 1.09-2.47 for total coliform and 1.89-2.09 for E. coli. With influent pharmaceutical concentrations ranging from 275 to 2000 µg/L, the zeolite-filled hybrid CWs achieved complete removal (>98 %) for ciprofloxacin, ofloxacin, erythromycin, and enrofloxacin, moderate removal (43 %-81 %) for flumequine and lincomycin, and limited removal (<8 %) for carbamazepine and diclofenac. The overall accumulation of pharmaceuticals in plant tissue and substrate adsorption accounted for only 2.3 % and 4.3 %, respectively, of the total mass removal. Biodegradation of these pharmaceuticals (up to 61 %) through microbial-mediated processes or within plant tissues was identified as the key removal pathway. For both conventional pollutants and pharmaceuticals, modified zeolite wetland media could only slightly enhance treatment without a significant difference between the two treatment groups. The final effluent from all hybrid CWs complied with Jordanian treated industry wastewater reuse standards (category III), and systems filled with raw or modified zeolite achieved over 95 % of samples meeting the highest water reuse category I. This study provides evidence of using hybrid CWs technology as a nature-based solution to address water safety and scarcity challenges.

Phytoremediation performance of mixed planting patterns and the associated rhizosphere microbial community in pilot-scale constructed wetlands.

Phytoremediation is a low-cost, environmentally friendly, and sustainable technology that can utilize vegetation and microorganisms to avoid eutrophication and purifying water environment. The ability of five different living aquatic plants of nitrogen (N), phosphorus (P), and chemical oxygen demand (CODcr) removal were investigated in pilot scale constructed wetlands (CWs). Aquatic plant mixes significantly improved CODcr removal and plant tissue uptake of nitrogen and phosphorus. The wetland performance of mixed plantings was also influenced by the specific species. The mixed planting of Phragmites australi, Nymphaea Colorado and Myriophyllum verticillatum (PNM)When assessing pollutant removal in CWs, PNM performed better within mixtures, a possible synergistic effect, while TNV Typha orientalis, Nymphaea Colorado, and Vallisneria natans (TNV) performed poorly, a possible antagonist effect. The nutrient uptake within plant tissues byunder mixed plants planting was always ahad synergistic effect. Mixed plantingAquatic plant mixes significantly increased the rhizosphere microbial diversity and promoted the growth of functional denitrifying flora.

A novel integrated approach employing Desertifilum tharense BERC-3 for efficient wastewater valorization and recycling for developing peri-urban algae farming system.

Peri-urban environments are significant reservoirs of wastewater, and releasing this untreated wastewater from these resources poses severe environmental and ecological threats. Wastewater mitigation through sustainable approaches is an emerging area of interest. Algae offers a promising strategy for carbon-neutral valorization and recycling of urban wastewater. Aiming to provide a proof-of-concept for complete valorization and recycling of urban wastewater in a peri-urban environment in a closed loop system, a newly isolated biocrust-forming cyanobacterium Desertifilum tharense BERC-3 was evaluated. Here, the highest growth and lipids productivity were achieved in urban wastewater compared to BG11 and synthetic wastewater. D. tharense BERC-3 showed 60-95% resource recovery efficiency and decreased total dissolved solids, chemical oxygen demand, biological oxygen demand, nitrate nitrogen, ammonia nitrogen and total phosphorus contents of the water by 60.37%, 81.11%, 82.75%, 87.91%, 85.13%, 85.41%, 95.87%, respectively, making it fit for agriculture as per WHO's safety limits. Soil supplementation with 2% wastewater-cultivated algae as a soil amender, along with its irrigation with post-treated wastewater, improved the nitrogen content and microbial activity of the soil by 0.3-2.0-fold and 0.5-fold, respectively. Besides, the availability of phosphorus was also improved by 1.66-fold. The complete bioprocessing pipeline offered a complete biomass utilization. This study demonstrated the first proof-of-concept of integrating resource recovery and resource recycling using cyanobacteria to develop a peri-urban algae farming system. This can lead to establishing wastewater-driven algae cultivation systems as novel enterprises for rural migrants moving to urban areas.