Effluent Quality In Terms Research Articles

Design of a Soft Sensor Based on Long Short-Term Memory Artificial Neural Network (LSTM) for Wastewater Treatment Plants.

Assessment of wastewater effluent quality in terms of physicochemical and microbial parameters is a difficult task; therefore, an online method which combines the variables and represents a final value as the quality index could be used as a useful management tool for decision makers. However, conventional measurement methods often have limitations, such as time-consuming processes and high associated costs, which hinder efficient and practical monitoring. Therefore, this study presents an approach that underscores the importance of using both short- and long-term memory networks (LSTM) to enhance monitoring capabilities within wastewater treatment plants (WWTPs). The use of LSTM networks for soft sensor design is presented as a promising solution for accurate variable estimation to quantify effluent quality using the total chemical oxygen demand (TCOD) quality index. For the realization of this work, we first generated a dataset that describes the behavior of the activated sludge system in discrete time. Then, we developed a deep LSTM network structure as a basis for formulating the LSTM-based soft sensor model. The results demonstrate that this structure produces high-precision predictions for the concentrations of soluble X1 and solid X2 substrates in the wastewater treatment system. After hyperparameter optimization, the predictive capacity of the proposed model is optimized, with average values of performance metrics, mean square error (MSE), coefficient of determination (R2), and mean absolute percentage error (MAPE), of 23.38, 0.97, and 1.31 for X1, and 9.74, 0.93, and 1.89 for X2, respectively. According to the results, the proposed LSTM-based soft sensor can be a valuable tool for determining effluent quality index in wastewater treatment systems.

Microalgae and co-culture for polishing pollutants of anaerobically treated agro-processing industry wastewater: the case of slaughterhouse

Anaerobically treated slaughterhouse effluent is rich in nutrients, organic matter, and cause eutrophication if discharged to the environment without proper further treatment. Moreover, phosphorus and nitrogen in agro-processing industry wastewaters are mainly removed in the tertiary treatment phase. The objective of this study is to evaluate the pollutant removal efficiency of Chlorella and Scenedesmus species as well as their co-culture treating two-phase anaerobic digester effluent through microalgae biomass production. The dimensions of the rectangular photobioreactor used to conduct the experiment are 15 cm in height, 20 cm in width, and 30 cm in length. Removal efficiencies between 86.74–93.11%, 96.74–97.47%, 91.49–92.91%, 97.94–99.46%, 89.22–94.28%, and 91.08–95.31% were attained for chemical oxygen demand, total nitrogen, nitrate, ammonium, total phosphorous, and orthophosphate by Chlorella species, Scenedesmus species, and their co-culture, respectively. The average biomass productivity and biomass yield of Chlorella species, Scenedesmus species, and their co-culture were 1.4 ± 0.1, 1.17 ± 0.12, 1.5 ± 0.13 g/L, and 0.18, 0.21, and 0.23 g/L*day, respectively. The final effluent quality in terms of chemical oxygen demand, total nitrogen, and total phosphorous attained by Chlorella species and the co-culture were below the permissible discharge limit for slaughterhouse effluent standards in the country (Ethiopia). The results of the study showed that the use of microalgae as well as their co-culture for polishing the nutrients and residual organic matter in the anaerobically treated agro-processing industry effluent offers a promising result for wastewater remediation and biomass production. In general, Chlorella and Scenedesmus species microalgae and their co-culture can be applied as an alternative for nutrient removal from anaerobically treated slaughterhouse wastewater as well as biomass production that can be used for bioenergy.Graphical

Assessment and modeling of effluent quality, economic benefits, and greenhouse gas reduction for receiving brewery wastewater on A2O by GPS-X

Recently, breweries have been allowed to discharge brewery wastewater (BWW) to the sewage pipe network to alleviate the shortage of carbon sources of municipal wastewater treatment plants (MWTPs) under the premise of signing a contract with MWTPs in some countries. This study aims to provide a model-based method for MWTPs to evaluate the threshold, the effluent risk, the economic benefits, and the potential greenhouse gas (GHG) emissions reduction of receiving BWW. In this research, a simulation model of an anaerobic-anoxic-oxic process (A2O) receiving BWW was established based on the data of a real MWTP and brewery using GPS-X. The sensitivity factors of 189 parameters were analyzed, and several sensitive parameters were calibrated stably and dynamically. By analyzing the errors and standardized residuals, the calibrated model was proved to be high-quality and reliable. In the next phase, the impact of receiving BWW on the A2O was evaluated in terms of effluent quality, economic benefits, and GHG emissions reduction. The results showed that receiving a certain amount of BWW can effectively reduce the carbon source cost and GHG emissions for the MWTP compared with adding methanol. Though the chemical oxygen demand (COD), biochemical oxygen demand in five days (BOD5), and total nitrogen (TN) in the effluent increased in various degrees, the effluent quality still met the discharge standard implemented by the MWTP. The study can also facilitate the modeling work for many researchers and promote more kinds of food production wastewater to be treated equally.

Optimal control of sewage treatment process using a dynamic multi-objective particle swarm optimization based on crowding distance

A variety of multi-objective optimization algorithms has been extensively investigated in the past decades to tackle the optimal decision of sewage treatment process. However, achieving the ideal solutions is challenging in the multi-criteria decision-making process from Pareto optimal sets due to the complicated relationships among influencing factors, especially in the case of large decision variables involved in the wastewater treatment process. We thus proposed an improved dynamic multi-objective particle swarm optimization algorithm based on crowding distance (DMOPSO-CD) to obtain global optimal solutions for the balance between energy consumption (EC) and effluent quality (EQ) in sewage treatment processes. The algorithm consists of optimization modules and a self-organizing fuzzy neural network, improving the global searching ability of particles, maintaining the diversity of non-inferior solutions, and solving the multi-objective vital issues in the optimization of sewage treatment process. The proposed optimization algorithm was applied to benchmark simulation model No.1, and the optimization results showed that the EC for wastewater treatment in dry, rainy, and storm weather was reduced by 7.87%, 6.28%, and 7.30%, respectively. This methodology outperformed several widely applied algorithms, including the multi-objective cuckoo search, non-dominated sorting genetic algorithm-II, and improving Pareto evolutionary algorithm in terms of EQ and EC, which opens a new window for the optimal decision of sewage treatment.

Comparison of Chemical and Biological Phosphorus Removal from Wastewater in Numaniya WWTP

The water quality management for surface water aims to reducing the eutrophication by controlling and reducing the input phosphorus to the lakes and waterways. Two methods are currently being used around the world to remove phosphorus in wastewater: biological and chemical phosphorus removal. This study was conducted to predict and compare the efficiency of phosphorus removal between designed biological process for Numaniya WWTP and chemical process as well as EBPR plus chemical process. Results obtained from the study demonstrate that combination between the EBPR plus chemical process removal performs better than other choices in terms of effluent quality and alum cost .

Modelling of aerobic granular sludge reactors: the importance of hydrodynamic regimes, selective sludge removal and gradients.

Hydraulic selection is a key feature of aerobic granular sludge (AGS) systems but existing aerobic granular sludge (AGS) models neglect those mechanisms: gradients over reactor height (Hreactor), selective removal of slow settling sludge, etc. This study aimed at evaluating to what extent integration of those additional processes into AGS models is needed, i.e., at demonstrating that model predictions (biomass inventory, microbial activities and effluent quality) are affected by such additional model complexity. We therefore developed a new AGS model that includes key features of full-scale AGS systems: fill-draw operation, selective sludge removal, distinct settling models for flocs/granules. We then compared predictions of our model to those of a fully mixed AGS model. Our results demonstrate that hydraulic selection can be predicted with an assembly of four continuous stirred tank reactors in series together with a correction code for plug-flow. Concentration gradients over the reactor height during settling/plug-flow feeding strongly impact the predictions of aerobic granular sludge models in terms of microbial selection, microbial activities and ultimately effluent quality. Hydraulic selection is a key to predict selection of storing microorganisms (phosphorus-accumulating organisms (PAO) and glycogen-accumulating organisms (GAO)) and in turn effluent quality in terms of total phosphorus, and for predicting effluent solid concentration and dynamic during plug-flow feeding.

Behaviour of 27 selected emerging contaminants in vertical flow constructed wetlands as post-treatment for municipal wastewater

Six substrates (i.e. sand enriched with activated or non-activated biochar or zeolite in different ratios) were tested in Vertical Flow Constructed Wetlands (VFCWs) planted with Phragmites australis and Iris pseudacorus for the removal of 27 emerging contaminants from municipal wastewater. The laboratory investigation under controlled conditions (spiked constant concentrations in synthetic wastewater) lasted 357 days and proved VFCWs being able to provide excellent effluent quality in terms of both macro - and micropollutant elimination. Because overall removal efficiencies exceeded 90% in most of the cases, significant differences among the substrates were not detectable. For compounds with medium elimination (i.e. AMPA) the type of substrate seemed to play a strong role and the maximum amount of active ingredient adsorbed per amount of substrate has been quantified (i.e. 0.77 μg of AMPA per g of 30% biochar mixed with sand). Three of the most promising substrates from laboratory where thus selected to be tested under real conditions (fluctuation in concentration, variable temperature). As result, VFCWs with 15% activated biochar mixed with sand proved to be effective in the removal of 18 emerging contaminants and complying with national discharge standards for 4 selected compounds.

Conventional and high resolution chemical characterization to assess refinery effluent treatment performance

Refinery effluents represent an emission source of hydrocarbons (HCs) and other constituents to the environment. Thus, characterisation of effluent quality in terms of concentrations of key parameters relative to permitted standards is important and for total petroleum hydrocarbons (TPH), the specific composition of the HC mixture can affect its toxicity to aquatic organisms. Therefore, this study was designed to analyse TPH, benzene, toluene, ethyl benzene, xylenes (BTEX), polycyclic aromatic hydrocarbons (PAHs), (bio) chemical oxygen demand, total nitrogen, total suspended solids and selected metals before, and after, treatment steps to demonstrate removal efficiencies across 13 refineries with variable wastewater treatment systems. Final discharge concentrations of the measured parameters were by 97% within the so called Best Available Technique Associated Emission Levels (BAT-AELs). Further, TPH composition was characterised using high-resolution two-dimensional gas chromatography (GCxGC) analysis to understand the mass distribution by carbon number and specific chemical class. Measurements were compared to SimpleTreat model predictions for validation. SimpleTreat successfully predicted the shape of the effluent composition since it is essentially a removal constant applied to the influent composition. The predictions were of similar magnitude as, or were greater than, the effluent concentrations since SimpleTreat is based on typical performance and is intended to be conservative. This was especially true for aromatic constituents. Reduction in potential HC exposures also coincided with a decrease in predicted toxicity using a mechanistic oil toxicity model, PETROTOX. Overall, the results indicate that EU petroleum refineries are likely to achieve a high performance level regarding effluent treatment.

Vertical flow constructed wetlands using expanded clay and biochar for wastewater remediation: A comparative study and prediction of effluents using machine learning

This study evaluated and compared the performance of two vertical flow constructed wetlands (VF) using expanded clay (VF1) and biochar (VF2), of which both are low-cost, eco-friendly, and exhibit potentially high adsorption as compared to conventional filter layers. Both VFs achieved relatively high removal for organic matters (i.e. Biological oxygen demand during 5 days, BOD5) and nitrogen, accounting for 9.5 – 10.5 g.BOD5.m−2.d−1 and 3.5 – 3.6 g.NH4-N.m−2.d−1, respectively. The different filter materials did not exert any significant discrepancy to effluent quality in terms of suspended solids, organic matters and NO3-N (P > 0.05), but they did influence NH4-N effluent as evidenced by the removal rate of that by VF1 and VF2 being of 82.4 ± 5.7 and 84.6 ± 6.4%, respectively (P < 0.05). The results obtained from the designed systems were further subject to machine learning to clarify the effecting factors and predict the effluents. The optimal algorithms were random forest, generalized linear model, and support vector machine. The values of the coefficient of determination (R2) and the root mean square error (RMSE) of whole fitting data achieved 74.0% and 5.0 mg.L−1, 80.0% and 0.3 mg.L−1, 90.1% and 2.9 mg.L−1, and 48.5% and 0.5 mg.L−1 for BOD5_VF1, NH4-N_VF1, BOD5_VF2, and NH4-N_VF2, respectively

Effects of pharmaceutical load on the effluent quality using sequencing batch reactor

The effect of pharmaceutical load on the performance of laboratory scale sequencing batch reactor (SBR) in terms of effluent quality and sludge settling ability was studied. The SBR was operated using low-strength domestic wastewater and spiked with a unique combination of drugs namely atenolol, gliclazide and prazosin after 21 days of reactor operation. Atenolol and gliclazide were spiked at concentration of 1000 µg/l while 100 µg/l for prazosin. Several parameters were observed which includes concentration of COD, ammonia, MLSS and SVI30. The effluent quality and sludge settling ability before and after drugs introduction were compared. The average COD removal efficiency before and after the introduction of pharmaceutical was 85% and 74%, respectively. The average ammonia removals were 84% and 62% before and after addition of pharmaceutical respectively. MLSS and SVI30 values was successfully maintained within desired value at the end of experiment indicating good sludge accumulation and sludge settling ability.

Impact of microaeration bioreactor on dissolved sulfide and methane removal from real UASB effluent for sewage treatment.

Two bioreactors were investigated as an alternative for the post-treatment of effluent from an upflow anaerobic sludge blanket (UASB) reactor treating domestic sewage, aiming at dissolved sulfide and methane removal. The bioreactors (R-control and R-air) were operated at different hydraulic retention times (HRT; 6 and 3 h) with or without aeration. Large sulfide and methane removal efficiencies were achieved by the microaerated reactor at HRT of 6 h. At this HRT, sulfide removal efficiencies were equal to 61% and 79%, and methane removal efficiencies were 31% and 55% for R-control and R-air, respectively. At an HRT of 3 h, sulfide removal efficiencies were 22% (R-control) and 33% (R-air) and methane removal did not occur. The complete oxidation of sulfide, with sulfate formation, prevailed in both phases and bioreactors. However, elemental sulfur formation was more predominant at an HRT of 6 h than at an HRT of 3 h. Taken together, the results show that post-treatment improved the anaerobic effluent quality in terms of chemical oxygen demand and solids removal. However, ammoniacal nitrogen was not removed due to either the low concentration of air provided or the absence of microorganisms involved in the nitrogen cycle.

Optimization of hybrid treatment of olive mill wastewaters through impregnation onto raw cypress sawdust and electrocoagulation.

This research investigation proposes a new method for sustainable olive mill wastewater (OMW) treatment and handling. It is based on the combination of its impregnation onto raw cypress sawdust (RCS) followed by electrocoagulation. The retention of OMW compounds onto various RCS doses show an important decrease of its chemical oxygen demand (COD) and its main cation and anion content. The maximum retention efficiencies of COD,Na+, K+, Ca2+, Mg2+, Cl-, [Formula: see text], and [Formula: see text] were about 51.0%, 75.3%, 28.7%, 77.9%, 84.7%, 41.1%, 98.3%, and 90.9%, respectively, for the highest RCS dose (200gL-1). This organic matter- and nutrient-loaded biomass could be thermochemically converted through pyrolysis into biofuel and biochar for energetic and agronomic purposes, respectively. The treatment by electrocoagulation of the pre-treated OMW using mild steel electrodes could be considered an attractive treatment method since 75.6% of COD removal efficiency was achieved. Besides, this approach permits a significant energy consumption reduction by 46% as compared with the electrocoagulation process alone. It allows also a significant improvement of the treated effluent quality in terms of both organic and mineral contents that could be reused for the irrigation of olive trees in the context of circular economy.

Efficient carbon, nitrogen and phosphorus removal from low C/N real domestic wastewater with aerobic granular sludge

This work reports on simultaneous nitrification, denitrification and phosphorus removal treating real domestic wastewater with low carbon/nitrogen (C/N) ratio by aerobic granular sludge (AGS). Operations at high sludge retention time (SRT = 61 ± 24 days) resulted in low biomass yield per chemical oxygen demand removed (CODrem) (0.21 ± 0.01 gCODx/gCODrem), lower COD demand for denitrification as well as high effluent quality in terms of total suspended solids (TSS) (22 ± 7 mgTSS/L). The average ratio between the biodegradable soluble COD stored anaerobically as polyhydroxyalkanoates (PHAs) and the N removed was 3.1 ± 0.6 gCODsto/gNrem, suggesting that nitrification/denitrification occurred partly via the nitrite pathway. Results revealed that stable AGS process with high C/N/P removal efficiency of 84/71/96% can be obtained besides a low organic loading rate (0.43 ± 0.11 g COD/L/d) and influent C/N ratio (3.8 ± 1.6 g/g), resulting in a high effluent quality characterized by 25 ± 6 mg sCOD/L, 0.09 ± 0.07 mgPO4-P/L, 9 ± 2 mgTIN/L (10 ± 2 mgTN/L) and 22 ± 7 mgTSS/L.

The Self-Forming Dynamic Membrane BioReactor (SFD MBR) as a suitable technology for agro-industrial wastewater treatment

Two bench-scale Self-Forming Dynamic Membrane BioReactors (SFD MBR), equipped with 50 μm nylon meshes were set up and operated under aerobic conditions in order to treat canning and winery wastewaters. The results showed different behaviors of the two systems, confirming the strong dependence of SFD MBR performance on the type of biomass and, in turn, on the type of stream being treated. Both plants achieved good results in terms of effluent quality, demonstrating the suitability of the proposed technology. Median values of effluent turbidity were 2.7 and 15.4 NTU (Nephelometric Turbidity Units) in the reactors fed with canning wastewater and winery wastewater, respectively. The removal of organic matter (as COD, Chemical Oxygen Demand) was consistently above 90 %, although the retention of suspended solids was variable and somewhat dependent on operating conditions and feed composition. The activated sludge characteristics were observed to affect filtration performance and in particular the capillary suction time (CST) was a possible indicator of efficiency, with a threshold value of 11 s above which filtration performance decreased. This parameter is proposed as an early warning tool for changes in the filtration performance of an SFD MBR, both for effluent quality and cleaning requirements.

Considerations on Applying Practical Control Methodsin the Biological Treatment of Wastewaters from Paper Manufacturing

Due to high efficiency, in terms of effluent quality, the activated sludge treatment is the most common method for removing the biodegradable impurities from industrial and urban wastewaters. Although these engineering systems of biological wastewater treatments increase the rate of biodegradable substances removing, in most cases, these are rarely able to achieve the maximum performances due to the lack of some fast methods to monitor and control the living biomass. In this context, in present paper are described some methods for evaluation of viability and biological activity of activated sludge, as essential parameters for ensuring the performance of biological treatment process. The proposed methods are based on the determination of metabolically active bacteria in activated sludge, using the activity of dehydrogenase enzymes (Triphenyl tetrazolium chloride TTC method) in the biological treatment of wastewaters generated from the paper manufacturing process.

Modeling an in-situ hydrogenotrophic denitrification and oxidation process in an experimental scale aquifer

This paper presents a mathematical model for an in-situ hydrogenotrophic denitrification and oxidation process in an experimental scale aquifer. This model was developed to investigate the stable denitrification performance of the aquifer as well as the effects of varying the molar ratio of nitrate load to hydrogen gas injection (N/H ratio) on the effluent quality in terms of nitrate and nitrite concentrations under a long-term operation. The model could fairly predict the effluent quality in terms of nitrate and nitrite concentrations in the aquifer, in response to the sudden decrease in H2 gas injection as well as different N/H ratios. Furthermore, the model clearly demonstrated that denitrification and nitrification proceeded in each zone injected with H2 gas or O2 gas, respectively, and that stable treatment can be achieved. There were some differences between the experimental data and the model results for nitrate, nitrite, dissolved oxygen, and dissolved hydrogen at the H2-injection zone, implying that mass transfer rates in biofilm should be taken into consideration for more precise modeling. A sensitivity analysis showed that effluent quality in terms of nitrate concentration was the most sensitive to changes in maximum nitrate and nitrite utilization rates.

APPLICATION OF ELECTRO-COAGULATION FOR TREATMENT OF WASTEWATER FROM PACKAGE PRINTING PROCESS

Printing wastewater is generally considered as hazardous waste whose treatment and disposal are strictly regulated. Although electro-coagulation (EC) process has been successfully applied for the treatment of different types of wastewater, its application for printing wastewater is rarely reported. In this study, EC was applied to treat the printing ink wastewater, taken from a paper packing factory in An Giang Plant Protection Join Stock Company, which was highly colored and contaminated with organic compounds. The treatment process was performed using aluminum electrodes for two hours. Effects of applied voltage (5 - 40 V), pH (5 - 9), electrodes distance (1 - 5 cm), salt concentration in electrolyte solution (0.05 - 0.4 g/L), and the rotational speed of stirring (0 - 400 rpm) on the removal efficiencies of color and COD were investigated. Based on the effects of various factors, optimum condition for the treatment was given. Results showed that the EC process can effectively remove color and COD for 30 min. The effluent quality in terms of color and COD met well National Technical Regulation on Industrial Wastewater (QCVN 40-2011/BTNMT, column B). Finally, a comparison in removal efficiencies between the processes of EC and chemical-coagulation was also presented.

Model-based energy and uncertainty analysis of membrane bioreactor to treat PVC production site wastewater

A pilot-scale membrane bioreactor (MBR) was developed to treat poly vinyl chloride (PVC) production site wastewater. Meanwhile, a simulation model based on activated sludge model No.1 (ASM1) was developed and calibrated for the MBR to evaluate performance in terms of effluent quality, energy consumption, and operation strategy reliability. Furthermore, a modified aeration model was proposed taking into consideration the effect of mixed liquor suspended solids (MLSS) on oxygen transfer. The results showed that the calibrated ASM1 was able to simulate NO3-N satisfactorily and simulate NH4-N and MLSS in the aerobic tank reasonably in both steady and dynamic states; the pilot-scale MBR consumed 0.73kWhm3 permeate production. After the calibration and validation of the MBR process model, a scenario analysis (SCA) was conducted to analyze the effect of sludge retention time (SRT), recirculation ratio (R), and dissolved oxygen (DO) on aeration energy demand and effluent quality. Moreover, Latin Hypercube Sampling (LHS) was performed to study the uncertainty of model parameters to judge the reliability of the operation strategy to meet certain criteria. It was evident that the current operation strategy was able to reach the target with an effluent NH4-N concentration lower than 2mgL−1 for about 97% chance.

Performance evaluation of a large sewage treatment plant in Brazil, consisting of an upflow anaerobic sludge blanket reactor followed by activated sludge.

The objective of this study was to evaluate the behaviour of a system comprising an upflow anaerobic sludge blanket reactor followed by activated sludge to treat domestic sewage. The Betim Central sewage treatment plant, Brazil, was designed to treat a mean influent flow of 514 L/s. The study consisted of statistical treatment of monitoring data from the treatment plant covering a period of 4 years. This work presents the concentrations and removal efficiencies of the main constituents in each stage of the treatment process, and a mass balance of chemical oxygen demand (COD) and nitrogen. The results highlight the good overall performance of the system, with high mean removal efficiencies: BOD (biochemical oxygen demand) (94%), COD (91%), ammonia (72%) and total suspended solids (92%). As expected, this system was not effective for the removal of nutrients, since it was not designed for this purpose. The removal of Escherichia coli (99.83%) was higher than expected. There was no apparent influence of operational and design parameters on the effluent quality in terms of organic matter removal, with the exceptions of the BOD load upstream of the aeration tank and the sludge age in the unit. Results suggest that this system is well suited for the treatment of domestic sewage.

Optimized MBR for greywater reuse systems in hotel facilities

Greywater is an important alternative water source, particularly in semi-arid, touristic areas, where the biggest water demand is usually in the dry period. By using this source wisely, tourist facilities can substantially reduce the pressure to scarce water resources. In densely urbanized touristic areas, where space has high value, compact solutions such as MBR based greywater reuse systems appear very appropriate. This research focuses on technical and economical evaluation of such solution by implementing a pilot MBR to a hotel with separated grey water. The pilot was operated for 6 months, with thorough characterisation of the GW performed, its operation was monitored and its energy consumption was optimized by applying a control system for the air scour. Based on the pilot operation a design and economic model was set to estimate the feasibility (CAPEX, OPEX, payback period of investment) of appropriate scales of MBR based GW systems, including separation of GW, MBR technology, clean water storage and disinfection. The model takes into account water and energy prices in Spain and a planning period of 20 years. The results demonstrated an excellent performance in terms of effluent quality, while the energy demand for air-scour was reduced by up to 35.2%, compared to the manufacturer recommendations. Economical evaluation of the entire MBR based GW reuse system shows its feasibility for sizes already at 5 m3/day (60 PE). The payback period of the investment for hotels like the demonstration hotel, treating 30 m3/day is 3 years.