Quality Of Wastewater Treatment Plant Research Articles

Adaptive prediction for effluent quality of wastewater treatment plant: Improvement with a dual-stage attention-based LSTM network

The accurate effluent prediction plays a crucial role in providing early warning for abnormal effluent and achieving the adjustment of feedforward control parameters during wastewater treatment. This study applied a dual-staged attention mechanism based on long short-term memory network (DA-LSTM) to improve the accuracy of effluent quality prediction. The results showed that input attention (IA) and temporal attention (TA) significantly enhanced the prediction performance of LSTM. Specially, IA could adaptively adjust feature weights to enhance the robustness against input noise, with R2 increased by 13.18%. To promote its long-term memory ability, TA was used to increase the memory span from 96 h to 168 h. Compared to a single LSTM model, the DA-LSTM model showed an improvement in prediction accuracy by 5.10%, 2.11%, 14.47% for COD, TP, and TN. Additionally, DA-LSTM demonstrated excellent generalization performance in new scenarios, with the R2 values for COD, TP, and TN increasing by 22.67%, 20.06%, and 17.14% respectively, while the MAPE values decreased by 56.46%, 63.08%, and 42.79%. In conclusion, the DA-LSTM model demonstrated excellent prediction performance and generalization ability due to its advantages of feature-adaptive weighting and long-term memory focusing. This has forward-looking significance for achieving efficient early warning of abnormal operating conditions and timely management of control parameters.

Pathways and efficiency of nitrogen attenuation in wastewater effluent through soil aquifer treatment

Soil Aquifer Treatment (SAT) is used to increase groundwater resources and enhance the water quality of wastewater treatment plant (WWTP) effluents. The resulting water quality needs to be assessed. In this study, we investigate attenuation pathways of nitrogen (N) compounds (predominantly NH4+) from a secondary treatment effluent in pilot SAT systems: both a conventional one (SAT-Control system) and one operating with a permeable reactive barrier (PRB) to provide extra dissolved organic carbon to the recharged water. The goal is to evaluate the effectiveness of the two systems regarding N compounds by means of chemical and isotopic tools. Water chemistry (NO3−, NH4+, Non-Purgeable Dissolved Organic Carbon (NPDOC), and O2) and isotopic composition of NO3− (ẟ15N–NO3- and ẟ18O–NO3-) and NH4+ (ẟ15N–NH4+) were monitored in the inflow and at three different sections and depths along the aquifer flow path. Chemical and isotopic results suggest that coupled nitrification-denitrification were the principal mechanisms responsible for the migration and distribution of inorganic N in the systems and that nitrification rate decreased with depth. At the end of the study period, 66% of the total N in the solution was removed in the SAT-PRB system and 69% in the SAT-Control system, measured at the outlet of the systems. The residual N in solution in the SAT-PRB system had an approximately equal proportion of N–NH4+ and N–NO3- while in the SAT-Control system, the residual N in solution was primarily N–NO3-. Isotopic data also confirmed complete NO3− degradation in the systems from July to September with the possibility of mixing newly generated NO3− with the residual NO3− in the substrate pool.

Enhancing Real-Time Prediction of Effluent Water Quality of Wastewater Treatment Plant Based on Improved Feedforward Neural Network Coupled with Optimization Algorithm

To provide real-time prediction of wastewater treatment plant (WWTP) effluent water quality, a machine learning (ML) model was developed by combining an improved feedforward neural network (IFFNN) with an optimization algorithm. Data used as input variables of the IFFNN included hourly influent water quality parameters, influent flow rate and WWTP process monitoring and operational parameters. Additionally, input variables included historical effluent water quality parameters for future prediction. The model was demonstrated in a WWTP in Jiangsu Province, China, where prediction of effluent chemical oxygen demand (COD) and total nitrogen (TN) with large variations were tested. Relative to the traditional feedforward neural network (FFNN) model without considering historical effluent water quality parameter input, the IFFNN enhanced prediction performance by 52.3% (COD) and 72.6% (TN) based on the mean absolute percentage errors of test datasets, after its model structure was optimized with a genetic algorithm (GA). The problem of over-fitting could also be overcome through the use of the IFFNN, with the determination of coefficient increased from 0.20 to 0.76 for test datasets of effluent COD. The GA-IFFNN model, which was efficient in capturing complex non-linear relationships and extrapolation, could be a useful tool for real-time direction of regulatory changes in WWTP operations.

Increased Transparency and Resource Prioritization for the Management of Pollutants From Wastewater Treatment Plants: A National Perspective From Australia

With increasing human populations in coastal regions, there is growing concern over the quality of wastewater treatment plant (WTP) discharge and its impacts on coastal biodiversity, recreational amenities, and human health. In Australia, the current system of WTP monitoring and reporting varies across states and jurisdictions leading to a lack of data transparency and accountability, leading to a reduced ability to comprehensively assess regional and national scale biodiversity impacts and health risks. The National Outfall Database (NOD) was developed to provide a centralized spatial data management system for sharing and communicating comprehensive, national-scale WTP pollutant data. This research describes the structure of the NOD and through self-organizing maps and principal component analysis, provides a comprehensive, national-scale analysis of WTP effluent. Such a broad understanding of the constituents and level of pollutants in coastal WTP effluent within a public database provides for improved transparency and accountability and an opportunity to evaluate health risks and develop national water quality standards.

Monitoring effluent quality of wastewater treatment plant by clustering based artificial neural network method

Monitoring effluent quality of wastewater treatment plant by clustering based artificial neural network method

Pollutant exchange between sewage and sediment in urban sewer systems

In this study, the apparent phenomenon of pollutant exchange between sewage and sediment that affected the influent quality of wastewater treatment plants was evaluated by a long-term monitoring in a pilot sewer system. In order to understand the in-depth effect of this phenomenon on water quality in sewer, the pollutant exchange pathways of physical pollutant deposition (PPD), biological transformation adsorption (BTA) and biological transformation release (BTR) were first proposed in this study. And then, the controlled experiments (prohibiting the microbial activity in either biofilms or sediment) were established to quantify the physical and biological pollutant exchange capacity. The results showed that the PPD values of organic, nitrogen and phosphorus pollutants were 144.0 mg/L, 5.15 mg/L and 3.79 mg/L, respectively, and this pathway accounted for over 70% of the pollutant decrease in sewage. It indicated that the PPD was the dominant pollutant exchange pathway in sewers. Meanwhile, the pollutant exchange values in BTR were more than two times of those in BTA (39.2 mg/L > 14.7 mg/L for organic matters; 1.79 mg/L > 0.85 mg/L for nitrogen pollutants; 2.12 mg/L > 1.01 mg/L for phosphorus pollutants). The result indicated that the BTR was the dominant biological reaction which affected the pollutant structures in sewage (especially resulting in the accumulation of volatile fatty acids), and consequently, changed the biodegradability of sewage. Therefore, this study revealed the characteristics of pollutant exchange pathways in sewers and could provide a theoretical basis for the future development of urban sewer systems.

A systematic approach of removal mechanisms, control and optimization of silver nanoparticle in wastewater treatment plants

The release of silver nanoparticles (AgNPs) to wastewater caused by over-generation and poor treatment of the remaining nanomaterial has raised the interest of researchers. AgNPs can have a negative impact on watersheds and generate degradation of the effluent quality of wastewater treatment plants (WWTPs). The aim of this research is to design and analyze an integrated model system for the removal of AgNPs with high effluent quality in WWTPs using a systematic approach of removal mechanisms modeling, optimization, and control of the removal of silver nanoparticles. The activated sludge model 1 was modified with the inclusion of AgNPs removal mechanisms, such as adsorption/desorption, dissolution, and inhibition of microbial organisms. Response surface methodology was performed to minimize the AgNPs and total nitrogen concentrations in the effluent by optimizing operating conditions of the system. Then, the optimal operating conditions were utilized for the implementation of control strategies into the system for further analysis of enhancement of AgNPs removal efficiency. Thus, the overall AgNP removal efficiency was found to be slightly higher than 80%, which was an improvement of almost 7% compared to the BSM1 reference value. This study provides a systematic approach to find an optimal solution for enhancing AgNP removal efficiency in WWTPs and thereby to prevent pollution in the environment.

Investigating the quality and quantity of effluent in wastewater treatment plants of Iran: A case study of Tehran

Control and monitoring of water sources from different types of contaminants especially collection and proper wastewater discharge is very important, in Iran which is considered as one of the dry regions in the world. Undesired quality of wastewater treatment plant’s (WWTPs) effluent causes many environmental problems.In this research the parameters of Biochemical oxygen demand, Chemical oxygen demand, Total solids, Total suspended solids, Total dissolved solids, Potential of Hydrogen, Mixed liquor suspended solids, Mixed liquor volatile suspended solids, Sludge volume index, and temperature are examined based on the book of Standard Methods. The results of analyzing the above parameters which are related to eight WWTPs effluent out flow in Tehran, were analyzed by SPSS and Excel soft wares. The achieved data were compared to the standards of Iran’s Environmental protection agency. The results has shown that the parameters of Potential of Hydrogen, Chemical oxygen demand, Biochemical oxygen demand, and Total suspended solids of WWTPs effluent in Tehran are in accordance with standards of Environmental protection agency which are respectively 97.5%, 95.8%, 96.1%, 68.8%.WWTPs of C has also the best operation among other WWTPs. In this study, due to ethical considerations, the name of the WWTPs is not mentioned. The names of the WWTPs are marked with A–H.

Estimation of pH and MLSS using Neural Network

The main challenges to achieving a reliable model which can predict well the process are the nonlinearities associated with many biological and biochemical processes in the system. Artificial intelligent approaches revolved as better alternative in predicting the system. Typical measured variables for effluent quality of wastewater treatment plant are pH, and mixed liquor suspended solids (MLSS). This paper presents an adaptive neuro-fuzzy inference system (ANFIS) and feed-forward neural network (FFNN) modeling applied to the domestic plant of the Bunus regional sewage treatment plant. ANFIS and feed- forward neural network techniques as nonlinear function approximators have demonstrated the capability of predicting nonlinear behaviour of the system. The data for the period of two years and nine months sampled weekly (140 week samples) were collected and used for this study. Simulation studies showed that the prediction capability of the ANFIS model is somehow better than that of the FFNN model. The ANFIS model may serves as a valuable prediction tool for the plant.

Water quality permitting: From end-of-pipe to operational strategies

End-of-pipe permitting is a widely practised approach to control effluent discharges from wastewater treatment plants. However, the effectiveness of the traditional regulation paradigm is being challenged by increasingly complex environmental issues, ever growing public expectations on water quality and pressures to reduce operational costs and greenhouse gas emissions. To minimise overall environmental impacts from urban wastewater treatment, an operational strategy-based permitting approach is proposed and a four-step decision framework is established: 1) define performance indicators to represent stakeholders’ interests, 2) optimise operational strategies of urban wastewater systems in accordance to the indicators, 3) screen high performance solutions, and 4) derive permits of operational strategies of the wastewater treatment plant. Results from a case study show that operational cost, variability of wastewater treatment efficiency and environmental risk can be simultaneously reduced by at least 7%, 70% and 78% respectively using an optimal integrated operational strategy compared to the baseline scenario. However, trade-offs exist between the objectives thus highlighting the need of expansion of the prevailing wastewater management paradigm beyond the narrow focus on effluent water quality of wastewater treatment plants. Rather, systems thinking should be embraced by integrated control of all forms of urban wastewater discharges and coordinated regulation of environmental risk and treatment cost effectiveness. It is also demonstrated through the case study that permitting operational strategies could yield more environmentally protective solutions without entailing more cost than the conventional end-of-pipe permitting approach. The proposed four-step permitting framework builds on the latest computational techniques (e.g. integrated modelling, multi-objective optimisation, visual analytics) to efficiently optimise and interactively identify high performance solutions. It could facilitate transparent decision making on water quality management as stakeholders are involved in the entire process and their interests are explicitly evaluated using quantitative metrics and trade-offs considered in the decision making process. We conclude that the operational strategy-based permitting shows promising for regulators and water service providers alike.

Application of dissolved air flotation (DAF) with coagulation process for treatment of phosphorus within permeate of membrane bioreactor (MBR)

It is well known that eutrophication is one of the main issues with regard to environmental pollution and that phosphorus is the most critical among various nutrients. Consequently, effluent water quality of wastewater treatment plants has been recently reinforced in Korea. Many studies have been made on membrane bioreactor (MBR) processes, some of the more advanced wastewater treatment processes. However, MBR processes are relatively vulnerable to biological phosphorus treatment in comparison with conventional activated sludge processes. Alternately, dissolved air flotation (DAF) processes were applied as post-treatment of MBR processes in order to decrease T-P concentration of the final effluent. It was observed that T-P removal efficiency was 51.2% and that T-P concentration of the final effluent ranged from 0.49 to 1.62 mg/L with addition of 15 mg/L of alum to the rapid mixing reactor of DAF processes. The next step includes the addition of anionic polymers and bentonite to slow and rapid mixing tanks of DAF processes, respectively, to improve phosphorus removal efficiencies. Although T-P removal efficiency increased significantly from 51.2 to 78%, T-P concentration of effluent was observed between 0.38 and 0.96 mg/L. Lastly, the MBR process was controlled by adding a low concentration of alum to an aerobic tank and influent under 1 ± 0.3 mg/L of T-P. While T-P removal efficiency was around 80% in both 7 and 10 mg/L of alum, most measured values were under 0.2 mg/L except for several days of measurement. This indicates the potential of DAF processes for removing phosphorus as post-treatment of MBR.

Numerical simulation of optimal submergence depth of impellers in an oxidation ditch

AbstractSubmergence depth of impellers for an oxidation ditch (OD) has significant impact on energy consumption and effluent quality of wastewater treatment plants. The effect of the submergence depth of impellers on the structure of flow fields in an OD was studied using an experimentally validated numerical tool, based on computational fluid dynamics (CFD) model. The two-phase gas–liquid model and the 3D RNG k–e turbulence model were used to describe flow in ODs. The pressure implicit with splitting of operators algorithm was used to solve velocity and pressure. The volume of fluid (VOF) method was used to simulate free-water surface. The concept of submergence depth ratio representing the impeller’s submergence depth h to the total water depth H, h/H, was introduced to analyze the simulation results. Under different submergence depth ratios of impellers in an OD, the velocity fields were computed and analyzed, which shows that with the submergence depth ratio 0.45, the percentage of VOF particles with ...

Optimization of modified ABA2 process using linearized ASM2 for saving aeration energy

Abstract In the recent years, increasingly strict demands on the effluent quality of wastewater treatment plants (WWTPs) and concern for energy consumption have led to the growing interest in the development of an optimization and control scheme for treatment processes. In general, operation of WWTPs can be controlled either by real-time monitoring of major constituents or through model prediction. In this research, a simplified ASM2 model was applied to describe the dynamics of NH 4 + , NO 3 − and PO 4 3− in a modified anaerobic, buffer, intermittently aerated, and oxic pilot-scale plant (treatment capacity = 50 m 3 d −1 ). Using this model, the system performance was optimized by adjusting aeration and non-aeration time to control effluent ammonia level to preset values and at the same time to minimize energy consumption for aeration. As a result of the operation, the system could achieve 89%, 73%, and 82% removal efficiencies for COD, TN, and TP, respectively. The average f a (aeration cycle time/total cycle time) values were 0.46 for optimization as compared to 0.57 for normal operation. The standard errors between model predictions and measured effluent NH 4 + –N were 0.1 mg L −1 for the optimization scheme. With an application of optimizer, it can maintain good effluent water quality while achieving energy saving. For our pilot scale plant, it was calculated that annual electricity cost of about 600 USD could be saved if the plant would be continuously operated by the optimization scheme.

Study on two operating conditions of a full-scale oxidation ditch for optimization of energy consumption and effluent quality by using CFD model

The operating condition of an oxidation ditch (OD) has significant impact on energy consumption and effluent quality of wastewater treatment plants (WWTPs). An experimentally validated numerical tool, based on computational fluid dynamics (CFD) model, was proposed to optimize the operating condition by considering two important factors: flow field and dissolved oxygen (DO) concentration profiles. The model is capable of predicting flow pattern and oxygen mass transfer characteristics in ODs equipped with surface aerators and submerged impellers. Performance demonstration and comparison of two operating conditions (existing and improved) were carried out in two full-scale Carrousel ODs at the Ping Dingshan WWTP in Henan, China. A moving wall model and a fan model were designed to simulate surface aerators and submerged impellers, respectively. Oxygen mass transfer in the ditch was predicted by using a unit analysis method. In aeration zones, the mass inlets representing the surface aerators were set as one source of DO. In the whole straight channel, the oxygen consumption was modeled by using modified BOD-DO model. The following results were obtained: (1) the CFD model characterized flow pattern and DO concentration profiles in the full-scale OD. The predicted flow field values were within 1.98 ± 4.28% difference from the actual measured values while the predicted DO concentration values were within −4.71 ± 4.15% of the measured ones, (2) a surface aerator should be relocated to around 15 m from the curve bend entrance to reduce energy loss caused by fierce collisions at the wall of the curve bend, and (3) DO concentration gradients in the OD under the improved operating condition were more favorable for occurrence of simultaneous nitrification and denitrification (SND).

Biofilm/membrane filtration for reclamation and reuse of rural wastewaters

To cost-effectively meet water quality and quantity requirements for rural areas, the objective of this research was to evaluate the performances of a three-stage process of anaerobic-oxic-anoxic biofilm filtration (AOBF) and membrane filtration (MF) processes and to assess the potential for reclamation and reuse of blended wastewater contained domestic wastewater, black water, and landfill leachate. The AOBF process at < LV 30 m/day showed good removal results of > 90% for conventional pollutants (> 75% for COD) and > 70% for nutrient. Influent step-feeding with 0.8Q into filter bed 1 and 0.2Q into filter bed 2 achieved denitrification efficiency of 5-10% higher than without step feed. Efficiencies of plate membrane removal were greater than 90% for COD and more than approximate 75% for nutrients and heavy metals, respectively. The AOBF/MF system showed excellent removal results of > 90-95% for soluble nutrients as well as nonsoluble fractions such as TSS, particulate COD. The effluent of AOBF/MF system met the reuse standard for industrial and agricultural water, while effluent of AOBF met the standard for the effluent quality of wastewater treatment plants. These results indicate that the AOBF/MF system was suitable for rural integrated wastewater treatment by achieving cost-effectively an effluent quality able to be used for industrial, agricultural and water bodies recharge purposes.

Development and characterization of a novel immobilized microbial membrane for rapid determination of biochemical oxygen demand load in industrial waste-waters

The rapid determination of waste-water quality of waste-water treatment plants in terms of pollutional strength, i.e. biochemical oxygen demand (BOD) is difficult or even impossible using the chemical determination method. The present study reports the determination of BOD within minutes using microbial BOD sensors, as compared to the 5-day determination using the conventional method. Multiple criteria establish the basis for the development of a BOD biosensor useful for rapid and reliable BOD estimation in industrial waste-waters. Of these, preparation of a suitable novel immobilized microbial membrane used in conjunction with an apt transducer is discussed. As a result, a microbial biosensor based on a formulated, synergistic, pre-tested microbial consortium has been developed for the measurement of BOD load of various industrial waste-waters. The sensor showed maximum response in terms of current difference, when a cell concentration of 2.25×10 10 CFU, harvested in their log phase of growth were utilized for microbial membrane construction. The sensor showed a stability of 180 days when the prepared membranes were stored at a temperature of 4 °C in 50 mM phosphate buffer of pH 6.8. The reusability of the immobilized membranes was up to 200 cycles without appreciable loss of their response characteristics. A linear relationship between the current change and a glucose–glutamic acid (GAA) concentration up to 60 mg l −1 was observed ( r=0.999). The lower detection limit was 1.0 mg l −1 BOD. The sensor response was reproducible within ±5% of the mean in a series of ten samples having 44 mg l −1 BOD using standard a GGA solution. When used for the BOD estimation of industrial waste-waters, a relatively good agreement was found between the two methods, i.e. 5-day BOD and that measured by the developed microbial sensor.

Optimal Combination of Flocculating Filtration and Ultra Filtration for Advanced Effluent Treatment in the Netherlands

With changing policies to solve local environmental and dehydration problems and with increasing interest in differentiation of water qualities by industrial and domestic users, a growing need exists to improve the effluent quality of wastewater treatment plants (wwtp) in the Netherlands. The change of policy to retain water in its original environment as much as possible leads to an increasing interest in discharging wwtp effluent into polders and local water courses instead of large surface waters. Besides, a new element is the interest in the production of household and industry water by the Dutch drinking water companies. At several Dutch wwtp's research on (the combination of) fluocculating filtration and ultra filtration is done to develop the possibilities of (re)using effluent in the Netherlands. The results of the research have shown that flocculating filtration and/or ultra filtration are technically and economically applicable for the production of household and industry water.

Optimal combination of flocculating filtration and ultra filtration for advanced effluent treatment in The Netherlands

With changing policies to solve local environmental and dehydration problems and with increasing interest in differentiation of water qualities by industrial and domestic users, a growing need exists to improve the effluent quality of wastewater treatment plants (wwtp) in the Netherlands. The change of policy to retain water in its original environment as much as possible leads to an increasing interest in discharging wwtp effluent into polders and local water courses instead of large surface waters. Besides, a new element is the interest in the production of household and industry water by the Dutch drinking water companies.At several Dutch wwtp's research on (the combination of) flocculating filtration and ultra filtration is done to develop the possibilities of (re)using effluent in the Netherlands. The results of the research have shown that flocculating filtration and/or ultra filtration are technically and economically applicable for the production of household and industry water.