Cloud-Model-Based Feature Engineering to Analyze the Energy-Water Nexus of a Full-Scale Wastewater Treatment Plant

Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.

Prediction and Analysis of Total Nitrogen in a Sewage Treatment Plant Effluent

Total nitrogen was an important indicator for characterizing eutrophication of polluted water. Although the use of water quality online monitoring instrument can monitor water quality changes in real time, the degree of intelligence was low, so it was urgent to predict the water quality and take precautions in advance. A predictive model for total nitrogen levels in a sewage treatment plant utilizing the Anaerobic-Anoxic-Oxic (AAO) process was investigated in this paper. This model demonstrated significant practical application value. Based on the ARIMA (Autoregressive Integrated Moving Average) model and taking into account the impact of Biochemical Oxygen Demand (BOD), a prediction model for effluent total nitrogen was developed. However, the initial results exhibited significant deviations. To address this issue, seasonal factors were further considered. Then, the dataset was divided into winter and Non-winter sub-samples, leading to a reconstruction of the prediction model. Additionally, in developing the Non-winter prediction model, life cycle considerations were incorporated, and consequently, a SARIMA (Seasonal Autoregressive Integrated Moving Average) model was established. The predicting deviation associated with both the winter and Non-winter forecasting models showed a significant reduction.

Advances in Research of Characteristics and Removal of Microplastics in Sewage Treatment Plants

Microplastic pollution has become a worldwide issue.The discharge of sewage treatment plants(STPs)or wastewater treatment plant(WWTPs)is an important way for microplastics to enter the environment.This study reviewed the sources and occurrence characteristics(type,size,color and components)of microplastics in domestic and foreign sewage plants.It elaborated the removal principles of microplastics by primary,secondary and tertiary treatments.In addition,the removal effects of various treatment units and different processes on microplastics were summarized.In the future,the removal mechanism of microplastics in sewage treatment plants should be discussed in more depth,so as to further improve the removal rate of microplastics by optimizing and transforming traditional sewage treatment processes.Therefore,it is necessary to develop new technologies/processes specifically for the removal of microplastics and promote them to practical applications.

Levels and distributions of polychlorinated biphenyls in sewage sludge of urban wastewater treatment plants

Concentrations of polychlorinated biphenyls （PCBs） have been measured in sewage sludge samples from 8 urban wastewater treatment plants in Beijing, China. The PCB congeners were analyzed by isotope dilution high resolution gas chromatography/high resolution mass spectrometry method. The concentration of PCBs ranged from 65.6 to 157 ng/g dry weight （dw）, with a mean value of 101 ng/g dw. The dioxin-like PCB WHO-TEQs （World Health Organization-Toxic Equivalents） of the sludge were lower than 1 pg /g dw. Consequently, all the concentrations of PCBs in sludge samples were below the upper limit for land application according to the Chinese legislation law for agriculture use. The PCB homologue profiles in sludge samples were dominated by tri-CBs and tetra- CBs. Similar distributions have been found in one of the Chinese PCB commercial products. The patterns of dioxin-like and indicator congeners observed in this study were quite similar in all samples. The predominant congener for dioxin-like and indicator PCBs were PCB-118 and PCB-28, respectively, while PCB-126 had the highest TEQ value.

Optimum municipal wastewater treatment plant design with consideration of uncertainty

A newly developed model for the optimum municipal wastewater treatment plant(MWTP) design is presented. Through introducing the interval variables, the model attempts to consider the effects of uncertainties caused by the fluctuation of the wastewater quality and quantity during the design of MWTP. The model solution procedure is illustrated in detail, and a numerical example is given to verify the feasibility and advantage of the model. Furthermore, the possibility of the model application is briefly outlined.

Advanced Treatment of Wastewater Treatment Plant Effluent by Using Biofilms on Filamentous Bamboo

[ Objective ] The study aimed at treating wastewater treatment plant （WWTP） effluent by using bio-film reactor with filamentous bamboo as bio-carrier. [ Method] With the aid of a continuous flow reactor, a bio-film reactor using filamentous bamboo as bio-carrier was used to treat WWTP effluent with low C/N ratio, and the removal effects of CODc,, TN （total nitrogen）, and NO3--N in the wastewater were analyzed.[ Result ] The average removal rates of CODcr, TN, and NO3- -N reached 47.7%, 23.6% and 34.5% when the C/N ratio of influent was around 2. In addi- tion, a stable bio-film was formed very well in the secondary effluent with low C/N ratio and hardly degradable organic pollutants. The pollutants could be removed effectively because of the excellent surface characteristics and compositions of filamentous bamboo. [ Conclusion] The research provides a new method to treat WWTP effluent with low C/N ratio.

Deep learning-based intelligent management for sewage treatment plants

It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily volumes of sewage.The generation of sewage is the result of multiple factors from the whole social system.Characterized by strong process abstraction ability,data mining techniques have been viewed as promising prediction methods to realize intelligent STP management.However,existing data mining-based methods for this purpose just focus on a single factor such as an economical or meteorological factor and ignore their collaborative effects.To address this challenge,a deep learning-based intelligent management mechanism for STPs is proposed,to predict business volume.Specifically,the grey relation algorithm(GRA) and gated recursive unit network(GRU) are combined into a prediction model(GRAGRU).The GRA is utilized to select the factors that have a significant impact on the sewage business volume,and the GRU is set up to output the prediction results.We conducted a large number of experiments to verify the efficiency of the proposed GRA-GRU model.

The Effect of Wastewater Treatment Plants on Retainment of Plastic Microparticles to Enhance Water Quality—A Review

Microplastics, plastic pieces of ≤5 mm in size, are ubiquitous in ther environment and can be found in both terrestrial and aquatic ecosystems. This manuscript reviews the literature on the fate of microplastics in wastewater treatment and briefly highlights novel developments in the removal of microplastics from aqueous systems.

Discussion on the Problems and Developing Trend of Construction of Sewage Treatment Plants in Small Towns

Existing problems of sewage treatment plants in small towns were summarized firstly,and then the developing trend of construction of sewage treatment plants in small towns was discussed from the aspects of project decision,site selection,design,processing technology and construction financing models. Finally,outlooks for its future development were proposed to provide reference for the construction of sewage treatment plants in small towns in future.

Notice on a Case Study on the Utilization of Wind Energy Potential on a Remote and Isolated Small Wastewater Treatment Plant

Small wastewater treatment plants (WWTP) are frequently located, by necessity, in remote and isolated sites, which increases the difficulty of its energy supply. Some of them are located near the seaside, in environmental sensible zones, and due to tourism activity of these sites, seasonal effects related with population size fluctuation can occur, which can originate certain inefficiencies concerning WWTP design and energy supply. The objective of this paper is to describe a step by step procedure for evaluation of the wind potential of sites that are dependent of in-situ energy generation, as well as, a case study on the utilization of the potential wind energy in Magoito WWTP (5000 p.e.). The employed methodology comprised the collection of one year of in-situ wind data and its validation by comparison with historical data of about 10 years of a nearby anemometric station. The data provided by the two anemometric stations was statistically treated. It allowed the analysis of the results from the two stations are promissory in terms of wind availability and velocity. Finally, it comprised the simulation of the local wind conditions for a considerable larger area in order to find the best site for locating a wind turbine.

Effectiveness of Centralized Wastewater Treatment Plant in Removing Emerging Contaminants: A Case Study at Kuching, Malaysia

Before the construction of the Kuching Centralized Wastewater Treatment System Package 1 (KCWTSP1), partially treated blackwater and greywater were discharged directly into natural waterways. The accumulated wastewater had polluted Sarawak river, which is regulated and cannot discharge freely into the South China Sea. The polluted Sarawak river has endangered human health, river water quality, and aquatic ecosystems. Hence, the KCWTSP1 commissioned in 2015 serves the purpose of removing pollutants from wastewater before it is discharged into natural waterways. However, the effectiveness of KCWTPP1 is unknown. This paper is aimed to discuss and review the effectiveness of KCWTPP1 in treating wastewater since its inception in 2015. From 2017 to 2020, KCWTPP1 has treated an average of 4,200,000 m3 of wastewater per year. Generally, most of the discharge effluent met Environmental Quality Act (1974) Standard A criteria, except for the oil and grease parameter. Initially, the plant could not treat suspended solids and total phosphorus, but this was greatly improved in subsequent years. Therefore, some improvements are required to treat oil and grease parameters effectively and efficiently to ensure that only Standard A effluent is discharged into the Sarawak River in the future.

Behavior of Antibiotic-Resistant Fecal Coliforms in the Stream of a Sewage Treatment Plant in Tokyo

We are confronting a new threat in the prevalence of antibiotic-resistant bacteria followed by epidemic spread in aquatic environments in metropolitan areas because damage from river floods is increasing remarkably in Japan due to global extreme weather. The sewer penetration rate is about 100% in Tokyo and reclaimed water from sewage treatment plants accounts for over 50% of all water in both the down- and mid-stream areas of local rivers. The water quality of these rivers, which contain microflora, seems to be seriously affected by reclaimed water. In this study, we collected water samples on July 17, 2018 and examined the behavior of antibiotic-resistant fecal coliforms in the stream of a sewage treatment plant in Tokyo. Extended-spectrum β-lactamase (ESBL)-producing fecal coliforms with encoding genes were found;the CTX-M-1, CTX-M-9, TEM, and SHV groups were found to have survived in the final effluent to the river after sterilization with sodium hypochlorite.

Phosphorus Recovery as Struvite from the Supernatant of Anaerobic Digestion in Wastewater Treatment Plant

Phosphorus is an irreplaceable and depletable element. Furthermore, it has an almost one-way circulation on earth, so it is necessary to close the phosphorus cycle loop. Phosphorus could be recovered as struvite, which is a good slow-released fertilizer for agriculture. The supernatant of anaerobic digestion used to treat sludge from wastewater treatment plant is one main source from which phosphorus can be recovered. Studies have proven that phosphorus recovery from digester supematant is a feasible choice to preserve phosphorus rock technically and economically. A modified ＂PHOSNIX＂ P-recovery process was applied under the operating conditions of a 9.0 pH value and a 1.8 mg： P ratio with the influent of the centrate coming from the sludge centrifuge of the Songjiang Wastewater Treatment Plant in Shanghai. More than 80% influent phosphorus was recovered as struvite. Crystal products with good purity and low heavy metal content were gained. The largest crystal had a length of up to 0.26 mm. It was found in our study that the reaction time did not play an important role in crystal growth. Therefore, the optimization of the reaction condition for crystal growth should be examined in future study.

Environmental Assessment of AI-Hilla City Wastewater Treatment Plants

Iraq is one of the countries that is suffering from water shortage problems and, for this reason, wastewater treatment plants become a necessity to minimize this problem. In this study, the impact of A1-Hilla WWTP （wastewater treatment plant） on the environment has been studied. This was achieved using SimaPro software package. This software is a powerful tool for analyzing the environmental impact on products during their whole life cycle. A huge amount of knowledge about the environment is built into the program and database, enabling to analyze a product with a minimum of specialized knowledge. The results of LCA （life cycle assessment） showed that the impact and damage on the environment by A1-Hilla WWTP was 41 bad points for each 1 m3 of treated wastewater. The most environmental impacts potentially were global warming, respiratory inorganics and non-renewable energy. The study also showed that most of the effects were the result of the use of cement, steel and electricity consumption.

Examination of the Level of Heavy Metals in Wastewater of Bandar Abbas Wastewater Treatment Plant

One of the main environmental pollutants is heavy metals. Due to extensive usage in industry, these metals enter biological cycle rapidly and contaminated water and soil resources rapidly. In this work, lead, copper, zinc and chromium of Bandar Abbas wastewater are examined. For this research, nine stations were set for measurement in urban level in Bandar Abbas and sampling of aforesaid metals was performed in fall and winter 2006 in these stations. After extraction and preparation operations using APDC-MIBK, samples were measured using flame atomic absorption system. According to results, concentrate of studied metals was lower than allowable standard value set by Iran environmental protection organization for agricultural purposes and sewage to ground level waters. In addition, efficiency of Bandar Abbas wastewater treatment plant to remove these metals is 40% - 70% from which highest removal is for zinc as much as 71.1% and lowest level is for copper as much as 40.5%. However, copper level was higher than allowable level for agricultural purposes in spring and summer (0.21 mg/L and 0.23 mg/L, respectively) and lower in fall and winter (0.103 mg/L and 0.098 mg/L, respectively). Furthermore, changes in concentration of metals in these stations in various seasons were measured and analyzed using one-way variance analysis and simultaneous effects of time and place on measured variables were analyzed using two-way variance analysis.

Current Seasonal Variations in Physicochemical and Heavy Metals Parameters of Sewage Treatment Plant Effluent and Suitability for Irrigation

The study aims to investigate the current extent of physicochemical parameters and heavy metal contamination in the effluent of the Jaganpur sewage treatment plant (STP), Dayalbagh, Agra India. Majority of the nearby farmers have access to use of STP effluent in irrigation purposes for growing major edible crops. The problems of using STP effluent for irrigation purpose, continuous water quality analysis required. To check the quality of irrigation water, substantial physicochemical parameters accordance to Indian Standards (IS-Reaffirmed 2002/2003) analysed to calculate Sodium absorption ratio (SAR) and Residual sodium carbonate (RSC). To estimate the heavy metal pollution index (HPI) and metal quality index (MQI), toxic Heavy metals such as As, Cr, Mn, Fe, Ni, Cu, Zn, Pd, Cd, Co, and B also determined in the STP effluent with an AAS and results verified with ICP-OES against certified standards. The high value of SAR (range 13 to 20) and RSC (range -10 to 11) in STP effluent exceeded the permissible limit for irrigation purpose. On the other hand, HPI and MQI values (1692.4 and 58.1, respectively) show that high metal contamination mainly due to industrial and domestic wastewater does not treat appropriately in the sewage treatment plant. Thus it is suggested that further studies are carried out on the STP effluents to improve the water quality through proper treatment. Treated wastewater used for irrigation purposes needs to analyse the contamination like heavy metals and pinpoint the pollution sources.

Emergency management of reservoirs and water treatment plants in typhoon season:a case study of Ningbo

Coastal cities represented by Ningbo are directly or indirectly affected by typhoons each year. By analyzing the past three typical typhoons landing in Ningbo from 2013 to 2016, it was found that before and after the typhoon transit, reservoir and water treatment plant would be made by the destructive impact, including the increasing water level, water volume in a short time, and the deteriorating water quality. Among those, the water quality caused by typhoons increased the water treatment process load, the amount of water purification agents increased significantly,and the emergency response put a great pressure on the inventory of water plants. Based on the statistics and analysis of the basic parameters of the reservoir and water treatment plant during the typhoon season, the emergency management of the typhoon was divided into three situations, namely, pre-typhoon, typhoon period and post-typhoon. Thus, it is effective for the relevant practitioners of the reservoir and water plant to ensure the safe water supply during typhoon season.

Common effluent treatment plant(CETP):Reliability analysis and performance evaluation

Common effluent treatment plants(CETPs) have been installed and are in operation at numerous industrial clusters throughout India. They serve to reduce effluent treatment cost, provide better collective treatment, and reduce land cost for small-scale industrial facilities that cannot afford individual treatment plants. Optimum working conditions for treatment of effluent to be at par with discharge standards is a major mandate for any CETP. In this study, the reliability and removal efficiencies(REs) of a CETP in the industrial area of Maharashtra State in India were examined. An established methodology was adopted to determine the effectiveness of the CETP in terms of biochemical oxygen demand(BOD), chemical oxygen demand(COD), total suspended solids(TSS), and oil and grease(O&G) concentrations. The CETP's compliance with respect to design standards and its operation were studied in detail. This paper highlights the results of RE and the coefficient of determination(R2) values obtained from the CETP data, estimates the pollutants removed at the highest and lowest rates over a period of time, and highlights the reasons for problem areas along with remedial measures. It was observed that, except O&G, all the parameters(BOD, COD, and TSS)showed fluctuations in removal efficiencies and their reliabilities. This situation can be improved by releasing effluent containing hydraulic and organic loading to the CETP as per standards and optimizing treatment processes, especially primary clari-flocculators and aeration tanks, both of which are important units of any CETP.

Simulation of Low TDS and Biological Units of Fajr Industrial Wastewater Treatment Plant Using Artificial Neural Network and Principal Component Analysis Hybrid Method

Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.

Performance Simulation of H-TDS Unit of Fajr Industrial Wastewater Treatment Plant Using a Combination of Neural Network and Principal Component Analysis

Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems and environmental engineers are dealing with them mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant, powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr—Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. The results of this model showed good accuracy of the model in estimating qualitative pro- file of wastewater. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of output.