Efficiency Of Wastewater Treatment Plants Research Articles

Bio2Py: An API for integrating Python with BioWin for enhanced data acquisition in wastewater treatment simulations

Commercial simulators for modeling wastewater treatment processes (WWTPs), such as BioWin, play a crucial role for optimizing the design, operation, and control of treatment facilities. These simulators offer fast and user-friendly interfaces and can be employed to enhance the efficiency of wastewater treatment plants. However, a notable limitation of BioWin and similar platforms is the lack of direct integration with Python®, a programming language renowned for its versatility and extensive data analysis and machine learning libraries. Bridging this gap constitutes an opportunity to significantly improve the simulation process by leveraging Python's capabilities. The Python package Bio2Py (BioWin to Python) is presented as a compelling solution, reconciling BioWin's specialized functionality and Python's automation and data processing strengths. By utilizing Python's PyAutoGUI package, Bio2Py automates various aspects of the simulation process, such as loading influent data, running simulations, and saving simulation results without manual intervention. The integration of BioWin with Python not only speeds up the workflow by automating repetitive tasks but also opens new possibilities, such as parameter calibration for specific wastewaters and using BioWin as a data generator for machine learning applications. This brief communication presents the Bio2Py API, illustrating its use and applicability through a simple implementation example. Bio2Py's ability to automate and optimize various aspects of wastewater treatment process simulation, including data acquisition, and its potential use for process variable optimization and parameter tuning, positions it as a valuable tool for engineers and researchers who work in this field.

Enzyme_Metal-Organic Framework Composites as Novel Approach for Microplastic Degradation.

Plastic pollution is one of the main worldwide environmental concerns. Our lifestyle involves persistent plastic consumption, aggravating the low efficiency of wastewater treatment plants in its removal. Nano/microplastics are accumulated in living beings, pushing to identify new water remediation strategies to avoid their harmful effects. Enzymes (e.g.,Candida rugosa-CrL) are known natural plastic degraders as catalysts in depolymerization reactions. However, their practical use is limited by their stability, recyclability, and economical concerns. Here, enzyme immobilization in metal-organic frameworks (CrL_MOF) is originally presented as a new plastic degradation approach to achieve a boosted plastic decomposition in aqueous systems while allowing the catalyst cyclability. Bis-(hydroxyethyl)terephthalate (BHET) was selected as model substrate for decontamination experiments for being the main polyethylene terephthalate (PET) degradation product. Once in contaminated water, CrL_MOFs can eliminate BHET (37%, 24h), following two complementary mechanisms: enzymatic degradation (CrL action) and byproducts adsorption (MOF effect). As aproof-of-concept, the capacity of a selected CrL_MOF composite to eliminate the BHET degradation products and its reusability are also investigated. The potential of these systems is envisioned in terms of improving enzyme cyclability, reducing costs along with feasible co-adsorption of plastic byproducts and other harmful contaminants, to successfully remove themin a single step.

Performance assessment of Al-Rustumiah wastewater treatment plant using multivariate statistical technique

An attempt has been made to assess the performance of the third expansion of the Al-Rustamiya wastewater treatment plant (WWTP). This plant serves approximately 1,500,000 people in east Baghdad city, the capital of Iraq, and the increase of the population in this part of the city has reached about 4 million which led to deterioration in their effluents quality. Furthermore, the plant has no improvement on their processing units. Al-Rustamiya WWTP uses a biological water treatment method known as the activated sludge process with an average wastewater treatment of about 300 million liters. In the present paper, a wastewater quality data of ten years has been subjected to a multivariate statistical technique to identify the most important factors that affect the performance of the plant and estimating its efficiency. The data was collected and examined by the central laboratory of the Al-Rustamiya wastewater treatment plant in the mayoralty of Baghdad. Factor Analysis has been used to assess the important water quality parameters: pH, Total Suspended Solids, Biochemical Oxygen Demand (BOD), and Chemical Oxygen Demand (COD). The results revealed that the major factor that affects the performance is the organic load of raw wastewater and the removal efficiency of the WWTP. Furthermore, the results present that the performance of the current plant system is acceptable exclude for the removal efficiency of BOD below the prescribed limit. As well as, The BOD and COD correlation can evaluate wastewater treatment plant efficiency, aid in prompt intervention, and monitor harmful substances.

A review of microplastics in wastewater treatment plants in Türkiye: Characteristics, removal efficiency, mitigation strategies for microplastic pollution and future perspective

ABSTRACT The effluent of WWTPs is an important source of microplastics (MP) for the aquatic environment. In this review study, MPs in wastewater treatment plants (WWTP) in Türkiye and their removal from WWTPs are reviewed for the first time. First, MP characteristics in the influent and effluent of WWTPs in Türkiye are discussed. In the next section, the abundance of MPs in the influent and effluent of WWTPs in Türkiye and the MP removal efficiency of WWTPs in Türkiye are evaluated. Then, the results of studies on MP abundance and characteristics in Türkiye's aquatic environments are presented and suggestions are made to reduce MPs released from WWTPs into the receiving environments. Strategies for reducing MPs released to the receiving environment from WWTPs of Türkiye are summarized. In the last section, research gaps regarding MPs in WWTPs in Türkiye are identified and suggestions are made for future studies. This review paper provides a comprehensive assessment of the abundance, dominant characteristics, and removal of MPs in WWTPs in Türkiye, as well as the current status and deficiencies in Türkiye. Therefore, this review can serve as a scientific guide to improve the MP removal efficiency of WWTPs in Türkiye.

Evaluation of the Environmental Impact and Energy Utilization Efficiency of Wastewater Treatment Plants in Tumen River Basin Based on a Life Cycle Assessment + Data Envelopment Analysis Model

The environmental impacts from energy consumption account for a high percentage of the environmental impacts of wastewater treatment plants (WWTPs) throughout their life cycle; therefore, controlling energy use in WWTPs could bring substantial benefits to the environment. In this study, according to the different percentages of electricity generation from renewable energy compared to fossil energy, the global warming, acidification, eutrophication, human toxicity, and photochemical smog, the environmental impacts of WWTP operation were considered. Furthermore, to explore a more sustainable way of operating WWTPs under the “dual-carbon” strategic decision, the environmental impacts and energy utilization efficiency of different power allocation scenarios at present and in the next 40 years were compared based on the LCA+DEA integrated model. The study revealed that in scenarios 1–5, as the proportion of renewable energy power generation gradually increased, all LCA results showed a gradual decrease, of which GWP decreased by 83.32% and human toxicity decreased by 93.34%. However, in scenarios 2–5, the contribution ratio (proportion) of gas and electricity to GWP and POCP gradually increased, reaching 77.11% and 59.44%, respectively, in scenario 5. The contribution ratio (proportion) of biomass generation to AP and EP gradually increased as well, reaching 65.22% and 68.75%, respectively, in scenario 5. Meanwhile, the combined technical efficiency in energy utilization in the five scenarios showed a decreasing trend; only scenario 1 was fully efficient, and the combined efficiency was 1. The values of combined technical efficiency in scenarios 2, 3, 4, and 5 gradually decreased and were 0.7386, 0.4771, 0.2967, and 0.1673, respectively. This study discusses whether the use of renewable energy in place of fossil energy power elicits an environmental impact in WWTPs. We explore the feasibility of achieving energy savings and emission reductions in WWTPs within the Tumen River Basin, to provide a theoretical basis for their sustainable development.

Analysis of factors influencing the energy efficiency in Chinese wastewater treatment plants through machine learning and SHapley Additive exPlanations

Wastewater treatment plants (WWTPs) contribute significantly to the control of pollution in water. However, they are significant energy consumers. Identifying the factors influencing energy consumption is crucial for enhancing the energy efficiency of WWTPs. To address this, the unit energy consumption (UEC) of WWTPs was predicted using machine learning models. In order to accurately evaluate WWTPs' energy utilization efficiency, a comprehensive energy evaluation indicator, UEC (kWh/kg TODremoved) was utilized in this study. Among the prediction models, the eXtreme Gradient Boosting (XGBoost) achieves the highest prediction accuracy. SHapley Additive exPlanations (SHAP) was adopted as the model explanation system, and the results revealed that UEC was negatively affected by TN concentration, which was the most influential factor. The stoichiometry-based model calculation result indicates that the nitrification consumes average 77 % of the overall oxygen demand. SHAP analysis illustrated that the UEC of main technologies decreases with increasing influential factors. Partial dependence plot (PDP) compared average UEC of these technologies and SBR consumed the least amount of energy. The research also indicated that low influent TN concentration is the main problem in China. Consequently, it is imperative to exert efforts in ensuring the influent TN concentration while simultaneously making appropriate adjustments to the treatment process. This study provides valuable implications and methods for retrofitting and upgrading WWTPs.

Study of BOD: COD Ratio as an Indicator for Wastewater of Rubber Industry Sector

When considering the rubber industry sector, the most significant challenge is the efficient wastewater treatment before discharging it into the natural environment. The rubber industry is considered to be highly chemical and water-intensive: and involves enormous quantitative s of waste production. The ratio between Biological Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) is a widely used parameter in characterising wastewater and then the same was used in this study as an indication to measure the efficiency of wastewater treatment plant operated in the rubber industry sector. Data for the study was extracted from samples collected from 10 wastewater treatment plants of rubber industries in the Sabaragamuwa Province; two samples from each representing before and after treatment. The samples were tested in two replicated for BOD5, COD, pH, and conductivity. These selected rubber factories contain lagoon/pond type wastewater treatment systems or activated sludge wastewater treatment systems. The results showed that the treated wastewater samples were within the range of 0.1–0.4 of BOD5: COD and were below the BOD5: COD permissible level as per CEA standards. (General standards for rubber in inland surface waters; Latex-BOD 60, COD 400; Lanka rubber/crepe rubber–BOD 50, COD 400) comparing the BOD, COD, pH, and conductivity influent and effluent of the treatment process proves the effectiveness of each treatment plant of the relevant industry. Tested samples show a high BOD5: COD ratio in influent and effluent of wastewater treatment system indicate that wastewater of the industry is easily biodegradable. However, more research comparing the characteristics of different rubber manufacturing processes is needed to develop this approach further. 
 Keywords: BOD, COD, BOD: COD ratio, Wastewater treatment plant

Aquifer contamination and efficiency of wastewater treatment plants in urban centers of Itapúa, Paraguay

La investigación analiza la calidad del agua subterránea y la eficacia del funcionamiento de dos plantas de tratamiento de efluentes domiciliarios en dos centros urbanos de Paraguay, así como la presencia de metales pesados en lodos residuales de ambas plantas de tratamiento. Para analizar la calidad del agua subterránea se recabaron datos de 59 muestreos de agua de 17 pozos profundos obtenidos en un periodo de 10 años entre el 2006 y el 2016. Para la evaluación del funcionamiento de las plantas de tratamiento se determinó la calidad de los efluentes luego del proceso de depuración. En los lodos generados en ambas plantas se analizó la presencia de metales pesados (Pb, Cr total, Cd y Hg). Los resultados obtenidos fueron contrastados con legislaciones nacionales e internacionales vigentes. Los datos cuantitativos fueron procesados estadísticamente mediante análisis de varianza y contraste de medias (Test de Duncan) con margen de error 5 %. Los principales resultados indican contaminación microbiológica del agua subterránea (acuífero Guaraní). Sin embargo, los parámetros físico-químicos analizados estaban dentro de los rangos establecidos por las normativas vigentes. Se identificó una inadecuada gestión en la planta de tratamiento de aguas residuales en uno de los centros urbanos (Hohenau). Se detectó presencia de Pb, Cr y Hg, a pesar de que las concentraciones se mantuvieron dentro de los rangos permisibles. Para salvaguardar la salud pública y el ambiente, tanto a nivel local como regional, es imperativo aplicar plenamente el marco legal y la implementación de la Gestión Integrada de los Recursos Hídricos.

Catalysing water treatments: A Comprehensive Examination of sludge, its treatment and Energy Valorisation Solutions

The escalating production of sewage sludge in WasteWater Treatment Plant (WWTP) due to urban population growth and its management poses a substantial risk to the energetic and environmental efficiency of WWTP. This paper aims to explore the potential for sludge as a renewable energy source to reduce reliance on traditional energy through a systematic literature review of peer-reviewed articles and case studies. This overview demonstrated that various treatment methods such as anaerobic digestion, incineration, gasification, and pyrolysis are the most used and the most promising in terms of their energy outputs and effectiveness. The paper discussed the complexity of sludge composition, its financial burden on WWTP, and the crucial role in the success of these systems. Moreover, a comparative analysis of the different valorisation techniques was conducted that highlighted the energy production potential existing within each method and its underlying constraints while emphasising on the proper sludge management for overall efficiency. Finally, this paper recommended the need for sustainable, cost-effective approaches, considering legal standards for efficient WWTP.

Pathogenic potential of enterococcus isolated from healthy people and wastewater

Introduction. Efficiency of wastewater treatment plants is a key for protection of common health. At the same time, all criteria for its evaluation are concerned about the overall biomass reduction rather than on pathogens that, in low amount, can still be present in the efflux. 
 Purpose of the study. Therefore it seems important to evaluate the effect of purification procedures on the pathogenic potential of bacteria. In the current study, it is performed using Enterococcus isolates, since pathogenic strains present considerable threat for human health, causing endocarditis, infections of urogenic tract, nosocomial infections, etc. 
 Materials and methods. PCR was used to evaluate the presence of potentially pathogenic genes in the extracted DNA. Seven genes were tested: genes of adhesion proteins (Esp, Asa1), proteins with lytic activity (cytolysine CylA, hyaluronidase hyl and gelatinase gelE), and antibiotic resistance factors (vanA, vanB). Three hundred sixty six isolates from wastewater plants of Moscow agglomeration and 168 from feces of healthy people were screened. 
 Results. Percentage of pathogenic isolates varied in different wastewater treatment plants (from 36 to 55%), with no relation with the volumes of treated sewage and the purification scheme of the plant. Similar species were recovered from wastewater plants and feces, with E. faecium (36% and 53%, correspondingly) and E. faecalis (28% and 38%) as most abundant. E. hirae was presented in different numbers (24% и 1.2%) as well as E. casseliflavus (3% and 0,6%). 
 E. durans, E. thailandicus, E. avium, E. mundtii were found from 2.5 to 1%, in similar amounts from both sources. Minor species E. raffinosus, E. moraviensis, E. malodatus presented with single isolates in wastewater plants, and E. canintеstini – in feces. The E. faecalis was the leader in percentage of pathogenic potential (75–80%). The most abundant pathogenic gene was gelE (30–33% from both sources) and asa1 (18–19%). CylA was found at similar levels 
 (4,4–4,8%). Esp was found in 9% of wastewater plants isolates and in 14% from feces. Hyl was specific to isolates from wastewater plants (2,5%), and was present in all non-monor species (E. faecium, E. faecalis, E. hirae, E. durans, E. thailandicus) and at different stages of water treatment. Vancomycin resistance genes were not detected.
 Limitations. When studying the pathogenic potential of enterococcal isolates from wastewater treatment plants in the city of Moscow and the Moscow region and the feces of practically healthy people, two samples were compared, consisting of 366 and 168 isolates, respectively, which represents a sufficient reference sample. The sample was limited by geography, so the conclusions can be applied to wastewater treatment plants in the city of Moscow and the Moscow region, where similar treatment schemes were used.
 Conclusions. The data from this study suggests the pathogenic potential of bacteria from wastewater treatment plants to be a little bit more than that of isolates from feces of healthy people. The activated sludge can be a reservoir for pathogens and can bring contamination to the environment.

Modeling spatiotemporal domestic wastewater variability: Implications for measuring treatment efficiency

Continuously measuring the efficiency of wastewater treatment plants is crucial to progress in sanitation management. Regulations for decentralized wastewater treatment plants (WWTP) can include rudimentary specifications for sporadic sampling, unencouraging continuous monitoring, and missing crucial domestic wastewater (DW) variability, especially in low- and middle-income countries. However, few studies have focused on modeling and understanding spatiotemporal DW variability. We developed and calibrated an agent-based model (ABM) to understand spatial and temporal DW variability, its role in estimated WWTP efficiency, and provide recommendations to improve sampling regulations. We simulated DW variability at various spatial and temporal resolutions in Santa Ana Atzcapotzaltongo, Mexico, focusing on chemical oxygen demand (COD) and total suspended solids (TSS). The model results show that DW variability increases at higher spatiotemporal resolutions. Without a proper understanding of DW variability, treatment efficiency can be overestimated or underestimated by as much as 25% from sporadic sampling. Sensor measurements at 6-min intervals over 3 hours are recommended to overcome uncertainty resulting from temporal variability during heavy drinking water demand in the morning. Reporting of sewage catchment areas, population sizes, and sampling times and intervals is recommended to compare WWTP efficiencies to overcome uncertainty resulting from spatiotemporal variability. The proposed model is a useful tool for understanding DW variability. It can be used to estimate the impact of spatiotemporal variability when measuring WWTP efficiencies, support improvements to sampling regulations for decentralized sanitation, and alternatively for designing and operating WWTPs.

Machine learning modeling for the prediction of phosphorus and nitrogen removal efficiency and screening of crucial microorganisms in wastewater treatment plants

The effectiveness of wastewater treatment plants (WWTPs) is largely determined by the microbial community structure in their activated sludge (AS). Interactions among microbial communities in AS systems and their indirect effects on water quality changes are crucial for WWTP performance. However, there is currently no quantitative method to evaluate the contribution of microorganisms to the operating efficiency of WWTPs. Traditional assessments of WWTP performance are limited by experimental conditions, methods, and other factors, resulting in increased costs and experimental pollutants. Therefore, an effective method is needed to predict WWTP efficiency based on AS community structure and quantitatively evaluate the contribution of microorganisms in the AS system. This study evaluated and compared microbial communities and water quality changes from WWTPs worldwide by meta-analysis of published high-throughput sequencing data. Six machine learning (ML) models were utilized to predict the efficiency of phosphorus and nitrogen removal in WWTPs; among them, XGBoost showed the highest prediction accuracy. Cross-entropy was used to screen the crucial microorganisms related to phosphorus and nitrogen removal efficiency, and the modeling confirmed the reasonableness of the results. Thirteen genera with nitrogen and phosphorus cycling pathways obtained from the screening were considered highly appropriate for the simultaneous removal of phosphorus and nitrogen. The results showed that the microbes Haliangium, Vicinamibacteraceae, Tolumonas, and SWB02 are potentially crucial for phosphorus and nitrogen removal, as they may be involved in the process of phosphorus and nitrogen removal in sewage treatment plants. Overall, these findings have deepened our understanding of the relationship between microbial community structure and performance of WWTPs, indicating that microbial data should play a critical role in the future design of sewage treatment plants. The ML model of this study can efficiently screen crucial microbes associated with WWTP system performance, and it is promising for the discovery of potential microbial metabolic pathways.

Characteristics of dissolved organic matter in point-source wastewaters at a petrochemical plant: Molecular constituents and contributions to the influent of wastewater treatment plant

Dissolved organic matter (DOM) in point-source petrochemical wastewaters (PCWs) from different operating units is closely linked to the efficiency of wastewater treatment plant (WWTP). However, systematic studies on DOM characters of point-source PCWs and their influences on WWTP influents were seldom conducted. In this study, DOM in three low-salinity point-source PCWs and four high-salinity point-source PCWs at a typical petrochemical plant were comprehensively characterized at a molecular level. Orbitrap mass spectrometry results indicated that point-source PCWs had diverse DOM constituents tightly related to the corresponding petrochemical processes. Phenols in oily wastewaters (OW), phenols and N-containing compounds in coal partial oxidation wastewater (POXW), and naphthenic acids (NAs) and aromatic acids in crude oil electric desalting unit wastewater (EDW) were characteristic DOM constituents for low-salinity point-source PCWs. While S-containing compounds (mercaptans, thiophenes) and NAs in spent caustic liquors (SCL), alcohols and esters in butanol-octanol plant wastewater (BOW), high molecular weight aromatic ketones in phenol-acetone plant wastewater (PAW), and oxygenated NAs as well as short chain N-containing compounds in concentrate from reverse osmosis unit (ROC) were characteristic DOM constituents for high-salinity point-source PCWs. Spearman correlation analysis indicated that though with relative low pollutant contents (OW) and discharge volume (EDW), N/O/S-containing compounds of OW and EDW greatly contributed to the polar DOM constituents of low-salinity influent in WWTP (R > 0.5, P < 0.001). While N-containing compounds of ROC mainly contributed to the polar DOM of high-salinity influent (R > 0.5, P < 0.001). Though N-/S-containing species in PAW had low contents, they also posed obvious impacts on DOM constituents of high-salinity influent. Interestingly, some O-/S-containing species were newly formed during the confluent process of high-salinity point-source PCWs. The results strengthened the combined contributions of pollutants contents, discharge emission and DOM constituents of point-source PCWs to the water matrix of WWTP influents, which would provide reference for the management of PCW streams.

An Assessment of Irrigation Water Quality with Respect to the Reuse of Treated Wastewater in Al-Ahsa Oasis, Saudi Arabia

Irrigation water quality is important to sustain agricultural productivity. The primary irrigation water sources in Al-Ahsa Oasis, KSA, are groundwater wells, mixed with treated wastewater and agricultural drainage. This study sought to evaluate irrigation water quality in Al-Ahsa Oasis with the aid of using irrigation water quality indices (IWQIs). One hundred and forty-eight different water samples were collected from various irrigation water resources throughout Al-Ahsa Oasis. The investigated physiochemical characteristics include pH, temperature, TDS, EC, turbidity, free chlorine, total hardness, cations (Na, K, Ca, Mg), anions (Cl, CO3, HCO3, SO4), organic matter indices (DO, BOD, COD), and nutrients (NH4, NO3, PO4). The IWQIs used in this study include salinity hazard, sodium adsorption ratio (SAR), Kelly’s ratio (KR), soluble sodium percentage (SSP), Permeability index (PI), residual sodium carbonate (RSC), and magnesium hazard (MH). The results indicated that treated wastewater mixed with groundwater is acceptable for irrigation. Spatial variations in irrigation water quality throughout Al-Ahsa are associated with water resources. For instance, groundwater mixed with agricultural drainage has the highest values of TDS, cations, and anions, whereas the lowest values were reported for treated wastewater, reflecting the good efficiency of wastewater treatment plants. The IWQI results revealed that 4.1% and 62.1% of the investigated irrigation water samples were considered good (class III) and satisfactory (class IV) for irrigation, respectively, whereas 33.8% of the collected water samples fall within the severe irrigation restrictions. Moreover, 79.7% of the investigated water samples were classified to have high to very high salinity hazards (C3, C4) and medium to high sodium hazards (S2, S3). Regular monitoring and assessment of treated water quality and wastewater treatment plant efficiency are important factors in achieving the sustainability of treated wastewater reuse in irrigation and consequently food security.

Searching for pharmaceutically active products and metabolites in environmental waters of Peru by HRMS-based screening: Proposal for future monitoring and environmental risk assessment

The presence of pharmaceutical active products (PhACs) in the aquatic environment is a matter of current concern, and there is an increasing trend to include these compounds in water quality monitoring programs and environmental risk assessments. Several studies have reported the presence of PhACs in environmental waters worldwide, but only a few studies have focused on Latin American countries. Thus, available information on the occurrence of parent pharmaceuticals, especially their metabolites, is very scarce. Peru is one of the less monitored countries in terms of contaminants of emerging concern (CECs) in waters, and only one study has been found, which was focused on the quantification of selected PhACs in urban wastewater and surface water. The aim of this work is to complement the previous data reported on PhACs in the aquatic environment by application of a wide-scope high-resolution (HRMS)-based screening, making use of target and suspect approaches. In the present work, 30 pharmaceuticals, drugs or other compounds (sweeteners, UV filters, etc.) and 21 metabolites have been identified, with antibiotics (and metabolites) being the most prevalent compounds. The use of liquid chromatography (LC) coupled to ion mobility-HRMS allowed the tentative identification of parent compounds and metabolites, for which the analytical reference standard was not available, with a high level of confidence in their identification. Based on the results obtained, a strategy for the monitoring of PhACs and relevant metabolites in environmental waters from Peru and for subsequent risk assessment is proposed. Our data will also help to focus future studies to evaluate the removal efficiency of wastewater treatment plants and the impact of treated water in receiving water bodies.

Tracing the fate of microplastic in wastewater treatment plant: A multi-stage analysis of treatment units and sludge

Microplastic (MP) pollution is ubiquitous in the environment presenting a global problem for both scientists and the general public. One of the major pathways of MPs entering the natural environment is through wastewater treatment plants (WWTPs). Once MPs reach the natural environment, they are posing threat to aquatic ecosystems and public health. The aim of this study is to investigate the concentration, morphology, and composition of MPs in different treatment units of a WWTP. Sampling included different points across WWTP in the water and sludge lines. Pre-treatment of the samples consists of advanced Fenton oxidation, and alkaline and enzymatic digestion followed by density separation. Once the particles were isolated, their morphology and size were studied using a stereoscopic and optical microscope followed by final confirmation with ATR-FTIR and micro-FTIR spectroscopy. Microplastic particle concentrations exhibit significant reductions as water undergoes treatment in the WWTP. For summer sampling, concentrations decreased from 351 MP/L (influent) to 35 MP/L (primary clarifier), 32 MP/L (biological reactor), and 13 MP/L (2.3 MP/L) (secondary clarifier). Similarly, winter sampling showed reductions from 403 MP/L (influent) to 159 MP/L (primary clarifier), 178 MP/L (biological reactor), and 26 MP/L (5.6 MP/L) (secondary clarifier). Removal efficiency of WWTP is high and exceeds 96%. The most abundant morphology is fibers followed by fragments and films. Polymers such as PE, synthetic cellulose, PP, PVC, PE-PP, PEEA, PA, acrylamide, and PES are widely detected in different units of WWTP. The number of MPs that are avoided from being emitted into the environment through direct water discharge was estimated to be 9.1 × 1012 MP/year. Removed MPs tend to accumulate in the sludge that is used for agricultural purposes although it should be managed as waste properly, avoiding the transition of MPs pollutants to terrestrial ecosystems adding to the number of MPs that will inevitably end up in receiving water bodies through direct WWTP effluent discharge that was set in 5.1 × 1010 MP/year in the studied WWTP.

Assessment of the Efficiency of Wastewater Treatment Plant in Oil and Gas Firm in Eleme Rivers State, Nigeria

The study aimed to determine the efficiency of a wastewater treatment plant and the quality of effluent discharged by the plant into the receiving water body (Okochiri River) in Eleme, Rivers State. The study lasted for four months. Wastewater samples were collected at various stages of the treatment unit and tested for major water quality parameter such as Biological Oxygen Demand (BOD), oil/grease, phenol, Dissolved Oxygen (DO), Total Suspended Solids (TSS), and sulphide. In general, the composite wastewater treatment system (comprising dissolve air floatation, Rotary Bio-Disk, and sedimentation unit) was effective in pollutant removal, except for sulphide, which had a negative efficiency (-238%). In line with Pearson Correlation, there are strong positive relationships between several parameters, such as pH and Sulphide (0.93), Phenol and Oil/grease (1.00), and Phosphate and Sulphide (0.91). The Principal Component Analysis yielded four principal components (PC1-4): PC1 parameters with the highest loadings on the first factor (D1) were sulphates and phenols, whereas Chemical Oxygen Demand and Biological Oxygen Demand had the highest loadings on the second factor (D2). Dissolved oxygen was most strongly associated with the third factor (D3), and pH was the parameter with the highest loading on the fourth factor (D4). It is recommended that the wastewater treatment system's overall efficiency be improved for the system to consistently meet regulatory limits for pollutant control. Recommendations for improving system efficiency include (1) ensuring regular maintenance of individual units in the treatment plant; and (2) maintaining optimal operating conditions for the rotary bio-disk unit.

Carbon emission efficiency evaluation of wastewater treatment plants: evidence from China.

A scientific evaluation of the carbon emission efficiency is crucial for ensuring the sustainable development of wastewater treatment plants (WWTPs). In this paper, we applied a non-radial data envelopment analysis (DEA) model to calculate the carbon emission efficiency of 225 WWTPs located in China.The results showed that the average carbon emission efficiency of China's WWTPs was 0.59, indicating that the efficiencies of most samples still require improvement. The carbon emission efficiency of WWTPs from 2015 to 2017 decreased because of the decrease in technology efficiency. Among the influencing factors, different treating scales had positive impact on carbon emission efficiency improvement. WWTPs with anaerobic oxic process and the first-class A standard were likely to have higher carbon emission efficiency in the 225 WWTPs. By incorporating direct and indirect carbon emissions into WWTP efficiency evaluation, this study helped decision-makers and related water authorities to better understand the contribution of WWTPs to the aquatic and atmospheric environments.

Development of IoT-Based Real-Time Monitoring System and LFA to Improve the Efficiency and Performance of Wastewater Treatment Plant in Udayana University Hospital

Indonesia is one of the countries infected by the Coronavirus Disease 2019 (COVID-19) pandemic, which is caused by acute respiratory syndrome virus 2 (SARS-CoV-2). At the end of March 2020, the provincial government of Bali appointed Udayana University Hospital to handle COVID-19 patients because the province has experienced an increase in the number of positive cases. In September 2020, COVID-19 cases in Bali increased by more than 100%, resulting in a higher volume and content of hazardous liquid waste. Furthermore, hazardous liquid waste is the residue of activities that contain substances that can pollute and damage the environment and health, necessitating more efforts in managing the processing of hazardous wastewater produced by the hospital. Based on the background above, this study developed and applied an Internet of Things (IoT) based monitoring system to the Wastewater Treatment Plant (WWTP) in Udayana University Hospital. In principle, the IoT system can be used as a real-time monitoring tool and minimizes direct contact activities of officers’ WWTP sites. Moreover, the Liquid Film Aerator (LFA) was applied to improve the efficiency of WWTP. The developed IoT system successfully monitors pH, DO, and real-time temperature, and the monitoring results were presented in a web-based user interface. The result shows better power usage efficiency than conventional aeration. Furthermore, conventional aeration with a root blower requires 619.8 watts to produce 1 mg/L of DO, while LFA only requires 273.2 watts. The developed systems can be applied to other hospitals or similar wastewater plants that handle COVID-19 cases.

A comprehensive assessment of energy efficiency of wastewater treatment plants: An efficiency analysis tree approach

Wastewater treatment plants (WWTPs) are energy intensive facilities. Controlling energy use in WWTPs could bring substantial benefits to people and environment. Understanding how energy efficient the wastewater treatment process is and what drives efficiency would allow treating wastewater in a more sustainable way. In this study, we employed the efficiency analysis trees approach, that combines machine learning and linear programming techniques, to estimate energy efficiency of wastewater treatment process. The findings indicated that considerable energy inefficiency among WWTPs in Chile existed. The mean energy efficiency was 0.287 suggesting that energy use should cut reduce by 71.3 % to treat the same volume of wastewater. This was equivalent to a reduction in energy use by 0.40 kWh/m3 on average. Moreover, only 4 out of 203 assessed WWTPs (1.97 %) were identified as energy efficient. It was also found that the age of treatment plant and type of secondary technology played an important role in explaining energy efficiency variations among WWTPs.