Operation Of Treatment Plants Research Articles

Comparison of statistical evaluation approaches for log-removal validation according to European water reuse regulations.

In 2020, the European Union published ordinance EU 2020/741, establishing minimum requirements for water reuse in agriculture. The ordinance differentiates between several water quality classes. For the highest water quality class (Class A), the ordinance mandates analytical validation of the treatment performance of new water reuse treatment plants (WRTP) related to the removal of microbial indicators for viral, bacterial, and parasitic pathogens. While the ordinance clearly defines the numeric target values for the required log10-reduction values (LRV), it provides limited to no guidance on the necessary sample sizes and statistical evaluation approaches. The main requirement is that at least 90% of the validation samples should meet the requirements. However, the interpretation of this 90% validation target can significantly impact the required sample size, efforts necessary, and the risk of misclassifying WRTPs in practice. The present study compares different statistical evaluation approaches that might be considered applicable for LRV validation monitoring. Special emphasis is placed on the use of tolerance intervals, which combine percentile estimations with sample size-based uncertainty and confidence regions. Tolerance interval-based approaches are compared with alternative methods, including a) a binomial evaluation and b) the calculation of empirical percentiles. The latter are already used in existing European and U.S. regulations for bathing water and irrigation water quality. Our study demonstrates that using tolerance intervals allows for the reliable validation of WRTPs that achieve high LRVs relative to regulatory targets with comparatively smaller sample sizes compared to the other two approaches, while reducing the risk of misclassification. Additionally, we show that simplified approaches, such as a "9 out of 10" approach, pose a substantial risk of misclassification and should not be applied. We illustrate the behavior of these different approaches through simulation experiments and application to real data collected in 2022 and 2023 at a large WRTP in Germany.

Coupling Driving Force–Pressure–State–Impact–Response–Management Framework with Hydrochemical Data for Groundwater Management on Sithonia Peninsula, Greece

Water scarcity in coastal tourist areas constitutes a critical environmental and socioeconomic sustainability issue. Hence, it is crucial to implement an integrated water resource management and protection plan. In this research, the DPSIR framework is coupled with hydrochemical data on groundwater resources in the fractured aquifer of the Sithonia Peninsula in Chalkidiki, North Greece. Geographical and demographic data, together with morphology, geology, hydrology, and groundwater quality data, were collected and evaluated to categorize the hydrosystem’s driving forces, pressures, states, impacts, and responses. The main pressures that affect groundwater quality in the study area are tourism, geological formation, and land use. Based on the analysis of the DPSIR framework, the absence of a landfill site, the inadequate operation of sewage treatment plants and biological wastewater treatment systems, and tourist activity contribute significantly to the degradation of groundwater quality. Additionally, the fractured rock aquifer develops preferential flow paths to pollutants through preexisting faults, which influence groundwater quality. The hydrochemical analysis of groundwater indicates seawater intrusion in the coastal area. The combination of DPSIR analysis and a water quality index based on ion ratios of groundwater samples identifies high-risk areas of seawater intrusion. Thus, it is essential to reinforce groundwater resources by implementing managed aquifer recharge, limiting unnecessary use of groundwater during the tourist season, and storing surface water during the wet period.

Machine learning application in municipal wastewater treatment to enhance the performance of a sequencing batch reactor wastewater treatment plant

An ML model optimized the performance of an SBR WWTP when applied to OSL scenarios, ensuring regulatory compliance.

Analysis and Optimization of Hydraulic Calibration for Maximum Performance of Wastewater Treatment Plants

The hydraulic calibration of treatment units in wastewater treatment plants is a crucial task. It involves demonstrating the relative placement of these various units in relation to the water line that traverses the plant, and helps indicate the ground surface for establishing the optimal elevations of the plant's structures and hydraulic controls. This process is meticulous, complex, and prone to errors. Special attention must be given to the issue of varying hydraulic loads that the plant will receive, particularly at the inlet. Such variations can disrupt hydraulic operation and negatively impact the plant's performance. For these reasons, the hydraulic calibration of treatment units must always be verified and analyzed for most of the common hydraulic constraints encountered in practice. This article focuses on the different types of flow and their regimes commonly found in wastewater treatment plants, and aims to guide users on how to optimize the hydraulic profile. It highlights the impact of head losses and integrates a range of potential alternatives for achieving hydraulic efficiency in a wastewater treatment plant.

Assessment of Wastewater Treatment Plants (WWTPs) Performance in El-Sharkia, Egypt

Assessment of Wastewater Treatment Plants (WWTPs) Performance in El-Sharkia, Egypt

Real-Time Determination of Total Suspended Solids in Activated Sludge’s Carousel Using a Single Emitter Ultrasonic Sensor

Sludge management is a very relevant aspect in the operation of Wastewater Treatment Plants (WWTPs). In activated sludge systems, it is common to have daily (or continuous) monitoring of total suspended solids in the aeration tank (MLSS). If such control is not properly performed, it can cause solids to wash out in the secondary sedimentation tank or significantly impact BOD (Biochemical Oxygen Demand) and nitrogen removal. There are many commercially available systems which can provide real-time monitoring of solids (mainly optical or ultrasound sensors). Even though commercially available (usually with a high cost), there are still issues related to the use of such sensors. The most important one is the progressive accumulation of solids, which cause measurement errors. In this work, the authors investigated the application of a low-cost US sensor for MLSS (mixed-liquor suspended solids) monitoring in two full-scale activated sludge WWTPs. The tested sensor was similar to a previously described device, which had been previously employed in a pilot-scale UASB reactor in Brazil. The main differences were related to an integrated treatment and acquisition system which allowed real-time treatment of the US wave as well as data acquisition at a predefined time. The values generated by the sensor were compared with a commercial optical sensor installed in the same WWTP and double-checked with periodic gravimetric tests. The results at a Leeuwarden WWTP showed that the measurements of the US sensor, the optical sensor, and gravimetric test did not present significant differences during the test period at a significance level of 5%. Absolute errors were on average 0.04% (US sensor) and 0.03% (optic sensor) of MLSS compared to the gravimetric test. Although the use of the tested US sensor for monitoring solids in WWTP is promising, there are still several improvements that need to be made to the sensor. These include implementing a more precise calibration frequency, establishing a cleaning routine, and preventing sensor fouling. Furthermore, the sensor still needs a more thorough cost–benefit analysis, which would help assess the practicality of implementing this technology in various WWTPs.

The Impact of Seasonal Variations in Rainfall and Temperature on the Performance of Wastewater Treatment Plant in the Context of Environmental Protection of Lake Como, a Tourist Region in Italy

This study investigates the impact of extreme weather conditions on the performance of a wastewater treatment plant (WWTP) in Como, Italy, in terms of influent (inf) and effluent (eff) quality parameters. During winter (October–December), the average temperature was 8.76 °C ± 11.43 °C, with 7.01 mm rainfall, while summer (May–September) averaged 23.24 °C ± 6.2 °C with 5.2 mm rainfall. Despite seasonal variations, the pH levels remained consistent. Phosphorus removal by the WWTP was efficient, with the winter influent averaging 4.16 ± 5.53 mg/L, the winter effluent averaging 0.33 ± 1.06 mg/L, the summer influent averaging 3.53 ± 2.9 mg/L, and the summer effluent averaging 0.31 ± 0.75 mg/L. The COD and BOD5 levels showed seasonal trends, with a higher winter-influent COD (450.43 ± 560.56 mg/L) than in summer (410.96 ± 302 mg/L). These higher winter values of effluent may be due to lower biological activity at cooler temperatures, affecting the efficiency of organic matter breakdown and treatment. The winter influent BOD averaged 249.57 ± 220.42 mg/L, with the winter effluent being 2.95 ± 2.04 mg/L, while the summer influent BOD was 214.44 ± 345.5 mg/L and the summer effluent was 3.01 ± 7.5 mg/L. The TSSs and Total-N showed similar seasonal patterns, with there being slight decreases in the TSSs removal efficiency during warmer months. Although microplastic pollution was not directly analyzed in this study, wastewater treatment plants play a crucial role in mitigating microplastic contamination. Despite rainfall influencing the phosphorus and organic load concentrations, the studied plant maintained over 90% pollutant removal efficiency, demonstrating resilience and compliance with regulatory standards. The WWTP’s consistent COD and BOD5 reductions highlight its robust performance amid climate variations

Analysis of domestic wastewater disinfection methods using chlorine dioxide and sodium hypochlorite

Pollution of surface water bodies poses a threat to the environment and human health. After improper wastewater treatment at municipal enterprises, mineral and organic pollutants gradually accumulate in water bodies, which in turn worsens the ecological situation and leads to outbreaks of infectious diseases. The reason for periodic violations of the operation of treatment plants is the imperfection of the technological regime. Therefore, there is an urgent need to improve the efficiency of existing biological treatment facilities by means of measures that ensure compliance with environmental requirements for urban wastewater treatment. Chlorine or its compounds are used as disinfectants: chlorine dioxide, sodium hypochlorite, calcium hypochlorite and others. Methods of wastewater disinfection using chlorine dioxide and sodium hypochlorite are considered in the work. The main advantages and problems of using these methods in comparison with the traditional use of chlorine are highlighted.

Effect of Differentially Charged Polystyrene Nanoplastics on the Performance of Biological Denitrification in Wastewater Treatment

Nanoplastics are widely distributed in the environment and can accumulate in organisms. Increasing attention has been paid to the toxic effects of nanoplastics in wastewater biological treatment processes. In this study, polystyrene nanoplastics with different charges were synthesized and used in sequencing batch activated sludge reactors for short-term nanoplastic exposure experiments. Both positively and negatively charged nanoplastics inhibited the nitrogen removal efficiency and gene expressions of nitrification and denitrification-related genes of activated sludge. The inhibiting effect on nitrification of both nanoplastics was enhanced with increasing concentration. The study further evaluated the molecular mechanisms by which differently charged nanoplastics affect denitrification efficiency using the model denitrifying bacterium Pseudomonas stutzeri （P. stutzeri）. The results showed that both positively and negatively charged nanoplastics affected the efficiency of biological denitrification by P. stutzeri, mainly including the promotion of NO3- to NO2- conversion and the significant acceleration of N2O production. Meanwhile, negatively charged nanoplastics inhibited the growth of P. stutzeri and disrupted the cell membrane of the bacterium； however, no change was observed in the expression of denitrification-related functional genes and the nanoplastics might have affected the enzymatic activities of Nir and Nos, which in turn affected the bioprocessing efficiency. This study can provide a certain reference for the evaluation of the biosafety of nanoplastics and provide a certain support for the stable operation of wastewater treatment plants.

Investigation of the Origin of Elevated Amounts of Iron and Manganese in a Dam Reservoir

On the outskirts of the Pinios dam reservoir (Ilia Regional Unit, Greece), a water treatment plant serves the water supply needs of the surrounding municipalities, in which high concentrations of Fe and Mn, before treatment, have been observed. The main purpose of this research was to investigate the mechanism of increased iron (Fe) and manganese (Mn) levels in the reservoir of the Pinios dam, which impacts its water treatment plant operation. A wide range of hydrochemical and sedimentological analyses were conducted over a hydrological year, focusing on the spatial and temporal distribution of Fe and Mn in both water and sediment samples across the established research monitoring stations. Sediment samples from the reservoir’s bottom revealed predominantly fine-grained material, rich in total organic carbon, with elevated Mn and Fe oxide levels. Significant seasonal variations in Fe and Mn levels were also discovered, with higher Mn levels observed in the anoxic bottom waters of the reservoir during the dry season, attributed to the reduced conditions favoring Mn oxide dissolution over Fe. Conversely, during the wet season, a homogenization of metal concentrations throughout the water column was observed due to increased oxygenation and freshwater inflow. These outcomes were confirmed by the hydrochemical analysis, indicating that the redox conditions, pH, and temperature, as well as the presence of organic matter, significantly influence the mobility and bioavailability of these metals in the reservoir. The findings of this study clarify that the high concentration of Fe and Mn can be linked to the mineral composition of the upstream Neogene and flysch formations in the study area. As these formations are affected by geological weathering, they tend to enrich the streams, through soil erosion and runoff processes, with metals like Fe and Mn, which are eventually transported into the dam reservoir. This study highlights the critical influence of lithological, sedimentological, and hydrological factors on the redox conditions and seasonal stratification that govern the behavior of Fe and Mn concentrations and mobility in dam reservoirs. These findings are critical for informing water resource management practices and dam infrastructure operators and developing effective environmental conservation strategies in similar cases.

Hybrid data driven approach based on ANNs-PCA for wastewater treatment plant performance assessment

In this paper, a data driven method to assess and predict performance of full scale urban activated sludge wastewater treatment plant (WWTP) is presented. The proposed hybrid approach consists of a combination of artificial neural networks (ANNs) and principal component analysis (PCA). Measurement results of a municipal activated sludge WWTP operation of 1.3 million inhabitant equivalents are presented and discussed. In ANNs PCA design, the ANNs used to calculate a nonlinear and dynamic model of the processes under normal operating conditions. Besides, PCA is used to generate monitoring charts based on all measured parameters. Results highlight that ANNs-PCA monitoring is crucial tool that can be used to optimize and predict process spatiotemporal evaluation. This research results provide a practical strategy for improving operation, management and performance prediction of studied WWTP. This supports Sustainable Development Goal (SDG) 6: Clean Water and Sanitation and worldwide sustainability actions and efforts.

A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants.

The precise detection of effluent biological oxygen demand (BOD) is crucial for the stable operation of wastewater treatment plants (WWTPs). However, existing detection methods struggle to meet the evolving drainage standards and management requirements. To address this issue, this paper proposed a multivariable probability density-based auto-reconstruction bidirectional long short-term memory (MPDAR-Bi-LSTM) soft sensor for predicting effluent BOD, enhancing the prediction accuracy and efficiency. Firstly, the selection of appropriate auxiliary variables for soft-sensor modeling is determined through the calculation of k-nearest-neighbor mutual information (KNN-MI) values between the global process variables and effluent BOD. Subsequently, considering the existence of strong interactions among different reaction tanks, a Bi-LSTM neural network prediction model is constructed with historical data. Then, a multivariate probability density-based auto-reconstruction (MPDAR) strategy is developed for adaptive updating of the prediction model, thereby enhancing its robustness. Finally, the effectiveness of the proposed soft sensor is demonstrated through experiments using the dataset from Benchmark Simulation Model No.1 (BSM1). The experimental results indicate that the proposed soft sensor not only outperforms some traditional models in terms of prediction performance but also excels in avoiding ineffective model reconstructions in scenarios involving complex dynamic wastewater treatment conditions.

Operators Need to Know How to Make Ethical Decisions

Understanding how ethics inform a water treatment plant operator's daily experience helps staff realize the significance of their efforts to protect public health and the environment.

Resilience Adaptation Through Risk Analysis for Wastewater Treatment Plant Operators in the Context of the European Union Resilience Directive

To combat new threats to critical infrastructure, the European Union enacted new regulations for their member states. With the directive on measures for a high common level of cybersecurity (NIS2) and the directive on critical infrastructure resilience (EU RCE), EU member states must identify critical infrastructure (CIs) and enable measures to reduce the risk of default in stress situations. The topic of resilience in urban water systems has already been of interest in previous research. However, there are still open questions. As it is a multidisciplinary term, understanding resilience and its adaptation into management systems is not an easy task for practitioners. This study will provide an overview of resilience within the framework of municipal wastewater treatment plants (WWTP) and show the current situation of existing implementation of safety and security regulations, taking Germany as an example. One of the main requirements of the EU RCE is a risk assessment (RA) for CIs. Until now, risk analysis for WWTP in research was mostly carried out for individual WWTP. By applying guidelines from the drinking water sector, this paper shows a possible methodology for a risk analysis. This paper aims to support practitioners by forming a common understanding of resilience and risk as well as providing an example for a risk analysis.

Practical implications of adding powdered activated carbon in advanced wastewater treatment for process and plant design

ABSTRACT The addition of powdered activated carbon (PAC) in advanced wastewater treatment is increasingly recognized for its effectiveness in removing micropollutants from secondary effluents. This study investigates the implications of PAC dosing on treatment performance, particularly in terms of natural and effluent organic matter (OM) removal, turbidity reduction, and sludge characteristics. Results indicate that while PAC incorporation significantly enhances the adsorption of OM, it necessitates higher coagulant dosages to achieve comparable or improved turbidity levels. The study also reveals that lower pH levels facilitate the removal of OM, thereby increasing the availability of adsorption sites on PAC for micropollutants. Moreover, PAC addition results in the formation of larger, denser flocs that settle faster, leading to a reduction in sludge volume by approximately 20%. However, the increased coagulant demand and the subsequent rise in sludge volume highlight the need for the optimized process design to balance treatment efficiency with operational costs. This research provides valuable insights for the design and operation of wastewater treatment plants, emphasizing the importance of tailored coagulant dosing and process adjustments when integrating PAC into existing treatment frameworks.

Intracellular and extracellular organic matter removal by BT/C heterogeneous interface under visible light photodriven

Algae-derived organic matter (AOM) limits the effectiveness of conventional water treatment processes, affects the normal operation of water treatment plants, and causes water quality deterioration. Efficient elimination of AOM is an urgent issue in the advanced treatment of drinking water. In this study, A heterogeneous interface for AOM removal was established based on BT/C, which can be driven by visible light. The removal efficiencies of extracellular organic matter (EOM), intracellular organic matter (IOM), and AOM by BT/C reached the optimal levels at 30 min, 60 min, and 90 min, respectively, reaching 48.5 %, 81.8 %, and 74.0 %. BT/C can oxidize and break down a large amount of high-molecular-weight organic matter in EOM into medium- and low-molecular-weight organic substances, and effectively remove the low-molecular-weight organic matter in EOM. In addition, BT/C can efficiently remove humic acids(HS) and aromatic protein organic matter in IOM, directly mineralize or decompose high-molecular-weight biopolymers into small-molecular-weight acidic and neutral organic matter; electron paramagnetic resonance spectroscopy and reactive oxygen species trapping experiments verified that hydroxyl radical (·OH) have play most important role on the degradation of various molecular weight organic matters. Superoxide radical (·O2–) plays a dominant role in the oxidation process of soluble microbial metabolites and HS, and ·OH plays a significant role in the oxidation process of amino acid-like proteins. This study provides new ideas and technical support for the complete removal of algae-derived organic matter and the protection of drinking water safety.

Assessment of radiological risk to workers and members of the public from the operation of a groundwater treatment plant in Jordan

ABSTRACT The study aimed to evaluate the radiation doses received by workers at a pilot water treatment plant (WTP) in Jordan. It also examined the concentrations of gross alpha, gross beta, and radium activities in both groundwater and treated water, along with a radiological risk assessment for the waste generated by the treatment process. The radioactivity levels of gross alpha and gross beta in the groundwater were found to exceed the established drinking water limits. In the pilot WTP, two methods were applied for water treatment, namely, ceramic ultra-filtration (CUF) and reverse osmosis (RO), both of which produced treated water that met drinking water quality standards. The annual effective dose from external radiation exposure to the WTP workers was found to be less than 0.007 mSv y−1 (during the filters backwash operation). However, the average annual dose from internal radiation due to inhalation of radon released from groundwater reached 3.2 mSv y−1, exceeding the 1 mSv y−1 limit. Therefore, monitoring radon levels in workplaces is recommended. Radioisotope concentrations in the waste (sludge) stockpiles exceeded clearance levels, requiring them to be treated as radioactive waste. Overall, the WTP successfully produced drinking water that met quality standards, and the methods used could be replicated in other locations.

Effects of Pulse Electromagnetic Field on Wastewater in Treatment Plants

The influence of a pulsed electromagnetic field (PEMF) with a pulse repetition rate of 16 Hz and a magnetic induction of no more than 500 nT on the solubility of oxygen in water and on wastewater treatment in two operating treatment plants was studied. It has been shown that treating wastewater with these pulses increases the maximum solubility of oxygen in water approximately by 30%, from 5.1 mg/dm3 to 6.8 mg/dm3 and accelerates all wastewater treatment processes by 10–20% and thereby creates a productivity reserve of the wastewater treatment plants. It was concluded that when operating blowers controlled by oxygen sensors, which turn on at an oxygen concentration of about 2 mg/dm3 and turn off at 4 mg/dm3, water PEMF treatment in the aeration tank leads to a reduction in the operating time of the blowers and, accordingly, energy savings by 15–28 %.

Energy efficiency evaluation of wastewater treatment plants: A methodological proposal for its benchmarking

To evaluate the energy performance of wastewater treatment plants (WWTPs), reliable, robust and holistic methods are needed. The data envelopment analysis (DEA) method, which allocates a flexible set of weights to input and output variables, has previously been used to benchmark the energy efficiency (EE) of WWTPs. However, this methodological approach suffers from discriminatory power, which makes it difficult to rank WWTPs and compare their performances because the EE scores are estimated under nonhomogeneous conditions. To overcome these limitations and to better understand the water-energy nexus, in this study, the EE of a sample of WWTPs was evaluated by allocating common weights to variables for all WWTPs in a DEA model (DEA-CSW). Evaluated WWTPs were shown to have a poor energetic performance, with an average EE score of 0.372. This means that WWTPs could save 62.8 % of their current energy use. Potential energy savings were estimated to be 118,206,789 kWh/year, which is equivalent to 29,552 tons of CO2eq/year. Based on a DEA-CSW approach, only one WWTP was identified as energy efficient; therefore, it is the best performer among the assessed WWTPs. Significant differences in the weights allocated to energy and pollutants removed from wastewater were reported by the DEA-CSW and DEA allocating flexible weights. Hence, under the latter methodological approach, some relevant variables, from the functionality perspective of WWTPs, were ignored in the EE assessment. This study demonstrates the relevance of using suitable methods to benchmark the energy performance of WWTPs to avoid misleading conclusions therefore, avoiding misguided regulatory decisions.

Nanostructured materials as hazardous wastewater micropullutants: Sources, behavior, and impact on functional bacterial community of activated sludge

Unique properties of nanoscale materials make them attractive for industrial, medical, agricultural, and environmental applications. Nevertheless, the release of nanoparticles into the environment is a major concern due to the lack of knowledge about their behavior in the environment and potential widespread environmental impacts. On the one hand, nanomaterials are perceived as pollutants that may affect activated sludge microorganisms and, consequently, the efficiency of wastewater treatment processes. On the other hand, some nanomaterials can be intentionally added to activated sludge systems to improve their performance in terms of, e.g., sludge settling and removing heavy metals or organic pollutants. As a result, nanoparticles are frequently accumulated in wastewater, which is considered to be a major source of nanoparticle release to the surrounding environment. Processes that involve the action of activated sludge are used worldwide in wastewater treatment plants due to their excellent capacity of removing nutrients, degrading toxins, and retaining biomass. High concentrations of nanoparticles entering activated sludge systems can affect their growth and metabolism. The research studies, which are reviewed in the present article, show that nanoparticles significantly reduce the relative abundance of the activated sludge microbial community associated with nitrification, denitrification, and phosphorus removal. The knowledge about the structure of the activated sludge microbial community with an assessment of nanomaterial toxicity can contribute to optimizing the sludge population and improving the performance of wastewater treatment plants.