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The aim of this study was to assess the impact of WWTP effluents on the sediment microbial communities throughout the Mureș River. This study shows the existence of an ecological equilibrium between the WWTP effluent disruptors and the resilience of the Mureș River sediment microbiomes, a fact that suggests the river’s stable/balanced ecological status in this regard, partly due to the microbial communities’ resilience to the local impact of WWTP effluents. High-throughput 16S bacterial metabarcoding was used to evaluate the bacterial communities in the sediment. Due to the lotic system’s sediment microbial communities’ sensitivity to environmental changes, we assumed the dependency of these community structures and functions on environmental abiotic and abiotic parameters. The study results show that, although bacterial communities are equally diverse in the three locations (upstream WWTP, WWTP effluents, and downstream WWTP), there is a difference in community structure between the upstream samples and the WWTP samples, while the downstream samples contain a mixture of the upstream and WWTP effluent communities. Just downstream of the WWTP sediment, microbial communities are influenced by the specific input from the WWTP effluents; nevertheless, the river sediment microbiome is resilient and able to further recover its natural microbial composition, as evidenced by the similarity in bacterial community structures at all upstream river locations. This study demonstrates the ecological equilibrium between the WWTP effluent disruptors and the resilience capacity of the Mureș River sediment microbiomes, a fact that indicates the river’s stable/balanced ecological status, in part due to the microbial communities’ resilience to the local impact of WWTP effluents. Based on these findings, a monitoring system should be implemented here in the future.

Bioaerosol emission at various WWTP treatment units has drawn attention due to their potential negative impacts on human health. This study conducted a bibliometric analysis of the global research on bioaerosol emissions from WWTPs from 1995 to 2022. The Scopus database was used to identify relevant articles and research trends, major contributors in the field, and recent developments. The study examined 122 articles in the field of bioaerosols in WWTPs. The analysis findings showed that publications and citations peaked in 2022, with values of 25 and 818, respectively. At the beginning of the study period, the USA, Poland, and Italy led the publications’ ranking, but with time, China emerged as the most influential country in the field. Recent advances in the field have revealed that spectral intensity bioaerosol sensors have contributed to the faster and more reliable identification and classification of bioaerosols. It was also observed that probabilistic techniques relying on mathematical models and assumptions to ascertain the risks associated with bioaerosols may result in false interpretations. Despite their high cost, epidemiological studies were best for assessing plant workers’ health risks. The outbreak has raised questions about accurately evaluating and modeling SARS-CoV-2 persistence, infectivity, and aerosolization over WWTP sites and environmental factors. Finally, the study highlighted the potential of three control treatment approaches: carbon absorption, UV irradiation, and ozone treatments, which proved efficient in reducing bioaerosol emissions.

Artificial Intelligence (AI) has recently emerged as a powerful tool with versatile applications spanning various domains. AI replicates human intelligence processes through machinery and computer systems, finding utility in expert systems, image and speech recognition, machine vision, and natural language processing (NLP). One notable area with limited exploration pertains to using deep learning models, specifically Recurrent Neural Networks (RNNs), for predicting water quality in wastewater treatment plants (WWTPs). RNNs are purpose-built for handling sequential data, featuring a feedback mechanism. However, standard RNNs may exhibit limitations in accommodating both short-term and long-term dependencies when addressing intricate time series problems. The solution to this challenge lies in adopting Long Short-Term Memory (LSTM) cells, known for their inherent memory management through a ‘forget gate’ mechanism. In general, LSTM architecture demonstrates superior performance. WWTP data represent a historical series influenced by fluctuating environmental conditions. This study employs simple RNNs and LSTM architecture to construct prediction models for effluent parameters, systematically assessing their performance through various training data scenarios and model architectures. The primary objective was to determine the most suitable WWTP dataset model. The study revealed that an epoch setting of 50 and a batch size of 100 yielded the lowest training time and root mean square error (RMSE) values for both RNN and LSTM models. Furthermore, when these models are applied to predict effluent parameters, they exhibit precise RMSE values for all parameters. The study results can be applied to detect potential upsets in WWTP operations.

Wastewater treatment plants (WWTPs) are energy-intensive facilities that fulfill stringent effluent quality norms. Energy consumption prediction in WWTPs is crucial for cost savings, process optimization, compliance with regulations, and reducing the carbon footprint. This paper evaluates and compares a set of 23 candidate machine-learning models to predict WWTP energy consumption using actual data from the Melbourne WWTP. To this end, Bayesian optimization has been applied to calibrate the investigated machine learning models. Random Forest and XGBoost (eXtreme Gradient Boosting) were applied to assess how the incorporated features influenced the energy consumption prediction. In addition, this study investigated the consideration of information from past data in improving prediction accuracy by incorporating time-lagged measurements. Results showed that the dynamic models using time-lagged data outperformed the static and reduced machine learning models. The study shows that including lagged measurements in the model improves prediction accuracy, and the results indicate that the dynamic K-nearest neighbors model dominates state-of-the-art methods by reaching promising energy consumption predictions.

For pharmacological reasons many active organic pharmaceutical substances (AOPSs) are singly or multiply halogenated. Halogenation can confer optimised steric fitting of an AOPS to its molecular receptor; moreover, by increasing the lipophilicity of a compound, passive permeation through bilipid membranes into target cells is enhanced. As halogenation is widely suspected to inhibit biodegradability in wastewater treatment plants, the relationship of halogenation vs. ready biodegradability was investigated. Among 230 AOPSs with empirical ready biodegradability data, all 70 halogenated AOPSs are not readily biodegradable, and halogenation is confirmed to be an impediment to ready biodegradability. As a counterexample to halogenation, hydrophilic substitutions (hydroxy, carboxylic-acid or terminal-amine groups) are positively correlated with ready biodegradability. Regarding halogenation, therefore, pharmacological goals stand in stark contrast to environmental goals. Possible ideas toward solutions for this contradiction are discussed.

With the increasing demands for higher treatment efficiency, better effluent quality, and energy conservation in Urban Wastewater Treatment Plants (WWTPs), research has already been conducted to construct an optimized control system for Anaerobic-Anoxic-Oxic (AAO) process using a data-driven approach. However, existing data-driven optimization control systems for AAO mainly focus on improving effluent water quality and reducing energy consumption, therefore they lack consideration for the stability of bioreactors. Meanwhile, safety in the optimization control process is still missing, resulting in a lack of reliability in practical applications. In this study, long short-term memory based model-predictive control (LSTM-MPC) with safety verificationis developed for the real-time control of AAO. It is used to optimize the control of aeration volume, internal recirculation, and sludge internal recycle processes for both saving energy and maintaining the stability of the bioreactor operation. To ensure the safety of the control process, this study proposes three rationality verification methods based on historical operation experience. These methods are validated through data from a real-world WWTP in eastern China. The results show that the prediction model of LSTM-MPC is capable of accurately predicting the water quality variables of the AAO system, with mean square error (MSE) close to 2.64 and Nash–Sutcliffe model efficiency coefficient (NSE) of 0.99 on the validation dataset. The combination of LSTM-MPC and rationality verification achieves a stable control trajectory with a 7% reduction in oxygen usage compared to a conventional controller, demonstrating its efficacy as a safe and reliable control strategy for WWTPs.

Wastewater treatment plants (WWTPs) represent an important input of contaminants in the environment. Therefore, it is critical to continuously monitor the performance of WWTPs to take appropriate action and avoid an influx of contaminants in the environment. In this study, a battery of seven in vitro bioassays covering a selected spectrum of toxicity effects is proposed for quality control of wastewater effluents. The bioassays address mixture toxicity, which is the combined adverse effect of multiple contaminants and can act as an early warning system. The proposed battery was applied to samples from 11 WWTPs of representative technology from the Danube River Basin (DRB). The order of toxic effects in terms of extent of exceedance of effect-based trigger values (EBTs) was PAH (PAH activity) > PXR (xenobiotic metabolism) > ERα (estrogenic activity) > PPARγ > Nrf2 (oxidative stress) > anti-AR > GR. A mitigation plan for WWTP operators based on EBT exceedance is proposed. This study demonstrates that the proposed effect-based monitoring battery is a complementary tool to the chemical analysis approach. A regular application of such time- and cost-effective bioanalytical tools in the WWTPs of the DRB is proposed to provide a ‘safety net’ for aquatic ecosystems.

Many quantitative and qualitative methods have been developed to estimate the seismic vulnerability of Wastewater Treatment Plants (WWTPs). The research approach using questionnaires is the most common qualitative process to quickly access estimation results. In the present study, the Experts’ Judgment method was implemented. A representative questionnaire was distributed to a hundred and sixteen (116) operators of Greece’s WWTPs according to proportional stratified sampling for seven months. The questionnaire was based on the main parameters that contribute to seismic vulnerability (structural, non-structural and operational matters). The examination of the results included the search for reliability and validity. Their collection also revealed that the average seismic vulnerability of the samples was found at a low level after a direct question, and was slightly increased after analyzing a group of questions. In the case of soil–water pollution during the post-seismic period, the answers showed low percentages for the contribution to the seismic vulnerability (at the partial mode), and divided answers existed at low and slightly increased percentages. Non-structural and operational vulnerability somewhat increased the percentages in the judgments. During the 24 h post-seismic period, the possibility of soil–water pollution was expected at low percentages and it remained constant. The results of this study could be compared to future surveys for qualitative approaches to disaster risks or could be used in addition to the results from quantitative methods.

Ensuring the stable operation of urban wastewater treatment plants (WWTPs) and achieving energy conservation and emission reduction have become serious problems with the improvement of national requirements for WWTP effluent. Based on a wastewater quality analysis, identification of the contaminant removal, and a simulation and optimization of the wastewater treatment process, a practical engineering diagnosis method for the cyclic activated sludge technology process of WWTPs in China and an optimal control scheme are proposed in this study. Results showed that exceeding the standard of effluent nitrogen and phosphorus due to unreasonable process cycle setting and insufficient influent carbon source is dangerous. The total nitrogen removal rate increased by 9.5% and steadily increased to 67% when agitation was added to the first 40 min of the cycle. Additionally, the total phosphorus (TP) was reduced to 0.27 mg/L after replacing the phosphorus removal agent polyferric sulfate with polyaluminum iron. The corresponding increase in the TP removal rate to 97% resulted in a reduction in the treatment cost by 0.008 CNY/t.

Wastewater treatment plants (WWTPs) are facing challenges concerning the service’s effectiveness and reliability, as well as the efficiency and sustainability of resource utilization, where energy represents one of the higher costs in activated sludge (AS) treatment. This paper presents the latest developments in the new energy performance indices (PXs) we have been developing for benchmarking, i.e., assessing and improving the performance of this widely used treatment. PXs compare the energy consumption with the energy requirements for the carbon and nitrogen removals needed for the plant’s compliance with the discharge consents (the closer they are, the better the performance). PXs are computed by applying to the state variables a performance function that is defined by the reference values for excellent, acceptable, and unsatisfactory performance. This paper shows the rationale for selecting the state variables for the AS energy performance and the comprehensive derivation of the equations to determine the reference values for energy consumption, which incorporate the effect of key parameters (flows, concentrations, and operating conditions). Reference values for the operating conditions affecting the energy performance are also proposed. A sensitivity analysis identified the key parameters for improving the aeration performance: α, F, and SOTE for air diffusers, and α and N0 for mechanical aerators. Fourteen Portuguese urban WWTPs (very diverse in size and inflows) were analyzed, and aeration (0.08–1.03 kWh/m3) represented 25–80% of total energy consumption (0.23–1.30 kWh/m3). The reference values for excellent performance were 0.23–0.39 kWh/m3 (P25–P75) for AS systems with air diffusers and 0.33–0.80 kWh/m3 for those with mechanical aerators. A comprehensive application in one WWTP (16–18 d solids retention time) showed the system’s ability at identifying which operating conditions to adjust (to F/M ratio lower than 0.09 d−1 and decreasing aeration during the low season) to improve the energy performance/savings while maintaining the treatment’s effectiveness and reliability.

Pharmaceuticals and personal care products (PPCPs) were investigated in five wastewater treatment plants (WWTPs), groundwater, irrigated soils, and plants in Amman and Al-Balqa governorates in Jordan. PPCPs were extracted from water samples by solid-phase extraction (SPE) and analyzed by high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC–MS/MS). Carbamazepine, ciprofloxacin, ceftiofur, diclofenac, erythromycin, lincomycin, ofloxacin, pyrimthamine, spiramycin, sulfamethoxazole, sulfapyridine, testosterone, trimethoprim, and thiamphenicol were detected in all raw wastewaters in μg/L, whereas 45 PPCPs were below the detection limits (

A simple and consolidated reliability-based method widely used to unveil the real reliability and stability of wastewater treatment plants (WWTPs) is herein proposed to trigger decision making on operational improvements and asset management for maintaining or improving treatment effectiveness, reliability, and efficiency. Five-year data (2015–2019) from 16 Portuguese activated sludge WWTPs were used. For the 73% of the yearly data which fitted a lognormal distribution, Niku’s coefficient was computed to assess the plant annual reliability for biological oxygen demand (BOD5), chemical oxygen demand (COD), and total suspended solids (TSS). The standard deviation of the annual concentrations was used to characterize the plant stability, and the maximum standard deviations allowed to comply with the European discharge requirements for urban WWTPs were derived. The results demonstrate extended aeration WWTPs were more reliable and stable than conventional aeration WWTPs (0.98 reliability vs. 0.82 for BOD5, 0.97 vs. 0.91 for COD, and 0.94 vs. 0.89 for TSS). Furthermore, the lower reliabilities and stabilities were found for the smaller WWTPs. These results are important for strategic asset management for designing and rehabilitation of the wastewater treatment system. At tactical and operational levels, for resources’ allocation and operating conditions set up, the computed WWTP’s coefficient of variation allows establishing the mean effluent concentrations required for compliance with a given reliability for different scenarios of discharge requirements.

Heavy metals may cause acute and chronic toxic effects to humans and other organisms, hence the need to treat wastewater properly, as it contains these toxicants. This work aimed at assessing zinc, copper, cadmium, and chromium in water, soil, and plants that are irrigated with effluent from Manase and Soche Wastewater Treatment Plants (WWTPs) in Blantyre, Malawi. Atomic Absorption Spectrophotometry (AAS) was used to assess the heavy metals. Heavy Metal Health Risk Assessment (HMHRA) on plants (vegetables) around both WWTPs was also conducted. Average daily dose (ADD) and target hazard quotients (THQ) were used to assess HMHRA. Physicochemical parameters were determined using standard methods from American Public Health Association (APHA). The heavy metal ranges were below detection limit (BDL) to 6.94 mg/L in water, 0.0003 to 4.48 mg/kg in soil, and 3 to 32 mg/L in plants. The results revealed that plants irrigated with effluent from WWTP had high values of aforementioned metals exceeding the Malawi Standards and WHO permissible limits. Furthermore, the health risk assessment values showed that vegetables consumed for a long period of time from Manase WWTP were likely to cause adverse health effects as compared to those from Soche WWTP.

In recent years, many scientific studies have focused their efforts on quantifying the different types of pollutants that are not removed in wastewater treatment plants. Compounds of emerging concern (CECs) have been detected in different natural environments. The presence of these compounds in wastewater is not new, but they may have consequences in the future. These compounds reach the natural environment through various routes, such as wastewater. This review focuses on the study of tertiary treatment with advanced oxidation processes (AOPs) for the degradation of CECs. The main objective of the different existing AOPs applied to the treatment of wastewater is the degradation of pollutants that are not eliminated by means of traditional wastewater treatment.

The use of micro-hydropower (MHP) for energy recovery in water distribution networks is becoming increasingly widespread. The incorporation of this technology, which offers low-cost solutions, allows for the reduction of greenhouse gas emissions linked to energy consumption. In this work, the MHP energy recovery potential in Spain from all available wastewater discharges, both municipal and private industrial, was assessed, based on discharge licenses. From a total of 16,778 licenses, less than 1% of the sites presented an MHP potential higher than 2 kW, with a total power potential between 3.31 and 3.54 MW. This total was distributed between industry, fish farms and municipal wastewater treatment plants following the proportion 51–54%, 14–13% and 35–33%, respectively. The total energy production estimated reached 29 GWh∙year−1, from which 80% corresponded to sites with power potential over 15 kW. Energy-related industries, not included in previous investigations, amounted to 45% of the total energy potential for Spain, a finding which could greatly influence MHP potential estimates across the world. The estimated energy production represented a potential CO2 emission savings of around 11 thousand tonnes, with a corresponding reduction between M€ 2.11 and M€ 4.24 in the total energy consumption in the country.

Treated sewage harbours pathogenic microbes, such as enteric bacteria and protozoa, are capable of causing several diseases. Some of these are emerging pathogens sometimes recovered in the absence of common water quality indicator organisms. The possibility of selected treatments plants serving as momentary reservoirs of Vibrio pathogens during a non-outbreak period was assessed. The occurrence and diversity of Vibrio pathogens were monitored for one year (December 2016 to November 2017) in the treated effluents and upstream and downstream areas of the receiving water bodies of two wastewater treatment plants (WWTPs), designated AL and TS. Physicochemical parameters of TS and AL WWTPs’ water samples were analysed using a multi-parameter meter (Hanna, model HI 9828, Padova, Italy) and a turbidimeter (HACH, model 2100P, Johannesburg, South Africa). Water samples were augmented with alkaline peptone water and cultured on thiosulfate citrate bile salts sucrose agar at 37 °C for 24 h. The recovered probable pathogens were confirmed via PCR amplification, using primers specific for Vibrio species of public health significance. The distribution of Vibrio species positively and significantly (p < 0.01) correlated with turbidity (r = 0.630), temperature (r = 0.615), dissolved oxygen (r = 0.615), pH (r = 0.607), biological oxygen demand (r = 0.573), total dissolved solid (r = 0.543), total suspended solid (r = 0.511), electrical conductivity (r = 0.499), residual chlorine (r = 0.463) and salinity (r = 0.459). The densities of Vibrio species were found to be significantly higher (p < 0.05) in effluents from both AL and TS WWTPs than upstream and downstream of the receiving rivers across the sampling regime. Furthermore, the maximum Vibrio species density across the sampling regime were observed during the warmer Summer and Spring season. Moreover, six medically important Vibrio species were detected in the water samples, indicating that the methods employed were efficient in revealing that WWTPs are potential reservoirs of Vibrio pathogens, which could pose a substantial public health risk if the receiving water is used for domestic purposes. Our findings further strengthen existing calls for the inclusion of emerging bacterial pathogens, including Vibrio species, as water quality indicators by the South African Department of Water Affairs. Hence, we recommend regular monitoring of treated effluents and receiving water bodies to ensure early control of potential outbreaks of vibriosis and cholera.

This work explores the possibilities of improving the eco-efficiency of Wastewater Treatment Plants (WWTPs) introducing a plant-wide perspective in the formulation of the control strategy. Eco-efficiency goals are contemplated in the analysis of the appropriateness of control actions, considering the seasonal effects of temperature into the decision-making process. Plant-wide control strategy handles are the operation variables of the activated sludge process, the volume of the primary clarifier, and the temperature of the anaerobic digester. Performance is evaluated in terms of energy use, biogas production, effluent quality, emissions to air and soil, considering annual and bimestrial average values of indicators to capture seasonal effect of temperature. The result is a set of possible solutions, obtained from a multi-objective decision-making procedure, consisting on a sequence of control actions applied at different temporal windows that improve the eco-efficiency indicators of the plant. The results obtained when applying the different solutions make evident how the application of plant-wide control strategies is useful to improve performance indicators that represent individual goals, leading to trade-off solutions that describe WWTPs’ eco-efficiency.

In the context of efficient and sustainable management of the elements of the urban water cycle as an aim of the Water Framework Directive (WFD), the evaluation of indicators such as the water footprint (WF) and the carbon footprint (CF) in a wastewater treatment plant (WWTP) provides a quantification of the environmental impact, both negative and positive, which implies its exploitation. In this study, in addition to WF and CF quantification, a joint evaluation of both indicators was conducted. Consumption is indicated by the blue water footprint (WFBlue) and emissions by CF. Both are related to the operational grey water footprint (∆WFG,mef) in two ratios, WFR and CFR. In this way, the water consumed and gases emitted are measured according to the reduction range of the pollutant load of the discharge. The results for four WWTPs show operational scenarios for better management in accordance with the WFD.

Baiyangdian Lake, the largest freshwater body in Northern China, is facing water shortage and eutrophication problems that threaten the lake’s ecosystem. Environmental water releases from upstream reservoirs to the lake are important measures to provide the freshwater resources demanded by the lake ecosystem. However, knowledge is limited regarding the influences of such water allocations on the water quality of the upstream rivers that receive the reservoir water and transport it into Baiyangdian Lake. To improve our understanding of possible influences of environmental water releases from upstream reservoirs, the spatial variation of water quality in rivers upstream of the lake during environmental water release periods from reservoirs was explored in this study. Water samples were collected along the two routes of water allocation: the WangKuai reservoir route (WKR) and the XiDaYang reservoir route (XDYR) and water quality parameters related to organic pollutants, nitrogen and phosphorus were analyzed. In the WKR, the pollutant concentrations generally increased from upstream to downstream. Chemical oxygen demand, total nitrogen, and total phosphorous at the sampling site closest to Baiyangdian Lake could not meet the water quality target of the water function zone. For the XDYR, pollutant concentrations peaked downstream of the major urban region of Baoding city and then decreased or remained at a similar level further downstream and only the total nitrogen concentration was worse than the target. The dissimilarities in spatial variation patterns of water quality may be caused by the different spatial distribution of wastewater treatment plants in the two routes.

As one of the major sources of pollutions in the environments, effluents from municipal wastewater recently became a hot topic. This study quantified monthly county-level releases of five heavy metals, i.e., lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), and mercury (Hg), from municipal wastewater into the environment in the Heilongjiang Province of China, based on sampling, measurement, and modeling tools. Wastewater samples were collected from 27 municipal wastewater treatment plants (MWTPs) in 15 county-level cities of Heilongjiang every month from 2015 to 2017. The concentrations of five heavy metals were analyzed in both influents (Pb: 160 ± 100 μg/L; Cd: 15 ± 9.0 μg/L; Cr: 170 ± 64 μg/L; Hg: 0.67 ± 1.5 μg/L; As: 6.2 ± 4.8 μg/L) and effluents (Pb: 45 ± 15 μg/L; Cd: 5.2 ± 5.1 μg/L; Cr: 57 ± 13 μg/L; Hg: 0.28 ± 0.12 μg/L; As: 2.6 ± 1.4 μg/L). The removal ratios of the five heavy metals ranged from 50% to 67%. Inflow fluxes of Pb, Cr, and Cd displayed increasing trends first then decreased after reaching a maximum value, whereas those of Hg and Pb remained stable. Material flow analysis reveals that constructions of MWTPs are conducive to significantly reduce the releases of heavy metals from urban areas into the aquatic environment in the study area. Additionally, municipal wastewater sludge (used as fertilizer or spread on the land) could be a significant source of heavy metals in the land.

Mercury (Hg) is still a focus of environmental research, since its levels in fish frequently exceed the Environmental Quality Standard (EQS) of 20 µg/kg for biota defined by the European Water Framework Directive (Directive 2008/105/EC). Current Hg levels in Abramis brama from German rivers are in the range of 73–346 µg/kg wet weight (2009) and exceed the EQS by a factor of 3.7–17.3. Therefore, it is important to identify the sources of Hg pollution in the aquatic environment and to develop effective strategies for reducing the input into associated river systems. The aim of the present study was to analyze Hg in the urban water cycle of the city of Frankfurt am Main, Germany. Samples were taken from the river Main crosscutting the city and its tributaries. In addition, precipitation, stormwater runoff, effluents of two municipal WWTPs, and stormwater management structures such as combined sewer overflows and stormwater retention basins have been analyzed. Loads of Hg have been determined based on the measured concentrations and a Hg mass balance for the aquatic system was created. A total of 160 water samples were analyzed by cold vapor atomic fluorescence spectroscopy (CVAFS) according to US EPA Method 1631. Results from the mass balance have shown that approximately 5 kg Hg/a enter and 15 kg Hg/a leave the study area of Frankfurt am Main via the river Main. The largest amount of Hg (24.58 kg/a) throughout the urban water cycle of Frankfurt am Main is transported via wastewater. However, municipal WWTPs in Frankfurt am Main have been identified as the largest Hg sink, since 99.7% (24.5 kg/a) of the Hg is shifted from the sewage water and stormwater during treatment into the sewage sludge. Thus, the increase of the Hg load in the river Main from 5 to 15 kg/a has to be attributed to other sources such as 3 industrial WWTPs, groundwater and non-treated stormwater runoff during heavy rain events.

In nutrient-sensitive estuaries, wastewater treatment plants (WWTPs) are required to implement more advanced treatment methods in order to meet increasingly stringent effluent guidelines for organic matter and nutrients. To comply with current and anticipated water quality regulations and to reduce the volume of produced sludge, we have successfully developed a vertical membrane bioreactor (VMBR) that is composed of anoxic (lower layer) and oxic (upper layer) zones in one reactor. Since 2009, the VMBR has been commercialized (Q = 1100–16,000 m3/d) under the trade-name of DMBRTM for recycling of municipal wastewater in South Korea. In this study, we explore the performance and stability of the full-scale systems. As a result, it was found that the DMBRTM systems showed excellent removal efficiencies of organic substances, suspended solids (SS) and Escherichia coli (E. coli). Moreover, average removal efficiencies of total nitrogen (TN) and total phosphorus (TP) by the DMBRTM systems were found to be 79% and 90% at 18 °C, 8.3 h HRT and 41 d SRT. Moreover, transmembrane pressure (TMP) was maintained below 40 kPa at a flux of 18 L/m2/h (LMH) more than 300 days. Average specific energy consumption of the full-scale DMBRTM systems was found to be 0.94 kWh/m3.

Nitrates pollution of waters is a worldwide problem and its remediation is a big challenge from the technical and the scientific point of view. One of the most used and promising cleaning techniques is the biological treatment of wastewaters operated by denitrifying bacteria. In this paper we begin a thorough study of denitrifying performances of the bacterium Azospira sp. OGA 24, recently isolated from the highly polluted Sarno river in the south of Italy. Here, the kinetics of nitrates consumption operated by bacteria in a specifically devised batch bioreactor, in anoxic condition and with acetate as the organic substrate, has been characterized. Experimental data were then used in a simplified model of a real wastewater treatment plant to find that OGA 24 can clean water with efficiency up to 90%. The denitrifying performances of OGA 24 match the requirements of Italian laws and make the bacterium suitable for its employment in treatment plants.

Two indices have been defined in this work to measure the pollution load that a Wastewater Treatment Plant (WWTP) receives and the efficiency of the process it carries out from the overall perspective of pollution removal and energy efficiency. The aim is to provide two performance parameters which could be used to characterize both the working conditions of a WWTP and how well it treats the pollution it receives. In this way, they may be used to compare the behavior of different plants in a certain geographical area. Forty-five WWTPs in the Southwest of Spain were studied to find out the most significant information that is to be used to identify and define both indices. Seven of the variables recorded were used to define each one. Their values were calculated for the whole set of plants studied. The results showed that most of the plants received a low pollution load. Only six of them suffered from a high pollution load, probably because of farms and food industries located in their surroundings. Only three plants showed a poor efficiency, while 23 of them presented a very good one.