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Wastewater treatment plants in Coimbatore South are under pressure from rapid urbanization, inadequate infrastructure, and industrial pollution, leading to environmental and public health concerns. This study aimed to identify suitable locations for wastewater treatment plants using a combination of machine learning, remote sensing, and GIS-based multicriteria decision analysis (MCDA). Several datasets were analysed, with the analytical hierarchy process (AHP) assigning weights to factors such as slope (18.51) and elevation (31.39), which were found to be crucial in site selection. The study classified the suitability of sites into five categories, with the western region being the most favourable due to its low elevation (147 to 200 m), gentle slopes (0–3%), and substantial land availability (approximately 309.00 sq. km). Overall, the site suitability analysis revealed that 14.48% (110.2 sq. km) of the area falls within "Very High Favourable Zones," while 11.21% (85.3 sq. km) is categorized as "High Favourable Zones." Moderate and low favourable zones account for 9.63% (73.3 sq. km) and 24.04% (182.9 sq. km), respectively. The remaining 40.57% (308.7 sq. km) is considered "Very Low Favourable Zones." These results can guide urban planning decisions, highlighting the importance of factors such as land availability, population growth, wastewater volume, and flood vulnerability. Integrating GIS technology with decision-making processes enhances the strategic placement of urban utilities, ensuring long-term sustainability for Coimbatore South's wastewater management. [ABSTRACT FROM AUTHOR]

Activated sludge is a complex wastewater purification process involving microorganisms, extracellular polymeric substances (EPS), and organic matter. Although this process has been utilized for over a century, our understanding of the relationships between the components of activated sludge and wastewater treatment plant (WWTP) metrics is still evolving. Polysaccharides play significant roles in water retention within loose-bound EPS and soluble EPS, negatively impacting dewaterability and flocculation. Conversely, proteins, primarily found in tightly bound EPS, are sensitive to pH and contribute positively to settleability and flocculation. Studies on eDNA are limited but suggest it has key functions in stabilizing the matrix and interacting with polymers. There is considerable information on how proteins and sugars affect sludge volume index, capillary suction time, and flocculation. Additionally, some studies investigated the biochemistry and molecular biology of activated sludge across temporal, geographical, and laboratory settings. However, there are few studies identifying trends between specific sugars, proteins, bacterial taxa, and WWTP metrics. This review explores the intermolecular forces binding these components together and the roles of proteins, polysaccharides, eDNA, and bacterial taxa in the sludge. It also examines the relationships between these sludge components and settleability, flocculation, dewaterability, type of WWTP, and environmental trends. The review provides a holistic and integrative perspective on EPS in activated sludge systems, emphasizing the significance of different EPS fractions (TB EPS and LB EPS) and their contributions to key WWTP metrics such as dewaterability, settleability, and flocculation. [ABSTRACT FROM AUTHOR]

In present time, there is no legal regulatory national document related to sludge management in Georgia, and the sludge removed from the treatment plant throughout the country is stored in the Wastewater Treatment Plants (WWTP) area after proper treatment (dewatering, drying). The purpose of our research was studying the limited and nutrients elements in the sludge generated at the WWTP and determine the optimal quantity/dosage for agriculture. Our studies have shown that the average values of seven heavy metals limited by the EU Directive do not exceed or only slightly exceed the established Limit Values and the annual maximum amount of sludge that can be used in the agricultural sector for 10 years is limited by the amount of zinc and is 68 092.06 kg/ha/year. Applying the specified amount of sludge to the soil primarily ensures its enrichment with the nutrient element - nitrogen. [ABSTRACT FROM AUTHOR]

Abstract Microplastics (MP), fragments of plastic generally defined as, less than 5 mm in size, originating from various urban sources, have become a significant environmental concern due to their widespread presence and potential impacts on ecosystems. This study investigates the efficiency of an advanced wastewater treatment plant discharging into the Mediterranean Sea in removing MPs from wastewater. The plant processes wastewater through a series of treatment stages, including screening, desanding, coagulation/flocculation, biological filtration, and sludge incineration. Samples were collected and analysed during three distinct campaigns (dry, rainy, and touristic seasons) to assess the plant’s performance under varying conditions. Using matrix-representative sampling methodologies and Focal Plane Array micro Fourier-Transform Infrared Spectroscopy (FPA-µFT-IR) for MP quantification, the study measured MP concentrations and removal rates. The treatment plant demonstrated high removal rates of microplastics across different periods. Using a mass balance approach, the removal efficiency during the dry sampling period was 99.85%. In the rainy campaign, the efficiency slightly decreased to 99.11% due to increased runoff, while during the touristic period, the efficiency peaked at 99.95%. Polyester was identified as the predominant polymer type. The primary treatment stages, particularly coagulation/flocculation and lamellar settling, are most effective in MP removal. The majority of MPs are retained in the sludge, which is subsequently incinerated, preventing environmental discharge. This research demonstrates that a WWTP employing advanced treatment processes is not a source of MP to the environment but rather a sink. Despite variations in influent MP concentrations across different seasons, the plant consistently maintained high removal rates, effectively mitigating MP pollution. In this study, sludge incineration further ensured that MPs were prevented from entering the environment.

Copyright of Journal of Anatolian Environmental & Animal Science is the property of Bulent Verep and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wastewater treatment must be proactive and sustainable to facilitate an increase in the circularity of water. Therefore, the current approach, based on a linear cycle, must be replaced with a circular economy concept that implements strategies to address the different byproducts in the wastewater treatment sector. In recent years, Nuevo León, Mexico, has encountered high water stress levels, with its main water bodies presenting their lowest levels ever recorded. This study was focused on the wastewater treatment plant Monterrey, which treats the largest volume at the state level. Throughout its operation process, it generates different potential byproducts that are yet to be harnessed to fully. This study developed three proposals using a circular economy approach: the treatment of water for the industrial sector, the use of residual sludge as an organic fertilizer, and the cogeneration of energy from biogas. These proposals can potentially generate benefits regarding the three pillars of sustainability, yielding a closed cycle in the wastewater treatment sector at the national level. [ABSTRACT FROM AUTHOR]

Microplastics (MP), fragments of plastic generally defined as, less than 5 mm in size, originating from various urban sources, have become a significant environmental concern due to their widespread presence and potential impacts on ecosystems. This study investigates the efficiency of an advanced wastewater treatment plant discharging into the Mediterranean Sea in removing MPs from wastewater. The plant processes wastewater through a series of treatment stages, including screening, desanding, coagulation/flocculation, biological filtration, and sludge incineration. Samples were collected and analysed during three distinct campaigns (dry, rainy, and touristic seasons) to assess the plant's performance under varying conditions. Using matrix-representative sampling methodologies and Focal Plane Array micro Fourier-Transform Infrared Spectroscopy (FPA-µFT-IR) for MP quantification, the study measured MP concentrations and removal rates. The treatment plant demonstrated high removal rates of microplastics across different periods. Using a mass balance approach, the removal efficiency during the dry sampling period was 99.85%. In the rainy campaign, the efficiency slightly decreased to 99.11% due to increased runoff, while during the touristic period, the efficiency peaked at 99.95%. Polyester was identified as the predominant polymer type. The primary treatment stages, particularly coagulation/flocculation and lamellar settling, are most effective in MP removal. The majority of MPs are retained in the sludge, which is subsequently incinerated, preventing environmental discharge. This research demonstrates that a WWTP employing advanced treatment processes is not a source of MP to the environment but rather a sink. Despite variations in influent MP concentrations across different seasons, the plant consistently maintained high removal rates, effectively mitigating MP pollution. In this study, sludge incineration further ensured that MPs were prevented from entering the environment. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) have been identified as important point sources for microplastics (MPs) in the environment; monitoring MP emissions in the WWTP effluent is therefore essential for contamination control. The aim of this study is to acquire a large number of samples (320) over a period of two years and three months to determine the temporal variations in microplastic contamination in the outlet of the municipal WWTP Landau-Mörlheim. The effluent of the third cleaning stage is sampled with a 10 µm filter cartridge, processed in the laboratory using a hydrogen peroxide treatment, and MPs are then detected by fluorescence staining. The results show high temporal variations in the microplastic concentrations in the effluent of the WWTP. This indicates that high numbers of samples are necessary to obtain a representative assessment of the microplastic emissions; single samples are not representative. The average microplastic concentration in the effluent was 27.8 ± 29.8 MP/L, ranging from 0.6 MP/L to 194.0 MP/L. This leads to a yearly emission of 1.5 × 1011 MP for the WWTP Landau-Mörlheim, corresponding to an emission of 2.8 × 106 MP/inhabitant and year. Statistically significant seasonal variations could not be observed, although there is a trend towards lower MP concentrations in summer. Further, no correlations with other wastewater or weather parameters could be found. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic in Peru, a notable increase in self-medication with antibiotics has been observed, raising concerns about the increase in bacterial resistance. In this context, we evaluated the situation in wastewater treatment plants (WWTPs) using biochemical methods and sensitivity tests, such as the Kirby-Bauer assay. The results of our study show a high sensitivity to antibiotics in most of the strains analyzed, particularly towards β-lactams. However, this sensitivity appears to be influenced by seasonal patterns of medication consumption, supported by studies indicating that its contribution to the total flow is minimal. We analyzed 49 strains of Escherichia coli, 27% of which showed no resistance to any antibiotic, while the highest resistance was observed against tetracycline (63%). High levels of resistance to fluoroquinolones, such as ciprofloxacin and levofloxacin, were also recorded. In contrast, amikacin and piperacillin-tazobactam showed minimal resistance, with only one strain resistant to each. Multiresistance, defined as resistance to at least two antibiotics, was identified in 35% of the strains, with two of them showing resistance to 8 and 10 antibiotics, respectively.

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.

Potable water and sanitation are priorities since pollutants pose health risks in Mexican rural communities. In this study, the San Francisco Pichataro (Michoacán) WWTP effluent was subjected to a post-bioadsorption treatment. For this purpose, activated bioadsorbents from avocado waste were developed. Avocado waste represents ∼34 metric tons per day in the considered municipality. The WQI tool was used to assess the water quality for the WWTP influent, effluent, and the post-bioadsorption effluent (permeate). The application of the activated bioadsorbent increased the WQI from 30 to 70, removing about 1600 to 1900 mg L−1 of COD and ≈50% of hardness (Mg2+ and Ca2+), and enhancing the quality of the WWTP effluent. This improvement means the permeate flux could be used for crop irrigation or sanitation activities, improving water resource management.

Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing importance of water quality has led to optimizing the operation of Wastewater Treatment Plants. This implies the monitoring of many parameters that measure aspects such as solid suspension, conductivity, or chemical components, among others. This paper proposes the use of one-class algorithms to learn the normal behavior of a Wastewater Treatment Plants and detect situations in which the crucial parameters of Chemical Oxygen Demand, Ammonia, and Kjeldahl Nitrogen present unexpected deviations. The classifiers are tested using different deviations, achieving successful results. The final supervision systems are capable of detecting critical situation, contributing to decision-making and maintenance effectiveness. [ABSTRACT FROM AUTHOR]

IPAL management is an important component in maintaining environmental quality and public health, especially in densely populated areas and the increasing development of vertical housing in East Jakarta with the largest population in Jakarta based on BPS 2023 data. Apartments are residences that produce waste water every day, which has the potential to pollute the environment if not managed well, based on the existing conditions in the field, it was found that there were still apartments that had not managed the IPAL properly, such as the IPAL not operating optimally. Technical aspects and Human Resources (HR) aspects play a very important role in managing IPAL in Apartments in operating and maintaining the IPAL system. This research aims to evaluate the management of IPAL Apartments in terms of technical and human resource aspects with a case study of four apartments in East Jakarta. The method used is taking domestic wastewater samples in four apartments in the low rise, medium rise and high rise categories and then comparing them with the standards set in Minister of Environment and Forestry Regulation No. 68 of 2016. Then a technical evaluation is carried out based on capacity, quality standards and allowance efficiency. HR analysis is carried out descriptively to assess the competency and habits of residents in environmental management. The research results show that apartments in the low rise and high rise categories have met the expected quality standards, capacity and allowance efficiency. From the HR aspect, management and operators in these apartments have competence in managing IPALs, whereas in medium rise category apartments they still do not meet the expected quality standards and allowance efficiency. This is due to the IPAL unit having damage to the blower and the unavailability of qualified operators. have a competency certificate in operating IPAL. [ABSTRACT FROM AUTHOR]

Waste Water Treatment Plants (WWTP) aim to reduce contamination in effluent water; however, studies indicate antimicrobial resistance genes (ARGs) persist post-treatment, potentially leading to their spread from human populated areas into the environment. This study evaluated the impact of a large WWTP serving 125,000 people on the Iskar River in Bulgaria, by characterizing the spatial and short-term temporal dynamics in bacterial community dynamics and resistance profiles of the surface water. Pairs of samples were collected biweekly on four dates from two different locations, one about 800 m after the WWTP effluents and the other 10 km downstream. Taxonomic classification revealed the dominance of Pseudomonodota and Bacteriodota, notably the genera Flavobacterium, Aquirufa, Acidovorax, Polynucleobacter, and Limnohabitans. The taxonomic structure corresponded with both lentic and lotic freshwater habitats, with Flavobacterium exhibiting a significant decrease over the study period. Principal Coordinate Analysis revealed statistically significant differences in bacterial community composition between samples collected on different dates. Differential abundance analysis identified notable enrichment of Polynucleobacter and Limnohabitans. There were shifts within the enriched or depleted bacterial taxa between early and late sampling dates. High relative abundance of the genes erm(B), erm(F), mph(E), msr(E) (macrolides); tet(C), tet(O), tet(W), tet(Q) and tet(X) (tetracyclines); sul1 and sul2 (sulphonamides); and cfxA3, cfxA6 (beta-lactams) were detected, with trends of increased presence in the latest sampling dates and in the location closer to the WWTP. Of note, genes conferring resistance to carbapenems blaOXA-58 and blaIMP-33-like were identified. Co-occurrence analysis of ARGs and mobile genetic elements on putative plasmids showed few instances, and the estimated human health risk score (0.19) according to MetaCompare2.0 was low. In total, 29 metagenome-assembled genomes were recovered, with only a few harbouring ARGs. This study enhances our understanding of freshwater microbial community dynamics and antibiotic resistance profiles, highlighting the need for continued ARGs monitoring. [ABSTRACT FROM AUTHOR]

The present study evaluates the application of heterogeneous catalytic ozonation for the removal of micropollutants from wastewater effluent in a pre-industrial-scale unit, consisting of a post-filtration, an ozone dilution, a catalytic ozonation, and a final biological stabilization step. The important step of ozone dilution is optimized by the use of a hollow fiber membrane that minimizes the loss of ozone gas due to the transfer of ozone to the liquid phase mainly by diffusion. It is observed that the efficiency of this sub-system is maximized for the dead-end operation of the membrane and the introduction of ozone gas to the shell side and liquid phase to the lumen side of the membrane module. Under these conditions, the concentration of dissolved ozone is directly dependent on the ratio of ozone gas feed to the wastewater flow subjected to post-treatment. Regarding the removal of MPs, part of their degradation already takes place at this stage (i.e., during ozone dilution), while after the post-treatment of wastewater effluent in the catalytic ozonation bed, the MP degradation yield ranges from 35% up to complete removal, depending on the type and properties of the specific MP. The addition of a final biological filtration bed to the overall treatment unit significantly increased its performance, regarding the removal of MPs, enhancing it by an additional removal rate that can reach up to 30%. [ABSTRACT FROM AUTHOR]

In wastewater treatment intensification, hierarchical control structures are developed to improve the plant's performance. This paper proposes two novel hybrid supervised hierarchical control structures for specifying the dissolved oxygen concentration in the last aerobic reactor of the wastewater treatment plant (WWTP) based on the nitrification rate and the ammonia level in this reactor. These structures combine the optimum disturbance rejection PI control (OPI), adaptive neuro-fuzzy inference system (ANFIS), and genetic algorithms (GA) to reduce energy consumption and operational costs, improve effluent quality, and reduce the number and percentage of times the established maximum concentration of pollutants in the effluent of the WWTP is violated. The proposed control strategy is implemented and evaluated using benchmark simulation model no. 1 (BSM1). The OPI-ANFIS-GA configuration significantly enhances effluent quality in dry, rainy, and stormy weather conditions, reducing total nitrogen violations by 50.17%, 63.35%, and 47.35%, respectively. Then, 6.79% and 7.12% of aeration energy and 1.44% and 1.46% of operational costs are reduced in dry and rain weather conditions. The OPI-ANFIS configuration enhanced significant energy savings and a cost reduction in storm weather conditions. Both configurations led to a 49.89% decrease in total suspended sludge (TSS) during stormy weather conditions. The proposed controller significantly improves the performance of the WWTP in all weather scenarios compared to the default controller and similar controllers found in the literature. [ABSTRACT FROM AUTHOR]

Currently large amounts of wastewater are produced by domestic and industrial activities. Discharge of wastewater to the receiving environment without treatment causes significant health and environmental problems. Modeling and optimization of Wastewater Treatment Plants (WWTP) developed to treat domestic wastewater play key roles in determining unit components, design parameters and operation conditions. Several models were proposed to predict the treatment performance in WWTP. The Activated Sludge Model No. 1 (ASM1) is one of the commonly-used standard models developed to better understand removal of carbonaceous and nitrogenous materials. In this study, a WWTP is proposed for domestic wastewater using grit chamber, circular primary and secondary clarifiers, completely-mixed aeration tank, sludge thickener, sludge dewatering and anaerobic digestion processes together. The WWTP was modeled with ASM1 noting the topographic and meteorological features of the city. The treatment performances with wastewater temperatures of 10°C and 20°C were investigated for this plant, operating at high elevation. Removal efficiencies at 20°C were 95.7%, 92.2%, 97.9% and 99.2% for MLSS, COD, BOD and NH4, while effluent concentrations were 14.83, 48.51, 6.55 and 0.3 mg L-1, respectively. At 10°C, removal efficiencies were 88.9%, 88%, 93.2%, and 26.9%, while effluent concentrations were 38, 75, 21.83 and 26.13 mg L-1, respectively. A clear reduction was observed in nitrogenous material removal at low temperatures. Additionally, keeping dissolved oxygen concentration in the aeration tank at 1.5 mg L-1 with PID control increased nitrification efficiency by 30%. The findings reveal the importance of modeling studies during planning of WWTP.

Location of Bahagia Market on K.H. Abdurrahman Wahid streets, Kubu Raya regency. Bahagia Market has been operation for two years but doesn’t have wastewater treatment, the liquid waste product is discharged directly into the waters. The purpose of this plan is to knowing the discharge of wastewater generated, so the treatment is adjusted to the quality of wastewater and the available land area, as well as calculating cost budget. Planning methods is area survey, data collection, waste inventory, sampling, quality analysis, calculation of wastewater discharge, planning of wastewater treatment, and calculation of cost budget. The planning results are Bahagia market has 11 stalls, 64 loss and 43 tables with 3 drains. The liquid of wastewater come from the washing of vegetables, fish, meats, and poultry. BOD, COD, TSS, and ammonia parameters are above quality standards, while total coliform, fat and oil are below quality standards. Wastewater treatment project for the 5 next years starting from 2023 to 2027 with wastewater effluent is 8640 liters/days. Treatment unit use are sump well, bar screen, rotating biological contactor, settling basins, disinfection tub, and sludge drying bed with a land area of 5 m2 and a cost budget of Rp. 69,315,479.

The intricate hydrological processes elucidating the interplay between rainfall and flow manifest through rainwater's traversal along diverse routes, encompassing surface runoff and subsurface flow. While the foundational association between these entities is discernible, the convoluted intricacies characterizing this correlation defy straightforward comprehension. Examining the data between 2019 and 2022, the average daily sewage outflow was 12,518 m3/d, with occasional peaks of up to 50,440 m3/d. The wastewater treatment plant's capacity of 35,000 m3/d was usually not exceeded. Overall, average daily sewage outflows varied between 11,716 m3/d and 13,969 m3/d during the studied period. Comprehending this interrelationship holds pivotal significance for the optimization of water-resource-management strategies. A moderate correlation (r = 0.42) between daily rainfall levels and sewage discharge was found in the dataset covering 2018–2023. When categorizing daily rainfall into groups labelled “A” through “G” and comparing them to sewage flows, a pattern emerged: Rain-free days in group “A” had the lowest average sewage flow (10,996 m3/d), while heavy rain days in group “G”, had the highest average flow (22,112 m3/d). This observation underscores a significant correlation between intensified rainfall and increased volume of sewage discharge. Through a comprehensive analysis of factors such as sewage composition, meteorological dynamics and chronological sequences, we will gain an enhanced ability to prognosticate and govern sewage systems. The significance of this is heightened within the context of evolving climatic dynamics.

Wastewater treatment must be proactive and sustainable to facilitate an increase in the circularity of water. Therefore, the current approach, based on a linear cycle, must be replaced with a circular economy concept that implements strategies to address the different byproducts in the wastewater treatment sector. In recent years, Nuevo León, Mexico, has encountered high water stress levels, with its main water bodies presenting their lowest levels ever recorded. This study was focused on the wastewater treatment plant Monterrey, which treats the largest volume at the state level. Throughout its operation process, it generates different potential byproducts that are yet to be harnessed to fully. This study developed three proposals using a circular economy approach: the treatment of water for the industrial sector, the use of residual sludge as an organic fertilizer, and the cogeneration of energy from biogas. These proposals can potentially generate benefits regarding the three pillars of sustainability, yielding a closed cycle in the wastewater treatment sector at the national level.

Wastewater treatment plants (WWTPs) are complex systems that must maintain high levels of performance to achieve adequate effluent quality to protect the environment and public health. Artificial intelligence and machine learning methods have gained attention in recent years for modeling complex problems, such as wastewater treatment. Although artificial neural networks (ANNs) have been identified as the most common of these methods, no study has investigated the development and configuration of these models. We conducted a systematic literature review on the use of ANNs to predict the effluent quality and removal efficiencies of full-scale WWTPs. Three databases were searched, and 44 records of the 667 identified were selected based on the eligibility criteria. The data extracted from the papers showed that the majority of studies used the feedforward neural network model with a backpropagation training algorithm to predict the effluent quality of plants, particularly in terms of organic matter indicators. The findings of this research may help in the search for an optimum design modeling process for future studies of similar prediction problems. HIGHLIGHTS Machine learning approaches are effective for modeling wastewater treatment plants (WWTPs).; Artificial neural networks (ANNs) are the most employed in the wastewater treatment sector.; The various ANN structures used in the sector have not been adequately studied.; The systematic review focused on the use of ANN for performance prediction of WWTPs.; The findings are beneficial for future studies with similar prediction problems.;

Water is one of the most basic and essential resources for life and is also a strategic component for the development of the economies of the different countries of the planet. The water sector in the context of ecological transition and the circular economy has enormous economic potential. However, the water resources present in a territory are, in many cases, very limited, and their availability is increasingly restricted. In this respect, current technologies make it possible to generate a whole range of renewable resources. In the case of wastewater treatment plants, in addition to obtaining clean water in sufficient quantity and quality, it is possible to take advantage of multiple other resources generated in the purification processes, such as fertilizers, biogas, bioplastics, and glass, and even recover adsorbents such as enzymes and proteins from wastewater. These resources represent a valuable social, environmental, and economic contribution. The scarcity of some of these resources causes continuous increases in market prices, generating economic tensions between producers and potential users. This work proposes to guide the potential of artificial intelligence (AI)-based methodologies in aspects related to the supply and demand of the resources generated in these infrastructures. Specifically, the use of machine learning (ML) allows for projecting economic scenarios based on multiple variables, such as the quality and quantity of the treated flows, the resources generated in the infrastructures, the current demands, and the prices of substitute goods. This aspect represents a substantial advance in terms of the circular economy since, beyond the technical aspects related to the processes, it ensures a sustainable balance between potential producers and end users. In conclusion, it brings sustainability to the urban water-cycle sector, ensuring the viability of the resources generated. [ABSTRACT FROM AUTHOR]

Wastewater-based surveillance (WBS) for SARS-CoV-2, the virus that causes COVID-19, is a complement to clinical testing that can provide an early warning of community infection. Applying WBS to centralized wastewater treatment plants (WWTPs), otherwise known as water resource recovery facilities, provides an opportunity to collect unbiased viral load information at the community scale. This study focuses on optimizing the sampling strategies from centralized WWTPs to best capture the signal of SARS-CoV-2 in wastewater. From November 2020 to February 2021, a total of 166 grab and 24-h composite wastewater and sludge samples were collected from 3 WWTPs in the Los Angeles (LA) County, with significant differences in size, service area, wastewater composition, and treatment technologies. Results showed that 24-h composite primary influent samples can best represent the trends of SARS-CoV-2 genome concentrations in centralized WWTPs, whereas grab samples showed significant variations in SARS-CoV-2 genome concentrations over a 24-h period. Primary sludge samples showed one log10 higher concentrations of SARS-CoV-2 genomes when compared with primary influent samples. The SARS-CoV-2 genome concentrations in primary influent samples ranged from 2.69 × 102 genome copies (GC)/mL to a high of 4.50 × 103 GC/mL. The virus concentrations in primary sludge ranged from 6.00 × 103 to 9.67 × 104 GC/mL. Ultimately, the SARS-CoV-2 genome concentrations in wastewater and sludge collected from large centralized WWTPs were correlated, and both reflected the general trend of COVID-19 cases in the broader LA metropolitan community. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) have been identified as significant point sources of microlitter particles (MPs) released into the environment. Simultaneously, they play a crucial role in effectively removing a substantial amount of MPs originated from domestic and industrial activities. This study evaluates the presence and chemical composition of MPs within the range of 5 mm to 25 µm in effluents from three WWTPs in the Canary Islands, each undergoing distinct treatment processes: pretreatment (PRET), activated sludge (AS), and membrane bioreactor (MBR) over an eight-month period. The concentrations of MPs exhibited substantial variations in the three effluent samples: 7461.50 ± 3843.87 MP/L in PRET, 32.71 ± 19.55 MP/L in AS, and 9.53 ± 5.21 MP/L in MBR. The predominant forms of MPs were fragments (58–66%) and fibers (27–33%), with the most prevalent size class being within the range of 150–25 µm. The mass concentrations of plastics, analyzed through pyrolysis gas chromatography–mass spectrometry (Pyr-GC/MS), were determined as 123.33 µg/L for PRET, 17 µg/L for AS, and 10 µg/L for MBR. This study revealed a diverse polymer profile, with polyvinyl chloride (PVC) and polyolefins (PE and PP) predominantly present. This work enhances our understanding of MP dynamics and provides a valuable reference for future assessments, aiding in the selection of effective removal technologies. [ABSTRACT FROM AUTHOR]