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Dissolved organic matter (DOM) is important in determining the drinking water treatment and the supplied water quality. However, a comprehensive DOM study for the whole water supply system is lacking and the potential effects of secondary water supply are largely unknown. This was studied using dissolved organic carbon (DOC), absorption spectroscopy, and fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC). Four fluorescent components were identified, including humic-like C1-C2, tryptophan-like C3, and tyrosine-like C4. In the drinking water treatment plants, the advanced treatment using ozone and biological activated carbon (O3-BAC) was more effective in removing DOC than the conventional process, with the removals of C1 and C3 improved by 17.7%-25.1% and 19.2%-27.0%. The absorption coefficient and C1-C4 correlated significantly with DOC in water treatments, suggesting that absorption and fluorescence could effectively track the changes in bulk DOM. DOM generally remained stable in each drinking water distribution system, suggesting the importance of the treated water quality in determining that of the corresponding network. The optical indices changed notably between distribution networks of different treatment plants, which enabled the identification of changing water sources. A comparison of DOM in the direct and secondary water supplies suggested limited impacts of secondary water supply, although the changes in organic carbon and absorption indices were detected in some locations. These results have implications for better understanding the changes of DOM in the whole water supply system to help ensure the supplied water quality.

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The concept of digital twins is one of the fundamental pillars of Industry 4.0. Digital twin allows the realization of a virtual model of a real system, enhancing the relevant performance (e.g., in terms of production rate, risk prevention, energy saving, and maintenance operation). Current literature presents many contributions pointing out the advantages that may be achieved by the definition of a digital twin of a water supply system. The Reference Architecture Model for Industry 4.0 introduces the concept of the Asset Administration Shell for the digital representation of components within the Industry 4.0 ecosystem. Several proposals are currently available in the literature considering the Asset Administration Shell for the realization of a digital twin of real systems. To the best of the authors' knowledge, at the moment, the adoption of Asset Administration Shell for the digital representation of a water supply system is not present in the current literature. For this reason, the aim of this paper is to present a methodological approach for developing a digital twin of a water supply system using the Asset Administration Shell metamodel. The paper will describe the approach proposed by the author and the relevant model based on Asset Administration Shell, pointing out that its implementation is freely available on the GitHub platform.

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Gadolinium-based contrast agents (GBCA) are essential for diagnostic MRI examinations. GBCA are only used in small quantities on a per-patient basis; however, the acquisition of contrast-enhanced MRI examinations worldwide results in the use of many thousands of litres of GBCA per year. Data shows that these GBCA are present in sewage water, surface water, and drinking water in many regions of the world. Therefore, there is growing concern regarding the environmental impact of GBCA because of their ubiquitous presence in the aquatic environment. To address the problem of GBCA in the water system as a whole, collaboration is necessary between all stakeholders, including the producers of GBCA, medical professionals and importantly, the consumers of drinking water, i.e. the patients. This paper aims to make healthcare professionals aware of the opportunity to take the lead in making informed decisions about the use of GBCA and provides an overview of the different options for action.In this paper, we first provide a summary on the metabolism and clinical use of GBCA, then the environmental fate and observations of GBCA, followed by measures to reduce the use of GBCA. The environmental impact of GBCA can be reduced by (1) measures focusing on the application of GBCA by means of weight-based contrast volume reduction, GBCA with higher relaxivity per mmol of Gd, contrast-enhancing sequences, and post-processing; and (2) measures that reduce the waste of GBCA, including the use of bulk packaging and collecting residues of GBCA at the point of application.Critical relevance statement This review aims to make healthcare professionals aware of the environmental impact of GBCA and the opportunity for them to take the lead in making informed decisions about GBCA use and the different options to reduce its environmental burden.Key points• Gadolinium-based contrast agents are found in sources of drinking water and constitute an environmental risk.• Radiologists have a wide spectrum of options to reduce GBCA use without compromising diagnostic quality.• Radiology can become more sustainable by adopting such measures in clinical practice.

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Ultrafiltration (UF) technology is widely used in secondary water supply systems (SWSS) to provide high-quality drinking water. However, the challenge of severe membrane fouling, which leads to frequent cleaning requirements, makes UF maintenance intensive. In this study, we tried to validate the feasibility of achieving zero fouling without the need for cleaning in the UF for SWSS, i.e., the fouling resistance can be maintained for a very long time without any increase. We operated dead-end UF systems at different fluxes, both with and without residual chlorine, and monitored the formation of fouling layers during filtration. The results demonstrated the successful achievement of zero fouling under a flux of 10 L/(m2 h) in the absence of chlorine, evidenced by no increase in transmembrane pressure for three months. This zero-fouling phenomenon was attributed to the formation of a self-regulating biofouling layer. This biofouling layer could degrade the deposited foulants and featured a loose morphology, facilitated by microbial activities in the cake layer. Although residual chlorine reduced the fouling rate by half at a flux of 30 L/(m2 h), it hindered the achievement of zero fouling at the lower flux of 10 L/(m2 h), due to its inhibitory effect on microbial activity. Intermittent operation of UF was effective in achieving zero fouling at higher fluxes (e.g., 30 L/(m2 h)). This benefit was primarily ascribed to the biodegradation of accumulated foulants and the expansion of biofouling layer during the pause of the intermittent filtration, which prompted the formation of biofouling layers with loose structure and balanced composition. To the best of our knowledge, this study is the first attempt to achieve zero fouling in UF for SWSS, and the findings may offer valuable insights for the development of cleaning-free and low-maintenance membrane processes.

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This study examined the factors that affect the private sectors' willingness to invest in rural water supply. The study applied a mixed methods approach, including an overview of relevant studies, expert consultation, exploratory factor analysis using SPSS software, and a fuzzy-analytic hierarchy process to identify and evaluate the factors applicable to Ha Nam province in Vietnam. Some factors were distinguished that are significant to private investors' rural water supply investment decisions, including tax incentive policy, policies to support preferred access to loans and credit, a state risk-sharing mechanism, a mechanism to adjust water price, community support, high community demand for clean water, and input water quality. In addition, the study constructed an investment attractiveness index to evaluate the attractiveness of private sector investment for two typical rural water supply projects in Ha Nam province. This index can be used as a basis for the government to design appropriate incentives to attract investment from private investors and construct an investment attractiveness map.

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The energy required for various processes in the water cycle can have significant economic and environmental impacts. Therefore, efficient energy management in urban water supply systems is crucial for a sustainable operation. By installing energy recovery technologies in these facilities, it is possible to reap the benefits of the infrastructure design by saving energy. In this study, a new methodology to assess the energy recovery at the inlets of district metered areas is presented, considering the city of Murcia (Spain) as case study. This methodology is based on creating a detailed model of city water supply system and calibrating such model with an experimental campaign of measurements. Then, the assessment of the hydraulic potential recovery is analysed through two different energy estimators, one considering the minimum available net head and the other assuming a variable net head. Results show that there are several points where turbines could be installed, most of them recovering in between 1000-5000 kWh, which could be used to cover the yearly energy consumption of about 24-120 m2 of a school or 10-50 traffic lights of such area. Moreover, in some points it could be recovered up to 14500 kWh. Even though these values are not high, the energy recovered could be used for self-consumption of nearby electrical loads, at the time that reduces the pressure in the system, thus leading to leak reductions. Moreover, this kind of energy recovery does not reduce the potential of other proposals for upstream energy recovery, such as replacing pressure reduction valves with turbines instead. The scripts developed to apply the proposed methodology are available in EPANET-Octave file exchange for the researcher community.

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The main purpose of this study was to evaluate the suitability of groundwater for sustainable drinking and irrigation purposes using various indices, such as the nitrate pollution index, agriculture suitability index (ASI), non-carcinogenic human risk assessment (NCHRA), and radial basic function (RBF) model. The novelty of the present study is to develop the ASI model and integrate with RBF model to identify the highly dominating parameter in chemical equilibrium of groundwater. Results showed that >85% of sample locations were suitable for drinking purposes, and the nitrate concentration in groundwater had a negative impact on the overall quality of water. Approximately 12 and 19 sample locations were contaminated owing to the high nitrate concentrations in the study region. The NCHRA study identified that approximately 8.5%, 27.28%, 29.54%, 40.40%, and 28.20% of area was excessively affected during the winter compared to summer season for people 6 to 12 y, 13 to 19 y, 20 to 29 y, 30 to 65 y, and >65 y of age. The RBF model shows that the R2 values for each season were 0.84 and 0.85 during summer and winter, respectively. The north-east and central parts of the study region were found to be more contaminated. The present study identified that, pathway of nitrate contaminant from the agriculture field towards to the sample locations. Overall, parent rock weathering, carbonate ion dissolution, and infiltration of rainwater and leachate from municipal waste dumping yards were the dominant factors influencing the chemical composition of groundwater. The present study achieved the vibrant knowledge about source of contamination, health effect on human body and impact on agriculture uses to develop the cleaner water supply system. The study results will be helpful in enhancing the sustainable action plan for water management in the study area.

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Water quality extremes, which water quality models often struggle to predict, are a grave concern to water supply facilities. Most existing water quality models use mean error functions to maximize the predictability of water quality mean value. This paper describes a composite quantile regression neural network (CQRNN) model, which simultaneously estimates non-crossing regression quantiles by minimizing the composite quantile regression error function. This method can improve the prediction of extremes. This paper evaluates the performance of CQRNN for predicting extreme values of turbidity and total organic carbon (TOC) and compares with quantile regression (QR), linear regression (LR), and k-nearest neighbors (KNN) in an application to the Hetch Hetchy Regional Water System, which is the primary water supply for San Francisco, CA. CQRNN is superior to QR, LR, and KNN for predicting the mean trend and extremes of turbidity and TOC, especially for the non-Gaussian turbidity data. The performance of CQRNN is the most stable relative to other methods over different training sample sizes.

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In rural areas, low-technology radon reduction methods are essential for safe access to clean groundwater. This study monitored the radon reduction rates in small-scale groundwater-based water supply systems in the Republic of Korea and also presented a mass balance equation using physical environmental conditions from three radon reduction methods. The mass balance results showed that the radon reduction rate would be affected by the groundwater flow rate (m3/day), capacity of the drainage facility (m3), surface area of air-water interface (m2), air-water ratio (dimensionless), and ventilation system. The radon reduction order was as follows: simultaneously powered and non-powered aeration method (free-fall (60.0 %) > aeration (19.6 %) > decay (0.9 %) > diffusion (0.2 %)), low-technology non-powered aeration (free-fall (60.0 %) > decay (3.4 %) > diffusion (0.9 %)), and only storage (free-fall (35.5 %) > decay (4.4 %) > diffusion (1.1 %)). Overall, non-powered aeration using the maximum free-fall effect has the potential for use as a low-technology reduction method and natural decay during water storage is the most important factor underlying seasonal variations in the reduction effect.

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With increased understanding of the differences in toxicity between species of haloacetic acids (HAAs) and the possibility of more stringent regulations, the ability to predict individual HAA species formation is important. Nine different haloacetic acids are regulated and their total concentration is referred to as HAA9. A mathematical model to predict concentrations of HAA species was proposed and tested using independent data sets. The amount of HAA9 formed per unit amount of chlorine consumed (µg-HAA9/mg-consumed chlorine) remained constant throughout the reaction times in each sample. Similarly, the fraction of a given HAA species largely remained constant during most of the reaction time. Thus, each HAA species was assumed to have its own yield with respect to consumed chlorine in a given water sample. The parallel second-order (2R) model describing chlorine decay kinetics was then extended to predict HAA species formation kinetics. The combined chlorine and HAA species model closely predicts all tested HAA species and its sum with standard error ≤ 5 µg/L. Within the tested waters having Cl2/N mass ratio ≥ 10.7 (g-Cl2/g-N), ammonia did not impact the mass yield. The mass yield of each HAA species can be calculated from three measurements (e.g. at 0, 4 and 24 h) of HAA species and chlorine. Once the yield is known, HAA species concentrations could be predicted for up to 120 h with only chlorine measurements. The model extends the previous work of predicting the trihalomethane species formation kinetics to HAA species formation kinetics. Further research is needed to understand how the yield varies with source water quality, treatment and in distribution systems.

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INTRODUCTION: Legionella disease can manifest as severe respiratory tract infection with a high mortality rate and is sometimes associated with a hospital outbreak by a contaminated water supply. A patient with breast cancer admitted about a month before. High fever was observed 18 days after admission and the Legionella antigen test showed the positive result. METHODS: Due to the incidence of Legionella infection, we demonstrated the active surveillance of Legionella contamination in the entire hospital. RESULTS: Cultures of her environmental samples revealed that hot water in two bathrooms were contaminated with Legionella. In our hospital, the hot water is heated and pumped up on the roof and distributed to each room. The contaminated bathrooms were related to the same plumbing. Therefore, we further collected samples throughout the hot water system. Legionella was not detected in the central part of the system. However, we detected Legionella in the hot water sampled from other five rooms, which were also associated with the same plumbing of the two bathrooms. The temperature and chlorine concentration of the hot water were not high enough to inactivate Legionella at the end of the plumbing. After the adjustment of the water temperature and chlorine concentration, Legionella became undetectable. Our prompt and active surveillance successfully identified the plumbing of the hot water system as the source of Legionella contamination and took precautions against future outbreaks. CONCLUSIONS: Monitoring of water temperature and chloride concentration at the end of the hot water circulation is important to prevent nosocomial Legionella disease.

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Urban water distribution networks (WDNs) in developing economies often refrain from investing in sensor-based leakage management technologies due to financial constraints and other techno-managerial issues. Thus, this study proposes a generalized decision support framework based on network sensitivity analysis (NSA) and multi-criteria decision-making (MCDM) to assess the prospect of effective leakage control through robust sensor placement in existing deficient WDNs. Four sensitivity parameters are formulated for NSA to ascertain the pressure response of the potential sensor positions for diverse hydraulic and leak scenarios. Subsequently, selecting the optimal number of sensors and their relative positions within the WDN is framed as an MCDM problem that entails the simultaneous maximization of Euclidean distances among the potential sensor positions and the leak-induced pressure residuals obtained at these sensors. The proposed methodology is developed on a numerical benchmark network assuming ideal conditions, and its applicability is verified on a sensor-equipped experimental network considering realistic system uncertainties. The outcome of this study aims to provide an insightful understanding of the system behavior that governs its leak localization potential and ascertain the practical challenges of sensor-based leakage monitoring in existing WDNs. Decision-makers of resource-strained utilities can beneficially utilize the proposed framework to assess the environmental and cost trade-offs of employing sensor-based technologies for leakage management and proactive decision-making before its actual implementation.

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Contrast media are essential for diagnostic and interventional procedures. Iodinated contrast media are the most commonly used agents, with CT requiring the largest overall quantities. Data show that these iodinated contrast media are found in sewage water, surface water and drinking water in many regions in the world. Because standard drinking water purification techniques only provide poor to moderate removal of iodinated contrast media, these substances pose a problem for drinking water preparation that has not yet been solved. There is a growing body of evidence supporting the negative environmental effects of iodinated contrast media via their breakdown products. The environmental impact of iodinated contrast media can be mitigated by measures focusing on the application of contrast media or the excretion of contrast media. Measures with respect to contrast application include reducing the utilization of contrast media, reducing the waste of contrast media and collecting residues of contrast media at the point of application. The amount of contrast media excreted into the sewage water can be decreased by introducing urine bags and/or special urine collection and waste-water processing techniques in the hospital. To tackle the problem of contrast media in the water system in its entirety, it is necessary for all parties involved to cooperate, from the producer of contrast medium to the consumer of drinking water. This paper aims to make health professionals aware of the opportunity to take the lead now in more conscious decisions regarding use of contrast media and gives an overview of the different perspectives for action.

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Microplastic (MP) pollution has received widespread attention; however, its occurrence and distribution in water supply systems, particularly in pipe scales, remains unclear. In this study, MPs were observed in water and pipe scale samples from the drinking water treatment plant (DWTP) and distribution system (DWDS), respectively. The MP concentrations ranged from 13.23 to 134.79 n/L and 569.99 to 751.73 n/kg in the water and pipe scale samples, respectively. The predominant particles in the pipe scales (50-100 µm) were smaller than those in the water samples (> 200 µm). Overall, MP fragments were the most abundant. Of all the identified MPs, nylon and polyvinyl chloride were predominant in the water and pipe scale samples, respectively. Furthermore, the DWTP and DWDS both prevented MPs from entering the tap water, thereby reducing their risk. The results of this study provide direct evidence for the strong adsorption of MPs onto pipe scales, indicating that pipe scale stability may play a role in improving water quality and security. However, the abundance of MPs in pipe scales cannot be ignored. Additionally, the results provide valuable background information on MP pollution in water supply systems.

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Monitoring of disinfection by-products (DBPs) in water supply system is important to ensure safety of drinking water. Yet it is a laborious job. Developing predictive DBPs models using simple and easy parameters is a promising way. Yet current models could not be well applied into practice because of the improper dataset (e.g. not from real tap water) they used or involving the parameters that are difficult to measure or require expensive instruments. In this study, four simple and easy water quality parameters (temperature, pH, UVA254 and Cl2) were used to predict trihalomethane (THMs) occurrence in tap water. Linear/log linear regression models (LRM) and radial basis function artificial neural network (RBF ANN) were adopted to develop the THMs models. 64 observations from tap water samples were used to develop and test models. Results showed that only one or two parameters entered LRMs, and their prediction ability was very limited (testing datasets: N25 = 46-69%, rp = 0.334-0.459). Different from LRM, the prediction accuracy of RBF ANNs developed with pH, temperature, UVA254 and Cl2 can be improved continuously by tweaking the maximum number of neuron (MN) and Gaussian function spread (S) until it reached best. The optimum RBF ANNs of T-THMs, TCM and BDCM were obtained when setting MN = 20, S = 100, 100.1 and 60, respectively, where the N25 and rp values for testing datasets reached 85-92% and 0.813-0.886, respectively. Accurate predictions of THMs by RBF ANNs with these four simple and easy parameters paved an economic and convenient way for THMs monitoring in real water supply system.

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Pathogenic Legionella species grow optimally inside free-living amoebae to concentrations that increase risks to those who are exposed. The aim of this study was to screen a complete drinking water system and cooling towers for the occurrence of Acanthamoeba spp. and Naegleria fowleri and their cooccurrence with Legionella pneumophila, Legionella anisa, Legionella micdadei, Legionella bozemanii, and Legionella longbeachae. A total of 42 large-volume water samples, including 12 from the reservoir (water source), 24 from two buildings (influents to the buildings and exposure sites (taps)), and six cooling towers were collected and analyzed using droplet digital PCR (ddPCR). N. fowleri cooccurred with L. micdadei in 76 (32/42) of the water samples. In the building water system, the concentrations of N. fowleri and L. micdadei ranged from 1.5 to 1.6 Log10 gene copies (GC)/100 mL, but the concentrations of species increased in the cooling towers. The data obtained in this study illustrate the ecology of pathogenic Legionella species in taps and cooling towers. Investigating Legionella's ecology in drinking and industrial waters will hopefully lead to better control of these pathogenic species in drinking water supply systems and cooling towers.

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Overuse of antibiotics is accelerating the spread of resistance risk in the environment. In drinking water supply systems, the effect of antibiotics on the resistance of biofilm is unclear, and there have been few studies in disinfectant-containing systems. Here, we designed a series of drinking water supply reactors to investigate the effects of antibiotics on biofilm and bacteria in the water. At low concentrations, antibiotics could promote the growth of bacteria in biofilm; among the tested antibiotics (tetracycline, sulfadiazine and chloramphenicol), tetracycline had the strongest ability to promote this. And the antibiotic resistant bacteria (ARB) could inhibit the growth of bacteria in drinking water. Results have shown that antibiotics enhanced the bacterial chlorine resistance in the effluent, but reduced that in the biofilm. Furthermore, metagenomic analysis showed that antibiotics reduced the richness of biofilm communities. The dominant phyla in the biofilm were Proteobacteria, Planctomycetes, and Firmicutes. In tetracycline-treated biofilm, the dominant phylum was Planctomycetes. In sulfadiazine- and chloramphenicol-treated groups, bacteria with complex cell structures preferentially accumulated. The dominant class in biofilm in the ARB-added group was Gammaproteobacteria. The abundance of antibiotic resistant genes (ARGs) was correlated with biofilm community structure. This study shows that antibiotics make the biofilm community structure of drinking water more resistant to chlorine. ARGs may be selective for certain bacteria in the process, and there may ultimately be enhanced chlorine and antibiotic resistance of effluent bacteria in drinking water.

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INTRODUCTION: Typhoid incidence in children is higher in urban areas than in rural areas of Bangladesh. This study examined whether healthy urban children harboured higher levels of Salmonella genes than healthy rural children. METHODOLOGY: Stool samples from 140 children were studied: 70 from rural areas and 70 from urban metropolitan areas. RESULTS: The stool samples of urban children contained more Salmonella genes (median 4, IQR 3-4) than those of rural children (median 3, IQR 3-4). This suggests that urban Bangladeshi children have more Salmonella genes in their guts than rural children. Especially, in those under 12 months of age, the Salmonella gene prevalence in urban children was unique. They had more Salmonella genes (median 4, IQR 4-5) than rural children in the same age group (median 3, IQR 2.5-4). We also found more Salmonella genes in urban children who drank tap water (median 4, IQR 3-5) than in rural children whose water source was tube well water (median 3, IQR 2-4) and boiled pond water (median 3, IQR 3-3.5). However, there was no significant difference of Salmonella genes between urban children who drank tap-water and children whose water source was a tube well (median 4, IQR 3-4). CONCLUSIONS: These data suggest that the urban environment, including the drinking water supply system, increases the likelihood of healthy children in urban areas harbouring more potentially pathogenic Salmonella organisms in their gut than found in rural healthy children.

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Drinking water provision has been a constant challenge in the Sahrawi refugee camps, located in the desert near Tindouf (Algeria). The drinking water supply system is itself divided in three zones which pump groundwater from different deep aquifers. It is equipped with reverse osmosis plants and chlorination systems for treating water. The allocation of water supplied to the Saharawi refugees for human consumption in 2016 has been estimated at between 14 and 17 L/person/day on average. This supplied water volume is below recommended standards, and also below the strategic objective of the Sahrawi government (20 L/person/day). Yet the local groundwater resources are huge in comparison with estimated consumption, and hence there is great potential for increasing the supplied volume through effecting improvements in the supply system. The physico-chemical quality of the raw and supplied water between 2006 and 2016 has been assessed according to Algerian standards for human consumption. The raw water of two zones of the supply system presents a very high conductivity and high concentrations of chloride, nitrate, fluoride, sulfate, sodium, calcium, potassium and iodide concentrations of natural origin, which may entail health risks. The treatment of water in a reverse osmosis plant greatly improves its quality and osmosed water met the standards. However, the supply of osmosed and raw water needs to be combined in Zone 1, to avoid an excessive reduction in water volume, and the supplied raw water poses a risk to the health of the refugees. The present study provides an example of a drinking water supply system under extreme drought conditions and in the political and social conditions of a refugee camp. Furthermore, it establishes a reference for supplied water allocation and quality in the Sahrawi refugee camps.

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Halobenzoquinones (HBQs) are an emerging class of drinking water disinfection byproducts (DBPs) that have been frequently detected in drinking water and are highly relevant to bladder cancer. Among the studied HBQs, 2,6-dichloro-1,4-benzoquinone (DCBQ) had the highest detection frequency and concentrations in drinking water. However, compared to other countries, the studies on HBQs that are being conducted in China, especially those on HBQs in drinking water, are not sufficient. Therefore, the concentrations of DCBQ in the Tianjin drinking water supply system were investigated in two seasons (winter and summer), and the risk that is posed by DCBQ in drinking water was evaluated for the first time. In addition, since HBQs are prone to hydrolysis in neutral and alkaline environments, identification of the hydrolytic characteristics of DCBQ at various pH values and in the real water environment is essential for better describing the environmental behavior of DCBQ; hence, the hydrolysis characteristics of DCBQ in phosphate buffers with various pH values and in four water samples were also examined in our study. The results demonstrated that DCBQ was widely detected in the drinking water treatment process and distribution systems, and the average concentration in our study (12.0 ng/L) was at a moderately high level compared with the reported concentration of DCBQ in the drinking water distribution networks. The risk quotient (RQ) of DCBQ is equivalent to that of trihalomethanes (THMs); thus, the relatively low concentrations of DCBQ should also be considered. Furthermore, the results demonstrated that the hydrolysis of DCBQ follows first-order reaction kinetics, the reaction rate accelerates as the pH of the phosphate buffer system increases, and the rate of hydrolysis of DCBQ in drinking water is affected not only by the pH but also by other environmental factors, such as the organic matter concentration. Therefore, further investigation is necessary to identify the main factor of DCBQ hydrolysis in real water environments.

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