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.

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.

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.

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.

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.

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.

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.

BACKGROUND: 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.

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.

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.