The aim of this work was to evaluate a smart electronic tongue device as an alternative for qualitative and quantitative monitoring of drinking water. The smart electronic tongue consisted of a voltametric polypyrrole sensor array, linked with a multi-channel electronic system (multipotentiostat) based on PSoC (programable system on chip) technology controlled by a smartphone with a data acquisition and control app. This device was used in the monitoring of drinking water from the Sincelejo city water supply system; also, water samples collected and analyzed by the public health agency were used. The voltammetric measurements carried out with the smart electronic tongue showed cross-sensitivity of the polypyrrole sensor array, which allowed the discrimination of the samples through of principal component analysis by artificial neural networks. In addition, the voltammetric signals registered with the smart electronic tongue allowed, through partial least square (PLS) by artificial neural networks analysis, estimating the concentrations of some important analytes in the evaluation of the physicochemical quality of drinking water with R2 values higher than 0.70. The results allowed to conclude that the smart electronic tongue can be a valuable analytical tool that allows, in a single measure, to perform qualitative and quantitative chemical analysis (alkalinity, calcium, residual chlorine, chlorides, total hardness, phosphates, magnesium, and sulfates), it is also a fast, portable method that can complement traditional analyzes.
In this research, reliability indicators of water distribution networks were evaluated under pipe failure conditions. The case studies included two benchmark networks and one real-life water distribution network in Iran with more hydraulic constraints. Some important reliability indicators were presented, such as resilience index, network resilience, modified resilience index, and minimum surplus head index. GANetXL was used to do the one-objective and two-objective optimization of the previously mentioned water distribution networks in order to not only minimize the cost but also maximize the reliability indicators. Moreover, the results of a statistical analysis for each pipe were used to determine the sensitive pipes that were of the most failure probability. GANetXL is an optimization tool in the Microsoft Excel environment and works based on a genetic algorithm. GANetXL has the capability of being linked to EPANET (hydraulic simulation software). The results obtained clearly showed that network resilience index was poor performance when compared with the other indexes under pipe failure conditions, especially in real-life networks that include small pipe diameters. It was also showed that if a water distribution network was optimized only in terms of cost, then there would be an unacceptable pressure drop at some nodes in case of pipe failure.
Drinking water distribution networks form an essential part of modern-day critical infrastructure. Sectorizing a network into district metered areas is a key technique for pressure management and water loss reduction. Sectorizing an existing network from scratch is, however, an exceedingly complex design task that designs in a well-studied general mathematical problem. Numerical optimization techniques such as evolutionary algorithms can be used to search for near-optimal solutions to such problems, but doing so within a reasonable time frame remains an ongoing challenge. In this work, we introduce two heuristic tricks that use information of the network structure and information of the operational requirements of the drinking water distribution network to modify the basic evolutionary algorithm used to solve the general problem. These techniques not only reduce the time required to find good solutions but also ensure that these solutions better match the requirements of drinking water practice. Both techniques were demonstrated by applying them in the sectorization of the actual distribution network of a large city.
Energy use in drinking Water Supply System represents an important part of the global energy consumption across all sectors. This portion is expected to raise, due to the raising demand and the recourse to unconventional water resources. For the water utilities, most of their operating costs are related to energy consumptions, especially the consumption of pumping systems. The main objective of this study is to produce a model which reflects the real behaviour of a pumping system to help in taking decisions on which pump to use First and which one to replace in case of a limited renovation. In order to do so, Multiple Linear regression was adopted to model the ratio kWh/m32 = 0.91), so it can be a good estimator as the calculated ratio is close to the experimental one. The Novelty of this approach is to have a model which takes into account the real behaviour of the system whereas most of the studies focus on the pump scheduling problem.
This study investigates the variational effect of climate factors on the productivity of a basin-type solar still during the harmattan season under the tropical savanna climate. The study was extended to examine the influences of selected climatic, operational, and design (COD) parameters on productivity. Additionally, the efficiency of solar still in removing water impurities during harmattan was also investigated. Explorative data and statistical analysis, and laboratory testing methods were used for these investigations. Results show that seasonal effects of harmattan can either increase or lower productivity. The effect of wind speed on productivity was not clearly defined during the harmattan season. Although high irradiation is essential for increased productivity, its effect is modified by other factors. Water temperature is the most significant to productivity amongst selected factors studied via the design of experiment (DOE). Moreover, the effect of harmattan on the water quality produced was not established. The main contribution of this work is the insights generated for both qualitative and quantitative reliability performance of a basin-type solar still under prevailing climate conditions.
The objective of this study is to prepare a cellulose paper that was impregnated with silver nanoparticles (AgNPs) for the purpose of water purification (disinfection and filtration). AgNP papers were prepared by chemical reduction of silver nitrate (AgNO3) with various concentrations (0.005 M, 0.015 M, 0.03 M, and 0.05 M) using sodium borohydride (NaBH4) as a reducing agent. Two ratios for
Turbidity is the most important parameter needed to check the status of drinking water, as it is an integrated parameter because its high values indicate high values of other parameters related to water quality. Coagulation and flocculation are the most essential processes for the removal of turbidity in drinking water treatment plants. Using alum coagulants increases the aluminum residuals in treated water, which have been linked to Alzheimer's disease pathogenesis.
In this paper, a hybrid algorithm (GA-ANN) used to predict the turbidity values in the drinking water purification plant in Al Qusayr was used.
The models were constructed using raw water data: turbidity of raw water, pH, conductivity, temperature, and coagulant dose, to predict the turbidity values coming out of the plant.
Several models built and fitness detected for each model, the network with the highest fitness was selected, and then a hybrid prediction network was constructed.
The selected network was the most able to predict turbidity of the outlet with high accuracy with a correlation coefficient (0. 9940) and a root mean square error of 0.1078.
And 4 equations for determining the value of the residual aluminum was obtained using Gene expression method, and the best equation produced results with very good accuracy, in this regard it can be referred to RMSE = 0.02 R = 0.9 for the best model.
By accurate predicting of pipe bursts, it is possible to schedule pipe maintenance, rehabilitation and improve the level of services in water distribution networks (WDNs). In this study, we aimed to implement five artificial intelligence and machine learning regression models such as multivariate adaptive regression splines (MARS), M5' regression tree (M5'), Least square support vector regression (LS-SVR), fuzzy regression based on c-means clustering (FCMR) and regressive convolution neural network with support vector regression (RCNN-SVR) for predicting pipe burst rate and evaluating the performance of these models. The most effective parameters for regression models are pipes age, diameter, depth of installation, length, average and maximum hydraulic pressure. In the present study, collected data include 158 cases for polyethylene (PE) and 124 cases for asbestos cement (AC) pipes during 2012-2019. The results indicate that the RCNN-SVR model has a great performance of pipe burst rate (PBR) prediction.
In Ethiopia (Ziway town) an excess fluoride (≥ 1.5 mg/L) consumption in drinking water (ground water and Lake Ziway) sources causes a health problem on the communities. The surrounding of inhabitant's peasant farmers of drinking water sources was extremely relying on this polluted fluoride concentration of water. This investigation was focused on defluoridation of drinking water by natural zeolite modified with a cationic surfactant in a batch system and Hexadecy Trimethyl Ammonium Bromide were used for zeolite modification. The Batch experiments also conducted to test for preferential removal of fluoride from water by surfactant-modified zeolite. The zeolite treatments had an aggregate size of 1.4 to 2.4 mm. The cationic surfactant-modified zeolite, and raw zeolite were used in all experiments. The removal efficiency of the treatment was influence by pH of solution (5.5 ± 0.2–8.5 ± 0.2), initial concentration of fluoride (1–10 mg/L), dose of surfactant-modified zeolite (2.5–18 g/L), contact time (30–180 Minute), and effect of temperature was investigated. The study investigated that, at the constant Blank of 10 mg/L, 5 g/L of Hexadecy Trimethyl Ammonium Bromide dosage noted the highest fluoride removal potential at the end of the 3hours runtime: Na-LSX (88.4 %), Na-LTA (64.6 %) and ZR (79.8 %). Incompatible to this reflection, the model waters with pH maintained at 5.5 ± 0.2 and 6.5 ± 0.2 verified rapid fluoride removal (89.7 % and 72.3 % respectively) within the first 60 minutes of runtime.
The study evaluates the hydraulic analysis of water supply distribution network using water GEMS v8i. which used for modeling and Simulation of hydraulic parameters in the distribution networks. The hydraulic parameters which analyzed by using this software were junction pressure, velocity of water in networking system, and nodal demands and the overall result of water supply did not satisfied demand. The water distribution system has been analyzed for steady state and extended period simulation for the present population scenario for intermittent water supply using water Gems v8i. About 14 percent of the total number of nodes analyzed had negative pressures while 68 percent of the nodes had pressures less than the adopted pressure for the analysis. These negative pressures indicate that there is inadequate head within the distribution network for water conveyance to all the sections. In the same manner 85.6 percent of flow velocities in the pipes were within the adopted velocity while around 14.4 percent of the velocities exceeded the adopted velocity. The results in this study revealed that the performance of the water distribution system of under current demand is inefficient.
The enormous problems caused by the scarcity of potable water and the transmission of waterborne diseases such as cholera, dracunculiasis, hepatitis, typhoid and filariasis in some parts of Nigeria have created a public health concern. Every day thousands of lives are lost due to contact with waterborne diseases. The insufficient medical resources available in developing countries are deployed towards the treatment of waterborne diseases that can easily be avoided if potable water can be made available. This study seeks to investigate the purification of four different water samples (namely water from flowing rivers, freshly dug well or groundwater, rainwater from the rooftops and heavily polluted dirty water) consumed by the people in the local community using a solar desalination method. A single basin solar still was constructed, and experimental studies were carried out to determine the influence of solar insolation and temperature variations on the yield of the distillate for both the passive and active solar stills tested. The quality of the distillate was tested by measuring the total dissolved solid (TDS) and electrical conductivity (EC) and later comparing it to the World Health Organization (WHO) standard for drinkable water. The values obtained after desalination fall within the acceptable/tolerable range for TDS and EC, in accordance with the WHO standard for drinkable water. This analysis provides an indigenous distillation method to enhance the production of drinkable water at a low cost.
It is common for bottled water and other assorted drinks to be seen displayed outside stores and in the sun in most parts of Nigeria. The country is mostly hot year-round, and over the course of the year, temperatures can rise to as high as 40 ∘C around March–April in the study area. The leaching effect of chemicals from polyethylene terephthalate (PET) bottled water was investigated for five commercially available bottled water brands. Temperature, pH, antimony, bisphenol A (BPA), and nitrate levels were measured on days 0, 14, and 28 for control samples and samples exposed to direct sunlight, using destructive sampling technique. Antimony was not detected in brands A, B, and E in the baseline measurement at day 0, while brands C and D had low values; after 28 d all the control samples still had antimony levels within the United States Environmental Protection Agency (US EPA) standard. Meanwhile, all the samples exposed to sunlight exceeded US EPA standard levels at 14 and 28 d, except brand A which was within limit at 14 d with value of 4.59 µg L−1. All control and exposed samples were below the European Union Drinking Water Directive (EU DWD) total daily intake (TDI) of BPA (0.05 mg per kilogram of body weight)−1 d−1. Values obtained for nitrate showed that all control samples did not exceed the US EPA guideline level for nitrates in drinking water for days 0, 14, and 28, while three of the samples, i.e. brands C, D, and E, exceeded the guideline level at day 28. Exposure of bottled water to sunlight was seen to impair the quality of the water for consumption.
Natural particles are frequently applied in drinking water treatment processes in fixed bed reactors, fluidised bed reactors, and sedimentation processes to clarify water and to concentrate solids. When particles settle, it has been found that, in terms of hydraulics, natural particles behave differently when compared to perfectly round spheres. To estimate the terminal settling velocity of single solid particles in a liquid system, a comprehensive collection of equations is available. For perfectly round spheres, the settling velocity can be calculated quite accurately. However, for naturally polydisperse non-spherical particles, experimentally measured settling velocities of individual particles show considerable spread from the calculated average values.
This work aims to analyse and explain the different causes of this spread. To this end, terminal settling experiments were conducted in a quiescent fluid with particles varying in density, size, and shape. For the settling experiments, opaque and transparent spherical polydisperse and monodisperse glass beads were selected. In this study, we also examined drinking-water-related particles, like calcite pellets and crushed calcite seeding material grains, which are both applied in drinking water softening. Polydisperse calcite pellets were sieved and separated to acquire more uniformly dispersed samples. In addition, a wide variety of grains with different densities, sizes, and shapes were investigated for their terminal settling velocity and behaviour. The derived drag coefficient was compared with well-known models such as the one of Brown and Lawler (2003).A sensitivity analysis showed that the spread is caused, to a lesser extent, by variations in fluid properties, measurement errors, and wall effects. Natural variations in specific particle density, path trajectory instabilities, and distinctive multi-particle settling behaviour caused a slightly larger degree of the spread. In contrast, a greater spread is caused by variations in particle size, shape, and orientation.In terms of robust process designs and adequate process optimisation for fluidisation and sedimentation of natural granules, it is therefore crucial to take into consideration the influence of the natural variations in the settling velocity when using predictive models of round spheres.The forward osmosis (FO) process has been considered for desalination as a competitive option with respect to the traditional reverse osmosis process. The interfacial polymerization (IP) reaction between two monomers (i.e., m-phenylenediamine, MPD, and 1,3,5-benzenetricarbonyl chloride, TMC) is typically used to prepare the selective polyamide layer that prevents salts and allows water molecules to pass. In this research, we investigated the effect of preparation conditions (MPD contact time, TMC reaction time, and addition of an amine salt) on the FO performance in terms of water flux and salt flux. The results showed that increasing MPD contact time resulted in a significant increase in the water flux and salt flux. However, increasing TMC reaction time caused a decline in both the water flux and the salt flux. The optimum condition that gave the highest water flux (64 L m−2 h−1) was found to be as 5 min for MPD and 1 min for TMC. The addition of an amine salt of camphorsulfonic acid-triethylamine (CSA-TEA) was able to have an apparent effect on the FO process by increasing the water flux (74.5 L m−2 h−1).
Developments such as climate change and a growing demand for drinking water threaten the sustainability of drinking water supply worldwide. To deal with this threat, adaptation of drinking water supply systems is imperative, not only on a global and national scale but particularly on a local scale. This investigation sought to establish characteristics that describe the sustainability of local drinking water supply. The hypothesis of this research was that sustainability characteristics depend on the context that is analysed, and therefore, a variety of cases must be analysed to reach a better understanding of the sustainability of drinking water supply in the Netherlands. Therefore, three divergent cases on drinking water supply in the Netherlands were analysed. One case related to a short-term development (2018 summer drought), and two concerned long-term phenomena (changes in water quality and growth in drinking water demand). We used an integrated systems approach, describing the local drinking water supply system in terms of hydrological, technical, and socio-economic characteristics that determine the sustainability of a local drinking water supply system. To gain a perspective on the case study findings that are broader than the Dutch context, the sustainability aspects identified were paired with global aspects concerning sustainable drinking water supply. This resulted in the following set of hydrological, technical, and socio-economic sustainability characteristics: (1) water quality, water resource availability, and impact of drinking water abstraction; (2) reliability and resilience of the technical system and energy use and environmental impact; (3) drinking water availability, water governance, and land and water use. Elaboration of these sustainability characteristics and criteria into a sustainability assessment can provide information on the challenges and trade-offs inherent in the sustainable development and management of a local drinking water supply system.
This paper has investigated the extensive implementation of distinct types of pipes in the Water Distribution System (WDS) and evaluated the impacts of particular leachable organic chemicals and bacteriological issues. Besides, the paper inspects significant parameters of water quality as the population of Rajshahi City, Bangladesh relies on water provided via pipes for drinking and other domestic purposes. This study aims to assess the quality of physical, chemical, and microbiological parameters of supplied drinking water through lines in Rajshahi City Corporation (RCC) by Rajshahi Water Supply and Sewerage Authority (RWASA). Therefore, the study managed a total of sixteen physical, chemical, and microbiological parameters to analyse them in the laboratory. The experimental results showed that pH and hardness of all samples were within the allowable limit as per Bangladesh Drinking Water Standards (BDWSs) and World Health Organization (WHO). All models contained an extreme level of iron and manganese. They also included a negligible amount of arsenic. The experiment detected lesser Dissolved Oxygen (DO), Residual Chlorine (Residual Cl), and the undesirable odour in about 90 % samples. All samples contained Total Coliform (TC) and Escherichia coliE. coli) bacteria. A few samples contained a significant amount of turbidity, Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD), and Electrical Conductivity (EC). The authors developed a statistical analysis by SPSS software to co-relate the parameters. This study recommends the presence of such bacteria, iron, and manganese in the pipeline.
The forward osmosis (FO) process has been considered to be a viable option for water desalination in comparison to the traditional processes like reverse osmosis, regarding energy consumption and economical operation. In this work, a polyacrylonitrile (PAN) nanofiber support layer was prepared using the electrospinning process as a modern method. Then, an interfacial polymerization reaction between m-phenylenediamine (MPD) and trimesoyl chloride (TMC) was carried out to generate a polyamide selective thin-film composite (TFC) membrane on the support layer. The TFC membrane was tested in FO mode (feed solution facing the active layer) using the standard methodology and compared to a commercially available cellulose triacetate membrane (CTA). The synthesized membrane showed a high performance in terms of water flux (16 Lm −2 h−1) but traded the salt rejection (4 gm−2 h−1) compared with the commercial CTA membrane (water flux = 13 Lm−2 h−1= 3 gm−2 h−1) at no applied pressure and room temperature. Scanning electron microscopy (SEM), contact angle, mechanical properties, porosity, and performance characterizations were conducted to examine the membrane.
Water has been recognized as one of the most significant natural resources and crucial for health and wealth. The increased demand for water has imposed pressure on the water supply system, which has led to environmental problems such as over-exploitation of water resources and breaks in the balance of the ecosystem. Determining the behavior of domestic water consumers can facilitate a more proactive approach to water demand management, and serves as the foundation for the development of any intervention strategies that seek to bring about sustained and substantial reductions in domestic water consumption. This study tried to investigate household water consumption patterns and management practices along with comparing the effectiveness of different water management measures on reducing the water deficit of the district. The primary data was collected through a questionnaire survey from 75 households belonging to the urban area in Batticaloa District in Manmunai Pattu, Sri Lanka. The data were analyzed both quantitatively and qualitatively. The findings show that people with higher incomes in urban areas are using more water than people with lower incomes. The water usage depends on the living standards, family size, age, and education level of household members and the number of taps present in the household. It is believed that the results of the study would be beneficial for domestic water consumption in urban Batticaloa.
Safe drinking water is one of the basic human needs. Poor quality of drinking water is directly associated with various waterborne diseases. The present study has attempted to analyze the household preferences for drinking water sources and the adoption of household water treatment (HWT) in Pakistan by using the household data of Pakistan Demographic and Health Survey 2017–2018 (PDHS, 2018). This study found that people living in rural areas, those with older heads of household and those with large family sizes are significantly less likely to use water from bottled or filtered water. Households with media exposure, education, women's empowerment in household purchases and high incomes are more likely to use bottled or filtered water. Similarly, households are more likely to adopt HWT in urban areas, when there is a higher level of awareness (through education and media), higher incomes, women enjoy a higher level of empowerment, and piped water is already used. However, households that use water from wells and have higher family sizes are less likely to adopt water purifying methods at home.
The role of a drinking water distribution network (DWDN) is to supply high-quality water at the necessary pressure at various times of the day for several consumption scenarios. Locating and identifying water leakage areas has become a major concern for managers of the water supply, to optimize and improve constancy of supply. In this paper, we present the results of field research conducted to detect and to locate leaks in the DWDN focusing on the resolution of the Fixed And Variable Area Discharge (FAVAD) equation by use of the prediction algorithms in conjunction with hydraulic modeling and the Geographical Information System (GIS). The leak localization method is applied in the oldest part of Casablanca. We have used, in this research, two methodologies in different leak episodes: (i) the first episode is based on a simulation of artificial leaks on the MATLAB platform using the EPANET code to establish a database of pressures that describes the network's behavior in the presence of leaks. The data thus established have been fed into a machine learning algorithm called random forest, which will forecast the leakage rate and its location in the network; (ii) the second was field-testing a real simulation of artificial leaks by opening and closing of hydrants, on different locations with a leak size of 6 and 17 L s−1. The two methods converged to comparable results. The leak position is spotted within a 100 m radius of the actual leaks.