Membrane filtration technology is widely applied in conventional surface water treatment plants because of its low power load and high filtration accuracy. This study follows the transition from a power-driven to a gravity-driven siphon-submerged ultrafiltration membrane system in a drinking water treatment plant in Shandong Province, China. The proportion of space membrane areas in the tank was further developed, by increasing the membrane areas of a single tank to 1.6 times of that before the transformation, the design production capacity of a single tank is increased from 10,000 m(3)/d before the transformation to 16,700 m(3)/d. The recovery rate of a single tank was also increased from 96.28 to 97.77%. The energy consumption per ton of water decreased from 0.06 to 0.017 MJ. The annual carbon emissions reduction reached 197.13 tons per tank. In terms of the water quality, the algae removal rate from surface water by the ultrafiltration membrane reached 100%. Further, the removal rates of 2 mu m particles, turbidity, and chlorophyll were above 99%. Our results suggest that gravity-driven siphon-submerged ultrafiltration promotes environmental protection, energy conservation, and emissions reduction. This technology introduces a new development direction for membrane filtering in drinking water treatment plants.
Filter backwashing is a supplemental part of a drinking water treatment (DWT) facility to wash the filter bed at regular intervals using water or air scour/water by fluidizing the filter bed. Suspended sediments that are retained by the filter bed consist of different particles such as sand, anthracite, and granular activated carbon (GAC) that decline the water flow rate of the filter, and hence consequently the filter bed must be cleaned using a backwashing procedure. Biofiltration has been extensively utilized to decrease organic matter and manage the occurrence of disinfection by-products within drinking water sources. Biological rapid sand filters are frequently utilized to eliminate ammonium from groundwater provinces with the purpose of meeting drinking water requirements. Biological activated carbon (BAC) filters require to be backwashed to wash and enhance the treatment capability by detaching both restrained materials and residual biomass. The reclamation of activated carbon-used backwash water (UBW) was managed by exercising an ultrafiltration (UF) procedure.
A large population depends on water resources generated due to runoff from Himalayan River basins. They provide enough water for drink-ing, domestic, industrial, and irrigation. Also, these rivers have a high hydropower potential. A lack of in-depth studies has made it difficult to understand how these rivers respond hydrologically to climate change (CC) and, thus, impact the environment. In this paper, modelling the Alaknanda River Basin (ARB) using the Soil and Water Assessment Tool (SWAT) has been conducted to understand the hydrological response and assess its water balance components. The result shows that the basin's water yield and Evapotranspiration (ET) vary from 58 to 63% and 34 to 39% of precipitation, respectively. The average annual contribution of snowmelt to the total riverine flow will range from 20 to 24% throughout the simulation period. SFTMP, TLAPS, SMTMP, CN2, SMFMX, and GW_DELAY is found to be most sensitive at the significance level of less than 0.05, showing the contribution of the snowmelt is significant in streamflow, while delay in the groundwater will affect the contribution of surface runoff and groundwater in the streamflow. Based on the results, it is highly recommended that the spatial and temporal hydro-meteorological should be investigated in-depth.
In this work, an attempt is made to predict the future water demand of a hilly region. The study area is selected based on the population and the water demand. For this work, Namunaghar and Wandoor Panchayats of Andaman and Nicobar Islands are selected. Initially, preliminary studies such as the current population and future growth and their water demand were analyzed. Also, using a geographical information system (GIS), the study area is located to identify the surface and groundwater sources. From the GIS data, a detailed map is prepared to conduct the physical verification and collect the water quality measurement. From the population forecast, it was identified that 435,000 and 480,300 l of water are required to meet the water demand in the year 2031 Namunaghar and Wander Panchayat, respectively. It also assessed the GIS data and found out potential water sources of 157 (67 wells, 58 ponds, and other minor sources) and 485 (215 wells, 229 ponds, and other minor sources) at Namunaghar and Wandoor Panchayats, respectively. Finally, all the potential water sources were checked for quality for drinking purposes.
Biofouling is one of the most challenging obstacles faced by reverse osmosis (RO) membrane systems to supply potable water. Currently, biofouling is imperfectly handled by RO feed water pre-chlorination, which is associated with the production of carcinogenic disinfection by-products. To propose a safer alternative to control biofouling in RO drinking water applications, this study investigates the efficacy of five biocides to prevent and remove Pseudomonas aeruginosa biofilms from RO membranes: (1) 2-methyl-4-isothiazolin-3-one (MIT); (2) 2,2-dibromo-3-nitrilopropionamide (DBNPA); (3) sodium bisulfite (SBS); (4) sodium benzoate (SB), and (5) ethyl lauroyl arginate (LAE). Experiments were conducted on the Center for Disease Control (CDC) Biofilm Reactor (CBR) with biocidal dosing estimated on 96-well microtiter plates. Confocal Scanning Laser Microscopy (CLSM) and Scanning Electron Microscopy (SEM) were used to analyze the biocides' anti-biofilm efficacies under dynamic conditions relative to minimum biofilm inhibitory and eradication concentrations. The results in this study indicated that LAE presented the best anti-biofilm efficacies in treating P. aeruginosa biofilms when compared to all studied biocides; it not only prevented biofilm formation (>98%) but also it effectively removed pre-established biofilms (>99%) from RO membrane coupons. Therefore, due to safety and efficacy, LAE is an excellent candidate for controlling biofouling in drinking water RO membrane systems.
The availability and quality of water resources for agricultural irrigation are being increasingly compromised by different factors. In this context, the installation of rainwater harvesting (RWH) systems for use in agricultural holdings can contribute to mitigating this problem. However, the use of these systems by farmers continues to be very low. This paper analyses the factors that influence a farmer's decision to adopt these systems to take advantage of rainwater. Greenhouse agriculture in southeast Spain is the case studied. For this, a binary logistic regression model based on a survey administered to farmers was used. Among the variables found to be significant, the most important variables are the quantity of water in the pond, the pond capacity and environmental awareness. The variables that least affect the adoption decision are age, education level and income. These results have allowed the development of the main lines of action for policy-makers to intervene in order to promote the adoption of these systems. These measures focus on enhancing the training of farmers, providing them with financial support and boosting their environmental awareness. The results of this study lead to improved research on farmers' behaviour and sustainable management of water resources in agriculture.
Population detonation and inflated demand for agricultural products have resulted in the rampant use of pesticides in recent years. These pesticides are used to reduce the number of pesticides by different mechanisms. They have been utilized in agriculture to expand agrarian profit, crop yield, quality, and storage life. The incessant and extensive use of resistant pesticides has contaminated the water bodies, fields, crops, and aquatic biota as well as poses a threat to human health. As a result, stringent regulations and limits are established to monitor the pesticide matrix. The current review focuses on pesticide contamination in the food chain, particularly from the aquatic bodies to fishes and humans. It also discusses strict regulations and limits including maximum residual limits for food items, acceptable daily intake, theoretical maximum daily intake, and estimated carcinogenicity/non-carcinogenicity for fishes and human health risks. In addition to conferring the negative effects of pesticides, this article discusses cost-effective remediation techniques such as phytoremediation, adsorption, the Fenton oxidation method, microalgal/high-rate algal ponds, and nanotechnology with the comparison of their remediation cost.
Surface waterbodies, on which the growing population of Kashmir Valley is reliant in a variety of ways, are increasingly deteriorated due to anthropogenic pollution from the rapid economic development. This research aims to assess the water quality of the surface waterbodies in the north-eastern region of Kashmir Valley. Standard analytical procedures were used to analyze the water samples taken from 11 distinct sampling stations for 14 physiochemical parameters. The results were compared with the standard permissible levels which showed that the water quality of rivers and lakes in the north-east Himalayan region has steadily declined. Furthermore, multivariate statistical techniques were used with the goal to identify key variables that influence seasonal and sectional water quality variations. The analysis of variance (ANOVA) analysis revealed that there is substantial spatio-temporal variability in the water quality parameters. According to principal component analysis (PCA) results, four primary components, which together accounted for 79.23% of the total variance, could be used to evaluate all data. Chemical, organic, and conventional pollutants were found to be significant latent factors influencing the water quality of rivers in the study region. The results indicate that PCA and ANOVA may be used as vital tools to identify crucial surface water quality indices and the most contaminated river sections.
Conventional treatments for antibiotic residues in effluents are inefficient and do not lead to complete removal. Though effective and feasible degradation of antibiotics using nanoparticles has been reported by several scientists, chemically synthesized nanoparticles have their own disadvantages. Thus, in this study, nZVI was biosynthesized using leaf extract of Shorea robusta and precursor FeSO4·7H2O for photocatalytically degrading tetracycline (TC) and ciprofloxacin (CIP). The characterization of nZVI was performed using SEM, TEM, AFM, EDX, FTIR, and XRD to test their properties, which revealed iron-rich, well-dispersed, spherical, crystalline nanoparticles. Photocatalytic degradation of TC and CIP under UV illumination revealed 88 and 84% optimum efficiency at antibiotic concentrations 15 and 25 mg L−1, 0.014 and 0.0175 g L−1 doses of nZVI, respectively in the pH range 4–6 in 70 min. The degradation was further verified using mass spectrometry, which confirmed the degradation of antibiotics into the breakdown products. Toxicity assay of the degraded antibiotic solution proved it non-toxic for bacteria and safe for discharge into water bodies. The cost analysis of antibiotic degradation using nZVI proved very economical, costing around 1.5 USD per 1,000 L of wastewater.
Geometrical changes and high flow velocity cause flow separation and cavitation in the transition regions of hydraulic structures. A few studies have been conducted on the flow pressure and cavitation index in these regions, and the results need to be still improved. The present study examined the flow pressure and cavitation index variations for expansion angles between 0° and 10° and Froude numbers up to 20.1. Several relevant equations were also suggested to predict permissible angles in the transition regions. The results showed that negative pressure occurred at all lateral expansion angles except 0° when the Froude number was equal to or greater than ≥6.5. The cavitation phenomenon did not occur on the side walls for Froude number up to 4.49. However, the values of the cavitation index were reduced to less than the critical value for the Froude number of 14 when expansion angle was greater than 6°. The results also revealed that the side walls should not be expanded when Froude number was equal to or greater than 17.5. The occurrence of the cavitation on these walls substantially increased for Froude number of 20.1 even as expansion angle equals 0°.
Herein, we report a facile approach for constructing a calixarene-based electrochemical heavy metal sensor (Calix/MPA/Au) via a one-pot reaction for the detection of Ni(II) and Zn(II) ions. The surface elemental properties and analytical performance of the Calix/MPA/Au sensor were characterized by X-ray photoelectron spectroscopy (XPS) and differential pulse voltammetry (DPV). Under optimum conditions, the sensor exhibited detection limits of 1.5 and 0.34 mg/L at linear ranges of 2.85–6.65 and 0.13–1.68 mg/L for the Zn(II) and Ni(II) ions, respectively. The developed sensor exhibited a better electrochemical performance in the detection of Zn(II) and Ni(II) ions owing to the favourable host–guest interactions between the hydroxyl groups-functionalized lower rim of dicarboxyl-calix[4]arene and the metal ions. The RSD of the five independent Calix/MPA/Au electrode for Zn(II) and Ni(II) ions was calculated to be 16.3 and 16.1%, respectively. Despite the lower sensitivity of the modified electrode towards Ni(II) ions, this finding proves the high selectivity of the calixarene as a detection probe towards the fitted size of guest ion, hence promising to be assembled and explored as a solid-state based-supramolecular host molecule for tracing metal ions.
Tea polyphenols can be developed into new types of disinfectants for drinking water. The antibacterial effect of epigallocatechin gallate (EGCG) on Escherichia coli (E. coli) in the presence of Ca2+ is affected by the Ca2+ concentration. The oxidative damage mechanism and oxi-dative damage process of EGCG in E. coli under the presence of Ca2+ were deeply analyzed under three aspects: reactive oxygen species (ROS), antioxidant system, and oxidative stress response in E. coli to provide a theoretical basis for the use of EGCG as a disinfectant in drink-ing water disinfection. EGCG leads to excessive production of superoxide anion in E. coli and the presence of Ca2+ promotes further imbalance of superoxide anion in E. coli; Ca2+ has little effect on EGCG hindering the scavenging of hydroxyl radicals in bacteria; EGCG can hinder the effect of antioxidant enzymes in E. coli, and Ca2+ has a particular regulatory effect on antioxidant enzymes, thus hindering the oxidative damage of EGCG to E. coli; Ca2+ can cause the expression of the oxyR and DPS genes, protect bacterial DNA, and prevent EGCG from damaging bacterial DNA. In the presence of a high concentration of Ca2+, it may activate the cell efflux pump through the soxS gene, resulting in E. coli resistance to EGCG.
The derivation of information from monitoring drinking water quality at high spatiotemporal resolution as it passes through complex, ageing distribution systems is limited by the variable data quality from the sensitive scientific instruments necessary. A framework is developed to overcome this. Application to three extensive real-world datasets, consisting of 92 multi-parameter water quality time series of data taken from different hardware configurations, shows how the algorithms can provide quality-assured data and actionable insight. Focussing on turbidity and chlorine, the framework consists of three steps to bridge the gap between data and information; firstly, an automated rule-based data quality assessment is developed and applied to each water quality sensor, then, cross-correlation is used to determine spatiotemporal relationships and finally, spatiotemporal information enables multi-sensor data quality validation. The framework provides a method to achieve automated data quality assurance, applicable to both historic and online datasets, such that insight and actionable insight can be gained to help ensure the supply of safe, clean drinking water to protect public health.
This article explores the forecasting capabilities of three classic linear and nonlinear autoregressive modeling techniques and proposes a new ensemble evolutionary time series approach to model and forecast daily dynamics in stream dissolved organic carbon (DOC). The model used data from the Oulankajoki River basin, a boreal catchment in Northern Finland. The models that were evolved used both accuracy and parsimony measures including autoregressive (AR), vector autoregressive (VAR), and self-exciting threshold autoregressive (SETAR). The new method, called genetic-based SETAR (GTAR), evolved through the integration of state-of-the-art genetic programming with SETAR. To develop the models, high-resolution DOC concentration and daily streamflow (as the external input for VAR) were measured at the same gauging station throughout the ice free season. The results showed that all the models characterize the DOC dynamics with an acceptable 1-day ahead forecasting accuracy. Use of the streamflow time series as an exogenous variable did not increase the predictive accuracy of AR models. Moreover, the hybrid GTAR provided the best accuracy for the holdout testing data and proved to be a suitable approach for predicting DOC in boreal conditions.
The textile industry generates enormous starch effluent from the desizing process that can be utilized as a nutrient source for fungal growth and simultaneous dye decolorization. In the present study, Trichoderma reesei was used as a potential fungal isolate for the decolorization of reactive dyes using a minimal salt media for growth. The dye removal of Reactive blue 13, Reactive red 198, Reactive yellow 176, and Reactive black 5 were 95.35, 88.17, 86.01, and 94.84 mg L−1, respectively, by fungal biomass at 100 mg L−1 of initial dye concentration in 48 h was achieved. T. reesei showed decolorization of dyes at initial concentrations upto 500 mg L−1 with high dye uptake capacity. The glucose (5 g L−1) and yeast extracts (2.5 g L−1) were optimal for maximum dye decolorization. The utilization of starch effluent as an alternative nutrient source supplemented with 3.5 g L−1 glucose as growth media by T. reesei showed >85% of decolorization of Reactive blue 13 (100–200 mg L−1). Thus, starch effluent could be partially supplemented with glucose to support fungal growth and dye decolorization, eliminating the requirement of minimal salts for dye decolorization that follows a sustainable approach.
In this study, a dual membrane process (DMP) that combines seven-hole ultrafiltration and nanofiltration was designed and compared to O3-biological activated carbon (O3-BAC) for high-quality drinking water production. The pollutant removal, membrane fouling, long-term operational characteristics, and technical economy were systematically investigated using raw water from Tai Lake, which has a high algae content. The results elucidate that the DMP has superb decontamination. This method has much better removal of turbidity, CODMn, UV254, and algae than O3-BAC. Its removal of ammonia nitrogen and fluorescent substances is slightly lower than that of O3-BAC, but the effluent still satisfies the drinking water standard. The DMP is also much more capable of dealing with high algae-laden raw water. Compared to O3-BAC, the cost of the DMP is 46.4% higher per ton without consuming chemicals, so it is more environmentally friendly. In summary, the DMP offers a promising and effective technology to treat high algae-laden water with the advantages of high stability, reliable effluent, and zero emissions.
In the remote and challenging terrain of the Himalayan region, accurate measurement of cyclic snow accumulation and depletion is a significant challenge. To overcome this, an attempt has been made in the present study by applying a statistical analysis of MODIS snow time series data with the Seasonal Autoregressive Integrated Moving Average (SARIMA) model from 2003 to 2018 over the Beas river basin. The Box–Jenkins methodology of forecasting is based on the identification using seasonality, stationarity, ACF, and PACF plots; and estimation based on maximum likelihood techniques; and the last diagnostic checking based on the residual and error values have been used. Later, forecasting models have been proposed separately for the snow accumulation period (October–February) as (1,1,1) (0,1,3)19 and for the snow depletion period (March–September) as (1,1,1) (1,1,2)27 after calibration of the data (2003–2015) and the same were then validated using data (2016–2018). The accuracy assessment of the models has been checked using performance criteria like AIC, MSE, and RSS. The comparison of the forecasting models with the observed data showed a good agreement with R2 of 0.83 and 0.89 for snow accumulation and snow depletion, respectively. This research highlights the potential of utilizing satellite data and statistical modeling to address the challenges of monitoring snow cover in remote and inaccessible regions.
To determine the response between the onshore sediment transport capacity (Tc) and various hydraulic parameters, a variable-slope, fixed-bed flume experiment was conducted to investigate Tc for five slopes and six flow rates by comparing five levels of sediment, and a total of 150 experiments were conducted. The results show that among the response relationships between each hydraulic parameter and Tc, the relationships between flow power, unit flow power, and average flow velocity and Tc is significant. In predicting Tc under different soil conditions, the shear stress produced divergence, which should be further explored. The reliability of using slope and flow rate as a single parameter to predict Tc is questionable. As a kinetic index, flow power can be used to predict Tc. The average flow velocity and unit flow power can predict Tc well and are closely related to the soil used in the experiments. The shear stress of water flow can express the evolution of Tc, which is mainly influenced by the median particle size of sediment particles in predicting Tc. The results of the study provide a new method for establishing a prediction model for soil erosion in the loess hilly gully area.
Tajikistan is a country in Central Asia with rich water resources. However, drinking water is used for agriculture and other non-drinking purposes owing to the fixed tariff system. Consequently, the overall level of water services has deteriorated and generated revenue is insufficient for operation and maintenance costs. Therefore, this study aimed to improve the quality of water supply services by providing hardware support, such as the construction of wells and the renewal of water distribution pipes. However, because hardware improvement alone cannot sufficiently enhance water supply services, software support to improve the capacity of the Vodokanal (utility) staff, including the preparation of a metered tariff system, was implemented through a technical cooperation project. The project successfully raised customer awareness of water conservation and the water consumption rate was reduced to two-thirds of that before the implementation of the project. Additionally, the water quantity, quality, pressure, and supply hours in the targeted area were significantly improved. Despite the resulting increase in financial burden, customer satisfaction regarding the water supply was enhanced from 51% before the project to 100% in the second half of the project. Simultaneously, the water supply revenue increased by 24% and this increase contributed to sustainable water supply management.
Household water consumption plays an important role in addressing the problem of water shortage and achieving sustainable water development. To identify, assess, and analyze the impact of a family structure on household water consumption, this study develops a mathematical statistical method to conduct multi-scenario simulations of average annual household water consumption based on data from the 2016 China Family Panel Studies (CFPS). The Kolmogorov-Smirnov test and the two independent sample t-tests were used to obtain the distribution with the highest degree of fitting, and the probability distribution and expected value of average annual household water consumption were obtained from the distribution probability function. The results demonstrated that the Birnbaum-Saunders distribution was the optimal distribution; families comprising one and two generations were dominant in terms of water consumption; and the number of water-saving households was far less than that of households with high levels of water consumption. The findings of this study have valuable implications for water governance and policy optimization.
