Tanneries produce significant quantities of hazardous wastewater and according to international environmental organizations, its further exploitation in the context of the circular economy consider being matador. Such a case study is the recovery of Cr(III), as it is an essential reagent in the treatment of the leather, but a significant portion ends up in wastewater. According to the literature, Cr(III) can be recovered directly from the wastewater and also from the corresponding sludge, which delivered by applying physicochemical and biological methods. Aim of this study is the optimization of Cr(III) hydrometallurgical recovery from tannery sludge, reporting a thorough investigation into; how experimental conditions affect the efficiency at all steps of the process, namely leaching and precipitation. The reference sample was air dried sludge, which obtained from the tannery wastewater treatment plant located in the industrial area of Thessaloniki in Northern Greece. The chemical characterization revealed that it contained high amounts of Cr(III) (14.1%), Ca (14.8%) and organic matter (22%). Τhe extraction of Cr(III) was examined by applying various acids (H2SO4, HNO3, HCl) with the following experimental conditions: concentration range 0.02-2 N, contact time 60 min, temperature at 25o C, and liquid-to-solid ratio (L/S) 25. According to the results, the highest selectivity was obtained for H2SO4, since the insoluble CaSO4 was formed, and also the highest efficiency, due to the formation of the soluble CrSO4+ (93% by the use of 1 N H2SO4). Regarding Cr(III) precipitation from the leaching solution, by increasing its equilibrium pH in the range 6-9.5, as alkaline reagents was examined NaOH and Ca(OH)2. A higher purity Cr(OH)3 precipitate was obtained by the application of NaOH (70 %). On the contrary, the use of Ca(OH)2 also led to the insoluble CaSO4 formation, but its efficiency was limited with respect to the Cr(III) content (16.5 %).
In this study, ZrO2 nanoparticles were prepared by successful microwave irradiation cohesive method. Compared to conventional methods, the advantages of microwave synthesis, very short reaction time and small particle production with narrow size distribution, high purity, efficient heating, environmentally friendly, cost-effective, uniform and special heat distribution and increase the speed of the reaction. On the other hand, ZrO2 is a highly resistant material to crack and fracture propagation, high thermal expansion, excellent conductivity and low thermal conductivity. In this type of synthesis, the aqueous solution containing Zr(NO3)4.5H2O and NaOH was exposed to 650 W microwave radiation. The obtained sediments were characterized by FT-IR and UV-vis analyzes. The sediments were uniformly coated on a ceramic membrane and a very thin layer formed by a wet layer on the substrate. The evaporation and drying process was performed under constant conditions. In this work, the ceramic membrane was used because of its apparent advantages, including high stability, long life, high flux and low deposition. The results showed that according to the XRD diagram based on the Shearer equation, the ZrO2 nanoparticles had crystalline order and sharp and distinct peaks. The FESEM images also showed that the morphology of the tubular structure was oriented towards the tetragonal and nanoparticles with dimensions less than 100 nm on the ceramic surface.
Spinel ferrite MFe2O4 (M= Cu, Ca, Mg, Ni, etc.) nanoparticles and their composites are a new promising materials because have shown their great interest in field of sensing, optoelectronics, catalysis and solar cells due to their unique physical and chemical properties differing from their bulk structures. Today, lots of CuFe2O4 nanomaterials have been synthesized by different methods including hydrothermal route and sol-gel combustion method and so forth. Nevertheless, there are hardly any results about photocatalytic activity of it. For this reason, optical properties is increased by preparing composite of it with other oxides. In this paper, CuFe2O4@CuO magnetic composite was synthesized by ultrasound method. The samples prepared were characterized by XRD, FT-IR spectroscopy, DRS and SEM images, VSM, and EDS-mapping. The catalytic activity of as-synthesized CuFe2O4@CuO was evaluated using the degradation of methylene blue. Furthermore, a possible reaction mechanism was discussed. Finally, the catalyst was used for effective degradation of MB in its solution, which indicated its potential for practical applications in water pollutant removal and environmental remediation.
Silica gel was used as adsorbent for dyes in aqueous solutions. Afterwards, the silica gel with the adsorbed dye was heated to 600 °C, at which the dye combusted, leaving behind clean silica gel. This silica gel can be reused in the adsorption process. The operation leaves behind little waste products. It is an optimal procedure for educational and other research laboratories which are working with biological stains, food colorants and some non-commercial dyes.
It is important to remember that water is a non-renewable resource, necessary for all creatures on earth. In cities, this resource is supplied by water supply networks, that must be flexible enough to follow the population growth.Those networks start to fail, for large or small cities, due to different situations: ageing process; linking new networks with old ones; lack of maintenance. One of the most undesirable failures is water losses due to leaks in the supplying system.
There are mainly two types of water losses: the visible and the non-visible. Within the non-visible we have those that are detectable by acoustic methods and those that are not. Here we decide to study new techniques for leak detection, since leaks non-visible are more difficult to find (detect).This is the aim of this paper.
In a previous stage we have been studying the possibility of obtaining thermographic images to develop visualisation techniques on pipes as an option for leak detection.Analysing this possibility, with previous studies we have established conditions for taking images for later analysis, which has confirmed the benefits of the use of thermography as a tool. Here we present a case study where images were taken in a controlled atmosphere in a laboratory, using a physical model that contained a buried pipe with a simulated loss of water. During the entire duration of the test, images were taken at a certain interval of time and afterwards the images where analysed. The results show the benefits and limitations of the technique, which should continue to be studied since thermal imaging cameras and computers to process the images are day by day more powerful and accessible.
Pipe failures in Water Distribution Networks (WDN) may cause economic, environmental and social costs. The application of statistical and Machine Learning (ML) models play a critical role in planning and decision support processes for WDN management. Failure models can provide valuable information for prioritizing the system rehabilitation even in data scarcity scenarios (such as developing countries). This study compares several statistical and ML pipe failure models thus providing useful information to practitioners to select a suitable model according to their needs.
Three statistical models (i.e. Linear, Poisson and Evolutionary Polynomial Regressions) were used for pipe failures prediction based on diameter, age of pipes and length as explanatory variables. The K-means clustering approach was applied to improve the performance of the statistical models. The performance indicators used were the coefficient of determination (R2) and the root mean square error (RMSE). ML approaches - namely Gradient Boosted Tree (GBT), Bayes, Support Vector Machine and Artificial Neuronal Networks (ANNs) - were compared in predicting individual pipe failure rates. The pipe’s attributes, environmental and operational variables were included as input variables. Their performance was evaluated using confusion matrices and receiver operating characteristic curves. The proposed approach was applied to a WDN in Bogotá (Colombia).
The results showed that the cluster-based prediction model reduces the prediction error of pipe failures. All the models demonstrated acceptable results in terms of their performance (R2 between 0.695-0.927 and RMSE between 45-22 for the test sample). Regarding ML models, all methods but the ANNs show acceptable performance. The GBT approach has the best performing classifier (79.41% correct predictions in the test sample). This model was used to calculate the failure rate of individual pipes for rehabilitation planning. Furthermore, a sensitivity analysis of the GBT model to the input variables was performed to provide information on its generalization capability.
The success of the analysis and design of a Water Network (WN) is strongly dependent on the veracity of the data and a priori knowledge used in the model calibration of the network. This fact motivates this paper in which an off-line approach to verify datasets acquired from WN is proposed. This approach allows separating data of abnormal events from normal-operation without requiring the knowledge of experts limited by the amount of data to be verified. The core of the approach is the combination of a systematic feature selection and an unsupervised classification tool, known as DBSCAN, which does not require setting the number of clusters to be identified. The proposal is applied to datasets acquired from a Mexican water management utility located in the center part of Mexico. The datasets were pre-processed to be synchronized since they were recorded and sent with different sampling times to a web platform. The pressure and flow-rate recorded every ten minutes correspond to dates between 01/07/2019 @ 00:00 and 01/09/2019 @ 23:50. The water network is formed by 90 nodes and 78 pipes and it provides service to approximately 2000 consumers. The data identified as abnormal were validated with the reports of the WDN managers. The abnormal events identified were communication problems, sensor failure, and draining of the network reservoir.
The paper aims to propose modulation of nodal outflows in water distribution networks (WDNs), to solve the problem of low disinfectant concentrations at critical dead-end nodes, in which low flow velocities and long residence times cause excessive disinfectant decay. In fact, the slight increase in nodal outflows at these sites, which can be obtained through the opening of a blowoff at the hydrant site, can help in tackling this problem with no need of increasing disinfectant doses at the source(s) and of installing additional disinfectant booster stations. The methodology is based on the combined use of optimization and of flow routing/water quality modelling of WDNs. The concentration of disinfectant at the source(s) and the values of nodal emitter coefficients at the critical dead-end nodes are the decisional variables to be optimized. Two objective functions are considered in the optimization, namely the total volume of water delivered in the network (inclusive of supply, leakage and additional nodal outflow considered for fixing chlorine residuals) and the total mass of disinfectant injected into the network. The effectiveness of the methodology is proven on a real WDN, yielding an insight into the economic feasibility of the solution.
Pressure reducing valves (PRVs) are widely used in water distribution networks for optimal pressure management. Several studies and field applications prove the effectiveness of PRVs for water loss reduction, but some recent studies have also highlighted some problems and operational limitations. In this study, we analyse the functioning of a piston actuated pressure reducing valve (where the regulating device operates in a parallel direction to the flow) with a mechanical pilot which is subjected to low flow regimes, a condition that is often observed in the real distribution networks. The analyses are carried out by means of laboratory tests featuring two sets of experiments, i.e. a) by testing the behaviour of the PRV when a pre-established initial value and subsequent variation of flow rate occurs in the system and b) by testing the PRV in face of a temporal series of flow rates observed at the inlet section of a real hydraulic district. The first set of tests highlighted different field behaviour of the PRV corresponding to well defined ranges of flow rate, and in particular that for some flow rates the PRV tends not to respect the imposed set-point value and, under certain flow rate values, an unstable behaviour characterised by significant pressure oscillations occurs. The second set of laboratory tests has shown that the anomalous behaviour identified in the first set of tests can occur in ordinary operational conditions of a network, implying potential technical and economic consequences in terms of damage to pipes and hydraulic devices.
Proper design of a pumping system requires the use of the pump curve and the system setpoint curve. Both have to be as close as possible so that the energy used is optimal. This is achieved by means of regulation systems, in which the type of control to be used (flow or pressure) and the combination between Fixed Speed Drives (FSD) pumps and Variable Speed Drive (VSD) pumps are involved.
The objective of this work is to determine the optimal number of FSD and VSD pumps for each flow rate range in order to discuss the classic design of pumping stations and their regulation modes. For this, a methodology consisting in defining a parametric form of the pump curve, the efficiency curve and the set-point curve in relation of the best efficient point is applied. In this way, dimensionless expressions are obtained and the influence of the set point parameters in the design of regulation modes can be analyzed. Additionally, the method includes to get an expression to estimate the performance of the frequency inverter based on the load and pump speed rotation.
The application of the methodology to different studie cases allows questioning many classic methods procedures for pumping stations. In summary, it can be concluded that the appropriate number of fixed speed pumps for each regulation mode cannot be established in advance but requires an in-depth study of the different options available.