Simulation of Chlorine Decay in Water Distribution Networks Using EPANET – Case Study

Deterioration of water quality in distribution networks has a great impact on human health and public acceptance of tap water reaching them. Residual chlorine should be maintained through network pipes to prevent contamination and microbial regrowth. This paper investigates the ability of EPANET 2.0, a free software developed by United States Environment Protection Agency (USEPA), to simulate residual chlorine decay through water networks, taking water-age analyses into consideration, and assesses the feasibility of using it as a measuring and controlling tool to estimate and predict chlorine concentration at different water network points. A study was performed on drinking water network of 6th of October city, where field measurements were done, while data required as program inputs were taken from the daily records of the 6th of October and El-Shaikh Zayed WTPs. The network model was calibrated to minimize error in program results. Errors were evaluated using statistical analyses. The calculated concentrations by the calibrated model were very close to the actual concentrations measured in field at different sampling points for different sampling days. Moreover, EPANET showed that for the water network concerned in this study, chlorine concentrations at network extremities did not recede 0.5 mg/l, the minimum allowable limit established in the Egyptian Code of Practice (ECP), even for those points having water age greater than 24 hours. Keywords: chlorine decay, water quality, water distribution networks, EPANET, water-ag

Adsorption of Pb(II) from Water onto ZnO, TiO2, and Al2O3: Process Study, Adsorption Behaviour, and Thermodynamics

This study is aimed at comparing the use of zinc oxide (ZnO), titanium dioxide (TiO2), and aluminium oxide (Al2O3) for removing lead ions from water through adsorption. The point of zero charge was obtained for ZnO, TiO2, and Al2O3 and was found to be 7.3, 7.1, and 9.0, respectively. The effect of pH, adsorbent dose, contact time, initial concentrations, and temperature was investigated in batch experiments. The optimal conditions obtained were 7, 2 g/L, 120 mins, 100 ppm, and 41°C, respectively, where the optimal removal efficiencies were 98.43%, 96.45%, and 85.50% for ZnO, TiO2, and Al2O3, respectively. In addition, analyses of adsorption kinetics, mechanisms, isotherms, and thermodynamics were performed. The adsorption kinetics of Pb(II) were compared to popular models, and it was found that the pseudo-second-order (PSO) model best fitted the Pb(II) uptake for all adsorbents at correlation coefficient (R2≥0.96). The adsorption isotherms of Pb(II) were also compared to popular models, and it was found that the Pb(II) uptake by TiO2 and ZnO was well-described by the Langmuir model (R2≥0.96) with maximum adsorption capacities of 55.04 and 58.88 mg/g, respectively. On the other hand, the behaviour of Al2O3 is described more accurately by the Dubinin-Radushkevich (D-R) model (R2=0.96), and the maximum adsorption capacity was 53.64 mg/g. The isotherm analysis proved that the limiting step of the adsorption process is the film diffusion mechanism. In addition, studying the heat of adsorption of Pb(II) implied that the adsorption is endothermic due to the positive values of enthalpy (ΔH°≥30) for all adsorbents. The absorbents were characterized using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) to study the morphology of surfaces and the chemical characterization of the adsorbents to ensure that adsorption is achieved. ZnO showed better performance for the uptake of lead followed by TiO2 then Al2O3

A review of coagulation explaining its definition, mechanism, coagulant types, and optimization models; RSM, and ANN

The textile business is one of the most hazardous industries since it produces several chemicals, such as dyes, which are released into water streams with ef-fluents. For the survival of the planet's life and the advancement of humanity, water is a crucial resource. One of the anthropogenic activities that pollute and consume water is the textile industry. Thus, the purpose of the current effort is to Apply coagulation as a Physico-chemical and biological treatment strat-egy with different techniques and mechanisms to treat the effluent streams of textile industries. The discharge of these effluents has a negative impact on the environment, marine life, and human health. Therefore, the treatment of these effluents before discharging is an important matter to reduce their adverse ef-fect. Many physico-chemical and biological treatment strategies for contaminants removal from polluted wastewater have been proposed. Coagulation is thought to be one of the most promising physico-chemical strategies for removing con-taminants and colouring pollutants from contaminated water. Coagulation is accompanied by a floculation process to aid precipitation, as well as the collection of the created sludge following the treatment phase.. Different commercial, and natural coagulants have been applied as a coagulants in the process of coagulation. Additionally, many factors such as; pH, coagulant dose, pollu-tants concentration are optimized to obtain high coagulants removal capacity. This review will discuss the coagulation process, coagulant types and aids in addition to the factors affecting the coagulation process. Additionally, a brief comparison between the coagulation process, and the other processes; princi-ple, advantages, disadvantages, and their efficiency were discussed throgh the review. Furthermore, it discusses the models and optimization techniques used for the coagulation process including response surface methodology (RSM), ar-tificial neural network (ANN), and several metaheuristic algorithms combined with ANN and RSM for optimization in previous work. The ANN model has more accurate results than RSM. The ANN combined with genetic algorithm gives an accurate predicted optimum solution

Potentials of algae-based activated carbon for the treatment of M.orange in wastewater

Activated carbon is a promising material with high efficiency in dye removal from polluted wastewater. However, commercial activated carbon is expensive and generates black color in the medium. Therefore, searching for low-cost, eco-friendly activated carbon sources such as agricultural wastes and algal biomasses is essential. Hence, this study is directed to prepare the physical and the H3PO4 chemical activated carbon from the algae ”Sargassum dent folium” and the raw algae itself and apply it for Methyl Orange (M. orange) removal from contaminated wastewater and compare its performance with the commercial activated carbon. First, adsorbent materials are prepared and involved in the optimization process for M. orange removal using some preliminary experiments, followed by Response Surface Method-ology (RSM) and Artificial Neural Network (ANN). Finally, Isotherm and kinetics are studied to explain the adsorption mechanism. In contrast to other materials, results show that physical algae-activated carbon achieves the maximum removal efficiency of 96.687%. These results are obtained from ANN combined with Moth Search Algorithm (MSA), representing the most effective model for achieving the highest M. orange removal efficiency from Physical algae activated carbon. In the algae case, the best experimental and predicted removal efficiencies are 85.9407 RE%, 88.5 indicated RSM RE%, and 85.9431 predicted ANN RE%. The best observed and predicted removal efficiencies for the H3PO4 chemical activated carbon are 89.6157 RE%, 82.38 predicted RSM RE%, and 89.5442 predicted ANN RE%. The best experimental and predicted removal efficiencies for the physical-activated carbon are 94.7935 RE%, 95.49 indicated RSM RE%, and 95.4298 predicted ANN RE%. The best observed and predicted removal efficiencies for the commercial-activated carbon are 92.2659 RE%, 96.65 predicted RSM RE%, and 92.2658 predicted ANN RE%. In the algae case, the best experimental and predicted removal efficiencies are 85.9407 %RE, 88.5 predicted RSM RE %, and 85.9431 expected ANN RE%. For the H3PO4 chemical activated carbon, the best experimental and predicted removal efficiencies are 89.6157%RE, 82.38 indicated RSM RE%, and 89.5442 predicted ANN RE%. For the physical-activated carbon, the best observed and predicted removal efficiencies are 94.7935 %RE, 95.49 predicted RSM RE%, and 95.4298 indicated ANN RE%. For the commercial-activated carbon, the best experimental and predicted removal efficiencies are 92.2659 %RE, 96.65 predicted RSM RE%, and 92.2658 predicted ANN RE%. This study intends to treat industrial wastewater contaminated with the anionic M. orange dye using raw algae and their generated activated carbon (physical and chemical forms), which are economical. It then compares the results to the effectiveness of commercial activated carbon. In the state of the raw algae, Temkin and Langmuir isotherm models best suit the data, while Temkin agrees well with the data from physical-activated carbon. Temkin and Freundlich's models are fitted with the H3PO4 chemical activated carbon. The model that fits the raw algae physically activated carbon and H3PO4 chemical-activated carbon the best is pseudo-second-order kinetics. Future research could examine the produced activated carbon-based algae's capacity to extract more contaminants from contaminated wastewater. This study intends to treat industrial wastewater contaminated with the anionic M. orange dye using raw algae and their generated activated carbon (physical and chemical forms), which are economical. It next compares the results to the effectiveness of commercial activated carbon