Dyes are hazardous contaminants normally found in industrial wastewaters necessitating costly and complex technologies for their removal. In this study, clay was used as an adsorbent in the removal of anionic acid red 88 (AR 88) dye from industrial wastewaters by adsorption. The dye removal efficiency and adsorption capacity of clay was studied by batch experimentation with respect to parameters of dye initial concentration, clay dosage, contact time, and pH. The dye removal efficiency of AR 88 improved with increasing dosage (r 0.9826, p < 0.05), contact time (r 0.9821, p 0.000683) and decreased with increasing initial concentration (r - 0.9168, p 0.02844) and pH (r -0.9666, p 0.007297) of the solution. At initial AR dye concentration of 100 mg/L, the removal efficiency and adsorption capacity of 89.7% and 4.38 mg/g, respectively were achieved after equilibrium time of 30 minutes under the optimum conditions of pH 2 and clay dosage 20 g/L. The study thrived in applying an efficient and low-cost adsorbent that could be used as a substitute to high-cost conventional commercial adsorbents in treating industrial wastewater with AR dye coloration

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Whenever there are substantial variations in the quantity of demands within a metropolitan water network, it is necessary to assess the pipe network to aid the water utilities in decision making. Variability in demand exists every time new industries or residences are connected to the network. In cases where no analyses are done prior to making new connections, unnecessarily huge funds are incurred and use of unreasonably bigger pipes is inevitable, some of which may stay redundant. The present study aims at developing a user-friendly numerical hydraulics model for analysing compound pipe networks. The model was developed using the V-Model approach, written in visual basic language to resolve the elementary pipe system equations using the improved Hardy Cross method. This program examines steady-state flows, head losses, flow velocities, and pressures for single, two, three, and four loop water distribution networks. The four-loop example represents the entire network of the case study area in consideration. The comparative study conducted on results from the program and EPANET indicated consistency in the results as coefficient of determinant, R^2, for all the computed variables was approximately unity (1). The Root Mean Square Error (RMSE) and Mean Bias Error (MBE) were found to be reasonably so small. Therefore, it can be concluded from the statistical analysis that the model is reliable for the analysis of a water network consisting of 1, 2, 3, and 4 closed loops.