Regression model, artificial neural network, and cost estimation for biosorption of Ni(II)-ions from aqueous solutions by Potamogeton pectinatus.

This study investigated the application of Potamogeton pectinatus for Ni(II)-ions biosorption from aqueous solutions. FTIR spectra showed that the functional groups of -OH, C-H, -C = O, and -COO- could form an organometallic complex with Ni(II)-ions on the biomaterial surface. SEM/EDX analysis indicated that the voids on the biosorbent surface were blocked due to Ni(II)-ions uptake via an ion exchange mechanism. For Ni(II)-ions of 50 mg/L, the adsorption efficiency recorded 63.4% at pH: 5, biosorbent dosage: 10 g/L, and particle-diameter: 0.125-0.25 mm within 180 minutes. A quadratic model depicted that the plot of removal efficiency against pH or contact time caused quadratic-linear concave up curves, whereas the curve of initial Ni(II)-ions was quadratic-linear convex down. Artificial neural network with a structure of 5 - 6 - 1 was able to predict the adsorption efficiency (R2: 0.967). The relative importance of inputs was: initial Ni(II)-ions > pH > contact time > biosorbent dosage > particle-size. Freundlich isotherm described well the adsorption mechanism (R2: 0.974), which indicated a multilayer adsorption onto energetically heterogeneous surfaces. The net cost of using P. pectinatus for the removal of Ni(II)-ions (4.25 ± 1.26 mg/L) from real industrial effluents within 30 minutes was 3.4 $USD/m3.

Experimental and theoretical approaches for Cd(II) biosorption from aqueous solution using Oryza sativa biomass.

Biomass of Oryza sativa (OS) was tested for the removal of Cd(II) ions from synthetic and real wastewater samples. Batch experiments were conducted to investigate the effects of operating parameters on Cd(II) biosorption. Fourier transform infrared spectroscopy, scanning electron microscopy, and energy-dispersive x-ray spectroscopy were used to examine the surface characteristics of the Cd(II)-loaded biomass. The maximum removal efficiency of Cd(II) was 89.4% at optimum pH 6.0, biosorbent dose 10.0 g L(-1), initial Cd(II) 50 mg L(-1), and biosorbent particle size 0.5 mm. The applicability of Langmuir and Freundlich isotherms to the sorbent system implied the existence of both monolayer and heterogeneous surface conditions. Kinetic studies revealed that the adsorption process of Cd(II) followed the pseudo-second-order model (r2: 0.99). On the theoretical side, an adaptive neuro-fuzzy inference system (ANFIS) was applied to select the operating parameter that mostly influences the Cd(II) biosorption process. Results from ANFIS indicated that pH was the most influential parameter affecting Cd(II) removal efficiency, indicating that the biomass of OS was strongly pH sensitive. Finally, the biomass was confirmed to adsorb Cd(II) from real wastewater samples with removal efficiency close to 100%. However, feasibility studies of such systems on a large-scale application remain to be investigated.

Artificial intelligence and regression analysis for Cd(II) ion biosorption from aqueous solution by Gossypium barbadense waste.

In this study, batch biosorption experiments were conducted to determine the removal efficiency of Cd(II) ion from aqueous solutions by Gossypium barbadense waste. The biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) connected with energy dispersive X-ray (EDX). The sorption mechanism was described by complexation/chelation of Cd2+ with the functional groups of O-H, C=O, -COO-, and C-O, as well as, cation-exchange with Mg2+ and K+. At initial Cd(II) ion concentration (C o), 50 mg/L, the adsorption equilibrium of 89.2% was achieved after 15 min under the optimum experimental factors of pH 6.0, biosorbent dosage 10 g/L, and particle diameter 0.125-0.25 mm. Both Langmuir and Freundlich models fitted well to the sorption data, suggesting the co-existence of monolayer coverage along with heterogenous surface biosorption. Artificial neural network (ANN) with a structure of 5-10-1 was performed to predict the Cd(II) ion removal efficiency. The ANN model provided high fit (R 2 0.923) to the experimental data and indicated that C o was the most influential input. A pure-quadratic model was developed to determine the effects of experimental factors on Cd(II) ion removal efficiency, which indicated the limiting nature of pH and biosorbent dosage on Cd(II) adsorption. Based on the regression model (R 2 0.873), the optimum experimental factors were pH 7.61, biosorbent dosage 24.74 g/L, particle size 0.125-0.25 mm, and adsorption time 109.77 min, achieving Cd2+ removal of almost 100% at C o 50 mg/L.

Urban water management : North Africa and the Middle East

The state of water management in the urban environments in the region was described and evaluated, it was found far from being satisfactory. The assessment of research and research capacities on water management using three samples from various sources indicated weakness in the interdisciplinary coordinated type of research, and the fragmented pieces of water management research missed almost all the social aspects and ignored any role of communities in water management and urbanization planning. Published and disseminated information on water science expertise and institutions in the region uncovered usually inaccurate and confusing data. Examples of wastewater reuse projects in the region were given and seems that the technological side of such water issue is the most active one; a full comprehensive approach to water management is neglected. Common regional approaches to urbanization and water management were discussed, with emphasis on the size of the problem and available funds, Egypt was taken as a study case. The relationship between the URB Program aspects and specific objectives and the existing regional research record and capacity was illustrated; a training programme to enhance the research capacity on water management in the region is proposed (AU)