The adsorption of the dyes Basic Red 46 (BR46) and Reactive Yellow 176 (RY176) from aqueous solution onto natural and modified zeolites has been investigated. The surfactants cetyltrimethylammonium bromide (CTAB) and hexadecyltrimethylammonium bromide (HDTMA) were used to modify the zeolite surface, and Fourier transform infrared spectroscopy (FTIR) spectral analysis was used to confirm the surface modification. The effects of initial dye concentration, contact time, pH, temperature, ionic strength, and surfactant type on adsorption were studied in a batch system. BR46 adsorption onto natural zeolite increased to minor a extent with increasing pH, whereas pH did not significantly affect RY176 adsorption. Adsorption capacities of dyes increased with contact time, initial concentration, and temperature for both BR46 and RY176. The increase in ionic strength caused a decrease in adsorption of BR46 and an increase in adsorption of RY176. Adsorption of BR46 on natural zeolite is more favorable than RY176 on the CTAB and HDTMA modified zeolites. The adsorption of basic and reactive dyes was spontaneous and endothermic as concluded from thermodynamic assays.
A three-layer Artificial Neural Network (ANN) model was developed to forecast air pollution levels. The subsequent SO 2 concentration (24-hour averaged) being the output parameter of this study was estimated by seven input parameters such as preceding SO 2 concentrations (24-hour averaged), average daily temperature, sea-level pressure, relative humidity, cloudiness, average daily wind speed and daily dominant wind direction. After Backpropagation training combined with Principal Component Analysis (PCA), the proposed model predicted subsequent SO 2 values based on measured data. ANN testing outputs were proven to be satisfactory with correlation coefficients of about 0.770, 0.744 and 0.751 for the winter, summer and overall data, respectively.
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