A New Approach in Regression Analysis for Modeling Adsorption Isotherms

Numerous regression approaches to isotherm parameters estimation appear in the literature. The real insight into the proper modeling pattern can be achieved only by testing methods on a very big number of cases. Experimentally, it cannot be done in a reasonable time, so the Monte Carlo simulation method was applied. The objective of this paper is to introduce and compare numerical approaches that involve different levels of knowledge about the noise structure of the analytical method used for initial and equilibrium concentration determination. Six levels of homoscedastic noise and five types of heteroscedastic noise precision models were considered. Performance of the methods was statistically evaluated based on median percentage error and mean absolute relative error in parameter estimates. The present study showed a clear distinction between two cases. When equilibrium experiments are performed only once, for the homoscedastic case, the winning error function is ordinary least squares, while for the case of heteroscedastic noise the use of orthogonal distance regression or Margart's percent standard deviation is suggested. It was found that in case when experiments are repeated three times the simple method of weighted least squares performed as well as more complicated orthogonal distance regression method

Arsenate adsorption on waste eggshell modified by goethite, alpha-MnO2 and goethite/alpha-MnO2

An efficient adsorbents for arsenate removal was developed by modification of calcined eggshell with goethite (calcined eggshell/goethite; sorbent 1), alpha-MnO2 (calcined eggshell/alpha-MnO2; sorbent 2) and hybride system goethite/alpha-MnO2 (calcined eggshell/goethite/alpha-MnO2; sorbent 3). Methods and processes for preparation of novel adsorbents were defined and obtained materials were characterized by BET, XRD, SEM and FTIR analysis. The influence of functionalization methods, solution pH, contact time, temperature, interfering ions and initial arsenate concentration on efficiencies of arsenate adsorption were studied in a batch system. Based on the orthogonal distance regression (ODR) fitting, using R-2, MARE and RMSRE statistical criteria, Langmuir and Sips equations were chosen for description of adsorption equilibriums on sorbents 1 and 3, respectively. The maximum adsorption capacities of 33.38 mg g(-1), 13.54 mg g(-1) and 47.04 mg g(-1) for sorbents 1-3, respectively, were obtained. Time-dependent study revealed that pseudo-second-order equation fitted well the kinetic data, while the Weber Morison model predicted intra-particle diffusion as main adsorption rate controlling step. Thermodynamic parameters indicated exothermic, feasible and spontaneous nature of adsorption process on sorbents I and 3. Results of Visual MINTEQ equilibrium speciation modeling program was used for studying pH, ionic strength and interfering ions influences on arsenate adsorption

Arsenic Removal from Water Using Industrial By-Products

In this study, removal of arsenic ions using two industrial by-products as adsorbents is represented. Removal of As(III) and As(V) from water was carried out with industrial by-products: residual from the groundwater treatment process, iron-manganese oxide coated sand (IMOCS), and blast furnace slag from steel production (BFS), both inexpensive and locally available. In addition, the BFS was modified in order to minimise its deteriorating impact on the initial water quality. Kinetic and equilibrium studies were carried out using batch and fixed-bed column adsorption techniques under the conditions that are likely to occur in real water treatment systems. To evaluate the application for real groundwater treatment, the capacities of the selected materials were further compared to those exhibited by commercial sorbents, which were examined under the same experimental conditions. IMOCS was found to be a good and inexpensive sorbent for arsenic, while BFS and modified slag showed the highest affinity towards arsenic. All examined waste materials exhibited better sorption performances for As(V). The maximum sorption capacity in the batch reactor was obtained for blast furnace slag, 4040 μgAs(V)/g