The aim of this study was to investigate the potential of treated rice husk ash (RHA) as adsorbent to adsorb acidic SO2 gas. The treated RHA was prepared using a water hydration method by mixing the RHA, Calcium oxide (CaO) and Sodium Hydroxide (NaOH). The addition of NaOH is to increase the dissolution of silica from the RHA to form reactive species responsible for higher desulfurization activity. The untreated and treated RHA were subjected to several characterizations and the characteristics of the adsorbents were compared. The functional groups present on the surface of the adsorbent were determined using Fourier Transform Infrared (FTIR). The chemical composition of the untreated and treated RHA was analyzed by using X-ray Fluorescence (XRF). Scanning electron microscope (SEM) analysis showed that the treated RHA has higher porosity compared to untreated RHA. Based on the SO2 adsorption analysis, it was found that the treated RHA has higher adsorption capacity, 62.22 mg/g, compared to untreated RHA, 1.49 mg/g.
Cross-linked chitosan-epichlorohydrin was prepared for the adsorption of Reactive Red 4 (RR4).
Response surface methodology (RSM) with 3–level Box-Behnken design (BBD) was employed to
optimize the RR4 dye removal efficiency from aqueous solution. The adsorption key parameters that were selected such as adsorbent dose (A: 0.5 – 1.5 g), pH (B: 4 – 10) and time (30 – 80 min). The F-value of BBD model for RR4 removal efficiency was 185.36 (corresponding p-value < 0.0001). The results illustrated that the highest RR4 removal efficiency (70.53%) was obtained at the following conditions: adsorbent dose (1.0 g), pH 4 and time of 80 min.
Chitosan-epichlorohydrin/TiO2 composite was synthesized to be employed as an adsorbent for the
removal of reactive red 4 (RR4) dye from aqueous solution. Response surface methodology (RSM) with 3-level Box-Behnken design (BBD) was utilized for the optimization of the removal of RR4. The process key variables which include adsorbent dose (A: 0.5 – 1.5 g), pH (B: 4 – 10) and time (30 – 80 min) were selected for the optimization process. The experimental data for RR4 removal were statistically analysed using analysis of variance (ANOVA). The significant interaction between key parameters on RR4 removal efficiency was observed by interaction between AB and AC. The highest RR4 removal (95.08%) was obtained under the following conditions; adsorbent dose (1.0 g), pH 4 and time of 80 min.