In this study, the kinetic parameters of rice husk ash (RHA)/CaO/CeO(2) sorbent for SO(2) and NO sorptions were investigated in a laboratory-scale stainless steel fixed-bed reactor. Data experiments were obtained from our previous results and additional independent experiments were carried out at different conditions. The initial sorption rate constant (k(0)) and deactivation rate constant (k(d)) for SO(2)/NO sorptions were obtained from the nonlinear regression analysis of the experimental breakthrough data using deactivation kinetic model. Both the initial sorption rate constants and deactivation rate constants increased with increasing temperature, except at operating temperature of 170 °C. The activation energy and frequency factor for the SO(2) sorption were found to be 18.0 kJ/mol and 7.37 × 10(5)cm(3)/(g min), respectively. Whereas the activation energy and frequency factor for the NO sorption, were estimated to be 5.64 kJ/mol and 2.19 × 10(4)cm(3)/(g min), respectively. The deactivation kinetic model was found to give a very good agreement with the experimental data of the SO(2)/NO sorptions.
The SO2 sorption capacity (SSC) of sorbents prepared from rice husk ash (RHA) with NaOH as additive was studied in a fixed-bed reactor. The sorbents were prepared using a water hydration method by slurrying RHA, CaO, and NaOH. Response surface methodology (RSM) based on four-variable central composite face centered design (CCFCD) was employed in the synthesis of the sorbents. The correlation between the sorbent SSC (as response) with four independent sorbent preparation variables, i.e. hydration period, RHA/CaO ratio, NaOH amount, and drying temperature, were presented as empirical mathematical models. Among all the variables studied, the amount of NaOH used was found to be the most significant variable affecting the SSC of the sorbents prepared. The SSC for sorbent prepared with the addition of NaOH was found to be significantly higher than sorbents prepared without NaOH. This is probably because NaOH is a deliquescent material, and its existence increases the amount of water collected on the surface of the sorbent, a condition required for sorbent-SO2 reaction to occur at low temperature. The effect of further treatment of RHA at 600 degrees C was also investigated. Although pretreated RHA sorbents demonstrated higher SSC as compared to untreated RHA sorbents, nevertheless, at optimum conditions, sorbents prepared from untreated RHA was found to be more favorable due to practical and economic concerns.
In this study, palm oil mill sludge was used as a precursor to prepare biochar using conventional pyrolysis. Palm oil mill sludge biochar (POSB) was prepared at different preparation variables, i.e., heating temperature (300-800 °C), heating rate (10-20 °C/min) and holding time (60-120 min). The prepared biochars were tested for sulfur dioxide (SO2) adsorption in a fixed bed reactor using 300 ppm of SO2 gas at 300 ml/min (with N2 gas as balance). Response surface central composite experimental design was used to optimize the production of biochar versus SO2 removal. A quadratic model was developed in order to correlate the effect of variable parameters on the optimum adsorption capacity of SO2 gas. The experimental values and the predicted results of the model were found to show satisfactory agreement. The optimum conditions for biochar preparation to yield the best SO2 removal was found to be at 405 °C of heating temperature, 20 °C/min of heating rate and 88 min of holding time. At these conditions, the average yield of biochar and adsorption capacity for SO2 gas was reported as 54.25 g and 9.75 mg/g, respectively. The structure of biochar and their roles in SO2 adsorption were investigated by surface area, morphology images, infrared spectra, and proximate analysis, respectively. The characterization findings suggested that POSB adsorbs SO2 mainly by the functional groups.
In this work, the application of response surface and neural network models in predicting and optimizing the preparation variables of RHA/CaO/CeO(2) sorbent towards SO(2)/NO sorption capacity was investigated. The sorbents were prepared according to central composite design (CCD) with four independent variables (i.e. hydration period, RHA/CaO ratio, CeO(2) loading and the use of RHA(raw) or pretreated RHA(600 degrees C) as the starting material). Among all the variables studied, the amount of CeO(2) loading had the largest effect. The response surface models developed from CCD was effective in providing a highly accurate prediction for SO(2) and NO sorption capacities within the range of the sorbent preparation variables studied. The prediction of CCD experiment was verified by neural network models which gave almost similar results to those determined by response surface models. The response surface models together with neural network models were then successfully used to locate and validate the optimum hydration process variables for maximizing the SO(2)/NO sorption capacities. Through this optimization process, it was found that maximum SO(2) and NO sorption capacities of 44.34 and 3.51 mg/g, respectively could be obtained by using RHA/CaO/CeO(2) sorbents prepared from RHA(raw) with hydration period of 12h, RHA/CaO ratio of 2.33 and CeO(2) loading of 8.95%.
Siliceous materials such as rice husk ash (RHA) have potential to be utilized as high performance sorbents for the flue gas desulfurization process in small-scale industrial boilers. This study presents findings on identifying the key factorfor high desulfurization activity in sorbents prepared from RHA. Initially, a systematic approach using central composite rotatable design was used to develop a mathematical model that correlates the sorbent preparation variables to the desulfurization activity of the sorbent. The sorbent preparation variables studied are hydration period, x1 (6-16 h), amount of RHA, x2 (5-15 g), amount of CaO, x3 (2-6 g), amount of water, x4 (90-110 mL), and hydration temperature, x5 (150-250 degrees C). The mathematical model developed was subjected to statistical tests and the model is adequate for predicting the SO2 desulfurization activity of the sorbent within the range of the sorbent preparation variables studied. Based on the model, the amount of RHA, amount of CaO, and hydration period used in the preparation step significantly influenced the desulfurization activity of the sorbent. The ratio of RHA and CaO used in the preparation mixture was also a significant factor that influenced the desulfurization activity of the sorbent. A RHA to CaO ratio of 2.5 leads to the formation of specific reactive species in the sorbent that are believed to be the key factor responsible for high desulfurization activity in the sorbent. Other physical properties of the sorbent such as pore size distribution and surface morphology were found to have insignificant influence on the desulfurization activity of the sorbent.