نویسندگان | سیدمهدی موسوی بفروئیه,داروش سالاری,علیقلی نیایی,پروانه نخستین پناهی |
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همایش | Asian Nano Forum Congress (ANFC2015) |
تاریخ برگزاری همایش | ۲۰۱۵-۳-۸ |
محل برگزاری همایش | کیش |
نوع ارائه | سخنرانی |
سطح همایش | بین المللی |
چکیده مقاله
The studies of the NOx emission control are one of the most important issues in the air pollution control and environmental protection, because of its various problems such as respiratory diseases, acid rain and photochemical smog. The selective catalytic reduction of NOx with ammonia (NH3-SCR) is a well-known technology for NOx emission control. In recent years, ceria mixed oxide nanocatalysts have been developed for NOx reduction, due to theirs good oxygen storage and release capabilities as well as redox properties. In this research, design of experiments (DOE) is used to model and optimize of NOx reduction by NH3 over Ba-CeO2-MnOx mixed oxide nanocatalysts. The CeO2-MnOx mixed oxide with Ce/(Ce+Mn) molar ratio of 0.75 was prepared by the sol-gel combustion method. Barium was loaded on the CeO2-MnOx mixed oxide by wetness impregnation method. The NH3-SCR tests were performed in a fixed bed reactor with a feed gas mixture consisting NO, NH3, O2 and Ar as balance (total flow rate of 200 cm3 min-1). A response surface methodology (RSM) is utilized to model and optimize the effect of process parameters, including concentration of O2 (vol. %), NH3/NO ratio in the gas feed, gas hourly space velocity (GHSV) and reaction temperature (°C) on the NO conversion and N2 selectivity as responses. The R2 values for both generated model were greater than 0.9. According to the results, GHSV had largest and negative effect on the NO conversion, while it was an insignificant parameter on the N2 selectivity in design space. Also NH3/NO ratio was most effective parameter on the N2 selectivity. Under the optimum conditions: 4.75 vol.% O2, NH3/NO ratio of 0.9, GHSV of 12000 h-1 and 197.5 °C, the predicted values for NO conversion and N2 selectivity were 96.47% and 93.96%, respectively. The obtained experimental values in optimum condition agreed with those predicted, indicating suitability of the RSM model to estimate the values of the responses.