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在流化床光反应器中用改性纳米二氧化钛(TiO)光催化降解空气污染物:优化与动力学建模。

Photocatalytic degradation of air pollutant by modified nano titanium oxide (TiO)in a fluidized bed photoreactor: Optimizing and kinetic modeling.

机构信息

State Key Laboratory of Bio-Fibers and Eco Textiles, Qingdao University, Qingdao, 266071, China.

School of Computer and Information Science, Hubei Engineering University, Xiaogan, 432000, China.

出版信息

Chemosphere. 2023 Apr;319:137995. doi: 10.1016/j.chemosphere.2023.137995. Epub 2023 Jan 30.

Abstract

Volatile organic compound (VOC) removal by photocatalytic oxidation (PCO) is the practical and economical process to reduce air pollutants. Many conditions, such as temperature, initial concentration of VOC, relative humidity, gas flow rate, and light intensity, affected this process. Therefore, finding the optimal operating conditions for the PCO process can increase the efficiency of the process and also operate the process more economically. Also, it is possible to scale up the process with more confidence by the kinetics modeling of the process and finding the rate constants. In this study, the effect of gas flow rate, light intensity, and VOC inlet concentration were investigated. The results show that the flow rate of 15 lit/min is more efficient, and the effect of the pollutant input concentration and light intensity directly affects the conversion percentage. The kinetic study of acetaldehyde removal was investigated in the fluidized bed reactor, and the best kinetic model was proposed based on reactor model regression on the outlet concentration data. The best model describes a langmuir-hynshelwood type model with adsorbed acetaldehyde's inhibition effect on the catalyst's surface. The R coefficient for the best kinetic type is 0.98.

摘要

挥发性有机化合物(VOC)的光催化氧化(PCO)去除是减少空气污染物的实用且经济的过程。许多条件,如温度、VOC 的初始浓度、相对湿度、气体流速和光强度,都会影响这个过程。因此,找到 PCO 过程的最佳操作条件可以提高过程的效率,并且更经济地运行过程。此外,通过该过程的动力学建模和找到速率常数,可以更有信心地对过程进行放大。在这项研究中,研究了气体流速、光强度和 VOC 入口浓度的影响。结果表明,流速为 15 升/分钟更有效,并且污染物输入浓度和光强度的影响直接影响转化率。在流化床反应器中研究了乙醛去除的动力学,并且根据出口浓度数据对反应器模型回归提出了最佳动力学模型。最佳模型描述了具有吸附乙醛对催化剂表面抑制作用的朗缪尔-欣谢尔伍德型模型。最佳动力学类型的 R 系数为 0.98。

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