Graduate Institute of Environmental Engineering, National Taiwan University, Taiwan.
J Environ Sci Health B. 2013;48(8):686-92. doi: 10.1080/03601234.2013.778623.
Photocatalytic degradation of malathion, is investigated using Titanium Nanotubes (TNT) and Pt modified TNT (Pt-TNT) photocatalyst in an aqueous solution under 365 nm UV lamp irradiation. The TNT photocatalyst is prepared on pretreated strong alkaline solution via the hydrothermal method. The Pt-TNT was prepared by light deposition. The variations in morphology, formation mechanism, phase structure, and pore structure of TNT and Pt-TNT are characterized using UV-Vis, transmission electron microscopy (TEM), and N₂ adsorption/desorption isotherm analyzer, respectively. The effect of the initial malathion concentration, reaction temperature, catalyst loading, solution pH value, irradiation time and Pt loading are studied and the optimized values are obtained. Moreover, the photodegradation performance and kinetics of malathion onto TNT and Pt-TNT are also examined with the aid of model analysis by kinetic data. The results show that under acid conditions, the performance of photocatalysts for treating malathion is high. The time of complete degradation increases with an increase in the initial malathion concentration. The degradation rate decreases with increasing initial malathion concentration. The degradation efficiency can reach 100% under acid conditions for any initial malathion concentration when the reaction time is 70 min. In addition, experimental decoloration kinetics data follow the pseudo-first-order reaction model.
采用钛纳米管(TNT)和 Pt 修饰的 TNT(Pt-TNT)光催化剂,在 365nmUV 灯照射下,在水溶液中研究马拉硫磷的光催化降解。TNT 光催化剂通过水热法在预处理过的强碱性溶液中制备。Pt-TNT 通过光沉积法制备。采用紫外-可见分光光度计、透射电子显微镜(TEM)和 N₂吸附/脱附等温线分析仪分别对 TNT 和 Pt-TNT 的形貌、形成机理、相结构和孔结构进行了表征。研究了初始马拉硫磷浓度、反应温度、催化剂负载量、溶液 pH 值、照射时间和 Pt 负载量的影响,并获得了优化值。此外,还借助动力学数据分析模型,研究了马拉硫磷在 TNT 和 Pt-TNT 上的光降解性能和动力学。结果表明,在酸性条件下,处理马拉硫磷的光催化剂性能较高。完全降解所需的时间随初始马拉硫磷浓度的增加而增加。降解速率随初始马拉硫磷浓度的增加而降低。在反应时间为 70min 时,在任何初始马拉硫磷浓度下,在酸性条件下,降解效率均可达 100%。此外,实验脱色动力学数据符合拟一级反应模型。