期刊
WATER PRACTICE AND TECHNOLOGY
卷 17, 期 1, 页码 1-13出版社
IWA PUBLISHING
DOI: 10.2166/wpt.2021.089
关键词
alum; humic acid; photocatalysis; residuals; ZnO
Utilizing alum residuals and zinc oxide composites significantly improved the photocatalytic degradation of humic acid, increasing removal efficiency and reducing energy consumption. An artificial neural network model was developed for predicting removal efficiency under different operating conditions, with the optimum structure achieving a high coefficient of determination.
Alum residuals were collected from a water treatment plant and used for improving the photocatalytic degradation of humic acid (HA) by combinations of zinc oxide (ZnO) and powdered residuals from water purification plant (PRWPP). The influence of operating conditions such as initial humic acid concentration, pH, irradiation time, PRWPP to ZnO ratio, catalyst dose, and light illuminance have been investigated. The optimum PRWPP to ZnO ratio was 10:90. Using the prepared composites instead of bare ZnO raised the HA removal efficiency from 85.5% to 97.8%, and from 38% to 48.1% at catalyst doses of 1.2 g/l and 0.4 g/l, respectively. Moreover, it reduced energy consumption from 210.4 to 166.2 Wh per mg of HA. An artificial neural network model (ANN) was developed to predict the removal efficiency under different operating conditions. The optimum ANN structure yielded a coefficient of determination (R-2 = 0.993). Modified Langmuir-Hinshelwood pseudo-first-order model was used for describing the degradation kinetics at different initial concentrations of HA.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据