• The coupling of oxidants with ZVI overcome the impedance of ZVI passive layer.• ZVI/oxidants system achieved fast and long-effective removal of contaminants.• Multiple mechanisms are involved in contaminants removal by ZVI/oxidant system.• ZVI/Oxidants did not change the reducing property of ORP in the fixed-bed system. Zero-valent iron (ZVI) technology has recently gained significant interest in the efficient sequestration of a wide variety of contaminants. However, surface passivation of ZVI because of its intrinsic passive layer would lead to the inferior reactivity of ZVI and its lower efficacy in contaminant removal. Therefore, to activate the ZVI surface cheaply, continuously, and efficiently is an important challenge that ZVI technology must overcome before its wide-scale application. To date, several physical and chemical approaches have been extensively applied to increase the reactivity of the ZVI surface toward the elimination of broad-spectrum pollutants. Nevertheless, these techniques have several limitations such as low efficacy, narrow working pH, eco-toxicity, and high installation cost. The objective of this mini-review paper is to identify the critical role of oxygen in determining the reactivity of ZVI toward contaminant removal. Subsequently, the effect of three typical oxidants (H2O2, KMnO4, and NaClO) on broad-spectrum contaminants removal by ZVI has been documented and discussed. The reaction mechanism and sequestration efficacies of the ZVI/oxidant system were evaluated and reviewed. The technical basis of the ZVI/oxidant approach is based on the half-reaction of the cathodic reduction of the oxidants. The oxidants commonly used in the water treatment industry, i.e., NaClO, O3, and H2O2, can be served as an ideal coupling electron receptor. With the combination of these oxidants, the surface corrosion of ZVI can be continuously driven. The ZVI/oxidants technology has been compared with other conventional technologies and conclusions have been drawn. 相似文献
The problem of algal bloom caused by eutrophication has attracted global attention. Many scholars have studied the problem associated with algae bloom, but few have carried out dynamic monitoring, instead focusing on the formation mechanism of cyanobacteria. For our study of the Taihu Lake in China, we used Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat remote sensing image data from 2017 to establish a prediction model. First, we used MODIS data to retrieve the concentration of N, P, and chlorophyll a in water. Then, we applied the analytic hierarchy process (AHP) model to the inversion results to construct the diffusion potential index. Finally, we used C# to compile the cellular automata (CA) model. We found that the distribution of cyanobacteria predicted by our method was consistent with the algal bloom situation of Taihu Lake in 2017. The results showed that the method effectively predicts the dynamic transfer of cyanobacteria from outbreak to diffusion in a short period of time, which can help decision-makers monitor lake health.