A review of combined advanced oxidation technologies for the removal of organic pollutants from water

Water pollution through natural and anthropogenic activities has become a global problem causing short-and long-term impact on human and ecosystems. Substantial quantity of individual or mixtures of organic pollutants enter the surface water via point and nonpoint sources and thus affect the quality of freshwater. These pollutants are known to be toxic and difficult to remove by mere biological treatment. To date, most researches on the removal of organic pollutants from wastewater were based on the exploitation of individual treatment process. This single-treatment technology has inherent challenges and shortcomings with respect to efficiency and economics. Thus, application of two advanced treatment technologies characterized with high efficiency with respect to removal of primary and disinfection by-products in wastewater is desirable. This review article focuses on the application of integrated technologies such as electrohydraulic discharge with heterogeneous photocatalysts or sonophotocatalysis to remove target pollutants. The information gathered from more than 100 published articles, mostly laboratories studies, shows that process integration effectively remove and degrade recalcitrant toxic contaminants in wastewater better than single-technology processing. This review recommends an improvement on this technology (integrated electrohydraulic discharge with heterogeneous photocatalysts) viz-a-vis cost reduction in order to make it accessible and available in the rural and semi-urban settlement. Further recommendation includes development of an economic model to establish the cost implications of the combined technology. Proper monitoring, enforcement of the existing environmental regulations, and upgrading of current wastewater treatment plants with additional treatment steps such as photocatalysis and ozonation will greatly assist in the removal of environmental toxicants

Impact of blend properties and process variables on the blending performance

In this study, quantitative relationships were established between blend properties, process settings and blending responses via multivariate data-analysis. Four divergent binary blends were composed in three different ratios and processed at various throughputs and impeller speeds. Additionally, different impeller configurations were tested to see their impact on the overall blending performance. During each run, feeder mass flows were compared with the API concentration (BU) in order to investigate the dampening potential of the blender. The blender hold-up mass (HM), mean residence time (MRT), strain on the powder (#BP) and BU variability (RSDBU) were determined as blending descriptors and analyzed via PLS-regression. This elucidated the correlation between process settings (i.e. throughput and impeller speed) and blending responses, as well as the impact of blend properties on MRT and RSDBU. Furthermore, the study revealed that HM does not need to be in steady state conditions to assure a stable BU, while it became clear that long/large feeder deviations can only be dampened by the blender when using dedicated impeller configurations. Overall, this study demonstrated the generic application of the blender, while the developed PLS models could be used to predict the blender performance based on the blend properties

Determination of a quantitative relationship between material properties, process settings and screw feeding behavior via multivariate data-analysis

In this study, a quantitative relationship between material properties, process settings and screw feeding responses of a high-throughput feeder was established via multivariate models (PLS). Thirteen divergent powders were selected and characterized for 44 material property descriptors. During volumetric feeder trials, the maximum feed capacity (FCCmax), the relative standard deviation on the maximum feed capacity (RSDFCmax), the short term variability (STRSD) and feed capacity decay (FCdecay) were determined. The gravimetric feeder trials generated values for the mass flow rate variability (RSDLC), short term variability (STRSD) and refill responses (V-refill and RSDrefill). The developed PLS models elucidated that the material properties and process settings were clearly correlated to the feeding behavior. The extended volumetric feeder trials pointed out that there was a significant influence of the chosen screw type and screw speed on the feeding process. Furthermore, the process could be optimized by reducing the feeding variability through the application of optimized mass flow filters, high frequency vibrations, independent agitator control and optimized top-up systems. Overall, the models could allow the prediction of the feeding performance for a wide range of materials based on the characterization of a subset of material properties greatly reducing the number of required feeding experiments