Environmental Engineering / Çevre Mühendisliği

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  • Book Part
    Arsenic Removal by Electrocoagulation
    (Wiley, 2022) Gören, Ayşegül Yağmur; Kobya, Mehmet
    Because of the toxic impacts on human health, the arsenic (As) limit value in drinking water was decreased from 50 to 10 ?g l-1 by the relevant authorities (WHO 1993; US EPA 2001). In this case, the problem of As pollution in natural water resources used for drinking water has grown even more and turned into a global crisis. According to reports in many parts of the world, over about 230 million people appear to be affected by high arsenic concentrations in groundwater. In this case, it turned out that there was a great need for cost-effective and environmentally friendly technologies from drinking water sources. One of the emerging water treatment technologies in recent years is electrocoagulation (EC) and it has been seen that it is effective in treating As (>99%) from water and eliminates some of the disadvantages of other conventional treatment processes. EC method includes electro-oxidation of anode electrode materials (iron and aluminum) and in situ production of coagulant agents. From groundwater resources with As content of 5-1000 ?g l-1, As removal efficiencies and operating costs (OCS) of EC technology using iron (Fe) and aluminum (Al) anodes were 85.0-99.9% and 0.0020-1.04 US$ m-3, respectively. Different types (plate, scrap, rod, and ball) of electrodes were used for As removal with the EC process, and it was observed that Fe electrodes or Fe-Al hybrid electrodes performed better in As removal. In addition, it has been determined that arsenate (As(V)) removal is more effective than arsenite (As(III)). A significant quantity of As(III) is oxidized in the EC process, resulting in precipitation, adsorption, and metal-oxy hydroxylic complex reactions. EC process has a lower OC to achieve As removal below the permissible WHO value compared to conventional treatment processes, accomplishing it as a further applicable option for As removal. © 2023 John Wiley & Sons, Inc.
  • Book Part
    Citation - Scopus: 32
    Language of Response Surface Methodology as an Experimental Strategy for Electrochemical Wastewater Treatment Process Optimization
    (Elsevier, 2022) Gören, Ayşegül Yağmur; Recepoğlu, Yaşar Kemal; Khataee, Alireza
    The availability and accessibility to safe and secure water resources are the key technological and scientific concerns of global significance. As a result of water scarcity worldwide, wastewater treatment and reuse are considered viable options to replace freshwater resources in agricultural irrigation and domestic and industrial purposes. A significant need for clean water has promoted the invention and/or enhancement of several electrochemical wastewater treatment (EWT) processes. Optimization of the process variables plays a crucial role in wastewater treatment to enhance technology performance, considering removal efficiency, operating cost, and environmental impacts. These processes are fundamentally complex multivariable, and the optimization through conventional methods is unreliable, inflexible, and time- and material-consuming. In this perspective, response surface methodology (RSM) appears to be a beneficial statistical experimental strategy for the performance optimization of the EWT process. This model could be utilized for the optimization and analysis of the individual and/or combined effects of operational variables on the treatment process to improve the system performance. Furthermore, this model provides a number of information from a slight number of experimental trials. In this chapter, a summary and a discussion are presented on the RSM model used in the electrochemical wastewater treatment processes to overcome process crucial challenges toward the optimization and modeling of process parameters. It provides a potential model to enhance the various types of wastewater treatment process performance with effective optimization. Overall, it is described that the RSM model can be used in EWT processes to find the optimum conditions.