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Researchers have recently focused their attention on emerging contaminants (ECs) in wastewater because they pose serious health and environmental risks. Because ECs are persistent in the environment and have the ability to disrupt the physiology of target receptors, they have been labeled as contaminants of recent environmental concern. For removing various ECs, a variety of treatment technologies have been developed, including biological, chemical, and physical methods. However, no single technology can currently effectively remove ECs, whereas hybrid systems have consistently proven to be more effective. Furthermore, the majority of existing technologies are energy and resource intensive, as well as expensive to maintain and operate. Furthermore, the majority of advanced treatment technologies that have been proposed have yet to be evaluated for large-scale feasibility. Some ECs, particularly pharmaceuticals and pesticides, were found to be significantly removed using a hybrid technique that included ozone/UV and granular activated carbon (GAC). Besides, the removal of effluent parameters (TDS, COD, TOC) was enhanced through the GAC surface oxidization as a catalyst with NaOH before the process and by ozone within the procedure as well. [ABSTRACT FROM AUTHOR]

Treatment of organic leachate is one the most controversial topics around the world which led this study to assess the efficiency of the combined oxidation and adsorption treatment (COAT) process in the treatment of forest polluting site (FPS) leachate by considering local experiments. The removal of effluent parameters (TDS, COD, BOD) was enhanced by oxidizing the GAC surface as a catalyst with NaOH before the process and by ozone within the procedure as well. comparison between COAT process and ozone-GAC was investigated based on variation in ozone dose, H2O2 and pH. Assessing the interacting effect of operating variables (i.e., ozone concentration, GAC density, reaction time and pH) provides valuable information for optimization. Response surface methodology (RSM) and for better prediction, another modeling tool, artificial neural networks (ANN), were employed. Moreover, the results of both software were compared and ANN showed a higher R2 of 0.908, 0.923, and 0.919 for TDS, COD, and BOD respectively in contrast with RSM (R2: TDS = 0.8538, COD = 0.9105, BOD = 0.8108). The optimized model's circumstances are the reaction time of 30.77 min, ozone dosage of 141.29 mg/l, pH of 7.2, and the GAC density of 1.29 gr/cm3 with the predicted removal percentage of 51.63%, 62.84%, and 56.13% for TDS, COD, and BOD respectively. Meanwhile, in the experimental situation among the various methods, the COAT process by the removal percentage of TDS = 59.47%, COD = 68.37%, and BOD = 67% showed proper efficiency. [ABSTRACT FROM AUTHOR]