Multivariate Optimization And Modeling of Gas Refinery Oily Wastewaters Treatment Utilizing Activated Carbon As High Throughput Adsorbent

<p style="text-align: left;"><strong>Introduction:</strong> Recently, adsorption-based wastewater treatment had been utilized as a cost-effective, high-throughput, and efficient method. It is reported that to reach an efficient treatment process, the adsorption process should be optimized by a reliable optimization process. In this regard, the response surface method (RSM) is a high throughput approach due to evaluating factors interactions and reducing the number of experimental runs, as well as, time- and cost-saving. <p style="text-align: left;"><strong>Methods:</strong> Multivariate optimization and modeling of gas refinery wastewater treatment were performed by utilizing activated carbon (AC) as a high throughput adsorbent through an adsorption mechanism. The AC was characterized by SEM, FT-IR, and XRD analysis. The specific surface area of AC as one of the most important factors that affect the adsorption yield was calculated by BET&amp;BJH as high as 897 m2 g-1. The factors affecting the removal yield including adsorbent amount, treatment time, temperature, and pH were optimized by multivariate optimization upon a response surface method (21 runs) for two types of wastewaters of gas refineries using Design-Expert software. <p style="text-align: left;"><strong>Findings:</strong> At optimal experimental conditions, the method revealed an %COD removal of 93.0% and 87.0% for output and input wastewater API gravity pool, in turn. Besides, the kinetic studies were performed for both output and input wastewaters, revealing that the adsorption process followed the intraparticle diffusion kinetics for the COD removal from both output and input wastewaters API gravity pool.