Pre-Treatment of Industrial Mineral Oil Wastewater Using Response Surface Methodology

Abstract

This study focuses on the process optimization of coagulation floatation by cross-interaction effects of the following multiple factors: pH, coagulant dosage and floatation time on the response of chemical oxidation demand (COD), soap oil and grease (SOG), turbidity and total suspended solids (TSS). The results from the response surface methodology incorporated with Box Benken design (BBD) models reveals significant correlations and interactions between the manipulated and response variables. To establish the optimum pre-treatment conditions, the experiment used the design BBD, using Design Expert (Design Expert 10.0.3) software. This ensures that the process engineers and scientists gain a better understanding of the practical application of the experimental results over the conventional method of one-factor-at-time (OFAT). The recent trend in industrialization and population growth has indeed deepened the demand on the world's energy (oil) and water resources. However, the need to meet the significance of energy and water for sustainable social economy growth and development has resulted in extremely adverse effects on water and environmental pollution. South Africa, well known as a water scarcity country, has also intensified its policy and increased fines for offenders who do not meet its regulations and discharge limits. In this context, the treatment of industrial mineral oil wastewater, which is regarded as hazardous and harmful to the environment, derived from petrochemical and oil refinery industries, has a recovery value. This has raised attention for systematic technology and approach in recovering oil and water for reuse to conserve the supply of fresh water and energy resources.

Acid Dye Removal from Aqueous Solution by Using Neodymium(III) Oxide Nanoadsorbents

“…On the other hand, the values found that were higher than 0.1000 indicate that the model terms are not significant. The factor coefficient confirms the influence of a fixed factor, while the two combined factors coefficients can reveal the interaction between them [49]. Table 3 indicates that independent variable, initial AB92 concentration (F-value: 161.7921) has the highest effect on the AB19 adsorption followed by initial pH (F-value: 116.8807), nanoadsorbent's dosage (F-value: 19.2103) and contact time (F-value: 6.0019).…”

“…The p-values were used to check the significance of each of the interactions among the variables, which may indicate the patterns of the interactions among the variables. A p-value less than 0.05 shows the influence and significance of a term [49]. After analysis, the Fisher's F-value was found to be 25.4683, suggesting that the model is significant for dye adsorption, presenting a 95% confidence level.…”

“…The pH is a very significant factor that affects an adsorption process [51][52][53]. The effect of pH on AB92 adsorption is linked to the solution pH and the functional groups exhibited by the Nd 2 O 3 nanoparticles which will consecutively influence its surface charge [49]. The adsorption percentage was increased by decreasing the pH of the solution.…”

Degradation of Veterinary Antibiotics From Slaughterhouse Wastewater Using Titanium Dioxide as a Catalyst

“…The design was applied for a threelevel variable on the response function, thus giving a minimum number of experiment. Further details about the application of the BBD and the advantages it presents can be found in the work by [14]. Table 1 shows the experimental design inputs and factors, three independent variables were used and codified for low, centre and high levels (-1, 0, +1).…”

“…The ranges of the variables and experimental conditions are shown further in Table 1. Input variables were coded according to eqn (2) [14]:…”