Water is extremely important for the continuation of life. Therefore, every decision and every step to be taken regarding water is vital [1]. Most of the pollutants in wastewater from industrial sources contain some organic chemicals and pathogens that must be removed or treated before being discharged into different water sources [2].
Synthetic dyes or colorings are basic chemicals for most industries that produce textiles, food, cosmetics, etc... [3, 4]. As a result a huge amount of dyestuff-contaminated water is left from the above industries and dye color is the main recognized pollutant in wastewater [5].
The presence of very small amounts of dyes in water is very pronounced and affects the aesthetic merit, water transparency and gas solubility in various water bodies. Water decolourisation is often more important than the removal of colorless, soluble organic matter, which typically contributes to the bulk of the biochemical oxygen demand (BOD) [6, 7].
Eosin Y (or more commonly, eosin) is one of the dyes that pollutes water. Eosin is a water-soluble dye that is a red crystalline powder, frequently used in textile dyeing and ink manufacturing. It is an acidic pigment belonging to the xanthine group, which has a yellowish-red color with a greenish fluorescence [8].
Organic dyes are considered hazardous water pollutants, so there are several ways to remove them from the environment, which mainly depend on biological, chemical and physical methods [9].
Most of the conventional chemical, physical and biological processes used to treat water contaminated with textile dye have drawbacks such as high cost, high energy requirements, etc… [10]. Therefore, it is urgent to find new and more efficient methods for treating wastewater contaminated with dyes.
In recent years, alternative technologies for treating dyes in industrial waters have been developed. These techniques are known as advanced oxidation processes (AOPs) [11, 12].
AOPs technologies have received wide attention for the decomposition of organic dyes. These technologies are based on the photo enhanced generation of highly reactive hydroxyl radicals, which oxidize the organic matter in solution and completely convert it to water, carbon dioxide and inorganic compounds [13]. Photocatalytic degradation, an AOP process that uses semiconductors such as titanium dioxide and zinc oxide to decompose organic pollutants, has been used in recent years as an effective alternative to treating dye-contaminated wastewater [14]. One of the unique features of the method of using semiconductors as a photocatalyst to remove pigments from polluted water is the complete mineralization into environmentally friendly products, without generating side waste [15]. Other advantages of semiconductors include ease of regeneration, reuse, and activity under readily available UV visible light. Zinc oxide is one of the best photocatalysts used recently [16].
Optimizing the quantities of the photocatalytic reagent plays a major role towards the success of the photocatalytic process [4, 17, 18]. The traditional method involves changing one variable (say the amount of Zn2−) while keeping the rest of the other variable influences constant, and studying the effect of this single variable on the response. This is very time consuming, expensive and complex for a multivariate system. To avoid these difficulties, a statistically based technique, called the response surface method (RSM) is used as a powerful experimental design tool that optimizes the factors influencing the photocatalytic process very precisely [19–22].
The present study is an investigation for the treatment of Eosin yellow dye wastewater by ZnO nano-particles as photocatalyst and for the parameters that affect the process. Also, optimization using RSM is conducted based on Box–Behnken design method.