Optimization of iron removal in water by nanobubbles using response surface methodology

Iron contamination, causing staining, discoloration and bad taste, is a worldwide water problem. It is necessary to focus on iron oxidation from the water. This work aims to develop nanobubbles (NBs) technology to remove iron (Fe 2 þ ) from aqueous solutions. In batch experiments, the effects of initial Fe 2 þ concentration, pH, and aeration pressure on the Fe 2 þ oxidation ef ﬁ ciency were carried out. The results showed that initial concentrations, pH and aeration pressure are signi ﬁ cant parameters in ﬂ uencing Fe 2 þ oxidation. On the basis of single factor experiments, the Box – Behnken design was used to optimize the Fe 2 þ oxidation conditions with NBs using three parameters (Fe 2 þ concentration, pH, and aeration pressure) under the response surface methodology. The optimal Fe 2 þ oxidation was achieved when the initial concentration was 13.7 mg·L (cid:2) 1 , pH ¼ 9, and the aeration pressure was 290 kPa. The regression model of Fe 2 þ oxidation rate under optimized test conditions is accurate and effective. The results showed that the combination of single factor test and response surface optimization can be used to optimize the Fe 2 þ oxidation process with NBs. It is concluded that NBs technology is promising for Fe 2 þ oxidation from water.


GRAPHICAL ABSTRACT INTRODUCTION
With the increase in industrial development, groundwater pollution is increasing worldwide. Iron is an indispensable basic element for human and animals. Its deficiency can cause changes in children's physical activities and mental development (Demlie et al. ). However, high iron can cause water pollution and many risks to human health, such as heart and liver damage, diabetes, liver cirrhosis, cartilage calcium, and other diseases. For water supply, iron (Fe 2þ ) causes staining, discoloration, bad taste, corrosion of pipes, and increase fouling and clogging in the pipelines, thereby improving bacterial growth and affecting water quality (Xie et al. ). For industries, such as printing, dyeing, and papermaking, high iron in water can decrease the quality of the products. According to the current Sanitary Standard for Drinking Water of China (GB5749-2006), iron in drinking water should not be higher than 0.3 mg·L À1 (Wang et al. ). Therefore, more attention must be paid to iron removal from water.
A common iron treatment for groundwater uses the processes of oxidation followed by sedimentation or filtration.
The chemicals for iron oxidation include potassium permanganate (KMnO 4 ), chlorine, and ozone (Choo et al. ; Phatai et al. ). KMnO 4 is more expensive than other oxidants and it is important to control the dosage to ensure all the iron has been oxidized and prevent the formation of pink sediment. Chlorination may cause trihalomethanes (THMs) formation, which can cause serious problems to human health.
The oxidation efficiency of ozone may be obviously reduced by the humic or fulvic substances in water (Chaturvedi & Dave ). Therefore, a suitable oxidizing agent for iron is oxygen without the addition of chemicals. The natural oxidation process takes a long time and requires large-scale equipment, resulting in increased costs. It is important to have a simple operation with high oxidation efficiency and sustainable development for iron pre-oxidation technology.
In the past decades, nanobubbles (NBs) have been used in many water or wastewater treatment processes. The lead (Pb(II)) adsorption process of activated carbon can be accelerated by 366% using air NBs (Kyzas et al. ). The combination of precipitation and flotation with micro-bubbles and NBs can remove 81% calcium ions (Ca 2þ ) and 91% magnesium ions (Mg 2þ ) from water (Silva et al. ). Using a micro-nano bubble aeration device to treat domestic sewage, the removal efficiency of chemical oxygen demand (COD), suspended solids (SS) and ammonia nitrogen (NH 3 -N) can be increased by 4.4%, 7.3%, and 15%, respectively (Ghadimkhani et al. ). Quiñones (Quiñones & Flores ) concluded that the chloroform in wastewater can be reduced from 0.8 mg·L À1 to 0.2 mg·L À1 by NBs. The supplementation of N 2 NBs, air NBs, and CO 2 NBs increased methane yields by 22%, 18%, and 10%, respectively, in the process of anaerobic digestion (AD) of refractory cellulose because cellulase activity was elevated (Ho et al. ; Wang et al. c).
After 5 days of NBs aeration in an urban black-odor river, dissolved oxygen (DO) improved from 0.60 mg·L À1 to over 5.00 mg·L À1 , and COD and NH 4 -N removal were increased by 50% (Wu et al. ). O 2 NBs can enhance photodegradation of oxytetracycline to 98% at pH 11.0 (Wang et al. However, as a high-efficiency green technology, NBs have not been used to remove Fe 2þ . Therefore, developing a NBs method for oxidizing Fe 2þ in water is the purpose of this work.
The Fe 2þ oxidation from water may depend on many parameters using NBs. In order to study the influence of different variables on the treatment, obtain the best operating con- This work investigated Fe 2þ oxidation from water and examined the influence of initial Fe 2þ concentration, pH, and aeration pressure on the oxidation efficiency using NBs.
The three-factor BBD was applied to optimize the operation conditions of Fe 2þ oxidation using NBs with the comprehensive evaluation index of Fe 2þ oxidation.

Preparation of NBs
NBs are generated in the Fe 2þ solution by aerating with O 2 (purity 99.999%). The NBs generation system is shown in

Batch experiments
At 25 C, the effects of initial Fe 2þ concentration (1.5 mg·L À1 -15 mg·L À1 ), pH (4.0-9.0), and aeration pressure (100 kPa-400 kPa) on the Fe 2þ oxidation were investigated. The solution pH was adjusted using 0.1 M NaOH and 0.1 M HCl. Under the continuous aeration with a NBs system, a water sample was taken every 30 min to determine the Fe 2þ concentration.
The phenanthroline spectrophotometry method was used to determine Fe 2þ concentration using an atomic absorption spectrophotometer.

Box-Behnken response surface optimization
In order to obtain the optimum conditions of Fe 2þ oxidation using NBs, the BBD with three factors (pH, initial Fe 2þ concentration, and aeration pressure) and three levels (À1, 0, 1) were used to design and analyze the experiments. The corresponding design coded is shown in Table 1. The comprehensive evaluation index is Fe 2þ oxidation. The design and statistical analysis were carried out using the Design-Expert 8.0.6 software. Regression models were obtained.

Batch experiments
The results in Figure 2(a) show that Fe 2þ oxidation using NBs was highly dependent on pH. The Fe 2þ oxidation efficiency progressively increased when pH was enhanced from 4.0 to 9.0 at aeration pressure of 300 kPa and the initial Fe 2þ concentration of 15 mg·L À1 . The oxidation rate of Fe 2þ was higher with an increase in pH, which is consistent with other reports (Sharma et al. a, b). At pH 4, 6, 8, and 9, the maximum oxidation rates of Fe 2þ were 36.2%, 46.8%, 98%, and 98.8%, respectively.   The effect of aeration pressure on the Fe 2þ oxidation is presented in Figure 2(c) at pH 9 and initial Fe 2þ concentration of 15 mg·L À1 . The oxidation is promoted with increasing aeration pressure. During the first 120 min, the Fe 2þ oxidation is higher.
After 120  The hydrolysis products of the ferrous ion are separated due to the neutralization of the electrical properties of the central ion, which weakens the polarization of the coordinated water molecules. Therefore, the shielding effect of the coordination water disappears and the oxidation rate of Fe 2þ increases.
The injection pressure can promote the dissolution of O 2 in water. When the pressure increased, the size of the generated nanobubbles declined and their specific surface area was enhanced. The mass transfer efficiency was improved. In the first 120 min, the amount of NBs increased with increasing pressure. The number of OH À radicals and DO in the solution increased, which enhanced the oxidation rate of Fe 2þ . When the reaction lasted for 120 min, the OH À and DO reached saturation, and the reaction rate became stable.

Box-Behnken experimental design and variance analysis
The Box-Behnken experimental design, and the experimental and predicted Fe 2þ removal efficiency using NBs are presented in Table 2. To determine the impact of operating parameters on the response, the experimental values were fitted to the following second regression equation: