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Evaluation of direct and alternating current on nitrate removal using a continuous electrocoagulation process: Economical and environmental approaches through RSM
Journal of Environmental Management 230 (2019) 245–254
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Research article
Evaluation of direct and alternating current on nitrate removal using a continuous electrocoagulation process: Economical and environmental approaches through RSM
T
Elnaz Karamati-Niaragha, Mohammad Reza Alavi Moghaddama,∗, Mohammad Mahdi Emamjomehb, Ebrahim Nazlabadia a b
Civil and Environmental Engineering Department, Amirkabir University of Technology (AUT), Hafez Ave., Tehran, 15875-4413, Iran Social Determinant of Health Research Center, Qazvin University of Medical Sciences, Qazvin, Iran
ARTICLE INFO
ABSTRACT
Keywords: Alternating current Direct current Nitrate removal Operating cost Response surface method
This study aims to investigate the effects of alternating current (AC) and direct current (DC) for nitrate removal and its operating costs by using a continuous electrocoagulation (CEC) process. For this purpose, two series of 31 experiments, which were designed by response surface method (RSM), were carried out in both cases of the AC and the DC modes. In each series, the effect of selected parameters, namely, initial nitrate concentration, inlet flow rate, current density and initial pH along with their interactions on the nitrate removal efficiency as well as its operating costs, as responses, were investigated separately. According to the analysis of variance (ANOVA), there is a reasonable agreement between achieving results and the experimental data for both responses. The nitrate removal in the AC mode was slightly more efficient than that of the DC mode. In addition, the average operating costs of the DC mode, including the energy and the electrode consumption for the CEC process were achieved 54 US$/(kg nitrate removed); whereas this amount was calculated 29 US$/(kg nitrate removed) for the AC mode. Therefore, the average of the operating costs was improved more than 40% using the AC mode, which was mainly related to reduction of aluminum electrode consumption.
1. Introduction Preserving the quality of drinking water resources presents one of the major challenges of the 21st century (Pulkka et al., 2014). Nitrate pollution, one of the serious environmental problems, has been increasing constantly in the last recent years, due to excessive application of fertilizers, discharge of municipal/industrial wastewater, animal wastes and septic systems (Azadeghan et al., 2014). Furthermore, health effects of high nitrate concentration in drinking water are most significantly linked to methemoglobinemia, also known as “blue-baby syndrome”, that affects infants (Ghafari et al., 2008). The maximum acceptable level of nitrate announced by WHO drinking water guideline is 50 mg/L as NO3− (WHO, 2013). In order to keep nitrate within the approved ranges, different treatment methods in terms of physical, chemical and biological methods are used to remove this anion (Moussa et al., 2017; Pulkka et al., 2014). Applying the common physicochemical treatments such as ion exchange, electrodialysis, reverse osmosis and nanofiltration may
be limited, mainly due to concentrating the pollution instead of removing it and they are also considered as expensive methods. The sensitivity of biological methods to temperature, long duration of treatment and low C:N ratios of waters are the major demerits of these approaches (Moussa et al., 2017; Yehya et al., 2015). Electrocoagulation (EC), is reported as a promising physicochemical technology to remove various kinds of pollutants (Hakizimana et al., 2017; Moussa et al., 2017; Nariyan et al., 2018), which also represents efficient ability in nitrate removal (Emamjomeh and Sivakumar, 2009; Govindan et al., 2015; Hashim et al., 2017a; Moussa et al., 2017; Nazlabadi and Alavi Moghaddam, 2017; Pulkka et al., 2014; Xu et al., 2018; Yehya et al., 2014). Advantages of the EC process, namely, flexibility, environmental compatibility, energy efficiency, cost-effectiveness, better amenability to automation and also the ability to cope with various kinds of pollutants make it more requesting (Moussa et al., 2017; Pulkka et al., 2014). In this process, coagulant and metallic hydroxide species are generated in situ by electro-dissolution of sacrificial anode materials triggered by electric current applied through the
Corresponding author. E-mail addresses: [email protected] (E. Karamati-Niaragh), [email protected] (M.R. Alavi Moghaddam), [email protected] (M.M. Emamjomeh), [email protected] (E. Nazlabadi). ∗
https://doi.org/10.1016/j.jenvman.2018.09.091 Received 15 May 2018; Received in revised form 5 September 2018; Accepted 25 September 2018 0301-4797/ © 2018 Elsevier Ltd. All rights reserved.
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electrodes (Moussa et al., 2017; Pulkka et al., 2014). In the EC process, direct current (DC) is generally applied to produce the electric current through the electrodes. In this condition, an impermeable oxide layer may form on the cathode as well as corrosion of anodes and inhibit the effective current transport between electrodes and therefore the efficiency of the EC process may diminish. Furthermore, flows of current in one direction can reduce the lifetime of the electrodes (Ghanizadeh et al., 2016; Moussa et al., 2017). The passivity of the electrodes can be minimized using the alternating current (AC) mode in which cathode and anode can be switched periodically. Thus, the delay in cathode passivation and the anode deterioration confirms acceptable electrode life (Vasudevan and Lakshmi, 2011). The AC mode was also considered as one of the proper alternative in the EC process for different types of pollutants namely, textile dye (Tiaibaa et al., 2017), fluoride (Ghanizadeh et al., 2016), oily water (Cerqueira et al., 2014), lead and zinc (Mansoorian et al., 2014), copper (Kamaraj et al., 2013), cadmium (Vasudevan and Lakshmi, 2011) and dyes (Eyvaz et al., 2009). Ghanizadeh et al. (2016) showed that DC mode had higher efficacy than that of AC mode for floride removal based on statistical analysis. However, Mansoorian et al. (2014) proved that the operating costs which related to energy consumption and electrode corrosion by using AC mode reduced for lead and zinc removal. Cerqueira et al. (2014) also indicated that application of AC mode of EC process for oil and grease removal promoted a lower electrode consumption as compared to using DC mode. Kamaraj et al. (2013) showed that the energy consumption reduced for copper removal as well as removal efficiency improved by using AC mode. Vasudevan and Lakshmi (2011) reported that the cadmium removal for AC mode was efficient than that of DC mode and the energy consumption reduced in AC mode, which lead to operating costs improvement. Eyvaz et al. (2009) also found that the AC mode was more efficient for dye removal. Nitrate removal by using the EC process have been studied by other research groups (Emamjomeh and Sivakumar, 2009; Govindan et al., 2015; Hashim et al., 2017a; Kumar and Goel, 2010; Lacasa et al., 2013; Lacasa et al., 2011; Moussa et al., 2017; Nazlabadi and Alavi Moghaddam, 2017; Pulkka et al., 2014; Xu et al., 2018; Yehya et al., 2014). Also, some studies indicate that the operating cost of nitrate removal is of high expenses using the EC process (Lacasa et al., 2013; Yehya et al., 2015). However, to the best of our knowledge, evaluation of AC mode of a continuous electrocoagulation (CEC) process has not been applied for nitrate pollution to reduce its operating costs. In addition, RSM as a statistical-mathematical method could be used to evaluate the selected parameters and their interactions between responses for the CEC process (Hakizimana et al., 2017; Hendaoui et al., 2018). As is known from the literature review, RSM method is applied to evaluate EC process in batch systems for nitrate removal (Emamjomeh et al., 2017; Nazlabadi and Alavi Moghaddam, 2017), however, this method has not been simultaneously applied for nitrate removal efficiency and its operating costs using AC and DC modes in the CEC process. The main objective of this research is an evaluation of the operating costs for nitrate removal using the CEC process. For this purpose, the electrode and the energy consumption using the AC and DC modes were compared. Hence, two series of 31 experiments were carried out in both cases through the RSM to identify the relationship between two responses (nitrate removal and its operating costs) and the selected effective parameters.
(dimension 100 × 70 × 1 mm) were connected in a monopolar parallel mode to the DC (Micro, PW4053R, 0–5A, 0–40 V) and the AC power supply (0–5A, 0–40 V, 50 Hz). The inter-electrode gaps were kept constant (10 mm) for all of the experiments. A peristaltic pump (Heidolph, PD 5201, Germany) was used to allow influent control from a reservoir tank to feed the electrolytic cell. Effluent from the electrolytic cell enters to a sedimentation tank to remove the produced suspended solids. 2.2. Experimental techniques Sodium nitrate (NaNO3) was dissolved in tap water for preparing the required initial concentration (50–250 mg/L as NO3−). In order to adjust the initial pH (2–10), sulphuric acid (2N) and sodium hydroxide (5N) were added to the solutions. To increase the conductivity of the solutions, sodium sulfate (Na2SO4) was used as a supporting electrolyte. The pH and the conductivity of the solutions were monitored during and at the end of the CEC process using a pH-meter (pH 340i, WTW, Germany) and a conductivity-meter (Cond 340, WTW, Germany). All of the experiments were conducted at the ambient temperature. At the end of each experiment, samples were taken from the effluent and were analyzed for nitrate concentration measurements. For this achievement, UV–Vis spectrophotometer (HACH, DR4000, USA) at a wavelength of 500 nm was applied according to the standard methods for examination of water and wastewater (AWWA, 1998). The performance of the CEC process was assessed in terms of the contents of nitrate concentration before and after treatment which was calculated using Eq. (1):
Nitrate Removal Efficiency (RE%) = (
Cr
Ct Cr
) × 100
(1)
where Cr and Ct are the nitrate concentration in raw and the treated solutions (mg/L-NO3-), respectively. The accuracy of the experiments was also assured using the random repetition of experiments. A scanning electron microscopy (SEM) (Seron, AIS2100, South Korea) was also used to evaluate the morphology of the electrodes after electrolysis (AC and DC modes). The SEM images of electrodes were related to those ones which were applied after all 31 runs in each current modes. 2.3. Economic analysis Feasibility study of the EC process in large scale application, mainly depends on its cost-effectiveness. The accurate operating cost of the EC process comprises the cost of chemicals, electrode consumption, energy consumption, sludge dewatering/disposal, maintenance, pertaining to labor and fixed costs (Hakizimana et al., 2017; Hashim et al., 2017b). According to the literature, costs of electrodes and energy consumption were considerable for preliminary cost evaluation of EC process due to their major role in high expenses (Behbahani et al., 2011; Yehya et al., 2014), especially for removing low concentration of nitrate (Yehya et al., 2014). The Eq. (2) was used for estimation of these operating costs US$/(kg NO3− removed):
Operating Cost (OC)=a×Cenergy + b×Celectrodes
(2)
where Cenergy (kWh/(kg NO3− removed)) and Celectrodes (kg Al/(kg NO3− removed)) are energy and electrode consumption for nitrate removal, respectively. Besides, a and b, the coefficient of the Iranian market in 2016, are described below:
2. Materials and methods
Coefficient a: industrial electricity price = 0.0222 US$/kWh Coefficient b: Wholesale Al electrode price = 1.56 US$/kg Al
2.1. Experimental setup A continuous EC process was used for nitrate removal as schematically shown in Fig. 1. An electrolytic cell was made from Plexiglas with an effective volume of 2.4 L. In the cell, aluminum plate electrodes
The electric energy consumption of the EC process was deduced as a function of operation time through Eq. (3) as follows (Behbahani et al., 2011; Hakizimana et al., 2017; Hashim et al., 2017b): 246
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Fig. 1. Continuous monopolar electrocoagulation process: 1) Reservoir tank; 2) Peristaltic pump; 3) Electrolytic cell; 4) Aluminum electrodes; 5) DC & AC power supply; 6) Sedimentation tank and 7) Effluent.
levels of the independent parameters are presented according to the RSM model. For statistical calculations, the variables Xi were coded as xi according to the following equation (Hakizimana et al., 2017; Behbahani et al., 2011):
t
E=
V·I dt
(3)
0
where E is the electric energy consumption (kWh/(kg NO3− removed)), V is the voltage (V), I is the current intensity (A) and t is the electrolysis time (hrs). In case of continuous EC, the energy consumption of the pump was also calculated in the present study, however mechanical power for mixing purposes was neglected. To obtain the mass depletion of the electrode corrosion due to the anodic oxidation, weight loss of the electrodes was calculated by subtracting the electrodes' weight at the beginning and at the end of each experiment. The electrodes were also cleaned after each run in order to prevent surface pollution of the electrodes which might affect the electrodes passivation.
xi =
Y= b0 +
mg/L mL/min A/m2 –
X1 X2 X3 X4
i= 1
k
k
b ijxixj
(6)
j= 1 i= 1
3. Results and discussion 3.1. Development of regression model and its validation for AC and DC modes The results of the conducted experiments corresponding to the RSM design for nitrate removal efficiency and operating costs in both cases of DC and AC modes are presented in Table 2. The modified quadratic model for nitrate removal efficiency (RE%) and operating costs (OC) in terms of the coded values for DC and AC mode are given by Eqs. (7a), (b) and (8a), (b), respectively: For DC mode:
Table 1 Levels of the parameters according to RSM for the CEC process.
Initial nitrate concentration Inlet flow rate Current density Initial pH
bii x 2i +
where Y is the required responses of the CEC process (nitrate removal efficiency and operating costs in this study) and b0, bi, bii, bij, xi and xj are the constant coefficient, the linear coefficient, the quadratic coefficient, the interaction coefficient and the coded values of the factors, respectively. In this study, only a two-way interaction has been considered. The statistical significance of the produced models was evaluated through ANOVA with a confidence level of 95%. Residual plots and coefficients of determination (R2, Adjusted R2 and Predicted R2) were also presented to express the quality of the fitted models.
where Nf is the number of points in the cube portion of the design and is equal to 2k, and k is the number of factors. Thus, the α was calculated to be 2 in the present study. In Table 1, selected factors and their five
Factors
k
bi xi + i= 1
(4)
Unit
(5)
k
In the present study, the central composite design (CCD) method of RSM, commonly used by other researchers, was selected to design the experiments, as well as to generate a quadratic model of the CEC process. In this method, minimum numbers of experiments are achieved and interaction between parameters is also analyzed (Karimifard and Alavi Moghaddam, 2018; Behbahani et al., 2011; Emamjomeh et al., 2017; Georgiou et al., 2014; Nazlabadi and Alavi Moghaddam, 2017; Nazlabadi and Alavi Moghaddam, 2014; Song et al., 2015; Varank and Sabuncu, 2015). According to our previous work and obtained significant parameters (Karamati Niaragh et al., 2017), four parameters including the initial nitrate concentration, inlet flow rate, current density and initial pH were selected in the present study to evaluate the combined effects of these factors as well as present a mathematical model. Thirty-one experiments were designed by employing the parameters with five-levels. These experiments consist of 16 factorial experiments, 8 axial experiments on the axis at a distance of ± α from the center, and 7 replicates at the center point. The value of α for rotatability was calculated as brought in Eq. (4):
Variables
X 0) X
where X0 is the value of Xi at center point and δX represents the stage change. The statistical software Design Expert 7 was applied to analyze the experimental data and generate a second-order polynomial model, thus ANOVA, regression coefficients, three dimensional curves of the response surfaces and residual plots were developed. The empirical model of RSM represented by a second order polynomial regression is calculated through Eq. (6):
2.4. Experimental design and data analysis
= (Nf )1/4
(Xi
YRE = 52.49
7.01x1
7.04x2 + 5.17x3 + 1.98x 4
Levels
2.77x1 x 4 + 2.72x2 x3
-α
−1
0
+1
+α
3.77x42
50 40 45 2
100 60 60 4
150 80 75 6
200 100 90 8
250 120 105 10
+
YOC = 43.49
4.64x1 x2 + 2.34x1 x3
2.62x12 + 1.63x 22
1.29x 32 (7a)
12.13x1
4.10x2 + 5.41x3
0.80x2 x 4 + 0.98x3 x 4 + For AC mode: 247
2.14x2 x 4
8.50x12
0.64x 4 11.25x 22
1.40x1 x3 +
8.67x42
0.7x1 x 4 (7b)
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Table 2 RSM experimental design and its observed values in both cases of DC and AC modes. Run number
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 a
Initial nitrate concentration (x1)
Inlet flow rate (x2)
Current density (x3)
Initial pH (x4)
Direct current (DC) RE (%)
RE (kg removed) × 104
OC (US$/kg NO3− removed)
RE (%)
RE (kg NO3− removed) × 104
OC (US$/kg NO3− removed)
0 0 +1 0 +1 0 0 +1 +2 0 −2 +1 −1 −1 0 0 0 0 +1 −1 −1 +1 −1 +1 0 +1 −1 0 0 −1 −1
0 0 +1 0 −1 −2 0 +1 0 0 0 +1 +1 −1 0 0 0 0 +1 +1 +1 −1 −1 −1 +2 −1 −1 0 0 +1 −1
−2 +2 +1 0 −1 0 0 −1 0 0 0 +1 −1 −1 0 0 0 0 −1 +1 −1 +1 −1 −1 0 +1 +1 0 0 +1 +1
0 0 +1 0 +1 0 0 +1 0 0 0 −1 −1 −1 −2 +2 0 0 −1 +1 +1 −1 +1 −1 0 +1 +1 0 0 −1 −1
34.67 60 61 49.33 56 74.67 48 55 28 55.33 56 50 52 57 30.67 57.33 52.44 53.33 45 66 58 59 68 54 43.33 64 71 50.67 56.67 60 56
0.52 0.9 1.22 0.74 1.12 1.12 0.72 1.1 0.7 1.01 2.8 1 0.52 0.57 0.46 0.86 0.79 0.8 0.9 0.66 0.58 1.18 0.68 1.08 0.65 1.28 0.71 0.76 0.85 0.6 0.56
48.29 47.24 33.42 45.98 36.60 52.57 45.75 24.50 54.19 40.29 100.81 40.20 52.02 62.96 75.94 80.42 43.05 43.88 33.48 55.98 49.56 45.80 55.37 37.56 54.71 44.81 74.45 44.10 41.38 64.84 95.33
35.33 60 61.5 50.67 55 76.67 50 52.5 28.8 66.67 60 47.5 55 60 34 62 54 54.67 30 70 59 55 69 50 44 57.5 75 52 53.33 61 65
0.53 0.9 1.23 0.76 1.1 1.15 0.75 1.05 0.72 1 0.3 0.95 0.55 0.6 0.51 0.93 0.81 0.82 0.6 0.7 0.59 1.1 0.69 1 0.66 1.15 0.75 0.78 0.8 0.61 0.65
30.51 29.11 19.23 28.73 21.50 27.34 30.03 15.62 32.35 20.83 67.97 26.43 33.36 37.10 46.58 45.72 28.62 24.04 22.22 31.88 31.80 26.04 29.63 20.99 30.56 27.19 41.01 25.01 13.66 36.43 50.30
a
Alternating current (AC)
NO3−
a
RE: Removal Efficiency, OC: Operating Costs.
YRE = 52.93
7.91x1
+ 0.028x2 x 4
6.71x2 + 5.36x3 + 3.34x 4 0.69x3 x 4
2.13x12
+
1.85x 22
statistically significant (P ˂0.0001), and implies that the modified second-order quadratic model is fitted well with the experimental results. The results also specified that all the selected independent parameters were significant for removal efficiency of both cases of DC and AC models. Also, the most important independent process variables for operating costs were found to be initial nitrate concentration (x1), inlet flow rate (x2) and current density (x3) (detailed data not shown). According to Table 3, the lack of fit for nitrate removal efficiency (Pvalue of 0.5180 and 0.1339 for DC and AC, respectively) and operating costs (P-value of 0.1592 and 0.5044 for DC and AC, respectively) were
2.11x1 x 4 + 2.64x2 x3 1.32x 32
+
3.50x42 (8a)
YOC = 25.45
7.89x1
1.16x2 x3
2.66x2 + 3.26x3
0.66x3 x 4 +
6.18x12
11.29x 4 + 0.41x1 x2 + 1.03x1 x 4 (8b)
7.74x 22 + 5.18x42
The ANOVA results for DC and AC modes are also summarised in Table 3. As indicated in Table 3, the quadratic model of nitrate removal efficiency and operating costs in both cases of DC and AC modes were
Table 3 ANOVA results and determination coefficients for RSM model in both cases of DC and AC mode. Current
DC
Response
RE (%)
OC (US$/kg NO3− removed) AC
RE(%)
OC(US$/kg NO3− removed)
Source
Model Lack of Fit Pure Error Total Model Lack of Fit Pure Error Total Model Lack of Fit Pure Error Total Model Lack of Fit Pure Error Total
DF
13 6 4 23 11 7 6 24 13 6 4 23 11 8 4 23
Adj SS
2388.70 48 31.48 2468.18 7094.74 73.21 26.74 7194.68 3394.27 51.01 10.30 3455.58 3035.02 96.11 44.40 3175.52
Adj MS
183.75 8 7.87 – 644.98 10.46 4.46 – 261.10 8.50 2.58 – 275.91 12.01 11.10 –
F
23.12 1.02 – – 83.89 2.35 – – 42.58 3.30 – – 23.56 1.08 – –
P
Coefficient of determination (%)
˂0.0001 0.5180 – – ˂0.0001 0.1592 – – ˂0.0001 0.1339 – – ˂0.0001 0.5044 – –
248
0.8 Pred-R2≤ Adj-R2 ≤1.2 Pred-R2 & Adj-R2≤ R2
R2
Adj-R2
Pred-R2
96.8
92.59
78.80
✓
98.6
97.4
92.1
✓
98.2
95.9
83.5
✓
95.6
91.5
80
✓
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(b)
(a)
Direct Current (DC) (a)
(b)
Alternating Current (AC) Fig. 2. Normal probability plots in both cases of DC and AC modes for (a) nitrate removal efficiency and (b) operating costs.
not significant; thus, the data was fitted well to the model. In addition, high values of R2 were achieved 96.8% and 98.6% for removal efficiency and operating costs of DC, respectively, indicated a satisfactory fit of the quadratic model to the experimental data. In the case of AC, values of R2 were found to be 98.2% and 95.6% for nitrate removal efficiency and operating costs, respectively. The values of adjusted R2 (Adj-R2) were also lower than the R2 values and the Adj-R2 and predicted R2 (Pred-R2) were within approximately 0.20, which indicated reasonable agreement. Furthermore, the adequacies of the models were controlled by analyzing the residuals. For this purpose, the normal probability plots for nitrate removal efficiency and operating costs, which indicates whether the residuals follow a normal distribution, are illustrated in Fig. 2. As seen in Fig. 2, the normal probability was relatively satisfied as the points in the plot follows from fairly straight line. All of the plots in Fig. 2 revealed that the model for both DC and AC modes were found to be adequate to describe the nitrate removal efficiency and its relative operating costs using CCD method of RSM.
the allowable WHO limitations for drinking water was 55 min (Hashim et al., 2017a). However, at the initial nitrate concentration of 150 mg/ L, the inlet flow rate of 100 mL/min was not enough for the CEC process to meet these limitations. The literature highlighted that current density, which determines the anodic dissolution rate and hydrogen gas generation, affected the EC performance (Behbahani et al., 2011; Koparal and Oğütveren, 2002; Moussa et al., 2017). Fig. 3(b) and (c) shows that higher nitrate removal rates were achieved with higher current density. In the current study, the experiments were carried out in different ranges of the current densities between 60 and 90 A/m2 to evaluate the influence of this main parameter on the CEC process for nitrate removal. For instance, according to Fig. 3(c), in constant initial nitrate concentration of 100 mg/L, initial pH of 7 and the inlet flow rate of 100 mL/min, the nitrate removal efficiency improved about 15%. The improving effects of increased current density were also observed for AC mode in the same conditions (data not shown here). However, the results of this study along with literature (Behbahani et al., 2011; Emamjomeh et al., 2017; Hashim et al., 2017a, 2017b; Karamati Niaragh et al., 2017; Nazlabadi and Alavi Moghaddam, 2017) showed that high amounts of current density had a significant negative effect on the energy consumptions, and consequently on the operating costs. Therefore, by considering the operating costs, the optimum current density for nitrate removal efficiency using the CEC process for both cases of DC and AC modes was calculated to be 70–80 A/m2 in the present study. Fig. 3(d) illustrates that at a constant initial nitrate concentration, by increasing the initial pH, nitrate removal rate increases. This can be related to the reaction between Al metal and hydroxide ions. In this work, the optimum removal efficiencies were obtained in the initial pH range of 7–8 for both AC and DC modes. The results of this study have been recently observed by the other research groups (Hashim et al., 2017a; Yehya et al., 2014; Kumar and Goel, 2010; Lakshmi et al., 2013; Nazlabadi and Moghaddam, 2017). Conversely, some research groups have been reported that the alkaline pH (9–11) is the optimum pH for nitrate removal (Koparal and Oğütveren, 2002; Emamjomeh et al., 2017; Emamjomeh and Sivakumar, 2009). But, Safari and Yehya study groups showed that the rate of nitrate removal had not changed significantly when the pH increases from 7 to 10 (Yehya et al., 2014; Safari et al., 2015).
3.2. Evaluation of nitrate removal for AC and DC modes Generally, the most important parameters, which affect the performance of the CEC process, are initial concentration of nitrate, current density, inlet flow rate and initial pH of the solution. The main parameters effects on the CEC process performance as well as their contribution ratio were elaborately discussed in our previous work (Karamati Niaragh et al., 2017). The significant relationships between nitrate removal efficiency and the two-way interaction terms of the DC mode for the CEC process are also shown in Fig. 3. According to Fig. 3(a), a higher removal efficiency occurred for low initial nitrate concentration and low inlet flow rate. At a constant nitrate removal efficiency, the required inlet flow rate reduced when the initial nitrate concentration increased. The similar results were also observed for AC mode (data not shown here). The removal efficiency was achieved higher than 60% when the initial nitrate concentration and the inlet flow rate were 100 mg/L and 100 mL/ min, respectively. The detention time required for the inlet flow rate of 100 mL/min was 48 min. This result is in agreement with the results achieved by Hashim et al. in batch EC process, which revealed that the required time to reduce the initial nitrate concentration of 100 mg/L to 249
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(a) al Nitrate remov ) (% cy en effici
al Nitrate remov ) (% y nc ie effic
(b)
e rat w flo in) let /m In (mL
nc
ate g/L) itr l n (m tia on Ini trati en
co
te w ra t flo Inle /min) (mL
nsity nt de Curre m2 ) (A/
(d)
al Nitrate remov ) efficiency (%
al Nitrate remov ) (% y efficienc
(c)
) e rat g/L nit (m n al iti io In trat en nc
co
) te /L tra g ni (m al on iti ti In ntra e
nc co
nt d
Curre
2 /m )
(A ensity
l pH
Initia
Fig. 3. Relation between nitrate removal efficiency and the interaction terms using 3d plots (DC mode): (a) the interaction between initial nitrate concentration and inlet flow rate; (b) the interaction between inlet flow rate and the current density; (c) the initial nitrate concentration and the current density; (d) the initial nitrate concentration and the initial pH.
3.3. Analysis of operating costs for AC and DC modes
efficient alternative. In agreement with this result, other research groups have reported that the high performance of AC in the removal of textile dye (Tiaibaa et al., 2017), oily water (Cerqueira et al., 2014), lead and zinc (Mansoorian et al., 2014), copper (Kamaraj et al., 2013), cadmium (Vasudevan and Lakshmi, 2011) and dyes (Eyvaz et al., 2009), but Ghanizadeh research group has confirmed that the efficacy of AC mode was not statistically significant for fluoride removal (Ghanizadeh et al., 2016). Therefore, in the present study, minimizing the electrodes passivity using the AC mode had no significant effect on nitrate removal efficiency during the CEC process. It may due to an insignificant increase in the resistance of the electrolyte in the applied detention times. In conjunction with operating costs, Fig. 4 illustrated that the removing nitrate operating costs of DC mode are higher than AC mode for the CEC process. The average operating cost of all experiments for DC mode was achieved 54 US$/(kg NO3− removed); while this amount was obtained 29 US$/(kg NO3− removed) using AC mode. As a result, the operating costs of nitrate removal efficiency using AC mode for the CEC process was improved about 40%. To elaborate how the costs were attributed to the amount of energy and electrode used in the CEC process, the energy and the electrode consumption of all experiments
From the literature, it is obvious that the application of EC for nitrate removal is of high operating costs, especially, it is expensive for treatment of water containing low nitrate concentrations (Yehya et al., 2014). However, for the EC lab scale units, the electrode material and the electrical energy consumption are of significant effect on operating costs (Yehya et al., 2014; Hashim et al., 2017a; Emamjomeh et al., 2017). In addition, a review of the existing literature indicated that the electrode material and energy consumption could be more cost-effective if the AC mode is used instead of the DC mode during the EC process. Furthermore, the application of AC can prohibit the formation of the impermeable layer on the surface of the anodes, which is considered as a demerits in DC mode of the EC process (Ghanizadeh et al., 2016; Cerqueira et al., 2014; Mansoorian et al., 2014; Kamaraj et al., 2013; Vasudevan and Lakshmi, 2011; Eyvaz et al., 2009). To investigate the techno-economical effects of AC and DC mode, two series of 31 experiments have been carried out using the AC mode as well as the DC mode. According to Table 2, nitrate removal efficiency in the AC mode is slightly higher (1%) than the DC mode in most of the experiments; however, it does not mean that the AC mode could be an 250
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Operating Cost (US$/kg nitrate removed)
120
AC DC
100 80 60 40 20 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Number of experiment Fig. 4. The operating costs of the CEC process through 31 experiments designed by RSM in both cases of DC and AC modes.
Energy consumption (kWh/gr nitrate removed)
3
AC DC
2.5 2 1.5 1 0.5 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Number of experiment
Electrode consumption (kg Al/kg nitrate removed)
Fig. 5. The energy consumption of the CEC process through 31 experiments designed by RSM in both cases of DC and AC modes.
50
AC
45
DC
40 35 30 25 20 15 10 5 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Number of experiment Fig. 6. The electrode consumption of the CEC process through 31 experiments designed by RSM in both cases of DC and AC modes.
are presented in Figs. 5 and 6, respectively, in both cases of AC and DC mode. According to Fig. 5, the energy consumption was slightly higher in the case of AC mode in current intensities between 2 and 4A for nitrate removal. Thus, it indicated that the energy consumption had may no relation with the impermeable oxide layer formed on cathodes in DC mode, which increase the resistivity of the electrolyte. This result is in agreement with Cerqueira research work on oily water treatment,
which demonstrated that the energy consumption was higher in the case of AC mode at current intensities lower than 3A (Cerqueira et al., 2014). Conversely, other research groups indicated that the energy consumption in the case of AC is lower than DC mode of EC process for removal of fluoride (Ghanizadeh et al., 2016), lead and zinc (Mansoorian et al., 2014), copper (Kamaraj et al., 2013), cadmium (Vasudevan and Lakshmi, 2011) and dyes (Eyvaz et al., 2009). The higher energy consumption in AC mode may due to the type of 251
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H2O
+2
provides a longer life for electrodes, which is considered as one of the disadvantages of the EC process. To obtain more insight into the effect of AC mode, the morphology of the aluminum anode surface after the CEC process was evaluated by SEM for both cases of AC and DC modes after 31 runs, which is presented in Fig. 8(a) and (b), respectively. It can be observed that less disordered pores formed in the case of AC which confirmed the uniform dissolving of the electrodes. While, for the DC mode, many tortuous pores of the electrode's surface shows the aluminum oxide may form.
H2O
NO2
-
e
-2
-
e
+6 e-
N2
NO3 +8
e-
NH3
-3
-
e
H2O
4. Conclusions The alternating current was applied in the present study to reduce the operating costs of the CEC process for nitrate removal. The performance and the operating costs of the CEC process using both cases of the AC and the DC modes was also compared. For this purpose, two series of 31 experiments, which were designed by RSM, were carried out in both current modes. The second modified quadratic models were also developed for the nitrate removal efficiency and the operating costs for both current modes, which were statistically significant. According to ANOVA results, the models fitted well with the experimental results. High R2 values for AC and DC modes were 96.8% and 98.6% for nitrate removal efficiency and 98.2% and 95.6% for operating costs, respectively. The R2, Adj-R2 and Pred-R2 were also in a reasonable agreement. Hence, the RSM method has been approved as a powerful tool to evaluate the CEC process. The performance of nitrate removal in the AC mode was slightly higher than that of the DC mode in more than 80% of the experiments. However, to choose the AC mode as an effective alternative, the performance of the CEC process has to be evaluated in conjunction with its operating costs. The operating costs of the DC mode was higher than that of the AC mode for nitrate removal efficiency using the CEC process. The average operating cost of the experiments using the DC mode was achieved 54 US$/(kg nitrate removed); while this amount was obtained 29 US$/(kg nitrate removed) for the AC mode. The significant reduction of the operating costs was related to the electrode consumption in this study rather than the energy consumption. The average electrode consumption of the experiments using the DC mode was more than 4 times higher than that of the AC mode. As a result, the operating costs was improved more than 40% using the AC mode. Therefore, the AC mode achieved to be a promising cost-effective alternative for nitrate removal using the CEC process.
H2O
Fig. 7. Schematic reduction pathway of nitrate anions.
pollutants and its complexes of removal mechanisms. The process of nitrate reduction is summarised in Fig. 7 (Govindan et al., 2015; Hashim et al., 2017a). Also, since the first step in nitrate removal is related to nitrate reduction, the key role on nitrate removal mechanism is the electricity, which has significant effect on energy consumption (Yehya et al., 2014). As depicted in Fig. 6, conducting of all experiments in constant situations for both AC and DC modes confirmed that the consumption of the aluminum electrode was significantly lower in the AC mode as compared to that of the DC mode. According to the obtained results, the average electrode consumption of the experiments using the DC was about 4 times higher than that of the AC mode. In other words, after same conditions of the CEC process, the average amount of aluminum electrode consumed in DC mode was 19.96 gr/(gr NO3−removed), whereas in the AC mode it was achieved 4.96 gr/(gr NO3− removed). Therefore, the DC mode of the CEC process consumed the electrode much faster and the AC mode performed efficiently. This was probably related to the uniform dissolution of the anode and the cathode during the CEC process using AC mode. It means that the higher electrode consumption by DC mode refers to one directional flows of DC mode, which allows the irregular wear on the electrode plates due to the oxidation at the same preferential points of the plates. The reversal of current in the AC mode induces the uniformly points of electrodes, thus,
(a)
(b)
Fig. 8. SEM images of aluminum anodes: (a) Alternating current; (b) Direct current.
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(b)
oval Nitrate rem ) efficiency (%
oval Nitrate rem ) cy efficien (%
(a)
te ra w n) lo t f /mi le In (mL
te tra n ni io al rat iti nt ) In nce g/L co (m
te w ra t flo Inle /min) (mL
nsity nt de Curre m2 ) (A/
oval Nitrate rem (%) cy en ci effi
(c)
te tra n ni io al rat iti nt ) In nce g/L co (m
al pH
Initi
Acknowledgments
Georgiou, S.D., Stylianou, S., Aggarwal, M., 2014. A class of composite designs for response surface methodology. Comput. Stat. Data Anal. 71, 1124–1133. Ghafari, S., Hasan, M., Aroua, M.K., 2008. Bio-electrochemical removal of nitrate from water and wastewater-A review. Bioresour. Technol. 99 (10), 3965–3974. Ghanizadeh, G., Shariati neghab, G., Salem, M., Khalagi, K., 2016. Taguchi experimental design for electrocoagulation process using alternating and direct current on fluoride removal from water. Desalination Water Treat. 57 (27), 12675–12683. Govindan, K., Noel, M., Mohan, R., 2015. Removal of nitrate ion from water by electrochemical approaches. J. Water Process Eng. 6, 58–63. Hakizimana, J.N., Gourich, B., Chafi, M., Stiriba, Y., Vial, C., Drogui, P., Naja, J., 2017. Electrocoagulation process in water treatment: a review of electrocoagulation modeling approaches. Desalination 404, 1–21. Hashim, K.S., Shaw, A., Al Khaddar, R., Pedrola, M.O., Phipps, D., 2017a. Energy efficient electrocoagulation using a new flow column reactor to remove nitrate from drinking water: experimental, statistical, and economic approach. J. Environ. Manag. 196, 224–233. Hashim, K.S., Shaw, A., Al Khaddar, R., Pedrola, M.O., Phipps, D., 2017b. Iron removal, energy consumption and operating cost of electrocoagulation of drinking water using a new flow column reactor. J. Environ. Manag. 189, 98–108. Hendaoui, K., Ayari, F., Rayana, I.B., Ammar, R.B., Darragi, F., Trabelsi-Ayadi, M., 2018. Real indigo dyeing effluent decontamination using continuous electrocoagulation cell: study and optimization using Response Surface Methodology. Process Saf. Environ. Protect. 116, 578–589. Kamaraj, R., Ganesan, P., Lakshmi, J., Vasudevan, S., 2013. Removal of copper from water by electrocoagulation process-effect of alternating current (AC) and direct current (DC). Environ. Sci. Pollut. Control Ser. 20 (1), 399–412. Karamati-Niaragh, E., Alavi Moghaddam, M.R., Emamjomeh, M.M., 2017. Techno-economical evaluation of nitrate removal using continuous flow electro-coagulation process: optimization by Taguchi model. Water Sci. Technol. Water Supply 17 (6), 1703–1711. Karimifard, S., Alavi Moghaddam, M.R., 2018. Application of response surface methodology in physicochemical removal of dyes from wastewater: a critical review. Sci.
The authors would like to thank the Amirkabir University of Technology for financial support. In addition, the authors wish to appreciate Mr. Mahyar Ghannadi and Ms. Pariya Sefatjoo (former M.Sc students of AUT) for their respected assistance during the experiments. References AWWA (American Water Works Association), APHA (American Public Health Association), WEF (Water Environment Federation), 1998. Standard Methods for the Examination of Water and Wastewater. Washington, DC, USA. Azadeghan, M.M., Alavi Moghaddam, M.R., Maknoon, R., 2014. Public awareness and performance regarding nitrate pollution in nitrate-polluted area of Tehran, Iran. Environ. Eng. Manag. J. (EEMJ) 13 (3), 611–617. Behbahani, M., Alavi Moghaddam, M.R., Arami, M., 2011. Techno-economical evaluation of fluoride removal by electrocoagulation process: optimization through response surface methodology. Desalination 271 (1–3), 209–218. Cerqueira, A.A., Souza, P.S.A., Marques, M.R.C., 2014. Effects of direct and alternating current on the treatment of oily water in an electroflocculation process. Braz. J. Chem. Eng. 31 (3), 693–701. Emamjomeh, M.M., Jamali, H.A., Moradnia, M., 2017. Optimization of nitrate removal efficiency and energy consumption using a batch monopolar electrocoagulation: prediction by RSM Method. J. Environ. Eng. 143 (7), 4017022. Emamjomeh, M.M., Sivakumar, M., 2009. Denitrification using a monopolar electrocoagulation/flotation (ECF) process. J. Environ. Manag. 91 (2), 516–522. Eyvaz, M., Kirlaroglu, M., Aktas, T.S., Yuksel, E., 2009. The effects of alternating current electrocoagulation on dye removal from aqueous solutions. Chem. Eng. J. 153 (1–3), 16–22.
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E. Karamati-Niaragh et al. Total Environ. 640, 772–797. Koparal, A.S., Oğütveren, Ü.B., 2002. Removal of nitrate from water by electroreduction and electrocoagulation. J. Hazard Mater. 89 (1), 83–94. Kumar, N.S., Goel, S., 2010. Factors influencing arsenic and nitrate removal from drinking water in a continuous flow electrocoagulation (EC) process. J. Hazard Mater. 173 (1–3), 528–533. Lacasa, E., Cañizares, P., Sáez, C., Martínez, F., Rodrigo, M.A., 2013. Modelling and cost evaluation of electro-coagulation processes for the removal of anions from water. Separ. Purif. Technol. 107, 219–227. Lacasa, E., Cañizares, P., Sáez, C., Fernández, F.J., Rodrigo, M.A., 2011. Removal of nitrates from groundwater by electrocoagulation. Chem. Eng. J. 171 (3), 1012–1017. Lakshmi, J., Sozhan, G., Vasudevan, S., 2013. Recovery of hydrogen and removal of nitrate from water by electrocoagulation process. Environ. Sci. Pollut. Control Ser. 20 (4), 2184–2192. Mansoorian, H.J., Mahvi, A.H., Jafari, A.J., 2014. Removal of lead and zinc from battery industry wastewater using electrocoagulation process: influence of direct and alternating current by using iron and stainless steel rod electrodes. Separ. Purif. Technol. 135, 165–175. Moussa, D.T., El-Naas, M.H., Nasser, M., Al-Marri, M.J., 2017. A comprehensive review of electrocoagulation for water treatment: potentials and challenges. J. Environ. Manag. 186, 24–41. Nariyan, E., Sillanpää, M., Wolkersdorfer, C., 2018. Uranium removal from Pyhäsalmi/ Finland mine water by batch electrocoagulation and optimization with the response surface methodology. Separ. Purif. Technol. 193, 386–397. Nazlabadi, E., Alavi Moghaddam, M.R., 2017. Simulation of nitrate removal in a batch flow electrocoagulation-flotation (ECF) process by response surface method (RSM). Trends in Asian Water Environmental Science and Technology. Springer, Cham, pp. 49–60. Nazlabadi, E., Alavi Moghaddam, M.R., 2014. Simulation of operation cost for nitrate removal using response surface method in electrocoagulation process. Int. J. Environ.
Eng. 1 (2), 91–95. Pulkka, S., Martikainen, M., Bhatnagar, A., Sillanpää, M., 2014. Electrochemical methods for the removal of anionic contaminants from water - a review. Separ. Purif. Technol. 132, 252–271. Safari, M., Rezaee, A., Ayati, B., Jonidi-Jafari, A., 2015. Simultaneous removal of nitrate and its intermediates by use of bipolar electrochemistry. Res. Chem. Intermed. 41 (3), 1365–1372. Song, P., Yang, Z., Zeng, G., Yang, X., Xu, H., Huang, J., Wang, L., 2015. Optimization, kinetics, isotherms, and thermodynamics studies of antimony removal in electrocoagulation process. Water Air Soil Pollut. 226 (11), 380. Tiaibaa, M., Merzoukb, B., Amourd, A., Mazoura, M., Leclerce, J.P., Lapicquee, F., 2017. Influence of electrodes connection mode and type of current in electrocoagulation process on the removal of a textile dye. Desalination Water Treat. 73, 330–338. Varank, G., Sabuncu, M.E., 2015. Application of central composite design approach for dairy wastewater treatment by electrocoagulation using iron and aluminum electrodes: modeling and optimization. Desalination Water Treat. 56 (1), 33–54. Vasudevan, S., Lakshmi, J., 2011. Effects of alternating and direct current in electrocoagulation process on the removal of cadmium from water: a novel approach. Separ. Purif. Technol. 80 (3), 643–651. WHO, 2013. Guidelines for Drinking-Water Quality, 4th ed. Water Sanitation Health, Geneva, Switzerland. Xu, D., Li, Y., Yin, L., Ji, Y., Niu, J., Yu, Y., 2018. Electrochemical removal of nitrate in industrial wastewater. Front. Environ. Sci. Eng. 12 (1), 9. Yehya, T., Balla, W., Chafi, M., Audonnet, F., Vial, C., Essadki, A., Gourich, B., 2015. Assessment of denitrification using electrocoagulation process. Can. J. Chem. Eng. 93 (2), 241–248. Yehya, T., Chafi, M., Balla, W., Vial, C., Essadki, A., Gourich, B., 2014. Experimental analysis and modeling of denitrification using electrocoagulation process. Separ. Purif. Technol. 132, 644–654.
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Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman
Research article
Evaluation of direct and alternating current on nitrate removal using a continuous electrocoagulation process: Economical and environmental approaches through RSM
T
Elnaz Karamati-Niaragha, Mohammad Reza Alavi Moghaddama,∗, Mohammad Mahdi Emamjomehb, Ebrahim Nazlabadia a b
Civil and Environmental Engineering Department, Amirkabir University of Technology (AUT), Hafez Ave., Tehran, 15875-4413, Iran Social Determinant of Health Research Center, Qazvin University of Medical Sciences, Qazvin, Iran
ARTICLE INFO
ABSTRACT
Keywords: Alternating current Direct current Nitrate removal Operating cost Response surface method
This study aims to investigate the effects of alternating current (AC) and direct current (DC) for nitrate removal and its operating costs by using a continuous electrocoagulation (CEC) process. For this purpose, two series of 31 experiments, which were designed by response surface method (RSM), were carried out in both cases of the AC and the DC modes. In each series, the effect of selected parameters, namely, initial nitrate concentration, inlet flow rate, current density and initial pH along with their interactions on the nitrate removal efficiency as well as its operating costs, as responses, were investigated separately. According to the analysis of variance (ANOVA), there is a reasonable agreement between achieving results and the experimental data for both responses. The nitrate removal in the AC mode was slightly more efficient than that of the DC mode. In addition, the average operating costs of the DC mode, including the energy and the electrode consumption for the CEC process were achieved 54 US$/(kg nitrate removed); whereas this amount was calculated 29 US$/(kg nitrate removed) for the AC mode. Therefore, the average of the operating costs was improved more than 40% using the AC mode, which was mainly related to reduction of aluminum electrode consumption.
1. Introduction Preserving the quality of drinking water resources presents one of the major challenges of the 21st century (Pulkka et al., 2014). Nitrate pollution, one of the serious environmental problems, has been increasing constantly in the last recent years, due to excessive application of fertilizers, discharge of municipal/industrial wastewater, animal wastes and septic systems (Azadeghan et al., 2014). Furthermore, health effects of high nitrate concentration in drinking water are most significantly linked to methemoglobinemia, also known as “blue-baby syndrome”, that affects infants (Ghafari et al., 2008). The maximum acceptable level of nitrate announced by WHO drinking water guideline is 50 mg/L as NO3− (WHO, 2013). In order to keep nitrate within the approved ranges, different treatment methods in terms of physical, chemical and biological methods are used to remove this anion (Moussa et al., 2017; Pulkka et al., 2014). Applying the common physicochemical treatments such as ion exchange, electrodialysis, reverse osmosis and nanofiltration may
be limited, mainly due to concentrating the pollution instead of removing it and they are also considered as expensive methods. The sensitivity of biological methods to temperature, long duration of treatment and low C:N ratios of waters are the major demerits of these approaches (Moussa et al., 2017; Yehya et al., 2015). Electrocoagulation (EC), is reported as a promising physicochemical technology to remove various kinds of pollutants (Hakizimana et al., 2017; Moussa et al., 2017; Nariyan et al., 2018), which also represents efficient ability in nitrate removal (Emamjomeh and Sivakumar, 2009; Govindan et al., 2015; Hashim et al., 2017a; Moussa et al., 2017; Nazlabadi and Alavi Moghaddam, 2017; Pulkka et al., 2014; Xu et al., 2018; Yehya et al., 2014). Advantages of the EC process, namely, flexibility, environmental compatibility, energy efficiency, cost-effectiveness, better amenability to automation and also the ability to cope with various kinds of pollutants make it more requesting (Moussa et al., 2017; Pulkka et al., 2014). In this process, coagulant and metallic hydroxide species are generated in situ by electro-dissolution of sacrificial anode materials triggered by electric current applied through the
Corresponding author. E-mail addresses: [email protected] (E. Karamati-Niaragh), [email protected] (M.R. Alavi Moghaddam), [email protected] (M.M. Emamjomeh), [email protected] (E. Nazlabadi). ∗
https://doi.org/10.1016/j.jenvman.2018.09.091 Received 15 May 2018; Received in revised form 5 September 2018; Accepted 25 September 2018 0301-4797/ © 2018 Elsevier Ltd. All rights reserved.
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electrodes (Moussa et al., 2017; Pulkka et al., 2014). In the EC process, direct current (DC) is generally applied to produce the electric current through the electrodes. In this condition, an impermeable oxide layer may form on the cathode as well as corrosion of anodes and inhibit the effective current transport between electrodes and therefore the efficiency of the EC process may diminish. Furthermore, flows of current in one direction can reduce the lifetime of the electrodes (Ghanizadeh et al., 2016; Moussa et al., 2017). The passivity of the electrodes can be minimized using the alternating current (AC) mode in which cathode and anode can be switched periodically. Thus, the delay in cathode passivation and the anode deterioration confirms acceptable electrode life (Vasudevan and Lakshmi, 2011). The AC mode was also considered as one of the proper alternative in the EC process for different types of pollutants namely, textile dye (Tiaibaa et al., 2017), fluoride (Ghanizadeh et al., 2016), oily water (Cerqueira et al., 2014), lead and zinc (Mansoorian et al., 2014), copper (Kamaraj et al., 2013), cadmium (Vasudevan and Lakshmi, 2011) and dyes (Eyvaz et al., 2009). Ghanizadeh et al. (2016) showed that DC mode had higher efficacy than that of AC mode for floride removal based on statistical analysis. However, Mansoorian et al. (2014) proved that the operating costs which related to energy consumption and electrode corrosion by using AC mode reduced for lead and zinc removal. Cerqueira et al. (2014) also indicated that application of AC mode of EC process for oil and grease removal promoted a lower electrode consumption as compared to using DC mode. Kamaraj et al. (2013) showed that the energy consumption reduced for copper removal as well as removal efficiency improved by using AC mode. Vasudevan and Lakshmi (2011) reported that the cadmium removal for AC mode was efficient than that of DC mode and the energy consumption reduced in AC mode, which lead to operating costs improvement. Eyvaz et al. (2009) also found that the AC mode was more efficient for dye removal. Nitrate removal by using the EC process have been studied by other research groups (Emamjomeh and Sivakumar, 2009; Govindan et al., 2015; Hashim et al., 2017a; Kumar and Goel, 2010; Lacasa et al., 2013; Lacasa et al., 2011; Moussa et al., 2017; Nazlabadi and Alavi Moghaddam, 2017; Pulkka et al., 2014; Xu et al., 2018; Yehya et al., 2014). Also, some studies indicate that the operating cost of nitrate removal is of high expenses using the EC process (Lacasa et al., 2013; Yehya et al., 2015). However, to the best of our knowledge, evaluation of AC mode of a continuous electrocoagulation (CEC) process has not been applied for nitrate pollution to reduce its operating costs. In addition, RSM as a statistical-mathematical method could be used to evaluate the selected parameters and their interactions between responses for the CEC process (Hakizimana et al., 2017; Hendaoui et al., 2018). As is known from the literature review, RSM method is applied to evaluate EC process in batch systems for nitrate removal (Emamjomeh et al., 2017; Nazlabadi and Alavi Moghaddam, 2017), however, this method has not been simultaneously applied for nitrate removal efficiency and its operating costs using AC and DC modes in the CEC process. The main objective of this research is an evaluation of the operating costs for nitrate removal using the CEC process. For this purpose, the electrode and the energy consumption using the AC and DC modes were compared. Hence, two series of 31 experiments were carried out in both cases through the RSM to identify the relationship between two responses (nitrate removal and its operating costs) and the selected effective parameters.
(dimension 100 × 70 × 1 mm) were connected in a monopolar parallel mode to the DC (Micro, PW4053R, 0–5A, 0–40 V) and the AC power supply (0–5A, 0–40 V, 50 Hz). The inter-electrode gaps were kept constant (10 mm) for all of the experiments. A peristaltic pump (Heidolph, PD 5201, Germany) was used to allow influent control from a reservoir tank to feed the electrolytic cell. Effluent from the electrolytic cell enters to a sedimentation tank to remove the produced suspended solids. 2.2. Experimental techniques Sodium nitrate (NaNO3) was dissolved in tap water for preparing the required initial concentration (50–250 mg/L as NO3−). In order to adjust the initial pH (2–10), sulphuric acid (2N) and sodium hydroxide (5N) were added to the solutions. To increase the conductivity of the solutions, sodium sulfate (Na2SO4) was used as a supporting electrolyte. The pH and the conductivity of the solutions were monitored during and at the end of the CEC process using a pH-meter (pH 340i, WTW, Germany) and a conductivity-meter (Cond 340, WTW, Germany). All of the experiments were conducted at the ambient temperature. At the end of each experiment, samples were taken from the effluent and were analyzed for nitrate concentration measurements. For this achievement, UV–Vis spectrophotometer (HACH, DR4000, USA) at a wavelength of 500 nm was applied according to the standard methods for examination of water and wastewater (AWWA, 1998). The performance of the CEC process was assessed in terms of the contents of nitrate concentration before and after treatment which was calculated using Eq. (1):
Nitrate Removal Efficiency (RE%) = (
Cr
Ct Cr
) × 100
(1)
where Cr and Ct are the nitrate concentration in raw and the treated solutions (mg/L-NO3-), respectively. The accuracy of the experiments was also assured using the random repetition of experiments. A scanning electron microscopy (SEM) (Seron, AIS2100, South Korea) was also used to evaluate the morphology of the electrodes after electrolysis (AC and DC modes). The SEM images of electrodes were related to those ones which were applied after all 31 runs in each current modes. 2.3. Economic analysis Feasibility study of the EC process in large scale application, mainly depends on its cost-effectiveness. The accurate operating cost of the EC process comprises the cost of chemicals, electrode consumption, energy consumption, sludge dewatering/disposal, maintenance, pertaining to labor and fixed costs (Hakizimana et al., 2017; Hashim et al., 2017b). According to the literature, costs of electrodes and energy consumption were considerable for preliminary cost evaluation of EC process due to their major role in high expenses (Behbahani et al., 2011; Yehya et al., 2014), especially for removing low concentration of nitrate (Yehya et al., 2014). The Eq. (2) was used for estimation of these operating costs US$/(kg NO3− removed):
Operating Cost (OC)=a×Cenergy + b×Celectrodes
(2)
where Cenergy (kWh/(kg NO3− removed)) and Celectrodes (kg Al/(kg NO3− removed)) are energy and electrode consumption for nitrate removal, respectively. Besides, a and b, the coefficient of the Iranian market in 2016, are described below:
2. Materials and methods
Coefficient a: industrial electricity price = 0.0222 US$/kWh Coefficient b: Wholesale Al electrode price = 1.56 US$/kg Al
2.1. Experimental setup A continuous EC process was used for nitrate removal as schematically shown in Fig. 1. An electrolytic cell was made from Plexiglas with an effective volume of 2.4 L. In the cell, aluminum plate electrodes
The electric energy consumption of the EC process was deduced as a function of operation time through Eq. (3) as follows (Behbahani et al., 2011; Hakizimana et al., 2017; Hashim et al., 2017b): 246
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Fig. 1. Continuous monopolar electrocoagulation process: 1) Reservoir tank; 2) Peristaltic pump; 3) Electrolytic cell; 4) Aluminum electrodes; 5) DC & AC power supply; 6) Sedimentation tank and 7) Effluent.
levels of the independent parameters are presented according to the RSM model. For statistical calculations, the variables Xi were coded as xi according to the following equation (Hakizimana et al., 2017; Behbahani et al., 2011):
t
E=
V·I dt
(3)
0
where E is the electric energy consumption (kWh/(kg NO3− removed)), V is the voltage (V), I is the current intensity (A) and t is the electrolysis time (hrs). In case of continuous EC, the energy consumption of the pump was also calculated in the present study, however mechanical power for mixing purposes was neglected. To obtain the mass depletion of the electrode corrosion due to the anodic oxidation, weight loss of the electrodes was calculated by subtracting the electrodes' weight at the beginning and at the end of each experiment. The electrodes were also cleaned after each run in order to prevent surface pollution of the electrodes which might affect the electrodes passivation.
xi =
Y= b0 +
mg/L mL/min A/m2 –
X1 X2 X3 X4
i= 1
k
k
b ijxixj
(6)
j= 1 i= 1
3. Results and discussion 3.1. Development of regression model and its validation for AC and DC modes The results of the conducted experiments corresponding to the RSM design for nitrate removal efficiency and operating costs in both cases of DC and AC modes are presented in Table 2. The modified quadratic model for nitrate removal efficiency (RE%) and operating costs (OC) in terms of the coded values for DC and AC mode are given by Eqs. (7a), (b) and (8a), (b), respectively: For DC mode:
Table 1 Levels of the parameters according to RSM for the CEC process.
Initial nitrate concentration Inlet flow rate Current density Initial pH
bii x 2i +
where Y is the required responses of the CEC process (nitrate removal efficiency and operating costs in this study) and b0, bi, bii, bij, xi and xj are the constant coefficient, the linear coefficient, the quadratic coefficient, the interaction coefficient and the coded values of the factors, respectively. In this study, only a two-way interaction has been considered. The statistical significance of the produced models was evaluated through ANOVA with a confidence level of 95%. Residual plots and coefficients of determination (R2, Adjusted R2 and Predicted R2) were also presented to express the quality of the fitted models.
where Nf is the number of points in the cube portion of the design and is equal to 2k, and k is the number of factors. Thus, the α was calculated to be 2 in the present study. In Table 1, selected factors and their five
Factors
k
bi xi + i= 1
(4)
Unit
(5)
k
In the present study, the central composite design (CCD) method of RSM, commonly used by other researchers, was selected to design the experiments, as well as to generate a quadratic model of the CEC process. In this method, minimum numbers of experiments are achieved and interaction between parameters is also analyzed (Karimifard and Alavi Moghaddam, 2018; Behbahani et al., 2011; Emamjomeh et al., 2017; Georgiou et al., 2014; Nazlabadi and Alavi Moghaddam, 2017; Nazlabadi and Alavi Moghaddam, 2014; Song et al., 2015; Varank and Sabuncu, 2015). According to our previous work and obtained significant parameters (Karamati Niaragh et al., 2017), four parameters including the initial nitrate concentration, inlet flow rate, current density and initial pH were selected in the present study to evaluate the combined effects of these factors as well as present a mathematical model. Thirty-one experiments were designed by employing the parameters with five-levels. These experiments consist of 16 factorial experiments, 8 axial experiments on the axis at a distance of ± α from the center, and 7 replicates at the center point. The value of α for rotatability was calculated as brought in Eq. (4):
Variables
X 0) X
where X0 is the value of Xi at center point and δX represents the stage change. The statistical software Design Expert 7 was applied to analyze the experimental data and generate a second-order polynomial model, thus ANOVA, regression coefficients, three dimensional curves of the response surfaces and residual plots were developed. The empirical model of RSM represented by a second order polynomial regression is calculated through Eq. (6):
2.4. Experimental design and data analysis
= (Nf )1/4
(Xi
YRE = 52.49
7.01x1
7.04x2 + 5.17x3 + 1.98x 4
Levels
2.77x1 x 4 + 2.72x2 x3
-α
−1
0
+1
+α
3.77x42
50 40 45 2
100 60 60 4
150 80 75 6
200 100 90 8
250 120 105 10
+
YOC = 43.49
4.64x1 x2 + 2.34x1 x3
2.62x12 + 1.63x 22
1.29x 32 (7a)
12.13x1
4.10x2 + 5.41x3
0.80x2 x 4 + 0.98x3 x 4 + For AC mode: 247
2.14x2 x 4
8.50x12
0.64x 4 11.25x 22
1.40x1 x3 +
8.67x42
0.7x1 x 4 (7b)
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Table 2 RSM experimental design and its observed values in both cases of DC and AC modes. Run number
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 a
Initial nitrate concentration (x1)
Inlet flow rate (x2)
Current density (x3)
Initial pH (x4)
Direct current (DC) RE (%)
RE (kg removed) × 104
OC (US$/kg NO3− removed)
RE (%)
RE (kg NO3− removed) × 104
OC (US$/kg NO3− removed)
0 0 +1 0 +1 0 0 +1 +2 0 −2 +1 −1 −1 0 0 0 0 +1 −1 −1 +1 −1 +1 0 +1 −1 0 0 −1 −1
0 0 +1 0 −1 −2 0 +1 0 0 0 +1 +1 −1 0 0 0 0 +1 +1 +1 −1 −1 −1 +2 −1 −1 0 0 +1 −1
−2 +2 +1 0 −1 0 0 −1 0 0 0 +1 −1 −1 0 0 0 0 −1 +1 −1 +1 −1 −1 0 +1 +1 0 0 +1 +1
0 0 +1 0 +1 0 0 +1 0 0 0 −1 −1 −1 −2 +2 0 0 −1 +1 +1 −1 +1 −1 0 +1 +1 0 0 −1 −1
34.67 60 61 49.33 56 74.67 48 55 28 55.33 56 50 52 57 30.67 57.33 52.44 53.33 45 66 58 59 68 54 43.33 64 71 50.67 56.67 60 56
0.52 0.9 1.22 0.74 1.12 1.12 0.72 1.1 0.7 1.01 2.8 1 0.52 0.57 0.46 0.86 0.79 0.8 0.9 0.66 0.58 1.18 0.68 1.08 0.65 1.28 0.71 0.76 0.85 0.6 0.56
48.29 47.24 33.42 45.98 36.60 52.57 45.75 24.50 54.19 40.29 100.81 40.20 52.02 62.96 75.94 80.42 43.05 43.88 33.48 55.98 49.56 45.80 55.37 37.56 54.71 44.81 74.45 44.10 41.38 64.84 95.33
35.33 60 61.5 50.67 55 76.67 50 52.5 28.8 66.67 60 47.5 55 60 34 62 54 54.67 30 70 59 55 69 50 44 57.5 75 52 53.33 61 65
0.53 0.9 1.23 0.76 1.1 1.15 0.75 1.05 0.72 1 0.3 0.95 0.55 0.6 0.51 0.93 0.81 0.82 0.6 0.7 0.59 1.1 0.69 1 0.66 1.15 0.75 0.78 0.8 0.61 0.65
30.51 29.11 19.23 28.73 21.50 27.34 30.03 15.62 32.35 20.83 67.97 26.43 33.36 37.10 46.58 45.72 28.62 24.04 22.22 31.88 31.80 26.04 29.63 20.99 30.56 27.19 41.01 25.01 13.66 36.43 50.30
a
Alternating current (AC)
NO3−
a
RE: Removal Efficiency, OC: Operating Costs.
YRE = 52.93
7.91x1
+ 0.028x2 x 4
6.71x2 + 5.36x3 + 3.34x 4 0.69x3 x 4
2.13x12
+
1.85x 22
statistically significant (P ˂0.0001), and implies that the modified second-order quadratic model is fitted well with the experimental results. The results also specified that all the selected independent parameters were significant for removal efficiency of both cases of DC and AC models. Also, the most important independent process variables for operating costs were found to be initial nitrate concentration (x1), inlet flow rate (x2) and current density (x3) (detailed data not shown). According to Table 3, the lack of fit for nitrate removal efficiency (Pvalue of 0.5180 and 0.1339 for DC and AC, respectively) and operating costs (P-value of 0.1592 and 0.5044 for DC and AC, respectively) were
2.11x1 x 4 + 2.64x2 x3 1.32x 32
+
3.50x42 (8a)
YOC = 25.45
7.89x1
1.16x2 x3
2.66x2 + 3.26x3
0.66x3 x 4 +
6.18x12
11.29x 4 + 0.41x1 x2 + 1.03x1 x 4 (8b)
7.74x 22 + 5.18x42
The ANOVA results for DC and AC modes are also summarised in Table 3. As indicated in Table 3, the quadratic model of nitrate removal efficiency and operating costs in both cases of DC and AC modes were
Table 3 ANOVA results and determination coefficients for RSM model in both cases of DC and AC mode. Current
DC
Response
RE (%)
OC (US$/kg NO3− removed) AC
RE(%)
OC(US$/kg NO3− removed)
Source
Model Lack of Fit Pure Error Total Model Lack of Fit Pure Error Total Model Lack of Fit Pure Error Total Model Lack of Fit Pure Error Total
DF
13 6 4 23 11 7 6 24 13 6 4 23 11 8 4 23
Adj SS
2388.70 48 31.48 2468.18 7094.74 73.21 26.74 7194.68 3394.27 51.01 10.30 3455.58 3035.02 96.11 44.40 3175.52
Adj MS
183.75 8 7.87 – 644.98 10.46 4.46 – 261.10 8.50 2.58 – 275.91 12.01 11.10 –
F
23.12 1.02 – – 83.89 2.35 – – 42.58 3.30 – – 23.56 1.08 – –
P
Coefficient of determination (%)
˂0.0001 0.5180 – – ˂0.0001 0.1592 – – ˂0.0001 0.1339 – – ˂0.0001 0.5044 – –
248
0.8 Pred-R2≤ Adj-R2 ≤1.2 Pred-R2 & Adj-R2≤ R2
R2
Adj-R2
Pred-R2
96.8
92.59
78.80
✓
98.6
97.4
92.1
✓
98.2
95.9
83.5
✓
95.6
91.5
80
✓
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(b)
(a)
Direct Current (DC) (a)
(b)
Alternating Current (AC) Fig. 2. Normal probability plots in both cases of DC and AC modes for (a) nitrate removal efficiency and (b) operating costs.
not significant; thus, the data was fitted well to the model. In addition, high values of R2 were achieved 96.8% and 98.6% for removal efficiency and operating costs of DC, respectively, indicated a satisfactory fit of the quadratic model to the experimental data. In the case of AC, values of R2 were found to be 98.2% and 95.6% for nitrate removal efficiency and operating costs, respectively. The values of adjusted R2 (Adj-R2) were also lower than the R2 values and the Adj-R2 and predicted R2 (Pred-R2) were within approximately 0.20, which indicated reasonable agreement. Furthermore, the adequacies of the models were controlled by analyzing the residuals. For this purpose, the normal probability plots for nitrate removal efficiency and operating costs, which indicates whether the residuals follow a normal distribution, are illustrated in Fig. 2. As seen in Fig. 2, the normal probability was relatively satisfied as the points in the plot follows from fairly straight line. All of the plots in Fig. 2 revealed that the model for both DC and AC modes were found to be adequate to describe the nitrate removal efficiency and its relative operating costs using CCD method of RSM.
the allowable WHO limitations for drinking water was 55 min (Hashim et al., 2017a). However, at the initial nitrate concentration of 150 mg/ L, the inlet flow rate of 100 mL/min was not enough for the CEC process to meet these limitations. The literature highlighted that current density, which determines the anodic dissolution rate and hydrogen gas generation, affected the EC performance (Behbahani et al., 2011; Koparal and Oğütveren, 2002; Moussa et al., 2017). Fig. 3(b) and (c) shows that higher nitrate removal rates were achieved with higher current density. In the current study, the experiments were carried out in different ranges of the current densities between 60 and 90 A/m2 to evaluate the influence of this main parameter on the CEC process for nitrate removal. For instance, according to Fig. 3(c), in constant initial nitrate concentration of 100 mg/L, initial pH of 7 and the inlet flow rate of 100 mL/min, the nitrate removal efficiency improved about 15%. The improving effects of increased current density were also observed for AC mode in the same conditions (data not shown here). However, the results of this study along with literature (Behbahani et al., 2011; Emamjomeh et al., 2017; Hashim et al., 2017a, 2017b; Karamati Niaragh et al., 2017; Nazlabadi and Alavi Moghaddam, 2017) showed that high amounts of current density had a significant negative effect on the energy consumptions, and consequently on the operating costs. Therefore, by considering the operating costs, the optimum current density for nitrate removal efficiency using the CEC process for both cases of DC and AC modes was calculated to be 70–80 A/m2 in the present study. Fig. 3(d) illustrates that at a constant initial nitrate concentration, by increasing the initial pH, nitrate removal rate increases. This can be related to the reaction between Al metal and hydroxide ions. In this work, the optimum removal efficiencies were obtained in the initial pH range of 7–8 for both AC and DC modes. The results of this study have been recently observed by the other research groups (Hashim et al., 2017a; Yehya et al., 2014; Kumar and Goel, 2010; Lakshmi et al., 2013; Nazlabadi and Moghaddam, 2017). Conversely, some research groups have been reported that the alkaline pH (9–11) is the optimum pH for nitrate removal (Koparal and Oğütveren, 2002; Emamjomeh et al., 2017; Emamjomeh and Sivakumar, 2009). But, Safari and Yehya study groups showed that the rate of nitrate removal had not changed significantly when the pH increases from 7 to 10 (Yehya et al., 2014; Safari et al., 2015).
3.2. Evaluation of nitrate removal for AC and DC modes Generally, the most important parameters, which affect the performance of the CEC process, are initial concentration of nitrate, current density, inlet flow rate and initial pH of the solution. The main parameters effects on the CEC process performance as well as their contribution ratio were elaborately discussed in our previous work (Karamati Niaragh et al., 2017). The significant relationships between nitrate removal efficiency and the two-way interaction terms of the DC mode for the CEC process are also shown in Fig. 3. According to Fig. 3(a), a higher removal efficiency occurred for low initial nitrate concentration and low inlet flow rate. At a constant nitrate removal efficiency, the required inlet flow rate reduced when the initial nitrate concentration increased. The similar results were also observed for AC mode (data not shown here). The removal efficiency was achieved higher than 60% when the initial nitrate concentration and the inlet flow rate were 100 mg/L and 100 mL/ min, respectively. The detention time required for the inlet flow rate of 100 mL/min was 48 min. This result is in agreement with the results achieved by Hashim et al. in batch EC process, which revealed that the required time to reduce the initial nitrate concentration of 100 mg/L to 249
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(a) al Nitrate remov ) (% cy en effici
al Nitrate remov ) (% y nc ie effic
(b)
e rat w flo in) let /m In (mL
nc
ate g/L) itr l n (m tia on Ini trati en
co
te w ra t flo Inle /min) (mL
nsity nt de Curre m2 ) (A/
(d)
al Nitrate remov ) efficiency (%
al Nitrate remov ) (% y efficienc
(c)
) e rat g/L nit (m n al iti io In trat en nc
co
) te /L tra g ni (m al on iti ti In ntra e
nc co
nt d
Curre
2 /m )
(A ensity
l pH
Initia
Fig. 3. Relation between nitrate removal efficiency and the interaction terms using 3d plots (DC mode): (a) the interaction between initial nitrate concentration and inlet flow rate; (b) the interaction between inlet flow rate and the current density; (c) the initial nitrate concentration and the current density; (d) the initial nitrate concentration and the initial pH.
3.3. Analysis of operating costs for AC and DC modes
efficient alternative. In agreement with this result, other research groups have reported that the high performance of AC in the removal of textile dye (Tiaibaa et al., 2017), oily water (Cerqueira et al., 2014), lead and zinc (Mansoorian et al., 2014), copper (Kamaraj et al., 2013), cadmium (Vasudevan and Lakshmi, 2011) and dyes (Eyvaz et al., 2009), but Ghanizadeh research group has confirmed that the efficacy of AC mode was not statistically significant for fluoride removal (Ghanizadeh et al., 2016). Therefore, in the present study, minimizing the electrodes passivity using the AC mode had no significant effect on nitrate removal efficiency during the CEC process. It may due to an insignificant increase in the resistance of the electrolyte in the applied detention times. In conjunction with operating costs, Fig. 4 illustrated that the removing nitrate operating costs of DC mode are higher than AC mode for the CEC process. The average operating cost of all experiments for DC mode was achieved 54 US$/(kg NO3− removed); while this amount was obtained 29 US$/(kg NO3− removed) using AC mode. As a result, the operating costs of nitrate removal efficiency using AC mode for the CEC process was improved about 40%. To elaborate how the costs were attributed to the amount of energy and electrode used in the CEC process, the energy and the electrode consumption of all experiments
From the literature, it is obvious that the application of EC for nitrate removal is of high operating costs, especially, it is expensive for treatment of water containing low nitrate concentrations (Yehya et al., 2014). However, for the EC lab scale units, the electrode material and the electrical energy consumption are of significant effect on operating costs (Yehya et al., 2014; Hashim et al., 2017a; Emamjomeh et al., 2017). In addition, a review of the existing literature indicated that the electrode material and energy consumption could be more cost-effective if the AC mode is used instead of the DC mode during the EC process. Furthermore, the application of AC can prohibit the formation of the impermeable layer on the surface of the anodes, which is considered as a demerits in DC mode of the EC process (Ghanizadeh et al., 2016; Cerqueira et al., 2014; Mansoorian et al., 2014; Kamaraj et al., 2013; Vasudevan and Lakshmi, 2011; Eyvaz et al., 2009). To investigate the techno-economical effects of AC and DC mode, two series of 31 experiments have been carried out using the AC mode as well as the DC mode. According to Table 2, nitrate removal efficiency in the AC mode is slightly higher (1%) than the DC mode in most of the experiments; however, it does not mean that the AC mode could be an 250
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Operating Cost (US$/kg nitrate removed)
120
AC DC
100 80 60 40 20 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Number of experiment Fig. 4. The operating costs of the CEC process through 31 experiments designed by RSM in both cases of DC and AC modes.
Energy consumption (kWh/gr nitrate removed)
3
AC DC
2.5 2 1.5 1 0.5 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Number of experiment
Electrode consumption (kg Al/kg nitrate removed)
Fig. 5. The energy consumption of the CEC process through 31 experiments designed by RSM in both cases of DC and AC modes.
50
AC
45
DC
40 35 30 25 20 15 10 5 0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Number of experiment Fig. 6. The electrode consumption of the CEC process through 31 experiments designed by RSM in both cases of DC and AC modes.
are presented in Figs. 5 and 6, respectively, in both cases of AC and DC mode. According to Fig. 5, the energy consumption was slightly higher in the case of AC mode in current intensities between 2 and 4A for nitrate removal. Thus, it indicated that the energy consumption had may no relation with the impermeable oxide layer formed on cathodes in DC mode, which increase the resistivity of the electrolyte. This result is in agreement with Cerqueira research work on oily water treatment,
which demonstrated that the energy consumption was higher in the case of AC mode at current intensities lower than 3A (Cerqueira et al., 2014). Conversely, other research groups indicated that the energy consumption in the case of AC is lower than DC mode of EC process for removal of fluoride (Ghanizadeh et al., 2016), lead and zinc (Mansoorian et al., 2014), copper (Kamaraj et al., 2013), cadmium (Vasudevan and Lakshmi, 2011) and dyes (Eyvaz et al., 2009). The higher energy consumption in AC mode may due to the type of 251
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H2O
+2
provides a longer life for electrodes, which is considered as one of the disadvantages of the EC process. To obtain more insight into the effect of AC mode, the morphology of the aluminum anode surface after the CEC process was evaluated by SEM for both cases of AC and DC modes after 31 runs, which is presented in Fig. 8(a) and (b), respectively. It can be observed that less disordered pores formed in the case of AC which confirmed the uniform dissolving of the electrodes. While, for the DC mode, many tortuous pores of the electrode's surface shows the aluminum oxide may form.
H2O
NO2
-
e
-2
-
e
+6 e-
N2
NO3 +8
e-
NH3
-3
-
e
H2O
4. Conclusions The alternating current was applied in the present study to reduce the operating costs of the CEC process for nitrate removal. The performance and the operating costs of the CEC process using both cases of the AC and the DC modes was also compared. For this purpose, two series of 31 experiments, which were designed by RSM, were carried out in both current modes. The second modified quadratic models were also developed for the nitrate removal efficiency and the operating costs for both current modes, which were statistically significant. According to ANOVA results, the models fitted well with the experimental results. High R2 values for AC and DC modes were 96.8% and 98.6% for nitrate removal efficiency and 98.2% and 95.6% for operating costs, respectively. The R2, Adj-R2 and Pred-R2 were also in a reasonable agreement. Hence, the RSM method has been approved as a powerful tool to evaluate the CEC process. The performance of nitrate removal in the AC mode was slightly higher than that of the DC mode in more than 80% of the experiments. However, to choose the AC mode as an effective alternative, the performance of the CEC process has to be evaluated in conjunction with its operating costs. The operating costs of the DC mode was higher than that of the AC mode for nitrate removal efficiency using the CEC process. The average operating cost of the experiments using the DC mode was achieved 54 US$/(kg nitrate removed); while this amount was obtained 29 US$/(kg nitrate removed) for the AC mode. The significant reduction of the operating costs was related to the electrode consumption in this study rather than the energy consumption. The average electrode consumption of the experiments using the DC mode was more than 4 times higher than that of the AC mode. As a result, the operating costs was improved more than 40% using the AC mode. Therefore, the AC mode achieved to be a promising cost-effective alternative for nitrate removal using the CEC process.
H2O
Fig. 7. Schematic reduction pathway of nitrate anions.
pollutants and its complexes of removal mechanisms. The process of nitrate reduction is summarised in Fig. 7 (Govindan et al., 2015; Hashim et al., 2017a). Also, since the first step in nitrate removal is related to nitrate reduction, the key role on nitrate removal mechanism is the electricity, which has significant effect on energy consumption (Yehya et al., 2014). As depicted in Fig. 6, conducting of all experiments in constant situations for both AC and DC modes confirmed that the consumption of the aluminum electrode was significantly lower in the AC mode as compared to that of the DC mode. According to the obtained results, the average electrode consumption of the experiments using the DC was about 4 times higher than that of the AC mode. In other words, after same conditions of the CEC process, the average amount of aluminum electrode consumed in DC mode was 19.96 gr/(gr NO3−removed), whereas in the AC mode it was achieved 4.96 gr/(gr NO3− removed). Therefore, the DC mode of the CEC process consumed the electrode much faster and the AC mode performed efficiently. This was probably related to the uniform dissolution of the anode and the cathode during the CEC process using AC mode. It means that the higher electrode consumption by DC mode refers to one directional flows of DC mode, which allows the irregular wear on the electrode plates due to the oxidation at the same preferential points of the plates. The reversal of current in the AC mode induces the uniformly points of electrodes, thus,
(a)
(b)
Fig. 8. SEM images of aluminum anodes: (a) Alternating current; (b) Direct current.
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(b)
oval Nitrate rem ) efficiency (%
oval Nitrate rem ) cy efficien (%
(a)
te ra w n) lo t f /mi le In (mL
te tra n ni io al rat iti nt ) In nce g/L co (m
te w ra t flo Inle /min) (mL
nsity nt de Curre m2 ) (A/
oval Nitrate rem (%) cy en ci effi
(c)
te tra n ni io al rat iti nt ) In nce g/L co (m
al pH
Initi
Acknowledgments
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The authors would like to thank the Amirkabir University of Technology for financial support. In addition, the authors wish to appreciate Mr. Mahyar Ghannadi and Ms. Pariya Sefatjoo (former M.Sc students of AUT) for their respected assistance during the experiments. References AWWA (American Water Works Association), APHA (American Public Health Association), WEF (Water Environment Federation), 1998. Standard Methods for the Examination of Water and Wastewater. Washington, DC, USA. Azadeghan, M.M., Alavi Moghaddam, M.R., Maknoon, R., 2014. Public awareness and performance regarding nitrate pollution in nitrate-polluted area of Tehran, Iran. Environ. Eng. Manag. J. (EEMJ) 13 (3), 611–617. Behbahani, M., Alavi Moghaddam, M.R., Arami, M., 2011. Techno-economical evaluation of fluoride removal by electrocoagulation process: optimization through response surface methodology. Desalination 271 (1–3), 209–218. Cerqueira, A.A., Souza, P.S.A., Marques, M.R.C., 2014. Effects of direct and alternating current on the treatment of oily water in an electroflocculation process. Braz. J. Chem. Eng. 31 (3), 693–701. Emamjomeh, M.M., Jamali, H.A., Moradnia, M., 2017. Optimization of nitrate removal efficiency and energy consumption using a batch monopolar electrocoagulation: prediction by RSM Method. J. Environ. Eng. 143 (7), 4017022. Emamjomeh, M.M., Sivakumar, M., 2009. Denitrification using a monopolar electrocoagulation/flotation (ECF) process. J. Environ. Manag. 91 (2), 516–522. Eyvaz, M., Kirlaroglu, M., Aktas, T.S., Yuksel, E., 2009. The effects of alternating current electrocoagulation on dye removal from aqueous solutions. Chem. Eng. J. 153 (1–3), 16–22.
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