Optimization of nitrogen removal from an anaerobic digester effluent by electrocoagulation process

Journal of Environmental Chemical Engineering 7 (2019) 103195

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Optimization of nitrogen removal from an anaerobic digester effluent by electrocoagulation process Azam Mohammadia, Ali Khadirb, Ramin M.A.Tehrania, a b

T

⁎

Department of Chemistry, Yadegar Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran Young Researcher and Elite Club, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran

A R T I C LE I N FO

A B S T R A C T

Keywords: Nitrogen Electrocoagulation Digester Effluent Anaerobic Adsorption

The present study deals with the applicability of electrocoagulation to remove total nitrogen from actual anaerobic digester effluent for the first time. The effects of the main operational parameters including electrolysis time, current density, inter-electrode distance, agitation speed, electrode material and punched electrodes were investigated. The results showed that at 100 min of electrolysis time, 66.32% of nitrogen was removed. Current density of 0.9 A revealed a higher nitrogen elimination. At inter-electrode distance of 3 and 7 cm, maximum efficiency and energy consumption was achieved, respectively. In terms of electrode materials, the maximum and the minimum nitrogen removal efficiency of 53.4% and 42% was attributed to Fe/Al, and Al/Al, respectively. Under optimum conditions, 81.59% of total nitrogen was removed. The mechanism of electrocoagulation was modeled using removal kinetics, adsorption kinetics, two and three-parameter isotherms. Linear and non-linear method was investigated and the best model was chosen according to different error functions. Pseudo first order model describes the reaction well since R2 (0.9997) value was too close to unity, and also error function values including Δq(%), SAE, ARED, and χ2 were 1.7, 48.84, 3.11, and 4.33, respectively. In terms of R2 value, it exhibited that Freundlich (0.953) and Sips (0.952) models were suitable to describe adsorption, suggesting heterogeneous adsorbent and quasi-Gaussian distribution energy.

1. Introduction Nitrogen (N), one of the most essential nutrients for all life forms, accounts for 78% of atmosphere as the form of N2 gas which indirectly is used for metabolism and plant uptake. All plants, animals, and humans require N to live since it presents in amino acid, proteins, RNA and DNA. There is no doubt that nitrogen is vitally important for living creatures, however, recent uncontrolled human activities have significantly altered nitrogen cycle on Earth in which leads to an increase of N compounds in environment including ground waters and surface waters. Half of the synthetic N fertilizer ever used on Earth has been used in just the last 15–20 years, for instance [1]. It was reported that since 1980s the concentration of N tended to increase in Chinese streams as a consequence of demographic, industrial, and agricultural development [2]. In most of the European countries nitrate concentration in groundwater was roughly stable (17.5 mg/L) from 1992 to 2012 and over that period Finland and Malta exhibited the minimum (1 mg/L) and maximum (58.1 mg/L) values, respectively [3]. Groundwater pollution by N compounds was also reported in various countries such as Morocco, Niger, Nigeria, Senegal, India-Pakistan, Japan,

⁎

Lebanon, Philippines, and Turkey [4]. Acidification and eutrophication of aquatic bodies, occurrence of toxic algae, methemoglobinemia disease, toxicity effect on aquatic animals, cancer and oxygen decline are main disadvantage of N increase which are induced by industrial wastewater effluent, runoff from agricultural regions, waste disposal leachate and livestock wastewaters [5–7]. Infant methemoglobinemia disease was observed in Eastern Europe, Hungary, Romania, and Albania [8,9]. In the case of fish, it was claimed that neurological disorder, hyperactivity, convulsions, lethargy, and loss in balance are the main side effect of being exposed to excessive amount of nitrogen [10]. Based on the above considerations, stringent regulations have passed and obliged the industrial activities to search for an appropriate alternative to minimize N release. Sludge digester supernatant is one of the potential sources of nitrogen concentration enhancement in the environment, and recently has received striking attention in the past decade [11]. Anaerobic digester unit (AD), biologically degradation of sludge in the presence of no oxygen, is considered as a sustainable process to recover methane and hydrogen from waste which can bring economic benefits or utilized for the production of heat [12]. Furthermore, less sludge production

Corresponding author. E-mail address: [email protected] (R. M.A.Tehrani).

https://doi.org/10.1016/j.jece.2019.103195 Received 1 May 2019; Received in revised form 27 May 2019; Accepted 1 June 2019 Available online 04 June 2019 2213-3437/ © 2019 Elsevier Ltd. All rights reserved.

Journal of Environmental Chemical Engineering 7 (2019) 103195

A. Mohammadi, et al.

reduction reaction (Eq. (2)):

than aerobic method is another factor of widespread use of AD in the past decade. Beside the advantages, digester supernatant and subsequently sludge dewatering supernatant generally contain high amount of nitrogen and cannot discharge directly into mainstream of the plant since it unbalance the chemical oxygen demand / total Kjeldahl nitrogen / total phosphorus ratio [13,14]. It was also reported that once supernatant is recycled back to the main streams, it causes larger reactors, high energy consumption, higher treatment cost, and degradation of effluent quality which induce nitrogen release [15]. Furthermore, recent studies has demonstrated that direct discharge of supernatant into the influent stream intensifies the sludge bulking and foaming in secondary sedimentation tank which is not desirable for achieving high standard effluent quality for nitrogen [16]. The recycled supernatant stream can account for 15–40% of the nitrogen load to the head of the wastewater treatment plant but contributes only 5–10% of the hydraulic load, resulting a heavy burden on the mainstream treatment [11,17,18]. For instance, in the Blue Plains AWTP sludge plant the supernatant contain as much as 1500 mg/L NH4+-N representing as much as one third of the biological process nitrogen load for nitrification and denitrification [19]. So, it is suggested to treat supernatants to lower its nitrogen concentration to average influent quality before addition to mainstream. Since now a few physical, chemical, and biological methods have been employed as the post-treatment for anaerobic digester and sludge dewatering supernatants. In terms of the biological processes, sequencing batch reactor [20], separate intermittent denitrification [21], complete nitrification denitrification [22], partial ammonium oxidation and denitrification [18], anammox [23,24], membrane bioreactor [25] etc have been proposed. Some difficulties could be observed in biological N removal from anaerobic effluent. Firstly, low chemical oxygen demand/total nitrogen (COD/TN) ratio (1–3) is inadequate to facilitate efficient TN removal [26]. It was claimed that optimum COD/TN ratio for TN removal by nitrification and denitrification should be between 4 and 5 in an activated sludge process [27]. Secondly, an external carbon source may be required for N removal which increases the operational cost by 40–50% [28]. For anammox process, sustaining the required number of anammox bacteria in the system might hinder the TN removal to some extend [12]. Sensitivity to pH, temperature, and dissolved oxygen are another reasons limiting the applicability of biological process for such a high concentrated effluent [29,30]. In terms of physico-chemical post-treatment methods, air stripping [26], membrane filtration [31], wet oxidation [32], adsorption [33], etc have been suggested for N removal. Electrocoagulation (EC) was first reported for wastewater treatment in England in 1889, but in that time its applicability was restricted to high capital investment and energy cost [34]. By resolving the issues in the recent years, EC is considered to be a promising technique since it has great advantages including no addition of chemicals, less sludge production as compared to chemical coagulation, an environmental friendly technology, minimal startup time, minimal risk of secondary pollutants as compared to advanced oxidation processes, low energy requirement, and facile operation [35,36]. The EC process is accomplished in three distinctive sections: (1) anode oxidation and cathode reduction (2) floatation (3) coagulation or adsorption. Adsorption is generally regarded as a facile, low-cost, and effective method for environment remediation, and since now various composite materials for pollutants removal have been synthesized [37–39]. To date, different adsorbents with various surface modification methods such as the mussel-inspired chemistry have been synthesized in the case of environmental and biomaterial applications [40–46]. In-situ generation of adsorbent/coagulant is one of the main advantages of EC over adsorption processes. When iron as anode is used in EC, Fe+2 is generated and dissolved in the wastewater solution, as follows (Eq. (1)):

Fe →

Fe+2

+

2e−

2H2 O + 2e− → 2OH− + H2

(2)

To the best of our knowledge, since now no investigation has been reported regarding TN removal from concentrated anaerobic digester effluent by EC process. The effect of electrolysis time, current density, inter-electrode distance, electrode material, punched electrode, and agitation speed on TN removal was studied. The removal pathway of TN was modeled with various kinetics and adsorption models. 2. Materials and method 2.1. Chemicals and materials Iron and aluminium were provided by a local market in Tehran, Iran. pH of the solution was determined by 780 pH Master, Metrohm (Switzerland). Oven model TC40, Salvislab (Switzerland) was used to dry the collected samples. UV-spectrophotometer model DR6000, HACH LANG (USA) was utilized for TN concentration determination. 2.2. Experimental set up and procedure It has been noted that several operating parameters influence the EC performance for the target pollutant removal. Among these parameters, the most important ones including reaction time, current density, electrode materials, agitation speed, and punched electrodes were investigate. In this regard, real samples from AD effluent were taken in the days of experiment. Since EC was performed for the actual solution, no changes for pH was considered in order to minimize cost regarding chemicals consumption and also strengthen the simplicity and applicability of the process in real environment. Furthermore, under optimum operation of AD, the pH of the reactor must be approximately neutral. Hence, it is expected that the in all EC experiments, the pH of the solution to be neutral. The samples used in this study were collected from an AD of a wastewater treatment plant in Iran. Samples were always taken at the same location and were stored at 4 ° C to prevent biological activities. The mean value of pH and temperature of the collected samples were 6.83, and 37 ° C, respectively as it was expected. The value of TN ranged from 850 to 950 mg/g because of the in situ operation of the systems. To conduct the experiments, the TN concentration was fixed at 900 mg/g. Other physico-chemical properties of the sample including total solid, dissolved solid, total phosphor, and chemical oxygen demand were tested to be 3520, 3572, 13.24, and 119 mg/L, respectively. The electrocoagulation experiments were conducted in a 1 L beaker. Iron and aluminium were used as anodes and cathode and the inter-electrode distance was fixed at 3 cm. Electrodes were bought from a local market in Iran, and then washed several times before experiment. The goal behind this approach was to minimize the cost of treatment and increase the feasibility of the process. The dimensions of electrodes were 10 × 4.1 × 0.1 cm . The electrodes were washed with 0.2 M HCl and rubbed with sand filter paper before each experiment. The electrodes were installed vertically in the reactor. Electrodes were connected to a direct power supply with adjustable amperage and voltage. The electrical conductivity of the solution was sufficient for electrolysis; no salt addition was used as supporting electrolyte. Experiments were done at ambient temperature (20 °C). A schematic of the electrochemical reactor is shown in Fig. 1. In terms of electrocoagulation efficiency, the percentage of TN removal was determined using the following (Eq. (3)):

Removal efficiency (%) =

TNi − TNo TNi

(3)

where TNi and TNo are concentration of initial total nitrogen and total nitrogen at time t, respectively. The theoretical amount of metal ions produced from anode during electrocoagulation process can be quantified by Faraday’s law, which is

(1)

Meanwhile at cathode, H2 gas is generated due to the water 2

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Fig. 1. Scheme for the working electrochemical reactor. n

expressed (Eq. (4)):

m=

ITM FZ

R2 = 1 −

∑i = 1 (qe, calculation − qe, experiment )2 n

¯ )2 ∑i = 1 (qe, experiment − qe, experiment

(6)

(4) 2.3.2. Normalized standard deviation (Δq (%)) The validity of the model can be defined by normalized standard deviation, and can be expressed as (Eq. (7)):

where I is the current (A), t is the process time (s), M is the molar mass of the electrode metal (g/mol), Z is the valency of the anode metal and F is Faraday’s constant (96,485 C/mol). Although in the present study Faraday’s law was employed for the amount of anode dissolution, it was previously reported that this amount is generally higher that real coagulant generation in the solution due to the pitting corrosion. Electrical energy consumption (EEC) is an important factor affecting the required cost for actual wastewater of industries. To calculate the amount of energy consumed during electrocoagulation, formula below can be applied (Eq. (5)):

2

Δq (%) = 100 ×

∑ ⎡ (qe, calculation − qe, experiment ) qe, experiment ⎤ ⎣ ⎦ N−1

(7)

2.3.3. The sum of the absolute error (SAE) The model provides a better fit as the magnitude of the difference between value obtained from experiment and calculation to be minimum (Eq. (8)).

KWh ⎞ VIT × 105 Electrical energy consumption ⎛⎜ ⎟ = (%removal of TN ) × VR ⎝ KgTNremoved ⎠

n

SAE =

(5)

∑ |qe, calculation − qe, experiment |

(8)

i=1

where, V is voltage (V), I is current (A), t is operating time in hours, VR is the volume of the wastewater treated (L) and TNi is the initial concentration of TN (mg/L) in wastewater.

2.3.4. Average relative error deviation (ARED) Minimization of the fractional error distribution across the entire studied concentration range is the superiority of this error (Eq. (9)).

2.3. Error analysis

ARED =

Since now, various mathematical models have been proposed to describe the experimental results obtained in a study, including electrocoagulation and adsorption processes. By fitting the experimental data to non-linear or linear equation, error functions may arise affecting the determination of the appropriate model. Kumar and Sivanesan have claimed that non-linear regression analysis method is a better way of obtaining the constant parameters involved in the equations [47]. In order to quantitatively compare the applicability of equations in fitting to data, several error functions were studied in the present study.

qe, calculation − qe, experiment 1 × 100 ∑ N qe, experiment

(9)

where N is the number of experimental data points, qe, calculation (mg/g) is the theoretically calculated adsorption capacity at equilibrium and qe, experiment (mg/g) is the experimental adsorption capacity at equilibrium. 2.3.5. Chi-square test (χ 2) The Chi-square statistic method is basically the sum of the squares of the differences between the experimental data and theoretically predicted data from models. The equivalent mathematical statement is (Eq. (10)):

2.3.1. Coefficient of determination (R2) R2 is one of the most commonly used method, indicating the level of variance in the dependent variable by its relationship with the independent variable and it is computed as a value between 0 and 1. The higher the value, the better the fit (Eq. (6)).

n

χ2 =

∑ i=1

(qe, calculation − qe, experiment )2 qe, calculation

If data from a model are similar to the experimental data, 3

(10)

χ2

will be

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Fig. 2. (a) The effect of electrolysis time (b) the amount of Fe(OH)3 generation (c) pH variation during EC (d) the effect of current density (e) the amount of energy consumed.

a small number, and if they are different, χ 2 will be a big number. The lower the value, the better the fit.

increases and provided more coagulant to adsorb TN from solution that resulted an increase in removal efficiency [48]. However, continuous generation of coagulant is not always favorable. Fig. 2b exhibits the amount of Fe(OH)3 generation at various time intervals. The authors think that optimum reaction time occur once there are enough coagulant to make flocks required to remove TN and beyond the optimum reaction time excess metal hydroxides are generated which are abundant due to availability of requires flocks, and a kind of energy wasting. For further investigation, pH variation during EC process was recorded (Fig. 2c). The pH alteration was almost rapid during the reaction. Specifically, pH was changed from 6.83 to 10.1 in the 150 min of the reaction. The pH increment in electrocoagulation is attributed to the formation of hydrogen gas at the cathode [49]. Generation of OH− in the EC is the main reason for pH enhancement during the elimination process [50]. According to the figure, optimum reaction time may be 160 min but for the ease of the following experiment, reaction time was chosen to be 100 min.

3. Results and discussion 3.1. Effect of electrolysis time Fig. 2a shows the effects of the reaction time on the removal efficiency of TN by the EC process. As seen in Fig. 2a the curve can be divided in two parts: until the reaction time of 100 min, the removal efficiency indicated not a significant rate but a suitable rate and reached a removal efficiency of 66.32%. However, with further increase in reaction time (100 to 180 min), the slope of the removal rate increases so smoothly that the removal efficiency becomes very close to each other. Similar results were observed for TN removed curved in which firstly high amount of TN are removed but as it goes on, removed TN concentration decreased very slightly. The reason behind this phenomenon is the fact that for a fixed current density, the number of metal hydroxide generation would increase as the reaction time 4

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motion of ions becomes easier due to reduction in IR- drop and consequently energy consumption was decreased and removal efficiency improved. On the other hand, increasing the inter-electrode distance resulted in two incidents. Firstly, motion of ions becomes difficult, IRdrop increases and results in more energy consumption. Secondly, the volume of wastewater needs treating increased, however, due to fixed current density in ration to lower inter electrode distance, the removal efficiency would decreased. Based on the obtained results, the interelectrode distanced was fixed at 3 cm for further experiments.

3.2. Effect of current density Current density, the amount of current applied per surface area of the anode, is one of the most influential parameter that directly affects the rate of coagulant generation and anode corrosion. Higher coagulant concentrations correspond to more active sites available which are to improve TN removal. Fig. 2d shows the effect of current density (0.3, 0.5, 0.9 A) on the removal efficiency of TN. The initial pH of the solution was tested to be 7.2. From the figure it can be said that with 0.3 A current density and a contact time of 100 min, removal efficiency was 70.53%, whereas with 0.5 A and 0.9 A current density over the same period, the removal efficiency was 72.11% and 75.91%, respectively. In fact, higher current density resulted in higher removal efficiency. Importance of adequate reaction time can be observed from this figure: for instance, at 50 min with 0.9 A, removal efficiency was 60.45%, while at the same current density and 100 min of reaction time, removal efficiency reached to 75.91%. In another point of view, treatment time can be reduced by utilizing high current density. The reason for this behavior is due to the fact that elevated current density leads to more anode dissociation and thus more Fe ions are generated according to Faraday’s law. In fact, generated Fe ions tend to react with OH− in the water to form Fe hydroxide acted as oxidic adsorbent to adsorb large amount of TN on its vast surface. Furthermore, it was found that hydrogen bubbles at the cathode surface are more generated with smaller size and lager surface area at elevated current density which helps to a greater upward flux and consequently more removal efficiency. It must be noted that high current density could ease mass transfer and solution mixing through the solution and the electrodes which are highly beneficial for electrocoagulation process. Generated monomeric ions and polymeric species such as FeOH+, FeOH2+, Fe(OH)+2 , Fe(H2 O)5 OH2 +, Fe(H2 O)4 (OH)+2 , Fe(H2 O)8 (OH)24 +, etc are capable of adsorbing N-species. Fig. 2e shows the energy consumption at 100 min of contact time with various current densities. From the figure, it can obviously be observed that by increasing the current density from 0.3 to 0.9 A, energy consumption also increased from 3.58 to 18.15 KWh/Kg TN removed. In other word, to reach high removal efficiency, more energy consumption and operational cost is required. The energy consumption at 0.9 A is approximately 5 times higher than that at 0.3 A. For the following experiments, the current density was fixed at 0.9 A to reach a high removal efficiency. The maximum applied voltage for 0.3 A, 0.5 A, and 0.9 A were 8.1 V, 10.5 V, and 15.3 V, which are in agreement with previous studying declaring that approximately high voltage is essential for nitrogen containing compounds removal [51]. Cho et al. previously reported that the removal efficiencies of NH4+–N from swine wastewater were proportional to the electric voltages applied [52]. Nitrogen removal pathway by electrocoagulation seems to be very complex, being influenced by many various factors. Briefly, it can be claimed that the oxidation of ammonium to N2 gas as well as precipitation of nitrogen containing groups with sweep coagulation by formation of polymeric complexes flocs and electrostatic adsorption are the main removal mechanism which will be discussed in detail later [53,54].

3.4. The effect of different electrode combination in electrocoagulation There is no any doubt that the electrode pair (anode/cathode) directly influences the generation of the coagulant and electrochemical efficiency. Therefore, in the present study, the effect of different combination of Al and Fe electrodes were investigated to figure out the maximum efficiency. Fig. 3b illustrated the obtained results from experimental test under optimum values of current density, and interelectrode distance. The contact time was fixed at 50 min. As can be seen from Fig. 3, the maximum and the minimum TN removal efficiency of 53.4% and 42% was attributed to Fe/Al, and Al/Al, respectively. By comparing the results, iron electrode as the anode is more attractive than Al. Previous studies declared that Al electrode is suitable for final purification of the solution [34]. The plausible explanation for this reason could be associated with higher adsorption capacity Fe-complexes and lower solubility [55,56]. Mahajan et al. used Fe/Fe and Al/ Al for treatment of a hospital operation theatre effluent. They observed a high removal efficiency by Fe/Fe [57]. Several other studies reached a similar result with present study for removal of different contaminants from water media [58,59]. 3.5. The effect of the punched electrode To investigate the effect of punch electrodes, the experiments were performed by taking two holes in the electrode with diameter of 2 cm. The results are shown in Fig. 3c. It can be noticed that higher removal efficiency was attained by punched electrode as compared to a plane one. The TN removal efficiency obtained by two holes electrode increased from 28.2% to 76.1% for an electrolysis time of 10 to 100 min. But in comparison to plane electrode it increased from 28% to 75.9% for the similar period. Once the electrode is punched, the electric field intensity at the edge of punched holes type electrodes become greater, resulting in an increase in the discharge current, and consequently higher removal efficiency [50]. In a study investigated the removal of acid red 131 dye by electrocoagulation, it was reported that the at an electrolysis time of 120 min, the removal efficiency of plane electrode and punched electrode was 95% and 99%, respectively [60]. 3.6. The effect of the agitation speed Agitation speed which is expressed as the rotational speed of the impeller is an influential parameter in the electrocoagulation process. Fig. 3d shows the effect of various agitation speeds ranging from 100 to 400 rpm on the efficiency of the TN removal. The figure denotes that by increasing the agitation speed, the removal efficiency increased as compared to non-agitation speed efficiency. At the an electrolysis time of 100 min for example, the removal efficiency for 100, 200, 300, and 400 rpm was 79.12%, 80%, 81.59%, and 79.56%, respectively; however, of non-agitation solution, it was 76.1%. To explain the reason it can be stated that once the solution is agitated, electrical resistance of the solution would decrease and leads to the movement of the generated flocks. In this direction, mass transfer of the solution promotes and agglomeration of small particles to make larger ones increase [61]. A closer look at the figure reveals that excessive agitation would hinder the generation of large flocks and reduce the efficiency of the process. Lowering the removal efficiency was observed by increasing the

3.3. Effect of inter-electrode distance Inter-electrode distance is an important variable that greatly influences the IR-drop, removal efficiency, energy consumption, and operational costs. The space between the electrodes is more importantly once the wastewater sample is low. To determine the effect of interelectrode distance, the distance between electrodes were kept at 3, 5, 6, and 7 cm. The results of inter-electrode distance on removal efficiency and energy consumption are presented in Fig. 3a. As it can be seen, by increasing the electrode distance from 3 to 7 cm, the removal efficiency decreases from 53.68% to 20%, however, the energy consumption increases from 4.75 to 19.01 KWh/Kg TN removed. It seems that there is an inverse relationship between removal efficiency and energy consumption. As the distance between electrodes becomes lower, the 5

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Fig. 3. The effect of (a) inter-electrode distance (b) electrode combination (c) punched electrode (d) agitation speed and (e) mass transfer coefficient.

removal results verify the calculated Km values. Similar results were also reported in other work [64].

agitation speed from 300 to 400 rpm. To confirm the increase of mass transfer by enhancing the agitation speed, mass transfer coefficient was calculated according to the expression below which is employed for stirred batch electrochemical reactor (SBER) (Eq. (11)) [62]:

XSBER = 1 − exp(

− Km A e t) VR

3.7. Kinetic study To design an optimum sorption process, prediction of batch kinetic is of great importance. Kinetic models are mainly divided to two groups; (1) solute concentration-based and (2) adsorbent dosage-based. The first group focuses on rate of the chemical reactions and how fast they proceed. However, kinetic models based on the adsorbent concentration involve the nature of the adsorption process along with chemical and physical characteristics of adsorbent. The production of metal hydroxides during the electrocoagulation acts like an adsorbent adsorbing TN from aqueous solution. The main difference between adsorption process and electrocoagulation is that adsorbent rapidly starts adsorption; however coagulant needs time to be produced adequately and then starts pollutant adsorption. Previously several researchers used different kinetics models to predict the mechanism involved in the sorption process. Similarly in the case of TN removal through electrocoagulation process, various kinetic models could be employed.

(11)

where VR is electrolyte volume (m3), Ae is the electrode area (m2), Km is mass transfer coefficient (m/s), t is reaction time (s), and XSBER is fractional TN conversion in stirred batch electrochemical reactor. This equation is a mass balance over the reactor via Faraday’s Law based on the fact that the longitudinal dispersion of flow due to diffusion is negligible [63]. The mass transfer coefficient was determined with respect to the electrolysis time with various agitation speeds (Fig. 3d). For each of the agitation speed, it is observed that the mass transfer coefficients decrease by increasing the reaction time. Logically, flocks generation and excessive turbidity of the working solution are the man plausible reasons. At 200 rpm for instance, mass transfer coefficient decreased from 0.141 to 0.065 (m/s) when the electrolysis time increases from 10 min to 100 min. Furthermore, at a constant electrolysis time of 10 min, mass transfer coefficients for 100, 200, and 300 rpm were 0.142, 0.141, and 0.157 (m/s), respectively, indicating the greater mass transfer at higher agitation speed. As it is expected, at 400 rpm it is seen that mass transfer coefficient declines, in which the obtained

3.7.1. First and second order As a matter of fact, the removal efficiency of TN through 6

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electrocoagulation is proportional to the amount of flocks generated and the pollutant concentration at ambient temperature and constant wastewater volume. For such electrocoagulation batch process, variations of TN concentration can be formulated by rate equation as follow for aluminium or ferric ions generation, respectively (Eq. (12,13)):

−d [TN ] = K1 [TN ][Al (OH )3] dt

(12)

−d [TN ] = K1 [TN ][Fe (OH )3] dt

(13)

equilibrium [66]. The non-linear PFO model expression is (Eq. (17)):

C (t ) = Ce + (C0 − Ce ) e−K app t

dqt = k (qe − qt )2 dt

Since the generation of aluminium hydroxide can be assumed constant for a given current density, the above equation can be written as (Eq. (14)):

−d [TN ] = K1 [TN ] dt

(14)

[TN ]t = −K1 t [TN ]0

qt =

Type 1:

Type 2:

(16)

where k2 is the second order rate constant and can be calculated from the plot 1 – 1 versus t.

3.7.2. Pseudo kinetic models Utilizing of pseudo kinetic model is another approach to describe time evolution of adsorption. In recent years, Legergen and Ho presented the models that called Pseudo-first-order (PFO) and Pseudosecond-order (PSO), respectively. Based on the PFO, the adsorption rate is directly proportional to the concentration difference at time t and at

Current density

Agitation speed

0.3 0.5 0.9 100 200 300 400

First Order Model R2

K2

R2

0.0053 0.0058 0.0067 0.0069 0.0073 0.0077 0.0074

0.9403 0.9215 0.9124 0.9330 0.9294 0.9172 0.9086

0.00002 0.00003 0.000035 0.000040 0.000041 0.000044 0.000042

0.9482 0.9768 0.9924 0.9409 0.9653 0.9570 0.9650

(20)

1 1 1 1 = + ( 2) qt qe Kqe t

(21)

1 qt Type 3: qt = qe − ( ) Kqe t

(22)

q Type 4: t = Kqe2 − Kqe qt t

(23)

Once the adsorption equilibrium state is reached through adsorption process, the interaction between adsorbent and adsorbate could be mathematically obtained, indicating valuable information regarding the removal process. Isotherm equations, in general are of those curves describing the mobility of the target pollutant from an aquatic environment to a solid phase at constant temperature and pH [71]. Adsorption isotherms help to find out the relationship between amount of adsorbate adsorbed on the adsorbent and the left out concentration of adsorbate in liquid at the time of equilibrium. Since now, various isotherm models have been proposed, in which each might be able to explain special sorption situation. Accordingly, Langmuir and Freundlich isotherms have been extensively employed in many studies.

Second Order Model

K1

t 1 t = + qt qe Kqe2

3.8. Adsorption isotherm

Table 1 Constant parameters for first and second order model. value

(19)

Firstly PSO was investigated. According to the figures related to linear and non-linear PSO models (Fig. 4a–e), it is evidently clear that this model cannot describe the kinetic of the adsorption. In the case of linear equations (PSO), the constant parameters, rate constant or adsorption capacity, were negative, implying the physically meaningless values. For non-linear equation, it is observed that there is a large difference between experimental data and calculated data according to the equation. These facts declare the inappropriately of the PSO to expound the kinetic regarding the TN removal by electrocoagulation. Better results were attained from PFO (Fig. 4f). R2 (0.9997) value of PFO is too close to unity, and also error function values including Δq (%) , SAE, ARED, and χ 2 were 1.7, 48.84, 3.11, and 4.33, respectively, owned acceptable values. Furthermore, the values of equilibrium concentration and apparent rate constant were found to be 163.91 mg/L and 0.0113 min−1, respectively, which are in strong conformation with experimental data after 150 min of electrocoagulation treatment.

[TN ]0

The kinetic parameters of first-order and second-order models with R2 values are given in Table 1. At current density, the R2 values of second-order model were greater than first-order model, and of course they are more than 0.94 and close to unity. Hence, second order is capable of describing removal rate of TN. By comparing the calculated K2 values, it is obvious that the highest rate constant is pertaining to current density of 0.9A, similarly exhibited the highest removal efficiency. At low agitation speed, it seems that second order governs the removal mechanism; however, at higher rates first order model acts the most important role. Thus, a combination of first-order and secondorder control the removal efficiency. As was shown that among various agitation speeds the most perfect efficiency was for 300 rpm, equivalently 300 rpm has the greatest K2 value.

Parameters

1 + qe t

In terms of linear form, the model could be linearized to four models as follows (Eqs. (20)–(23)):

where TN0 refers the initial effluent TN and TNt refers the effluent TN at time t. K1, the reaction rate constant, can be estimated from the plot [TN ] log [TN ]t versus electrolysis time. 0 On the other hand, if the first order model cannot describe the removal mechanism, the second order model needs studying. Similarly, the second order model is obtained as (Eq. (16)):

[TN ]t

qe2 Kt

(15)

1 1 = + K2 t [TN ]t [TN ]0

(18)

Where K (g/mg min) is PSO rate constant of adsorption, qe and qt (mg/ g) are named the adsorption capacity at time of equilibrium and t. Integrating the above equation with applying border conditions t = 0 and t = t, qt = 0and qt=qt, gives (Eq. (19)) [70]:

The integration of Eq. (14) called as the first order model yields (Eq. (15)) [65]:

log

(17)

where K app is the apparent PFO rate constant in min−1 and Ce is the equilibrium concentration. The ability of the PSO model for entire sorption period for most of the adsorption systems is one the greatest advantage of the model in compared to the others [47,67–69]. The PSO is expressed as (Eq. (18)):

3.8.1. Two parameter isotherms Langmuir model was firstly utilized to describe gas-solid phase adsorption onto activated carbon, and due to some of its intrinsic 7

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Fig. 4. (a, b, c, d) linear and (e) non-linear plot of PSO (e) non-linear plot of PFO.

limitations, it is mostly suitable for bio-sorbents [72]. Based on the fundamental assumptions, the empirical model is valid for a monolayer deposition of adsorbates over a homogeneous surface of adsorbent at a fixed number of sites. Also, there is no lateral interaction between adsorbed pollutant molecules and all molecules possess the same sorption activation energy [73]. The mathematical expression of Langmuir equation is the following (Eq. (24)) [74]:

qe =

qm KL Ce 1 + KL Ce

Model 4:

qe Ce

= qm KL − KL qe (

qe Ce

vs. qe )

(28)

Where Ce (mg/L) is the equilibrium concentration of dye, qe (mg/g) is the equilibrium adsorption capacity, qm (mg/g) is the maximum adsorption capacity of dye on the adsorbents, and KL (L/g) is Langmuir constant. Separation factor (RL) is the dimensionless constant of Langmuir isotherm, proposed by Webber and Chakkravorti to reveal shape of the Langmuir isotherm and represented as (Eq. (29)) [75]:

(24)

RL =

Different types of Langmuir linearizations are possible as follows (Eq. (25)–(28)):

1 1 + KL C0

(29)

Model 1:

Ce C 1 C = e + ( e vs. Ce ) qe qm Qm KL qe

(25)

Favorable adsorption is achieved with lower RL value (Table 2). The Freundlich isotherm is expressed by the following equation (Eq. (30)) [76]:

Model 2:

1 1 1 1 1 1 = + ( vs. ) qe qm Qm KL Ce qe Ce

(26)

qe = KF Ce1/ n

(27)

The equation may be linearized by taking the logarithm of both sides (Eq. (31)) [77]:

Model 3: qe = qm −

q 1 qe (q vs. e ) KL Ce e Ce

8

(30)

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heterogeneous surface with non-linear distribution of adsorption heat. The DR model was firstly proposed by Dubinin to describe subcritical vapors adsorption onto microporous solids based on adsorption potential theory and assumed that the adsorption process was related to micropore volume filling as opposed to layer-by-layer adsorption on pore walls [79,80]. The superiority of this model to Langmuir is that DR model assumes a heterogeneous surface with a Gaussian energy distribution [81]. It can be expressed as (Eq. (32)):

Table 2 RL values and their definitions. RL value

Adsorption type

RL > 1 RL=1 0 < RL < 1 RL=0

unfavorable linear favorable irreversible

lnqe = lnKF +

1 lnCe n

qe = qm exp(−βε 2) (31)

(32)

The linear form could be written as (Eq. (33)):

which produces a straight line with a slope of 1/n and an intercept of ln (KF) when plotting ln (qe) versus ln (Ce). The slope ranges between 0 and 1 is a measure of adsorption intensity or surface heterogeneity, becoming more heterogeneous as its value gets closer to zero [78]. The slope of the plot provides information regarding chemical adsorption 1 1 ( n < 1) , and cooperative adsorption ( n > 1) . The imperfection of the process relates to its limitation of a thermodynamic basis. Freundlich isotherm was the earliest model developed for the adsorbent owning

lnqe = lnqm − βε 2 2

(33) −2

where β (mol kJ ) is a constant related to the adsorption energy; and ε (kJ mol−1) is the desorption potential. Meanwhile, the parameter ε and E can be computed by the relationship (Eq. (34,35)) [82]:

ε = RTln (1 +

1 ) Ce

Fig. 5. (a–d) linear and (e) non-linear plot of Langmuir. 9

(34)

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E=

1 2β

3.8.2. Three-parameter isotherms Redlich–Peterson (R-P) isotherm was initially suggested by Redlich and Peterson in 1959 as a three-parameter isotherm equation, containing some features of Langmuir and Freundlich isotherms [84]. Various papers have reported the validity of R-P isotherm to experimental data than Langmuir or Freundlich isotherms [85–87]. It has a linear dependence on concentration in the numerator and an exponential function in the denominator [85]. The R–P isotherm model can be applied to both homogenous and heterogeneous systems and is expressed as (Eq. (38)):

(35)

T is the temperature (K) and R is the universal gas constant (8.314 J mol−1 K−1). Generally, the adsorption can be classified into two types of sorption according to the interaction between adsorbate and adsorbent. Normally, physisorption involves low energy level, usually no more than 8 Kj mol−1. However, chemisorption occurs once the interaction between adsorbate and adsorbent is due to the electron transfer, consequently, requiring higher sorption energy. Temkin model was initially conceived for the adsorption of hydrogen onto platinum electrodes within the acidic solutions. The model assumes that the heat of adsorption would decline linearly with coverage of the adsorbent surface and it is suitable for common concentrations not extremely high or not extremely low. The coverage of adsorbent surface is dependent on various factors including adsorption energy, the concentration of TN in the solution, and the working temperature [83]. The reduction in energy level is because of the adsorbate and adsorbent interaction. The non-linear and linear Temkin isotherms are given by (Eqs. (36, 37)) [77]:

qe = BT lnAT Ce

(36)

qe = BT lnAT + BT lnCe

(37)

qe =

KR Ce 1 + AR Ceβ

(38)

where KR (L/g) and AR (L/mg) are the R-P constants, while β is the R-P exponent, which lies between 1 and 0. The Sips or Langmuir-Freundlich isotherm is appropriately employed for heterogeneous adsorption, circumventing the drawbacks of Freundlich isotherm. At low adsorbate concentrations, it reduces to Freundlich isotherm; while at high concentrations, it would converted to Langmuir, predicting a monolayer adsorption (Eq. (39)) [88].

qe =

K S Ceβs 1 + αs Ceβs

(39)

where αs and βs represent the adsorption equilibrium constant and the dissociation parameter, respectively. If n = 1, the Sips model reduces to the Langmuir model. Toth isotherm model is a Langmuir-based isotherm derived from potential theory proposed by Toth and suitable for highlighting heterogeneous adsorption systems with submonolayer coverage (Eq. (40)) [89,90].

RT

where AT and BT (= b ) are the Temkin isotherm equilibrium binding T constant (L/g) and Temkin constant related to the heat of adsorption (Jmol-1). The constant parameters can be calculated from the plot of qe versus Ce. Figs. 5 and 6 showed the plots (linear and non-linear) of studied two-parameter isotherms and Table 3 revealed the constants related to each isotherm. In terms of determining the most suitable isotherm, on the one hand, R2 values obtained from linear and non-linear plots were compared. In case of Langmuir, all four linear equations provided negative constant values, indicating that this phenomenon was impossible with no physical meaning. The reason for this phenomenon can be ascribed to the intrinsic error structures combined with transformation of non-linear functions to linear models. By fitting the non-linear equation R2 value of 0.8244 was obtained. For Freundlich, DR, and Temkin, R2 values of linear plots were 0.9513, 0.8938, and 0.8638, and for non-linear plots it was 0.9531, 0.8880, and 0.8638, respectively. It can be deduced that the order of isotherm fitting is as follows:

qe =

qmax Ce 1

(αs + Cem) m

(40)

Fig. 7 showed the plots (non-linear) of studied three-parameter isotherms and Table 3 revealed the constants related to each isotherm. To obtain the best applicable three-isotherm model describing the removal mechanism, it can be noticed that the experimental data matched the considered adsorption isotherms in the following increasing order by intending the R2 value:

Sips (0.952) > R − P (0.850) = Toth (0.850) Comparison of these three-parameter isotherms for fitting TN adsorption equilibrium curves showed Sips model was more suitable for describing the adsorption process, and the adsorption was heterogeneous in nature. Since P-R and Toth exhibited the same R2 value, further optimization was conducted in detail in terms of the other error functions. It expressed that Toth isotherm had a lower error values than R-P (Table 4). Therefore, it can be concluded that the adsorption follows the order of:

Freundlich > DR > Temkin > Langmuir On the other hand, further investigations were conducted through other four error functions to calculate the error deviation between experimental and predicted equilibrium adsorption data. Hence, according to Table 4, it seems that Freundlich isotherm is the most suitable model to satisfactorily describe the studied the TN removal by electrocoagulation. The claim was due to the lowest Δq (%) , SAE, and ARED values calculated in compared to DR, Temkin, and Langmuir for non-linear regression analysis. Moreover, the highest χ 2 value was achieved by Langmuir isotherm, showing the inapplicability of the present isotherm to describe the removal process. The Freundlich isotherm exhibited lower χ 2 value than Temkin and DR, which was considered to be a better fit. In the case of error functions, the order of isotherm fitting is as follows:

Sips > Toth > R − P By comparing the two and three parameter isotherm, it could virtually deduced that Sips isotherm and Freundlich isotherm were found to be the best model to represent equilibrium data, indicating that the adsorption was heterogeneous and virtually could be assumed a quasiGaussienne distribution energy owing to the high correlation coefficients. Similar results have been reported in previous studies. Removal of oxytetracycline hydrochloride as a pharmaceutical drug from aqueous solution was studied, and and it was declared that the Sips isotherm was the best model [82]. In another study regarding tetracycline removal, it was found that the Sips isotherm matched satisfactorily experimental data [88]. Also, Sips was the dominant in another investigation concerning defluoridation of drinking water by electrocoagulation [91]. Furthermore, removal of basic dye rhodamine B from aqueous solution by electrocoagulation was studied and it was found

Freundlich > DR > Temkin > Langmuir In conclusion, it can be inferred that Freundlich isotherm was the most appropriate model for TN removal by electrocoagulation process. The value 1/n was upper than 1, declaring that the adsorption process was the cooperative process, involving multiple mechanisms as alluded to by the S-type isotherm pattern. 10

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Fig. 6. Linear and non-linear plots of (a, b) Langmuir, (c, d) DR, and (e, f) Temkin. Table 3 Non-linear isotherms constants.

Table 4 Error values obtained from non-linear isotherm models.

Non-linear isotherm constants Langmuir Freundlich DR Temkin R-P

Sips

Toth

qm KL n KL qm B BT AT KR Ar B KS BS as qmax as m

45997.9 0.00012 0.652 0.1777 3.44E+128 4.84E-05 0.174024 0.00449 5.4236 0.0577 0.001 0.1539 1.562 0.00088 6.04079 10870.8 55.845

Error Functions

Δq (%)

SAE

ARED

Chi-square

Langmuir Freundlich DR Temkin P-R Sips Toth

19.8208 12.2937 14.9212 19.277 18.1901 12.3924 17.9665

2007.89 893.056 1591.409 1794.18 1858.77 902.614 1845.62

17.1764 8.14256 13.0154 15.7953 15.7907 8.2436 15.5804

354.13 120.926 215.925 331.902 298.814 122.924 297.874

that the data fitted well with Sips isotherm model [92].

3.9. Removal mechanism For TN removal from actual AD effluent by electrocoagulation, various parameters including electrolysis time, current density, interelectrode distance, electrode material, agitation speed, and punched electrode were studied. TN is comprised of four different species: 11

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Fig. 7. Non-linear plots of (a) R-P (b) Sips, and (c) Toth.

(Eq. (48)) [53].

Organic nitrogen, ammonium, nitrite, and nitrate. In the case of AD effluent, ammonium nitrogen is the most abundant one, due to the fact that in AD reactor long retention time is applied and the resistant nitrogen-compounds degrade to ammonium ions. However, it is true that not all the compounds are degraded. Considering the fact that various studies have claimed the complex removal pathway of nitrogen in electrochemical processes, the proposed mechanisms are divided in sections as follow:

Fe (OH )3 + NO3−/NO2− → [Fe (OH )3. NO3−/NO2−]

1) Also, some of the generated light flocs may collide with H2 bubbles and floated on the surface of solution. Hence, removal of nitrate/ nitrite is achieved as the floc-foam layer (Eq. (49)).

Light Flocs + H2 → Floated Flocs containing nitrate /nitrite

1) Chloride ions naturally exist in wastewater. By applying electricity to wastewater, chlorine gas is generated in the solution as shown (Eq. (41)) [51,93]:

2Cl− → Cl2 + 2e−

Then chlorine gas is hydrolyzed and hypochlorous acid and hypochlorite ion are formed, depending on the pH of the solution (Eq. (42)).

4. Conclusion

(42)

This study is the first investigation of the electrocoagulation process for nitrogen removal with high concentrations (approximately 900 mg/ L) from anaerobic digester effluent. The effects of operating parameters were studied and optimized. It was found that higher removal efficiency was achieved by increasing the electrocoagulation time and the maximum removal efficiency (70%) at time of 160 min. In all experiments, the initial pH of the wastewater was roughly neutral. Since the current density directly influences the amount of anode dissociation, higher TN removal was obtained at 0.9 A than 0.3 A. It must be noted that energy consumption at 0.9A was approximately 3.9 times higher than that at 0.3A. Hence, a logical trade-off between energy consumption and removal efficiency must be considered. It was shown that the better removal was observed at inter-electrode distance of 3 cm, and while the distance was increased, removal efficiency decreased and energy consumption increased. Furthermore, the Fe/Al combination revealed the highest efficiency (53.4%) as compared to Al/Al, Fe/Fe, and Al/Fe. The obtained results exhibited that the punched electrode (80.11%) had enhanced efficiency as compared to plane electrode (72.11%). As it was expected, once the solution was agitated removal efficiency was improved because of the fact that greater mass transfer was attained. In terms of kinetics modeling, removal and adsorption pathway were examined. High R2 value of second order rate showed its capability to describe removal rate of TN. In the case of adsorption kinetics,

These two ions have high oxidative potentials and are capable of indirectly oxidizing the ammonium into nitrogen gas (Eq. (43,44)) [94].

2NH4+ + 3HOCl → N2 + 3H2 O + 5H+ + 3Cl−

(43)

2NH4+ + 2OCl− → N2 + 2HCl + 2H2 O + 2H+

(44)

1) Nitrogen in the form of nitrate can be reduced to nitrogen gas and ammonia in the vicinity of cathode. The following equations are an illustration of this phenomenon (Eq. (45)–(47)) [95,96] :

NO3− + 3H2 O + 5e →

1 N2 + 6OH− 2

(45)

NO2− + 2H2 O + 3e →

1 N2 + 4OH− 2

(46)

2NO2−

+ 5H2 O + 6e → NH3 +

7OH−

(49)

1) According to the predominance-zone diagrams of iron anode, at pH greater than 9.6, Fe (OH )−4 is produced, enabling to provide an electrostatic attraction force with positive N species [97]. The negatively charged surfaces can provide the driving force for electrostatic interaction with positive species [98].

(41)

Cl2 + H2 O → HOCl + H+ + Cl−

(48)

(47)

The generated ammonium again experience further oxidation to convert into nitrogen gas. 1) Furthermore, by dissociation of anode electrode and hydrolysis of iron ions, hydroxo-amorphous polymeric complexes are generated acting like an adsorbent to adsorb nitrite and nitrate ions. After the adsorption was completed, precipitation of the flocs was observed 12

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PFO and PSO were tested and the results showed the suitability of PFO due to acceptable values of R2 (close to unity 0.9997) as well as the calculated error functions. In the case of isotherms modeling, linear and non-linear two and three parameter-isotherms were intended. Freundlich and Sips were the best isotherms for two and three parameters models among the others, respectively. It can be concluded that the removal pathway of TN is combined of a physical and chemical combination and a cooperative process. Hence, the obtained results in the present study declare that the electrocoagulation of anaerobic digester effluent might be a promising technique in terms of nitrogen removal.

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