Accepted Manuscript Title: Terephthalic acid removal from aqueous solution by electrocoagulation and electro-Fenton methods: process optimization through response surface methodology Authors: Vishal Kumar Sandhwar, Basheshwar Prasad PII: DOI: Reference:
S0957-5820(17)30056-3 http://dx.doi.org/doi:10.1016/j.psep.2017.02.014 PSEP 981
To appear in:
Process Safety and Environment Protection
Received date: Revised date: Accepted date:
24-11-2016 12-2-2017 16-2-2017
Please cite this article as: Sandhwar, Vishal Kumar, Prasad, Basheshwar, Terephthalic acid removal from aqueous solution by electrocoagulation and electro-Fenton methods: process optimization through response surface methodology.Process Safety and Environment Protection http://dx.doi.org/10.1016/j.psep.2017.02.014 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Terephthalic acid removal from aqueous solution by electrocoagulation and electro-Fenton methods: process optimization through response surface methodology Vishal Kumar Sandhwar*, Basheshwar Prasad Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India
Graphical abstract
Highlights
Removal of terephthalic acid was found maximum in EF treatment.
Closeness of experimental and CCD predicted results indicates good model adequacy.
Energy consumption was minimum in case of EF treatment at optimum conditions.
Operating cost during EF treatment was lower than EC treatment at optimum conditions.
Amount of generated sludge was higher in EC treatment.
Abstract The present work deals with the treatment of terephthalic acid (TPA) and chemical oxygen demand (COD) from synthetic aqueous solution. Initially the aqueous solution was treated by acid precipitation at different pH (2-5) and temperature (15-60 oC). Approximately 87.1% of TPA and 68.85% of COD were removed by acid precipitation treatment at optimum conditions. After acid precipitation, the filtered supernatant was further treated by electrocoagulation (EC) and electro-Fenton (EF) techniques separately. Operating parameters viz. pH- (4-12), current density (A/m2)- (15.24-45.72), Na2SO4 concentration (mol/L)- (0.02-0.04) and time (min)- (1070) for EC treatment and pH- (1-5), current density (A/m2)- (15.24-45.72), H2O2 concentration (mg/L)- (50-250) and time (min)- (10-70) for EF treatment were optimized and modeled by Central Composite Design (CCD) in Response Surface Methodology (RSM). Maximum removal of TPA- 82.76%, 91.87% COD – 79.56%, 89.68% with electrical energy consumption (kWh/kg COD removed) – 22.65, 18.11 were obtained through EC and EF treatment respectively at
optimum conditions. Sludge generated at optimum conditions via electrochemical treatments was characterized by FTIR, XRD, SEM/EDX and TGA/DTA techniques. Keywords: Terephthalic acid; Electrocoagulation, Electro-Fenton; Graphite cathode; Sludge analysis *Corresponding author Tel: +91- 8307070357; E-mail:
[email protected]
1. Introduction Purified terephthalic acid (PTA) is a petrochemical product manufactured by oxidation of paraxylene. It is widely applicable for the production of plastic bottles, pesticides, polyester films, textile fibers and dyes (Wittcoff et al., 2004; Kleerebezem et al., 2005). Approximately 3-10 m3 of wastewater gets generated per tonne of PTA which contains various toxic aromatic compounds and 5-20 kg of COD/m3 (Macarie and Guyot, 1992; USEPA, 2010; Kleerebezem et al., 1999). Terephthalic acid (TPA) is one of the major aromatic compounds present in PTA wastewater with very high concentration (Karthik et al., 2008). It is used as an intermediate for the manufacturing of polyesters, clamshell, pesticides, adhesive, bio-plastics, poultry feed additives, synthetic perfumes and many other chemical compounds (Stales et al., 1997; Kleerebezem and Lettinga, 2000; Moraes et al., 2004; Jang et al., 2013). Intake in higher dosage of TPA causes acute toxicity, chronic toxicity, molecular toxicity, damage of bladder, liver, kidneys and histopathological abnormalities in human beings due to its high toxicity (Zhang et al., 2010; Meyer et al., 1984; Cui et al., 2006; Cui et al., 2004; Lamb et al., 1987). United States Environmental Protection Agency (USEPA) added TPA in priority pollutants list because of its hazardous nature (Shirota et al., 2008; Wu, 2007; US EPA, 1992). There is no specific discharge limit for TPA, prescribed by pollution regulating bodies in India. Central Pollution Control
Board (CPCB) of India has proposed the permissible discharge limit of COD (< 250 mg/L) for the petrochemical wastewater into surface waters (CPCB, 2012). Various physico-chemical and bioremediation techniques have been employed for the treatment of PTA wastewater in recent years. But some of these techniques show operational difficulties such as partial degradation of effluents, production of toxic intermediates and high energy consumption. Among these techniques electrochemical technologies appear as a better option due to their higher efficiency, versatility, automation and cost effectiveness. Recently more interest has been shown in development of highly efficient electrochemical techniques for degradation of aromatic compounds present in wastewater (Silva et al., 2013; Canizares et al., 2011; Fu et al., 2010; Sandhwar and Prasad, 2017 ). Electrocoagulation (EC) EC process comprises following serial steps: (i) Electrolytic reactions take place at electrode surfaces (Valero at el., 2008). (ii) In situ oxidation of metal ions and eventual precipitation of metallic hydroxides in the aqueous phase. (iii) Adsorption of dissolved and colloidal pollutants on the surface of coagulants. (iv) Removal of pollutants by sedimentation or flotation (Sayiner et al., 2008). In case of iron anode, the following mechanism has been proposed for the production of metal hydroxides (Sengil and Ozacar, 2006). At anode Fe(s) → Fe2+(aq) + 2e─
(1)
4Fe2+(aq) + 10H2O(l) + O2(aq) → 4Fe(OH)3(s) +8H+(aq)
(2)
At cathode 4H+(aq) +4e─ → 2H2 (g) Overall
(3)
4Fe(s) +10 H2O(l) +O2(aq) → 4Fe(OH)3(s) +4H2 (g)
(4)
Electro-Fenton (EF) EF is one of the most prominent electrochemical advanced oxidation processes as well as an ecofriendly technique for wastewater remediation (Mohajeri et al., 2009). EF process comprises two distinct configurations. Addition of Fenton reagents to reactor from outside in the first configuration while in the second configuration, only hydrogen peroxide (H2O2) is added to reactor from outside and ferrous ions are generated from sacrificial iron anode (Lee and Shoda, 2008). The following reactions indicate EF process (Mohanty and Wei, 1993; Guinea et al., 2008): H2O2 + Fe2+ → Fe3++ OH─+ ●OH
(5)
RH + ●OH → R● + H2O
(6)
Where, RH is organic pollutant R● + Fe3+ → R+ +Fe2+
(7)
Fe2+ + ●OH → Fe3+ + OH─
(8)
In this study, treatment of TPA and COD from aqueous solution was done through acid precipitation followed by electrocoagulation and electro-Fenton techniques using iron anode and graphite cathode. Electrochemical studies were performed by using central composite design (CCD) of response surface methodology (RSM) in Design Expert Software (DES). RSM is an effective tool for the optimization of industrial processes (Virkutyte et al., 2010). Hence to achieve maximal removal of TPA and COD with minimal electrical energy consumption (EEconsumption), RSM was used to optimize various independent parameters viz. pH, current density, electrolyte concentration or H2O2 concentration and reaction time.
2. Materials and methods 2.1 Chemicals All the chemicals used during study were of analytical grade (AR). Sodium sulfate (Na2SO4) was procured from by Loba Chemie Pvt. Ltd. Mumbai (India). TPA was purchased from Himedia Lab Pvt. Ltd. Mumbai (India). Hydrogen peroxide (H2O2) (30% w/v), Sulfuric acid (H2SO4), mercury (II) sulphate (HgSO4), methanol (CH3OH), sodium hydroxide (NaOH), acetic acid (CH3COOH), potassium dichromate (K2Cr2O7), isopropyl alcohol (C3H8O), and silver sulphate (Ag2SO4) were procured from Ranbaxy Fine Chemicals Limited, New Delhi (India). 2.2 Preparation of synthetic wastewater solution and sample analysis Stock solution of TPA (1000 mg/L) was synthetically prepared with distilled water at laboratory. Entire reagents and wastewater samples were preserved at 4 0C to avoid the biodegradation and microorganisms growth. Initial concentration of TPA (400 mg/L) was taken according to previous studies (Marashi et al., 2013; Anand et al., 2014). Initial COD of aqueous solution was found 584 mg/L. Wastewater characteristics viz. pH and COD were determined through the standard methods (APHA, 1995). Concentrations of TPA were analyzed by High Performance Liquid Chromatography (HPLC) (Waters, USA) with UV detector (Waters 2487 absorbance detector, USA) at 240 nm wavelength in C18 column at ambient temperature (Garg et al., 2014; Thiruvenkatachari et al., 2006). Mobile phase solution of 91% milli-pore water, 7% isopropyl alcohol and 2% acetic acid with a flow rate of 1.2 mL/min was used during HPLC analysis (Park et al., 2003). COD value was measured by COD analyzer (Aqualytic, Germany). Removals of TPA and COD were calculated by Eq [9]. % Removal =
𝐶𝑖 −𝐶𝑓 𝐶𝑖
× 100
(9)
Where Ci – Initial concentration, Cf - Final concentration Energy consumption during electrochemical treatment was estimated by Eq [10]. V×I×T×100
EEconsumption (kWh/kgCODremoved) = (% Removal of COD)C
CODi ×VS
× 1000
(10)
Where V, I, T, CCODi and VS are voltage (volt), current (amp), time (hour), initial COD (mg/L) and volume of aqueous solution (liter) respectively. 3. Experimental procedure Acid precipitation treatment was performed in a 1 liter glass beaker by addition of sulfuric acid (1N) to the aqueous solution at different pH (2-5) and temperature (15-60 oC). Precipitated solution was then allowed to settle for 4 hours. After settling, the supernatant was filtered through Whatman filter paper (̴ 11-μm) and further treated by EC and EF methods separately. Both electrochemical experiments were performed in a rectangular open batch cell of 1.6 liter capacity. Iron anode (100 mm×80 mm×1mm) and graphite cathode (100 mm×80 mm×3 mm) with an effective electrode area of 131.2 cm2 were used during EC and EF treatment of 1 liter of solution. Distance between parallel electrodes was kept 2 cm. The schematic diagram of electrochemical setup is shown in Fig. 1. Electrodes were cleaned first with H2SO4 solution (5% v/v) and subsequently washed with distilled water after each successive run. Direct current (0-4 A) and voltage (0-35 V) were used to power the parallel electrodes. Entire electrochemical studies were performed at room temperature (25 ± 2 0C) and atmospheric pressure. Initially, some random runs were performed to determine the operating parameters range in both the electrochemical treatments. Table 1 and 2 indicate operating parameters range for EC and EF processes respectively. EC and EF experiments were performed at operating conditions predicted by RSM as shown in Table 3 and 4 respectively.
4. Results and discussion 4.1 Effect of acid precipitation on removal of TPA and COD TPA remains in ionized state in the aqueous solution, as the pKa values for TPA are 3.51 and 4.82. The solubility product constant (Ksp) and the ionic product value for TPA are 5.8 × 10 −9 and 2.9 ± 0.9 × 10−4 respectively (Thamer and Voigt 1952). Reduction of solution pH by mixing of 1N H2SO4 solution enhances hydrogen ions concentration in the solution which favors conversion of dissociated acid ions to undissociated acid molecules (Verma et al., 2014). Eventually the ionic product value of TPA surpass its solubility product value due to commonion effect (hydrogen ions) resulting in the precipitation of acid. Acid precipitation treatment was performed at different pH (2-5) and temperature (15–60°C) as shown in Fig. 2(a & b). 87.1% of TPA and 68.85% of COD were removed by acid precipitation at optimum conditions (pH- 2 and temperature- 15 oC). Finally the supernatant was having new concentrations of TPA- 51.6 mg/L and COD- 182.21 mg/L and was further treated by EC and EF techniques. 4.2 Effect of pH on removal of TPA and COD pH is an effective operating parameter during electrochemical treatment. Effect of pH on percent removal of TPA, COD and Electrical Energy consumption are shown in Figs. 3(a, c & e) and Figs.4 (a, c & e) for EC and EF processes respectively. At low pH hydroxides of metal ions found in dissolved form resulting in lower removal. Concentration of metal hydroxides increases with pH which favors higher removal. Removal decreases beyond optimum pH (7.44) as shown in Fig. 3(a & c). This is due to the weak interaction among metal hydroxide ions and suspension of impurities at high pH (Kushwaha et al., 2010). In EF, removal of TPA and COD was higher in
acidic condition as shown in Fig. 4(a & c). Acidic medium favors formation of hydroxide radicals (●OH) from H2O2 during EF treatment as given in Eq [5] resulting higher removal (Kallel et al., 2009; Watts et al., 1999). At very low pH, formation of oxonium ions (H3O2+) takes place (Zhou et al., 2007) and at high pH decomposition of H2O2 into water and oxygen occurs resulting in lower removals. 4.3 Effect of current density and time on removal of TPA and COD Removal efficiency and EEconsumption during electrochemical treatments strongly depend on current density and electrolysis time. Various current densities (15.25- 45.72 A/m2) and time (1070 minutes) were studied during EC and EF treatments. High current density favors generation of more amounts of charges during electrochemical treatment resulting higher removal. Beyond optimum current density i.e. 32.71 A/m2 for EC and 27.89 A/m2 for EF, removal efficiencies decrease due to high consumption of charges by some side reactions and ineffectiveness of electrodes due to corrosion. In addition, higher current density causes rise in solution temperature and more energy consumption (Pennizza and Cerisola, 2007; Pennizza and Cerisola, 2008). Concentration of metal ions and ●OH also increases with reaction time. Beyond optimum values of reaction time (i.e. 43.49 min for EC and 38.55 min for EF) removal efficiency decreases due to insufficient formation of metal ions and ●OH into solution. Effect of current density and time on percent removal of TPA and COD are shown in Figs. 3(a-f) and Figs.4 (a-f) by EC and EF processes respectively. 4.4 Effect of Na2SO4 and H2O2 concentration on removal of TPA and COD Supporting electrolyte plays a vital role during electrochemical treatment. It is used for the enhancement of conductivity and electron transfer rate during electrolysis. In EC study, various concentrations of sodium sulfate were used as a supporting electrolyte and an optimum value
(0.04 mol/L) as shown in Figs 3(b, d & f) was obtained. The same optimum amount (0.04 mol/L) of electrolyte was used in EF treatment. To achieve maximum removal efficiency during EF treatment, it is necessary to determine an optimum amount of H2O2. Based on solution COD (after acid precipitation treatment) i.e. 182.21 mg/L, theoretical amount of H2O2 required to provide oxygen (O2) for oxidation was calculated and accordingly different amounts of H2O2 (50-250 mg/L) were fed to reactor before supply of electrical current. It was observed that beyond optimum concentration of H2O2 (142.7 mg/L) removal decreased due to presence of excess amount of H2O2 that favors scavenging effect on ●OH as shown below (Mohajeri et al., 2009; Lee and Shoda, 2008). H2O2 + ●OH → HO2● +H2O
(11)
4.5 Effect of pH, current density, Na2SO4 and H2O2 concentration and time on EEconsumption Energy consumption strongly depends on current density, time and COD removal as can be seen in Eq [10]. Initially, EEconsumption was high due to low COD removal at a particular current density. At optimum operating conditions (i.e. at pH- 7.44, CD- 32.71 A/m2, Na2SO4 concentration- 0.04 mol/L, time- 43.49 min for EC and at pH- 3.20, CD- 27.89 A/m2, H2O2 concentration -142.7 mg/L, time- 38.55 min for EF), EEconsumption was minimum in both electrochemical processes due to optimum current density value, time and high COD removal as shown in Figs. 3(e & f) and 4(e & f). Beyond optimum conditions, EEconsumption was increased because of high current density, longer time and low COD removal. 5. RSM study 5.1 Optimization
Both EC and EF processes were optimized to get maximum removal of TPA and COD with minimum electrical energy consumption based on CCD results. All the operating conditions as well as their experimental run and CCD results are given in Table 3 and 4. The optimized results are shown in Table 5. Closeness of experimental results and CCD predicted values shows good adequacy of the model. 5.2 Model equations based on ANOVA analysis In this study second-order polynomial regression model equations were used to show correlations between responses and independent variables. Generalized equation: Ri = b0 + b1×pH + b2 × CD + b3 × Ci + b4 ×t + b11 × pH2 + b22 × CD2 + b33 × Ci2 + b44 × t2 + b12 × pH × CD + b13 × pH × Ci + b14 × pH × t + b23 × CD × Ci + b24 × CD × t + b34 × Ci × t
(12)
TPA REC = 70.17 + 2.42×pH +5.29×CD + 1.51×C1 + 2.49×t – 5.43×pH2 – 3.48×CD2 – 3.01×C12 – 4.27×t2 – 2.46×pH×CD – 0.50×pH×C1 –2.60×pH×t – 3.63×CD×C1 –1.60×CD×t + 3.02×C1×t (13) REF = 80.33+ 2.47×pH +4.59×CD + 1.30×C2 + 2.49×t – 6.08×pH2 – 3.01 ×CD2 – 2.71×C22 – 3.93×t2 – 2.81×pH×CD – 0.69×pH×C2 –2.25×pH×t – 2.48×CD×C2 –1.31×CD×t + 2.67×C2×t (14) COD REC = 67.53 + 2.13×pH +3.23×CD + 1.50×C1 + 3.89×t – 7.02×pH2 – 2.54×CD2 – 4.09×C12 – 4.05×t2 – 2.92×pH×CD + 0.06×pH×C1 –2.33×pH×t – 1.61×CD×C1 –2.69×CD×t + 2.63×C1×t
(15) REF = 71.74 - 0.55×pH +4.13×CD + 1.31×C2 + 3.12×t – 7.66×pH2 – 1.57×CD2 –1.65×C22 – 1.94×t2 – 4.14×pH×CD + 0.05×pH×C2 –0.55×pH×t – 1.17×CD×C2 –1.46×CD×t+1.95×C2×t (16) EEconsumption REC = 17.36 – 0.71×pH +6.57×CD – 0.63×C1 + 7.78×t + 3.09×pH2 + 1.08×CD2 +1.60×C12 + 0.82×t2+1.38×pH×CD+0.23×pH×C1+ 1.49×pH×t +1.00×CD×C1 +3.11×CD×t – 1.10×C1×t (17) REF = 17.18 +0.62×pH + 5.81×CD – 0.32×C2+ 6.49×t + 2.74×pH2 +0.23×CD2 +0.28×C220.27×t2+1.50×pH×CD+0.03×pH×C2 +0.18×pH×t + 0.07CD×C2+2.50×CD×t – 0.30×C2×t (18) Where R- Response, C1- Electrolyte concentration, C2- H2O2 concentration, CD- Current density, t-Time 6. Sludge analyses Sludge obtained by electrochemical treatments at optimum conditions was characterized by following techniques. 6.1 . Settling & sludge volume index, point of zero charge (PZC) and FTIR Settling & sludge volume index (SVI) - Settling experiments of sludge were performed in a glass cylinder having one liter capacity based on standard method (APHA, 1995). Fig. 5(a) shows settling characteristics of EC and EF generated sludge. Initially, level of sludge
supernatant interface was 8.5 cm and 8 cm for EC and EF generated sludge respectively. After 10 min, level was 5.2 cm for EC generated sludge and 4.9 cm for EF generated sludge. Finally after 90 min and 70 min, settling was found constant at 1.5 cm and 1.4 cm for EC and EF generated sludge respectively. The above results represent better settling characteristics by EF produced sludge than EC sludge. SVI of EC generated sludge (44.15 mL/g) was higher in comparison of EF generated sludge (32.97 mL/g). PZC- It is the pH value where a solid submerged in electrolyte exhibits zero net charge at solid surface (Song et al., 2005). Fig. 5(b) indicates PZC values of sludge obtained by EC and EF treatments at optimum operating conditions. To determine PZC values, salt addition method recommended by American Society for Testing of Materials (ASTM) D-3838-05 was used (ASTM, 2011). An intersection point on the curve plotted between ∆pH [∆pH= pH0 (Initial pH) pHf (Final pH)] and pH0 at ∆pH= 0 gives PZC value. PZC values are found 7.33 and 6.5 for EC and EF generated sludge respectively. FTIR- It recognizes different kinds of functional groups present in sample and also informs about surface chemistry of sample. Functional groups present in sludge samples favors electrolyte interaction of cations and flocs resulting removal of colloidal particles during treatment. In the present spectra broad and intense band 3203 cm-1, 3232 cm-1 shows stretching vibrations of hydroxyl group (OH) and hydrogen ring characteristics. Wavelength lies in the region of 1147–1550 cm-1 and 1600–400 cm- 1 shows the presence of carbonyl group (C=O) and aromatic C=C stretching (Anand et al., 2014) 6.2. XRD, SEM/EDX, TGA/DTA XRD- XRD spectra of sludge obtained after electrochemical treatments are shown in Fig. 5(d). Sludge obtained at optimum conditions was dried at 105 oC and analyzed by Braker AXS D8
advance X-ray diffractometer having wavelength 1. 54439Å. The angle (2ɵ) was taken in the range of 5-90o. Spectra with broad and shallow diffraction peaks shows crystalline nature and broad and lower intensity peak indicates analyzed phase (Garg and Prasad, 2015). In the present study EC generated sludge having more sharp peaks than EF generated sludge indicating poor crystalline nature. SEM/EDX- Fig. 5(e & f) show high magnification images of sludge obtained after EC and EF treatments respectively. SEM analysis informs about the surface structure i.e. either crystalline or amorphous. Sludge obtained by EC and EF treatments was dried at 105 oC and then SEM/EDX analysis was performed. EF generated sludge was found much porous than EC generated sludge. It shows that the particle sizes of EF sludge are smaller than EC sludge. Elemental composition of EC and EF generated sludge was performed by EDX as given in Table 6. EDX analysis of both EC and EF generated sludge shows higher weight percent of Fe in comparison of carbon, oxygen, sodium and sulfur. DTA/TGA- DTA/TGA curves of EC and EF generated sludge are shown in Fig. 5(g) & (h) respectively. The air flushing rate of 200 mL/min was maintained during DTA/TGA analyses. Sludge samples were heated from 35 oC to 1200 oC with 10 K/min heating rate. TGA analysis of EF generated sludge indicates higher oxidation capacity than EC generated sludge. TGA graphs shows that the percentage weight loss of EC generated sludge was higher than EF sludge due to formation of CO2 and CO during reaction. Reduction in weights was approximately 2.29 % and 1.47 % for EC and EF generated sludge respectively below 200 oC. This is because of incomplete evaporation of pore solution at ambient temperature (Garg and Prasad, 2015). DTA graph of EC generated sludge show endothermic characteristics at 907 oC with 59.6 mJ/mg of
heat requirement where DTG analysis of EF generated sludge shows maximum rate of weight loss is 0.049 mg/min at 256 oC. 7. Operating cost The operating cost during EC and EF treatments at optimum conditions was determined by following equation. Operating cost = EEconsumption (kWh/kgCODremoved) × EEC + Electrode consumption (kg/kgCODremoved) × ELC + H2O2 (kg/kgCODremoved) × HC
(19)
Where, EEC- Electrical energy cost (Rs. 5.75/kWh), ELC- Electrode cost (Rs. 55/kg for Fe electrode), HC- H2O2 cost (Rs. 22/kg (30% w/v)). It was observed that operating cost for EF treatment at optimum operating condition is lower than EC treatment due to lower consumption of electricity and electrode material as given in Table 7. 8. Conclusion In the present study EC and EF processes are investigated for the removal of TPA, COD and EEconsumption. Prior to EC and EF treatments, acid precipitation was carried out at different pH and temperature. A maximum removal of 87.1% of TPA and 68.8% of COD at pH- 2 and temperature- 15 oC was obtained. The supernatant was further treated by electrochemical techniques and achieved maximum removal of TPA- 82.76 % and COD- 79.56% with EEconsumption (kWh/kg CODremoved)- 22.65 at pH- 7.44, CD- 32.71 A/m2, Na2SO4 concentration0.04 mol/L, time- 43.49 min and TPA- 91.87% and COD- 89.68% with EEconsumption (kWh/kg CODremoved)- 18.11 at pH- 3.20, CD- 27.89 A/m2, H2O2 concentration -142.7 mg/L, time- 38.55 min by EC and EF methods respectively. It was observed that CCD developed model indicates high correlation between model and actual values of responses. The sludge analyses revealed that
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Fig. 1: Schematic diagram of experimental setup for electrochemical treatment.
90 o 15 C o 30 C o 45 C o 60 C
% Removal of TPA
80
70
60
50
40 2
3
4
5
pH
Fig. 2(a) 80 o 15 C o 30 C o 45 C o 60 C
% Removal of COD
70
60
50
40
30
20 2
3
4
5
pH
Fig. 2(b) Fig. 2. Effect of pH at different temperatures in acid precipitation process (a) on removal of TPA (b) on removal of COD .
3(a)
3(d)
3(b)
3(e)
3 (c)
3 (f)
Fig. 3 Effects of pH, CD, time and Na2SO4 concentration on percentage removal of TPA, COD and EEconsumption for EC.
4(a)
4(d)
4(b)
4(e)
4(c)
4(f)
Fig. 4 Effects of pH, CD, time and H2O2 concentration on percentage removal of TPA, COD and EEconsumption for EF.
0.6
Difference (Initial pH - Final pH)
10
Sludge height (cm)
8
EC EF
6
4
2
EC EF
0.4
0.2
7.33 0.0
6.5 -0.2
-0.4
-0.6
0 0
20
40
60
80
2
100
4
6
8
10
Initial pH (pH0)
Time (min)
Fig. 5(a)
Fig. 5(b)
1200
100 1000
EF EC 800
60
EC EF
40
Intensity
% Transmittance
80
600
400
20 200
0 0
0
500 1000 1500 2000 2500 3000 3500 4000 4500 -1
Wavenumber (cm )
Fig. 5(c)
0
20
40
2 Theta
Fig. 5(d)
60
80
100
12
Fig. 5(e)
Fig. 5(f)
200.0
285 Cel 47 ug/min
50 106.0
0
103.0
100.0 50.0 59.6 mJ/mg
-50.0 99.8 Cel 98.61 % -100.0
-200
DTA uV
-150 100.0
100.0
200 Cel 98.53 %
-100.0 100 Cel 99.26 %
98.0
99.0 -250 300 Cel 95.51 %
98.0
299 Cel 96.97 %401 Cel 500 Cel 600 Cel 700 Cel 1000 Cel1100 Cel 96.74 %96.71 %96.74 %96.71 %800 Cel 900 Cel 96.52 %96.58 %96.62 %96.54 %
-150.0
-300
-10
-15
-200.0 200 Cel 97.71 %
-50
33 Cel 100.00 % DTG ug/min
907 Cel -2.9 uV
TG %
DTA uV
26.1 Cel 99.98 %
102.0
0.0
-100 101.0
0.0
0
104.0
-50
102.0
TG %
100.0
108.0
256 Cel 49 ug/min
50
104.0
-300.0
97.0
400 Cel 500 Cel 600 Cel 94.29 %94.10 % 93.99 %700 Cel 93.64 %800 Cel 900 Cel 1000 Cel 93.18 % 92.96 % 92.68 %1100 Cel 91.99 %
-350
96.0
-20 94.0
92.0
-25
-400.0
-200.0
96.0
1213 Cel 95.61 % 200
400
600 Temp Cel
Fig. 5 (g)
800
1000
1212 Cel 89.92 %
-400
1200
200
400
600 Temp Cel
800
1000
Fig. 5(h)
Fig. 5 (a) Settling characteristics (b) Point of zero charge (c) FTIR spectra (d) XRD spectra (e & f) SEM images (g & h) DTA/TGA graphs obtained of EC and EF generated sludge.
90.0
1200
-30
Table 1: Operating parameters and their levels obtained from the statistical software for EC process. Central Composite Design characteristics Levels
Parameter (Range) X1 pH
X2 CD (A/m2)
X3 Na2SO4 concentration 𝑚𝑜𝑙
(
𝐿
X4 Time (min)
)
-2(-α)
4
15.24
0.02
10
-1
6
22.86
0.03
25
0
8
30.48
0.04
40
+1
10
38.10
0.05
55
+2(α)
12
45.72
0.06
70
Table 2: Operating parameters and their levels obtained from the statistical software for EF process. Central Composite Design characteristics Levels
Parameter (Range) X1 pH
X2 CD (A/m2)
X3 H2O2 concentration 𝑚𝑔 (𝐿)
X4 Time (min)
-2(-α)
1
15.24
50
10
-1
2
22.86
100
25
0
3
30.48
150
40
+1
4
38.10
200
55
+2(α)
5
45.72
250
70
Table 3: Actual and CCD predicted removal efficiencies of TPA, COD and EEconsumption for EC process.
Run no. X1: (pH) 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
% Removal of TPA:(R1)
Independent variables
6 10 6 10 6 10 6 10 8 8 6 12 6 10 6 10 6 10 8 8 4 10 8 8 8 8 8 8 8 8
X2: X3: (CD) (Na2SO4) (A/m2) (mol/L) 22.86 0.03 22.86 0.02 38.10 0.05 38.10 0.06 22.86 0.05 22.86 0.05 38.10 0.05 38.10 0.05 30.48 0.04 30.48 0.05 22.86 0.03 22.86 0.03 38.10 0.03 38.10 0.05 22.86 0.05 15.24 0.05 38.10 0.05 38.10 0.05 30.48 0.03 30.48 0.04 30.48 0.04 30.48 0.04 22.86 0.04 38.10 0.04 30.48 0.03 45.72 0.04 30.48 0.04 22.86 0.04 22.86 0.04 38.10 0.03
X4: (t) (min.) 55 25 25 55 25 55 55 25 40 40 25 55 55 10 70 25 40 55 40 55 40 40 40 40 25 40 25 55 25 55
Actual (Exp.)
CCD Predicted
40.91 37.25 51.01 51.78 42.28 59.64 69.24 60.21 70.28 69.12 35.17 37.49 64.54 38.11 56.65 42.81 54.19 53.11 68.65 72.71 41.37 64.35 59.89 77.69 63.92 68.31 66.02 61.17 51.36 58.34
41.81 39.81 51.17 49.24 39.73 62.72 64.19 55.28 70.16 68.66 34.48 33.92 61.39 41.18 56.09 42.48 61.94 57.89 65.64 68.39 43.61 67.15 61.42 76.97 61.91 66.82 63.41 61.23 53.04 64.68
% Removal of COD:(R2) Actual CCD (Exp.) Predicted 37.22 33.62 46.51 47.89 37.26 54.84 64.37 57.01 67.11 63.25 31.48 32.94 60.77 34.44 52.88 39.21 49.84 50.21 62.56 63.34 36.55 60.66 55.65 72.61 60.32 63.66 62.33 57.12 46.74 53.21
44.78 34.06 47.52 44.05 33.07 61.72 59.84 50.71 67.53 64.94 32.21 31.72 54.91 37.07 55.56 38.94 57.73 53.73 61.94 67.37 35.18 62.64 61.77 70.22 56.63 63.84 59.59 64.31 51.13 58.76
EEconsumption (kWh/kg CODremoved) :(R3) Actual CCD (Exp.) Predicted 28.38 14.28 22.12 47.27 12.88 19.26 35.17 18.05 17.44 18.51 15.25 32.07 37.25 11.95 25.42 6.99 33.03 45.09 18.71 25.41 32.03 19.30 13.80 23.99 12.13 34.48 11.74 12.12 10.27 42.54
25.61 14.53 21.72 47.39 15.54 18.96 38.29 20.51 17.36 18.33 17.06 32.36 40.21 11.72 24.25 6.24 29.17 43.07 19.59 25.96 31.14 19.73 11.87 25.01 11.54 34.82 10.41 17.36 8.02 39.04
Table 4: Actual and CCD predicted removal efficiencies of TPA, COD and EEconsumption for EF process.
Run no. X1 (pH) 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
% Removal of TPA:(R1)
Independent variables
2 4 2 4 2 4 2 4 3 3 2 5 2 4 2 4 2 4 3 3 1 4 3 3 3 3 3 3 3 3
X2: (CD) (A/m2) 22.86 22.86 38.10 38.10 22.86 22.86 38.10 38.10 30.48 30.48 22.86 22.86 38.10 38.10 22.86 15.24 38.10 38.10 30.48 30.48 30.48 30.48 22.86 38.10 30.48 45.72 30.48 22.86 22.86 38.10
X3: 𝑚𝑔 H2O2( 𝐿 )
X4: (t) (min.)
100 50 200 250 200 200 200 200 150 200 100 100 100 200 200 200 200 200 100 150 150 150 150 150 100 150 150 150 150 100
55 25 25 55 25 55 55 25 40 40 25 55 55 10 70 25 40 55 40 55 40 40 40 40 25 40 25 55 25 55
Actual (Exp.) 53.66 52.65 64.11 64.91 52.65 69.55 79.25 69.23 78.54 77.32 45.51 48.97 73.11 48.61 65.24 54.82 65.45 63.53 87.26 84.45 49.89 76.65 71.09 81.64 74.22 79.56 78.45 73.18 64.80 69.78
CCD Predicted 53.65 54.77 62.96 61.26 50.49 72.69 75.15 65.41 80.33 78.92 46.87 46.57 70.8 52.05 64.86 54.55 72.98 68.58 86.32 78.88 51.08 76.72 72.73 81.91 72.57 77.49 73.91 72.6 65.03 74.97
% Removal of COD:(R2)
Actual (Exp.) 49.76 46.25 58.88 60.71 48.18 64.55 77.01 64.56 75.32 74.01 41.45 44.12 69.14 43.17 61.37 50.11 60.59 60.1 81.36 76.18 44.52 41.06 67.33 76.64 68.84 75.42 74.17 68.27 60.04 64.67
CCD Predicted 51.97 48.25 63.67 58.86 46.55 66.91 72.01 55.53 71.74 71.41 45.59 37.95 67.93 46.65 61.99 49.96 69.78 61.64 80.78 72.93 42.21 63.54 66.04 74.31 65.67 73.74 66.68 68.69 59.52 70.29
EEconsumption (kWh/kg CODremoved) :(R3) Actual CCD (Exp.) Predicted 21.23 10.38 17.47 37.29 9.96 16.36 29.39 15.94 15.54 15.82 11.58 23.94 32.74 9.53 21.91 5.47 27.17 37.67 15.74 21.13 26.29 28.51 11.41 21.48 10.63 29.10 9.86 15.47 7.99 35.01
19.76 10.22 15.05 37.04 11.29 16.98 32.04 19.02 17.17 17.13 11.55 25.78 33.22 9.36 21.01 5.04 23.81 36.71 17.77 23.39 26.9 20.54 11.59 23.21 10.71 29.7 10.42 15.31 7.34 32.75
Table 5: Optimum-operating conditions predicted by CCD and experimental test run by EC and EF process. pH
CD
Na2SO4
H2O2
Time
(A/m2)
Concn
Concn
(min)
(mol/L)
(mg/L)
% Removal of % Removal of TPA
EEconsumption
COD
(kWh/kg CODremoved)
CCD
Test
CCD
Test
CCD
Test
(Pre.)
Run
(Pre.)
Run
(Pre.)
Run
EC
7.44
32.71
0.04
-
43.49
82.76
79.56
78.33
75.04
22.65
27.86
EF
3.20
27.89
-
142.7
38.55
91.87
89.68
85.11
82.78
18.11
20.75
Table 6: Elemental composition of sludge based on EDX results for both EC and EF processes. Element Weight %
CK
OK
Na K
SK
Fe K
EC (sludge)
8.40
22.91
18.72
16.21
33.76
EF (sludge)
5.32
26.03
20.65
17.56
30.44
Table 7: Operating cost during EC and EF process at optimum operating conditions given by CCD and experimental test runs. Treatment
Electrical energy
Electrode
H2O2
Operating
method
consumed
consumed
consumed
cost ($)
(kWh/kgCODremoved) (kg/kgCODremoved) EC
EF
(kg/kgCODremoved) 1 $ = 66 Rs.
CCD
22.65
2.40
-
3.97
Test run
27.86
2.58
-
4.57
CCD
18.11
1.30
0.92
3.84
Test run
20.75
1.37
0.95
4.16
32