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An efficient wastewater treatment approach for a real woolen textile industry using a chemical assisted NF membrane process
Accepted Manuscript Title: An efficient wastewater treatment approach for a real woolen textile industry using a chemical assisted NF membrane process Authors: E. Hassanzadeh, M. Farhadian, A. Razmjou, N. Askari PII: DOI: Reference:
S2215-1532(17)30005-3 http://dx.doi.org/doi:10.1016/j.enmm.2017.06.001 ENMM 93
To appear in: Received date: Revised date: Accepted date:
8-1-2017 31-5-2017 6-6-2017
Please cite this article as: E.Hassanzadeh, M.Farhadian, A.Razmjou, N.Askari, An efficient wastewater treatment approach for a real woolen textile industry using a chemical assisted NF membrane process, Environmental Nanotechnology, Monitoring and Managementhttp://dx.doi.org/10.1016/j.enmm.2017.06.001 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.
An efficient wastewater treatment approach for a real woolen textile industry using a chemical assisted NF membrane process E. Hassanzadeh1,2, M. Farhadian3*, A. Razmjou4, N. Askari3 1
Environmental Engineering Department, Faculty of Agriculture, Islamic Azad University Bandar Abbas Branch, Iran 2
Water and Environmental Group, Isfahan High Education and Research Institute, Isfahan, Iran
3*
Chemical Engineering Department, Faculty of Engineering, University of Isfahan, Isfahan, Iran
4Department
of Biotechnology, Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran
3
* E-mail: [email protected]
Highlights: - NF process at optimum conditions and after chemical pretreatment has an effective efficiency for real woolen textile wastewater treatment. - The results showed that the best conditions for the pretreatment process were pH of 8, FeSO4 of 600 mg/L. - For the NF process, by increasing pH and pressure, removal efficiency of turbidity and COD increased up to 98%. However, by enhancing the color concentrations, the COD removal efficiency reduced to about 90%.
Abstract Woolen textile industries produces a significant high contaminated wastewater streams which have raised environmental concerns as their turbidity (>40 NTU) and COD (>1500mg/L) are very high. To address their issue, usually a high level of chemical treatment are utilized; however, the addition of such level of chemicals itself creates another issue such as high concentrated sludge. In this study, chemical pretreatment (FeSO4 as coagulant, 400-800 mg/L, pH 6-10,) experiments was employed to reduce COD and turbidity to maximum 200 mg/L and 25 NTU respectively. The chemically assisted nanofiltration (NF) process (operating conditions: 4-8 bar, COD of 50-200 mg/L and pH of 6-10) by using a commercial spiral wound polyamide nano filter (TFC) was used to treat a real woolen textile effluent. Response surface methodology (RSM) was employed to determine the effects of operating parameters. The results showed that the best conditions for the pretreatment process were pH of 8, FeSO4 of 600 mg/L. For the NF process, by increasing pH and pressure, removal efficiency of turbidity and COD increased up to 98%. However, by enhancing 1
the color concentrations, the COD removal efficiency reduced to about 90%. The results demonstrated that NF process at optimum conditions and after chemical pretreatment has an effective efficiency for real textile wastewater treatment.COD: Chemical Oxygen Demand DOE: design of experiment MWCO: molecular weight cut-off NF: nanofiltration RSM: Response surface methodology
Abbreviations CF: Coagulation–flocculation
Keywords: Nanofiltration; Textile industry; Water reuse; Wastewater Treatment; RSM
NOMENCLATURE Symbols Cp: concentration of pollutant in the permeate C0: concentration of pollutant in the feed 1. Introduction Due to the shortage of water resources and poor water quality in industrial regions, authorities try to find new guidelines for reusing industrial wastewater streams. High water consumption in textile industries has forced theses industries to treat and reuse their produced wastewater (Arnal et al. 2008). Alongside dyes in textile wastewater, different chemicals such as salts, heavy metals,
dispersing agents, smoothing agents and surfactants could also be traced, which makes the waste water treatment more complicated (Nataraj et al. 2009). Membrane technology is capable of eliminating the organic and inorganic materials as well as water hardness in a one-step process (Mondal et al. 2016). This makes the replacement/amendment of traditional wastewater treatment process possible with membrane processes, which encourages companies to invest and research in the membrane science and technology (Yu et al. 2010). Nanofiltration (NF) can be used for the removal of natural organic matters as well as dyes from wastewater (Ong et al. 2014). Based on the well-known mechanism of screening, NF membranes 2
are considered as a process between the reverse osmosis and ultrafiltration separation processes (Izadpanah et al. 2012). Comparing to reverse osmosis, the permeate flux of NF is greater while its pressure drop is lower (Daraei et al. 2013). The separation mechanisms for NF are based on the size exclusion and electrostatic repulsive forces (Arsuaga et al. 2008). A direct feeding of wastewater stream into an NF process can cause the irreversible fouling issue leading to higher operation costs and energy consumption as well as lower membrane life-time. Therefore, providing a feed pretreatment process before NF seems necessary to mitigate membrane fouling (Yu et al. 2014). A physicochemical method of coagulation-flocculation is considered as an effective pretreatment method due to its low capital cost besides its tendency to reduce the fouling (Dong et al. 2007). However, the current physicochemical methods often requires a significant amount of chemicals which could lead to a high concentrated sludge. Hence, the combination of Coagulation– Flocculation and membrane processes seems to be an effective strategy to address complex wastewater streams and to reduce substantially the amount of used chemicals. A variety of parameters such as pore size, membrane type, pollutant concentration, operating pressure, pH and temperature have significant effect on the performance of membrane (Van der Bruggen et al. 2002). Torres et al. (2010) used a combination of coagulation–flocculation and nanofiltration to remove color from wastewater.Their results showed that the combination of these techniques enhanced the removal percentage to over 98% and provided a chance to reduce the concentration of resins needed in their study. Bes-Pia et al. (2003) studied the effect of operating pressures, cross- flow velocities and coagulants, in an NF process as a post-treatment after the coagulation–flocculation. They showed that nanofiltration of the physico-chemical treated wastewater could produce permeate with a COD lower than 100 mg/L. Sari et al. (2013) evaluated the capability of different pretreatment processes such as microfiltration (MF), chemical (alum) coagulation–MF, electrocoagulation–MF, and electro flotation to reduce fouling of a thin-film composite NF membrane for surface water treatment. Damas et al. (2012) evaluated the performance of ultrafiltration ceramic membranes for the wastewater treatment of a textile factory. Different operating conditions such as pressure (1-4.5 bar) and pH (8-12) were studied. Results showed that at the lowest tested pH, the flow rate of water increased as the pressure increased. In their work, the removal efficiencies of 70%, 96%, 93% for COD, color and turbidity, respectively were achieved. Sojka et al. (2010), studied the effect of operating conditions including temperature (40-
3
60 °C), and pH (4-10) on the performance of a polymeric NF process. In their work, the best efficiency was achieved in the pH range of 7-10 and at the temperatures below 60°C. Gozalvez-Zafrilla et al. (2008) investigated the use of NF for the purification of secondary wastewater in a textile industry using three NF membranes with different pores sizes (NF270, NF200, and NF90). Their findings showed that the NF200 and NF270 have similar behavior in the removal of salt, whereas NF90 showed a better efficiency such that salt removal increased by increasing the pressure. For COD removal, membranes showed different behaviors, NF90 membrane eliminated a greater percentage of COD. Askari et al. (2015) studied the performance of NF membrane in the removal of anthraquinone dyes from simulated textile wastewater at different dye concentration and pH values. Results showed that dye removal efficiency enhanced about 10% by increasing pH from 6 to 10. Although physicochemical treatment and NF process have been studied individually before, their combination and their synergic effect have yet to be investigated. In addition, the hybrid system of chemical coagulation and NF process for a real textile feed has not been reported. In this study, the effect of operating parameters (pH, concentration, and pressure) for the performance of NF process for COD removal after physico-chemical pretreatment have been studied. The response surface methodology (RSM) was used to conduct the research and analysis. The aim of this study is to find the optimum operating conditions to maximize the COD and color removal efficiency. 2. Experiments 2.1. Materials and Methods A raw woolen real wastewater as the feed was provided by Golnesar Woolen Co. (Isfahan, Iran). The feed characteristics was COD (1560-3420 mg/L), BOD5 (558-1450 mg/L), turbidity (41-65 NTU) and pH (5.3 -9.2). FeSO4 and CaO were prepared from Sigma-Aldrich and used in the jartests as the coagulant and co-coagulant, respectively. For the NF experiments the pH of solutions were adjusted by HCl (0.1M) and NaOH (0.1M) from Merck. The coagulation–flocculation experiments were optimized in a jar test apparatus (JTR90) as a pretreatment for NF process. The coagulant was added and rapidly mixed (100 rpm) during 60 seconds, flocculation (25 rpm) and the settling time were set to 60 minutes. The jar test was done based on the upper level of raw wastewater.
4
Membrane filtration as the post-treatment was implemented in a laboratory scale setup using a polyamide spiral wound NF membrane. Figure 1 shows the schematic diagram of the membrane system in continuous operational mode.The membrane specifications are presented in Table 1. The levels for design of experiment of the NF process was selected based on the preliminary experiments which was tested on the woolen wastewater. All of the experiments were performed according to the water and wastewater examination methods (Yu et al. 2014).
Fig. 2.Contours diagram of change in turbidity removal versus actual operating levels for mixing time and pH in constant concentration of 600mg / L (RSM method)
Fig. 4. Contours diagram of change in COD removal versus operating levels for pressure (bar) and pH in constant COD concentration of 100 mg / L .
Figure3. Contours diagram of change in turbidity removal versus actual operating levels for mixing time and coagulant concentration in constant pH of 8 (RSM method)
Fig. 5. Contours diagram of change in COD removal efficiency versus actual operating levels for pressure (bar) and COD concentration (mg/l) at constant pH of 8.
Table 2. Factors and selected levels for coagulation-flocculation method
5
Levels Factors
-1
0
+1
Time (min) Coagulant concentration (mg/L)
8 400
10 600
15 800
pH
6
8
10
Table 3. Factors and selected levels for NF process Levels Factors
-1
0
+1
COD (mg/L)
4 50
6 100
8 200
pH
6
8
10
Pressure (bar)
Table 4.Box-Behnken design results for coagulation – flocculation wastewater pretreatment method Experiment No. pH Mixing time TurbidityRemo FeSO4 Concentration ) min ( val Percentage )mg/L( 1 400±2 6.00±0.1 15 31.7 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Experiment No.
800±5 400±2 800±5 400±2 800±5 400±2 800±5 600±3 600±3 600±3 600±3 600±3 600±3 600±3
6.00±0.1 10.0±0.1 10.0±0.1 8.00±0.1 8.00±0.1 8.00±0.1 8.00±0.1 6.00±0.1 10.0±0.1 6.00±0.1 10.0±0.1 8.00±0.1 8.00±0.1 8.00±0.1
15 15 15 10 10 20 20 10 10 20 20 15 15 15
Table 5.Box-Behnken design results for NF process. pH pressure COD Concentration )bar( )mg/L(
74.0 45.5 82.9 44.7 78.0 61.0 94.3 62.6 69.9 80.5 87.0 87.0 87.0 87.0
1
50±.02
6.00±0.1
6
COD Removal Percentage 94
2 3 4 5 6 7
200±5 50.0±2 200±5 50.0±2 200±5 50.0±2
6.00±0.1 10.0±0.1 10.0±0.1 8.00±0.1 8.00±0.1 8.00±0.1
6 6 6 4 4 8
89 98 92.5 94 90 97
6
8 9 10 11 12
200±5 100±3 100±3 100±3 100±3
13 14 15
8.00±0.1 6.00±0.1 10.0±0.1 6.00±0.1 10.0±0.1
8 4 4 8 8
91 93 95.5 94 97
100±3
8.00±0.1
6
94
100±3 100±3
8.00±0.1 8.00±0.1
6 6
94 94
Table 6. Analysis of variance for TDS removal rate Mean Sum of Degree of F-value P-value square squares freedom 8153.2 8153.2 2 2404.3 0.000
Significant
1120.1
1120.1
2
303.3
0.000
Significant
C: Mixing time
1444.5
1444.5
2
425.9
0.000
Significant
A× B A× C B ×C Pure Error
70.4 2.4 23.6 13.5
70.4 2.4 23.6 13.5
4 4 4 8
10.4 0.36 3.48 -
0.003 0.83 0.063 -
significant Not significant Not significant -
Model terms A: FeSO4concentratio n B:pH
Status
Table 7. Analysis of variance for COD removal rate Mean Sum of Degree of F-value P-value square squares freedom 47.5 47.5 1 79.7 0.003
Significant
B:pH
28.12
28.12
1
47.2
0.001
Significant
C: p
11.28
11.28
1
18.9
0.007
Significant
A× B A× C B ×C Pure Error
0.06 0.25 0.56 1.33
0.06 0.25 0.56 2.67
1 1 1 2
0.1 0.4 0.9 -
0.5457 0.3759 0.2564 -
Not significant Not significant Not significant -
Model terms A:COD concentration
Table 1.Properties of commercial TFC NF membrane used in this study Country of Manufacture
Status
South Korea
Material membrane
Polyamide
Maximum pressure
9 bar
Max Temperature
45° C
pH range
2-11
Iso-electric point
4.5
Membrane surface charge
Negative
7
0.35 m2
Membrane surface area Failure membrane molecular weight(MWCO)
300 Dalton
2.3. Membranes performance evaluation The performance of NF membrane was expressed by measuring the removal efficiency of COD. Equation (1) is used for the calculation of the removal efficiency:(1)
Where “R” represents the percentage of removed pollutants, Cp and C0 indicate the concentration of the pollutant in permeate and feed, respectively. For optimization of coagulation–flocculation method, turbidity removal efficiency as an indirect measurement for COD removal was considered. 2.4. Design of experiment The statistical design of experiment (DOE) is a structured method in which all factors vary simultaneously over a set of experiments to determine the relationship between the operating parameters and the response. So, the numbers of the experiments are reduced in DOE methods such as Response Surface Methodology (RSM) in comparison to a full factorial design. RSM is an effective method for improving the responses with the optimal experimental conditions. In this study, the RSM method was used to analyze the effect of factors on the physicochemical and NF processes. RSM consists several designs, in this study Box‐Behnken design has been used. Coagulant concentration, pH and mixing time for the chemical treatment process and COD, pressure and pH for the membrane process were the selected parameters to be studied. Then, these factors should be considered in an interval regarding facilitate, general information from previous research, and the actual values in the selected range. Table 2 shows factors and selected levels for evaluating the performance of the coagulationflocculation method and NF membrane. Due to the wide range of COD after the physic-chemical method (Table 3 for 5 samples), three values of COD in the range were selected in this study.
8
3. Results and discussion The RSM has been applied to find out the relation between the dye removal and the operating factors. The responses of the experiments according to the design obtained by RSM for both wastewater treatment methods are presented in Table 4 and 5. Higher turbidity removal represents better COD removal.
Analyses of variance (ANOVA) for the RSM model are shown in Table 6 and 7. F-values imply the importance of the factor such that as F-value increases, its effect on the response increases.
9
3.1. Coagulation-flocculation experiments 3.1.1. Effect of concentration, pH and mixing time on turbidity removal As shown in Figure 2 and 3, by increasing the concentration of coagulant, the removal efficiency of turbidity increased. With increasing the concentration of coagulant, the metal hydroxide concentration increased due to a reduction in the electrostatic barrier between the particles. Therefore, the efficient collision of the particles to each other leads to a better coagulation. These results are in consistent with data from other researchers (Gao et al. 2007). It was observed that the removal efficiency of turbidity increased with increasing pH from 6 to 8, then decreased from pH 8 to 10. As a result, the contaminant removal efficiency increased with increasing the pH. Also due to the fact that iron sulfate functions properly in pH 4 to 9, the removal of the turbidity began to decline from pH=8. The use of Ca(OH)2 for pH adjustment raised the rate of flocculation process and contaminant removal efficiency. With increasing the flocculent time, the number of collision of formed floc raised.
3.2. NF experiments 3.2.1. Effect of pressure on COD removal Figures 4 and 5 show the effect of pH and pressure on the response of pollutants removals. The results showed that the contaminant removal efficiency increased at higher operating pressure. As the pressure increased, the driving force of filtration process enhanced as well. Since the concentration is constant, with increasing the output flux, the contaminant removal efficiency rose. According to Razmjou et al. (2011) when feed pressure increases foulants with a particle size 10
greater than membrane pore size accumulate on the membrane surface leading to the formation of a loose cake layer that acts as an extra barrier for pollutants to pass through membrane resulting in a higher Rejection values. These findings are also in consistent with the data obtained from other researchers (Garcia et al. 2006). 3.2.2. Effect of pH on the COD removal efficiency The results (Figure 4) showed that the contaminant removal efficiency increases with increasing the pH. Since the iso-electric point of the used NF membrane is about pH of 4.5, at pH above this point, the surface charge of NF membrane is negative. Therefore, the increase of pH leads to an increase in the negative charge of the membrane, which enhanced the electrical repulsive force between the contaminants and membrane and shows a better separation. These results are in consistent with findings of other researchers (Richards et al. 2010; Santafé-Moros et al. 2007).
3.2.3. Effect of COD on the removal efficiency Contours diagram of the pollutants removal is shown in Figure 5. The results showed that with increasing the concentration of the COD, the percentage of pollutants removal reduced. Because of increasing the concentration of COD, concentration of cations in the solution increases. Since the membrane surface is negatively charged, absorption of cations on the surface of the membrane increases and the cation layer on the membrane surface is formed. As a result, the shielding phenomenon occurs and the removal of pollutants reduced. These results are in agreement with the data of other researchers ( Garcia et al. 2006; Richards et al. 2010; Santafé-Moros et al. 2007; Wang et al. 2005).
4. Conclusion The results of this study indicated that NF process by using a commercial spiral wound polyamide nano filter (TFC) after coagulation-flocculation has an effective efficiency for woolen textile wastewater treatment. Response surface statistical analyses indicated that the optimized control factors settings for the concentration of coagulant, pH range, COD concentration after chemical treatment and operating pressure are 800 mg/L, 10, 50 mg/L, and 8 bar, respectively. Also, the 11
data from the RSM method revealed that with increasing the pH of the feed and pressure of the process, there is a possibility to increase the efficiency of contamination removal. However, with increasing the concentration of COD, removal of pollutants reduced in both methods. As a conclusion, the NF process has a great potential for the removal of pollutants (e.g. color, and minerals) for recycling textile wastewater streams in production lines.
Acknowledgment The authors would like to thank the Golnesar Woolen Co. (Isfahan, Iran) for providing financial support, and the Environmental Research Institute (University of Isfahan) and Mrs M. Faghih as well as Mrs N. Imami who helped in this work.
References Arnal J. M, León M. C, Lora J, Gozalvez J. M, Santafé A, Sanz D, Tena J. (2008) Ultrafiltration as a pretreatment of other membrane technologies in the reuse of textile wastewaters.Desalination, 221(1), 405412. doi:10.1016/j.desal.2007.01.099 Arsuaga J. M, López-Muñoz M. J, Aguado J, Sotto A. (2008) Temperature, pH and concentration effects on retention and transport of organic pollutants across thin-film composite nanofiltration membranes.Desalination, 221(1), 253-258. doi:10.1016/j.desal.2007.01.081 Askari, N., Farhadian, M., Razmjou, A., &Hashtroodi, H. (2015). Nanofiltration performance in the removal of dye from binary mixtures containing anthraquinone dyes. Desalination and Water Treatment, 1-8. doi: 10.1080/19443994.2015.1090917 Barredo-Damas S, Alcaina-Miranda M. I, Iborra-ClarM. I, Mendoza-Roca J. A. (2012) Application of tubular ceramic ultrafiltration membranes for the treatment of integrated textile wastewaters. Chemical engineering journal, 192, 211-218. doi:10.1016/j.cej.2012.03.079 Bes-Pia A , Mendoza-Roca J. A, Alcaina-Miranda M. I, Iborra-Clar A, Iborra-Clar M. I. (2003) Combination of physico-chemical treatment and nanofiltration to reuse wastewater of a printing, dyeing and finishing textile industry.Desalination, 157(1), 73-80. doi:10.1016/S0011-9164(03)00385-0 Daraei P, Madaeni S. S, Ghaemi N, Khadivi M. A, Rajabi L, Derakhshan A. A, Seyedpour F. (2013) PAA grafting onto new acrylate-alumoxane/PES mixed matrix nano-enhanced membrane: Preparation, 12
characterization and performance in dye removal. Chemical Engineering Journal, 221, 111-123. doi:10.1016/j.cej.2013.01.079 Dong B. Z, Yan C. H. E. N, Gao N. Y, Fan J. C. (2007) Effect of coagulation pretreatment on the fouling of ultrafiltration membrane. Journal of Environmental Sciences, 19(3), 278-283. doi: 10.1016/S10010742(07)60045 Gao B. Y, Yue Q. Y, Wang Y. (2007) Coagulation performance of polyaluminum silicate chloride (PASiC) for water and wastewater treatment. Separation and Purification Technology, 56(2), 225-230. doi:10.1016/j.seppur.2007.02.003 Garcia F, Ciceron D, Saboni A, Alexandrova S. (2006) Nitrate ions elimination from drinking water by nanofiltration: membrane choice. Separation and purification technology, 52(1), 196-200. doi: 10.1016/j.seppur.2006.03.023 Gozálvez-Zafrilla J. M, Sanz-Escribano D, Lora-García J, Hidalgo M. L. (2008) Nanofiltration of secondary effluent for wastewater reuse in the textile industry.Desalination, 222(1), 272-279. doi:10.1016/j.desal.2007.01.173 Izadpanah A. A, Javidnia, A. (2012) The ability of a nanofiltration membrane to remove hardness and ions from diluted seawater.Water, 4(2), 283-294. doi: 10.3390/w4020283 Mondal M, De S. (2016) Treatment of textile plant effluent by hollow fiber nanofiltration membrane and multi-component steady state modeling.Chemical Engineering Journal, 285, 304-318. doi:10.1016/j.cej.2015.10.005 Nataraj S. K, Hosamani K. M, Aminabhavi T. M. (2009) Nanofiltration and reverse osmosis thin film composite membrane module for the removal of dye and salts from the simulated mixtures. Desalination, 249(1), 12-17. doi:10.1016/j.desal.2009.06.008 Ong Y. K, LiF. Y, Sun S. P, Zhao B. W, Liang C. Z, ChungT. S. (2014) Nanofiltration hollow fiber membranes for textile wastewater treatment: Lab-scale and pilot-scale studies. Chemical Engineering Science, 114, 51-57. doi:10.1016/j.ces.2014.04.007 Razmjou A, Mansouri J, Chen V. (2011). The effects of mechanical and chemical modification of TiO 2 nanoparticles on the surface chemistry, structure and fouling performance of PES ultrafiltration membranes. Journal of Membrane Science, 378(1), 73-84. doi:10.1016/j.memsci.2010.10.019 Riera-Torres M, Gutiérrez-Bouzán C, Crespi M. (2010). Combination of coagulation–flocculation and nanofiltration techniques for dye removal and water reuse in textile effluents.Desalination, 252(1), 53-59. doi:10.1016/j.desal.2009.11.002 Richards L. A, Vuachère M, Schäfer A. I. (2010) Impact of pH on the removal of fluoride, nitrate and boron by nanofiltration/reverse osmosis. Desalination, 261(3), 331-337. doi: 10.1016/j.desal.2010.06.025 Santafé-Moros A, Gozálvez-Zafrilla J. M, Lora-Garcia J. (2007) Nitrate removal from ternary ionic solutions by a tight nanofiltration membrane. Desalination, 204(1), 63-71.doi:10.1016/j.desal.2006.04.024 Sari M. A, Chellam S. (2013) Surface water nanofiltration incorporating (electro) coagulation– microfiltration pretreatment: Fouling control and membrane characterization. Journal of Membrane Science, 437, 249-256. doi:10.1016/j.memsci.2013.02.050 13
Sojka-Ledakowicz J, Zylla R, Mrozinska Z, Pazdzior K, Klepacz-Smolka A, Ledakowicz S. (2010) Application of membrane processes in closing of water cycle in a textile dye-house. Desalination, 250(2), 634-638. doi:10.1016/j.desal.2009.09.039 Van der Bruggen B, Braeken L, Vandecasteele C. (2002) Evaluation of parameters describing flux decline in nanofiltration of aqueous solutions containing organic compounds.Desalination, 147(1), 281-288. doi:10.1016/S0011-9164(02)00553-2 Wang D. X, Su M, Yu Z. Y, Wang X. L, Ando M, Shintani T. (2005) Separation performance of a nanofiltration membrane influenced by species and concentration of ions.Desalination, 175(2), 219-225. doi:10.1016/j.desal.2004.10.009 Yu W, Xu L, Graham N, Qu J. (2014) Pre-treatment for ultrafiltration: effect of pre-chlorination on membrane fouling. Scientific reports, 4. doi:10.1038/srep06513 Yu S, Liu M, Ma M, Qi M, Lü Z, Gao C. (2010) Impacts of membrane properties on reactive dye removal from dye/salt mixtures by asymmetric cellulose acetate and composite polyamide nanofiltration membranes.Journal of Membrane Science, 350(1), 83-91. doi:10.1016/j.memsci.2009.12.014
Fig. 1.Schematic diagram of the CF-NF setup
14
S2215-1532(17)30005-3 http://dx.doi.org/doi:10.1016/j.enmm.2017.06.001 ENMM 93
To appear in: Received date: Revised date: Accepted date:
8-1-2017 31-5-2017 6-6-2017
Please cite this article as: E.Hassanzadeh, M.Farhadian, A.Razmjou, N.Askari, An efficient wastewater treatment approach for a real woolen textile industry using a chemical assisted NF membrane process, Environmental Nanotechnology, Monitoring and Managementhttp://dx.doi.org/10.1016/j.enmm.2017.06.001 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.
An efficient wastewater treatment approach for a real woolen textile industry using a chemical assisted NF membrane process E. Hassanzadeh1,2, M. Farhadian3*, A. Razmjou4, N. Askari3 1
Environmental Engineering Department, Faculty of Agriculture, Islamic Azad University Bandar Abbas Branch, Iran 2
Water and Environmental Group, Isfahan High Education and Research Institute, Isfahan, Iran
3*
Chemical Engineering Department, Faculty of Engineering, University of Isfahan, Isfahan, Iran
4Department
of Biotechnology, Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran
3
* E-mail: [email protected]
Highlights: - NF process at optimum conditions and after chemical pretreatment has an effective efficiency for real woolen textile wastewater treatment. - The results showed that the best conditions for the pretreatment process were pH of 8, FeSO4 of 600 mg/L. - For the NF process, by increasing pH and pressure, removal efficiency of turbidity and COD increased up to 98%. However, by enhancing the color concentrations, the COD removal efficiency reduced to about 90%.
Abstract Woolen textile industries produces a significant high contaminated wastewater streams which have raised environmental concerns as their turbidity (>40 NTU) and COD (>1500mg/L) are very high. To address their issue, usually a high level of chemical treatment are utilized; however, the addition of such level of chemicals itself creates another issue such as high concentrated sludge. In this study, chemical pretreatment (FeSO4 as coagulant, 400-800 mg/L, pH 6-10,) experiments was employed to reduce COD and turbidity to maximum 200 mg/L and 25 NTU respectively. The chemically assisted nanofiltration (NF) process (operating conditions: 4-8 bar, COD of 50-200 mg/L and pH of 6-10) by using a commercial spiral wound polyamide nano filter (TFC) was used to treat a real woolen textile effluent. Response surface methodology (RSM) was employed to determine the effects of operating parameters. The results showed that the best conditions for the pretreatment process were pH of 8, FeSO4 of 600 mg/L. For the NF process, by increasing pH and pressure, removal efficiency of turbidity and COD increased up to 98%. However, by enhancing 1
the color concentrations, the COD removal efficiency reduced to about 90%. The results demonstrated that NF process at optimum conditions and after chemical pretreatment has an effective efficiency for real textile wastewater treatment.COD: Chemical Oxygen Demand DOE: design of experiment MWCO: molecular weight cut-off NF: nanofiltration RSM: Response surface methodology
Abbreviations CF: Coagulation–flocculation
Keywords: Nanofiltration; Textile industry; Water reuse; Wastewater Treatment; RSM
NOMENCLATURE Symbols Cp: concentration of pollutant in the permeate C0: concentration of pollutant in the feed 1. Introduction Due to the shortage of water resources and poor water quality in industrial regions, authorities try to find new guidelines for reusing industrial wastewater streams. High water consumption in textile industries has forced theses industries to treat and reuse their produced wastewater (Arnal et al. 2008). Alongside dyes in textile wastewater, different chemicals such as salts, heavy metals,
dispersing agents, smoothing agents and surfactants could also be traced, which makes the waste water treatment more complicated (Nataraj et al. 2009). Membrane technology is capable of eliminating the organic and inorganic materials as well as water hardness in a one-step process (Mondal et al. 2016). This makes the replacement/amendment of traditional wastewater treatment process possible with membrane processes, which encourages companies to invest and research in the membrane science and technology (Yu et al. 2010). Nanofiltration (NF) can be used for the removal of natural organic matters as well as dyes from wastewater (Ong et al. 2014). Based on the well-known mechanism of screening, NF membranes 2
are considered as a process between the reverse osmosis and ultrafiltration separation processes (Izadpanah et al. 2012). Comparing to reverse osmosis, the permeate flux of NF is greater while its pressure drop is lower (Daraei et al. 2013). The separation mechanisms for NF are based on the size exclusion and electrostatic repulsive forces (Arsuaga et al. 2008). A direct feeding of wastewater stream into an NF process can cause the irreversible fouling issue leading to higher operation costs and energy consumption as well as lower membrane life-time. Therefore, providing a feed pretreatment process before NF seems necessary to mitigate membrane fouling (Yu et al. 2014). A physicochemical method of coagulation-flocculation is considered as an effective pretreatment method due to its low capital cost besides its tendency to reduce the fouling (Dong et al. 2007). However, the current physicochemical methods often requires a significant amount of chemicals which could lead to a high concentrated sludge. Hence, the combination of Coagulation– Flocculation and membrane processes seems to be an effective strategy to address complex wastewater streams and to reduce substantially the amount of used chemicals. A variety of parameters such as pore size, membrane type, pollutant concentration, operating pressure, pH and temperature have significant effect on the performance of membrane (Van der Bruggen et al. 2002). Torres et al. (2010) used a combination of coagulation–flocculation and nanofiltration to remove color from wastewater.Their results showed that the combination of these techniques enhanced the removal percentage to over 98% and provided a chance to reduce the concentration of resins needed in their study. Bes-Pia et al. (2003) studied the effect of operating pressures, cross- flow velocities and coagulants, in an NF process as a post-treatment after the coagulation–flocculation. They showed that nanofiltration of the physico-chemical treated wastewater could produce permeate with a COD lower than 100 mg/L. Sari et al. (2013) evaluated the capability of different pretreatment processes such as microfiltration (MF), chemical (alum) coagulation–MF, electrocoagulation–MF, and electro flotation to reduce fouling of a thin-film composite NF membrane for surface water treatment. Damas et al. (2012) evaluated the performance of ultrafiltration ceramic membranes for the wastewater treatment of a textile factory. Different operating conditions such as pressure (1-4.5 bar) and pH (8-12) were studied. Results showed that at the lowest tested pH, the flow rate of water increased as the pressure increased. In their work, the removal efficiencies of 70%, 96%, 93% for COD, color and turbidity, respectively were achieved. Sojka et al. (2010), studied the effect of operating conditions including temperature (40-
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60 °C), and pH (4-10) on the performance of a polymeric NF process. In their work, the best efficiency was achieved in the pH range of 7-10 and at the temperatures below 60°C. Gozalvez-Zafrilla et al. (2008) investigated the use of NF for the purification of secondary wastewater in a textile industry using three NF membranes with different pores sizes (NF270, NF200, and NF90). Their findings showed that the NF200 and NF270 have similar behavior in the removal of salt, whereas NF90 showed a better efficiency such that salt removal increased by increasing the pressure. For COD removal, membranes showed different behaviors, NF90 membrane eliminated a greater percentage of COD. Askari et al. (2015) studied the performance of NF membrane in the removal of anthraquinone dyes from simulated textile wastewater at different dye concentration and pH values. Results showed that dye removal efficiency enhanced about 10% by increasing pH from 6 to 10. Although physicochemical treatment and NF process have been studied individually before, their combination and their synergic effect have yet to be investigated. In addition, the hybrid system of chemical coagulation and NF process for a real textile feed has not been reported. In this study, the effect of operating parameters (pH, concentration, and pressure) for the performance of NF process for COD removal after physico-chemical pretreatment have been studied. The response surface methodology (RSM) was used to conduct the research and analysis. The aim of this study is to find the optimum operating conditions to maximize the COD and color removal efficiency. 2. Experiments 2.1. Materials and Methods A raw woolen real wastewater as the feed was provided by Golnesar Woolen Co. (Isfahan, Iran). The feed characteristics was COD (1560-3420 mg/L), BOD5 (558-1450 mg/L), turbidity (41-65 NTU) and pH (5.3 -9.2). FeSO4 and CaO were prepared from Sigma-Aldrich and used in the jartests as the coagulant and co-coagulant, respectively. For the NF experiments the pH of solutions were adjusted by HCl (0.1M) and NaOH (0.1M) from Merck. The coagulation–flocculation experiments were optimized in a jar test apparatus (JTR90) as a pretreatment for NF process. The coagulant was added and rapidly mixed (100 rpm) during 60 seconds, flocculation (25 rpm) and the settling time were set to 60 minutes. The jar test was done based on the upper level of raw wastewater.
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Membrane filtration as the post-treatment was implemented in a laboratory scale setup using a polyamide spiral wound NF membrane. Figure 1 shows the schematic diagram of the membrane system in continuous operational mode.The membrane specifications are presented in Table 1. The levels for design of experiment of the NF process was selected based on the preliminary experiments which was tested on the woolen wastewater. All of the experiments were performed according to the water and wastewater examination methods (Yu et al. 2014).
Fig. 2.Contours diagram of change in turbidity removal versus actual operating levels for mixing time and pH in constant concentration of 600mg / L (RSM method)
Fig. 4. Contours diagram of change in COD removal versus operating levels for pressure (bar) and pH in constant COD concentration of 100 mg / L .
Figure3. Contours diagram of change in turbidity removal versus actual operating levels for mixing time and coagulant concentration in constant pH of 8 (RSM method)
Fig. 5. Contours diagram of change in COD removal efficiency versus actual operating levels for pressure (bar) and COD concentration (mg/l) at constant pH of 8.
Table 2. Factors and selected levels for coagulation-flocculation method
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Levels Factors
-1
0
+1
Time (min) Coagulant concentration (mg/L)
8 400
10 600
15 800
pH
6
8
10
Table 3. Factors and selected levels for NF process Levels Factors
-1
0
+1
COD (mg/L)
4 50
6 100
8 200
pH
6
8
10
Pressure (bar)
Table 4.Box-Behnken design results for coagulation – flocculation wastewater pretreatment method Experiment No. pH Mixing time TurbidityRemo FeSO4 Concentration ) min ( val Percentage )mg/L( 1 400±2 6.00±0.1 15 31.7 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Experiment No.
800±5 400±2 800±5 400±2 800±5 400±2 800±5 600±3 600±3 600±3 600±3 600±3 600±3 600±3
6.00±0.1 10.0±0.1 10.0±0.1 8.00±0.1 8.00±0.1 8.00±0.1 8.00±0.1 6.00±0.1 10.0±0.1 6.00±0.1 10.0±0.1 8.00±0.1 8.00±0.1 8.00±0.1
15 15 15 10 10 20 20 10 10 20 20 15 15 15
Table 5.Box-Behnken design results for NF process. pH pressure COD Concentration )bar( )mg/L(
74.0 45.5 82.9 44.7 78.0 61.0 94.3 62.6 69.9 80.5 87.0 87.0 87.0 87.0
1
50±.02
6.00±0.1
6
COD Removal Percentage 94
2 3 4 5 6 7
200±5 50.0±2 200±5 50.0±2 200±5 50.0±2
6.00±0.1 10.0±0.1 10.0±0.1 8.00±0.1 8.00±0.1 8.00±0.1
6 6 6 4 4 8
89 98 92.5 94 90 97
6
8 9 10 11 12
200±5 100±3 100±3 100±3 100±3
13 14 15
8.00±0.1 6.00±0.1 10.0±0.1 6.00±0.1 10.0±0.1
8 4 4 8 8
91 93 95.5 94 97
100±3
8.00±0.1
6
94
100±3 100±3
8.00±0.1 8.00±0.1
6 6
94 94
Table 6. Analysis of variance for TDS removal rate Mean Sum of Degree of F-value P-value square squares freedom 8153.2 8153.2 2 2404.3 0.000
Significant
1120.1
1120.1
2
303.3
0.000
Significant
C: Mixing time
1444.5
1444.5
2
425.9
0.000
Significant
A× B A× C B ×C Pure Error
70.4 2.4 23.6 13.5
70.4 2.4 23.6 13.5
4 4 4 8
10.4 0.36 3.48 -
0.003 0.83 0.063 -
significant Not significant Not significant -
Model terms A: FeSO4concentratio n B:pH
Status
Table 7. Analysis of variance for COD removal rate Mean Sum of Degree of F-value P-value square squares freedom 47.5 47.5 1 79.7 0.003
Significant
B:pH
28.12
28.12
1
47.2
0.001
Significant
C: p
11.28
11.28
1
18.9
0.007
Significant
A× B A× C B ×C Pure Error
0.06 0.25 0.56 1.33
0.06 0.25 0.56 2.67
1 1 1 2
0.1 0.4 0.9 -
0.5457 0.3759 0.2564 -
Not significant Not significant Not significant -
Model terms A:COD concentration
Table 1.Properties of commercial TFC NF membrane used in this study Country of Manufacture
Status
South Korea
Material membrane
Polyamide
Maximum pressure
9 bar
Max Temperature
45° C
pH range
2-11
Iso-electric point
4.5
Membrane surface charge
Negative
7
0.35 m2
Membrane surface area Failure membrane molecular weight(MWCO)
300 Dalton
2.3. Membranes performance evaluation The performance of NF membrane was expressed by measuring the removal efficiency of COD. Equation (1) is used for the calculation of the removal efficiency:
Where “R” represents the percentage of removed pollutants, Cp and C0 indicate the concentration of the pollutant in permeate and feed, respectively. For optimization of coagulation–flocculation method, turbidity removal efficiency as an indirect measurement for COD removal was considered. 2.4. Design of experiment The statistical design of experiment (DOE) is a structured method in which all factors vary simultaneously over a set of experiments to determine the relationship between the operating parameters and the response. So, the numbers of the experiments are reduced in DOE methods such as Response Surface Methodology (RSM) in comparison to a full factorial design. RSM is an effective method for improving the responses with the optimal experimental conditions. In this study, the RSM method was used to analyze the effect of factors on the physicochemical and NF processes. RSM consists several designs, in this study Box‐Behnken design has been used. Coagulant concentration, pH and mixing time for the chemical treatment process and COD, pressure and pH for the membrane process were the selected parameters to be studied. Then, these factors should be considered in an interval regarding facilitate, general information from previous research, and the actual values in the selected range. Table 2 shows factors and selected levels for evaluating the performance of the coagulationflocculation method and NF membrane. Due to the wide range of COD after the physic-chemical method (Table 3 for 5 samples), three values of COD in the range were selected in this study.
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3. Results and discussion The RSM has been applied to find out the relation between the dye removal and the operating factors. The responses of the experiments according to the design obtained by RSM for both wastewater treatment methods are presented in Table 4 and 5. Higher turbidity removal represents better COD removal.
Analyses of variance (ANOVA) for the RSM model are shown in Table 6 and 7. F-values imply the importance of the factor such that as F-value increases, its effect on the response increases.
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3.1. Coagulation-flocculation experiments 3.1.1. Effect of concentration, pH and mixing time on turbidity removal As shown in Figure 2 and 3, by increasing the concentration of coagulant, the removal efficiency of turbidity increased. With increasing the concentration of coagulant, the metal hydroxide concentration increased due to a reduction in the electrostatic barrier between the particles. Therefore, the efficient collision of the particles to each other leads to a better coagulation. These results are in consistent with data from other researchers (Gao et al. 2007). It was observed that the removal efficiency of turbidity increased with increasing pH from 6 to 8, then decreased from pH 8 to 10. As a result, the contaminant removal efficiency increased with increasing the pH. Also due to the fact that iron sulfate functions properly in pH 4 to 9, the removal of the turbidity began to decline from pH=8. The use of Ca(OH)2 for pH adjustment raised the rate of flocculation process and contaminant removal efficiency. With increasing the flocculent time, the number of collision of formed floc raised.
3.2. NF experiments 3.2.1. Effect of pressure on COD removal Figures 4 and 5 show the effect of pH and pressure on the response of pollutants removals. The results showed that the contaminant removal efficiency increased at higher operating pressure. As the pressure increased, the driving force of filtration process enhanced as well. Since the concentration is constant, with increasing the output flux, the contaminant removal efficiency rose. According to Razmjou et al. (2011) when feed pressure increases foulants with a particle size 10
greater than membrane pore size accumulate on the membrane surface leading to the formation of a loose cake layer that acts as an extra barrier for pollutants to pass through membrane resulting in a higher Rejection values. These findings are also in consistent with the data obtained from other researchers (Garcia et al. 2006). 3.2.2. Effect of pH on the COD removal efficiency The results (Figure 4) showed that the contaminant removal efficiency increases with increasing the pH. Since the iso-electric point of the used NF membrane is about pH of 4.5, at pH above this point, the surface charge of NF membrane is negative. Therefore, the increase of pH leads to an increase in the negative charge of the membrane, which enhanced the electrical repulsive force between the contaminants and membrane and shows a better separation. These results are in consistent with findings of other researchers (Richards et al. 2010; Santafé-Moros et al. 2007).
3.2.3. Effect of COD on the removal efficiency Contours diagram of the pollutants removal is shown in Figure 5. The results showed that with increasing the concentration of the COD, the percentage of pollutants removal reduced. Because of increasing the concentration of COD, concentration of cations in the solution increases. Since the membrane surface is negatively charged, absorption of cations on the surface of the membrane increases and the cation layer on the membrane surface is formed. As a result, the shielding phenomenon occurs and the removal of pollutants reduced. These results are in agreement with the data of other researchers ( Garcia et al. 2006; Richards et al. 2010; Santafé-Moros et al. 2007; Wang et al. 2005).
4. Conclusion The results of this study indicated that NF process by using a commercial spiral wound polyamide nano filter (TFC) after coagulation-flocculation has an effective efficiency for woolen textile wastewater treatment. Response surface statistical analyses indicated that the optimized control factors settings for the concentration of coagulant, pH range, COD concentration after chemical treatment and operating pressure are 800 mg/L, 10, 50 mg/L, and 8 bar, respectively. Also, the 11
data from the RSM method revealed that with increasing the pH of the feed and pressure of the process, there is a possibility to increase the efficiency of contamination removal. However, with increasing the concentration of COD, removal of pollutants reduced in both methods. As a conclusion, the NF process has a great potential for the removal of pollutants (e.g. color, and minerals) for recycling textile wastewater streams in production lines.
Acknowledgment The authors would like to thank the Golnesar Woolen Co. (Isfahan, Iran) for providing financial support, and the Environmental Research Institute (University of Isfahan) and Mrs M. Faghih as well as Mrs N. Imami who helped in this work.
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Fig. 1.Schematic diagram of the CF-NF setup
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