Treatment of Pulp and Paper Mill Wastewater Using Utrafiltration

Article pubs.acs.org/IECR

Treatment of Pulp and Paper Mill Wastewater Using Utrafiltration Process: Optimization of the Fouling and Rejections Z. Beril Gönder,* Semiha Arayici, and Hulusi Barlas Department of Environmental Engineering, Faculty of Engineering, Istanbul University, Avcilar, Istanbul 34320, Turkey ABSTRACT: Treatment of pulp and paper mill wastewater using ultrafiltration (UF) membranes was investigated in this study. A Taguchi experimental design was implemented for design of the experiments to investigate optimum operating conditions that achieve higher removal of pollutants and lower membrane fouling. Four factors at three different levels were considered for the experimental design, namely, pH, temperature, transmembrane pressure, and volume reduction factor (VRF). Under the optimized conditions (pH 10, temperature 25 °C, transmembrane pressure 6 bar, and VRF 3), a 35% flux decline caused by fouling occurred. Higher rejections were observed for total hardness (83%), sulfate (97%), spectral absorption coefficient (SAC254) (95%), and chemical oxygen demand (COD) (89%), but not for conductivity (50%), under these conditions. From the analysis of variance (ANOVA), it was determined that the factor of pH made the greatest contribution to response parameters. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) analyses showed that membrane fouling occurring on the membrane surface and within pores decreased by optimizing the operating conditions. The Taguchi method was successfully applied to find the optimum conditions for the treatment of pulp and paper mill wastewater using the UF process. et al.13 investigated the suitability of different polymeric UF membranes and MF membranes for the treatment of acidic clear filtrate (ACF). The tested membranes retained over 90% of the turbidity with high filtration capacity. The regenerated cellulose (RC) UF membrane showed a lower fouling tendency than other membranes. Membrane fouling is still a limiting factor for the utilization of membrane filtration at a greater scale in pulp and paper mill applications. In the literature, some studies have been performed dealing with the fouling of UF membranes in the treatment of pulp and paper wastewater. Maartens et al.14 investigated the fouling of polyethersulfone (PES) UF membranes fouled with extraction stage (E-stage) pulp mill effluent. Their results showed that increasing the hydrophilic characteristics of the membranes could reduce the amount of organic foulants that adsorbed onto the membranes. Puro et al.15 compared the fouling of RC and PES membranes in the UF of chemithermomechanical pulp mill process waters. The results of this study revealed that all of the membrane characteristics should be optimal for obtaining an optimal lowfouling membrane. Weis et al.16 studied the fouling mechanisms of polysulfone (PS), PES, and RC UF membranes fouled with spent sulfite liquor using Fourier transform infrared (FTIR) spectroscopy and zeta potential and contact angle measurements. They determined that the hydrophilicity of the membranes played an important role in reducing fouling by spent sulfite liquor feed. To attain high filtration performance and low fouling, the operating conditions, which are influenced by several factors, must be carefully optimized. Therefore, the application of

1. INTRODUCTION The pulp and paper industry is a very water-intensive industry in terms of freshwater use. Currently, the increasing needs to reduce water consumption and to satisfy tightened discharge standards in stringent environmental regulations have forced paper mills to treat their effluent using advanced treatment processes. Potential advanced treatment processes that are used for wastewater treatment from pulp and paper mills include chemical coagulation and flocculation,1 adsorption,2,3 and advanced oxidation processes.4−8 Membrane processes (especially reverse osmosis, nanofiltration, and ultrafiltration) are gaining wider application in pulp and paper wastewater treatment among advanced treatment processes with the aim of water recycling, because such processes offer a high level of contaminant removal with a relatively low level of energy consumption. Moreover, they require small floor space, so they are easy to fit into existing mill water circuits. Ultrafiltration (UF) can be successfully used in the pulp and paper mill industry as internal process water recycling or external treatment. It can be applied to reuse process water and thus reduce the organic load in the wastewater treatment plant. UF is an attractive process for pulp and paper mill wastewaters, as most of the pollutants consist of high-molecular-weight compounds that are easily retained by UF. This process removes about 30% of the organic load and renders the permeate pure enough to replace mechanically treated water as the paper machine shower water.9 Zaidi et al.10 studied the treatment of kraft bleaching effluents using UF and achieved 85−90% chemical oxygen demand (COD) removal efficiency. Fälth et al.11 investigated UF of alkaline filtrates from kraft pulp mills and determined that UF is a useful technology for treating these wastewaters. Liu et al.12 studied the treatability of kraft spent liquor by microfiltration (MF) and UF. Their experimental results showed that higher lignin retention (90%) was achieved with UF membranes than MF membranes. Kallioinen © 2012 American Chemical Society

Received: Revised: Accepted: Published: 6184

October 25, 2011 March 30, 2012 April 2, 2012 April 2, 2012 dx.doi.org/10.1021/ie2024504 | Ind. Eng. Chem. Res. 2012, 51, 6184−6195

Industrial & Engineering Chemistry Research

Article

outlet of the retentate), a high-pressure pump, and a cooling apparatus. The cross-flow rate (Q) was kept at 2.0 L min−1, which created a cross-flow velocity of 1.06 m s−1 throughout all experiments. The experiments were conducted in concentration mode of filtration (CMF), where permeates were collected in a separate container and retentates were circulated back to the feed tank. Because the feed solution was reduced continuously, the feed quality continuously worsened. In the CMF tests, VRF was calculated using the equation

statistical experimental designs described as design of experiments (DOE) for process optimization has great importance. DOE significantly reduces the number of experiments and cost while simultaneously yielding reliable results and products. Among the DOE methods, the Taguchi method, a popular experimental design method applied in various fields of science, can reduce the disadvantages associated with full-factorial design. The parameter design used in the Taguchi method integrates traditional engineering with statistics.17,18 In this method, large numbers of variables can be studied with small numbers of experiments by using the special design of an orthogonal array (OA). In an OA, all of the parameters are varied at the same time, and their effects are studied simultaneously to determine which factors have more or less influence. The Taguchi method recommends the use of the loss function to measure the performance characteristics deviating from the desired value. The value of the loss function is further transformed into a signalto-noise (S/N) ratio. The optimum conditions should be determined using the S/N ratio of the results obtained from experiments designed by the OA technique. The Taguchi method includes the following steps: (a) identify the performance characteristics and select process parameters to be evaluated, (b) determine the number of parameter levels for the process, (c) select the appropriate OA and assign the process paremeters to the OA, (d) conduct experiments based on the OA, (e) calculate the performance characteristics, (f) analyze the experimental results using the performance characteristics and analysis of variance (ANOVA), (g) select the optimum levels of process parameters, and (h) verify the optimal levels of the process parameters through confirmation experiments.19,20 Based on a literature review, no such systematic investigation on the effects of operating conditions in pulp and paper wastewater treatment with the UF process has been published. In our previous study, we investigated the application of a two-step nanofiltration (NF) process to the treatment of biologically treated pulp and paper wastewater for the purpose of reuse. The effects of pH, temperature, transmembrane pressure, and volume reduction factor (VRF) on the membrane fouling were studied.21 In the present study, the specific objective was to investigate optimum operating conditions that achieve higher removal of pollutants and lower membrane fouling in the treatment of pulp and paper wastewater with UF. Experiments were conducted using a Taguchi experimental design. The results of the experiments were analyzed as follows: (a) determine the optimum conditions for the process, (b) identify the contributions of individual factors, and (c) verify the optimum process parameters through confirmation experiments. ANOVA was used to determine the relative importance of the factors quantitatively. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) measurements were also used to investigate membrane fouling in detail.

VRF = Vf /Vc

(1)

where Vf and Vc are the initial volume of the feed and the final volume of the concentrate, respectively. All experimental runs were started with a feed volume of 7 L at the beginning of each run. The flat-sheet PES membrane used in this study was an FM UP005 membrane (Microdyn-Nadir GmbH) characterized by a 5-kDa MWCO (molecular weight cutoff). According to the manufacturer, the recommended maximum temperature is 95 °C, and the recommended pH range is 0−14 for the FM UP005 membrane. Prior to experiments, the membranes were pretreated with distilled water by compacting them for 5 h at the operating transmembrane pressure to remove preservatives and to obtain a stable membrane structure. 2.2. Pulp and Paper Mill Wastewater Characteristics. The study was conducted with pulp and paper wastewater samples supplied from a pulp and paper manufacturing company. The wastewater was treated with an anaerobic process followed by an aerobic process. The characteristics of the biological wastewater treatment plant effluent are given in Table 1. The wastewater was stored at 4 °C in a cold room to preserve its characteristics. Table 1. Characteristics of Biologically Treated Pulp and Paper Wastewater parameter

units

value

total hardness sulfate conductivity COD SAC254 pH

mg L−1 as CaCO3 mg L−1 μs cm−1 mg L−1 m−1 −

480 150 1200 850 135 7.0

2.3. Methods. Conductivities were measured by a WTW level 3 conductivity device. The pH of each sample was monitored with a Thermo Orion 3-Star model pH meter. The COD values were obtained using a Merck Picco photometer at a wavelength of 605 nm. Total hardness and sulfate analyses were performed according to the standard methods. 22 The spectral absorption coefficient SAC 254 (specific UV absorbance at 254 nm), which is an index to evaluate unsaturated organic substances (dissolved aromatic hydrocarbons, double-bond or carbonyl organic substances) in water was analyzed using a PG Instruments T60U model spectrophotometer according to standard DIN 38404.23 The membrane top surface was studied by AFM before and after fouling. The images were obtained using a contact-mode NanoScope IV AFM system (Digital Instruments, Buffalo, NY). The membrane surfaces were imaged at a scan size of 10 × 10 μm. The membrane surfaces were

2. EXPERIMENTAL SECTION 2.1. Experimental Setup and Membrane. The experiments were carried out in a laboratory-scale plant that was purchased from Osmo, Warendorf, Germany, with a cross-flow module (250 mm × 98 mm × 24 mm) having a flat-sheet membrane. The filtration cell, which had an effective area of 80 cm2, was constructed from stainless steel. The experimental setup was equipped with two pressure gauges (at the inlet and 6185

dx.doi.org/10.1021/ie2024504 | Ind. Eng. Chem. Res. 2012, 51, 6184−6195


Article

where n is the number of repetitions performed for an experimental combination, Yi is the performance value of the ith experiment, and MSe is the variance of the error. 2.4.3. Prediction of Optimum Performance. The performance value corresponding to the optimum working conditions can be predicted using the equation25

characterized in terms of the mean roughness (Ra), the rootmean-square roughness (Rrms), and the mean difference in height between the five highest and the five lowest points (Rz). Membrane fouling within the pores was observed using a JEOL/JSM-6335F-INCA instrument at an accelerating voltage of 10.0 kV. The dried membranes were cut under liquid nitrogen and coated with a thin layer of gold prior to analysis. 2.4. Calculations. 2.4.1. Flux Decline Analysis and Rejections. The permeate flux, J, was calculated as

1 dVp J= A m dt

Yopt =

(2)

CI =

(3)

flux decline caused by concentration polarization =

Jf − Js J0 (4)

flux decline caused by fouling =

⎛1 ⎞ Ω(dB) = −10 log⎜ − 1⎟ ⎝P ⎠

J0 − Jf J0

(6)

⎛1 S/N (dB) = − 10 log⎜⎜ ⎝n

n

∑ i=1

1 ⎞ ⎟⎟ Yi 2 ⎠

n

⎞

i=1

⎠

∑ Yi 2⎟⎟

S/N (dB) = − 10 log MSe

(12)

3. RESULTS AND DISCUSSION 3.1. Design of Experiments. Optimization of the operating conditions in the UF process by classical experimental methods involves the changing of one variable at a time while other variables are fixed at constant levels. This means that the interactions of factors have been omitted, which might result in incorrect conclusions. To overcome such problems, the Taguchi method as the DOE was applied for this study. The experimental design used for the UF of wastewater was carried out by selecting four different factors, namely, pH (A), temperature (B), transmembrane pressure (C), and VRF (D). The second stage of the Taguchi approach is selection of the appropriate orthogonal array. An L9 (34) orthogonal array was used for the examination of the effects of four factors with three levels. The selected operating conditions (factors) and their ranges (levels) for the proposed experimental design (L9 array) are given in Table 2. Each row of the matrix represents one experiment. The sequence in which these experiments are carried out is randomized. Also, to observe the effect of noise sources (uncontrollable factors) on the process, each experimental trial was repeated. In this study, the membrane fouling parameter (flux decline caused by fouling) and rejection parameters (total hardness,

where Cp represents the concentration of a particular component in the composite permeate at the end of the experiment and Cf is its feed concentration. 2.4.2. S/N Ratio. The Taguchi method uses the statistical measure of performance called the S/N ratio to analyze the experimental results. The S/N ratio is defined as the ratio of the mean response (signal) to the standard deviation (noise). The S/N ratio equation depends on the criterion for the quality characteristics to be optimized. There are three basic S/N ratio options: the larger-the-better, the smaller-the-better, and the nominal-the-best options. These S/N ratios are calculated by following equations, respectively24 ⎛1 S/N (dB) = − 10 log⎜⎜ ⎝n

(11)

where Ω (dB) is the decibel value of the percentage value subject to the omega transformation and P is the percentage of the product obtained experimentally. The values of interest were also later determined by carrying out the reverse transformation using the same equation.

(5)

The separation performance of the membrane was evaluated by the percent rejection (R) of feed components, calculated as ⎛ Cp ⎞ R (%) = ⎜1 − ⎟ × 100 Cf ⎠ ⎝

⎡⎛ 1 + m ⎞ ⎛ 1 ⎞⎤ ⎟ + ⎜ ⎟ Fα ;1,DOFe MSe⎢⎜ ⎥ ⎣⎝ N ⎠ ⎝ S ⎠⎦

where CI is the confidence interval, F is the value of the F table at the desired confidence level at degrees of freedom of 1 and degrees of freedom of error (DOFe), α is the confidence level, MSe is the mean of the square (variance) of the error, m is the number of degrees of freedom used in the prediction of Yopt, N is the total number of observations, and S is the sample size for the confirmation test. If the experimental results are given in percentages, such as flux declines and rejections, before evaluating eq 10 and 11, the Ω transformation of percentage values should be applied by using the equation27

J0 − Js J0

(10)

where N is the total number of observations; T is the sum of all observations; and A̅ i and B̅ j are the averages of the responses at levels i and j, respectively. Because eq 10 involves point estimation, the confidence interval must be evaluated at the selected error level using the equation26

where J is the permeate flux, Am is the effective membrane area, Vp is the total volume of permeate, and t is the filtration time. The flux declines were determined by measuring the fluxes in three stages: (1) The pure-water flux was measured, and the flux at steady state was defined as J0. (2) The pure water was subsequently replaced by wastewater, and the flux at the end of the experiment was defined as Js. (3) The pure-water permeate flux with the fouled membrane was measured again until a stable permeate flux was obtained, and it was defined as Jf. The flux declines were calculated based on the following equations total flux decline =

⎛ T T⎞ ⎛ T⎞ + ⎜A̅ i − ⎟ + ⎜Bj̅ − ⎟ + ... ⎝ N N⎠ ⎝ N⎠

(7)

(8) (9) 6186



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The overall mean S/N value was calculated as −33.41 for flux decline caused by fouling. As seen from Figure 1, the variations around the mean S/N value were different for different factors. The factor with the lowest variation around the mean S/N value was found to be the transmembrane pressure. On the other hand, the pH caused a significant variation around the mean S/N value for the membrane fouling parameter. The maximum variation level was determined as −1.5 for flux decline caused by fouling. Under the optimum conditions, the highest S/N value is desired. Therefore, the levels that gave the highest S/N value indicated the optimum conditions for the considered factors. We compared the S/N values (Figure 1) for different factors to determine the optimum operating conditions. The lowest membrane fouling occurred at the third level of pH (10), the first level of temperature (25 °C), the second level of transmembrane pressure (6 bar), and the first level of VRF (3). 3.3. Rejection Optimization. Rejections of total hardness, sulfate, conductivity, COD, and SAC254 were calculated based on the initial feed concentrations and the composite permeate concentrations obtained from the experiments performed according to the experimental plan. Mean rejections and corresponding S/N values are given in Table 4. The larger-the-better option (eq 7) was selected to maximize the rejections for the calculation of S/N ratios. The highest rejections were obtained in trial 9 for the analyzed parameters except for conductivity. The highest conductivity rejection occurred in trial 7, and the calculated rejection rates in trials 9 and 7 were close to each other. The mean S/N ratio for a single factor was calculated by averaging the values of the S/N ratios at different levels. The mean S/N ratio response curves are shown in Figure 2 for each rejection parameter. Overall mean S/N values were calculated as 27.18, 37.34, 23.37, 38.09, and 38.63 for the rejections of total hardness, sulfate, conductivity, COD, and SAC254, respectively. The factors with the lowest variations around the mean S/N values were transmembrane pressure for COD rejection and temperature and transmembrane pressure for SAC254 rejection (Figure 2). On the other hand, the variations around the mean S/N values were close to each other for the factors of temperature, transmembrane pressure, and VRF for the total hardness, sulfate, and conductivity rejections. The factor of pH caused significant variations around the mean S/N value for each rejection parameter. In other words, pH was more effective for rejection parameters than other factors. The maximum variation levels were determined as 19.49, 4.14, 20.28, 1.43, and 1.18 for total hardness, sulfate, conductivity, COD, and SAC254 rejections, respectively. The optimum operating conditions that achieved the highest rejections were determined as pH 10, temperature 25 °C, transmembrane pressure 6 bar, and VRF 3. 3.4. Effects of Operating Conditions on the Response Parameters. The effects of pH on the membrane fouling and rejection parameters are shown in Figures 1a and 2a, respectively. The highest S/N ratio was determined at pH 10, so lower membrane fouling and higher rejections were achieved at this pH value. Many factors affect the membrane separation performance. The electrostatic interactions between membrane surface charge and charged components in the feed solution play a crucial role in the rejection. Zeta potential measurements were carried out to determine the membrane surface charge at different pH values. Membranes are positively charged at pH values below the

Table 2. Taguchi L9 (34) Orthogonal Array of Selected Factors and Their Levels (Coded and Actual) trial no.

A

pH

B

temperature (°C)

C

transmembrane pressure (bar)

D

VRF

1 2 3 4 5 6 7 8 9

1 1 1 2 2 2 3 3 3

4 4 4 7 7 7 10 10 10

1 2 3 1 2 3 1 2 3

25 35 45 25 35 45 25 35 45

1 2 3 2 3 1 3 1 2

4 6 8 6 8 4 8 4 6

1 2 3 3 1 2 2 3 1

3 4 5 5 3 4 4 5 3

sulfate, conductivity, SAC254, COD) were chosen as the response parameters to evaluate the performance of UF membranes. 3.2. Membrane Fouling Optimization. According to the design of experiments based on the Taguchi method, filtration experiments of pulp and paper mill wastewater were performed using FM UP005 membranes. The measured mean fluxes and computed S/N ratios for each series of experiments are presented in Table 3. Because a lower flux decline is desirable Table 3. Experimental Results for Flux Decline and Corresponding S/N Ratios flux (L m−2 h−1) trial no.

J0

Jf

mean flux decline (%)

S/N ratio (dB)

1 2 3 4 5 6 7 8 9

161 265 339 205 303 229 244 205 297

88 127 159 106 170 101 137 119 178

45 52 53 48 44 56 44 42 40

−33.06 −34.32 −34.48 −33.62 −32.87 −34.96 −32.87 −32.46 −32.04

for minimum membrane fouling, the smaller-the-better option (eq 8) was chosen for the S/N ratio. As seen from Table 3, the highest flux decline (56%) caused by fouling occurred in trial 6. The Taguchi method employs graphs of the mean S/N ratio for every factor. The peak points in these graphs correspond to the optimum conditions. The S/N ratio for a single factor can be calculated by averaging the S/N ratios at different levels. The mean S/N ratio response curves of each factor for the response are shown in Figure 1.

Figure 1. Main effect plots for S/N ratios of flux decline caused by fouling: (a) pH, (b) temperature, (c) transmembrane pressure, (d) VRF. 6187



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Table 4. Experimental Results for Rejections and Corresponding S/N Ratios mean rejection rate (%)

S/N ratio (dB)

trial no.

total hardness

sulfate

conductivity

COD

SAC254

total hardness

sulfate

conductivity

COD

SAC254

1 2 3 4 5 6 7 8 9

8 10 3 41 43 20 64 45 70

74 72 71 67 68 44 97 89 97

4 4 3 24 27 20 43 30 41

80 71 70 84 85 75 87 85 88

82 80 80 85 86 80 92 91 94

18.06 20 9.54 32.26 32.67 26.02 36.12 33.06 36.90

37.38 37.15 37.02 36.52 36.65 32.87 39.73 38.99 39.73

12.04 12.04 9.54 27.60 28.63 26.02 32.67 29.54 32.26

38.06 37.02 36.90 38.48 38.59 37.50 38.79 38.59 38.89

38.28 38.06 38.06 38.59 38.69 38.06 39.27 39.18 39.46

interface that eventually reach the gelation concentration. The gel that is formed provides an additional hydraulic resistance and results in an increase in the osmotic pressure, causing an increase in the flux decline by reducing the driving force.33,34 As a result of concentration polarization, more particles cross the membrane because of the increasing difference in the concentration between the two sides of the membrane.35 Figures 1d and 2d show the effects of VRF on the response parameters. The highest S/N ratio was determined at VRF 3, so higher rejections were obtained at the lowest level of VFR. This behavior is typical of filtration in concentration mode, because an increase in VRF implies lower rejection according to diffusion control theory. 36 In this study, increasing VRF caused an increase in the pollutant concentration in the feed solution, which facilitates pollutant transport through the membrane, thus decreasing the rejection. At VRF 3, because the amount of pollutants passing through the membrane was lower, lower membrane fouling occurred. Thus, VRF 3 was determined as the optimum VRF level. 3.5. ANOVA Results. After performing the analysis of the S/N ratio, we carried out ANOVA to estimate the variance of the error (MSe) and determine the relative importance of various factors. The ANOVA was performed by separating the total variability into contributions from each of the design parameters and errors. The ANOVA procedure was employed by calculation of sum of squares (SS), degrees of freedom (DOF), mean of squares (MS), and associated F test of significance:37

isoelectric point, whereas they are negatively charged at pH values above the isoelectric point. 28 In the literature, it has been reported that zeta potentials become more negative as pH increases for PES membranes.29,30 According to this information, it was assumed that the surface charge of FM UP005 membrane should be negative at high pH values and that the negative charge density should increase as the pH increases. Also, many of the dissolved components in pulp and paper wastewater are negatively charged. 31 Assuming that the negative charge density of FM UP005 membrane increased at pH 10, the electrostatic repulsion forces between the membrane and negative charged compounds in the wastewater increased at this pH. Consequently, the components were rejected easily, and the highest rejections were obtained. Also, compounds might not accumulate on the membrane surface and/or within membrane pores with increasing repulsion forces. This behavior also explains the reduction in membrane fouling. Figures 1b and 2b show the effects of temperature on the response parameters. As the temperature increased, the S/N ratio decreased. At higher temperature (45 °C), higher membrane fouling and lower rejections were obtained. Temperature has a significant effect on permeability. Increasing temperature increases the solvent diffusion coefficient and thermal expansion of the membrane materials, which increases the permeation flux through the membrane.32 At higher temperature, increasing diffusion coefficient might facilitate the transport of pollutants through the membrane, and as a consequence, the pollutant concentration in the permeate would increase and the rejections would decrease. On the other hand, increasing amounts of pollutants resulted in a greater flux decline with accumulation of pollutants on the membrane surface and within the membrane pores. Therefore, 25 °C was determined as the optimum temperature level. The effects of transmembrane pressure on the membrane fouling and rejection parameters are shown in Figures 1c and 2c, respectively. As shown from the figures, the highest S/N ratio was achieved at 6 bar, whereas the lowest S/N ratio was determined at the lowest transmembrane pressure level (4 bar). Therefore, the highest rejections and the lowest membrane fouling were achieved at 6 bar. The S/N ratio decreased when the transmembrane pressure was increased from 6 to 8 bar. The lower rejections and higher flux declines obtained at 8 bar compared to 6 bar can be explained by concentration polarization. Increasing the transmembrane pressure enhances the formation of a higher-density cake/gel layer. Concentration polarization is the accumulation of macromolecules at the membrane

⎛ kA A 2 ⎞ T 2 SSA = ⎜⎜∑ i ⎟⎟ − N ⎝ i=1 n Ai ⎠

where kA is the number of levels of factor A, nAi is number of all observations at level i of factor A, Ai is sum of all observations of level i of factor A, and T is sum of all observations. SS of error is computed using equation SSe = SST − (SSA + SSB + ...)

(13)

the the the the (14)

where SST is the total SS N

SST =

∑ Yi 2 − i=1

T2 N

(15)

where Yi is the observation of i. MS is calculated by dividing the sum of squares by the degrees of freedom. DOFA is 6188



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Figure 2. Main effect plots for S/N ratios of (A) total hardness, (B) sulfate, (C) conductivity, (D) COD, and (E) SAC254 for (a) pH, (b) temperature, (c) transmembrane pressure, (d) VRF. 6189



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estimated as DOFA = kA − 1. The F value was calculated as follows: FA =

MSA MSe

of transmembrane pressures considered. The factor of pH had the highest percent contribution (49%) to the flux decline caused by fouling. pH was also the most important factor for all rejection parameters. This indicates that charge repulsion between the membrane and the pollutants in the wastewater was effective in the removal mechanism. The value of wastewater pH can change the membrane surface charge through the disassociation of the membrane’s functional groups and can therefore affect the membrane separation performance. 3.6. Verifying the Results. Examination of Table 2 shows that the optimum conditions (pH 10, temperature 25 °C, transmembrane pressure 6 bar, VRF 3) were not applied in any of the trials in the experimental design. Therefore, a confirmation experiment was performed with a combination of the optimum levels to determine and verify predicted results. Figure 4 shows the permeate flux as a function of VRF under optimized conditions during UF of pulp and paper mill wastewater. During the early period of filtration, the permeate flux decreased slowly until the VRF value reached to 2, after which it remained almost constant for higher VRF values. The pure-water flux (Jf) of the fouled membrane was measured as 134 L m−2 h−1 in the confirmation experiment. The flux decline caused by fouling was calculated as 35% using the measured Jf (134 L m −2 h −1) and J0 (205 L m−2 h−1) values. The pollutant concentrations of the composite permeates obtained with the FM UP005 membrane under optimized conditions were 80 mg L−1 CaCO3, 5 mg L−1, 600 μs cm−1, 6 m−1, and 90 mg L−1 for total hardness, sulfate, conductivity, SAC254, and COD, respectively. The observed results, the calculated predicted results, and the 95% confidence intervals for response parameters are reported in Table 7. As can be seen from Table 7, there is good agreement between the predicted and observed results, indicating that the additive model is adequate for describing the depence of membrane fouling and rejections on the selected operating conditions. Also, the experimental results are within a ±5% error range, confirming that the effects of interactions among parameters are indeed negligible.20 3.7. AFM and SEM Characterizations of Clean and Fouled Membranes. Membrane fouling can be explained using the information provided by AFM and SEM images. AFM and SEM analyses were used to evaluate the deposition of pollutants onto the membrane surface and membrane pores, respectively. Because pH was the most important factor for flux decline according to the ANOVA results, AFM and SEM measurements were carried out for membranes at different pH values. The membrane samples selected for the analyses were as follows: (a) FM UP005 membrane before filtration; (b) FM UP005 membrane after filtration at pH 4, for which the highest membrane fouling (53%) occurred; (c) FM UP005 membrane after filtration at pH 7, for which intermediate membrane fouling (48%) occurred; and (d) FM UP005 membrane after filtration at pH 10, for which the lowest membrane fouling (40%) occurred. Figure 5 shows AFM images of the selected FM UP005 membranes. The roughness parameters (Ra, Rrms, and Rz) of the surfaces examined by AFM measurements at different pH values are also included in Figure 5.

(16)

where MS e is the variance of error. Also, the pure sums (S′) and percent contributions (P) of the factors were computed using the equations SA′ = SSA − (MSeDOFA )

(17)

SA′ SST

(18)

PA (%) =

respectively. The results of ANOVA for the parameters of membrane fouling and rejections are presented in Tables 5 and 6, respectively. Table 5. Results of ANOVA for Flux Decline Caused by Fouling factor pH temperature transmembrane pressure VRF error total

DOF

SS

MS

F ratio

pure sum (Sı)

P (%)

2 2 2

118.2 29.5 1.5

59.1 14.75 −

78.8 19.7 pooled

116.7 28 −

48.85 11.72 −

2 2 8

89.5 1.5 238.9

44.75 0.75

59.7

88

37.46 1.97 100

The F ratio was employed to examine the significance of the factors in the ANOVA. It was calculated from the experimental results using eq 16 and compared to the critical F value (Fcr), which can be found in most statistics and experimental design books.18 If the calculated F ratio is greater than the Fcr value, the statistical test is significant at the selected confidence level. In the study, pooled ANOVA was applied to eliminate the zero DOF from the error term. The details of pooled ANOVA were described in a previous study.21 The Fcr value with the appropriate numbers of degrees of freedom for the error (2) and degrees of freedom for the factors (2) was determined (F0.05;2,2) as 19 at a confidence level of 95%. When the F ratios were compared with the Fcr value, it was seen that the effects of pH, temperature, and VRF were significant at the 95% confidence level and were meaningful in terms of membrane fouling (Table 5). Analysis of Table 6 indicates that the effects on the total hardness, conductivity, and SAC 254 rejections of only pH are significant at the 95% confidence level. However, the effects of pH, temperature, and VRF on the COD rejection are significant. On the other hand, none of the factors were found to have statistically meaningful effects on sulfate rejection. It is thus thought that sulfate rejection occurs independent of the operating conditions. Percent contributions, defined as the ratio of the pure sum of the factors to the total sum of squares, of all factors are presented in Figure 3. As can be seen from Figure 3, the percent contribution of transmembrane pressure was negligible for flux decline caused by fouling. This might be because of the low range 6190



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Table 6. Results of ANOVA for Rejections factor

DOF

F ratio

pure sum (Sı)

P (%)

57.67 pooled 5.84 2.74

4092 − 349.3 125.4

84.3 − 7.19 2.58 5.93 100

Sulfate 923.1 58.1 93.4 − 56.4

16.37 1.03 1.66 pooled

1733.4 3.4 74 −

76.62 0.15 3.27 − 19.96 100

Conductivity 892.1 − 33.45 19.45 8.75

101.9 pooled 3.82 2.2

1766.7 − 49.4 21.4

92.61 − 2.59 1.12 3.68 100

COD 128.1 27.1 − 35.1 0.75

170.8 36.1 pooled 46.8

254.7 52.7 − 68.7

66.64 13.79 − 17.97 1.6 100

SAC254 110.1 − 3.4 8.2 2.1

52.43 pooled 1.62 3.9

216 − 2.6 12.6

87.03 − 1.05 5.08 6.84 100

SS

pH temperature transmembrane pressure VRF error total

2 2 2 2 2 8

4164.2 72.2 421.5 197.6 72.2 4855.6


2 2 2 2 2 8

1846.2 116.2 186.8 112.8 112.8 2262.2


2 2 2 2 2 8

1784.2 17.5 66.9 38.9 17.5 1907.6


2 2 2 2 2 8

256.2 54.2 1.5 70.2 1.5 382.2


2 2 2 2 2 8

220.2 4.2 6.8 16.8 4.2 248.2

MS Total Hardness 2082.1 − 210.75 98.8 36.1

Figure 3. Percent contributions of various factors to the response parameters.

The clean membrane (Figure 5a) had a smooth surface, whereas morphological variations occurred on the fouled membranes (Figure 5b−d) as a result of the accumulation of pollutants. This accumulation on the membrane surface increased as the pH decreased. From the data in Figure 5, it can be seen that the lowest and the highest Ra, Rrms, and Rz values compared to those of the clean membrane were obtained at pH 10 and pH 4, respectively. Therefore, the fouling on the surface of the membrane was rather lower at pH 10 compared to the other pH values. The flux declines

Figure 4. Permeate flux as a function of VRF under optimized conditions during UF of pulp and paper mill wastewater (pH 10, temperature 25 °C, transmembrane pressure 6 bar, VRF 3, cross-flow rate 2 L min−1).

decreased from 53% to 40% when the pH was increased from 4 to 10. The SEM images of the same clean and fouled membranes at different pH values are presented at Figure 6. It can be clearly 6191



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repulsion forces between the membrane and the negatively charged compounds in the wastewater. Figure 7 shows AFM and SEM images of fouled FM UP005 membranes after filtration under optimized conditions. According to Figure 7a, it can be said that the fouled membrane looks similar to the clean membrane. However, morphological variations were observed because of the fouling. The Rrms value of the fouled membrane was determined to be 4.64 nm, which is greater than that of the clean membrane (2.26 nm) because of surface fouling. As can be seen from the SEM image of the fouled membrane (Figure 7b), the size of the pores seemed to remain unchanged, but some pores disappeared as a result of pore clogging. This result shows that, even though the operating conditions were optimized, pore clogging can occur for the filtration of pulp and paper wastewater by UF.

Table 7. Observed Results, Calculated Predicted Results, and Confidence Intervals for Response Parameters parameter Flux decline caused by fouling total hardness rejection sulfate rejection conductivity rejection SAC254 rejection COD rejection

observed result (%)

predicted result (%)

confidence interval (%)

35

36

3−91

83 96.6 50 95 89

75 96.9 45 94 91

62−85 95.9−97.7 15−80 59−99 36−99

seen from Figure 6 that pore narrowing and pore clogging occurred at all pH conditions. Notably, the pores of the membrane that was fouled at pH 4 almost disappeared with additional pore clogging. This effect was attributed to decreasing

Figure 5. AFM images of clean and fouled FM UP005 membranes at different pH values: (a) clean membrane, (b) pH 4, (c) pH 7, (d) pH 10. 6192



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transmembrane pressure level (4 bar). The highest rejections and the lowest membrane fouling were achieved at 6 bar. The S/N ratio decreased when the transmembrane pressure was increased from 6 to 8 bar because of concentration polarization. This phenomenon resulted in an increase in the osmotic pressure, and the difference in the concentration between the two sides of the membrane caused decreasing rejections and an increasing flux decline. The highest S/N ratio was determined at VRF 3. Increasing the VRF caused an increase of the pollutant concentrations in the feed solution, which facilitated the transport of the pollutants through the membrane, thus decreasing the rejections. Also, because the amounts of pollutants passing through the membrane were lower at VRF 3, lower membrane fouling occurred. Therefore, the optimum conditions were achieved when pH was at its highest level (10), temperature (25 °C) and VRF (3) were at their lowest levels, and transmembrane pressure was at its medium level (6 bar) for all response parameters. Close agreement between the predicted results and the observed results was obtained from the confirmation experiment. This indicates that the additive model is adequate for describing the depence of membrane fouling and rejections on the selected operating conditions. Also, it can be concluded that the Taguchi method is suitable for finding the optimum conditions for the treatment of pulp and paper mill wastewater using the UF process. From the ANOVA analysis, it was determined that the factor of pH had the greatest effects among all factors on the response parameters. The lowest and highest Ra, Rrms and Rz values compared to those of the clean membrane were obtained at pH 10 and pH 4, respectively. These results were supported by measurements of the flux decline caused by fouling. SEM images of clean and fouled membranes at different pH values showed that pore narrowing and pore clogging occurred at all pH values. This effect was clear at pH 4 because of additional pore clogging. Also, AFM and SEM measurements of fouled FM UP005 membranes after filtration under optimized conditions were carried out. It was determined that the membrane fouling that occurred on the membrane surface and within the pores decreased by optimizing the operating conditions based on these measurements. However, some pores disappeared as a result of pore clogging. Under the optimized conditions, a 35% flux decline was caused by fouling. It might thus be concluded that optimization of the operating conditions was not quite efficient in decreasing the membrane fouling. However, the FM UP005 membrane demonstrated very high removal of total hardness (83%), sulfate (97%), SAC254 (95%), and COD (89%) for pulp and paper wastewater treatment under the optimized conditions. However, conductivity rejection was 50%. Although UF is relatively efficient in generating permeate that can be used for different purposes such as shower water of paper machine and process water, conductivity rejection could be improved by including an additional nanofiltration (NF) or reverse osmosis (RO) process.

Figure 6. SEM images of clean and fouled FM UP005 membranes at different pH values: (a) clean membrane, (b) pH 4, (c) pH 7, (d) pH 10.

Figure 7. (a) AFM and (b) SEM images of fouled FM UP005 membranes under optimized conditions.

4. CONCLUSIONS In this study, application of the Taguchi method was investigated for the treatment of pulp and paper mill wastewater using the UF process. The Taguchi method was applied to determine the optimum operating conditions that achieved the highest removal of pollutants and lowest membrane fouling with a minimum number of experiments. For the calculation of S/N ratios, the smaller-the-better and larger-the-better options were selected to minimize the membrane fouling and maximize the rejections, respectively. Considering the S/N ratios for the factor of pH, it was found that the best results, in terms of the highest rejections and lowest membrane fouling, were obtained at pH 10, presumably because the negative charge density of the FM UP005 membrane increased at this pH value. As the temperature was increased from 25 to 45 °C, the S/N ratio decreased for all response parameters. An increase in the diffusion coefficient with increasing temperature might facilitate the transport of pollutants through the membrane, resulting in an increase in the pollutant concentration in the permeate. This case also caused a greater flux decline with accumulation of pollutants on the membrane surface and clogging within the membrane pores. The lowest S/N ratio was determined at the lowest

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AUTHOR INFORMATION

Corresponding Author

*Tel.: +90 212 4737070. Fax: +90 212 4737180. E-mail: [email protected]. Notes

The authors declare no competing financial interest. 6193



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ACKNOWLEDGMENTS This work was supported by the Research Fund of Istanbul University (Project T-952/06102006).

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NOMENCLATURE Ai = sum of all observations of level i of factor A A̅ i = average of responses at level i of factor A Am = effective membrane area (m2) ACF = acidic clear filtrate AFM = atomic force microscopy ANOVA = analysis of variance B̅ j = average of responses at level j of factor B Cf = concentration of a particular component in the feed wastewater (mg L−1) Cp = concentration of a particular component in the permeate (mg L−1) CI = confidence interval CMF = concentration mode of filtration COD = chemical oxygen demand (mg L−1) DOE = design of experiment DOF = degrees of freedom DOFe = degrees of freedom of error Fcr = critical F value FTIR = Fourier transform infrared kA = number of the levels of factor A J = permeate flux (L m−2 h−1) J0 = pure-water flux of the clean membrane (L m−2 h−1) Jf = pure-water flux of the fouled membrane (L m−2 h−1) Js = wastewater flux (L m−2 h−1) m = degrees of freedom used in the prediction of Yopt MF = microfiltration MS = mean of square (variance) MSe = variance of error MWCO = molecular weight cutoff (Dalton) n = number of repetitions performed for an experimental combination nAi = number of all observations at level i of factor A N = total number of all observations NF = nanofiltration OA = orthogonal array Q = cross-flow rate (L min−1) P = percentage of the product obtained experimentally PES = polyethersulfone PS = polysulfone R = rejection of feed components (%) Ra = mean roughness of the membrane surface (nm) Rrms = root-mean-square of average height of membrane surface peaks (nm) Rz = mean difference between five highest peaks and lowest valleys (nm) RC = regenerated cellulose RO = reverse osmosis S = sample size for confirmation test Sı = pure sum SAC254 = spectral absorption coefficient SEM = scanning electron microscopy S/N = signal-to-noise ratio SS = sum of squares SST = total sum of squares t = filtration time (min) T = sum of all observations UF = ultrafiltration

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Vc = final volume of the concentrate (L) Vf = initial volume of feed (L) Vp = total volume of permeate (L) VRF = volume reduction factor Yi = observation of i Yopt = performance value corresponding to the optimum working conditions Ω = percentage value subject to omega transformation (dB)

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Treatment of Pulp and Paper Mill Wastewater Using Utrafiltration

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