# Characterization of fouling mechanism during membrane bio-reactor (MBR) process for industrial wastewater treatment

Bahman Nazari, Mohsen Taghavijeloudar

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Bahman Nazari, Mohsen Taghavijeloudar. Characterization of fouling mechanism during membrane bio-reactor (MBR) process for industrial wastewater treatment. 4th Internationa Congress on Engineering, Technology and Innovation, Sep 2022, Darmastadt, Germany. hal-04363016

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# Characterization of fouling mechanism during membrane bio-reactor (MBR) process for industrial wastewater treatment

Bahman Nazariª, Mohsen Taghavijeloudar*

ª Department of Chemical Engineering, Babol Noshirvani University of Technology, P.O.B. 484, Babol, Iran, Bn.nazari1991@gmail.com

ᵇ Department of Civil and Environmental Engineering, Seoul National University, 151-744, Seoul, South Korea, mohsen@snu.ac.kr

## Abstract

Pulp and paper industry is known as the third-largest consumer of water quantities, generating about 70-150 m³ wastewater per ton of paper produced. Membrane bioreactor (MBR) technology is one of the promising methods for pulp and paper wastewater (PPWW) treatment. However, membrane fouling is remain as the main obstacle of the MBR process. In this research, the fouling mechanism during membrane bioreactor (MBR) was characterized using classical blocking models (Cake filtration, standard blocking, intermediate and complete blocking). To do this, the degree of membrane clogging at a constant flux of 1.5 LMH was studied by measuring the changes in trans-membrane pressure (TMP) increase using real industrial and synthesized wastewater. Based on the results, the pressure increased from 20 to 84 kPa and 10 to 31 kPa for real and synthesized wastewater respectively, during 30 days of treatment. The modelling simulation revealed that fouling mechanism matched with intermediate blocking model during the first stage and then followed by cake filtration mechanism and ended up with complete blocking mechanism. These results may be due to the presence of more organic matter and suspended solids in the industrial effluent, which increase the pressure by covering the surface of the membrane.

**Keywords:** Pulp and paper, Membrane bioreactor, fouling, Wastewater treatment
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# 1. INTRODUCTION

Pulp and paper industry is known as the third-largest consumer of water quantities, generating about 70-150 m³ wastewater per ton of paper produced [1]. Pulp and paper wastewater (PPWW) contains high level of chemical oxygen demand (COD), turbidity, heavy metals and more than 250 dangerous chemicals such as tannins, resin acids, unsaturated fatty acids, chlorinated resin acids, chlorate ions, dioxins, furans, chlorophenol, acetone, sulfur compounds and color [2-5] [24-26]. Releasing the untreated pulp and paper wastewater (PPWW) to environmental ecosystems leads to severe problems: contaminating water and soil ended up harm human health. Several methods have been proposed for PPWW treatment (PPWWT) including physicochemical treatment methods [6], biological methods [7], sedimentation [8], flotation [9], electrolysis [10], adsorption [11] ozonation [12], reverse osmosis [13], ultrafiltration, nanofiltration [14] and coagulation/flocculation [15]. The conventional wastewater treatment methods have some disadvantages that limits their application in large-scale like not being cost effective, long contact time, and their difficulty to operate [16].

Among the different treatment methods, MBR has received great attention due to its simplicity, low cost and relatively high efficiency [23]. An MBR combines an activated sludge process with a physical separation by membrane [22]. Compared with conventional activated sludge (CAS) process, the MBR technique has many advantages, including high efficiency, less sludge production, high disinfection ability and also small footprint [17]. One of the main obstacle in MBR process for WWT is membrane fouling [18]. Membrane fouling causes due to pore clogging and bio-film formation over membrane surface during MBR process [19]. The fouling mechanism defines by the exponent N in classical blocking model [20]:

$$ \frac{d^2 t}{dV} = k \left( \frac{dt}{dV} \right)^N $$

Where, t is membrane time, V is permeate volume and k is a fitting parameter [21]. Although several research have been conducted regarding membrane fouling during MBR process, a limited study focused on the fouling mechanism variation during MBR process.

Therefore, in this research we characterized the fouling mechanism during membrane bioreactor (MBR) using classical blocking models. To do this, the changes in pressure (TMP) level were recorded during MBR process of real industrial and synthesized wastewater treatment under a constant flux of 1.5 LMH. Model evaluation has been performed using statistical analysis of standard deviation (σ) and mean relative deviation (SSD).
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## 2. Materials and Methods

The raw pulp and paper recycling wastewater (PPWW) samples were obtained from the Pouya Ayesh Mazand paper mill in Raja industrial park of Babol, Mazandaran province, Iran at latitude of 36°21'54.3"N and a longitude of 52°37'49.7"E. Sample collection was carried out manually during daytime for 20 weeks and all samples were transferred in three polyethylene containers to the laboratory. Then they were cooled to room temperature before refrigerating them at 4 °C to reduce biodegradation owing to biological activity. The characteristics of the wastewater samples were determined using the standard methods of American Public Health Association (APHA, 2012) as pH = 6.68 ± 0.3, total suspended solids (TSS) = 720 ± 30 mg/L, chemical oxygen demand (COD) = 4500 ± 350 mg/L, biological oxygen demand (BOD) = 2100 ± 150 mg/L, turbidity = 1550 ± 25 (NTU), and conductivity = 620 ± 30 ms/cm.

The schematic of the MBR is shown in Figure 1. The membrane fouling mechanism was evaluated using classical blocking model for constant flux and table (1):

$$ \frac{dp}{dV} = kP^N $$

<table><caption>**Table 1: Classical blocking models**</caption><thead><tr><td>N power</td><td>Model</td><td>P = F(t, J)</td></tr></thead><tbody><tr><td>N = 0</td><td>Cake filtration</td><td>P/P₀ = 1 + k_c J₀ t</td></tr><tr><td>N = 1</td><td>Intermediate</td><td>P/P₀ = e<sup>k_i t</sup></td></tr><tr><td>N = 3/2</td><td>Standard</td><td>P/P₀ = (1 - k_s Jt/2)<sup>-2</sup></td></tr><tr><td>N = 2</td><td>Complete</td><td>P/P₀ = (1 - k_b Jt/J₀)<sup>-1</sup></td></tr></tbody></table>

TMP was measured using a pressure meter in outlet pipe. All experiments were carried out in triplicates. Model evaluation was done based on MRE: Mean relative deviation, SSD: Sum of squared deviation, σ: Standard deviation and R² = R-Squared

<figure><img src="image_7.png" /><figcaption>**Figure1.** Schematic diagram of the new MBR</figcaption></figure>
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# 3. Results and discussion

## 3.1. Fouling characterization of real wastewater

Figure 2 shows the TMP variation (the circles) and modelling simulation (the lines) in the MBR during 30 days real wastewater treatment process. The TMP in the reactor increased gradually during the initial 5 days which was matched better with intermediate blocking models (N=1). After 5 days up to 20 day, the TMP rate rapidly enhanced and showed perfect agreement with cake filtration model (N=0) indicating that a bio-film formed on top of the membrane. During the last stage of MBR process (5 last days) the TMP variation showed a good agreement with complete blocking model (N = 2).

<figure><img src="image_9.png" /><figcaption>**Figure 2.** TMP (a) variation during PPWW treatment using MBR and (b) modeling evaluation</figcaption></figure>

Statistical analyses of the models evaluation during the whole MBR process is shown in Table 2. According to Table 2, intermediate model showed the best match with the experimental data

<table><caption>**Table 2: Statistical analysis of models evaluation during real WWT**</caption><thead><tr><td>N power</td><td>Model</td><td>Fitting parameter</td><td>MRE</td><td>SSD</td><td>σ</td><td>R<sup>2</sup></td></tr></thead><tbody><tr><td>N = 0</td><td>Cake filtration</td><td>K<sub>c</sub> = 170000</td><td>0.051</td><td>16.689</td><td>4.085</td><td>0.9738</td></tr><tr><td>N = 1</td><td>Intermediate</td><td>K<sub>i</sub> = 0.225</td><td>0.0541</td><td>8.2784</td><td>2.8772</td><td>0.9857</td></tr><tr><td>N = 3/2</td><td>Standard</td><td>K<sub>s</sub> = 0.175</td><td>0.0865</td><td>16.5578</td><td>4.0691</td><td>0.9649</td></tr><tr><td>N = 2</td><td>Complete</td><td>K<sub>b</sub> = 0.0015</td><td>0.1878</td><td>53.3463</td><td>7.3039</td><td>0.9356</td></tr></tbody></table>
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## 3.1. Fouling characterization of synthesized wastewater

Figure 3 shows the TMP variation (the circles) and modelling simulation (the line) in the MBR during 30 days of synthesized wastewater treatment process. Similar to real wastewater, The TMP in the reactor increased gradually during the initial 7 days indicating following intermediate blocking models (N=1). After the first week and up to 20 day, the TMP rate increased and matched better with cake filtration model (N=0) indicating that a bio-film formed on top of membrane surface. During last stage the TMP variation showed a good agreement with complete blocking model (N = 2).

<figure><img src="image_11.png" /><figcaption>**Figure 3.** TMP (a) variation during PPWW treatment using MBR and (b) modelling evaluation</figcaption></figure>

Statistical analyses of the models evaluation during the whole MBR process is shown in Table 2. According to Table 3, intermediate model showed the best match with the experimental data

<table><caption>**Table 3: Statistical analysis of models evaluation during synthesis WWT**</caption><thead><tr><td>N power</td><td>Model</td><td>Fitting parameter</td><td>MRE</td><td>SSD</td><td>σ</td><td>R<sup>2</sup></td></tr></thead><tbody><tr><td>N = 0</td><td>Cake filtration</td><td>K<sub>c</sub> = 150000</td><td>0.025</td><td>0.656</td><td>0.810</td><td>0.9896</td></tr><tr><td>N = 1</td><td>Intermediate</td><td>K<sub>i</sub> = 0.21</td><td>0.0388</td><td>1.0775</td><td>1.0380</td><td>0.9875</td></tr><tr><td>N = 3/2</td><td>Standard</td><td>K<sub>s</sub> = 0.16</td><td>0.0589</td><td>2.1842</td><td>1.4779</td><td>0.9736</td></tr><tr><td>N = 2</td><td>Complete</td><td>K<sub>b</sub> = 0.000000265</td><td>0.0885</td><td>4.3855</td><td>2.0942</td><td>0.9419</td></tr></tbody></table>
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### 3.3. TMP variation during PPWW treatment of real and synthesized

In MBRs process, The TMP variation is one of the most important factors to evaluate the system performance. The online monitoring of TMP was carried out during the 30 days operation of new MBR for both real wastewater (RWW) and synthesized wastewater (SWW). Figure 4 shows a comparison of the TMP variation for RWW and SWW during the 30 days operation of reactor. The TMP was increased gradually from 20 to 84 and 10 to 31 kPa for RWW and SWW respectively, during 30 days of PPWT wastewater treatment. The higher TMP level in the case of real wastewater might be attributed to the higher MLSS and the presence of organic matters results in higher EPS and SMP lever in real wastewater in comparison with synthesized wastewater.

<figure><img src="image_13.png" /><figcaption>**Figure 4.** TMP and flux variation during PPWW treatment using new MBR</figcaption></figure>

### 4. Conclusion

In this research, the fouling mechanism during membrane bioreactor (MBR) was characterized by using classical blocking models. Based on the results, the pressure increased from 20 to 84 and 10 to 31 kPa for real and synthesized wastewater respectively, during 30 days of treatment. The modelling simulation revealed that fouling mechanism matched with intermediate blocking model during the first stage and then followed by cake filtration mechanism and ended up with complete blocking mechanism. These results may be due to the presence of more organic matter and suspended solids in the industrial effluent, which increase the pressure by covering the surface of the membrane.
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