Performance of Horizontal Roughing Filter forColour Removal of Palm Oil Mill E�uent UsingNatural AdsorbentArezoo Fereidonian Dashti  ( arezoodashti@yahoo.com )

Universiti Sains MalaysiaHamidi Abdul Aziz 

Universiti Sains Malaysia - Engineering Campus Seri Ampangan: Universiti Sains Malaysia - KampusKejuruteraan Seri AmpanganMohd Nordin Adlan 

Universiti Sains Malaysia - Engineering Campus Seri Ampangan: Universiti Sains Malaysia - KampusKejuruteraan Seri AmpanganAli Huddin Ibrahim 

Universiti Sains Malaysia - Engineering Campus Seri Ampangan: Universiti Sains Malaysia - KampusKejuruteraan Seri Ampangan

Research Article

Keywords: Calcination, Raw Limestone, Central Composite Design, Isotherm study, Palm Oil Mill E�uent

Posted Date: April 26th, 2021

DOI: https://doi.org/10.21203/rs.3.rs-252985/v1

License: This work is licensed under a Creative Commons Attribution 4.0 International License.  Read Full License

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Performance of Horizontal Roughing Filter for Colour Removal of Palm Oil Mill Effluent 3

Using Natural Adsorbent 4

Arezoo Fereidonian Dashti1*, Hamidi Abdul Aziz1, Mohd Nordin Adlan2, Ali Huddin Ibrahim1

1School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal,

Penang, Malaysia 2Solid Waste Management Cluster, Science and Technology Research Centre, Engineering Campus, Universiti

Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia

5 *Corresponding author at: School of Civil Engineering, Universiti Sains Malaysia, Nibong Tebal, Seberang Perai 6

Selatan, Pulau Pinang, 14300, Malaysia. E-mail address: arezooferei3@gmail.com 7

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Abstract 10

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Palm oil wastewater treatment was investigated via a filtration process using raw and calcinated limestone. The 12

column studies were conducted using different limestone sizes (4, 12, and 20 mm), calcination temperature (800 13

°C and 600 °C) and various filtration rates (20, 60, and 100 mL/min) and a comparison was made with raw limestone 14

under similar conditions. The response surface methodology using central composite design was employed to 15

optimize the process parameter. The experimental data was analyzed via the analysis of variance to identify the 16

interaction between the parameters and the dependent parameter. The results showed that the colour removal 17

increased with an increase in temperature (800 ºC) for filtration rate of 20 mL/min, the retention time of 317 min 18

and the smaller size (4 mm) of limestone and decreased with an increase in the filtration rate and size of raw 19

limestone. Based on the achieved results, the optimum condition for colour removal was at temperature 800 °C (61%), 20

600 oC (56%) and raw limestone (49%) respectively with the same experimental setup (flow rate of 20 mL/min and 21

limestone size of 4 mm). According to the statistical analysis, quadratic models demonstrated significant values 22

(0.000) for the response (colour). Freundlich and Langmuir isotherms also provided good correlation coefficient for 23

the colour removal. The data conforms to the Langmuir isotherm with the best fit model (R2=0.7). 24

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Keywords: Calcination; Raw Limestone, Central Composite Design, Isotherm study, Palm Oil Mill Effluent 28

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1. Introduction 31

Palm oil industry is considered as an agro-based industry that provides positive economic impact worldwide 32

and to Malaysia specifically (Nasrullah et al. 2017; Bello and Raman 2017). It is reported that the worldwide 33

production of palm oil was over 70 million metric tonnes in 2018, and it is anticipated to exceed 75 million metric 34

tonnes in 2020 (Hayawin et al. 2020). The production of one tonne of crude palm oil needs 5-7.5 tonnes of water and 35

more than half of it is discharged as wastewater called palm oil mill effluent (POME) (Dashti et al. 2020; Sani et al. 36

2020; Bello et al. 2017). Palm Oil Mill Effluent (POME) is characterized as a thick liquid that contains high organic 37

contents with brownish colour and strong smell. It also contains Biochemical Oxygen Demand (BOD), Oil and Grease 38

(O&G), high concentration of Chemical Oxygen Demand (COD), Suspended Solid (SS) and total solids. The 39

discharge of POME without proper treatment imposes serious pollution to the environment (Hossain et al. 2019; 40

2

Bashir et al. 2019; Fereidonian et al. 2018). The colour is formed by refractory compounds of natural organic matter, 41

such as tannins, phenolic compounds, and melanoidin (generated by heating organic oil from the extraction process) 42

(Limkhuansuwan and Chaiprasert 2010). The discharge of brownish colour wastewater into the water bodies can cause 43

adverse effects to aquatic lives by filtering the light passing through which results in less photosynthesis activity and 44

less dissolved oxygen in the water (Ratpukdi 2012). The most usual technology to treat POME is the biological 45

treatments using aerobic or an anaerobic ponding process, due to its low operating cost (Lawal et al. 2020). On the 46

other hand, the biological treatment is a long process, since it requires an extended treatment time to degrade the 47

organic particles (Kim et al. 2020; Chung et al.,2018; Lek et al. 2018). Moreover, lack of regulative control on 48

emission of greenhouse gases caused by biological treatment process is the main drawback of the available and 49

existing POME treatment process (Khadaroo et al. 2019). The process of biological wastewater treatment is ranked as 50

the second-largest producer of greenhouse gases in Malaysia. Gases produced by the biological treatment process are 51

odorous and corrosive as they contain ammonia and hydrogen sulfide (Mat et al. 2020; Hossain et al. 2019; Bakar et 52

al. 2018). The ponding system is also influenced because of the excessive organic load and low pH in addition to the 53

colloidal nature of the suspended solids in POME (Nahrul et al. 2017). Consequently, COD, residual BOD, turbidity 54

and SS concentration in treated POME do not meet the standard discharge constraints for industrial effluents provided 55

by Department of Environment (DOE), Malaysia (Jagaba et al. 2020; Bashir et al. 2019; Dashti et al. 2019). Alternative 56

methods were applied on POME treatment such as membrane, membrane bioreactor, physicochemical, ozonation, and 57

aerobic systems. However, these systems were not implemented in large scale due to operational problems such as 58

scum formation, sludge flotation, or high-energy requirements from the treatment system (Saeed et al. 2015). In this 59

research, we used POME from a polishing pond. After measuring the parameters, it was confirmed that physical 60

treatment could be used because the amount of BOD over COD was less than 0.1. 61

62

The features such as being chemical-free, being high solid retention capacity, having simple management and 63

low-cost maintenance are the highlighted benefits of Roughing Filter (RF) (Khazaei et al.,2016). Usually, RFs are 64

filled with the media of diameter ranging from 4 mm to 30 mm and operate at low hydraulic load varying from 0.3 m 65

h−1 to 1.5 m h−1 (Zeng et al. 2018; Khezri et al. 2015). During RF process, particles are removed if they are smaller 66

than the filter media. The particle removal is efficient when particles are successfully transported and attached on the 67

surface area of the media (or collector). This is defined by the approach to design deep-bed filters and is an estimate 68

using colloid filtration theory (CFT) (Watanabe et al 2002). When a particle is carried by gravitational settling from 69

its fluid streamline to a collector surface, sedimentation (ŋG) takes place. Sedimentation can be calculated by (1) 70

(Watanabe et al. 2002): 71

72

ŋ" =$%&'%()+,&

-

./0ʋ (1) 73

In (1), the fluid density, particle density, gravitational constant and the average particle diameter are presented by 74

𝜌3(gm/𝑐𝑚:), 𝜌<(gm/𝑐𝑚:), g (cm/ s2) and 𝑑<(cm) respectively. µ (gm/cm/s) is the fluid dynamic viscosity and v 75

(cm/s) is the fluid approach velocity. 76

Due to porosity, various physicochemical properties and particularly surface area of the filter media plays an important 77

role on RFs process (Lin et al. 2008). Various materials have been used as filter media, such as broken brick, various 78

gravel, charcoal (Ochieng et al. 2006), sand (Lin et al.,2008) and plastic (Nkwonta 2010). Limestone is one of the 79

most well-known media utilized in RF. The physical structure of limestone deteriorates quickly when it is calcinated 80

at the temperature of 600 °C. Under mentioned condition, both the peak stress and the coefficient of elasticity decrease 81

quickly which results in more cracks, porosities and enlargement of the surface area (Dashti et al. 2019; Zhang et al. 82

2017), and finally, leads to more absorption ability. This research aims to reduce the colour in polishing pond of 83

POME using calcinated limestone. Hence, the conditions for calcinating various sizes of limestone in different flow 84

rates were optimized using Central Composite Design (CCD) and Response Surface Methodology (RSM). The novelty 85

of this research lies in the use of the calcinated limestone to improve adsorption capabilities. Filter performance was 86

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also systematically studied with the aim of developing an effective new treatment technology for POME polishing 87

pond. 88

89

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2. Materials and Methods 91

2.1 POME Sampling, Analysis and Preservation 92

The final discharge effluent of an open anaerobic pond (polishing pond), belonging to MALPOM Industries 93

located in Malaysia, was selected to be used in this research. Hanna HI8314 portable pH meter was used to measure 94

the pH of the POME on-the-location of MALPLM. During the process of sampling and transporting POME to the 95

laboratory, in order to keep it away from light exposure, 25-L black and air-tight container was used. In the laboratory, 96

the POME was immediately stored in cooling room (4 ºC) to be preserved for future biological activities. The COD 97

removal was evaluated based on APHA Standard Method 5220D, program 435 COD HR, HACH DR/ 2800 98

spectrophotometer while turbidity was measured by the method 2130B (APHA 2005) using HACH 2100Q 99

Turbidimeter. The colour was determined by the method 2120C (APHA 2005), Platinum-Cobalt Standard. Ammonia 100

nitrogen-Nessler method coupled with HACH DR/ 2800 spectrophotometer were used to measure Ammonia nitrogen. 101

102

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2.2 Filter Design and Operation 104

The horizontal filter is an acrylic column which is 75 cm wide, 20 cm long, and 9 cm high (Table 1). Raw and 105

calcinated limestones with various sizes are used as a filter media during the process. The column study was run by 106

passing the POME through the horizontal filter (Fig. 1a) with 3 different filtration rates of 100, 60 and 20 mL/min. In 107

order to create different flow rates, Masterflex pump with capacity of 2000 mL/min was used to carry POME from 108

the tank to the horizontal roughing filter. The filtration process was carried out by taking samples from the inlet and 109

the outlet both prior to and after the retention time for different filter media sizes and flow rates over seven successive 110

days. 111

Colour removal efficiency percentage from POME was calculate by the following equation: 112

113

P = @A'@B@A

× 100 (2) 114

115

where C0 (PtCo) and C1(PtCo) represent the concentration of colour in influent and effluent of POME, respectively. 116

117

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2.3 Calcination Limestone Process 119

The natural limestone used in the experiment was produced by a marble factory in Ipoh, Malaysia. The limestone 120

is crushed into 3 different small sizes of 20, 12 and 4 mm. After that, they were sieved to be uniform in terms of size, 121

between 4 mm and 20 mm using a sieve. They were washed to remove any impurities and then dried at room 122

temperature for 24 hours. By means of a stainless-steel furnace with inner length and diameter of 1.5 cm and 2.5 cm, 123

respectively, and outer length of 50 cm. The furnace was equipped with 2 different gauges. One for adjusting gas flow 124

and the other one for controlling the temperature (Fig. 1b). A Teflon tube piped the furnace to the gas tank. In the 125

course of the calcination process, nitrogen gas (Well Gas Company) with the flowrate of 200 cm3/min was flowing to 126

the tank. A scanning electron microscope (SEM) (Carl Zeiss Supra -35 VP, Germany) was used to measure 127

morphology of the surface area for both raw and calcinated limestone. Moreover, to evaluate the total surface area 128

metrics such as pore volume and pore size, the Brunauer-Emmett-Teller (BET) process (ASTM D3037) was applied 129

for the three media. X-ray fluorescence (XRF) was also used to measure the elemental composition of all three media. 130

131

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133

(a) 134

135

(b) 136

Fig. 1. Horizontal roughing filter schematic (a) and calcination experimental diagram (b). 137

138

2.4 Data Analysis 139

RSM was used to analyse the colour removal efficiency of POME. Two independent variables namely, the flow 140

rate (20-100 mL/min) and the limestone size (4-20 mm) were selected to obtain the colour removal efficiency. Each 141

experiment was run 13 times. Experimental range of each variable was between their minimum and maximum level 142

as requested by CCD. The colour removal efficiency was treated as the dependent response (Y). To recognize the 143

sufficiency of the models, both independent factors and dependent response were optimized using analysis of variance 144

(ANOVA). Similar to previous works, for quantifying the effects of two different factors, a second-order polynomial 145

quadratic model (3) was used (Fereidonian Dashti et al. 2018; Zhong et al. 2014; Hay et al. 2012). 146

147

𝑌 = 𝛽H +∑ 𝛽K𝑋K +∑ 𝛽KK𝑋KM +∑ ∑ 𝛽KN𝑋K𝑋N +⋯+ 𝑒Q

NQKRSN

QKT.

QKT. (3) 148

149

In (3), Y is the dependent parameter (colour) and 𝑋K and 𝑋N represent the independent parameters. Subscript 0 is a fixed 150

coefficient while the coefficients of higher order are denoted by i, ii, and ij. 151

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3 Results and Discussion 152

3.1 POME Properties 153

154

The POME used was characterized by 4000 Pt Co colour, 2750 mg/L COD, pH 8.3 and 652 mg/L SS, and 155

collected from United Palm Oil Mill Sdn. Bhd in Nibong Tebal, Pulau Pinang of polishing pond (last pond of 156

biological treatment) as presented in Table 3. Generally, raw palm mill wastewater is acidic (pH 3 - 4) and high in 157

temperature. COD and BOD of fresh POME are in the range of 50,000 mg/L and 25,000 mg/L, respectively. Moreover, 158

SS and Dissolved Solids (DS) are remarkably high value components of POME (Garritano et al. 2018). Hence, the 159

polishing pond characteristics in the current work was different from the conventional raw POME. All the parameters 160

evaluated in this work were measured following the Standard Methods for Water and Wastewater Examination (APHA 161

2005). The temperature and the pH were measured in the field while ammonia nitrogen, turbidity, BOD, COD, colour 162

and SS were analyzed via laboratory analyses. Measuring the mentioned parameters supported physical treatment due 163

to the amount of BOD over COD which was less than 0.1 (UVW

XVW< 0.1). The concentration of

UVW

XVW revealed the rate of 164

degradation and biodegradability of wastewater organic components. To determine proper strategies for the 165

wastewater treatment plan, stable zone, biodegradable area, toxic region and finally the UVW

XVW zones proposed by 166

Samudro and Mangkoedihardjo (2010) were used. The amount of BOD and COD in the wastewater helps evaluate 167

the organic matter content in effluent, where an elevated UVW

XVW ratio demonstrates the incidence of biodegradation 168

(Huang et al. 2017; Aziz 2011). 169

170

171

3.2 Media Properties 172

Chemical components shown in Table 4 belong to XRF results of raw and calcinated limestone. According to 173

Table 4, the two main components of limestone are calcium oxide and magnesium oxide (Dashti et al. 2019). It is 174

concluded that calcinated limestone has fewer impurities (iron, silica) in comparison with raw limestone. The findings 175

of this work agree with the results from previous works (Wang et al. 2016; Ramezani et al. 2017). 176

177

178

3.3 Morphology Analysis of the Surface Area 179

A previous study (Côté and Konrad 2009) showed that the mechanical and porous properties of limestone are 180

quickly changed when the temperature rises from 200 °C to 500 °C. This is because, in the mentioned temperature 181

range, decomposition and expansion occur in minerals which cause water evaporation inside the stone. This 182

evaporation results in physical and chemical changes among some minerals (Cai et al. 2017; Ozguven and Ozcelik 183

2014) and these changes cause new cracks in the stone which generate, propagate and coalesce pores. When the 184

temperature rises from 500 °C to 600 °C, almost all amount of moisture in the limestone evaporates. A huge number 185

of stomata, cracks and powder are created, and only few unbroken crystal ribbons remain both during and at the end 186

of calcination process in 800 °C temperature (Chen et al. 2009; Kavosh 2015) as shown in Fig. 2. Furthermore, Chen 187

et al. (2009) validated that the occurrence of coalescence during the calcination process converted the smaller pores 188

into larger pores which improved the adsorption capability of the limestone. The porosity of the limestone was 189

reduced, and its apparent weight was increased in the temperature of above 1000 °C as validated by Kilic (2014). Fig. 190

2 depicts the morphologies of the raw and calcinated limestone in the temperature of 600°C and 800°C. BET results 191

show that surface area and total pore volume in calcinated limestone were higher than raw limestone as shown in 192

Table 5. These findings agree with previous research (Fereidonian Dashti et al. 2018; Chen et al. 2017). 193

194

195

196

6

197

(a) (b) 198

199

200

(c) 201

Fig. 2. The SEM images of (a) raw limestone; (b) calcinated limestone at 600 °C; and (c) calcinated limestone at 202

800 °C 203

204

3.4 Process Optimization of Colour Removal 205

In this study, the quadratic model was used to measure colour removal efficiency. The results of the Analysis 206

of Variance (ANOVA) for POME colour removal under different flowrates and sizes for raw and calcinated limestone 207

are shown in Tables 6, 7 and 8, respectively. The mean squares were afforded by dividing the sum of squares of every 208

two variations by the error of variance shown by the Degrees of Freedom (DF). The F-value of the different models 209

was assessed by dividing the mean squared of models by residual mean. The R2 coefficient represents the ratio of the 210

regression sum of squares to the total sum of squares. A R2 value close to 1 is a favourable and agrees with previous 211

research (Ghafari et al. 2009). A desired model could be achieved by minimum R2 value of 0.80 (Dashti et al. 2020 212

7

and Fereidonian Dashti et al. 2018). Meanwhile, the Lack-of-Fit (LoF) was insignificant. An insignificant LoF is 213

preferable because the primary objective of this study is to create a model that fits the experimental data (Dashti et al. 214

2019; Pambi and Musonge 2016). In this research due to pure error, all three models were insignificant for both the 215

calcinated and raw limestone response. Tables 6 to 8 report that the Coefficient of Variance (CV) ratio is less than 216

10% for all three quadratic models. It should be kept in mind that a CV more than 10 percent imply a reproducible 217

model. Comparing the average prediction error to the range of the predicted values at the design points is called 218

Adequate Precision (AP) and ratios greater than 4 indicate an adequate model discrimination. Moreover, predicted 219

models can be used to navigate the design space defined by the CCD when AP values are higher than 4 for the achieved 220

responses. According to the findings and based on (4) to (6), A (raw and calcinated limestone (mm), B (flow rate 221

ml/min) , and A2 were significant for all three models. Actual factors of models and trace the effect of their changes 222

in the process on removal efficiency of the colour in POME can be calculated by (4) to (6). Model adequacy is normally 223

evaluated by applying diagnostic plots provided by Design Expert software, such as the predicted versus actual value 224

and the normal residual probability plots in Fig. 3. The expected colour removal efficiency values achieved from the 225

actual experimental data and that of the model were in good agreement with 3 models (Bhatti et al. 2011; Wang et al. 226

2014). Fig. 4 illustrates the plot of disruption of the comparative effects of two independent variables on the efficiency 227

of colour removal for 3 models. In Fig. 4, a sharp curvature for the flow rate (mL/min) (A) and limestone particle size 228

(mm) (B) is observed, showing that the colour removal efficiency response was slightly sensitive to both process 229

variables. 230

231

Colour Removal %= 53.52 - 0.07A - 0.52B - 1.74A2 - 0.02B2 + 3.90AB (4) 232

Colour Removal% =54.97 + 0.57A - 3.19B - 5.32A2 + 0.10B2 - 3.90AB (5) 233

Colour Removal %= 67.66 + 0.12A - 2.46B - 2.39A2 + 0.04B2 + 3.12AB (6) 234

235

236

237

(a) (b) 238

333

Actual

Pre

dic

ted

Predicted vs. Actual

18.00

25.83

33.66

41.49

49.32

18.00 25.83 33.66 41.49 49.32

22

Actual

Pre

dic

ted

Predicted vs. Actual

27.00

34.84

42.67

50.51

58.34

27.00 34.84 42.67 50.51 58.34

8

239

(c) 240

Fig. 3. Actual predicted plot of colour removal using: (a) raw limestone; (b) calcinated limestone at 600 °C; and (c) 241

calcinated limestone at 800 °C 242

243

244

(a) (b) 245

22

Actual

Pre

dic

ted

Predicted vs. Actual

33.00

40.00

47.00

54.00

61.00

33.00 40.00 47.00 54.00 61.00

Perturbation

Deviation from Reference Point

Co

lou

r

-1.000 -0.500 0.000 0.500 1.000

18

26

34

41

49

A

A

B

B

Perturbation

Deviation from Reference Point

Colo

ur

-1.000 -0.500 0.000 0.500 1.000

27

35

43

51

58

A

A

B

B

9

246

(c) 247

Fig. 4. Colour removal plot using: (a) raw limestone; (b) calcinated limestone at 600 °C; and (c) calcinated 248

limestone at 800 °C 249

250

251

3.5 Performance of Filters 252

Table 2 lists the results of 36 runs for the CCD experimental design of all 3 models. 3-D plots are created to 253

investigate the effect of two factors namely, size and flow rate on the colour removal efficiency. According to the 254

results and based on (4) to (6), both particle size of limestone and flow rate have a significant effect on response. Fig. 255

5 shows that the colour removal efficiency increased with the reduction of flow rate and limestone particle size, which 256

agrees with the results reported by Daee et al. (2019) and Maung (2006). The optimum colour removal efficiencies 257

obtained by applying roughing filter with particle size of 4 mm and flow rate of 20 mL/min were 49% for raw 258

limestone, and 58% at 600 °C and 61% C at 800 °C for calcinated limestone, respectively. Therefore, increasing the 259

pore volume, the surface area of limestone and the temperature improve the colour removal efficiency, as also 260

validated by Chen et al. (2009). In the course of the roughing filter process some suspended particles were settled 261

through the settling process due to their gravity. A particle requires less time to travel along the settling distance and 262

stick to or absorb onto the media layer if the flow rate is faster (Khezri et al. 2015; Dastanai et al. 2007). Nkwonta 263

(2010) pointed out that the flow rate has a significant influence on colour removal. Effective colour removal in 264

roughing filters are achieved with low flow rates because low flow rates are critical to retain particles that are 265

gravitationally deposited to the surface of the media. Affam and Adlan (2013) investigated the removal of colour from 266

leachate using vertical up-flow filtration technique by combination of three different media sizes (i.e., 4-8 mm, 8-12 267

mm and 12-18 mm) and five different filtration rates (100 mL/min, 80 mL/min, 60 mL/min, 40 mL/min and 20 268

mL/min). The filter media were stacked in descending sizes from bottom to top for all experiments. The results showed 269

that removal efficiency was improved from 36% to 62% for colour removal at flow rate of 20 mL/min. 270

271

272

273

Perturbation

Deviation from Reference Point

Co

lou

r

-1.000 -0.500 0.000 0.500 1.000

33

40

47

54

61

A

A

B

B

10

274

275

(a) 276

277

278

(b) 279

280

e

18

26

34

42

49

C

olo

ur

20

40

60

80

100

4

8

12

16

20

A: Flow rate

B: Limestone

ne

28

35

43

51

59

C

olo

ur

20

40

60

80

100

4

8

12

16

20

A: Flow rate

B: Limestone

11

281

(c) 282

Fig. 5. Response surface for colour removal efficiency using: (a) raw limestone; (b) calcinated limestone at 600 °C; 283

and (c) calcinated limestone at 800 °C 284

285

286

3.6 Numerical Optimization 287

In this work, some parameters such as limestone size, temperature and flow rate have significant effects on 288

POME treatment and can improve colour removal efficiency for certain conditions. Therefore, in order to find the best 289

values of independent variables that present optimum values for colour removal, RSM was applied. Each of the 290

independent factors is exclusively tuned in an attempt to earn the optimum value for colour removal (Bashir et al. 291

2010; Hosseini 2012; Aziz et al. 2011; Ahmad et al. 2005). Table 9 shows the limitations of each variable and the 292

desired response. When desirability is 1 or close to 1, the best outcome of the experiment and the most optimum 293

conditions for each solution can be selected for further validation (Hosseini 2012). In this work, the range of flow rate 294

and size of limestone were from 20 to 100 mL/min and from 4 to 20 mm, respectively. As Table 9 reports, optimum 295

removal efficiency and desirability were achieved by the lower range of limestone size (4 mm) and flow rate (20 296

mL/min). Table 9 also reports that the responses of different model predictions are closely agreeing with the results 297

of laboratory experiment. 298

299

300

3.7 Adsorption Isotherms 301

Qualitative information of the special relation between the amount of adsorbate mass on the surface of 302

adsorbent and the concentration of adsorbent in addition to the kind of solute-surface interaction are described by 303

adsorption isotherms (Khandaker et al. 2020). The current work used two different isotherms, namely Freundlich and 304

Langmuir, to fit the equilibrium data acquired from the actual experiments. Theoretically, the assumption of the 305

Langmuir isotherm is that the adsorbate covers the homogeneous surface of adsorbent in a monolayer (Jawad et al. 306

2020). The Langmuir isotherm is presented in (7): 307

33

40

47

54

61

C

olo

ur

20

40

60

80

100

4

8

12

16

20 A: Flow rate

B: Limestone

12

.

[/\= .

]^X_+ .

] (7) 308

309

In (7), the rate of adsorption, adsorption capacity, adsorbate equilibrium concentration and the quantity of adsorbate 310

are denoted by b (L/mg), Q (mg/g), Ce (mg/L) and x/m (qe) (mg/g), respectively. According to Table 10, the Langmuir 311

model sufficiently fits the equilibrium data. The equilibrium parameter (RL) (Balark et al. 2017) can also be used to 312

explain the Langmuir isotherm features (8): 313

𝑅a =.

(.b^XA) (8) 314

315

In (8), the initial colour concentration and the Langmuir constant are denoted by C0 (mg/L) and b, respectively. 316

Isotherms can be categorized into three different categories based on the value of favorable (RL<1), linear (RL = 1), 317

and unfavorable (RL>1) (Isa et al. 2007). Table 10 shows favorable adsorption process for colour for all types of 318

limestone. The main underlying theory of the Freundlich isotherm model is the assumption that the adsorption process 319

occurs on heterogeneous surfaces and can be presented as the empirical (9) (Dashti et al. 2020): 320

321

322

𝑙𝑜𝑔 𝑞g = 𝑙𝑜𝑔𝐾 + .i𝑙𝑜𝑔 𝐶g (9) 323

324

where, qe = colour amount adsorbed per unit of mass adsorbent (mg/g); Ce = adsorbate equilibrium (mg/L); n = 325

adsorption intensity; and K = adsorption capacity (mg/g). A favorable adsorption mechanism (.

i < 1) increases 326

adsorption capacity while a weak adsorption capacity is the result of an unfavorable adsorption mechanism (.

i > 1) 327

(Aziz et al. 2008 and Hossain et al. 2019). R2 and K values for the Freundlich isotherm based on linear regression 328

correlation (9) are listed in Table 11 and are shown in Fig. 7. Findings of this work validated that the Langmuir 329

isotherm model fits the experimental data better than the other model (Fig 6). Another outcome is that the colour 330

coated the surface of the adsorbent in a monolayer fashion and homogenously. This is caused by the higher R2 value 331

acquired using Langmuir isotherm (0.735) compared with the Freundlich isotherm (0.622) (Fig. 6 and 7). Keong 332

(2012) achieved colour removal of leachate (Q) equal to 1.070 Pt Co/g and 0.065 Pt Co/g; and b values of 5.36×10-3 333

/Pt Co and 5.44×10-3 /Pt Co for calcinated limestone at 400 ̊ C and 200 ̊ C, respectively. The values of R2 for Freundlich 334

model were 0.751 and 0.605 in comparison to Langmuir model which were 0.502 and 0.376 for calcinated limestone 335

at 400 ˚C and 200 ˚C. Pala and Erden (2004) used lime for leachate treatment. They found out that Langmuir isotherm 336

was more satisfactory (R2=0.97) for colour removal compared to Freundlich model. 337

338

13

339

(a) 340

341

(b) (c) 342

Fig 6. Langmuir Isotherm for Colour adsorption: (a) raw limestone, calcinated limestone at 600 ˚C; (b) 343

and calcinated limestone at 800 ˚C; (c) 344

345

y = -794855x + 1442.6

R² = 0.6411

10801090110011101120113011401150116011701180

0.0000 0.0001 0.0002 0.0003 0.0004 0.0005

1/q

e

1/Ce

y = -493978x + 1103.8

R² = 0.7085

850

860

870

880

890

900

910

920

930

0.0000 0.0002 0.0004 0.0006

1/q

e

1/Ce

y = -356460x + 888.74

R² = 0.735

680

690

700

710

720

730

740

750

760

770

0.0000 0.0002 0.0004 0.0006

1/q

e

1/Ce

14

346

(a) 347

348

(b) (c) 349

Fig 7. Freundlich Isotherm for colour adsorption: (a) raw limestone, calcinated limestone at 600 ˚C; 350

(b) and calcinated limestone at 800 ˚C; (c) 351

352

353

y = -0.2486x - 2.2047

R² = 0.6053

-3.07

-3.07

-3.06

-3.06

-3.05

-3.05

-3.04

-3.04

3.34 3.36 3.38 3.40 3.42 3.44

Log x

/m

Log Ce

y = -0.1046x - 2.513

R² = 0.6065

-2.89

-2.88

-2.87

-2.86

-2.85

-2.84

-2.83

3.00 3.10 3.20 3.30 3.40 3.50

Log x

/m

Log ce

y = -0.2422x - 2.1351

R² = 0.6229

-2.97

-2.96

-2.96

-2.95

-2.95

-2.94

-2.94

-2.93

3.30 3.35 3.40 3.45

Log x

/m

Log ce

15

4. Conclusions 354

This research focused on development of a low-cost, eco-friendly and functionalized material to remove colour 355

from palm oil mill effluent (POME). More specifically, the optimum conditions of colour removal from polished 356

POME were investigated using calcinated and raw limestone in a horizontal roughing filter process as filter media. 357

The interaction between the variables (flow rate and limestone size) and experimental parameter had been used to 358

enhance the colour removal using response surface methodology. Optimum variables, according to the model, 359

consisted of calcinated limestone at 800 ℃ with the size of 4 mm and a flow rate of 20 mL/min. The mentioned settings 360

led to 61% colour removal, while only 18% was achieved when using raw limestone with the size of 20 mm and flow 361

rate of 100 mL/min. A particle requires less time to travel along the settling distance and stick to or absorb onto the 362

media layer if the flow rate is fast. According to the achieved results, when the size of filter media is small and the 363

flow rate is low, more colour removal is achieved. Furthermore, the Langmuir isotherm yielded R2 of 0.735 and fitted 364

well the adsorption data in this study. 365

366

367

368

Acknowledgements 369

370

This research was awarded Universiti Sains Malaysia Short-Term Grant (Grant No. 304/ PAWAM/60311001). 371

which is belong to the Solid Waste Management group, Engineering Campus, USM. 372

373

Conflict of Interest 374

The authors notify that there are no conflicts of interest. 375

376

Availability of data and materials 377

All authors agreed that all data and materials as well as software support our published and comply with 378

field standards 379

380

Declarations 381

382

The authors declare that they have no known competing financial interests or personal relationships that 383

could have appeared to influence the work reported in this paper. The research leading to these results 384

received funding from Universiti Sains Malaysia Short-Term Grant under Grant Agreement No (304/ 385

PAWAM/60311001) 386

387

Authors' contributions 388

Formal analysis and investigation; Writing - original draft preparation: Dr. Arezoo Fereidonian Dashti 389

Supervisor and co-supervisor: Prof. Mohd Nordin Adlan; Prof. Hamidi Abdul Aziz 390

Methodology: Ali Huddin Ibrahim 391

392

16

393

Abbreviations and Chemical Symbols 394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

ANOVA Analysis of variance

AP Adequate Precision APHA American Public Health Association

AWWA American Water Works Association

BET Brunauer-Emmett-Teller

BOD Biological oxygen demand CaO Lime

CaCo3 Calcium Carbonate

COD Chemical oxygen demand ºC Degrees celsius

CCD Central composite design

CL Calcinated limestone

CV Coefficient of variance DOE Department of Environment

Fe2O3 Ferric oxide

Fig Figure g Grams

ha Hectare

HRF Horizontal roughing filter HRT Hydraulic retention time

Kg Kilogram

L Liters

LOF Lack of Fit LS Limestone

Mm Millimeters

Mg/L Milligrams per liter MgO Magnesium oxide

m2/g Square meter per gram

% Percent POME Palm oil mill effluent

pH Potential hydrogen

RL Raw Limestone

RSM Response Surface Methodology SD Standard deviation

SEM Scanning electron microscopy

SiO2 Silicon dioxide SS Suspended Solid

XRD X-Ray Diffraction

Cc/g Cubic centimeter per gram

17

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Figures

Figure 1

Horizontal roughing �lter schematic (a) and calcination experimental diagram (b).

Figure 2

The SEM images of (a) raw limestone; (b) calcinated limestone at 600 °C; and (c) calcinated limestone at800 °C

Figure 3

Actual predicted plot of colour removal using: (a) raw limestone; (b) calcinated limestone at 600 °C; and(c) calcinated limestone at 800 °C

Figure 4

Colour removal plot using: (a) raw limestone; (b) calcinated limestone at 600 °C; and (c) calcinatedlimestone at 800 °C

Figure 5

Response surface for colour removal e�ciency using: (a) raw limestone; (b) calcinated limestone at 600°C; and (c) calcinated limestone at 800 °C

Figure 6

Langmuir Isotherm for Colour adsorption: (a) raw limestone, calcinated limestone at 600 ˚C; (b) andcalcinated limestone at 800 ˚C; (c)

Figure 7

Freundlich Isotherm for colour adsorption: (a) raw limestone, calcinated limestone at 600 ˚C; (b) andcalcinated limestone at 800 ˚C; (c)

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