Coagulation and Dissolved Air Flotation as Pretreatment ...

Coagulation and Dissolved Air Flotation as

Pretreatment for Ultrafiltration of Vegetable

Processing Wastewater

By

Xiaoyan Chen

A Thesis

Presented to

The University of Guelph

In partial fulfilment of requirements

For the degree of

Master of Applied Science

In

Engineering

Guelph, Ontario, Canada

© Xiaoyan Chen, May, 2015

ABSTRACT

COAGULATION AND DISSOLVED AIR FLOTATION AS PRETREATMENT FOR

ULTRAFILTRATION OF VEGETABLE PROCESSING WASTEWATER

Xiaoyan Chen Advisor:

University of Guelph, 2015 Professor Hongde Zhou

Professor Keith Warriner

Fresh vegetable processing plants generate a large quantity of wastewater that must be treated in

order to meet the sewer discharge limits. The objectives of this research are to evaluate the

feasibility of coagulation, and dissolved air flotation (DAF) as pre-treatment options for

ultrafiltration (UF) to treat spent leafy green wastewater, and potato wastewater.

Both coagulation and DAF experiments were conducted to examine the effects of their key

process parameters in terms of suspended solids, turbidity, COD, and colloidal TOC removal.

Membrane filtration tests were conducted using a dead-end submerged hollow fibre UF

membrane module. Results showed both coagulation and DAF treatment reduced the fouling

rate. The suspended solids and phosphorous removal efficiencies were over 67% and 90%,

respectively. COD, BOD5 and colloidal TOC were removed by around 70% for potato

wastewater, and less than 20% for spinach wastewater.

iii

ACKNOWLEDGEMENTS

First and foremost, I would express my deep appreciation to my advisor, Dr. Hongde

Zhou for his insights, and suggestions, which guided me to finish the project.

I would also like to thank my co-advisor, Dr. Keith Warriner for his support and

providing me the opportunity for this project.

I am also grateful to OMAFRA for generous financial support and introducing me to the

growers for taking wastewater samples.

Thanks to all my friends, who assisted me to a great extent during my research: Richard

Chen, Carlos Torres, Bei Wang, Wenbo Yang, Adam Moore, Gurvinder Mundi, and

many other friends, which are not mentioned. I also appreciate the help of Joanne Ryks,

Phil Waston and other staff in School of Engineering for their help in conducting my

experiments.

Lastly, I thank all my family members. Especially, my dad and mom, who were the

biggest inspiration, gave me the most love and care with my health and happiness. Also,

my sisters, and brothers gave me the determination, and much needed courage at most

difficult times during this project.

iv

TABLE OF CONTENTS

ABSTRACT ................................................................................................... ii

ACKNOWLEDGEMENTS ........................................................................ iii

TABLE OF CONTENTS ............................................................................. iv

TABLE OF FIGURES ................................................................................ vii

TABLE OF TABLES .................................................................................... x

Chapter 1 INTRODUCTION ....................................................................... 1

1.1 Current Status of Wastewater Treatment in Food Processing Industries ................. 1

1.2 Organization of Thesis .............................................................................................. 2

Chapter 2 LITERATURE REVIEW ........................................................... 3

2.1 Challenges of Food Industries .................................................................................. 3

2.2 Current Practices of Wastewater Treatment in the Food Industry ............................ 6

2.3 Membrane Filtration ............................................................................................... 10

2.3.1 Membrane Characteristics and Materials ......................................................... 11

2.3.2 Membrane Fouling Mechanisms and Factors Affecting Processes ................. 14

2.3.3 Fouling Control ................................................................................................ 15

2.4 Coagulation ............................................................................................................. 17

2.4.1 Introduction ...................................................................................................... 17

2.4.2 Applications of Aluminum Sulfate in Food Industrial Wastewater ................. 18

2.4.3 Effects of Coagulation on Membrane Fouling................................................. 19

2.5 Dissolved Air Flotation ........................................................................................... 20

2.5.2 Effects of DAF on Membrane Fouling ............................................................ 20

2.5.1 Introduction ...................................................................................................... 20

Chapter 3 OBJECTIVES ............................................................................ 24

Chapter 4 METHODOLOGY .................................................................... 26

4.1 Material and Methods ............................................................................................. 26

4.1.1 Wastewater Sampling ...................................................................................... 26

4.1.2 Jar Test Apparatus and Testing Protocol ......................................................... 27

v

4.1.3 DAF Apparatus and Operation ........................................................................ 29

4.1.4 Membrane Apparatus and Operation ............................................................... 32

4.2 Analytical Methods ................................................................................................. 35

4.3 QC/QA .................................................................................................................... 38

Chapter 5 RESULTS AND DISSCUSSION ............................................. 39

5.1 Fruit & Vegetable Wastewater Characterization .................................................... 39

5.2 Coagulation ............................................................................................................. 44

5.2.1 Turbidity Removal ........................................................................................... 44

5.2.2 COD/cTOC Removal ....................................................................................... 47

5.3 DAF Results ............................................................................................................ 50

5.3.1 DAF Water Saturation ..................................................................................... 50

5.3.2 Contaminant Removal ..................................................................................... 52

5.3.3 Comparison between Coagulation - Sedimentation and Coagulation -DAF ... 56

5.4 Membrane Filtration of Pretreated Spinach Wastewater ........................................ 60

5.4.1 Air Scouring Rate Selection............................................................................. 60

5.4.2 Critical Fluxes of Spinach Wastewater and Wastewater after Pretreatment ... 61

5.4.3 Membrane Fouling ........................................................................................... 64


5.5 Effects of Different Pretreatment on Membrane Fouling of Potato Wastewater .... 75

5.5.1 Air Scouring Rate Selection............................................................................. 75

5.5.2 Critical Fluxes of Potato Wastewater and Wastewater after Pretreatment ...... 76

5.5.3 Membrane Fouling ........................................................................................... 78


Chapter 6 CONCLUSIONS AND RECOMMENDATIONS .................. 89

6.1 Conclusions ............................................................................................................. 89

6.2 Recommendations and Future Work ...................................................................... 90

REFERENCES ............................................................................................ 92

APPENDICES ............................................................................................ 103

A.1 Water Characteristics ........................................................................................... 104

A.2 Standard Curves for Water Quality Analyses ...................................................... 114

A.3 Experiments data of Jar Tests .............................................................................. 118

A.4 Experiments data of DAF Tests ........................................................................... 120

vi

A.5 Experiments data of Membrane Filtration Tests .................................................. 130

vii

TABLE OF FIGURES

Figure 4-1 Bench-scale batch jar test apparatus ........................................................................... 28

Figure 4-2 Bench-scale batch DAF apparatus .............................................................................. 30

Figure 4-3 Schematic diagram of DAF treatment ......................................................................... 31

Figure 4-4 Batch bench-scale dead – end submerged UF system ................................................ 33

Figure 4-5 Schematic diagram of dead-end submerged UF system ............................................. 34

Figure 5-1 Turbidity removal percentage from spinach wastewater by coagulation .................... 44

Figure 5-2 Turbidity removal percentage from potato wastewater by coagulation ...................... 46

Figure 5-3 COD removal percentage from spinach wastewater by coagulation .......................... 47

Figure 5-4 CTOC removal percentage from potato wastewater by coagulation .......................... 49

Figure 5-5 Effects of pressure on DAF water saturation .............................................................. 50

Figure 5-6 Effects of DAF recycle rate on suspended solids removal in the treatment of

spinach wastewater .................................................................................................... 52

Figure 5-7 Effects of DAF flotation time on turbidity removal in the treatment of spinach

wastewater .................................................................................................................. 53

Figure 5-8 Effects of DAF recycle rate on contaminants removal efficiencies in the

treatment of potato wastewater .................................................................................. 54

Figure 5-9 Effects of DAF flotation time on suspended solids removal efficiencies in the

treatment of potato wastewater .................................................................................. 55

Figure 5-10 Contaminants removal efficiencies by coagulation - sedimentation and

coagulation - DAF of spinach wastewater ................................................................. 59

viii


coagulation - DAF of potato wastewater ................................................................... 59

Figure 5-12 Effects of UF air scouring rate on fouling resistance in the treatment of

spinach wastewater .................................................................................................... 61

Figure 5-13 Critical flux measurement of spinach raw wastewater ............................................. 62

Figure 5-14 Critical flux measurement of spinach wastewater after coagulation ........................ 62

Figure 5-15 Critical flux measurement of spinach wastewater after coagulation and DAF ......... 63

Figure 5-16 Fouling resistance of spinach raw wastewater (SR), spinach wastewater after

coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in

UF test 1 ..................................................................................................................... 68

Figure 5-17 Fouling rate of spinach raw wastewater (SR), spinach wastewater after


UF test 1 ..................................................................................................................... 68



UF test 2 ..................................................................................................................... 69



UF test 2 ..................................................................................................................... 69

Figure 5-20 Comparison of effluent qualities after different treatment methods of spinach

wastewater .................................................................................................................. 73


potato wastewater ....................................................................................................... 75

ix

Figure 5-22 Critical flux measurement of potato raw wastewater (PR) ....................................... 76

Figure 5-23 Critical flux measurement of potato wastewater after coagulation (PC) .................. 77

Figure 5-24 Critical flux measurement of potato wastewater after coagulation and DAF

(PD) ............................................................................................................................ 77

Figure 5-25 Fouling resistance of potato raw wastewater (PR), potato wastewater after

coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF

test 1 ........................................................................................................................... 79

Figure 5-26 Fouling rate of potato raw wastewater (PR), potato wastewater after


test 1 ........................................................................................................................... 79



test 2 ........................................................................................................................... 80



test 2 ........................................................................................................................... 81

Figure 5-29 Comparison of effluent qualities after different treatment methods of potato

wastewater .................................................................................................................. 87

x

TABLE OF TABLES

Table 2-1 Sanitary and combined sewer discharge limits .............................................................. 3

Table 2-2 Vegetative wastewater characteristics ............................................................................ 5

Table 2-3 Current treatment applied in food industrial wastewater ............................................... 8

Table 2-4 General characteristics of membrane processes (Metcalf & Eddy, 2003) ................... 13

Table 4-1 Vegetable wastewater sampling details ........................................................................ 27

Table 4-2 Experimental arrangement of jar tests .......................................................................... 29

Table 4-3 Experimental arrangement of DAF tests ...................................................................... 32

Table 5-1 Characteristics of different vegetative wastewater ....................................................... 41

Table 5-2 Spinach and potato raw water characteristics and effluent results from

coagulation and sedimentation or by coagulation and DAF ...................................... 57

Table 5-3 Spinach feed water parameters for UF Test 1 and Test 2 ............................................. 66

Table 5-4 Potato feed water parameters for UF test 1 and test 2 .................................................. 84

1

Chapter 1 INTRODUCTION

1.1 Current Status of Wastewater Treatment in Food Processing Industries

Canadian food industry generated over 300 million cubic meters of wastewater each year

to produce a wide variety of commodities. Within this industry, the fresh fruit and

vegetable processing represents one of major sources because of washing and cooling

(Dupont & Renzetti, 1998, Casani et al., 2005). Furthermore, many of processing plants

are facing the challenges to meet increasingly stricter regulatory discharge limits. Some

of them are five day biochemical oxygen demand (BOD5), total suspended solid (TSS),

total Kjeldahl nitrogen (TKN) and total phosphorus (TP), the violation of which could

lead to serious penalties or even the complete closure (Toronto, 2000).

The general strategy to meet the designated discharge limits is to minimize water usage

and implement treatment technologies prior to disposal. An added benefit would be to

treat the wastewater to a quality, where it could be recycled back into the processing line.

As well, there are a diverse range of water treatment technologies available that are

dependent on cost, requirements, degree of maintenance, and ultimate use of the end

water. In the following thesis, the treatment technologies selected for the study were

coagulation, dissolved air flotation (DAF), and ultrafiltration (UF). The aforementioned

technologies can potentially meet the demands of the industry in terms of a small

footprint, cost and maintenance requirements to treat this vegetable processing

wastewater that contains relatively low solids.

2

1.2 Organization of Thesis

Chapter 1 briefly introduces the challenges in water treatment within the food processing

industry. Chapter 2 provides a more in depth background to the research area. This

chapter will discuss the parameters to characterize wastewater, current water management

options, and a detailed description of the technologies to be studied. Chapter 3 lists the

objectives of this research. Chapter 4 provides a description of methods used in the

reported research with Chapter 5 presents the results and discussions. Chapter 6 provides

the conclusions along with future work.

3

Chapter 2 LITERATURE REVIEW

2.1 Challenges of Food Industries

Canadian food industry was reported to use over 300 million cubic meters of water

representing the fourth largest water consumption after paper, metals and chemical

industries. Over 90% of the intake water within the food industry ended up in the sewer

(Statistics Canada, 2009). However, this practice will bring the food industry a large

surcharge bill due to violating the sewer discharge limits set by the municipalities. Table

2-1 lists the sanitary and combined sewer discharge limits set by the Ministry of the

Environment.

Table 2-1 Sanitary and combined sewer discharge limits

Parameters MOE

(Ministry of the

Environment, 1989)

Cambridge

(City of

Cambridge, 2002)

Toronto

(Toronto’s Sewers

Bylaw, 2000)

BOD5 (mg/L) 300 300 300

TSS (mg/L) 350 350 350

TKN (mg/L) 100 100 100

TP (mg/L) 10 10 10

Total Aluminum

(mg/L)

/ 50 50

pH 6 - 10.5 5.5 - 9.5 6 - 11.5

Table 2-2 summarized the main characteristics from six different vegetable processing

wastewater sources. As compared with the sanitary sewer use by-law (Table 2-1), the

4

untreated discharge effluents exceed the discharge limits. The TSS and BOD5 in the

reviewed vegetable processing industrial effluents were higher than that in the discharge

limits, respectively. Especially, beets processing wastewater showed a high BOD5 of

7600 mg/L. Although a low TP concentration was found in carrot processing wastewater,

other types of food processing wastewater would produce the effluents with the

phosphorus content significantly over the sewer discharge limit. It is expected that the

current limits will continue to be reviewed by regulatory agencies, and much stringer

limits will be introduced on the fresh produce sector (Government of Canada, 2014).

Therefore, on-site wastewater treatment is necessary for food processing industry prior to

discharge.

5

Table 2-2 Vegetative wastewater characteristics

TSS: Total suspended solids; cTOC: colloid Total organic carbon; TN: Total nitrogen; TP: Total phosphorus; TS: Total solids.

Wastewater

Source

BOD5

(mg/L)

COD

(mg/L)

TSS

(mg/L)

TN

(mg/L)

TP

(mg/L)

pH References

Potato 2650-

37000

1650-

4420

165 5-9 (Burgoon et al., 1999;

Karim & Sistrunk, 1985a;

Muniraj et al., 2013)

Carrot 670 680 - 1300 41 5.8 7 (Hamilton, 2006; Kern,

2006, Reimann, 2002)

Beans 1800 3410 1340 112 21.5 6 (Soderquist et al., 1975)

Beets 1580-7600 1820-8740 94.5 (Soderquist et al., 1975)

Spinach 40 240 1400 (Wright et al., 1979)

Tomato 3280 -

6960

1120-

1380

46.2 -47.5 4-6 (Gohil & Nakhla, 2006)

6

2.2 Current Practices of Wastewater Treatment in the Food Industry

Thus far, most of the small-scale food processing industries apply relatively simple

physical operations wastewater treatment technologies such as, screening and

sedimentation prior to discharging into the municipal sewer. However, these practices

show poor results on reducing suspended solid contents or organic loads in the effluents.

Furthermore, in order to recycle the used water back into production line, which requires

the drinking water qualities, advanced or tertiary treatment processes are required due to

meeting the standard (Casani et al., 2005). Therefore, water reuse in these small-scale

food processing facilities may not be economically feasible. Instead, the main target of

wastewater treatment is to improve the effluent quantities and to meet the current and

future environmental legislations.

Wastewater treatment processes can be classified into three categories, which are known

as the primary, secondary and tertiary treatment. Primary treatment usually involves

physical operations, and chemical additions for removing at least 60% of suspended

solids and 20-30% of BOD5 from wastewater. Screening, sedimentation, coagulation and

DAF are typical primary treatment technologies. Secondary treatment is applied if

organic or nutrients removals are necessary, and it involves biological, and chemical

processes, such as aerobic, anaerobic, attached-growth or combined

aerobic/anoxic/anaerobic. The objectives of these secondary treatment technologies are

removing or reducing the organic matters, suspended solids, and nutrients. The last level

of wastewater treatment is the tertiary level, which is targeted to remove residual

7

suspended solids and other contaminants after secondary treatment. Typical tertiary

treatment technologies include disinfection and granular medium filtration or

microsecreens (Bouallagui et al., 2004; Bouallagui et al., 2005; Lepist; & Rintala, 1997;

Metcalf & Eddy, 2003).

In this research, different treatment processes that have been applied in variable food

industries including meat, beverage, and vegetable & fruit sectors are summarized in

Table 2-3. Most fruit & vegetable industries applied conventional wastewater treatment

methods such as, anaerobic and aerobic biological process; whereas the meat processing

industries use membrane treatment technologies.

However, the conventional biological treatment requires a higher biodegradable influent,

where a higher BOD5 / COD ratio is usually necessary. Many fruit & vegetable

wastewater studies found that the BOD5/COD ratio varied from 0.18 to 0.50, with beets

processing wastewater had a higher ratio that was 0.87 (Burgoon et al., 1999; Gohil &

Nakhla, 2006b; Karim & Sistrunk, 1985b). A low BOD5/COD ratio requires

pretreatment before a biological wastewater process, which can raise the overall cost of

treatment. For some leafy green wastewater, the concentration of COD in spinach

wastewater is 235 mg/L (Wright et al., 1979b), which is much lower than the required

COD concentration for anaerobic treatment.

8

Table 2-3 Current treatment applied in food industrial wastewater

Food Products Treatment method Removal Objective Reference

Surimi processing UF Protease activity, COD, turbidity, recover

protein

(Lin et al., 1995)

Bottle washing Pre-

filtration+NF+RO+UV

PH, electronic conductivity, COD, TOC,

Calcium, Magnesium, Iron, Chloride, Nitrite

(Mavrov & Bélières, 2000)

FVW (potato

peelings, salad

wastes, green peas

and carrots)

Anaerobic digestion TS, TVS and organic fraction reduction (Bouallagui et al., 2005)

FVW Anaerobic digestion TOC, TS, TVS, TN and pH (Bouallagui et al., 2004)

Carrot, potato and

swede peeling and

blanching

wastewater

Thermophilic Up-flow

Anaerobic Sludge Blanket

Reactors

COD, BOD5 (Lepist; & Rintala, 1997)

Vegetable oil

refinery

Aerobic Biological

Treatment Reactor

COD, oil and grease loads (Azbar & Yonar, 2004)

Potato processing Integrated Natural

Systems

COD, TSS, TN, organic nitrogen, ammonia

nitrogen

(Burgoon et al., 1999)

Dairy wastewater Ultrafiltration Immersed

Membrane Bioreactor

(IMBR)

BOD5, COD and TSS (Bick et al., 2005)

9

Fishing industry Crossflow membrane Suspended materials, fats (Almas, 1985)

Food and beverage

industry

Combined MBR and two-

stage NF+UV

SS, electrical conductivity, content of Na+-

ions and Cl--ions, COD, TOC, E. coli

coliform bacteria, fecal streptococci, sulfite

reducing, spore forming anaerobes,

(Blöcher et al., 2002)

Corn starch

wastewater

MF+RO TS, TSS, BOD5 (Cancino-Madariaga &

Aguirre, 2011)

Food industrial

wastewater

Two-stage NF+UV

disinfection

TOC, electrical conductivity, nitrite (Fähnrich et al., 1998)

Vegetable oil

factory

UF Reduction in COD, TOC, TSS, [PO4-3

] and

[C1-]

(Mohammadi & Esmaeelifar,

2004)

Dairy wastewater Horizontal-Flow Biofilm

Reactor

COD and TN reduction (Rodgers et al., 2006)

Carrot

Wastewater

UF+RO BOD5, COD, TN, TP (Reimann, 2002)

Fish Farming

Wastewater

DAF TP, TSS (Jokela et al., 2001)

UF: Ultrafiltration; UV: Ultraviolet radiation; MF: Microfiltration; NF: Nan filtration; RO: Reverse Osmosis; FVW: Fruit and

vegetable wastewater; DAF: Dissolved Air Flotation; TVS: Total volatile solids; TKN: Total Kjeldahl Nitrogen.

10

DAF is also widely adopted in food industries due to its flexibility in operation, less

operation time; good performance in TSS, high oil & grease removal efficiency (RE), and

small footprint (Bensadok et al., 2007; Chan, 2010; Jokela et al., 2001; Liu & Lien, 2001;

Viitasaari et al., 1995). In many industrial effluents, the quantities, and qualities fluctuate

frequently. Comparing to sedimentation, DAF has a higher tolerance to a wide range of

solid loading rates, and less sensitive to hydraulic variations.

Another common treatment alternative showed in Table 2-3 is membrane technologies,

which includes microfiltration (MF), ultrafiltration (UF), nano-filtration (NF), and

reverse osmosis (RO). Membranes are also used in membrane bioreactors (MBR).

Numerous studies prove that membrane filtrations such as MF and UF are viable and

competitive technologies for removing suspended solids and organic matters from food

processing, industrial and municipal wastewater (Ramirez & Davis, 1998). In particular,

ultrafiltration over the coagulation/flocculation and DAF is thought to be an effective

treatment process for producing the good quality permeate which can be disposed directly

into the sewer (Afonso & Bórquez, 2003).

2.3 Membrane Filtration

Membrane filtration is defined as a separation process driven by pressure or a vacuum, in

which an engineered barrier is used to reject particulate matter that larger than specific

membrane nominal pore size. This definition is intended to include the common

membrane classifications: MF, UF, NF, and RO (Metcalf & Eddy, 2003).

11

2.3.1 Membrane Characteristics and Materials

General characteristics of different membrane filters are summarized in Table 2-4.

Among these different membrane processes and configurations, backwash-able hollow-

fiber MF and UF has had the most profound impact to wastewater treatment in 1990s

(Blanpain & Lalande, 1997; “Membrane Filtration Guidance Manual| US EPA,” 2005).

Especially for vegetative wastewater treatment, UF can be a potential treatment process

applied in the food processing industries.

For UF, membrane can be made from organic materials or inorganic materials. Although,

inorganic materials have higher resistance to chemicals and temperature, its high cost and

brittleness limit its application in commercial markets, which has promoted organic

membrane materials to become more widely used (Zhou & Smith, 2002). Typically,

organic membrane materials such as cellulose acetate (CA), polyether sulfone (PES) and

polyvinylidene fluoride (PVDF) are the most widely used materials in ultrafiltration

(Metcalf & Eddy, 2003).

CA has a rough susceptibility to particle adsorption, and charge interaction, which can

minimize the organic fouling (Xie, 2006). However, the cost of CA membrane is three to

five times higher than that of polymeric membranes (Garmash et al., 1995). PES is

widespread because of its properties such as: high pH tolerance, high tolerance of a wide

range temperature, good chlorine resistance, and can be manufactured for a wide range of

pore sizes (Yang, 2005). These properties allow it to have a good resistance to alcohols,

acid and especially large particles (Xie, 2006). PVDF has similar properties to PES

(Riedl et al., 1998; Yu et al., 2009): 1. PVDF has high chemical tolerance to acids and

12

alkalis; 2. Superior thermal and hydrolytic resistance; 3. Outstanding membrane forming

properties. Nevertheless, PVDF has gained more commercial interests compared to PES

due to its economical production (Liu et al., 2011).

13

Table 2-4 General characteristics of membrane processes (Metcalf & Eddy, 2003)

Membrane

Processes

Typical

separation

mechanism

Typical

operating

range

(µm)

Rate of

flux

(L/m^2

/d)

Configuration Permeate

description

Typical constituents

removed

Microfiltration Sieve 0.08-2.0 405-1600 Spiral wound,

hollow fiber, plate

and frame

Water and

dissolved solutes

TSS, turbidity, protozoan

oocysts and cysts, some

bacterial and viruses

Ultrafiltration Sieve 0.005-0.2 405-815 Spiral wound,

hollow fiber, plate

and frame

Water and small

molecules

Macromolecules, colloids,

most bacteria, some viruses,

proteins

Nanofiltration Sieve+sulutio

n/diffusion+e

xclusion

0.001-0.01 200-815 Spiral wound,

hollow fiber

Water and very

small molecules,

ionic solutes

Small molecules, some

hardness, viruses

Reverse

Osmosis

Sieve+sulutio

n/diffusion+e

xclusion

0.0001-

0.001

320-490 Spiral wound,

hollow fiber, thin-

film composite

Water and very

small molecules,

ionic solutes

Very small molecules, color,

hardness, sulphates, nitrate,

sodium, other ions

14

As listed in Table 2-4, modules for membrane filters are diversified, and have a variety of

configurations for different membranes. In recent years, unlike the traditional cross-flow

UF process, which requires high energy input and maintenance, submerged UF processes

have been subjected to significant research and applied because of its low-cost, energy

efficiency and less maintain (Xie et al., 2008).

2.3.2 Membrane Fouling Mechanisms and Factors Affecting Processes

A major challenge with membrane filtration is the accumulation of organic and inorganic

matters deposit on the surface of membrane surface, which leads to membrane fouling.

The membrane fouling reduces the membrane permeate abilities or increases the

transmembrane pressure (TMP), and ultimately reduces the working lifespan of the filter

unit (Metcalf & Eddy, 2003). The art of preventing the fouling of membranes has been

based on understanding the underlying phenomenon.

Two main kinds of membrane fouling mechanisms can be summarized according to

previous studies (Blanpain & Lalande, 1997; Czekaj et al., 2000; Karimi, 2012;

Yazdanshenas et al., 2012). The first kind of fouling is pore narrowing caused by the

accumulation of particles of equal size or smaller than the pores. The particles essentially

accumulate within the pore causing reduced flux or high TMP. The second type of

fouling involves macromolecules that are adsorbed onto the membrane surface thereby

forming a cake/gel layer that ultimately blocks the pores.

According to the mechanisms of fouling, foulants that cause membrane fouling are

suggested to be divided into three main groups: 1. Particulates; 2.Organic; 3.Inorganic; 4:

15

Micro-biological organisms (Guo et al., 2012). Particles and colloid are responsible for

the initial phase of fouling as they can physically blind the membrane surface(Guo et al.,

2012). Especially, small particles that have similar size to the membrane pore size are

expected to cause the pore blocking (Lim & Bai, 2003). Organic components such as

humic acid will be adsorbed by membrane, and lead to pore narrowing. Inorganic

components may be introduced to the feed water by overdosing coagulation/flocculation

processes, and tend to precipitate onto the membrane surface after oxidation and pH

changes. Microbiological organisms can result in the biofilm formation due to the

attachment of microorganisms onto the surface of membrane (Guo et al., 2012).

Among these foulants, the main foulants in this research should be particles, and organic

components. Fruit, and vegetable wastewater always contains a rich amount of suspended

solids and a high concentration of organic matters (Jang et al., 2013; Kalyuzhnyi et al.,

1998).

2.3.3 Fouling Control

For control of membrane fouling, modifying operation conditions, membrane cleaning

and pretreatment are applied according to the mechanisms of membrane fouling.

According to Defrance & Jaffrin’s (1999) studies, operating in a constant flux mode

resulted in less fouling than operating in a constant TMP mode. However, when

operating the filtration at a constant flux higher than the critical flux, the membrane

fouling will be worse than operating in a constant TMP mode (Vyas et al., 2002).

Critical flux has many definitions with one of the mostly widely applied being the flux

below the key flux that can maintain the flux or rarely fouling is observed on the start-up

16

period. Above it, fouling is observed and the decline of flux will occur due to membrane

fouling (Field et al., 1995). Thus, operating the membrane filtration with constant flux

under critical flux is suggested.

Apart from the operation of membrane filtration, membrane cleaning is another method

to control the membrane fouling, and extend the lifetime of membrane. As early as before

1990, many industries were adopting two common methods for cleaning membranes of

fouling materials and these two methods are backwash and periodic cleanings (Gekas &

Hallström, 1990). Normally, membrane cleaning can be divided into two types of

cleaning: physical cleaning, and chemical cleaning. Backwash is a proven mechanism for

physical cleaning to wash out foulants from the membrane surface by dislodging the

loosely attached filter cake from membrane surface (Karimi, 2012). In most cases,

backwash is only applicable for reversible fouling and external fouling. For internal

fouling, backwash has a limited impact. Accordingly, chemical cleaning is also needed

for flux recovery, which includes: chemically enhanced backwash (daily), maintenance

cleaning with higher chemical concentration (weekly), and intensive/recovery chemical

cleaning (once or twice a year) (Le-Clech et al., 2006). Furthermore, research has found

that the combination of chemical cleaning and clean water backwash was the most

effective way to recover the permeate flux; whereas cleaning only with DI water was

least effective and chemical clean alone was insufficient at removing the cake layer from

the membrane (Fan et al., 2007). An effective sequence of cleaning applied in Lim &

Bai’s (2003) experiment is alkali treatment was applied to the module and followed by a

brief rinse of the module with DI water, and then the acid treatment was applied.

17

Recall that the large solids can be absorbed onto the membrane surfaces and cause the

cake/gel layer, air scouring help reduce this type of membrane fouling while chemical

cleaning was insufficient at removing the cake/gel layer (Gao et al., 2011). Air is

injected into the feed water tank in a submerged membrane system which forms air

bubbles, this also where the buoyancy forces associated with the bubbles. This

phenomena keeps the suspension in motion and detaches the deposited cake layer via

scouring to the membrane surface thus reducing the fouling (Pradhan et al., 2012).

An alternate effective method for reducing membrane fouling is applying the

pretreatment process before membrane filtration further that the pretreatment allows for a

higher quality permeate. There are many popular pretreatment technologies such as

peroxidation, biological treatment processes, coagulation and DAF (Braghetta et al.,

1997; Gao et al., 2011). As a cost-effective method, coagulation is one of the most widely

applied pretreatment processes. Coagulation can increase the solid size for faster

sedimentation via aggregating small particles in the feed water. It can also destabilize

contaminants to avoid contaminants to be adsorbed onto the membrane surface (Huang et

al., 2009).

2.4 Coagulation

2.4.1 Introduction

Coagulation and flocculation process is defined as the use of chemicals to destabilize

colloidal particles and aggregate small particles to larger particles via particle collisions

(Metcalf & Eddy, 2003). The coagulation process involves the addition of a cationic

18

species (Al3+

, Fe3+

or polymer) to the wastewater and flowed by subsequent agitation to

bring the negatively charged constituents together for forming the flocs. Studies showed

that up to 90% of solids can be removed by this process (Matilainen et al., 2010;

Vandevivere et al., 1998). Although there are a range of coagulating agents to choose

from, alum (Al2(SO4)3·12-14H2O) remains the type most commonly applied. The

advantages associated with alum includes less sludge formation compared to lime, high

solubility in water and consistent (predictable) performance (Ebeling et al., 2004;

Matilainen et al., 2010). However, alum is toxic with the potential of leading to

neurological conditions and consequently requires to be constantly monitored to prevent

carry over in water (DeWolfe, 2003). Indeed, the water regulations stipulate that total

aluminum (derived from exogenous and endogenous) should be less than 50 mg/l. The

risk of exceeding regulatory limits is controlled by the quantity of the coagulant added to

water, which can be challenging given the coagulation process is dependent on the

concentration of solids, nature of organics and pH of the water.

2.4.2 Applications of Aluminum Sulfate in Food Industrial Wastewater

Specific studies on evaluating the efficacy of coagulation processes on treating

wastewater derived from the fruit and vegetable industry are relatively few. Yet,

examples have been published in the literature on treatment technology directed at

cleaning-up wastewater from the food industry. The general conclusion from studies is

that alum can aggregate a wide range of solids from water provided considerations are

given to dose and pH of the system (Ho & Tan, 1989). For example, Rusten et al. (1990)

found the optimum pH range was 4.5 – 6 with a dosage of 120 – 170 mg/l to achieve a 40

– 67% removal efficiency of COD (Rusten et al., 1990). Many other researchers also

19

found over 50% of COD and over 90% of TSS removal from bakery wastewater or oil

mill wastewater can be achieved (Malakahmad, 2013).

The use of alum to coagulate wastewater derived from fruit and vegetable processing has

not been studied to a great extent and hence represents a knowledge gap. Thus, the alum

has a potential for fruit & vegetable wastewater treatment on COD and TSS removal

accompany with the risk of poor COD removal efficiency. The removal efficiency of

COD depends on the wastewater characteristics since coagulation is agreed that has

difficulties in removing soluble substances (Ho & Tan, 1989). Hence, if the large portion

of COD in the wastewater is soluble COD, coagulation will be insufficient on COD

removal.

2.4.3 Effects of Coagulation on Membrane Fouling

By applying coagulation as the pretreatment for membrane filtration, some researchers

achieved lower tendencies of membrane fouling. For example, Haberkamp et al. (2007)

found AlCl3 had a positive effect on reduction of membrane fouling in a neutral pH

environment via removing macromolecular particles which are humic acid or DOM.

Coagulation has two main mechanisms and they play different roles in controlling

membrane fouling. Lee et al. (2000) applied two different coagulation conditions and

investigated the influences on membrane fouling. One of the conditions was conducted

when the mixed solution had a pH 5 with a dosage of alum of 10 mg/L. The main

mechanism predominating in this range is destabilization. The other coagulation

condition was the traditional pH 6 - 8 environment with a dosage of 30 mg/L alum. The

predominant mechanism was sweep flocs. The results indicated the charge neutralization

20

contributed to higher membrane permeability than sweep flocs mechanism did in a dead-

end submerged hybrid MF. The difference was caused by the cake resistance was smaller

when flocs formed by charge- neutralization while the cake resistance was larger when

flocs formed via sweep floc. However, they did not apply any air scouring to the dead-

end MF, which could affect the abilities of coagulation on controlling membrane fouling.

While many researchers concluded that coagulation as a pre-treatment has a positive

effect on membrane fouling, Braghetta et al. (1997) found with an in-line addition of 45

mg/L alum, membrane fouling was more severe than without adding coagulants. This

may be caused by excess coagulants. Nevertheless, Braghetta et al. (1997) did not give

out the pH range applied in the coagulation, instead of mentioning the condition was

based on enhanced coagulation for cTOC removal. Moreover, limited research had been

applied to coagulation for fruit & vegetable wastewater treatment. The effect of

coagulation on membrane fouling for fruit & vegetable wastewater treatment is needed to

be investigated.

2.5 Dissolved Air Flotation

2.5.1 Introduction

Dissolved air flotation (DAF) is defined as a solid and liquid separation process that

removes particles using granular media filtration (Edzwald, 2010). DAF was being

adopted in mid 1990s by large water utilities and developed rapidly in the last ten years.

DAF can remove particles from liquid by bringing particles to the surface and then using

a skimmer to separate solids/liquid. In order to bring particles to the surface, air is over

dissolved in a saturator at a high pressure and which forms microbubbles when pressure

21

depletion occurs. Microbubbles will attach to particles and in consequence float to the

surface when wastewater is released in the flotation cell at atmospheric pressure (Yoo &

Hsieh, 2010). DAF is thought as a very reliable treatment technology that can achieve a

high removal efficiency over a wide range of flotation overflow rates (Filho & Brando,

2001). This is one of the advantages that make DAF appealing to industries for

wastewater treatment. The other advantage of DAF is fast flotation time. Flotation time is

defined as the time for air-particle flocs to float to the surface of wastewater for

screening. Typical flotation time applied in cases is 5- 6 minutes (Edzwald et al., 1994).

When operating DAF treatment, parameters concerned with DAF process include DAF

configuration, flocs size, bubble size and the ratio of the amount of air to the mass of

solids (Bickerton, 2012; Metcalf & Eddy, 2003). The most applied DAF configuration is

recycle-flow pressure flotation and it is generally employed where coagulation and

flocculation are needed and the flocculated particles are mechanically weak (Al-Shamrani

et al., 2002).

The ideal flocs size for a DAF process is ranging around 25 to 50 µm in diameter

(Edzwald, 2010). A flocculation process is designed to produce large flocs – over

hundreds of µm, DAF still works well with a condensed flocculation stage by utilizing

flocculation detention times as low as 5 to 10 minutes; whereas the conventional

sedimentation plants flocculates 20 to 30 minutes (Bickerton, 2012).

The second key parameter of DAF is bubble size. Microbubbles are expected because

large bubbles initiate the fast rising of flocs and reduce the contact area between bubbles

and particles (Al-Shamrani et al., 2002). In order to produce microbubbles, it is

22

recommended that set the pressure range from 60 to 90 psi in the saturation tank (Al-

Shamrani et al., 2002). The most important and reliable parameter of DAF performance is

the bubble volume. There are two ways to control the amount of air bubbles in the

flotation tank. The first is changing the saturator pressure and the second is either

increasing or decreasing the recycle rate. Recycle rate is the ratio of the amount of over-

saturated water to the volume of wastewater. However, the former method does not vary

much within the pressure in the range of 60 – 90 psi. Hence, the optimal way to control

the air production is changing the recycle rate (Edzwald, 2010).

Lovett and Travers (1986) demonstrated that an air/solids (A/S) ratio >0.030 mL/mg was

required to prevent settling of solids in abattoir wastewater (Lovett & Travers, 1986).

However, this value is different when applying to different kinds of wastewater. The ratio

of the volume of air to the mass of solids has to be obtained by using a laboratory

flotation cell when evaluating the performance of a DAF system (Metcalf & Eddy, 2003).

Although DAF is widely applied in recent years, there are still some limitations. Firstly,

DAF cannot process over turbid wastewater with high-density suspended solids.

Moreover, the weather is a limitation because floats can be frozen in snowy days or sink

back to the tank in rainy days, thus leading to the failure of flocs float to the surface of

the tank, resulting in the failure of DAF process (Crossley & Valade, 2006). In summary,

challenges include the performance on high turbid wastewater, complexity of operation

and need for maintenance.

23

2.5.2 Effects of DAF on Membrane Fouling

DAF has primarily been used in combination with membrane filtration in metal

industries, meat processing, desalination and municipal wastewater treatment plants

(Aparecida Pera do Amaral et al., 2013; Matis et al., 2005; Peleka et al., 2006; Peleka &

Matis, 2008). By using a combination of DAF and either MF or UF, it is possible to

achieve up to 99% in turbidity reduction, along with a significant reduction in membrane

fouling (Braghetta et al., 1997). However, no studies have yet been performed on using

DAF as pretreatment for UF of fruit and vegetable wastewater. Research for effects of

DAF on membrane filtration of vegetable processing wastewater should be conducted.

Moreover, investigating the potential application of a hybrid process with DAF as

pretreatment for membrane filtration is valuable for industries and research as well.

Overall, through the review of literatures, this research will focus on applying

coagulation and DAF as the pretreatment prior to UF for treating vegetative wastewater.

24

Chapter 3 OBJECTIVES

The purposes of the proposed study were to investigate the performance of membrane

filtration on different fruit & vegetable wastewater and the effects of different

pretreatment technologies include coagulation and DAF on membrane fouling control.

The specific objectives include:

1. Characterizing wastewaters derived from different fruit & vegetable processing

facilities and draw a matrix of physical and chemical parameters of the fruit &

vegetable processing wastewater.

2. Adjusting the jar test conditions for spinach wastewater and potato wastewater by

evaluating turbidity and COD/cTOC removal efficiencies.

3. Adjusting the DAF system and operating conditions for removal of TSS, COD

and turbidity for spinach and potato wastewater after coagulation.

4. Comparing coagulation/DAF and coagulation/sedimentation removal abilities of

TSS, BOD5, COD, cTOC, ammonia, nitrate and TP on the two streams of

vegetative wastewater -- spinach wastewater and potato wastewater.

5. Examining the performances of coagulation and coagulation coupled with DAF

on UF fouling control.

6. Examining performances of the same treatment processes on different kinds of

vegetative wastewater.

7. Reviewing performances of different treatment processes in terms of effluent

qualities and suggesting the potential applications of the treatment processes in

the field of vegetative wastewater.

26

Chapter 4 METHODOLOGY

4.1 Material and Methods

4.1.1 Wastewater Sampling

Wastewater from different kinds of food industry was characterized and then divided into

two main categories. Potato processing industries contain processes of transporting

potatoes, manually sorting of the potatoes, pre-washing and/or a second cycle of washing.

Water was used for washing food products and food processing facilities. Similar

processes were applied for carrot industry, ginseng industry and mixed vegetable

industry. Wastewater samples were collected from the inlet point of the settling tank,

where all the wastewater from the facility was gathered and situated before any onsite

treatment plant.

Apple industries have two washing processing lines, each line has one flume. Water from

both flumes will be gathered to a final flume. Wastewater was grabbed from the final

flume. The spinach processing line contains the transporting, manual sorting of spinach,

washing of the leaves and a disinfection process. In order to avoid the effects caused by

disinfection, spinach wastewater was grabbed from the washing tank.

27

Table 4-1 Vegetable wastewater sampling details

Products Sampling times

Sampling volume (L) NO. of sampled industries

Apple 3 2 2

Potato 7 2+ 60 (for three times) 3

Mushroom 1 2 1

Ginseng 2 2 2

Carrot 5 2 2

Spinach 6 50-75 1

Mixed Vegetable

2 2 1

Table 4-1 presented the sampling frequencies and sampling volume of each sampling.

The collected wastewater samples for characterization were placed in a cooler and

transported back to the University of Guelph and analyzed within 48h. Further, for

continuous study of coagulation, DAF and UF treatment processes, 60 L of spinach and

60 L of potato wastewater were sampled each time and stored in a fridge at 4 °C on

campus.

4.1.2 Jar Test Apparatus and Testing Protocol

The jar test apparatus consisted of six identical containers which were used to simulate

the coagulation and flocculation process (Figure 4-1). Each container made from

polymethyl methacrylate (PMMA) beakers (11.5 cm (W) x 11.5 cm (L) x 21 cm (H))

with a work volume of 2 liter, and a central paddle blade that was rotated at a set rate by a

speed control (Phipps & Bird Stirrer, Model 7790-400). Paddles that each has a 14 cm2

cross-sectional area were the main mixing instrument.

28

Figure 4-1 Bench-scale batch jar test apparatus

The mixing protocol included 1 minute of rapid mixing at 300 rpm followed by 20

minutes of slow mixing at 30 rpm. The solution was settled for 30 minutes prior to

sampling. 50 mL of the sample was withdrawn for turbidity and COD/cTOC analysis.

Results of removal efficiency affected by different pH values and different dosages alum

were shown in a contour drawn by R programming. The dosage and pH applied were

shown in Table 4-2 below.

29

Table 4-2 Experimental arrangement of jar tests

Sample Operational Conditions

pH Dose (mg/L) Temperature (°C)

Spinach Wastewater 5, 7 and 9 0, 2.5, 5, 10, 30 and 50 20

Potato Wastewater 5, 7 and 9 0, 50, 100, 200, 250 and

300

20

The coagulant applied in this research was aluminum sulfate (Al2(SO4)3 ·12-14 H2O).

Stock solution was made via dissolving solid aluminum sulfate into de-ionized (DI) water

with the concentration being 500 mg/L of alum. The solution was kept at room

temperature.

In order to maintain the pH value in the mixed solution, the pH was monitored by a pH

meter during slow mixing. 1N of hydrochloric and 1N of sodium hydroxide were used to

adjust the mixed solution to the desired pH value.

4.1.3 DAF Apparatus and Operation

The DAF unit consisted of a pressure vessel (EC Engineering, Alberta, Canada)

containing DI water to be aerated (Figure 4-2). Air was introduced into the vessel through

a ball valve (Cole Parmer, Mississauga, Canada) with the pressure being monitored by a

pressure gauge (Cole Parmer, Mississauga, Canada). Excess pressure was released

through a needle valve on the top of the vessel. The air saturated water was fed into a 2 L

cylinder (Ø = 3.53 cm) (Figure 4-2) containing the wastewater sample to be treated.

Nozzles (EC Engineering, Alberta, and Canada) were connected with water inlet tubes to

cause pressure reduction. Each graduated cylinder was equipped with two sampling

30

valves (Cole Parmer, Mississauga, Canada) as shown in the Figure 4-2. One port was

located 6 cm from the bottom and the other one was inserted at 13 cm from the bottom of

both cylinders. Stands were clamped tight on the cylinders to prevent shaking from

transferring floats to middle layer or bottom layer of treated wastewater.

Figure 4-2 Bench-scale batch DAF apparatus

31

Figure 4-3 Schematic diagram of DAF treatment

The system was optimized by varying the pressure between 50 – 90 psi, to saturate the

water with samples being withdrawn. This allowed for the dissolved oxygen (DO)

content to be determined. The DO concentration was measured by a portable DO meter

(Hach, London, Canada) after saturation, marked as DO final. Measuring the DO final

and compared it to theoretical DO concentration.

Optimum recycle rate and flotation time for each wastewater were determined by

experiments. Conditions and analytical parameters were listed in Table 4-3. When

running DAF operational conditions, the wastewater were pretreated with optimum

coagulation conditions found in previous experiments. Applying coagulant with rapid

mixing and slowing mixing to raw wastewater, which was the same as previous jar test

procedures, followed by transporting the pretreated wastewater to the flotation cylinders.

Starting pumping over-saturated DI water into flotation cylinders for separation. After

measuring the concentration of analytical parameters, timing the dilution factor caused by

recycle rate to the reading concentration for an actual removal percentage of

contaminants.

Air

Over-saturated water

32

Table 4-3 Experimental arrangement of DAF tests

Sample Operational Conditions

Recycle

Rate (%)

Flotation Time (min) Analytical Parameters

Spinach Wastewater 10, 30, 50

and 70

10, 20, 30, 40, 50 Turbidity (NTU) &

TSS (mg/L)

Potato Wastewater 10, 30, 50

and 70

10, 20, 30, 40, 50 Turbidity (NTU), TSS

(mg/L) & COD (mg/L)

4.1.4 Membrane Apparatus and Operation

Dead – end submerged UF membrane modules were fabricated from polyvinylidene

fluoride (PVDF) (GE Water & Process Technologies, 0.04 µm pore size, Ø19 mm). The

surface area of modules were 0.003 – 0.004 m2. A 1L round beaker was used as the tank

for submerging the membrane module and contained the feed water. A data logger

(OMEGA Environmental, Canada) and a pressure gauge (Cole Parmer, Mississauga,

Canada) were used for recording and monitoring the TMP while filtering the wastewater.

The peristaltic pump (Cole Parmer, Mississauga, Canada) provided the suction power to

filter the feed water from the tank into the module loop. A digital balance (Cole Parmer,

Mississauga, Canada) was equipped for recording the weight of the permeate.

33

Figure 4-4 Batch bench-scale dead – end submerged UF system

An air stone was submerged in the feed tank (Pet Valu, Guelph, Canada) which can help

reducing the surface fouling via air scouring. An air flow meter (Cole Parmer,

Mississauga, Canada) was used to help monitoring the stable airflow rate. A schematic

diagram of the lab-scale submerged UF apparatus was shown in Figure 4-55.

34

Figure 4-5 Schematic diagram of dead-end submerged UF system

Three types of feed water were applied to the UF – vegetative raw wastewater, vegetative

coagulated wastewater and vegetative wastewater treated with coagulation/DAF.

Wastewater with coagulation was prepared according to the jar test procedures, however,

without sedimentation, and operational conditions were those found in experiments of jar

tests. The wastewater after DAF was prepared following the DAF procedures, which

including coagulation procedures. Operational conditions of DAF for each kind of

wastewater were the same as those found in DAF experiments. Conditions including

recycle rate and flotation time. Each condition chosen would be illustrated in the results

section of coagulation and DAF tests.

The filtration cycle was set by a timer with 9-minutes permeation slash 1-minutes off.

After recording the weight of permeate water, the permeate water was recycled back to

the feed water beaker. Filtration was terminated when the TMP was close to 50 kPa.

Filtration was operated under constant flux.

35

The operational filtration flux was recommended according to critical flux tests. Critical

fluxes were determined by standard flux-step method (Clech et al., 2003). When a

different increasing transmembrane pressure trend was found in the critical flux

determination, the flux before that increasing point was the critical flux. Set the operating

flux below critical fluxes and then used for further filtration. Potato wastewater filtration

flux was also determined by critical flux tests of the three types of potato wastewater.

Filtration of DI water was run prior to feed wastewater filtration for measuring membrane

resistance.

Short-term filtration tests were used to determine the air scouring rate. Three air scouring

rate – 1 L/min, 2 L/min and 4L/min, were tested for choosing the scouring rate in terms

of reducing the surface fouling. Modules applied in the research were used membrane

module. Before and after each filtration test, the membranes were cleaned with distilled

water and gently scrubbing with sponge. The module was soaked in 200 mg/L sodium

hypochlorite solution for 24 hours, followed by soaking in 2000 mg/L citric acid for

another 24 hours before filtration and measuring the membrane resistance.

4.2 Analytical Methods

COD is reported in terms mg O2/L of sample; it was quantified by using HACH DBR 200

Reactor (Hach Co., Loveland, CO) for digestion and HACH DR 2800 (Hach Co.,

Loveland, CO) for colorimetric determination method according to Standard Method

5220D (APHA, AWWA, WEF, 1989). The results in mg/L BOD5 are defined as the mg

O2/L of sample by analytical procedures adopted from the Standard Methods, Method

5210 (APHA, AWWA, WEF, 1989).

36

TSS is reported in terms of mg TSS/L; it was quantified by using a filtration method

described as the TSS which dried at 103-105oC method according to Standard Method

2540D (APHA, AWWA, WEF, 1989). The filter paper (Whatman 934-AH Glass

Microfiber Filters, 1.5um, 11cm) was purchased from Cole Parmer. TS was measured

similar to TSS and was tested according to the Standard Methods, Method 5210 (APHA,

AWWA, WEF, 1989). Turbidity was measured by turbidity meter (Micro 100, HF

Science Inc.) adopted as NTU.

Measurements of cTOC and total nitrogen (TN) were done by using a Total Organic

Carbon analyzer (Model: TOC-VCSH TOC analyzer, Shimadzu), which was also

approved by USEPA and following Standard Method 5310B (APHA, AWWA, WEF,

1989). Dissolved organic carbon (DOC) measurement is similar to cTOC. DOC

measurement samples were obtained by filtering wastewater through a 0.45μm

polycarbonate membrane filter and analysis performed with the cTOC analyzer (Model:

TOC-VCSH TOC analyzer, Shimadzu).

Other nutrient parameters, which contains nitrate (NO3-N), ammonia (NH4

+-N) and TP

were tested by using Hach method -- Method 10020, Method 10023 (low range) / Method

10031 (high range) and Method 8190, respectively.

Analytical parameters were reported as average concentration plus or minus standard

deviation.

For membrane fouling results, the fouling resistance was calculated according to Darcy’s

Law (Yang, 2005) and the definition of fouling resistance (Metcalf & Eddy, 2003):

37

𝑅𝑡 =∆𝑃

𝜇𝐽 𝑅𝑓 = 𝑅𝑡 − 𝑅𝑚 (1)

Where: J – permeate flux, m/s

∆P – transmembrane pressure, Pa

μ– viscosity, Pa·s

Rt – total membrane resistance, 1/m

Rm – membrane resistance, 1/m

The average fouling rate was calculated as the difference between the initial and final

TMP, divided by the duration of filtration cycle below (Fan, 2006; Le-Clech et al., 2006):

FR =𝑇𝑀𝑃𝑡2−𝑇𝑀𝑃𝑡1

𝑡2−𝑡1 Or FR =

𝑅𝑓2−𝑅𝑓1𝑡2−𝑡1

(2)

Where: FR – fouling rate, kPa/min or 1/m/min

TMP – transmembrane pressure, kPa

Rf – fouling resistance, 1/m

t2 – filtration ending time, min

t1 – filtration start time, min

38

4.3 QC/QA

Wastewater samples were analyzed the same day as they were delivered and analyzed

using calibrated equipment. The cTOC meter required standard solutions for making new

calibration curves and the accuracy was checked before using. The room temperature was

set to 20 ºC to avoid affecting the flocs of DAF treatment. It was necessary for the jar test

and DAF apparatus to use the same conditions in the six different jars or the two

cylinders. The same wastewater was also used and analyzed for turbidity to assure the

system was consistent. Specific to membrane filtration, each vegetative wastewater and

treated wastewater were completed within two days in order to minimize the changing

parameters affecting fouling results.

All the experimental data was analyzed by coefficient of variance which can determine

whether the value was statistically reasonable or not. Results such as parameters were

illustrated by an average with standard deviation shown in figures by using Microsoft

Excel. The optimum conditions for jar tests and DAF were tested for duplicate and

averaged results which was analyzed via R programming or Microsoft Excel. Standard

deviations were investigated for data accuracy.

39

Chapter 5 RESULTS AND DISSCUSSION

5.1 Fruit & Vegetable Wastewater Characterization

Wastewater samples were collected from leafy green, mixed vegetable, carrot, ginseng,

potato and apple processing facilities and then subsequently characterized in terms of

turbidity, solids contents, BOD5, COD, cTOC and nutrients (Table 5-1).

With respect to solids, potato and ginseng wastewater had significantly higher TSS

concentration than other types of wastewater (Table 5-1). But in terms of organic matters,

apple wastewater contained the highest concentration of cTOC and BOD5, followed by

mushroom wastewater. Wastewater from apple and potato processing facilities had

higher COD and nutrient contents compared to the other types of tested wastewater.

Previous studies have also reported high COD content of potato wastewater. Burgoon et

al. (1999) and Muniraj et al. (2013) found the potato processing wastewater (which

included the peeling process) contained 2700 – 37000 mg/L COD, while in this research,

where there was no peeling process, the COD concentration of potato wastewater was

700 – 7800 mg/L. Physical and biological characteristics of carrot found in this research

seem to be consistent with those in other researches (Hamilton, 2006; Kern, 2006).

In terms of standard deviations, for example, ginseng wastewater had a standard

deviation of TSS larger than the average TSS concentration. The main reason of this is

that the processes in food industries are different. One of the sampled ginseng industries

has a shaking process before washing the products, in turn; they introduce fewer solids

into washing water. However, the other sampled ginseng industry does not have a

40

shaking process before washing ginsengs. Hence, wastewater from the second industry

contained higher level of TSS than the former one. With respect to this problem, the

matrix of fruit & vegetable processing wastewater can be developed to a more specific

one, which is including the effects of specific processes on the same products.

41

Table 5-1 Characteristics of different vegetative wastewater

Wastewater TSS

(mg/L)

COD

(mg/L)

BOD5

(mg/L)

cTOC

(mg/l)

BOD5/

COD

COD/

cTOC

NO3-N

(mg/L)

NH4+-N

(mg/L)

Filtered

TN

(mg/L)

TP

(mg/L)

pH Turbidity

(NTU)

Apple 130±

10

2000±

2700

1200±

1600

680±

920

0.38±

0.29

4.4±

2.1

24±

28

0.3±0.1 19±23 38±28 10.4 56

Potato 3600±

2600

2200±

2100

240±

270

87±46 0.11±

0.06

36±

34

3.2±3.3 8.8±12 20±19 30±32 7.5±

0.4

870±140

Mushroom 400±

62

1800±

51

960±16 460 0.55±

0.01

3.8 4.0 0.1 4.0 2.9 nd nd

Carrot 200±

14

420±

130

56±20 110±10 0.15±

0.08

4.6±

2.2

2.0±0.6 0.9±1.0 2±1 1.7±

1.3

7.7±

0.1

410±410

Spinach 110±

64

370±

110

220±88 130±15 0.59±

0.01

3.1±

0.3

2.6±1.1 0.4±0.2 3±1 2.1±

1.5

4.7±

0.7

92±51

Mixed

Vegetable

550±

130

140±

39

95 27±1.0 0.57 5.1±

1.6

9.7 0.1 23 4.7 7.2±

0.7

560±42

Ginseng 700±

1100

75±48 8.9 36±5.0 0.08 1.5±

4.0

1.4±0.2 0.8±1.0 0.9±0.1 1.2±

0.6

7.0±

0.4

360±330

42

Although different vegetative wastewater had a wide variety of different characteristics,

these types of wastewater can be classified into two categories. The BOD5/COD ratio is

the most applicable parameter. Metcalf & Eddy (2003) demonstrated that the BOD5/COD

ratio can be used to determine whether the wastewater is suitable for biological treatment.

When the BOD5/COD ratio is over 0.5, this kind of wastewater is easily biodegradable

and suitable for biological treatment; whereas when the ratio is lower than 0.2, this type

of wastewater is barely biodegradable and compatible with physical operation and

chemical treatment. Thus, the BOD5/COD ratio was used in this section to divide the

sample wastewater into two categories: easily biodegradable group and barely

biodegradable group.

Potato, ginseng and carrot wastewater had low ratio numbers of 0.11 ± 0.06, 0.08 and

0.15 ± 0.08, respectively. The low BOD5/COD ratio implies the solids within the

wastewater were soils rather than organic substrates that could be utilized by microbes.

Although these kinds of wastewater maybe not compatible with biological water

treatment technologies when compared to wastewater that is rich of low molecular weight

soluble solids, the high inorganic content could be more amenable to physical operations.

According to Table 5-1, mushroom, spinach and mixed vegetative wastewater had

BOD5/COD ratios close to 0.6, which is considered suitable for biological treatment.

Similarly, apple wastewater had a ratio of around 0.5, which is also regarded as easily

biodegradable. Potato, carrot and ginseng are stem or root products and they all had a

BOD5/COD ratio of less than 0.2; hence unsuitable for biological treatment. Potato

43

wastewater and wastewater derived from leafy green processing were selected for further

study given the contrasting characteristics.

Spinach wastewater will be a challenge for most biological treatment technologies,

because of the low concentrations of solid contents and acidic (pH 4.7 ± 0.7) pH

environment, both of which will limit microbial growth (Metcalf & Eddy, 2003). More

significantly, the diluted nature of the solids in spent leafy green wastewater means that

little treatment is required to meet the regulatory standards, making treatment

unnecessary. Potato wastewater is very representative of low BOD5/COD ratio group

since it had the highest TSS concentration coupling with high COD and nutrient

concentrations. Furthermore, by looking at the parameters of all tested fruit and vegetable

wastewater in Table 5-1, BOD5, TP and TSS prove to be the main problem when

treatment processes are applied to satisfy the sanitary sewer limits.

Treatment technologies applied in this research were physical operations such as DAF

and UF and chemical treatment method like coagulation. If there are treatment

technologies that show economical and high removal efficiencies on tested wastewater,

the treatment technologies can probably be adopted for other similar kinds of vegetative

wastewater.

44

5.2 Coagulation

5.2.1 Turbidity Removal

Effects of pH and coagulant concentration on coagulation treatment performances were

shown in contours in terms of removal efficiencies of the turbidity. After gathering the

average of the jar test results, a contour was plotted by using R programming with pH

values as the horizontal axis and alum dosage as the vertical axis.

Figure 5-1 Turbidity removal percentage from spinach wastewater by coagulation

As was shown in Figure 5-1, when dosing concentration was smaller than 10 mg/L,

higher dosages of alum were needed to achieve 95% turbidity removal efficiency in pH

range 5 - 6 for spinach wastewater, while at higher pH environments such as a pH of 6,

45

the dosage needed was only 5 mg/L. However, when the alum dosage was over 10 mg/L,

in the range of pH 5 – 7, higher pH environments needed more coagulants. Besides, for

pH of 7 – 9, less alum was added into the wastewater and better removal efficiencies

were achieved when the coagulant dosage was over 10 mg/L.

The results here were different from many other wastewater coagulation results.

Typically, higher pH environment, such as pH 7 and 8 requires dose from 20 mg/L to 60

mg/L to achieve the optimum particle removal by sweeping flocks (Metcalf & Eddy,

2003). There could be two reasons: 1, the turbidity of spinach is 66 ± 2 NTU, which is

one fourth of that in municipal wastewater. Hence, while municipal wastewater needs 20

mg/L of alum for sweep flock mechanism, 10 mg/L of alum was sufficient for spinach

wastewater. There were researches which also pointed out less coagulant will be needed

when the turbidity is smaller (Lin et al., 2008); 2, with respect to charge neutralization,

dosage over 10 mg/L is regarded as over dose, which can re-stabilize the particles by

resulting in positively charged particles and less turbidity removal (DeWolfe, 2003).

46

Figure 5-2 Turbidity removal percentage from potato wastewater by coagulation

For potato wastewater, 90% removal efficiency was achieved by dosing 50 mg/L of alum

at a pH ranges from 6.5 to 9. Interestingly, with a dosage of 250 mg/L at pH 5, 7 and 9,

the turbidity was 3.12 NTU, 2.29 NTU and 2.45 NTU, respectively. When dosing of 100

mg/L at pH 5, 7 and 9, turbidity results were 12.7 NTU, 3.23 NTU and 3.37 NTU,

respectively. As results show in Figure 5-2, the turbidity of potato wastewater was always

too turbid to be detected and regarded as over 1000 NTU. So from turbidity removal

results, the removal efficiency of potato wastewater via coagulation was 98.7% ~ 99.8%.

Overall, alum works efficiently for both spinach wastewater and potato wastewater in

terms of turbidity removal.

47

5.2.2 COD/cTOC Removal

TOC analyzer was out of work during the optimization of jar test conditions with spinach

wastewater, so COD was applied to substitute for cTOC with an observed a stable COD

to cTOC ratio in the raw wastewater.

Figure 5-3 COD removal percentage from spinach wastewater by coagulation

While the optimum for turbidity removal by coagulation was at pH 7 and 5 mg/l alum,

the COD removal was optimized at pH 5.5 and 10 mg/L alum. The higher COD removal

in a slightly acidic environment was also observed in an earlier study (Xie, 2006), where

the solubility of the organic matter was reduced in the lower pH condition. Many

48

researchers have suggested that with the use of aluminum based coagulants, pH

conditions should be controlled within 4.5 – 6.5 to optimize organic removal on food

industry wastewater (Ho & Tan, 1989; Liu & Lien, 2001; Rusten et al., 1990).

However, compared to the previous studies listed in literature review, alum had

considerably poor removal abilities of COD on spinach wastewater. The difference is

caused by the percentage of soluble organic matters in the wastewater. For example,

Rusten et al. (1990) found that the removal efficiency of COD of dairy wastewater was

40-67%, while the soluble COD to total COD ratio varied from 0.48 to 0.7.

Although soluble COD was not measured, argument could be made that the soluble COD

was higher or equal to the COD concentration of permeate. This is because the nominal

pore size of the membrane material applied in this research is 0.04 micron, smaller than

the pore size which defines dissolved solids at 0.45 µm. From the results shown in Figure

5-20, the COD concentration before filtration of spinach raw water was 370 mg/L and

after UF of spinach raw water, the COD concentration was 360 mg/L. It implied that over

97% of COD in spinach was soluble COD. This can explain why coagulation cannot

remove a higher percentage of COD from the spinach wastewater.

49

Figure 5-4 CTOC removal percentage from potato wastewater by coagulation

At the same dosage as 250mg/L of alum, more cTOC was removed in slightly acidic

environment of potato wastewater. However, the difference was negligible. RE of cTOC

at a pH of 5 with dosing of 250 mg/L alum was 75%, while at a pH of 7 with the same

dosage, the RE was 72%. The coefficient of variance of these two numbers is 0.06,

implying these two means have no distinct differences. If the pH of 5 is applied, there

will be a risky problem namely the residual alum maybe over the limitations set by the

city by-law (Toronto, 2000). Thus, dosing 250 mg/L of alum at pH 7 was chosen as the

optimum jar test condition of potato wastewater. Compared with jar test results on

spinach wastewater and potato wastewater, it is obvious that alum has better removal

abilities on organic matters for potato wastewater.

50

5.3 DAF Results

5.3.1 DAF Water Saturation

In order to make sure the water in pressure vessel was fully over-saturated, saturating

pressure and saturation time were optimized. Figure 5-5 showed the effects of saturation

pressure on saturation rate.

Figure 5-5 Effects of pressure on DAF water saturation

However, based on Henry’s law (Schnabel et al., 2005):

(3)

Where: p -- the partial pressure of the gaseous solute above the solution (atm)

c – The concentration of the dissolved gas (mol/L)

0

5

10

15

20

25

50 60 70 80 90

DO

Co

ncen

trati

on

(%

)

Saturation Pressure (psi)

DOfconcentration

51

KH -- a constant with the dimensions of pressure divided by concentration, for

oxygen at 298 K is 769.2 L·atm/mol.

According to the formula, the dissolved oxygen concentration in the water should be 42

mg/L at 70 psi at 298 K. However, the DO concentrations at different pressures in the

water presented in the Figure 5-5 were smaller than 20 mg/L. The smaller value

compared to theoretical estimate was probably caused by the escape of oxygen when

measuring the DO, since the water was measured at atmospheric pressure. At 1 atm and

298 K, the DO concentration in water should be 8.56 mg/L. Hence, the excess oxygen

leaked out from the over-saturated water and caused the unbalanced values. In order to

get the accurate saturation efficiency, developed technology is needed for DO saturating

measurement. Method applied in this experiment was not credential for finding the

optimum saturation pressure. However, in this research, it is not a key parameter for the

adjustment of DAF operations. 70 psi was chosen as the saturation pressure. Typically,

pressure ranges from 60 to 90 psi are recommended which ensures the saturation can

produce the desire fine bubble. Moreover, pressure over 500 kPa (~70 psi) has a small

effect on producing desire bubble size (Edzwald, 1995).

The parameters that primarily affect the batch bench-scale DAF performance are

concentration of particles and the amount of air introduced to the system (Edzwald,

2010). These two factors can be summed in the formation of the ratio of the amount of air

to the mass of solids (A/S) (Metcalf & Eddy, 2003). The A/S ratio varies for every kind

of wastewater and must be determined by investigating the effect of recycle rate on DAF

performance. The recycle rate is defined as the volume of saturated water to the volume

52

of wastewater ratio (Edzwald, 2010). The appropriate amount of saturated water was

investigated by applying different recycle rates for each wastewater.

5.3.2 Contaminant Removal

According to the observation of results in Figure 5-6, over 80% of turbidity was removed

by DAF with all different recycle rates. However, when the 30% of recycle rate was

applied to the spinach wastewater after coagulation, around 80% of TSS was removed;

whereas when other recycle rate (10%, 50% or 70%) was applied, only 70% of TSS was

removed. Thus, 30% of recycle rate is suitable for the treatment of spinach wastewater

and would be applied in further experiments.

Figure 5-6 Effects of DAF recycle rate on suspended solids removal in the treatment of

spinach wastewater

0

20

40

60

80

100

0 15 30 45 60 75

Rem

ov

al E

ffic

ien

cy (

%)

Recycle Rate (%)

Turbidity

TSS

53

Figure 5-7 Effects of DAF flotation time on turbidity removal in the treatment of spinach

wastewater

Unlike the recycle rate, the flotation time had no significant influence on turbidity

removal (Figure 5-7). Thus, a shorter time 10 minutes was adopted for flotation and

further research.

0

20

40

60

80

100

0 10 20 30 40 50

Rem

ov

al E

ffic

ien

cy (

%)

Flotation Time (min)

Turbidity

54

Figure 5-8 Effects of DAF recycle rate on contaminants removal efficiencies in the

treatment of potato wastewater

The removal of COD by DAF from potato wastewater was less than 40% for every

recycle rate applied in this research, which was significantly low when compared to the

removal of turbidity and TSS. Around 90% of turbidity and TSS were removed at a

recycle rate of 30%. Nevertheless, when applying a 10% recycle rate in DAF for potato

wastewater treatment, less than 80% of turbidity was removed. This was mainly because

the recycle rate was too low to introduce sufficient fine bubbles for carrying solids to the

surface for the potato wastewater. This also explained why recycle rate of 30% and 50%

had better removal abilities on different parameters as was shown in Figure 5-8.

However, with a 70% recycle rate, the removal efficiencies of turbidity and TSS on

potato wastewater were decreased when compared with applying a recycle rate of 30%. It

was because while doing the DAF treatment for potato wastewater, at least 5 cm thick of

0

20

40

60

80

100

120

140

0 10 20 30 40 50 60 70

Rem

ov

al E

ffic

ien

cy (

%)

Recycle Rate (%)

Turbidity

TSS

COD

55

settling was observed during the flotation. The settling which occurred in the graduated

cylinder during flotation was due to the fact that solids in potato wastewater after

coagulation were too heavy to be carried to the surface by fine bubbles. Hence, these

heavy solids kept settling down. However, a 70% of recycle rate, which introduced too

much air into the graduate cylinder, prevented the heavy solids from settling down and

kept solids suspended in the middle layer. Overall, a recycle rate of 30% was adopted as

the operational condition for the potato wastewater.

Figure 5-9 Effects of DAF flotation time on suspended solids removal efficiencies in the

treatment of potato wastewater

Similar to the results shown in Figure 5-7, flotation time still did not show significant

differences, 70 ± 3% for turbidity RE and 90 ± 5.5 % for TSS RE over 10 to 50 minutes

flotation time. However, from observation during the experiments, there was a challenge

with 10 minutes flotation time. For 10 minutes flotation of potato wastewater, treated

potato wastewater can only be gathered by the higher position sampling port, which is 13

0

20

40

60

80

100

0 10 20 30 40 50

Rem

ov

al E

ffic

ien

cy (

%)

Flotation Time (min)

Turbidity

TSS

56

cm from the bottom due to the block of lower sampling port from settling solid. After 30

minutes, the settling solids were thickened and the lower sampling port was available for

sampling. Hence, for the purpose of gathering an increasing amount of treated water for

characterization and further filtration, 30 minutes of flotation time was adopted for

further operations.

5.3.3 Comparison between Coagulation - Sedimentation and Coagulation -DAF

From Table 5-2, it is apparent that both the spinach after coagulation/settling and potato

after coagulation/sedimentation had better TSS and COD removal ability compared to

spinach wastewater after DAF (SD) and potato wastewater after DAF (PD), respectively.

However, the results were different from other studies which also compared the DAF and

sedimentation. Both Bourgeois et al. (2004) and Khiadani (2014) concluded that the DAF

had slightly higher contaminants removal efficiency than traditional sedimentation. This

could be for two reasons: one is the operation condition, and the other is the apparatus

design dimensions. For Khiadani (2014), he applied a continuous pilot-scale DAF system

and sedimentation apparatus in his research, which is different from this research.

Hydraulic condition can reduce the settling removal abilities by affecting the formation

and flocks structure via shear stress (Ma et al., 2012). Bourgeois et al. (2004) also applied

a batch jar test DAF apparatus. Thus, the difference may due to the apparatus design.

Both of them have a smaller width to length ratio than the ratio of that of the DAF

apparatus applied in this research. Dockko et al. (2014) has already demonstrated, by

increasing the diameter of reaction tube, that contaminants can be more efficiently

removed by DAF since there is more space for micro bubble binding particles or

contaminants.

57

Table 5-2 Spinach and potato raw water characteristics and effluent results from coagulation and sedimentation or by coagulation and

DAF

Sample TSS

(mg/L)

cTOC

(mg/L)

COD

(mg/L)

BOD5

(mg/L)

TS (mg/L) TDS

(mg/L)

Filtered

TN

(mg/L)

NO3-N

(mg/L) TP

(mg/L)

NH4+-N

(mg/L)

SR 110±64 130±39 370±110 220±88 520±110 430±110 3±0 2.6±1.1 2.1±1.5 0.4±0.2

SCS 4.3±2.9 120±44 340±120 150±130 910±18 650±450 3±0 2.8±0.1 0.9±0.5 0.3±0.2

SD 10±5.9 71±55 360±160 140±130 810±260 670±290 2±1 2.7±0.6 0.4±0.4 0.3±0.2

PR 3000±1000 71±58 1200±480 150±89 3600±1600 1000±630 24±21 2.2±1.0 15±13 3.4±2.4

PCS 30±20 19±19 170±220 ND 620±300 600±290 16±14 1.4±0.2 0.9±0.8 3.9±3.0

PD 100±30 20±15 250±230 210±4.0 560±240 450±210 13±14 1.7±0.5 1.7±0.5 2.5±2.2

SR/PR: Spinach / Potato raw wastewater; SCS/PCS: Spinach / Potato wastewater after coagulation - sedimentation; SD/PD: Spinach /

Potato wastewater after coagulation – DAF.

58

In addition, for TP removal efficiency, while potato wastewater after DAF had worse

removal efficiency than potato wastewater after coagulation – sedimentation, spinach

wastewater after DAF had better removal efficiency than spinach wastewater after

coagulation-sedimentation. It implied that sedimentation was more suitable for more

turbid wastewater. This was maybe caused by particles size in water body. More micron

particle in treated water contributes to the high removal efficiency of DAF while in

contrast; larger particle results in the low removal efficiency of DAF. However, with

lacking of particle size tests, it is hard to conclude the reasons that caused the differences

of removal abilities of the same treatment process for different wastewater. From Figure

5-10 and Figure 5-11, it is obvious that, coagulation with sedimentation and coagulation

with DAF both can remove 66 – 85% TP of both spinach and potato wastewater by

adding aluminum sulfate.

Coagulation and DAF can remove more contaminants with respect to COD, TN and

cTOC from potato wastewater compared to those derived from spinach processing

wastewater. The two kinds of wastewater have many differences as discussed before:

more solids content in potato wastewater while higher cTOC concentration in spinach

wastewater. Spinach had a high cTOC to COD ratio at 0.36, while potato had a ratio as

0.06; BOD5 to COD ratio of spinach was 0.6 while that of potato was 0.12. The spinach

had a high percentage of soluble COD. These differences implied that the coagulation

and DAF will be more suitable for wastewater which has a low cTOC/COD or

BOD5/COD ratio and wastewater which contains a lower percentage of soluble COD.

59


coagulation - DAF of spinach wastewater


coagulation - DAF of potato wastewater

96

7

19 13

67

6

19

0

77

5 17

27

85

21

24

21

0

20

40

60

80

100

120

TSS BOD5 COD cTOC TP NH4+-N NO3-N TN

Rem

ov

al eff

icie

ncy (

%) Sedimentation

DAF

99

73

70

85

30

37

96

73 66

83

52

25

0

20

40

60

80

100

120

TSS COD cTOC TP TN NO3-N

Rem

ov

al eff

icie

ncy (

%)

Sedimentation

DAF

60

Moreover, the NO3-N removals were not obvious in spinach wastewater treatment via

coagulation or DAF. Only DAF showed 20% removal efficiency on TN, but when

tracking down the actual values in Table 5-2, the concentration of filtered TN of spinach

raw water was 3 mg/L and DAF is 2 mg/L. For potato wastewater, concentration of TN

was reduced from 24 mg/L to 13 mg/L. This result highlights the discussion that physical

and chemical treatment processes are more applicable for wastewater with a low BOD5 to

COD ratio.

5.4 Membrane Filtration of Pretreated Spinach Wastewater

5.4.1 Air Scouring Rate Selection

Membrane fouling of ultrafiltration membranes results in decreased filtration rates and

consequently the efficiency of the process. In order to reduce the influence of surface

fouling, air scouring was applied during filtration. Three different air scouring rates – 1

L/min, 2 L/min and 4 L/min were applied for adjusting this operation condition.

Calculations of the fouling rates for 1 L/min, 2 L/min and 4 L/min air scouring rate, were

found to be 1.9x1010

1/m·min-1

, 0.8x1010

1/m·min-1

and 0.6x1010

1/m·min-1

, respectively

(Figure 5-12). Although the 4 L/min scouring rate had a non-significant smaller fouling

rate, the 2 L/min scouring rate was more cost - effective in terms of energy demand. The

fouling rate increased 25% when applied with a 2 L/min air scouring rate from 4 L/min

air scouring rate, but the energy was conserved by 100% when applied with a 2 L/min air

scouring rate from a 4 L/min air scouring rate. Hence, for the spinach wastewater, 2

L/min was adopted as the air scouring rate during the membrane filtration.

61


spinach wastewater

5.4.2 Critical Fluxes of Spinach Wastewater and Wastewater after Pretreatment

Each kind of feed wastewater was filtered with different fluxes for adjusting the filtration

conditions. The critical fluxes of spinach raw wastewater, spinach wastewater after

coagulation and spinach wastewater after DAF were shown in Figure 5-13, Figure 5-14

and Figure 5-15, respectively.

0.00E+00

2.00E+11

4.00E+11

6.00E+11

8.00E+11

1.00E+12

0 10 20 30 40 50

Fo

ulin

g R

esis

tan

ce (

1/m

)

Time (min)

2L/min

1L/min

4L/min

62

Figure 5-13 Critical flux measurement of spinach raw wastewater

Figure 5-14 Critical flux measurement of spinach wastewater after coagulation

0

10

20

30

40

50

60

70

0

10

20

30

40

50

0 10 20 30 40 50

TM

P

(kP

a)

Time (min)

TMP (kPa)

Flux (LMH)

0

10

20

30

40

50

0

10

20

30

40

50

60

0 10 20 30 40 50 60

TM

P (

kP

a)

Time (min)

TMP (kPa)

Flux (LMH)

Flu

x (L

MH

)

63

Figure 5-15 Critical flux measurement of spinach wastewater after coagulation and DAF

Interestingly, for spinach raw wastewater, a flux of 40 LMH was over the critical flux,

since the TMP increased rapidly in one cycle of filtration. The fouling rate with respect to

TMP and a flux of 40 LMH was 1.54 kPa/min during the 9- minute filtration test while

the fouling rate of the previous flux of 27 LMH was 0.61 kPa/min.

According to the definition of critical flux, the flux of 27 LMH was adopted as the

critical flux of spinach raw wastewater, and 30 LMH was regarded as the critical flux for

spinach wastewater after coagulation. Besides, spinach wastewater after coagulation and

DAF has the highest critical flux which was observed at 43 LMH from Figure 5-15.

According to three critical flux tests, a constant flux operated during the UF was set

around 30 LMH.

0

10

20

30

40

50

60

0

10

20

30

40

50

60

0 10 20 30 40 50 60

TM

P （

kP

a)

Time (min)

TMP (kPa)

Flux (LMH)

64

Although spinach wastewater after coagulation/DAF (SD) had a significantly higher

operating flux than spinach wastewater after coagulation and spinach raw wastewater

(SR), it is now generally accepted that the critical flux test cannot predict the absolute

permeation ability of the membrane (Le-Clech et al., 2006). Operations below the critical

flux can slow down the increase of TMP, thus reducing the operation cost with the

reducing of chemical cleaning frequencies and membrane changing (Stoller & Chianese,

2006).

5.4.3 Membrane Fouling

For spinach raw wastewater, the main difference between test 1 and test 2 was that the

TSS for test 1 was 130 ± 8 mg/L, while for test 2 was 32 ± 1 mg/L. The turbidity for test

1 and 2 were 65 NTU and 27 NTU, respectively. Moreover, it is 95% confident that the

TSS, cTOC and turbidity of spinach raw water (SR) were the same as those of spinach

wastewater after coagulation (SC). This implies these three parameters are likely to have

no influence on membrane fouling with UF between SR and SC in each test. The cTOC

concentration may affect the membrane fouling between SR/SC and SD.

It is apparent that after coagulation, TSS of SC was larger than SR in both tests. This

could be after coagulation, when some dissolved particles (< 1.5 µm) formed into

colloids or even larger particles (> 1.5 µm). In the meantime, pH was adjusted to 5.5

from 4.1, decreasing the solubility of organic matters, and thus dissolving matters

crystallized to colloids. Therefore, when measuring the TSS, more solids were retained

on the filter paper so that a higher concentration of TSS in SC was observed.

65

Overall, there were different fouling rates observed between spinach raw water and

spinach wastewater after coagulation, and the reason for this difference should not be

turbidity, TSS or cTOC. This conclusion can help determine the potential reason for the

fouling of spinach wastewater.

66

Table 5-3 Spinach feed water parameters for UF Test 1 and Test 2

Feed Water TSS

(mg/L)

pH cTOC

(mg/L)

DOC

(mg/L)

NO3-N

(mg/L) TP

(mg/L)

NH4+-N

(mg/L)

COD

(mg/L)

BOD5

(mg/L)

Turbidity

(NTU)

SR Test 1 130 4.1 160 150 0.7 3.8 0.1 490 280 65

SC Test 1 160 5.4 150 150 0.6 3.7 0.1 480 270 67

SD Test 1 10 5.5 130 120 0.5 0.9 0.1 310 190 4.3

SR Test 2 32 4.3 130 120 2.7 2.2 0.4 360 18 27

SC Test 2 60 5.7 120 130 2.0 2.3 0.4 360 200 26

SD Test 2 3.0 5.7 100 94 1.9 0.5 0.3 260 150 3.8

67

Figure 5-16 presented the fouling rate of spinach raw wastewater increased significantly

in the 140- minute filtration when compared after coagulation and after DAF, while UF

with coagulation had higher fouling resistances than UF with DAF. Although both

coagulation and DAF as pretreatment did not significantly improve effluent qualities after

UF, they significantly reduced the membrane fouling of spinach wastewater. Moreover,

according to the fouling rates shown in Figure 5-17 and Figure 5-19, the fouling rates of

wastewater after DAF were smaller than that of wastewater after coagulation in both

filtration tests. These implied that DAF as pretreatment had better fouling control than

coagulation for UF treatment of spinach wastewater.

DOC is highly related to humic substances (HS) that represent the highest proportion of

soluble solids (Tian et al., 2013). HS is reported to be one of the most severe membrane

foulants in many studies (Fan, 2006; Reimann, 1997; Zularisam et al., 2006). However,

combined with certain feed water DOC differences, DOC had no significant effect on

membrane fouling. As mentioned before, the DOC concentration in spinach raw

wastewater and spinach wastewater after coagulation were the same, but the fouling rate

of raw wastewater was 2.3 times higher than that of wastewater after coagulation.

68


coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in UF test 1



0.0E+00

3.0E+11

6.0E+11

9.0E+11

1.2E+12

1.5E+12

1.8E+12

2.1E+12

10 30 50 70 90 110 130 150

Fo

ulin

g r

esis

tan

ce (

1/m

)

Time (min)

After coagulation

After DAF

Raw

0

0.1

0.2

0.3

0.4

0.5

0 30 60 90 120 150

Fo

ulin

g r

ate

(kP

a/m

in)

Time (min)

SR SC SD

69





0

7E+10

1.4E+11

2.1E+11

2.8E+11

3.5E+11

4.2E+11

10 30 50 70 90 110 130

Fo

ulin

g r

esis

tan

ce (

1/m

)

Time (min)

After coagulation

After DAF

Raw

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 20 40 60 80 100 120 140 160

Fo

ulin

g r

ate

(kP

a/m

in)

Time (min)

SR SC SD

70

Tian et al. (2013) also found similar results that no significant correlation was observed

between DOC and UF fouling potential. They suggested that the ratio of NOM/EfOM

molecular size to membrane pore size might be the more important factor on membrane

fouling. Lim & Bai (2003) also concluded that the size of small particles which is

expected to be close to the membrane pore size can cause internal and external pore

blocking.

However, lacking of analysis of particle size, there is no way to relate their conclusions to

this research. This highlights the importance of particle size analysis again. However,

considering the detection limit of particle size analyzer, 20% of solids have to be

represented in the wastewater. For measuring the particle size, at least 20 L of each feed

wastewater was needed due to the preparation and centrifuge before measuring. A lab-

scale apparatus is not enough for preparing 20 L of spinach wastewater after DAF,

because the DAF apparatus can only hold 2 L spinach wastewater.

Comparing the two tests, test 2 had a much smaller fouling rate than test 1, but it was

difficult to formulate a reason for this. The potential factor may be particular matters.

Turbidity and TSS in test 2 were smaller than those in test 1. However, when comparing

wastewater after DAF in test 1 with wastewater after coagulation in test 2, wastewater

after coagulation in test 2 had higher TSS and turbidity levels than wastewater after DAF

in test 1 as well while the fouling resistance of wastewater after coagulation in test 2 was

smaller than wastewater after DAF in test 1. This implied that coagulation and DAF

cannot really affect the membrane fouling by removing particles from spinach

wastewater. More research is needed for the mechanism of how coagulation and DAF

help reducing the membrane fouling of spinach wastewater. Overall, by applying

71

coagulation and DAF, the TMP rising rates and fouling resistance were reduced, whereas

DAF treatment had slightly lower fouling rates than coagulation.


Nine physical parameters were measured for reviewing effluent qualities of different

treatment technologies on spinach wastewater.

72

(a)

(c)

(e)

(b)

(d)

(f)

130 130

100

110 110

81

0

40

80

120

160

200

SR SC SD SRU SCU SDU

CT

OC

co

ncen

trati

on

(m

g/L

)

373 440 406

363 346

355

0

100

200

300

400

500


CO

D c

on

cen

trati

on

(m

g/L

)

220 240 210

140 150 150

0

80

160

240

320

400


BO

D5 c

on

cen

trati

on

(m

g/L

)

100

74

12 0 0 0

0

40

80

120

160

200


TS

S c

on

cen

trati

on

(m

g/L

)

92

47

5.9 0.6 0.3 0.3 0.0

30.0

60.0

90.0

120.0

150.0


Tu

rbid

ity (

NT

U)

4.7 5.5 5.7

5.4 5.8 5.9

0.0

2.0

4.0

6.0

8.0

10.0


pH

73

(g)

(h)

(i)

SR: spinach raw wastewater

SC: spinach wastewater after

coagulation

SD: spinach wastewater after DAF

SRU: spinach wastewater after UF

SCU: spinach wastewater after

coagulation and UF

SDU: spinach wastewater after DAF and

UF

Figure 5-20 Comparison of effluent qualities after different treatment methods of spinach

wastewater

2.6

1.8

2.3 2.0

1.6 1.7

0.0

1.0

2.0

3.0

4.0

5.0


NO

3-N

co

ncen

trati

on

(m

g/L

)

0.4

0.3 0.2

0.3 0.2 0.2

0.0

0.2

0.4

0.6

0.8

1.0


NH

4+-N

co

ncen

trati

on

(m

g/L

)

2.1 2.5

1.4

1.2

0.4 0.4

0.0

1.0

2.0

3.0

4.0

5.0


TP

co

ncen

trati

on

(m

g/L

)

74

From Figure 5-20, it is obvious that the three kinds of treatment technologies had poor

removal abilities on COD. Only 3% of COD was removed by UF with coagulation.

Around 30 - 40% removal efficiency was achieved with respect to cTOC and BOD5 by

UF or UF with DAF. Moreover, with the more cTOC were removed, the pH became

higher. It is mainly because removing humic acid can cause the pH slightly increasing.

UF with pretreatment process showed great removal efficiency in terms of TP for spinach

wastewater. Although coagulation and DAF only removed 33 – 43% TP, combined with

UF, these two treatment technologies achieved an 80% TP removal efficiency. Between

coagulation with UF and coagulation/DAF with UF, no distinct difference of removal

efficiencies of different parameters was found.

If summarizing the performance of coagulation and DAF on membrane fouling and

effluent qualities, DAF seems to be a redundant treatment of spinach wastewater

treatment, without considering the cTOC removal efficiency. In terms of effluents

qualities, the only advantage shown in this research of DAF was that the cTOC removal

efficiency was 20% higher when applying DAF as pretreatment for UF. For both

treatment processes, nitrate and ammonia was removed less than 20% or even no

significant removal was observed in ammonia concentration.

For spinach wastewater, with respect to the contemporary city by-laws of Toronto,

Cambridge and the Kitchener area, the raw wastewater just meets the limits of different

parameters except the pH, which would need to be adjusted to higher than 6. For future

legislatives, suitable treatment technologies are still needed.

75

5.5 Effects of Different Pretreatment on Membrane Fouling of Potato Wastewater

The effects of different air scouring rate on membrane fouling were investigated for

potato wastewater and results are shown below.

5.5.1 Air Scouring Rate Selection

An optimum air scouring rate during a forty- minute filtration test was observed for

potato wastewater.


potato wastewater

The optimum air scouring rate which was 2L/min, was observed in Figure 5-22. With a

higher air scouring rate, this cannot really reduce more surface fouling over a lower air

scouring rate. Similar results were shown by Xin Xie (2006). Thus, 2 L/min was chosen

as the air scouring condition for further filtration tests.

0.0E+00

4.0E+11

8.0E+11

1.2E+12

1.6E+12

2.0E+12

0 10 20 30 40 50

Fo

ulin

g R

esis

tan

ce (

1/m

)

Time (min)

1L/min

4L/min

2 L/min

76

5.5.2 Critical Fluxes of Potato Wastewater and Wastewater after Pretreatment

Compared to spinach wastewater, the potato wastewater had to be operated at a smaller

flux, for its critical flux threshold was lower than spinach wastewater.

According to Figure 5-22, Figure 5-23 and Figure 5-24, critical flux thresholds for potato

raw wastewater, wastewater after coagulation and wastewater after DAF were 12.5 LMH,

12.6 LMH and 13.4 LMH, respectively. Unlike the spinach wastewater after DAF, which

had a significant higher critical flux than raw wastewater and wastewater after

coagulation, the critical flux thresholds for three kinds of potato wastewater were very

close to each other. Thus, a 13 LMH operating flux was chosen as the permeate condition

for further filtration.

Figure 5-22 Critical flux measurement of potato raw wastewater (PR)

0

5

10

15

20

25

30

0

3

6

9

12

15

18

0 10 20 30 40 50 60

TM

P (

kP

a)

Time (min)

TMP (kPa)

Flux (LMH)

Flu

x (L

MH

)

77

Figure 5-23 Critical flux measurement of potato wastewater after coagulation (PC)

Figure 5-24 Critical flux measurement of potato wastewater after coagulation and DAF

(PD)

0

5

10

15

20

25

30

0

2

4

6

8

10

12

0 10 20 30 40 50 60

TM

P (

kP

a)

Time (min)

TMP (kPa)

Flux (LMH)F

lux (L

MH

)

0

6

12

18

24

30

0

2

4

6

8

10

0 10 20 30 40 50

TM

P (

kP

a)

Time (min)

TMP (kPa)

Flux (LMH)

Flu

x (L

MH

)

78

According to the critical fluxes, both coagulation and DAF as pretreatment did not

significantly improve the critical flux of UF treatment on potato wastewater. The reasons

can be two. One is that the contaminants removed by pretreatment methods were not the

main fouling factors of UF. The other one is the limitation of the instrument which was

used for TMP recording. Through reviewing the deduction of fouling resistance by

pretreatment methods, the first reason can be judged. The instrument recording the TMP

had a wide range of fluctuation, which resulted in a rough average number of TMP was

observed. In this situation, the increase of TMP was not that obvious. Misjudgments of

critical fluxes occurred when reading the TMP increasing rate.

5.5.3 Membrane Fouling

Fouling resistance and fouling rate were applied for evaluating membrane fouling of

potato wastewater.

79


coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF test 1



0.0E+00

2.0E+11

4.0E+11

6.0E+11

8.0E+11

1.0E+12

1.2E+12

1.4E+12

0 20 40 60 80 100 120

Fo

ulin

g r

esis

tan

ce (

1/m

)

Time (min)

Raw

After coagulation

After DAF

0

0.02

0.04

0.06

0.08

0.1

0.12

0 20 40 60 80 100 120

Fo

ulin

g r

ate

(kP

a/m

in)

Time (min)

PD PC PR

80



0.0E+00

2.0E+11

4.0E+11

6.0E+11

8.0E+11

1.0E+12

10 30 50 70 90 110

Fo

ulin

g r

esis

tan

ce (

1/m

)

Time (min)

Raw

After coagulation

After DAF

81



Similar to spinach wastewater, potato raw wastewater had the highest fouling resistance

among the three kinds of feed water. Both DAF and coagulation significantly reduced the

fouling resistances of potato wastewater after UF. However, DAF did not present

consistently lower fouling rates than that of coagulation, as pretreatment methods. In

most filtration time, DAF had the same fouling rates as coagulation for potato

wastewater.

The TMP of potato wastewater after DAF increased rapidly at 0.07 kPa/min during the

first 20 minutes in test 1, but in test 2 the same situation was not observed. The fouling

rates during the first 20 minutes of PD in test 2 were below 0.01 kPa/min. The reason

could be that the operating flux during UF with DAF in test 1 was slightly higher than

that of raw wastewater and wastewater after coagulation, while they had the same critical

flux. The operating flux for PR and PC in test 1 was around 12.5 LMH, and for PD in test

0

0.02

0.04

0.06

0.08

0.1

0 20 40 60 80 100

Fo

ulin

g r

ate

(kP

a/m

in)

Time (min)

PR PC PD

82

1 was 13.7 LMH. The system was calibrated before filtering wastewater, but after

changing the feed water from clean water to tested samples, the flux became higher.

The 90-minute fouling rate for raw wastewater, wastewater after coagulation and

wastewater after DAF in test 1 was 0.029 1/min·m-1

, 0.014 1/min·m-1

and 0.014 1/min·m-

1, respectively. The fouling rates for aw wastewater, wastewater after coagulation and

wastewater after DAF in test 2 were 0.025 1/min·m-1

, 0.006 1/min·m-1

and 0.009

1/min·m-1

, respectively. These data implied, between the two UF tests of potato

wastewater, the raw wastewater had similar fouling conditions while pretreatment had

better control abilities on membrane fouling in test 2. According to the different

characteristics of feed and wastewater between the two tests shown in Table 5-4, the

parameters changed significantly. For example, the TSS for test 1 PR was 3200 mg/L

and, in test 2 it was 8200 mg/L, but COD in test 1 PR was 1900 mg/L while that in test 2

was 940 mg/L. Moreover, the cTOC was the same in both test 1 and test 2 of potato raw

wastewater. So comparison of membrane fouling based on organic matters or particle

concentration was not able to be summarized. However, it can still be concluded that the

coagulation and DAF had higher capabilities to reduce the membrane fouling, with

respect to fouling resistance. The fouling rates also decreased after applying pretreatment

methods for UF. Besides, coagulation as pretreatment had better fouling control ability

than that of DAF as pretreatment for potato wastewater filtration, according to results

shown in Figure 5-25, Figure 5-26, Figure 5-27 and Figure 5-28.

Compared with the spinach wastewater fouling results, although potato wastewater

contains significantly more particles and higher COD concentration in the wastewater,

the fouling rates of potato raw wastewater were smaller than that of spinach raw

83

wastewater. It implies that UF is more suitable for potato wastewater rather than spinach

wastewater.

84

Table 5-4 Potato feed water parameters for UF test 1 and test 2

Feed

Water

TSS

(mg/L)

pH cTOC

(mg/L)

NO3-N

(mg/L) TP

(mg/L)

NH4+-N

(mg/L)

COD

(mg/L)

Turbidity

(NTU)

PR Test 1 3200 7.0 30 0.8 9.8 6.6 1900 1000

PC Test 1 3700 7.0 22 0.7 6.7 5.2 1200 560

PD Test 1 14 7.2 16 0.5 0.4 2.5 130 27

PR Test 2 8200 6.6 36 0.4 33 1.4 940 1000

PC Test 2 28000 6.7 35 0.5 33 1.6 1100 1000

PD Test 2 14 7.2 16 0.5 0.2 1.4 110 21

85


Physical and biochemical parameters of effluents from raw potato wastewater and five

kinds of treated potato wastewater were analyzed and shown in the following figures.

86

(a)

(c)

(e)

(b)

(d)

(f)

40

28 19

28

22

21

0

12

24

36

48

60

PR PC PD PRU PCU PDU

CT

OC

co

ncen

trati

on

(m

g/L

)

1220

905

159 144 131 152

0

400

800

1200

1600

2000

PR PC PD PRUPCUPDU

CO

D c

on

cen

trati

on

(m

g/L

)

210

300

25 44 51 39

0

100

200

300

400

500


BO

D5 c

on

cen

trati

on

(m

g/L

)

5800

16000

83 0 0 0 0

7000

14000

21000

28000

35000

TS

S c

on

cen

trati

on

(m

g/L

)

1000

780

24 0.65 0.68 0.02 0

400

800

1200

1600

2000


Tu

rbid

ity (

NT

U)

6.8 6.8 7.2 8.0 7.4 7.6

0.0

2.0

4.0

6.0

8.0

10.0


pH

87

(g)

(h)

(i)

PR: potato raw wastewater

PC: potato wastewater after coagulation

PD: potato wastewater after DAF

PRU: potato wastewater after UF

PCU: potato wastewater after

coagulation and UF

PDU: potato wastewater after DAF and

UF

Figure 5-29 Comparison of effluent qualities after different treatment methods of potato

wastewater

1.7

0.6

1.1 1.1

1.0

1.2

0.0

0.5

1.0

1.5

2.0

2.5

PR PC PD PRUPCUPDU

NO

3-N

co

ncen

trati

on

(m

g/L

)

26 24

2.4 1.1 0.7 0.2 0.0

9.0

18.0

27.0

36.0

45.0


TP

co

ncen

trati

on

(m

g/L

)

3.9

8.4

3.5

2.1

3.3

1.6

0.0

4.0

8.0

12.0

16.0

20.0


NH

4+-N

co

ncen

trati

on

(m

g/L

)

88

Coagulation coupled with UF can achieve 25% of cTOC removal efficiency, 75% of BOD5

removal efficiency, over 90% removal efficiency on TP and COD. Especially for TP, 97% of TP

was removed. DAF as pretreatment for UF was able to remove 50% of cTOC, around 90% for

BOD5 and COD, and 99% of TSS, TP and turbidity. Although DAF as pretreatment for UF did

not show significant higher removal abilities on variety contaminants than UF, DAF treatment,

without UF, greatly removed BOD5, TSS and TP from potato wastewater. According to Figure

5-29, with the application of DAF, BOD5, TSS and TP can be reduced down to 25 mg/L, 83

mg/L and 2.4 mg/L, respectively.

89

Chapter 6 CONCLUSIONS AND RECOMMENDATIONS

6.1 Conclusions

The following conclusions are:

1) Different fruit & vegetable wastewater has various characteristics, and different food

processes will contain varying wastewater characteristics. However, the BOD5/ COD

ratio is applicable to dividing the wastewater into two main categories: those that are

easily treatable by biological treatment, and those that are not.

2) The suitable coagulation operation parameters of spinach wastewater were with a dose of

10 mg/L alum at a pH 5.5; alternative conditions were with a dose of 5 mg/L alum at a

pH 7. Potato wastewater needs a higher dosage of alum: with a dose of 250 mg/L alum at

a pH 7.

3) The suitable DAF operation parameters for DAF treatment of spinach wastewater were

determined as 30% recycle rate coupled with a 10- minute flotation while the suitable

condition of potato wastewater were 30% recycle rate and a 30- minute flotation.

4) DAF had slightly better separation abilities on nutrients than sedimentation.

5) DAF and coagulation separated more organic contaminants from potato wastewater but

had weaker removal efficiencies on spinach wastewater. This is mainly because the

spinach wastewater contained more soluble organic matters than potato wastewater. In

potato wastewater, 70% of COD was removed; whereas for spinach wastewater, less than

20% of COD was removed.

90

6) After UF was applied to pre-treated spinach wastewater, removal efficiency of cTOC and

BOD5 was increased to 40% from 23% and to 36% from 3%, respectively.

7) Both DAF and coagulation as pretreatment had great removal efficiencies for TSS and

TP. However, as pretreatment, they did not significantly improve the overall removal

abilities for UF.

8) Both coagulation and DAF significantly reduced the fouling rates, but the abilities of

controlling the fouling rate for both treatment technologies were similar. For the spinach

wastewater, DAF had smaller fouling resistances and slower fouling rates than

coagulation. But for the potato wastewater, DAF had smaller fouling resistances but

faster fouling rates than coagulation.

9) UF significantly removed larger percentages of contaminants from potato wastewater

than that from spinach wastewater, which implied UF was more feasible to wastewater

that similar to potato wastewater.

6.2 Recommendations and Future Work

According to the biodegradable ratio, the vegetative wastewater can be divided into two

categories; treatment technologies suitable for different vegetative wastewater can follow

spinach wastewater and potato wastewater. For example, carrot wastewater is another kind of

wastewater that has a small BOD5/COD ratio. After adjusting coagulation and DAF treatment

conditions, contaminants such as TSS, TP and COD of carrot wastewater will be greatly

removed. However, for biodegradable vegetative wastewater, other treatment technologies need

to be investigated. In order to better understand the low BOD5/COD ratio in other kinds of

91

vegetative wastewater, sieve analysis will be involved to help explain the low ratio and find out

the solid textures. The matrix of fruit & vegetable wastewater characteristics also can be

specified to different processes among the same product industries.

Even though coagulation/DAF produces better effluent qualities, it has similar membrane fouling

control with coagulation. Cost evaluation on treatment technologies, and effluent quality should

be suggested, and considered when these treatment technologies are applied for potato

wastewater.

In order to meet the current sanitary sewer discharge limits, spinach industry can increase the pH

value for the spinach raw wastewater, and UF treatment can be adopted for potato wastewater.

But for meeting future legislations, biological treatment or other treatment technologies need to

be investigated for spinach wastewater.

92

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APPENDICES

104

A.1 Water Characteristics

Table A. 1 Vegetative Raw Wastewater Characteristics

Wastewater TSS

(mg/L)

COD

(mg/L)

BOD5

(mg/L)

cTOC

(mg/l)

BOD5/COD COD/

cTOC

NO3-N

(mg/L)

NH4+-N

(mg/L)

Filtered

TN

(mg/L)

TP

(mg/L)

pH Turbidity

(NTU)

Apple 126 3900 2283 1329 0.59 2.93 43.5 0.4 35 18.3 10.4 56

Apple 140 142 25 24 0.18 5.92 3.5 0.2 3 58.4 nd nd

Apple Ave 133 2021 1154 677 0.38 4.43 23.5 0.3 19 38.4 10.4 56

std 10 2657 1597 923 0.29 2.11 28.3 0.1 23 28.4 na na

Carrot nd 654 44 106 0.07 6.17 1.4 2.0 2 3.9 7.6 700

Carrot 206 370 48 120 0.13 3.08 2.7 0.1 2 1.3 7.8 123

Carrot 182 338 86 nd 0.25 na 1.8 2.0 3 0.4 nd nd

Carrot 198 373 nd nd na na 2.2 0.2 3 1.3 nd nd

Carrot 214 366 48 nd 0.13 na nd 0.1 2 1.4 nd nd

Carrot Ave 200 420 56 113 0.15 4.63 2.0 0.9 2 1.7 7.7 412

105

std 14 131 20 10 0.08 2.18 0.6 1.0 1 1.3 0.1 408

Ginseng 32 37 nd nd na na nd 0.3 nd nd nd nd

Ginseng 32 30 nd 41 na 0.90 1.3 0.3 1 0.8 nd nd

Ginseng 312 114 9 34 0.08 0.90 1.7 0.4 1 1.7 7.2 124

Ginseng 2392 119 nd 33 na 3.48 1.2 2.3 nd nd 6.6 595

Ginseng

Ave

692 75 9 36 0.08 1.76 1.4 0.8 1 1.2 6.9 360

std 1141 48 na 5 na 1.49 0.2 1.0 0 0.6 0.4 333

Mixed

Vegetable

638 110 nd 28 na 3.98 nd nd nd nd 6.7 530

Mixed

Vegetable

456 165 95 26 0.57 6.25 9.7 0.1 23 4.7 7.7 530

Mixed

Vegetable

Ave

547 138 95 27 0.57 5.11 9.7 0.1 23 4.7 7.2

std 128 39 na 1 na 1.61 na na na na 0.7 745

Potato 2738 867 32 120 0.04 7.22 11.0 4.0 6 8.8 7.6 830

Potato 2846 1000 160 102 0.16 9.77 1.2 4.6 10 9.0 7.2 958

106

Potato 1768 1049 66 12 0.06 88.26 2.3 0.7 4 6.5 8.3 620

Potato 3894 1870 190 135 0.10 13.87 2.0 34.9 49 98.7 7.2 817

Potato 1772 788 94 34 0.12 23.41 3.5 5.0 13 29.4 7.8 1000

Potato 7794 5340 300 62 0.06 86.09 1.5 4.0 11 26.3 7.2 1000

Potato 7160 5740 860 124 0.15 46.44 0.8 16.9 53 52.7 7.3 1000

Potato 698 1115 251 108 0.22 10.34 3.5 0.8 17 7.1 7.2 871

Potato Ave 3584 2221 244 87 0.11 35.67 3.2 8.8 20 29.8 7.5 142

std 2585 2077 265 46 0.06 34.16 3.3 11.7 19 32.1 0.4 na

Sweet

Potato 1

900 854 62 nd nd nd nd nd nd nd 6.7 352

Mushroom 446 1790 970 460 0.54 3.89 4.0 0.1 4 3.5 nd nd

Mushroom 358 1718 947 nd 0.55 nd nd 0.1 nd 2.5 nd nd

Mushroom

Ave

402 1754 959 460 0.55 3.89 4.0 0.1 4 3.0 nd nd

std 62 51 16 na 0.01 na na 0.0 na 0.7 na na

107

TSS

(mg/L)

Filtered

TN

(mg/L)

Filtered

TOC

(mg/L)

NO3-N

(mg/L)

TP

(mg/L)

NH4+-N

(mg/L)

COD

(mg/L)

BOD5

(mg/L)

TS

(mg/L)

pH Turbidity

sc 5 3 164 2.9 1.3 0.4 440 135 950 5.4 nd

sc 8 3 119 2.9 1.4 0.3 443 131 900 5.7 nd

sc 155 nd 125 1.7 2.3 0.4 363 362 932 5.4 26.2

sc 170 nd 124 2.2 nd 0.4 436 314 908 nd 67.1

sc 59 nd 146 0.6 3.5 0.1 479 217 720 nd nd

sc 57 nd 154 0.5 3.9 0.1 476 180 380 nd nd

sc 63 nd 75 nd nd nd nd 278 380 nd nd

266

258

Spinach 74 3 130 1.8 2.5 0.3 440 238 739 5.5 46.7

108

Wash Water

After

Coagulation

std 65 0 29 1.1 1.2 0.1 42 90 256 0.2 28.9

sd 14 1 53 2.1 1.7 0.2 334 124 895 6.0 5.5

sd 10 3 75 1.9 1.7 0.1 337 108 905 nd nd

sd 9 3 94 2.3 3.1 0.1 352 87 505 nd 4.3

sd 9 3 101 3.1 3.3 0.1 334 100 455 nd 3.8

sd 11 nd 163 1.9 1.1 0.3 259 265 760 5.7 nd

sd 3 nd 97 1.8 0.6 0.3 257 225 770 nd nd

sd 119 0.6 0.6 0.1 310 242 596 5.5 nd

sd 125 0.4 0.8 0.1 315 155 608 nd nd

sd 153 480 nd nd

sd 138 500 nd nd

sd 200

sd 182

Spinach 12 2 103 1.8 1.4 0.2 312 165 647 5.7 4.5

109

Wash Water

After

Coagulation

and DAF

std 5 1 33 0.9 1.1 0.1 36 58 172 0.3 0.9

sru nd 1 37 2.7 0.4 0.4 323 97 740 6.5 0.5

sru nd 3 144 1.9 0.4 0.3 338 79 525 4.4 1.2

sru nd na 122 0.7 2.2 0.1 343 227 520 5.1 0.2

sru nd na 140 0.6 2.1 0.1 341 153 nd nd nd

sru nd na na 3.0 1.1 0.3 415 147 nd nd nd

sru nd na na 3.3 1.1 0.3 415 na nd nd nd

Spinach

Wash Water

After UF

2 111 2.0 1.2 0.3 363 141 595 5.4 0.6

std 1 50 1.2 0.8 0.1 41 58 126 1.1 0.5

scu nd 2 122 2.2 0.3 0.4 345 98 nd 6.3 0.4

scu nd 0 131 1.7 0.4 0.4 401 77 nd 5.4 0.1

scu nd nd 142 0.7 0.5 0.2 331 243 865 5.6 0.3

scu nd nd 37 0.4 0.3 0.2 325 180 950 nd nd

110

2.3 0.3 0.0 335

2.5 or 0.0 341

Spinach

Wash Water

After

Coagulation

and UF

1 108 1.6 0.4 0.2 346 150 908 5.8 0.3

std 1 48 0.9 0.1 0.2 28 77 60 0.5 0.1

sdu nd 0 35 1.6 0.2 0.3 250 76 720 6.8 0.5

sdu nd 2 131 1.3 0.2 0.3 241 66 795 5.3 0.0

sdu nd nd 89 0.3 0.3 0.1 330 169 640 5.6 0.2

sdu nd nd 125 0.3 0.3 0.1 297 135 630 nd nd

sdu nd nd 27 2.1 0.4 0.1 262 144 na nd nd

1.9 0.3 0.1 260

Spinach

Wash Water

After Cog,

DAF and

UF

1.1518 81.2286 1.2500 0.3005 0.1583 273.3333 118.1240 696.2500 5.9167 0.2167

std 0.9817 48.7543 0.7842 0.0508 0.0960 33.6670 44.7385 77.1767 0.7826 0.2303

111

TSS

(mg/L)

Filtered

TOC

(mg/L)

NO3-N

(mg/L)

TP

(mg/L)

NH4+-N

(mg/L)

COD

(mg/L)

BOD5

(mg/L)

pH Turbidity

potato after coagulation 28753 22 0.7 20.0 16.9 489 221 7.0 564

potato after coagulation 27967 35 0.6 98.0 16.8 491 228 6.7 1000

potato after coagulation 3555 na 0.6 99.0 1.5 1110 468 nd nd

potato after coagulation 3755 na 0.4 or 1.7 1230 or nd nd

potato after coagulation 5.2 968

potato after coagulation 1144

pc ave 16008 28 0.6 72.3 8.4 905 306 6.8 782

pc std 14267 9 0.1 45.3 7.8 333 141 0.2 308

potato after coagulation/DAF 92 31 1.8 10.8 5.2 147 30 7.2 27

potato after coagulation/DAF 116 5 1.6 7.0 1.4 118 28 7.2 21

potato after coagulation/DAF 84 4 0.4 1.1 1.4 116 23 nd nd

potato after coagulation/DAF 14 16 0.6 7.0 or 109 25 nd nd

potato after coagulation/DAF 14 16 0.5 0.7 or or 22 nd nd

potato after coagulation/DAF nd na 0.4 7.0 or or 20 nd nd

112

pd ave 64 14 0.9 5.6 2.7 123 25 7.2 24

pd std 47 11 0.6 3.9 2.2 17 4 0.0 5

potato raw water after UF nd 19 1.6 3.2 2.5 109 48 8.1 1

potato raw water after UF nd 38 0.5 3.7 1.9 150 41 7.9 0

potato raw water after UF nd na lr 3.1 1.9 159 lr nd nd

potato raw water after UF nd na lr or or 157 lr nd nd

pru ave nd 28 1.1 3.3 2.1 144 44 8.0 1

pru std nd 13 0.8 0.3 0.3 23 5 0.1 0

potao after coagulation/UF nd 17 1.3 1.5 5.4 140 56 7.3 1

potao after coagulation/UF nd 27 1.0 1.4 5.2 144 47 7.5 0

potao after coagulation/UF nd na 0.9 3.6 1.5 109 lr nd nd

potao after coagulation/UF nd na 0.6 or 0.9 nd lr nd nd

pcu ave nd 22 1.0 2.2 3.3 131 51 7.4 1

pcu std nd 7 0.3 1.2 2.4 19 6 0.1 1

potato after coagulation,

DAF/UF

nd 17 1.3 0.3 1.5 118 49 7.5 0

potato after coagulation, nd 16 1.3 0.6 1.5 118 33 7.7 0

113

DAF/UF


DAF/UF

nd na 0.6 or 0.9 114 29 nd nd


DAF/UF

nd na 0.6 or 1.0 118 lr nd nd

pdu ave nd 16 1.0 0.4 1.2 117 37 7.6 0

pdu std nd 0 0.4 0.2 0.3 2 11 0.2 0

114

A.2 Standard Curves for Water Quality Analyses

Table A. 2 Parameters standard curves

115

Figure A. 1 COD high range calibration curve

Figure A. 2 Ammonia high range calibration curve

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 200 400 600 800 1000 1200

Ab

s

COD standard solution concentration (mg/L)

y = 0.0276x - 0.0065 R² = 0.9993

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 10 20 30 40 50 60

Ab

s

Ammonia standard solution concentration (mg/L)

116

Figure A. 3 Ammonia low range calibration curve

Figure A. 4 COD low range calibration curve

y = 0.9222x - 0.0079 R² = 0.9998

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 0.5 1 1.5 2 2.5

Ab

s

Ammonia standard solution concentration (mg/L)

y = -0.0029x + 0.0104 R² = 0.9963

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0 50 100 150

Ab

s

COD standard solution concentration (mg/L)

117

Figure A. 5 TOC calibration curve

Figure A. 6 TN calibration curve

y = 5.3331x - 0.371 R² = 0.9998

0

200

400

600

800

1000

1200

1400

0 50 100 150 200 250 300

Are

a

TOC standard solution concentration (mg/L)

y = 20.534x + 6.6451 R² = 0.9995

0

200

400

600

800

1000

1200

0 10 20 30 40 50 60

Are

a

TN standard solution concentration (mg/L)

118

A.3 Experiments data of Jar Tests

pH in

spinach

mixed

solution

Alum

Dose

(mg/L)

Turbidity

(NTU)

Turbidity

Raw

(NTU)

COD

(mg/L)

COD

Raw

(mg/L)

RE of

Turbidity

RE

of

COD

4 0 11.7 67 nd 362 0.83

4 50 31.4 71 202 220 0.56 0.08

4 30 23.3 71 194 220 0.67 0.12

4 50 9 197 241 294 0.95 0.18

4 10 6.08 71 191 220 0.91 0.13

5 30 2.56 197 219 294 0.99 0.26

5 5 4.66 67 188 220 0.93 0.15

5 50 1.65 67 nd 362 0.98

5 2.5 29.7 71 196 220 0.58 0.11

5 0 47.3 71 205 220 0.33 0.07

5 10 3.7 197 222 294 0.98 0.24

5 30 1.71 67 nd 362 0.97

7 10 5.09 67 nd 362 0.92

7 10 0.7 82.2 186 220 0.99 0.15

7 0 47 82.2 204 220 0.43 0.07

7 5 2.68 67 nd nd 0.96

7 5 0.35 82.2 190 220 1.00 0.14

7 0 23.7 67 nd nd 0.65

7 2.5 4.5 82.2 190 220 0.95 0.14

7 30 2.04 27.1 324 362 0.92 0.10

7 50 3.61 27.1 326 362 0.87 0.10

119

7 2.5 13.7 67 nd nd 0.80

9 0 24.6 71 362 362 0.65 0.00

9 5 0.62 27.1 328 362 0.98 0.09

9 10 3.61 27.1 334 362 0.87 0.08

9 30 14.4 27.1 353 362 0.47 0.02

pH Dose

(mg/

L)

Turbidi

ty

(NTU)

cTO

C

(mg/

L)

RE of

Turbidi

ty

RE

of

cTO

C

Turbidi

ty

(NTU)

cTO

C

(mg/

L)

RE of

Turbidi

ty

RE

of

cTO

C

5 0 182 39 0.5 0.6 68 49 0.9 0.0

5 50 10 43 1.0 0.1

5 100 13 28 1.0 0.7 9 38 1.0 0.2

5 200 5 27 1.0 0.7 24 38 1.0 0.2

5 250 3 27 1.0 0.7

5 300 3 27 1.0 0.7 14 36 1.0 0.3

5 350 5 28 1.0 0.7

7 0 194 44 0.5 0.6 852 44 0.1 0.1

7 50 19 42 1.0 0.2

7 100 3 31 1.0 0.7 7 42 1.0 0.1

7 200 3 31 1.0 0.7 6 40 1.0 0.2

7 250 2 30 1.0 0.7

7 300 3 30 1.0 0.7 8 38 1.0 0.2

7 350 3 29 1.0 0.7

120

9 0 224 39 0.4 0.6 934 51 0.1 0.0

9 100 3 30 1.0 0.7 5 43 1.0 0.1

9 50 3 41 1.0 0.2

9 200 4 30 1.0 0.7 6 39 1.0 0.2

9 250 2 32 1.0 0.7

9 300 3 29 1.0 0.7 6 38 1.0 0.2

9 350 3 28 1.0 0.7

Ra

w

0 353 108 1000 49

A.4 Experiments data of DAF Tests

Table A. 3 DAF saturation pressure optimization

Saturation Pressure (psi) DO initial (mg/L) DO final (mg/L) Saturation Rate (%) Air concentration final (mg/L)

50 8.3 14.25 42 67.86

60 8.3 13.96 41 66.48

70 8.3 13.65 39 65.00

80 8.3 11.75 29 55.95

90 8.3 12.36 33 58.86

50 8.4 16.92 50 80.57

60 8.43 16.64 49 79.24

70 8.43 18.46 54 87.90

80 8.35 17.37 52 82.71

90 8.49 19.77 57 94.14

50 8.35 15.76 47 75.05

60 8.47 18.87 55 89.86

70 8.33 19.52 57 92.95

80 8.32 20.93 60 99.67

90 8.3 17.12 52 81.52

Saturation Pressure (psi) Saturation Rate std Air concentration std

50 46 4 74 6

60 48 7 79 12

70 50 10 82 15

80 47 16 79 22

90 47 13 78 18

121

Table A. 4 DAF apparatus saturation time optimization

Sample Recycl

e Rate

(%)

Flotatio

n Time

(min)

Turbidit

y (NTU)

Spinach

after cog

30 10 5.35

Spinach

after cog

30 20 5.81

Spinach

after cog

30 30 8.54

Spinach

after cog

30 40 5.68

Saturation

Time (min)

DO initial

(mg/L)

DO final

(mg/L)

Saturatio

n Rate (%)

Air

concentratio

n final (mg/L)

5 8.34 17.29 107 82.33

10 8.34 18.14 118 86.38

15 8.34 18.04 116 85.90

20 8.34 17.35 108 82.62

25 8.34 19.2 130 91.43

5 8.43 14.76 75 70.29

10 8.43 17.41 107 82.90

15 8.43 16.32 94 77.71

20 8.43 17.84 112 84.95

25 8.43 17.61 109 83.86

5 8.78 15.15 73 72.14

10 8.78 17.24 96 82.10

15 8.78 16.67 90 79.38

20 8.78 16.98 93 80.86

25 8.78 18.35 109 87.38

30 8.78 17.62 101 83.90

122

Spinach

after cog

30 50 6.61

Spinach

raw

water

71.4

Dilutio

n

TSS

before

(g)

Volumn

(ml)

TSS

after

(g)

Deleptio

n TSS

TSS

(mg/

L)

TSS

real

(mg/L

)

Turbidit

y

(NTU)

DAF

+cog

10%

1.1 2.5506 450 2.556

1

0.0055 12 13 8.03

DAF

+cog

30%

1.3 2.5205 350 2.525

1

0.0046 13 17 10.1

DAF

+cog

50%

1.5 2.5216 350 2.529

4

0.0078 22 33 18.1

DAF

+cog

70%

1.7 2.5361 500 2.551

2

0.0150 30 51 16.3

Control 88 71

DAF

+cog

10%

1.1 2.3444 350 2.350

9

0.0065 19 20 9.06

DAF

+cog

30%

1.3 2.3451 350 2.350

0

0.0049 14 18 8.29

DAF

+cog

50%

1.5 2.3557 350 2.359

8

0.0041 12 18 5.18

DAF

+cog

70%

1.7 2.2941 350 2.298

8

0.0047 13 23 6.97

123

Spinach 1 88 67.3

DAF

+cog

10%

1.1 2.3532 200 2.357

7

0.0045 22 25 26

1.1 2.3882 200 2.393

1

0.0049 25 27

DAF

+cog

30%

1.3 2.3522 200 2.354

4

0.0022 11 14 15

1.3 2.3761 300 2.379

7

0.0036 12 16

DAF

+cog

50%

1.5 2.3466 225 2.351

4

0.0048 21 32 26

1.5 2.3473 225 2.350

4

0.0031 14 21

DAF

+cog

70%

1.7 2.3659 300 2.370

1

0.0042 14 24 26

1.7 2.3376 300 2.342

6

0.0050 17 28

Spinach 1 2.5788 200 2.595

7

0.0169 84 84 81

1 2.4992 200 2.514

7

0.0155 77 77

Removal

Efficien

cy

TSS Turbidit

y

DAF

+cog

10%

77 89

124

DAF

+cog

30%

79 86

DAF

+cog

50%

80 75

DAF

+cog

70%

74 77

DAF

+cog

10%

68 87

DAF

+cog

30%

82 88

DAF

+cog

50%

67 92

DAF

+cog

70%

68 90

Average Recycl

e Rate

(%)

RE of

TSS

(%)

RE of

Turbidit

y (%)

tss std turbidit

y std

DAF

+cog

10%

10 72 88 6.1513 1.5219

DAF

+cog

30%

30 80 87 1.5733 1.3487

DAF

+cog

50%

50 74 83 8.8691 12.5837

125

DAF

+cog

70%

70 71 83 4.4120 8.9103

Flotatio

n Time

(min)

Turbidit

y RE

DAF

+cog

30%

10 93

DAF

+cog

30%

20 92

DAF

+cog

30%

30 88

DAF

+cog

30%

40 92

DAF

+cog

30%

50 91

126

Sample Recycle

Rate

(%)

Flotation

time

(min)

Dilution Turbidity

(NTU)

TSS (mg/L) COD

(mg/L)

Real

TSS

(mg/L)

Real

COD

(mg/L)

Potato after

coagulation

10 10 1.1 1000 23685 16040 26053.5 17644

Potato after

coagulation

30 10 1.3 755 4215 4560 5479.5 5928

Potato after

coagulation

50 10 1.5 1000 3335 4010 5002.5 6015

Potato after

coagulation

70 10 1.7 1000 28560 2950 48552 5015

Potato after

coagulation

10 30 1.1 260 295 3010 324.5 3311

Potato after

coagulation

30 30 1.3 60.4 72 2690 93.6 3497

Potato after

coagulation

50 30 1.5 187 150 2500 225 3750

Potato after

coagulation

70 30 1.7 856 838 2600 1424.6 4420

potato raw 1.0 1000 7169 5740

127

wastewater

Removal Efficiency

Recycle Rate (%) Flotation

time

(min)

Tur RE TSS RE COD RE

10 10 0 0 0

30 10 25 41 -3

50 10 0 53 -5

70 10 0 0 13

10 30 74 95 42

30 30 94 99 39

50 30 81 97 35

70 30 14 80 23

Recycle Rate (%) Flotation

time

(min)

Turbidity

(NTU)

Turbidity

RE

TSS

(mg/L)

TSS RE

30 10 99.35 72 66 91

128

30 20 85.15 76 79 89

30 30 104.5 70 69 90

30 40 114.5 68 64.5 91

30 50 98.95 72 70 90

Potato raw

wastewater

353 698

Sample TSSb(g) Volume

Added

(mL)

TSSa(g) TSS TURBIDITY

(NTU)

P3-Pre DAF 30%

@10 mins

2.3121 100 2.3185 64 94.7

P3-Pre DAF 30%

@10 mins

2.2608 100 2.2676 68 104

P3-Pre DAF 30%

@20 mins

2.2697 100 2.2777 80 77.2

P3-Pre DAF 30%

@20 mins

2.2369 100 2.2447 78 93.1

P3-Pre DAF 30%

@30 mins

2.3074 100 2.3146 72 106

129

P3-Pre DAF 30%

@30 mins

2.2387 100 2.2453 66 103

P3-Pre DAF 30%

@40 mins

2.3367 100 2.3434 67 113

P3-Pre DAF 30%

@40 mins

2.3235 100 2.3297 62 116

P3-Pre DAF 30%

@50 mins

2.2754 100 2.2825 71 97.9

P3-Pre DAF 30%

@50 mins

2.2913 100 2.2982 69 100

130

A.5 Experiments data of Membrane Filtration Tests

Figure A. 7 Spinach UF TMP results

Figure A. 8 Spinach UF TMP results

0

5

10

15

20

25

30

0 50 100 150

TM

P (

kP

a)

Time (min)

Spinach Raw Water

Spinach AfterCoagulationTreatment

Spinach AfterCoagulation andDAF Treatments

0

2

4

6

8

10

12

14

0 50 100 150

TM

P (

kP

a)

Time (min)

Spinach Raw Water

Spinach AfterCoagulationTreatment

Spinach AfterCoagulation andDAF Treatments

131

Figure A. 9 Spinach Pretreatment at pH 7 UF TMP results

Figure A. 10 Potato UF TMP results

0

2

4

6

8

10

12

14

16

18

0 50 100 150

TM

P(k

Pa)

Time (min)

Spinach Raw Water

Spinach AfterCoagulationTreatment at pH 7

spinach after cogand daf at pH 7

0

2

4

6

8

10

12

14

0 50 100 150

TM

P (

kP

a)

Time (min)

PD

Potato AfterCoagulation

PR

132

Figure A. 11 P UF TMP results

Table A5-1 Filtration data of UF test 1 of spinach raw wastewater

Setting Filtration

Time (min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

35 1 2.06 0.004 2.06 32.35 0.00E+00

40 1.3 3.07 0.004 2.36 37.09 0.00E+00

37 1 2.17 0.004 2.17 34.08 0.00E+00

33 1 1.94 0.004 1.94 30.47 0.00E+00

DI water Filtration

Time (min)

Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Ave Rm

(1/m)

35 9 10 17.95 0.004 1.99 31.32 10.72 1.23E+12 1.26E+12

35 9 20 17.92 0.004 1.99 31.27 10.72 1.23E+12

35 9 30 18 0.004 2.00 31.41 10.72 1.23E+12

35 9 40 17.92 0.004 1.99 31.27 11.08 1.28E+12

35 9 50 17.9 0.004 1.99 31.24 11.07 1.28E+12

35 9 60 17.92 0.004 1.99 31.27 11.31 1.30E+12

Spinach

Raw

Filtration

Time (min)

Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

0

1

2

3

4

5

6

7

8

9

0 20 40 60 80 100 120

TM

P (

kP

a)

Time (min)

Potato Raw

Potato After Coagulation

Potato After Coagulationand DAF

133

35 9 10 17.48 0.004 1.94 30.50 16.69 1.97E+12 7.12E+11

35 9 20 17.44 0.004 1.94 30.43 18.22 2.16E+12 8.97E+11

35 9 30 17.59 0.004 1.95 30.70 19.46 2.28E+12 1.02E+12

35 9 40 17.53 0.004 1.95 30.59 20.50 2.41E+12 1.15E+12

35 9 50 17.46 0.004 1.94 30.47 21.06 2.49E+12 1.23E+12

35 9 60 17.45 0.004 1.94 30.45 21.73 2.57E+12 1.31E+12

35 9 70 17.39 0.004 1.93 30.35 22.47 2.67E+12 1.41E+12

35 9 80 17.3 0.004 1.92 30.19 23.09 2.75E+12 1.50E+12

35 9 90 17.34 0.004 1.93 30.26 23.70 2.82E+12 1.56E+12

35 9 100 17.42 0.004 1.94 30.40 24.38 2.89E+12 1.63E+12

35 9 110 17.32 0.004 1.92 30.23 24.93 2.97E+12 1.71E+12

35 9 120 17.28 0.004 1.92 30.16 25.18 3.01E+12 1.75E+12

35 9 130 17.25 0.004 1.92 30.10 25.67 3.07E+12 1.81E+12

35 9 140 17.3 0.004 1.92 30.19 26.29 3.13E+12 1.88E+12

35 9 150 17.25 0.004 1.92 30.10 26.47 3.17E+12 1.91E+12

Table A5-2 Filtration data of UF test 1 of spinach wastewater after coagulation

Setting Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rm (1/m)

35 1 1.67 0.004 1.67 24.69 4.33 6.31E+11

37 1.5 3.22 2.15 31.73 7.82 8.87E+11

DI water Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rm (1/m) Ave Rm (1/m)

37 9 10 19.26 2.14 31.63 7.26 8.27E+11

37 9 20 19.11 2.12 31.39 7.40 8.49E+11 8.60E+11

37 9 30 19.12 2.12 31.40 7.54 8.64E+11

134

37 9 40 19.12 2.12 31.40 7.59 8.70E+11

37 9 50 19.15 2.13 31.45 7.56 8.65E+11

37 9 60 19.12 2.12 31.40 7.72 8.85E+11

Spinach after coagulation

Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rt (1/m) Rf (1/m)

37 9 10 19.04 2.12 31.27 8.93 1.03E+12 1.68E+11

37 9 20 19.2 2.13 31.54 9.73 1.11E+12 2.51E+11

37 9 30 19.05 2.12 31.29 10.10 1.16E+12 3.02E+11

37 9 40 19.06 2.12 31.31 10.59 1.22E+12 3.58E+11

37 9 50 19.03 2.11 31.26 10.96 1.26E+12 4.02E+11

37 9 60 19.05 2.12 31.29 11.33 1.30E+12 4.44E+11

37 9 70 19.03 2.11 31.26 11.64 1.34E+12 4.81E+11

37 9 80 19.00 2.11 31.21 11.89 1.37E+12 5.12E+11

37 9 90 19.00 2.11 31.21 12.13 1.40E+12 5.39E+11

37 9 100 19.01 2.11 31.22 12.69 1.46E+12 6.03E+11

37 9 110 18.94 2.10 31.11 12.69 1.47E+12 6.08E+11

37 9 120 18.91 2.10 31.06 13.05 1.51E+12 6.53E+11

37 9 130 18.92 2.10 31.08 13.30 1.54E+12 6.81E+11

37 9 140 18.93 2.10 31.09 13.55 1.57E+12 7.09E+11

37 9 150 18.93 2.10 31.09 13.63 1.58E+12 7.18E+11

Table A5-3 Filtration data of UF test 1 of spinach wastewater after DAF

Setting Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rm (1/m)

20 1 1.26 0.004 1.26 18.63 0.00E+00

30 2 3.54 0.004 1.77 26.16 0.00E+00

135

35 1 2.06 0.004 2.06 30.45

40 2 4.65 0.004 2.325 34.37

36 1 2.18 0.004 2.18 32.23

DI water Time acc

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)


36 18 20 37.11 2.061666667 30.48 9.40 1.11E+12 1.13E+12

36 9 30 18.52 2.06 30.42 8.64 1.02E+12

36 9 40 18.57 2.06 30.50 9.37 1.11E+12

36 9 50 18.55 2.06 30.47 9.92 1.17E+12

36 9 60 18.57 2.06 30.50 10.33 1.22E+12

36 9 70 18.55 2.06 30.47 9.95 1.18E+12

Spinach after DAF

Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rt (1/m) Rf (1/m)

36 9 10 18.51 0.004 2.06 30.40 10.72 1.27E+12 1.35E+11

36 9 20 18.52 0.004 2.06 30.42 11.52 1.36E+12 2.29E+11

36 9 30 18.54 0.004 2.06 30.45 12.25 1.45E+12 3.14E+11

36 9 40 18.51 0.004 2.06 30.40 11.95 1.42E+12 2.81E+11

36 9 50 18.51 0.004 2.06 30.40 11.52 1.36E+12 2.29E+11

36 9 60 18.52 0.004 2.06 30.42 12.32 1.46E+12 3.23E+11

36 9 70 18.53 0.004 2.06 30.43 13.12 1.55E+12 4.17E+11

36 9 80 18.54 0.004 2.06 30.45 13.12 1.55E+12 4.17E+11

36 9 90 18.50 0.004 2.06 30.39 11.52 1.36E+12 2.30E+11

36 9 100 18.49 0.004 2.05 30.37 13.05 1.55E+12 4.12E+11

36 9 110 18.48 0.004 2.05 30.35 13.36 1.58E+12 4.50E+11

36 9 120 18.45 0.004 2.05 30.30 13.30 1.58E+12 4.45E+11

36 9 130 18.48 0.004 2.05 30.35 12.32 1.46E+12 3.26E+11

36 4 140 8.12 0.004 2.03 30.01 13.12 1.57E+12 4.39E+11

36 9 150 18.47 0.004 2.05 30.34 13.92 1.65E+12 5.17E+11

136

Table A5-4 Filtration data of UF test 2 of spinach raw wastewater

Setting Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

36 1 1.77 0.004 1.77 26.16 4.33 5.96E+11

38 0.5 1.13 0.004 2.26 33.41 7.82 8.43E+11

DI

water

Time

acc

Ave

Rm(1/m)

38 9 10 19.21 0.004 2.134444444 31.55 6.16 7.03E+11

38 9 20 19.22 0.004 2.14 31.57 6.14 7.00E+11 7.01E+11

38 9 30 19.18 0.004 2.13 31.50 6.27 7.17E+11

Raw Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

38 9 10 19.09 0.004 2.12 31.35 7.64 8.77E+11 1.76E+11

38 9 20 19.09 0.004 2.12 31.35 7.44 8.54E+11 1.53E+11

38 9 30 19.13 0.004 2.13 31.42 7.44 8.53E+11 1.51E+11

38 9 40 19.08 0.004 2.12 31.34 8.10 9.30E+11 2.29E+11

38 9 50 19.06 0.004 2.12 31.31 8.46 9.73E+11 2.72E+11

38 9 60 19.08 0.004 2.12 31.34 8.39 9.64E+11 2.62E+11

38 9 70 19.05 0.004 2.12 31.29 8.39 9.65E+11 2.64E+11

38 9 80 19.07 0.004 2.12 31.32 8.75 1.01E+12 3.04E+11

38 9 90 19.05 0.004 2.12 31.29 9.12 1.05E+12 3.47E+11

38 9 100 19.04 0.004 2.12 31.27 8.75 1.01E+12 3.06E+11

38 9 110 19.04 0.004 2.12 31.27 8.72 1.00E+12 3.02E+11

38 9 120 19.04 0.004 2.12 31.27 9.41 1.08E+12 3.81E+11

38 9 130 19.03 0.004 2.11 31.26 9.48 1.09E+12 3.90E+11

38 9 140 19.03 0.004 2.11 31.26 8.97 1.03E+12 3.32E+11

Table A5-5 Filtration data of UF test 2 of spinach wastewater after coagulation

Setting Time

(min)

Δ

Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

38 2.5 5.52 0.004 2.208 32.64 4.33 4.78E+11

37 1 2.08 0.004 2.08 30.75 7.82 9.16E+11

DI water Time

acc

Δ

Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m) Ave Rm

(1/m)

37.5 9 10 19.26 0.004 2.14 31.63 9.42 1.07E+12

37.5 9 20 19.3 0.004 2.14 31.70 9.61 1.09E+12 1.08E+12

137

Coagulation Time

(min)

Δ

Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

37.5 9 10 18.59 0.004 2.07 30.53 9.32 1.10E+12 1.66E+10

37.5 9 20 18.74 0.004 2.08 30.78 9.63 1.13E+12 4.40E+10

37.5 9 30 18.74 0.004 2.08 30.78 9.65 1.13E+12 4.68E+10

37.5 9 40 18.77 0.004 2.09 30.83 9.65 1.13E+12 4.50E+10

37.5 9 50 18.79 0.004 2.09 30.86 9.65 1.13E+12 4.38E+10

37.5 9 60 18.81 0.004 2.09 30.89 9.85 1.15E+12 6.59E+10

37.5 9 70 18.81 0.004 2.09 30.89 10.05 1.17E+12 8.92E+10

37.5 9 80 18.83 0.004 2.09 30.93 10.05 1.17E+12 8.80E+10

37.5 9 90 19.34 0.004 2.15 31.77 10.13 1.15E+12 6.67E+10

37.5 9 100 18.83 0.004 2.09 30.93 10.25 1.19E+12 1.11E+11

37.5 9 110 18.83 0.004 2.09 30.93 10.25 1.19E+12 1.11E+11

37.5 9 120 18.81 0.004 2.09 30.89 10.18 1.19E+12 1.05E+11

37.5 9 130 18.8 0.004 2.09 30.88 10.18 1.19E+12 1.05E+11

37.5 9 140 18.81 0.004 2.09 30.89 10.32 1.20E+12 1.20E+11

37.5 9 150 18.81 0.004 2.09 30.89 10.25 1.19E+12 1.13E+11

Table A5-6 Filtration data of UF test 2 of spinach wastewater after DAF

Setting Time

(min)

Δ

Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

37.5 1 2.15 0.004 2.15 31.78 4.33 4.90E+11

DI

water

Time acc Δ

Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

37.5 9 10 17.51 0.004 1.945555556 28.76 7.06 8.84E+11 30.57176

38 9 20 19.17 0.004 2.13 31.49 7.43 8.50E+11 8.67E+11

38 9 30 19.16 0.004 2.13 31.47 7.59 8.68E+11

DAF Time

(min)

Δ

Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

38 9 10 19.16 0.004 2.13 31.47 8.82 1.01E+12 1.41E+11

38 9 20 19.16 0.004 2.13 31.47 8.72 9.97E+11 1.30E+11

38 9 30 19.16 0.004 2.13 31.47 8.92 1.02E+12 1.53E+11

38 9 40 19.17 0.004 2.13 31.49 9.12 1.04E+12 1.75E+11

38 9 50 19.16 0.004 2.13 31.47 8.72 9.97E+11 1.30E+11

38 9 60 19.17 0.004 2.13 31.49 8.72 9.96E+11 1.29E+11

38 9 70 19.16 0.004 2.13 31.47 8.72 9.97E+11 1.30E+11

38 9 80 19.16 0.004 2.13 31.47 8.72 9.97E+11 1.30E+11

38 9 90 19.16 0.004 2.13 31.47 8.72 9.97E+11 1.30E+11

138

38 9 100 19.16 0.004 2.13 31.47 8.52 9.74E+11 1.07E+11

38 9 110 19.17 0.004 2.13 31.49 8.72 9.96E+11 1.29E+11

38 9 120 19.17 0.004 2.13 31.48 8.72 9.97E+11 1.29E+11

38 9 130 19.17 0.004 2.13 31.49 8.72 9.96E+11 1.29E+11

38 9 140 19.17 0.004 2.13 31.49 8.72 9.96E+11 1.29E+11

Table A5-7 Filtration data of UF test 1 of potato raw wastewater

Setting Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

10 1 0.59 0.003 0.59 13.48 4.33 1.16E+12

DI water Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m) Ave Rm

(1/m)

10 9 10 5.37 0.60 13.63 7.52 1.98E+12 13.56751

10 9 20 5.32 0.59 13.50 7.52 2.00E+12 2.00E+12

10 9 30 5.33 0.59 13.53 7.52 2.00E+12

potato raw Water Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

10 9 10 5.05 0.56 12.82 9.31 2.61E+12 6.18E+11

10 9 20 5.09 0.57 12.92 9.28 2.58E+12 5.89E+11

10 9 30 5.08 0.56 12.89 9.92 2.77E+12 7.72E+11

10 9 40 5.09 0.57 12.92 9.99 2.78E+12 7.88E+11

10 9 50 5.09 0.57 12.92 9.88 2.75E+12 7.57E+11

10 9 60 5.09 0.57 12.92 10.72 2.99E+12 9.90E+11

10 9 70 5.11 0.57 12.97 10.83 3.01E+12 1.01E+12

10 9 80 5.08 0.56 12.89 10.84 3.03E+12 1.03E+12

10 9 90 5.03 0.56 12.77 11.15 3.14E+12 1.15E+12

10 9 100 5.03 0.56 12.77 11.09 3.13E+12 1.13E+12

10 9 110 5.06 0.56 12.84 11.15 3.12E+12 1.13E+12

10 9 120 5.06 0.56 12.84 11.33 3.18E+12 1.18E+12

Table A5-8 Filtration data of UF test 1 of potato wastewater after coagulation

Setting Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm

(1/m)

10 1 0.63 0.003 0.63 14.07 4.33 1.11E+12

DI water Time

acc

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)


10 9 10 5.02 0.003 0.56 12.46 5.95 1.72E+12

10 9 20 5.01 0.003 0.56 12.43 5.83 1.69E+12 1.72E+12

10 9 30 5.08 0.003 0.56 12.61 6.15 1.76E+12

139

potato after

coagulation

Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

10 9 10 5.06 0.003 0.56 12.56 7.12 2.04E+12 3.19E+11

10 9 20 5.06 0.003 0.56 12.56 7.18 2.06E+12 3.38E+11

10 9 30 5.07 0.003 0.56 12.58 7.52 2.15E+12 4.29E+11

10 9 40 5.06 0.003 0.56 12.56 7.92 2.27E+12 5.48E+11

10 9 50 5.06 0.003 0.56 12.56 7.92 2.27E+12 5.48E+11

10 9 60 5.06 0.003 0.56 12.56 8.05 2.31E+12 5.86E+11

10 9 70 5.07 0.003 0.56 12.58 7.92 2.26E+12 5.43E+11

10 9 80 5.07 0.003 0.56 12.58 7.92 2.26E+12 5.43E+11

10 9 90 5.06 0.003 0.56 12.56 7.92 2.27E+12 5.48E+11

10 9 100 5.04 0.003 0.56 12.51 7.92 2.28E+12 5.57E+11

10 9 110 5.07 0.003 0.56 12.58 7.92 2.26E+12 5.43E+11

10 9 120 5.07 0.003 0.56 12.58 7.98 2.28E+12 5.62E+11

10 9 130 5.10 0.003 0.57 12.66 8.32 2.36E+12 6.44E+11

Table A5-9 Filtration data of UF test 1 of potato wastewater after DAF

Setting Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm

(1/m)

10 1 0.6 0.003 0.6 14.36 4.33 1.09E+12

DI water Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m) Ave Rm

(1/m)

10 9 10 4.95 5.06 0.55 13.16 3.52 9.61E+11

10 9 20 4.95 0.55 13.16 3.52 9.61E+11 1.05E+12

10 9 30 5.16 0.57 13.72 3.89 1.02E+12

10 9 40 5.16 0.57 13.72 3.94 1.03E+12

potato

after

DAF

Time

(min)

Δ Weight

(g)

Area (m2) Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt

(1/m)

Rm (1/m) Rf (1/m)

10 9 10 5.07 0.56 13.48 6.18 1.65E+12 6.04E+11

10 9 20 5.13 0.57 13.64 6.72 1.77E+12 7.25E+11

10 9 30 5.1 0.57 13.56 6.34 1.68E+12 6.36E+11

10 9 40 5.09 0.57 13.54 6.40 1.70E+12 6.54E+11

10 9 50 5.11 0.57 13.59 6.72 1.78E+12 7.32E+11

10 9 60 5.12 0.57 13.62 6.72 1.78E+12 7.29E+11

10 9 70 5.12 0.57 13.62 6.50 1.72E+12 6.72E+11

10 9 80 5.09 0.57 13.54 6.72 1.79E+12 7.39E+11

10 9 90 5.10 0.57 13.56 6.72 1.78E+12 7.36E+11

10 9 100 5.13 0.57 13.64 6.77 1.79E+12 7.39E+11

10 9 110 5.1 0.57 13.56 6.98 1.85E+12 8.07E+11

10 9 120 5.11 0.57 13.59 6.93 1.84E+12 7.89E+11

140

Table A5-10 Filtration data of UF test 2 of potato raw wastewater

Setting Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m)

15 4 2.4 0.004 0.6 8.87 3.89 1.58E+12

DI water Time

acc

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rm (1/m) Ave Rm

(1/m)

15 9 10 7.80 0.004 0.87 12.81 3.90 1.10E+12

15 9 20 7.72 0.004 0.86 12.68 3.93 1.12E+12 1.13E+12

15 9 30 7.76 0.004 0.86 12.75 4.14 1.17E+12

15 9 30 7.72 0.004 0.86 12.68 3.93 1.12E+12

Raw Time

(min)

Δ Weight

(g)

Area

(m2)

Flow

(ml/min)

Flux

(L/m2/h)

TMP

(kPa)

Rt (1/m) Rf (1/m)

15 9 10 7.66 0.004 0.85 12.58 4.92 1.41E+12 2.81E+11

15 9 20 7.66 0.004 0.85 12.58 5.56 1.59E+12 4.64E+11

15 9 30 7.63 0.004 0.85 12.58 6.08 1.74E+12 6.11E+11

15 9 40 7.65 0.004 0.85 12.53 6.32 1.81E+12 6.87E+11

15 9 50 7.65 0.004 0.85 12.56 6.48 1.86E+12 7.28E+11

15 9 60 7.63 0.004 0.85 12.56 6.64 1.90E+12 7.74E+11

15 9 70 7.61 0.004 0.85 12.53 6.88 1.97E+12 8.48E+11

15 9 80 7.63 0.004 0.85 12.50 7.04 2.03E+12 8.99E+11

15 9 90 7.66 0.004 0.85 12.53 7.12 2.04E+12 9.17E+11

15 9 100 7.66 0.004 0.85 12.58 7.12 2.04E+12 9.09E+11

15 9 110 7.66 0.004 0.85 12.58 7.34 2.10E+12 9.72E+11

15 9 120 7.67 0.004 0.85 12.58 7.52 2.15E+12 1.02E+12

Table A5-11 Filtration data of UF test 2 of potato wastewater after coagulation

Setting Time (min)

Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rm (1/m)

15 1 0.96 0.004 0.96 14.19 4.33 1.10E+12

DI water

Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)


15 5.5 10 4.83 0.004 0.88 12.98 3.52 9.75E+11

15 9 20 7.58 0.004 0.84 12.45 3.43 9.92E+11 9.79E+11

15 9 30 7.58 0.004 0.84 12.45 3.36 9.72E+11

141

after coagulation

Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rt (1/m) Rf (1/m)

15 9 10 7.68 0.004 0.85 12.61 4.16 1.19E+12 2.06E+11

15 9 20 7.68 0.004 0.85 12.61 4.16 1.19E+12 2.06E+11

15 9 30 7.69 0.004 0.85 12.63 4.24 1.21E+12 2.28E+11

15 9 40 7.7 0.004 0.86 12.65 4.40 1.25E+12 2.72E+11

15 9 50 7.71 0.004 0.86 12.66 4.40 1.25E+12 2.70E+11

15 9 60 7.72 0.004 0.86 12.68 4.56 1.29E+12 3.14E+11

15 9 70 7.72 0.004 0.86 12.68 4.56 1.29E+12 3.14E+11

15 9 80 7.72 0.004 0.86 12.68 4.72 1.34E+12 3.59E+11

15 9 90 7.72 0.004 0.86 12.68 4.76 1.35E+12 3.72E+11

Table A5-12 Filtration data of UF test 2 of potato wastewater after DAF

Setting Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rm (1/m)

15 4 2.4 0.004 0.6 8.87 3.89 1.58E+12

DI water Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rm (1/m) Ave Rm

(1/m)

15 9 10 7.80 0.004 0.87 12.81 3.90 1.10E+12

15 9 20 7.72 0.004 0.86 12.68 3.93 1.12E+12 1.13E+12

15 9 30 7.76 0.004 0.86 12.75 4.14 1.17E+12

15 9 30 7.72 0.004 0.86 12.68 3.93 1.12E+12

DAF Time (min)

Δ Weight

(g)

Area (m2)

Flow (ml/min)

Flux (L/m2/h)

TMP (kPa)

Rt (1/m) Rf (1/m)

15 9 10 7.66 0.004 0.85 12.58 4.92 1.41E+12 2.81E+11

15 9 20 7.66 0.004 0.85 12.58 5.56 1.59E+12 4.64E+11

142

15 9 30 7.63 0.004 0.85 12.58 6.08 1.74E+12 6.11E+11

15 9 40 7.65 0.004 0.85 12.53 6.32 1.81E+12 6.87E+11

15 9 50 7.65 0.004 0.85 12.56 6.48 1.86E+12 7.28E+11

15 9 60 7.63 0.004 0.85 12.56 6.64 1.90E+12 7.74E+11

15 9 70 7.61 0.004 0.85 12.53 6.88 1.97E+12 8.48E+11

15 9 80 7.63 0.004 0.85 12.50 7.04 2.03E+12 8.99E+11

15 9 90 7.66 0.004 0.85 12.53 7.12 2.04E+12 9.17E+11

15 9 100 7.66 0.004 0.85 12.58 7.12 2.04E+12 9.09E+11

15 9 110 7.66 0.004 0.85 12.58 7.34 2.10E+12 9.72E+11

15 9 120 7.67 0.004 0.85 12.58 7.52 2.15E+12 1.02E+12

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