1. pets
2. dogs

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
University of Guelph, 2015
Advisor:
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.
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.
iii
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
iv
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
5.4.4 Contaminant Removal ..................................................................................... 71
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
5.5.4 Contaminant Removal ..................................................................................... 85
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
v
A.5 Experiments data of Membrane Filtration Tests .................................................. 130
vi
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
vii
Figure 5-11 Contaminants removal efficiencies by coagulation - sedimentation and
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
coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in
UF test 1 ..................................................................................................................... 68
Figure 5-18 Fouling resistance of spinach raw wastewater (SR), spinach wastewater after
coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in
UF test 2 ..................................................................................................................... 69
Figure 5-19 Fouling rate of spinach raw wastewater (SR), spinach wastewater after
coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in
UF test 2 ..................................................................................................................... 69
Figure 5-20 Comparison of effluent qualities after different treatment methods of spinach
wastewater .................................................................................................................. 73
Figure 5-21 Effects of UF air scouring rate on fouling resistance in the treatment of
potato wastewater ....................................................................................................... 75
viii
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
coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF
test 1 ........................................................................................................................... 79
Figure 5-27 Fouling resistance of potato raw wastewater (PR), potato wastewater after
coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF
test 2 ........................................................................................................................... 80
Figure 5-28 Fouling rate of potato raw wastewater (PR), potato wastewater after
coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF
test 2 ........................................................................................................................... 81
Figure 5-29 Comparison of effluent qualities after different treatment methods of potato
wastewater .................................................................................................................. 87
ix
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
x
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.
1
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.
2
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
Cambridge
Toronto
(Ministry of the
Environment, 1989)
(City of
Cambridge, 2002)
(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
/
50
50
6 - 10.5
5.5 - 9.5
6 - 11.5
Total Aluminum
(mg/L)
pH
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
3
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.
4
Table 2-2 Vegetative wastewater characteristics
Wastewater
Source
BOD5
(mg/L)
Potato
COD
(mg/L)
TSS
(mg/L)
TN
(mg/L)
265037000
16504420
165
Carrot
670
680 - 1300
Beans
1800
3410
Beets
1580-7600
1820-8740
Spinach
40
240
1400
3280 6960
11201380
Tomato
1340
TP
(mg/L)
pH
References
5-9
(Burgoon et al., 1999;
Karim & Sistrunk, 1985a;
Muniraj et al., 2013)
41
5.8
7
(Hamilton, 2006; Kern,
2006, Reimann, 2002)
112
21.5
6
(Soderquist et al., 1975)
94.5
(Soderquist et al., 1975)
(Wright et al., 1979)
46.2 -47.5
4-6
(Gohil & Nakhla, 2006)
TSS: Total suspended solids; cTOC: colloid Total organic carbon; TN: Total nitrogen; TP: Total phosphorus; TS: Total solids.
5
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
6
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.
7
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
Prefiltration+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
Potato processing
Aerobic Biological
Treatment Reactor
Integrated Natural
Systems
COD, oil and grease loads
(Azbar & Yonar, 2004)
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)
8
Fishing industry
Crossflow membrane
Food and beverage Combined MBR and twostage NF+UV
industry
Suspended materials, fats
(Almas, 1985)
SS, electrical conductivity, content of Na+ions and Cl--ions, COD, TOC, E. coli
coliform bacteria, fecal streptococci, sulfite
reducing, spore forming anaerobes,
TS, TSS, BOD5
(Blöcher et al., 2002)
Corn starch
wastewater
MF+RO
(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
Fish Farming
Wastewater
UF+RO
BOD5, COD, TN, TP
(Reimann, 2002)
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.
9
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).
10
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 hollowfiber 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
11
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).
12
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
Microfiltration
Sieve
0.08-2.0
405-1600
Spiral wound,
Water and
hollow fiber, plate dissolved solutes
and frame
TSS, turbidity, protozoan
oocysts and cysts, some
bacterial and viruses
Ultrafiltration
Sieve
0.005-0.2
405-815
Spiral wound,
Water and small
hollow fiber, plate molecules
and frame
Macromolecules, colloids,
most bacteria, some viruses,
proteins
Nanofiltration
Sieve+sulutio
n/diffusion+e
xclusion
0.001-0.01
200-815
Spiral wound,
hollow fiber
Small molecules, some
hardness, viruses
Reverse
Osmosis
Sieve+sulutio
n/diffusion+e
xclusion
0.00010.001
320-490
Spiral wound,
Water and very
hollow fiber, thin- small molecules,
film composite
ionic solutes
13
Permeate
description
Water and very
small molecules,
ionic solutes
Typical constituents
removed
Very small molecules, color,
hardness, sulphates, nitrate,
sodium, other ions
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:
14
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
15
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.
16
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
17
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
18
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
19
contributed to higher membrane permeability than sweep flocs mechanism did in a deadend 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 deadend 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
20
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
21
recommended that set the pressure range from 60 to 90 psi in the saturation tank (AlShamrani 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 oversaturated 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.
22
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.
23
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.
24
25
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.
26
Table 4-1 Vegetable wastewater sampling details
Products
Apple
Potato
Mushroom
Ginseng
Carrot
Spinach
Mixed
Vegetable
Sampling
times
3
7
1
2
5
6
2
Sampling volume (L)
2
2+ 60 (for three times)
2
2
2
50-75
2
NO. of sampled
industries
2
3
1
2
2
1
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.
27
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.
28
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
29
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
30
Air
Over-saturated
water
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.
31
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.
32
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.
33
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.
34
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).
35
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):
36
𝑅𝑡 =
∆𝑃
𝑅𝑓 = 𝑅𝑡 − 𝑅𝑚
𝜇𝐽
(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 −𝑅𝑓1
𝑡2 −𝑡1
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
37
(2)
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.
38
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
39
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.
40
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
3600±
2600
400±
62
200±
14
110±
64
550±
130
700±
1100
2000±
2700
2200±
2100
1800±
51
420±
130
370±
110
140±
39
75±48
1200±
1600
240±
270
960±16
680±
920
87±46
4.4±
2.1
36±
34
3.8
24±
28
3.2±3.3
0.3±0.1
19±23
38±28
10.4
56
8.8±12
20±19
30±32
870±140
4.0
0.1
4.0
2.9
7.5±
0.4
nd
56±20
110±10
0.9±1.0
2±1
2.6±1.1
0.4±0.2
3±1
95
27±1.0
9.7
0.1
23
1.7±
1.3
2.1±
1.5
4.7
8.9
36±5.0
0.08
1.4±0.2
0.8±1.0
0.9±0.1
7.7±
0.1
4.7±
0.7
7.2±
0.7
7.0±
0.4
410±410
130±15
4.6±
2.2
3.1±
0.3
5.1±
1.6
1.5±
4.0
2.0±0.6
220±88
0.38±
0.29
0.11±
0.06
0.55±
0.01
0.15±
0.08
0.59±
0.01
0.57
Potato
Mushroom
Carrot
Spinach
Mixed
Vegetable
Ginseng
460
41
1.2±
0.6
nd
92±51
560±42
360±330
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
42
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.
43
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,
44
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).
45
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.
46
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
47
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.
48
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.
49
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.
DO Concentration (%)
25
20
15
10
DOf
concentration
5
0
50
60
70
80
Saturation Pressure (psi)
90
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)
50
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
51
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.
Removal Efficiency (%)
100
80
60
40
Turbidity
20
TSS
0
0
15
30
45
Recycle Rate (%)
60
75
Figure 5-6 Effects of DAF recycle rate on suspended solids removal in the treatment of
spinach wastewater
52
Removal Efficiency (%)
100
80
60
40
20
Turbidity
0
0
10
20
30
Flotation Time (min)
40
50
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.
53
140
Turbidity
Removal Efficiency (%)
120
TSS
COD
100
80
60
40
20
0
0
10
20
30
40
Recycle Rate (%)
50
60
70
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
54
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.
Removal Efficiency (%)
100
80
60
40
Turbidity
20
TSS
0
0
10
20
30
Flotation Time (min)
40
50
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
55
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.
56
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)
SR
110±64
130±39
370±110
220±88
SCS
4.3±2.9
120±44
340±120
SD
10±5.9
71±55
PR
3000±1000
PCS
PD
NO3-N
(mg/L)
TP
(mg/L)
NH4+-N
(mg/L)
3±0
2.6±1.1
2.1±1.5
0.4±0.2
650±450
3±0
2.8±0.1
0.9±0.5
0.3±0.2
670±290
2±1
2.7±0.6
0.4±0.4
0.3±0.2
24±21
2.2±1.0
15±13
3.4±2.4
600±290
16±14
1.4±0.2
0.9±0.8
3.9±3.0
450±210
13±14
1.7±0.5
1.7±0.5
2.5±2.2
TDS
(mg/L)
Filtered
TN
(mg/L)
520±110
430±110
150±130
910±18
360±160
140±130
810±260
71±58
1200±480
150±89
30±20
19±19
170±220
ND
620±300
100±30
20±15
250±230
210±4.0
560±240
3600±1600 1000±630
SR/PR: Spinach / Potato raw wastewater; SCS/PCS: Spinach / Potato wastewater after coagulation - sedimentation; SD/PD: Spinach /
Potato wastewater after coagulation – DAF.
57
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.
58
Removal efficiency (%)
120
100
96
85
Sedimentation
77
DAF
67
80
60
19
40
20
7
24
13
19
17
5
21
21
27
6
0
0
TSS
BOD5
COD
cTOC
TP
NH4+-N
NO3-N
TN
Figure 5-10 Contaminants removal efficiencies by coagulation - sedimentation and
coagulation - DAF of spinach wastewater
120
Removal efficiency (%)
100
99
96
Sedimentation
85 83
DAF
80
73 73
70 66
52
25
60
37
30
40
20
0
TSS
COD
cTOC
TP
TN
NO3-N
Figure 5-11 Contaminants removal efficiencies by coagulation - sedimentation and
coagulation - DAF of potato wastewater
59
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.
60
1.00E+12
Fouling Resistance (1/m)
2L/min
1L/min
8.00E+11
4L/min
6.00E+11
4.00E+11
2.00E+11
0.00E+00
0
10
20
30
Time (min)
40
50
Figure 5-12 Effects of UF air scouring rate on fouling resistance in the treatment of
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.
61
50
70
TMP (kPa)
60
40
TMP (kPa)
Flux (LMH)
50
30
40
30
20
20
10
10
0
0
0
10
20
30
Time (min)
40
50
Figure 5-13 Critical flux measurement of spinach raw wastewater
60
50
TMP (kPa)
50
Flux (LMH)
40
TMP (kPa)
30
30
Flux (LMH)
40
20
20
10
10
0
0
0
10
20
30
Time (min)
40
50
60
Figure 5-14 Critical flux measurement of spinach wastewater after coagulation
62
TMP （kPa)
60
60
50
50
40
40
30
30
20
20
TMP (kPa)
10
10
Flux (LMH)
0
0
0
10
20
30
Time (min)
40
50
60
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.
63
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.
64
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.
65
Table 5-3 Spinach feed water parameters for UF Test 1 and Test 2
(mg/L)
TP
(mg/L)
NH4+-N
(mg/L)
COD
(mg/L)
BOD5
(mg/L)
Turbidity
(NTU)
150
0.7
3.8
0.1
490
280
65
150
150
0.6
3.7
0.1
480
270
67
5.5
130
120
0.5
0.9
0.1
310
190
4.3
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
Feed Water
TSS
(mg/L)
pH
cTOC
(mg/L)
DOC
(mg/L)
SR Test 1
130
4.1
160
SC Test 1
160
5.4
SD Test 1
10
SR Test 2
NO3-N
66
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.
67
2.1E+12
After coagulation
Fouling resistance (1/m)
1.8E+12
After DAF
Raw
1.5E+12
1.2E+12
9.0E+11
6.0E+11
3.0E+11
0.0E+00
10
30
50
70
90
Time (min)
110
130
150
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
Fouling rate (kPa/min)
0.5
0.4
SR
SC
SD
0.3
0.2
0.1
0
0
30
60
90
120
150
Time (min)
Figure 5-17 Fouling rate of spinach raw wastewater (SR), spinach wastewater after
coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in UF test 1
68
4.2E+11
After coagulation
After DAF
Fouling resistance (1/m)
3.5E+11
Raw
2.8E+11
2.1E+11
1.4E+11
7E+10
0
10
30
50
70
90
Time (min)
110
130
Figure 5-18 Fouling resistance of spinach raw wastewater (SR), spinach wastewater after
coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in UF test 2
0.16
Fouling rate (kPa/min)
0.14
0.12
SR
SC
SD
0.1
0.08
0.06
0.04
0.02
0
0
20
40
60
80
100
Time (min)
120
140
160
Figure 5-19 Fouling rate of spinach raw wastewater (SR), spinach wastewater after
coagulation (SC) and spinach wastewater after coagulation – DAF (SD) in UF test 2
69
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 labscale 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
70
coagulation and DAF, the TMP rising rates and fouling resistance were reduced, whereas
DAF treatment had slightly lower fouling rates than coagulation.
5.4.4 Contaminant Removal
Nine physical parameters were measured for reviewing effluent qualities of different
treatment technologies on spinach wastewater.
71
200
200
130
110 110
160
100
100
TSS concentration
(mg/L)
CTOC concentration
(mg/L)
130
81
120
80
40
0
160
74
120
80
40
12
SR
SC
SD SRU SCU SDU
SR
SC
(a)
373
440
400
406
363
0
SD SRU SCU SDU
150.0
92
346
355
120.0
300
200
90.0
47
60.0
100
30.0
0
0.0
5.9
SR
SC
SR
SD SRU SCU SDU
SC
0.6
0.3
0.3
SD SRU SCU SDU
(d)
(c)
400
10.0
220 240
240
210
8.0
140
150 150
6.0
4.7
5.5
SR
SC
5.7
5.4
5.9
5.8
pH
BOD5 concentration
(mg/L)
0
(b)
Turbidity (NTU)
COD concentration
(mg/L)
500
320
0
0
160
4.0
80
2.0
0
0.0
SR
SC
SD SRU SCU SDU
(e)
SD SRU SCU SDU
(f)
72
4.0
5.0
2.6
2.3
2.0
1.8
3.0
TP concentration (mg/L)
NO3-N concentration
(mg/L)
5.0
1.6
1.7
2.0
1.0
0.0
SR
SC
SD SRU SCU SDU
4.0
2.1 2.5
1.4
3.0
1.2
2.0
1.0
0.4
0.4
0.0
SR
SC
SD SRU SCU SDU
(g)
(i)
NH4+-N concentration
(mg/L)
1.0
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
0.8
0.6
0.4
0.3
0.4
0.3
0.2
0.2 0.2
0.2
0.0
SR SC SD SRU SCU SDU
(h)
Figure 5-20 Comparison of effluent qualities after different treatment methods of spinach
wastewater
73
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.
74
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.
Fouling Resistance (1/m)
2.0E+12
1L/min
4L/min
1.6E+12
2 L/min
1.2E+12
8.0E+11
4.0E+11
0.0E+00
0
10
20
30
Time (min)
40
50
Figure 5-21 Effects of UF air scouring rate on fouling resistance in the treatment of
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.
75
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.
18
30
TMP (kPa)
15
25
12
20
9
15
6
10
3
5
0
Flux (LMH)
TMP (kPa)
Flux (LMH)
0
0
10
20
30
Time (min)
40
50
60
Figure 5-22 Critical flux measurement of potato raw wastewater (PR)
76
12
30
TMP (kPa)
10
25
8
20
6
15
4
10
2
5
0
Flux (LMH)
TMP (kPa)
Flux (LMH)
0
0
10
20
30
Time (min)
40
50
60
Figure 5-23 Critical flux measurement of potato wastewater after coagulation (PC)
10
30
TMP (kPa)
24
Flux (LMH)
6
18
4
12
2
6
0
Flux (LMH)
TMP (kPa)
8
0
0
10
20
30
Time (min)
40
50
Figure 5-24 Critical flux measurement of potato wastewater after coagulation and DAF
(PD)
77
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.
78
1.4E+12
Fouling resistance (1/m)
1.2E+12
1.0E+12
8.0E+11
6.0E+11
4.0E+11
Raw
After coagulation
2.0E+11
After DAF
0.0E+00
0
20
40
60
80
100
120
Time (min)
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
Fouling rate (kPa/min)
0.12
0.1
PD
PC
PR
0.08
0.06
0.04
0.02
0
0
20
40
60
Time (min)
80
100
120
Figure 5-26 Fouling rate of potato raw wastewater (PR), potato wastewater after
coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF test 1
79
1.0E+12
Raw
After coagulation
Fouling resistance (1/m)
8.0E+11
After DAF
6.0E+11
4.0E+11
2.0E+11
0.0E+00
10
30
50
70
Time (min)
90
110
Figure 5-27 Fouling resistance of potato raw wastewater (PR), potato wastewater after
coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF test 2
80
Fouling rate (kPa/min)
0.1
PR
0.08
PC
PD
0.06
0.04
0.02
0
0
20
40
60
Time (min)
80
100
Figure 5-28 Fouling rate of potato raw wastewater (PR), potato wastewater after
coagulation (PC) and potato wastewater after coagulation – DAF (PD) in UF test 2
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
81
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·m1
, 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
82
wastewater. It implies that UF is more suitable for potato wastewater rather than spinach
wastewater.
83
Table 5-4 Potato feed water parameters for UF test 1 and test 2
(mg/L)
TP
(mg/L)
NH4+-N
(mg/L)
COD
(mg/L)
Turbidity
(NTU)
30
0.8
9.8
6.6
1900
1000
7.0
22
0.7
6.7
5.2
1200
560
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
Feed
Water
TSS
(mg/L)
pH
cTOC
(mg/L)
PR Test 1
3200
7.0
PC Test 1
3700
PD Test 1
NO3-N
84
5.5.4 Contaminant Removal
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.
85
40
35000
48
TSS concentration
(mg/L)
CTOC concentration
(mg/L)
60
28
28
36
19
22
21
24
12
16000
28000
21000
14000
5800
7000
83
0
0
0
0
0
PR PC PD PRU PCU PDU
(a)
2000
1220
1600
1200
Turbidity (NTU)
COD concentration
(mg/L)
2000
(b)
905
800
400
159 144 131 152
1600
1000
1200
780
800
400
24 0.65 0.68 0.02
0
0
PR PC PD PRU PCU PDU
PR PC PD PRU PCU PDU
(c)
400
10.0
300
8.0
210
300
pH
BOD5 concentration
(mg/L)
500
(d)
200
8.0
7.4
7.6
6.8
6.8
7.2
PR
PC
PD PRU PCU PDU
6.0
4.0
100
25
44
51
2.0
39
0
0.0
PR PC PD PRU PCU PDU
(e)
(f)
86
2.0
1.1
1.7
1.1
NH4+-N concentration
(mg/L)
NO3-N concentration
(mg/L)
2.5
1.2
1.0
1.5
1.0
0.6
0.5
0.0
TP concentration (mg/L)
(g)
26
8.0
3.9
3.5
3.3
2.1
4.0
1.6
0.0
PC
PD PRU PCU PDU
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
36.0
27.0
18.0
2.4
12.0
(i)
24
9.0
8.4
16.0
PR
PR PC PD PRUPCUPDU
45.0
20.0
1.1
0.7
0.2
0.0
PR
PC
PD PRU PCU PDU
(h)
Figure 5-29 Comparison of effluent qualities after different treatment methods of potato
wastewater
87
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.
88
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.
89
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
90
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.
91
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APPENDICES
103
A.1 Water Characteristics
Table A. 1 Vegetative Raw Wastewater Characteristics
Wastewater
TSS
COD BOD5 cTOC BOD5/COD COD/ NO3-N NH4+-N Filtered
TP
(mg/L) (mg/L) (mg/L) (mg/l)
(mg/L) (mg/L)
TN
(mg/L)
cTOC
(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
104
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
105
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
106
TSS Filtered Filtered NO3-N
TP
(mg/L)
TN
TOC
(mg/L) (mg/L)
(mg/L) (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
739
5.5
46.7
266
258
Spinach
74
3
130
1.8
2.5
0.3
107
440
238
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
647
5.7
4.5
Spinach
12
2
103
1.8
1.4
0.2
108
312
165
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
109
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
0.2303
110
44.7385
77.1767
0.7826
NO3-N
TP
(mg/L) (mg/L)
NH4+-N
(mg/L)
COD
(mg/L)
BOD5
(mg/L)
pH
Turbidity
20.0
16.9
489
221
7.0
564
0.6
98.0
16.8
491
228
6.7
1000
na
0.6
99.0
1.5
1110
468
nd
nd
na
0.4
or
1.7
1230
or
nd
nd
5.2
968
TSS
(mg/L)
Filtered
TOC
(mg/L)
potato after coagulation
28753
22
0.7
potato after coagulation
27967
35
potato after coagulation
3555
potato after coagulation
3755
potato after coagulation
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
111
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
112
DAF/UF
potato after coagulation,
DAF/UF
nd
na
0.6
or
0.9
114
29
nd
nd
potato after coagulation,
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
113
A.2 Standard Curves for Water Quality Analyses
Table A. 2 Parameters standard curves
114
0.45
0.4
0.35
Abs
0.3
0.25
0.2
0.15
0.1
0.05
0
0
200
400
600
800
1000
COD standard solution concentration (mg/L)
1200
Figure A. 1 COD high range calibration curve
1.6
y = 0.0276x - 0.0065
R² = 0.9993
1.4
1.2
Abs
1
0.8
0.6
0.4
0.2
0
-0.2
0
10
20
30
40
50
Ammonia standard solution concentration (mg/L)
Figure A. 2 Ammonia high range calibration curve
115
60
2
y = 0.9222x - 0.0079
R² = 0.9998
1.8
1.6
1.4
Abs
1.2
1
0.8
0.6
0.4
0.2
0
0
0.5
1
1.5
2
Ammonia standard solution concentration (mg/L)
Figure A. 3 Ammonia low range calibration curve
0.05
0
Abs
-0.05
-0.1
-0.15
-0.2
-0.25
y = -0.0029x + 0.0104
R² = 0.9963
-0.3
0
50
100
150
COD standard solution concentration (mg/L)
Figure A. 4 COD low range calibration curve
116
2.5
1400
y = 5.3331x - 0.371
R² = 0.9998
1200
Area
1000
800
600
400
200
0
0
50
100
150
200
250
TOC standard solution concentration (mg/L)
300
Figure A. 5 TOC calibration curve
1200
y = 20.534x + 6.6451
R² = 0.9995
1000
Area
800
600
400
200
0
0
10
20
30
40
50
TN standard solution concentration (mg/L)
Figure A. 6 TN calibration curve
117
60
A.3 Experiments data of Jar Tests
Alum
pH in
Dose
spinach (mg/L)
mixed
solution
0
4
50
4
30
4
50
4
10
4
30
5
5
5
50
5
2.5
5
0
5
10
5
30
5
10
7
10
7
0
7
5
7
5
7
0
7
2.5
7
30
7
50
7
Turbidity Turbidity COD
COD
RE of
RE
(NTU)
Raw
(mg/L) Raw
Turbidity of
(NTU)
(mg/L)
COD
11.7
67
nd
362
0.83
31.4
71
202
220
0.56
0.08
23.3
71
194
220
0.67
0.12
9
197
241
294
0.95
0.18
6.08
71
191
220
0.91
0.13
2.56
197
219
294
0.99
0.26
4.66
67
188
220
0.93
0.15
1.65
67
nd
362
0.98
29.7
71
196
220
0.58
0.11
47.3
71
205
220
0.33
0.07
3.7
197
222
294
0.98
0.24
1.71
67
nd
362
0.97
5.09
67
nd
362
0.92
0.7
82.2
186
220
0.99
0.15
47
82.2
204
220
0.43
0.07
2.68
67
nd
nd
0.96
0.35
82.2
190
220
1.00
23.7
67
nd
nd
0.65
4.5
82.2
190
220
0.95
0.14
2.04
27.1
324
362
0.92
0.10
3.61
27.1
326
362
0.87
0.10
118
0.14
2.5
13.7
67
nd
nd
0.80
0
24.6
71
362
362
0.65
0.00
5
0.62
27.1
328
362
0.98
0.09
10
3.61
27.1
334
362
0.87
0.08
30
14.4
27.1
353
362
0.47
0.02
7
9
9
9
9
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
119
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 (%)
50
8.3
14.25
60
8.3
13.96
70
8.3
13.65
80
8.3
11.75
90
8.3
12.36
42
41
39
29
33
Air concentration final (mg/L)
67.86
66.48
65.00
55.95
58.86
50
60
70
80
90
8.4
8.43
8.43
8.35
8.49
16.92
16.64
18.46
17.37
19.77
50
49
54
52
57
80.57
79.24
87.90
82.71
94.14
50
60
70
80
90
8.35
8.47
8.33
8.32
8.3
15.76
18.87
19.52
20.93
17.12
47
55
57
60
52
75.05
89.86
92.95
99.67
81.52
Saturation Pressure (psi) Saturation Rate
50
60
70
80
90
std
46
48
50
47
47
Air concentration
4
7
10
16
13
120
std
74
79
82
79
78
6
12
15
22
18
Table A. 4 DAF apparatus saturation time optimization
Air
Saturation DO initial DO final Saturatio concentratio
Time (min) (mg/L)
(mg/L) n Rate (%) 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
10
15
20
25
8.43
8.43
8.43
8.43
8.43
14.76
17.41
16.32
17.84
17.61
75
107
94
112
109
70.29
82.90
77.71
84.95
83.86
5
10
15
20
25
30
8.78
8.78
8.78
8.78
8.78
8.78
15.15
17.24
16.67
16.98
18.35
17.62
73
96
90
93
109
101
72.14
82.10
79.38
80.86
87.38
83.90
Sample
Recycl
e Rate
(%)
Flotatio Turbidit
n Time y (NTU)
(min)
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
121
Spinach
after cog
30
50
Spinach
raw
water
6.61
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
88
71
Control
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
122
Spinach
1
DAF
+cog
10%
1.1
2.3532
200
2.357
7
0.0045
1.1
2.3882
200
2.393
1
1.3
2.3522
200
1.3
2.3761
1.5
DAF
+cog
30%
DAF
+cog
50%
DAF
+cog
70%
Spinach
88
67.3
22
25
26
0.0049
25
27
2.354
4
0.0022
11
14
300
2.379
7
0.0036
12
16
2.3466
225
2.351
4
0.0048
21
32
1.5
2.3473
225
2.350
4
0.0031
14
21
1.7
2.3659
300
2.370
1
0.0042
14
24
1.7
2.3376
300
2.342
6
0.0050
17
28
1
2.5788
200
2.595
7
0.0169
84
84
1
2.4992
200
2.514
7
0.0155
77
77
Removal
Efficien
cy
TSS
Turbidit
y
DAF
+cog
10%
77
89
123
15
26
26
81
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
124
DAF
+cog
70%
70
71
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
83
4.4120
125
8.9103
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
1.0
1000
7169
5740
potato raw
126
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 (%)
30
Flotation Turbidity Turbidity
time
(NTU)
RE
(min)
10
99.35
TSS
(mg/L)
TSS RE
66
91
72
127
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
353
Potato raw
wastewater
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
128
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
129
A.5 Experiments data of Membrane Filtration Tests
30
TMP (kPa)
25
Spinach Raw Water
20
15
Spinach After
Coagulation
Treatment
10
Spinach After
Coagulation and
DAF Treatments
5
0
0
50
100
Time (min)
150
Figure A. 7 Spinach UF TMP results
14
12
TMP (kPa)
10
Spinach Raw Water
8
Spinach After
Coagulation
Treatment
6
4
Spinach After
Coagulation and
DAF Treatments
2
0
0
50
100
Time (min)
150
Figure A. 8 Spinach UF TMP results
130
18
16
TMP(kPa)
14
Spinach Raw Water
12
10
Spinach After
Coagulation
Treatment at pH 7
8
6
4
spinach after cog
and daf at pH 7
2
0
0
50
100
Time (min)
150
Figure A. 9 Spinach Pretreatment at pH 7 UF TMP results
14
12
TMP (kPa)
10
PD
8
6
Potato After
Coagulation
4
PR
2
0
0
50
100
150
Time (min)
Figure A. 10 Potato UF TMP results
131
9
8
TMP (kPa)
7
6
Potato Raw
5
4
Potato After Coagulation
3
Potato After Coagulation
and DAF
2
1
0
0
20
40
60
80
Time (min)
100
120
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)
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)
35
9
10
17.95
0.004
1.99
31.32
10.72
1.23E+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)
132
TMP
(kPa)
Rm (1/m)
Ave Rm
(1/m)
1.26E+12
Rf (1/m)
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
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
DI water
Time
(min)
Δ Weight
(g)
Area
(m2)
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
37
9
30
19.12
2.12
31.40
7.54
8.64E+11
133
Ave Rm
(1/m)
8.60E+11
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
Time
(min)
Δ Weight
(g)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rt (1/m)
Rf (1/m)
Spinach after
coagulation
Area
(m2)
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)
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
134
TMP
(kPa)
Rm (1/m)
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
Time
acc
Δ Weight
(g)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
Ave Rm
(1/m)
1.13E+12
DI water
36
18
20
37.11
2.061666667
30.48
9.40
1.11E+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
Time
(min)
Δ Weight
(g)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rt (1/m)
Rf (1/m)
Spinach after
DAF
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
135
Table A5-4 Filtration data of UF test 2 of spinach raw wastewater
Δ Weight
(g)
1.77
Area
(m2)
0.004
Flow
(ml/min)
1.77
Flux
(L/m2/h)
26.16
TMP
(kPa)
4.33
Rm (1/m)
36
Time
(min)
1
38
0.5
1.13
0.004
2.26
33.41
7.82
8.43E+11
Setting
5.96E+11
9
Time
acc
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
38
9
30
19.18
0.004
2.13
31.50
6.27
7.17E+11
Area
(m2)
0.004
Flow
(ml/min)
2.12
Flux
(L/m2/h)
31.35
TMP
(kPa)
7.64
Rf (1/m)
9
Δ Weight
(g)
19.09
Rt (1/m)
38
Time
(min)
10
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
DI
water
38
Raw
Ave
Rm(1/m)
7.01E+11
Table A5-5 Filtration data of UF test 2 of spinach wastewater after coagulation
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
2.5
Δ
Weight
(g)
5.52
0.004
2.208
32.64
4.33
4.78E+11
1
2.08
0.004
2.08
30.75
7.82
9.16E+11
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
0.004
2.14
31.63
9.42
1.07E+12
0.004
2.14
31.70
9.61
1.09E+12
Setting
Time
(min)
38
37
37.5
9
10
Δ
Weight
(g)
19.26
37.5
9
20
19.3
Time
acc
DI water
136
Ave Rm
(1/m)
1.08E+12
37.5
9
10
Δ
Weight
(g)
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
Coagulation
Time
(min)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rt (1/m)
Rf (1/m)
Table A5-6 Filtration data of UF test 2 of spinach wastewater after DAF
Setting
Time
(min)
37.5
1
Δ
Weight
(g)
2.15
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
0.004
2.15
31.78
4.33
4.90E+11
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
37.5
9
10
Δ
Weight
(g)
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
Time
(min)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rt (1/m)
Rf (1/m)
0.004
2.13
31.47
8.82
1.01E+12
1.41E+11
Time acc
DI
water
38
9
10
Δ
Weight
(g)
19.16
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
DAF
137
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)
1
10
Δ Weight
(g)
0.59
Area
(m2)
0.003
Flow
(ml/min)
0.59
Flux
(L/m2/h)
13.48
TMP
(kPa)
4.33
Rm (1/m)
Δ Weight
(g)
5.37
Area
(m2)
Flow
(ml/min)
0.60
Flux
(L/m2/h)
13.63
TMP
(kPa)
7.52
Rm (1/m)
1.16E+12
10
9
Time
(min)
10
1.98E+12
Ave Rm
(1/m)
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
Δ Weight
(g)
5.05
Flow
(ml/min)
0.56
Flux
(L/m2/h)
12.82
TMP
(kPa)
9.31
Rt (1/m)
Rf (1/m)
DI water
10
9
Time
(min)
10
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
potato raw Water
Area
(m2)
Table A5-8 Filtration data of UF test 1 of potato wastewater after coagulation
Setting
10
Time
(min)
1
Δ Weight
(g)
0.63
Area
(m2)
0.003
Flow
(ml/min)
0.63
Flux
(L/m2/h)
14.07
TMP
(kPa)
4.33
Rm
(1/m)
1.11E+12
Δ Weight
(g)
5.02
Area
(m2)
0.003
Flow
(ml/min)
0.56
Flux
(L/m2/h)
12.46
TMP
(kPa)
5.95
Rm (1/m)
10
9
Time
acc
10
10
9
20
5.01
0.003
0.56
12.43
5.83
1.69E+12
10
9
30
5.08
0.003
0.56
12.61
6.15
1.76E+12
DI water
138
Ave Rm (1/m)
1.72E+12
1.72E+12
Δ Weight
(g)
5.06
Area
(m2)
0.003
Flow
(ml/min)
0.56
Flux
(L/m2/h)
12.56
TMP
(kPa)
7.12
Rt (1/m)
Rf (1/m)
9
Time
(min)
10
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
potato after
coagulation
10
Table A5-9 Filtration data of UF test 1 of potato wastewater after DAF
Setting
10
Δ Weight
Area
(g)
(m2)
0.6
0.003
Time
(min)
1
Δ Weight
(g)
4.95
Flow
Flux
TMP
Rm
(ml/min) (L/m2/h) (kPa)
(1/m)
0.6
14.36
4.33
1.09E+12
10
9
Time
(min)
10
10
9
20
4.95
0.55
13.16
3.52
9.61E+11
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
10
Time
(min)
Δ Weight
(g)
Area (m2)
Flux
(L/m2/h)
TMP
(kPa)
Rt
(1/m)
Rm (1/m)
Rf (1/m)
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
DI water
Area
(m2)
5.06
Flow
(ml/min)
Flow
(ml/min)
0.55
Flux
(L/m2/h)
13.16
TMP
(kPa)
3.52
Rm (1/m)
139
Ave Rm
(1/m)
9.61E+11
1.05E+12
Table A5-10 Filtration data of UF test 2 of potato raw wastewater
Setting
15
Time
(min)
4
Δ Weight
(g)
2.4
Area
(m2)
0.004
Flow
(ml/min)
0.6
Flux
(L/m2/h)
8.87
TMP
(kPa)
3.89
Rm (1/m)
Δ Weight
(g)
7.80
Area
(m2)
0.004
Flow
(ml/min)
0.87
Flux
(L/m2/h)
12.81
TMP
(kPa)
3.90
Rm (1/m)
1.58E+12
15
9
Time
acc
10
15
9
20
7.72
0.004
0.86
12.68
3.93
1.12E+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
Area
(m2)
0.004
Flow
(ml/min)
0.85
Flux
(L/m2/h)
12.58
TMP
(kPa)
4.92
Rf (1/m)
9
Δ Weight
(g)
7.66
Rt (1/m)
15
Time
(min)
10
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
DI water
Raw
Ave Rm
(1/m)
1.10E+12
1.13E+12
Table A5-11 Filtration data of UF test 2 of potato wastewater after coagulation
Setting
Time
(min)
15
1
DI
water
Time
(min)
Δ Weight
(g)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
0.96
0.004
0.96
14.19
4.33
1.10E+12
Time
(min)
Δ Weight
(g)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
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
15
9
30
7.58
0.004
0.84
12.45
3.36
9.72E+11
140
Ave Rm
(1/m)
9.79E+11
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
Δ Weight
(g)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rm (1/m)
DI water
Time
(min)
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
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
Time
(min)
Δ Weight
(g)
Area
(m2)
Flow
(ml/min)
Flux
(L/m2/h)
TMP
(kPa)
Rt (1/m)
Rf (1/m)
DAF
1.13E+12
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
141
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
142