INVESTIGATION OF MICROBUBBLES AND NANOBUBBLES GAS FLOTATION
FOR OIL SEPARATION FROM MARINE OILY WASTEWATER USING RESPONSE
SURFACE METHODOLOGY
by
Wanhua Shen
B.Sc., Wenzhou University, 2019

THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
NATURAL RESOURCES AND ENVIRONMENTAL STUDIES

UNIVERSITY OF NORTHERN BRITISH COLUMBIA
December 2022
© Wanhua Shen, 2022

Abstract
Oily wastewater caused by marine oil spills brings great harm to the environment. In this
work, the application of gas flotation with microbubbles and nanobubbles in separating crude oil
droplets from oily wastewater is reported. The experiments were conducted in a flotation column
with an internal diameter of 5.2 cm and a height of 100 cm. Response surface methodology was
employed to examine the effects of three experimental factors (initial oil concentration, flotation
time, and temperature of inlet wastewater) on the oil separation performance and the interaction
between experimental factors. A good agreement was obtained between the predicted and
experimental data of oil separation efficiency, with a high R2 of 0.99 and an adjusted R2 of 0.98.
The optimization results demonstrate that the maximum oil separation efficiency (98.3%) was
achieved under optimum experimental conditions of 524.5 mg/L initial oil concentration, 28.6 min
flotation time, and 21.2°C inlet wastewater temperature.

ii

List of Publications
This master thesis yielded one published manuscript for Chapter 2, while the other chapters
are combined into one paper and ready for submission. There is another paper (not included in the
thesis) which is already published based on this master’s research. Publication and authorships of
the papers were listed as follows (Published or prepared for submission):
Shen, W., Mukherjee, D., Koirala, N., Hu, G., Lee, K., Zhao, M., & Li, J. (2022). Microbubble
and nanobubble-based gas flotation for oily wastewater treatment: A review. Environmental
Reviews, (ja). (Chapter 2)
Shen, W., Koirala, N., Mukherjee, D., Lee, K., Zhao, M., & Li, J. (2022). Tween 20 Stabilized
Conventional Heavy Crude Oil-In-Water Emulsions Formed by Mechanical Homogenization.
Frontiers in Environmental Science, 486.
Shen, W., Mao, J., Hu, G., Zhao, M., & Li, J. (2022). Investigation of microbubbles and
nanobubbles gas flotation for oil separation from oily wastewater using response surface
methodology. (Prepared for submission)

iii

Table of Contents

Abstract ........................................................................................................................................... ii
List of Publications ........................................................................................................................ iii
Table of Contents ........................................................................................................................... iv
List of Tables ................................................................................................................................ vii
List of Figures .............................................................................................................................. viii
Glossary .......................................................................................................................................... x
Acknowledgement ........................................................................................................................ xii
Chapter 1 Introduction .................................................................................................................... 1
Chapter 2 Literature Review* ......................................................................................................... 4
2.1 Introduction ........................................................................................................................... 4
2.2 Properties of MBs and NBs .................................................................................................. 7
2.2.1 Bubble size ..................................................................................................................... 7
2.2.1.1 Size definition ......................................................................................................... 7
2.2.1.2 Size measurement ................................................................................................... 8
2.2.1.3 Bubble size impact factor........................................................................................ 9
2.2.2 Specific surface area .................................................................................................... 11
2.2.3 Zeta potential ............................................................................................................... 12
2.2.4 Rising velocity ............................................................................................................. 14
2.2.5 Internal pressure ........................................................................................................... 15
2.2.6 Stability of NBs............................................................................................................ 16
2.3 Generation of MBs and NBs ............................................................................................... 19
2.3.1 Pressurized dissolution type ......................................................................................... 19
2.3.2 Venturi type ................................................................................................................. 20
2.3.3 Swirl flow type ............................................................................................................. 22
2.3.4 Porous membrane type ................................................................................................. 23
2.3.5 Ultrasonic irridation type ............................................................................................. 23
2.3.6 Electrolysis type ........................................................................................................... 24
2.4 Gas flotation ........................................................................................................................ 26
2.4.1 Dissolved gas flotation ................................................................................................. 30
2.4.2 Induced gas flotation .................................................................................................... 33
2.4.3 Electrolytic flotation .................................................................................................... 34
iv

2.5 Design parameters for gas flotation .................................................................................... 36
2.5.1 Gas dissolution ............................................................................................................. 36
2.5.2 Gas holdup ................................................................................................................... 37
2.5.3 Recycle ratio ................................................................................................................ 38
2.5.4 Interfacial tension......................................................................................................... 38
2.5.5 Spreading coefficient ................................................................................................... 39
2.6 Factors affecting oil separation efficiency in gas flotation ................................................. 40
2.6.1 Initial oil concentration ................................................................................................ 40
2.6.2 pH ................................................................................................................................. 41
2.6.3 Temperature ................................................................................................................. 42
2.6.4 Pressure ........................................................................................................................ 43
2.6.5 Salinity ......................................................................................................................... 44
2.6.6 Flotation time ............................................................................................................... 45
2.6.7 Oil droplet size ............................................................................................................. 46
2.7 Discussion and conclusions ................................................................................................ 47
Chapter 3 Materials and Methods ................................................................................................. 49
3.1 Materials ............................................................................................................................. 49
3.2 Oil weathering ..................................................................................................................... 50
3.3 Preparation of oily wastewater............................................................................................ 50
3.4 Experimental setup and procedure ...................................................................................... 51
3.5 Experimental design............................................................................................................ 52
3.6 Microscopy analysis............................................................................................................ 55
3.7 Oil concentration analysis ................................................................................................... 56
Chapter 4 Results and Discussion ................................................................................................. 57
4.1 Size distribution of NBs ...................................................................................................... 57
4.2 Regression model generation and statistical analysis ......................................................... 57
4.3 Effect of process parameters on oil separation efficiency .................................................. 60
4.3.1 Effect of initial oil concentration ................................................................................. 60
4.3.2 Effect of flotation time ................................................................................................. 63
4.3.3 Effect of temperature of inlet wastewater .................................................................... 64
4.3.4 Interaction of parameters ............................................................................................. 65
4.4 Response surface optimization and validation of optimized results ................................... 67
4.5 Control experiments ............................................................................................................ 68
4.6 Effect of crude oil condition on oil separation efficiency................................................... 69
v

Chapter 5 Conclusions .................................................................................................................. 71
5.1 Research summary .............................................................................................................. 71
5.2 Limitations and future research .......................................................................................... 72
References ..................................................................................................................................... 74

vi

List of Tables
Chapter 2
Table 2.1 Different factors affecting bubble size .......................................................................... 10
Table 2.2 Different factors affecting zeta potential ...................................................................... 13
Table 2.3 The change of NB concentration and mean diameter in a specific period of time ....... 18
Table 2.4 Comparison of different bubble generation methods ................................................... 25
Table 2.5 Application of gas flotation system for treating oily wastewater ................................. 27
Table 2.6 Summary of different types of gas flotation systems ................................................... 29
Table 2.7 Summary of different gases used in DGF system for wastewater treatment ................ 32
Table 2.8 List of oil droplet size measurement methods .............................................................. 47

Chapter 3
Table 3.1 Physiochemical properties of fresh and weathered CHCO .......................................... 49
Table 3.2 Summary of bubble generator specifications................................................................ 51
Table 3.3 Experimental range and levels of independent variables.............................................. 54
Table 3.4 Experimental matrix of CCD design with oil separation results .................................. 54

Chapter 4
Table 4. 1 Results for oil separation efficiency of CHCO ............................................................ 57
Table 4.2 ANOVA results of the regression model for oil separation efficiency ......................... 58
Table 4.3 Validation results with the actual and the predicted efficiency .................................... 67

vii

List of Figures
Chapter 2
Figure 2.1 Summarized diameter range of MBs and NBs .............................................................. 8
Figure 2.2 Photo of MBs and NBs from a phase-contrast microscope (provided by K. Takahashi,
personal communication, 2022) ...................................................................................................... 9
Figure 2.3 Contaminant separation efficiency with and without NBs .......................................... 12
Figure 2.4 Schematic diagram showing the behavior of MBs and NBs under water (modified
from Agarwal et al. 2011) ............................................................................................................. 16
Figure 2.5 Bubble generation methods ......................................................................................... 19
Figure 2.6 Pressurized dissolution type bubble generator (modified from Arumugam, 2015) .... 20
Figure 2.7 Venturi type bubbe generator (modified from Zhao et al., 2017; Li et al., 2017) ....... 21
Figure 2.8 Swirl liquid flow type bubble generator (modified from Parmar and Majumder, 2013)
....................................................................................................................................................... 22
Figure 2.9 Schematic of DGF system (modified from Behin and Bahrami, 2012) ...................... 30
Figure 2.10 Different flow schemes of DGF system, (a) full-flow pressurization, (b) split-flow
pressurization, and (c) recycled flow pressurization (modified from Radzi 2016) ...................... 32
Figure 2.11 Schematic of IGF system (modified from Zasadowski et al., 2014) ......................... 33
Figure 2.12 Schematic of EF system (modified from Palaniandy et al., 2017) ............................ 35
Figure 2.13 Schematic diagram of two different contact modes between oil droplet and gaseous
bubbles (modified from Zhang et al., 2016) ................................................................................. 40
Figure 2.14 The effect of pH on oil separation efficiency using MBs gas flotation..................... 42
Figure 2.15 The effect of flotation time on oil separation efficiency ........................................... 46

viii

Chapter 3
Figure 3.1 Cumulative mass loss of CHCO at different times ..................................................... 50
Figure 3.2 Laboratory MBs and NBs flotation setup (a) and appearance of MBs in test water (b)
....................................................................................................................................................... 52

Chapter 4
Figure 4.1 Particle size distribution of NBs .................................................................................. 57
Figure 4.2 Predicted effects of experimental factors on oil separation efficiency, (a) flotation
time: 20 min, temperature of inlet wastewater: 21 °C; (b) initial oil concentration: 400 mg/L,
temperature of inlet wastewater: 21 °C; (c) initial oil concentration: 400 mg/L, flotation time: 20
min ................................................................................................................................................ 62
Figure 4.3 Effect of flotation time on oil separation efficiency .................................................... 64
Figure 4.4 3D response surface graph showing the interaction effects of experimental factors on
oil separation efficiency at (a) temperature of inlet wastewater = 21°C; (b) initial oil
concentration = 400 mg/L; (c) flotation time = 20 min ................................................................ 66
Figure 4.5 Comparison of oil separation efficiency between gravity separation and gas flotation
....................................................................................................................................................... 68
Figure 4.6 Microscopic images and corresponding oil droplet size distribution plots of the
generated oily wastewater (a) with fresh CHCO, (b) with weathered CHCO .............................. 69
Figure 4.7 Effect of CHCO condition on oil separation efficiency .............................................. 70

ix

Glossary
ANOVA

Analysis of variance

CHCO

Conventional heavy crude oil

CCD

Central composite design

DAF

Dissolved air flotation

DGF

Dissolved gas flotation

DI

Deionized

DLS

Dynamic Light Scattering

EF

Electrolytic flotation

GHG

Greenhouse gases

IAF

Induced air flotation

IFT

Interfacial tension

IGF

Induced gas flotation

LD

Laser diffraction

MPRI

Multi-Partner Oil Spill Research Initiative

MBs

Microbubbles

NBs

Nanobubbles

NTA

Nanoparticle tracking analysis

PVC

Polyvinyl chloride

RSM

Response surface methodology

R2

Coefficient of determination

SDS

Sodium dodecyl sulfate

USEPA

United States Environmental Protection Agency

x

UPW

Ultrapure water

ZP

Zeta potential

WCSB

Western Canada Sedimentary Basin

xi

Acknowledgement
This thesis reflects the final part of my master’s study at the University of Northern British
Columbia. First of all, I am deeply grateful to my supervisor, Dr. Jianbing Li, for his insightful
thoughts, valuable suggestions, encouragement and support throughout my research and study. He
gave me great opportunities to work on different projects and present my research in conferences,
which helped strengthen my research skills and improve my confidence.
I would like to express my sincere gratitude to Dr. Min Zhao and Dr. Ronald W. Thring
for serving as my co-supervisor and supervisory committee member. I greatly appreciate their
quick response, insightful comments, and great discussions. My gratitude also goes to Dr. Guangji
Hu, who served as a postdoctoral fellow in our research group, for his valuable feedback on my
papers. I would also like to thank Conan Ma for his help with lab materials supply and sample
delivery at Chemstore.
Moreover, I would like to extend my sincere thanks to people in my research group for
their kind help and valuable discussions; they are Dixuan Li, Cheng Lu, Narayan Koirala, Ashkan
Hosseinipooya, and Nahid Hassanshahi. I would also like to thank all my lovely friends that I have
met in Canada and all my friends back in China for always being thoughtful and supportive.
Finally, I would like to dedicate this work to my family for their unconditional love and
support. Without their understanding and encouragement in the past three years, it would be
impossible for me to complete my master’s degree. Specially thanks go to my mother, who takes
care of all the family members and works hard to provide a better life for the family. She is the
one who has taught me to thrive through hard times. And my father, who has showed me to
embrace the beauty of life and stay positive no matter what, for which I will always be thankful.

xii

Chapter 1 Introduction
Large amounts of oily wastewater are generated from various activities, including oil and
gas production (Pendashteh et al., 2012), metal manufacturing (An et al., 2017), food processing
(Zhao et al., 2021), petroleum refining processes (Hoseini et al., 2015), and marine oil spill
response (Liang and Esmaeili, 2021). Offshore oil spills have been of significant concern due to
their negative and long-term environmental impacts (Li et al., 2016c). When an oil spill occurs in
the ocean, it undergoes various chemical, physical, and biological processes such as spreading,
evaporation, dissolution, photo-oxidation, and biodegradation which collectively turn the fresh oil
into weathered oil (Liu et al., 2012; Bacosa et al., 2021). The process of weathering extends the
lifespan of oil in the marine environment, making its negative impacts more persistent and harmful
(Mishra and Kumar, 2015). When oil is spilled on the marine water surface, with the presence of
wind, waves, and currents in the ocean, adequate agitation is created on the spilled oil that leads
to mixing with the underlying water and reaches the shorelines, causing damage to both aquatic
and terrestrial ecosystems (Chen et al., 2021).
Different technologies have been developed to separate oil from oily wastewater, including
centrifugation (Issaka et al., 2015), ultrafiltration (Kumar et al., 2017), bioremediation (Sun et al.,
2019), microwave irradiation (Lemos et al., 2010), and chemical demulsification (Kang et al.,
2018). These technologies have different advantages and limitations. For example, centrifugation
and microwave irradiation are associated with high energy consumption (Yau et al., 2017). On the
other hand, membrane fouling can lead to an increased cost of ultrafiltration, and the periodic
cleaning of the membrane is necessary (Shi et al., 2014). The screening of effective chemicals for
separating different types of oil is time-consuming (Kang et al., 2018). Also, the use of chemicals
is hazardous to human health and the environment (Esmaeili et al., 2021). Although
1

bioremediation is considered environmentally friendly and sustainable, it is a very slow treatment
process and is sensitive to environmental conditions (Zolfaghari et al., 2016). Therefore, there is a
great need to explore other oily wastewater treatment technologies that are effective,
environmentally friendly, and scalable.
Flotation has been extensively used in the separation of oils from polluted water due to its
high separation efficiency and throughput, low operational cost, less sludge production, and easy
operation (da Silva et al., 2015; Cai et al., 2017; Rocha e Silva et al., 2018). It is a physical
separation process based on the attachment of oil droplets to gas bubbles to increase the buoyant
force of oil droplets by forming oil-bubble agglomerates, which significantly accelerates oil
floating to the surface of the water (Saththasivam et al., 2016; Chakibi et al., 2018). Several studies
have been conducted to investigate oily wastewater treatment using gas flotation technology. For
example, Tansel and Pascual (2011) used dissolved air flotation (DAF) to treat fuel oilcontaminated pond water with an initial oil concentration of 1500 mg/L, and they achieved 87%
petroleum hydrocarbon separation after 30 min of batch operation. Eftekhardadkhah et al. (2015)
conducted laboratory-scale induced gas flotation (IGF) experiments to separate three types of
crude oil emulsions, and they observed the highest oil separation efficiency for the heaviest crude
oil, which reached 98% separation after 10 min of flotation. Rajak et al. (2015) investigated the
application of air flotation to the separation of emulsified light crude oil and observed higher
separation efficiency at higher salinity and longer flotation time. However, so far limited studies
have been reported on the application of microbubbles (MBs) and nanobubbles (NBs) gas flotation
technology for marine oil spill response operation. In addition, the in-depth effects of influential
factors have not been well studied. Thus, a comprehensive study of the application of MBs and
NBs gas flotation to oily wastewater is necessary.

2

In this study, the separation of conventional heavy crude oil (CHCO) droplets in saline
water with gas flotation by MBs and NBs is examined. Three experimental factors, including initial
oil concentration, flotation time, and temperature of inlet wastewater, are investigated on the oil
separation efficiency using response surface methodology (RSM). The main objective of this study
was to evaluate the effects of different parameters on oil separation efficiency and the interactions
between the considered variables, as well as to find optimum treatment conditions and to predict
the oil separation efficiency within the investigated parameter range. The results would provide
valuable information on the development of reliable and effective technology to separate oil from
oily wastewater in a sustainable manner and lay a solid foundation for scaling up this technology
for field application.

3

Chapter 2 Literature Review*
*This review has been published as: Shen, W., Mukherjee, D., Koirala, N., Hu, G., Lee, K., Zhao,
M., & Li, J. (2022). Microbubble and nanobubble-based gas flotation for oily wastewater
treatment: A review. Environmental Reviews, (ja).

2.1 Introduction
Oily wastewater is generated from oil spill incidents and many other sources, such as food
processing, oil refining, textile and leather industries, metal rolling and finishing, paper deinking,
and petrochemical industries (Hassan et al., 2015; Huang et al., 2018). Different types of oil and
oil components can be found in wastewater, such as animal grease, crude oil, lubricating oil, and
cutting oil, depending on the source of wastewater generation (Putatunda et al., 2019). Marine oil
spills are regarded as a major threat to the environment. The growing maritime transportation of
petroleum products has led to increased risks of oil spills from ships and other oil handling facilities
(Transports Canada, 2017). Once an oil spill has occurred, proper spill response must be taken to
curtail and separate the spilled oil from the marine for impact minimization. However, marine oil
spill response would generate a large volume of oily wastewater that needs effective treatment.
The ineffective treatment and discharge of oily wastewater would pose secondary adverse impacts
to the environment. For example, insufficiently treated oily wastewater can cause air pollution
because of the evaporation of light petroleum hydrocarbons and jeopardize the aquatic
environment because of the presence of toxic substances (Jamaly, 2015; Ismail et al., 2020). Thus,
stringent discharge regulations must be applied to minimize the harmful effects. The approved
daily average discharge limit for oil and grease in Canada is 30 mg/L (Al-Dulaimi and Al-Yaqoobi,
2021). According to the United States Environmental Protection Agency (USEPA), the oil and
4

grease discharge limit is 29 mg/L for monthly average with a maximum daily discharge of 42 mg/L
(Souza et al., 2020).
Oil spills in the Arctic Ocean are of particular concern since the oil spill response in this
region is much more challenging than temperate regions. The specific challenges are mainly due
to the unique harsh environments in the Arctic, such as lack of sunlight in winter, strong wind,
cold temperature, remoteness, and the presence of sea ice (Nordam et al., 2019). On the other hand,
global climate change has already altered the ice cap coverage in the Arctic and led to increased
opportunities for marine activities (e.g., oil exploration and transport, tourism), which would
potentially increase the risk of oil spills (Crépin et al., 2017; Wilkinson et al., 2017). In addition,
the drastic reduction of ice coverage in the Arctic may result in faster spread of spilled oil and
higher risks of shoreline exposure when oil spills occur (Nordam et al., 2017). Considering the
lack of sufficient infrastructure and remoteness in the Arctic, it is highly desirable to have onboard systems in response vessels for treatment of oily wastewater generated from oil spill
response operations.
The oil can exist in wastewater in three different forms, as free oil (the diameter of oil
droplets > 150 μm), dispersed oil (20–150 μm), and emulsified oil (< 20 μm) (Yu et al., 2020).
The most challenging part for treating oily wastewater is the presence of stable oil-water emulsion.
There are various oil-water separation technologies available for breaking oil-water emulsions
(i.e., demulsification), including chemical treatment, biological process, and membrane filtration.
However, these demulsification methods are associated with different drawbacks, such as
secondary contamination caused by chemical reagents, slow biological treatment process, and high
operational costs due to short membrane life (Oliveira et al., 2017). In terms of marine oil spill
response, the effective separation of oil from oil-water emulsion is of critical importance for

5

greatly enhancing the response capacity of response vessels that have limited storage space.
However, the lack of technologies for effective oil-water separation and at-sea disposal of decanted
water becomes a bottleneck in response operations in many countries such as Canada, USA and
China (Mohammadiun et al., 2021). Therefore, it is necessary to explore new technologies that
could be more efficient in demulsification.
In recent years, NBs and MBs-based gas flotation technology has been used for wastewater
treatment such as surface water purification (Kyzas and Matis, 2018) and groundwater remediation
(Xia and Hu, 2016). Gas flotation-based technologies may have great potential in treating oily
wastewater due to the compact footprint of equipment required, high separation efficiency, and
limited sludge production (Yu et al., 2017). Unlike some other conventional wastewater treatment
methods (e.g., biological processes), gas flotation-based technology is more sustainable and
environmentally friendly without resulting in direct greenhouse gases (GHG) emissions or
significant secondary pollution (Campos et al., 2016). MBs and NBs can adsorb oil droplets to
form light flocs that can float to the wastewater surface due to decrease in the overall density (Bai
et al., 2011). The separation of oil droplets and water can be achieved by skimming off the floating
oil flocs on the liquid surface (Saththasivam et al., 2016). Based on the recent advancements in the
gas flotation-based wastewater treatment, there is a need for a comprehensive review of MBs and
NBs-based gas flotation technologies to help better understand the mechanisms behind the oilwater separation process and its potential for use in new applications (e.g., decanting of oily
wastewater generated from marine oil spill response). The main objectives of this review are (a)
to introduce the mechanisms and properties of MBs and NBs as well as their generation methods,
(b) to summarize the types of MBs and NBs-based gas flotation system and their design

6

considerations, and (c) to discuss the influential factors affecting oil-water separation as well as
future development needs in MBs and NBs-based gas flotation.

2.2 Properties of MBs and NBs
A number of fundamental bubble properties may influence the use and effectiveness of
MBs and NBs in gas flotation. These include bubble size, specific surface area, zeta potential (ZP),
rising velocity, internal pressure, and bubble stability.
2.2.1 Bubble size
2.2.1.1 Size definition
There are different definitions of MBs and NBs. For example, the diameter of MBs was
defined to be less than 50 μm by Kobayashi et al. (2011). According to Agarwal et al. (2011), the
size of MBs is in the range of 10 to 50 μm in diameter. However, Pérez-Garibay et al. (2012)
categorized MBs with a diameter of 30–100 μm. Ross et al. (2019) suggested that the size of MBs
is typically 30–70 μm in diameter. Although a consensus on the size of MBs has not been reached,
it is generally accepted that MBs fall within a size range of 1–100 μm.
As for NBs, Agarwal et al. (2011) categorized NBs as those with a diameter of less than
200 nm. Attard (2016) classified NBs as those within a range of 10 to 500 nm. Rameshkumara et
al. (2019) mentioned that NBs are gaseous cavities having the size of 100–800 nm in diameter. In
recent studies, Yasuda et al. (2019) stated that NBs have a diameter of less than 1 μm, and Kim et
al. (2020) classified NBs as ultrafine bubbles with a diameter of 100 nm–1 μm. Overall, the size
of NBs is in the order of nanometers as shown in Figure 2.1.

7

Figure 2.1 Summarized diameter range of MBs and NBs

2.2.1.2 Size measurement
Different techniques have been developed and used to measure the bubble size and its
distribution. Li et al. (2016b) used a microscope equiped with an image processing software called
Image-Pro Plus to determine the distribution of micro- and macro-bubbles in the range of 10–150
μm. ImageJ TM is also a widely used software to process images obtained from microscope
observation (Gonzalez-Galvis and Narbaitz, 2020). A microscopic photo including a MB of about
12 μm (upper right) and NBs with diameters of 100–500 nm is shown in Figure 2.2. Although
visible images could be generated, it was a tedious task as the field of view under a microscope is
limited (Temesgen et al., 2017). Meegoda et al. (2018) determined the distribution of nano- and
micro-bubbles over a size range of 0.3 nm to 10 μm using a Dynamic Light Scattering (DLS)
instrument (Zetasizer Nano ZS, Malvern Instruments Ltd.). da Cruz et al. (2016) used laser
diffraction (LD) method (Mastersizer 2000SM device, Malvern Instruments Ltd.) to determine the
average bubble size generated in EF system. Compared with LD, DLS can be used to detect
samples with much smaller particle sizes (Badger, 2019). An acoustic bubble spectrometer was
applied by Rehman et al. (2015) to measure the bubble size distribution over a size range of 80–
450 μm. According to Desai et al. (2019), acoustic spectrometry is able to detect smaller bubbles
in comparison to LD and optical techniques.
8

Figure 2.2 Photo of MBs and NBs from a phase-contrast microscope (provided by K. Takahashi,
personal communication, 2022)

2.2.1.3 Bubble size impact factor
Many studies have been conducted to investigate the effects of different factors on bubble
size. According to Wu et al. (2012), temperature has a significant effect on bubble size because it
can greatly affect the coalescence of bubbles. Higher temperatures led to the formation of larger
bubbles. Gas flow rate and gas pressure are two other important factors affecting bubble size
(Meegoda et al., 2018). Nazari et al. (2020b) investigated the effect of air flow rate on the size of
bubbles generated from a Venturi tube, and they obtained smaller bubbles when a high air flow
rate (increasing dissolved gas) was applied. Temesgen et al. (2017) concluded that smaller bubbles
would be produced under higher pressure due to increased air density. Calgaroto et al. (2014)
found that to some extent bubble size is dependent on the magnitude of ZP and the maximum
bubble size was achieved at the isoelectric point. Table 2.1 lists the aforementioned impact factors,
operating conditions, and the related bubble size measurement methods.
9

0.1
0.18
0.25
0.33
0.4
pH
2
4
6
8
10
Note: NA = not available

Gas flow rate
(L/min)

Gas pressure
(kPa)

629 nm
482 nm
390 nm
300 nm
243 nm
130 nm
570 nm
715 nm
420 nm
300 nm

200 nm
230 nm
265 nm
310 nm
360 nm
66.5 μm
54.4 μm
47.7 μm

Solution
temperature
(°C)

20
25
30
35
40
482
551
620

Bubble size

Factors

The size measurements were
performed with tap water and
conducted under room
temperature = 20 ± 2 °C
Liquid temperature = 32 °C,
pH = 8, gas pressure = 325 kPa

Gas pressure = 455 kPa,
bubbles were produced in 10-2
mol/L NaCl solution

Zetasizer Nano ZS –
Zen3600 (Malvern
Instruments)

NA

Operating conditions

High-speed highresolution flare
camera + ImageJ
software
Mastersizer 2000
(Malvern
Instruments)

Mastersizer 2000
(Malvern
Instruments)

Size measurement

Table 2.1 Different factors affecting bubble size

Calgaroto et
al., 2014

Nazari et al.,
2020b

10

GonzalezGalvis and
Narbaitz, 2020

Ahmadi and
Khodadadi
Darban, 2013

Reference

2.2.2 Specific surface area
The specific surface area of MBs and NBs are larger than that of the conventional macrobubbles and it can be calculated by the following equations (Li et al., 2013):
=4

(2.1)

= 4⁄3

(2.2)

⁄ = 3⁄

(2.3)

Where S is the surface area (m2), V is the volume (m3), and r is the radius of the bubble
(m). From the above equations, it can be found that the specific surface area (surface area per unit
volume) will be larger for bubbles with a smaller radius. For example, the specific surface area of
NBs with radius of 10 nm is 1000 times larger than that of MBs with radius of 10 μm and is 10,000
times larger than that of macro-bubbles with radius of 1 mm. According to Swart et al. (2020), the
specific surface area is in the order of 105 m-1. Therefore, the large surface area of MBs and NBs
can sequester more unwanted particles in the solution than macro-bubbles for improved adsorption
performance.
Calgaroto et al. (2015) investigated the flotation of fine quartz particles (mean diameter of
32 μm) with and without NBs (200–720 nm), and they found that the recovery of quartz particles
was increased from 44% to 64% with the assistance of NBs. Similarly, Nazari and Hassanzadeh
(2020a) observed around 27% improvement in quartz particles separation in the presence of NBs
(mean diameter of 247 nm). Rosa and Rubio (2018) successfully increased the separation of quartz
particles (mean diameter of 50 μm) by 23% with NBs (150–200 nm). Etchepare et al. (2017a)
improved the oil separation efficiency from 72.6% with MBs (30–40 μm) alone to 83.9% with
MBs and NBs (150–350 nm). Figure 2.3 shows that the contaminant separation efficiency
increases with the addition of NBs in the gas flotation system.

11

Figure 2.3 Contaminant separation efficiency with and without NBs

2.2.3 Zeta potential
ZP is the electrical potential of any particles (e.g., gas bubbles or oil droplets) in suspension
which shows repulsive or attractive forces between themselves (Gurung et al., 2016). It is formed
at the particle-liquid interface. The stability of the colloidal dispersions can be represented by the
magnitude of ZP. A higher value of absolute ZP indicates that the dispersion or solution is more
stable because it has stronger resistance to agglomeration (Shangguan et al., 2018). Generally,
bubbles are negatively charged in distilled water because of the adsorption of hydroxyl ions (OH ) at the gas-liquid interface (Bui et al., 2019).
Table 2.2 summarizes some studies investigating the effects of various factors (gas type,
gas pressure, solution pH, and the addition of surfactant) on ZP. For example, ZP is affected by
the type of gas used to form bubbles. High ZP of MBs and NBs can be achieved using oxygen and
nitrogen as the injection gas compared with other types of injection gas including carbon dioxide,
12

xenon, and air (Ushikubo et al., 2010a). Similarly, Meegoda et al. (2018) used ozone, oxygen, air
and nitrogen to generate NBs in deionized water (DI) and the highest ZP was observed in ozone
bubbles followed by oxygen, air, and nitrogen. They concluded that the difference in ZP is caused
by different gas diffusion rates and gas solubility, which impact the ability of OH- ions formation
at the bubble surface. Jia et al. (2013) investigated the effects of surfactant type and concentration
on ZP of air bubbles in aqueous solution. They concluded that addition of cationic surfactant
reduced the negative charge of ZP and even changed the negative charge into positive, however,
the addition of anionic surfactant helped make the ZP more negative.
Table 2.2 Different factors affecting zeta potential
Factors
Gas type

Pressure (kPa)

pH

Anionic surfactant
concentration (ppm)

Nitrogen
Air
Oxygen
Ozone
138
207
275
345
414
5
7
9
11
50
100
150
200

ZP (mV)
-19.8
-21.3
-22.4
-27.0
-0.3
-3.8
-10.0
-15.2
-22.5
-18.2
-21.8
-28.1
-30.5
-37.8
-42.0
-52.2
-64.1

Reference
Meegoda et al., 2018

Ahmed et al., 2018

Kim and Kwak, 2017

Jia et al., 2013

Note: ZP = zeta potential

13

2.2.4 Rising velocity
The rising velocity (Vr) of MBs and NBs can be expressed by the equation of Stoke’s Law,
which states that the rising speed of bubbles is directly proportional to bubble size and inversely
proportional to the viscosity of surrounding liquid (Zhang et al., 2019):
=

(

)

(2.4)

Where d is the bubble diameter (m), g is the gravitational acceleration constant (9.8 m/s2),
μl is the viscosity of the surrounding liquid (Pa·s), ρg is the density of gas bubble (kg/m3) and ρl is
the density of the surrounding liquid (kg/m3).
This equation is valid only for sphere shape and same size of bubbles in laminar flow.
However, it is impossible to achieve all these conditions in a real-world situation (Atarah, 2011;
Saththasivam et al., 2016). The rising velocity is dependent on the physical properties of the liquids
and the diameter of bubbles. Because of their small diameter, MBs and NBs tend to have a slow
rising velocity, enabling much longer stagnation under water surface compared with other
conventional large bubbles (Tsuge, 2014; Shangguan et al., 2018). Thus, MBs and NBs will spend
more time under water which leads to higher rate of collision; hence, more opportunities to adsorb
oil particles during the treatment process. Bubble rising velocity is commonly measured using
high-speed photography combined with digital image analysis technique (Liu et al., 2016). Swart
et al. (2020) listed that when the diameter of MBs is in the range of 10–120 μm, the rising velocity
is from 1 to 12 mm/s. As for NBs, the rising velocity of NBs with a diameter of 100 nm is 2.7 nm/s
according to the calculation by Alheshibri et al. (2016).
The low rising velocity means that NBs alone are not effective for flotation (Gurung et al.,
2016; Calgaroto et al., 2015). According to Azevedo et al. (2016), the rising velocity of MBs in
DI water was enhanced from 0.062 cm/s to 0.081 cm/s with the help of NBs. They concluded that
14

the collision and attachment of contaminant particles to MBs were facilitated by NBs. In addition,
Calgaroto et al. (2015) indicated that the most important mechanisms of NBs aiding the flotation
with MBs are: the contact angle between contaminant particles and MBs was enhanced, and the
aggregation of particles was induced. It was reported that the combination of MBs and NBs has a
high potential in separating pollutants from wastewater (Kyzas et al. 2021).

2.2.5 Internal pressure
The relationship between the size of bubble and its internal pressure can be illustrated by
the Young-Laplace equation (Tsuge, 2014; Faghri and Zhang, 2020):
∆ =4 ⁄

(2.5)

Where ΔP is the pressure difference between the internal gaseous bubble and the
surrounding bulk liquid (Pa), σ is the surface tension (N/m) of the liquid and d is the bubble
diameter (m).
The gas pressure inside the bubble would increase when the bubble size decreases in the
aqueous solution (Agarwal et al., 2011). High internal pressure is a driving force that leads to gas
diffusion from the high partial pressure area inside of the bubble to the low partial pressure area in
the surrounding liquid. Consequently, the size of MBs will be reduced due to the internal gas
reduction and the internal pressure will become higher, which causes further bubble shrinkage
until the MBs disappear (Xu et al., 2008). However, it was claimed that when the diameter of MBs
is beyond 50 μm, the bubbles will swell and rise to the water surface and then burst; otherwise,
they will shrink under water (Meegoda et al., 2018). In the case of NBs, their size under water
surface remains almost unchanged once they are produced, which means NBs are highly resistant
to gas diffusion as shown in Figure 2.4. According to Ohgaki et al. (2010), the low gas diffusivity

15

of NBs is based on the strong hydrogen bonds on the surface that increase the surface tension of
NBs (e.g., 2 times higher than the normal value), restraining the internal gases from permeating
through the interfacial film of NBs. The low buoyancy of NBs prevents them from rising to the
water surface. Instead, they are subjected to Brownian motion resulting in random movement
under water (Farid et al. 2022). The detailed movements of MBs and NBs in the liquid and their
interactions need to be further investigated.

Figure 2.4 Schematic diagram showing the behavior of MBs and NBs under water (modified
from Agarwal et al. 2011)

2.2.6 Stability of NBs
The characteristic distinguishing NBs from other types of bubbles is that NBs can last for
a long period of time under aqueous solution without bursting out (Rameshkumara et al., 2019).
Etchepare et al. (2017b) used a centrifugal multiphase pump to generate air NBs and summarized
that the NBs can be stable in the aqueous solution for more than two months with almost
unchanged bubble concentration and mean size (Table 2.3). Oh et al. (2015) investigated the
16

stability of hydrogen NBs in gasoline fuel and concluded that there was no notable change in the
concentration and mean diameter of NBs for 121 days. Michailidi et al. (2020) reported that both
air and oxygen filled NBs can remain stable for 3 months or even longer. NBs are remarkably
stable due to the following reasons: (a) the formation of micrometer-sized clusters helps to prevent
the diffusion of gas inside of the bubbles (Ulatowski et al., 2019); (b) the electrostatic repulsive
forces generated by the strong absolute ZP between neighboring NBs could stop bubbles from
aggregation and coalescence (Ushikubo et al., 2010b); (c) the gas outflux and the gas influx are at
equilibrium when the NBs exist in a saturated solution (Azevedo et al., 2016); (d) the high
resistance of gas diffusion at the bubble interface due to its different structure (e.g., strong
hydrogen bonds) also contributes to the stability of NBs (Wang et al., 2013).

17

NB concentration

Mean diameter
(nm)
88.50 ± 9.59
159.00 ± 31.91
150-200

NB concentration

(particles/mL)

(3.47 ± 0.39) × 108

(11.25 ± 2.77) × 108

6.0 × 108

5.1× 108

(10.87 ± 0.64) × 108

(2.94 ± 0.16) × 108

(particles/mL)

Final stage

Initial stage

300

146.80 ± 8.11

110.00 ± 4.58

(nm)

Mean diameter

60

121

1

(day)

Duration

18

Etchepare et al., 2017b

Oh et al., 2015

Oh and Kim, 2017

Reference

Table 2.3 The change of NB concentration and mean diameter in a specific period of time

2.3 Generation of MBs and NBs
As shown in Figure 2.5, several methods can be used to generate NBs and MBs. The
strengths and weaknesses of some widely used bubble generation methods are listed in Table 2.4.

Pressurized
dissolution

Electrolysis

Venturi

Generation
method

Ultrasonic
irradiation

Swirl flow

Porous
membrane

Figure 2.5 Bubble generation methods

2.3.1 Pressurized dissolution type
For bubble generation by pressurized dissolution, the gas will be dissolved in water under
high pressure (typically at 3–4 atm) within a saturator vessel to create a supersaturated condition
(Agarwal et al., 2011; Parmar and Majumder, 2013). When this supersaturated water is introduced
into a tank of water through a nozzle under atmospheric pressure (Figure 2.6), MBs are rapidly
formed as the gas escapes (Arumugam, 2015). Maeda et al. (2015) summarized that by increasing

19

the dissolved gas concentration in the liquid phase, the mean diameter and number density of
bubbles will also be increased. Norarat et al. (2019) used a bubble generator based on the
pressurized dissolution method and investigated the effect of its operation time on bubble
concentration. They found that the increased operation time led to higher bubble concentration and
the bubble size distribution shifted to smaller sizes under longer operation times.

Figure 2.6 Pressurized dissolution type bubble generator (modified from Arumugam, 2015)

2.3.2 Venturi type
Venturi based bubble generation involves three major components: a converging inlet, a
throat, and a diverging outflow as shown in Figure 2.7 (Zhao et al., 2017; Huang et al., 2020). It
includes the injection of gas into the venturi tube along with water through the converging inlet
(Parmar and Majumder, 2013) or at the throat section (Li et al., 2017; Huang et al., 2020). Zhao et
al. (2017) investigated the bubble generation mechanisms in a venturi type bubble generator and
they found that there was a pressure decrease in the throat region which leads to the increasing
20

bubble velocity. After that the air bubbles are rapidly decelerated when entering the diverging
outflow section due to the pressure recovery. The relative flow velocity difference between liquid
phase and air bubbles generates a shock wave with high shear forces that cause bubble deformation
and the collapse of large bubbles into a large number of tiny bubbles (Zhao et al., 2017; Tsuge,
2014). MBs with diameter less than 100 μm can be formed by this method (Agarwal et al., 2011).
Li et al. (2017) showed that the divergent angle is a significant parameter influencing the
performance of venturi type bubble generator. The produced bubble size decreases with an
increase in divergent angle. Huang et al. (2020) indicated that liquid flow rate is the main parameter
controlling the bubble size and distribution. A more uniform bubble size distribution can be
obtained by increasing the liquid flow rate.

Figure 2.7 Venturi type bubbe generator (modified from Zhao et al., 2017; Li et al., 2017)

21

2.3.3 Swirl flow type
Bubble generation by swirl flow involves the pumping of pressurized water into a
cylindrical container to form a spiral flow pattern as shown in Figure 2.8 (Parmar and Majumder
2013). The rotary liquid flow could lead to low pressure in the central axis part that draws in gas
from the bottom of the cylindrical container into the water vortex (Agarwal et al., 2011;
Arumugam, 2015; Ulatowski and Sobieszuk, 2020). Tiny bubbles are generated in the top part of
the container by high shearing force in the process of vortex breakdown (Parmar and Majumder,
2013). Alam et al. (2018) used a computational fluid dynamic simulation method to study the
performance of a swirl flow bubble generator that produced MBs with an average diameter of 50
μm. They found that the number of MBs produced is dependent on the air mass flow rate, and the
lower mass flow rates produced a higher number of MBs.

Figure 2.8 Swirl liquid flow type bubble generator (modified from Parmar and Majumder, 2013)
22

2.3.4 Porous membrane type
In porous membrane bubble generation, compressed gas is introduced from the outside of
the membrane through its pores. A liquid phase flows inside the membrane and generates shear
force to form bubbles on the membrane surface (Khirani et al., 2012; Ulatowski and Sobieszuk,
2020). Xie et al. (2021) designed a MBs generation system using a commercial porous ceramic
membrane. In their experiments, the liquid phase was pumped into the inner of membrane which
created shear flow to disperse nitrogen to MBs. They investigated the effect of liquid flow velocity
on MBs size and found that the increase of liquid flow velocity led to higher wall shear force in
the membrane which accordingly decreased the MBs size. Also, they concluded that membrane
pore size is an important factor controlling MBs size, while smaller pore diameter results in smaller
bubble generation (Xie et al., 2021). Khirani et al. (2012) investigated MBs formation through
tubular ceramic membranes using different continuous phases (water / heptane), different
dispersed phase (air / nitrogen) and different membrane materials (alumina oxides / zirconium
oxides). However, they summarized that smaller membrane pore size will lead to bigger bubble
size which is contrary to the conclusion brought up by Xie et al. (2021). Moreover, they indicated
that the use of more hydrophobic membrane surface favors the generation of smaller MBs.

2.3.5 Ultrasonic irridation type
Yasuda et al. (2019) formed NBs in the size range of 90–100 nm diameter by irradiating
ultrasound to ultrapure water. A high density of NBs could be achieved by increasing the ultrasonic
power and irradiation time and decreasing the ultrasonic frequency. Xu et al. (2008) used two types
of surfactants including Sodium dodecyl sulfate (SDS) and L-150A (10% ethanol, 38% sucrose

23

laurate ester and 52% water) for generating MBs by sonication. Based on their results, the use of
1% SDS yielded larger bubble diameter of 46 μm compared to that of 26 μm using 1% L-150A.
Besides, the volumetric bubble concentration was 8.3×106/mL when using SDS as surfactant while
it was 2.5×107/mL when using L-150A. Lee et al. (2020) studied the effect of dissolved gas
concentration on NB generation by ultrasonic irradiation. They used an ultrasonic horn booster at
20 kHz to irradiate the ultrasound for 10 min in three types of DI water namely under-saturated,
saturated, supersaturated. They found that with the increase of the dissolved gas concentration, the
surface tension of DI water decreased, causing a reduction in the concentration of NBs.

2.3.6 Electrolysis type
Oxygen and nitrogen bubbles can be produced by electrolysis at both the anode and cathode
respectively due to redox reactions (Favvas et al., 2021). Lucero et al. (2017) performed
experiments to evaluate the effect of NaCl concentration, current density, and electrode distance
on MBs generation rate. Among all the parameters, current density directly controlled the
generation rate, and higher current density resulted in faster bubble generation. The power
requirement of the electrolysis process was decreased by the addition of NaCl and narrowing the
electrode distance. Ulatowski et al. (2021) also investigated the influence of salt concentration and
electrolysis time on the mean diameter of nitrogen and oxygen bubbles formed by electrolysis. It
was observed that the diameter of bubbles increased with the increase in salt concentration, while
the extension of electrolysis time only affected the hydrogen bubble size, which tended to be
smaller with the increase of electrolysis time. In the process of electrolysis, the mean diameter of
bubbles decreased at first and then reached equilibrium after an hour (Chandran et al., 2015).

24

Ultrasonic method

• Can generate mono-dispersed fine MBs
• Short bubble generation time
• Compact bubble generator with simple
operation

• The generated bubble density is
not high

(Maeda et al., 2015;
Yasuda et al., 2019)

(Wang et al., 2020;
Terasaka et al., 2011)

• Strong shear flow causing
breakage of the product
• Complicated structure

Swirl flow

(Huang et al., 2020;
Kobayashi et al., 2022)

• The generated bubble size differs
from tens of microns to
millimeters (lack uniformity)

• Less maintenance (no internal moving
parts)
• Low power consumption
• Easy to install due to its simple structure
• High efficiency and good reliability
• Highest gas holdup and gas transfer
comparing with other methods

Venturi

Reference
(Maeda et al., 2015;
Tamura et al., 2014)

Weakness
• High energy consumption
• Probability of blockage of air
supply due to circulation of
contaminated water

Strength
• Stable and uniform MBs with high bubble
density can be generated
• Simple system

Methods
Pressurized
dissolution

Table 2.4 Comparison of different bubble generation methods

25

2.4 Gas flotation
There are currently three principal gas flotation technologies, including dissolved gas
flotation (DGF), IGF, and electrolytic flotation (EF). They have been adopted for oily wastewater
treatment, and Table 2.5 lists some application examples. The advantages and limitations of the
three flotation systems in wastewater treatment are listed in Table 2.6.

26

93%

>85%

Macro-bubbles

NA

NA

85%-95%

MBs

89%

95%

MBs and NBs

Macro-bubbles

>99%

Macro-bubbles

DAF

Induced air
flotation
(IAF)

Oil
separation
98%

Bubbles type

Flotation type

Mohammed et al.,
2013

Rattanapan et al.,
2011

Silva et al., 2019

Etchepare et al.,
2017a

Rajak et al., 2015

Reference

Emulsion with 500 mg/L initial oil concentration; aluminum Hoseini et al., 2015
sulfate was used for the coagulation process; flotation time
was 10 min
Three types of stabilized oily wastewater which contain 1
Chawaloesphonsiya
g/L cutting oil, 3 g/L lubricant oil, and 5 g/L palm oil;
et al., 2019
optimum alum dosages:150 mg/L for cutting oil, 400 mg/L

Light crude oil was used to prepare emulsion with different
initial oil concentrations (e.g., 850 ppm, 1130 ppm);
flotation time varied from 10 min to 4 h for different
flotation process
1.6 g/L of medium crude oil emulsion was used to conduct
the experiments; Dismulgan V3377 was used to destabilize
the emulsion before flotation; 5 min of flotation with a
recycle ratio of 25%
Motor oil was used to generate emulsion with a
concentration of 15 g/L; biosurfactant produced from the
bacteria Pseudomonas aeruginosa was used to facilitate the
coalescence of contaminant particles
Wastewater with 7-15 g/L biodiesel; acidification and alum
coagulation were applied before DAF; retention time in the
flotation cell was 7 and 9 min for 20% and 40% recycle
ratio
Oily wastewater with initial oil concentration of 30, 100,
and 800 ppm; optimal flotation time was 20-25 min

Remark

Table 2.5 Application of gas flotation system for treating oily wastewater

27

99%

99%

85%

NA

NA

NA

Note: NA = not available

EF

Synthetic emulsions with 500 mg/L crude oil, 15%
surfactant, and saline water; maximum oil separation
achieved after 35 min; increasing current density and NaCl
concentration increase oil separation efficiency
500 mg/L of emulsified lubricant oil used; aluminum
electrodes preferred than iron electrodes in order to attain a
higher separation efficiency; 99% separation efficiency
achieved in 10 min; separation efficiency increased with
electrode size and the gap between electrodes
Bor oil (a common cutting oil) was used to prepare oily
wastewater; maximum oil separation efficiency was
obtained when the highest voltage (15V) was applied

for lubricant oil, and 800 mg/L for palm oil; 0.1-1 L/min of
air flow rate (optimum 0.3 L/min)

Genç and Goc, 2018

Mohammed and AlGurany, 2010

Hassan et al., 2015

28

• Continuous supply of electricity is
required for bubble generation
• Maintenance and replacement of
anodes on regular basis which may
lead to high cost

• Uniform mixing of gas bubbles
and wastewater can be achieved
• Operating conditions (e.g., gas
production) can be easily
controlled
• Lack of requirement for chemicals
additives

EF

IGF

Disadvantage
• High equipment footprint and
capital cost
• Not suitable for treating wastewater
with high inlet concentration
• Bubble quantity generated is low
due to the limitation on saturation
• High maintenance cost due to wear
and tear of impellers
• If diffusers are used to introduce gas,
they might be clogged leading to less
effectiveness of the system

Advantage
• Low maintenance cost (nonmoving parts)
• Easy to operate
• Widely used technology with huge
market, high maturity, and reliable
performance
• Low retention time resulting in a
compact footprint
• Low capital cost
• High inlet concentration can be
accepted
• No compressor needed (saving the
running cost)

Types of flotation
DGF

Table 2.6 Summary of different types of gas flotation systems

29

Khalek et al., 2019; Kyzas
and Matis, 2016

Ebrahiem et al., 2021;
Piccioli et al., 2020

Reference
Saththasivam et al., 2016;
Ebrahiem et al., 2021

2.4.1 Dissolved gas flotation
DGF is the most commonly used technique for treating industrial wastewater especially
oily wastewater (Kyzas and Matis, 2018). In the DGF process (Figure 2.9), fine gas bubbles are
formed due to the pressure reduction in the pre-saturated aqueous solution when it passes through
needle valves or orifices (Fonseca et al., 2017). The generated bubbles have a size range of 20–
100 μm diameter (Edzwald, 2010; Brasileiro et al., 2020).

Figure 2.9 Schematic of DGF system (modified from Behin and Bahrami, 2012)
In terms of effectiveness, Rattanapan et al. (2011) stated that DGF is effective to separate
liquid or solid particles with low concentrations from aqueous suspension. However, Jaji (2012)
noted that the retention time in DGF can be in the range of 20-60 min which makes it infeasible to
treat wastewater with high feed flow rates. Furthermore, due to the high retention time, DGF
systems are associated with higher equipment footprint and capital costs (Saththasivam et al.,
2016).

30

There are three different liquid flow schemes in the DGF system including full-flow, splitflow, and recycled flow (Figure 2.10). The wastewater stream is entirely pressurized in the
saturator vessel in the full-flow scheme, while it is partially pressurized in the split-flow system.
The recycled flow DGF system is the most widely used scheme for the flotation treatment process.
Only a part (15%–30%) of the treated effluent is pumped into the saturator vessel to be pressurized
and then it is recycled back to the flotation tank (Wang et al., 2010). While air is the most
commonly used gas for the DGF system, a number of other gases have been used (Table 2.7), such
as nitrogen, carbon dioxide, ozone, and methane.

31

Figure 2.10 Different flow schemes of DGF system, (a) full-flow pressurization, (b) split-flow
pressurization, and (c) recycled flow pressurization (modified from Radzi 2016)

Table 2.7 Summary of different gases used in DGF system for wastewater treatment
Gas types

Wastewater

References

Air

Restaurant dishwasher effluent

Wu, 2017

Nitrogen

Produced water

Maelum and Rabe, 2015
32

Carbon dioxide

Livestock wastewater

Kwak and Chae, 2016

Ozone

Cosmetic wastewater

Wiliński et al., 2017

Methane

Oilfield wastewater

Wang et al., 2010

2.4.2 Induced gas flotation
IGF is also called dispersed gas flotation. It involves turbulent hydrodynamic conditions
under which bubbles are generated by mechanical mixing and the dispersion of gas into water
phase streams through high-speed impellers or diffusers as described for swirl liquid flow bubble
generators (Saththasivam et al., 2016; Prakash et al., 2018). IGF systems (Figure 2.11) have been
widely used in treating various types of industrial wastewater from different sources including oil
and gas production, pulp and paper mills, and dairy industry (Chebbi et al., 2018; Zasadowski et
al., 2014; Al-Maliky, 2010).

Figure 2.11 Schematic of IGF system (modified from Zasadowski et al., 2014)
A relatively large amount of gas is required for gas bubble formation in IGF systems to
produce the high concentration of bubbles and their required size (typically in the range of 700–
33

1500 μm diameter) (Wang et al., 2010; Radzi, 2016; Naghdi and Schenk, 2016). Due to its
considerably lower retention time (normally less than 5 min) than that of the DGF system (Piccioli
et al., 2020), the IGF system has a more compact footprint (Wang et al., 2010). While the capital
cost of IGF systems is relatively low, maintenance costs may be high due to wear and tear of
mechanical parts such as impellers (Saththasivam et al., 2016).

2.4.3 Electrolytic flotation
EF is a wastewater treatment process using fine hydrogen and oxygen bubbles which are
generated by electrolytic decomposition of aqueous solutions as illustrated in Figure 2.12 (Eskin
et al., 2015). Oxygen is generated at the anode electrode due to the oxidation of water (Eq. 2.6)
while hydrogen is released as a result of reduction reaction at the cathode (Eq. 2.7). The overall
redox reaction (Eq. 2.8) is also shown below (Mohtashami and Shang, 2019):
At the anode: 2

→4

+

At the cathode: 4

+4

→4

+2

Overall reaction: 2

→

↑ +2

↑

(2.6)

↑ +4
↑

(2.7)
(2.8)

34

Figure 2.12 Schematic of EF system (modified from Palaniandy et al., 2017)
Kyzas and Matis (2016) listed some advantages of EF including: wastewater and gas
bubbles can be well mixed by covering the whole surface area of the flotation cell with electrode
grids. The voltage that is needed for electrolysis is within the range of 5–20 V, which makes it safe
to operate and a large amount of tiny bubbles can be generated with minimal turbulence. According
to Matis and Peleka (2010), coagulation of small particles and liquid droplets occurs without
applying any chemical reagents in the EF cell. Alam (2015) suggested that the operating conditions
of EF can be easily controlled. While the size of gas bubbles in their test system had an average
size of around 20 μm, it was noted that the size and concentration of gas bubbles could be changed
by varying the electrical current density.
There are still some disadvantages and challenges existing in the EF treatment method. The
main drawback is the amount (and cost) of electrical energy required for continuous bubble
formation (Tadesse et al., 2019). Sarkar (2011) noted another major technical issue encountered
by EF that is the control of pH, since hydrogen and hydroxide ions are continuously released into
35

the system. Montes-Atenas et al. (2010) stated that in order to protect the system from overheating
because of charge transfer, a cooling system might be needed. In addition, due to the oxidation
that takes place at the surface of electrodes, the maintenance and replacement of anodes are
regularly required which will increase its total operational cost (Khalek et al., 2019).

2.5 Design parameters for gas flotation
A number of factors need to be taken into consideration in the design of MBs and NBs
based gas flotation systems, including gas dissolution, gas holdup, recycle ratio, interfacial tension
(IFT), and spreading coefficient.
2.5.1 Gas dissolution
Gas dissolution is a critical factor in the design of effective gas flotation systems. When
higher pressure is applied, more gas will be dissolved in the solution which will bring more bubbles
into existence when the pressure is reduced back to atmospheric pressure (Atarah, 2011). As
indicated by Wang et al. (2022c), large bubbles were generated due to low gas dissolution, which
resulted in poor pollutant separation. Haarhoff and Edzwald (2013) reported that liquid salinity
has a significant effect on Henry’s Law constant, that is much higher in saline water than in
freshwater, leading to lower gas solubility in saline water. Fanaie and Khiadani (2020) also showed
that gas solubility decreased with salinity increase. Moreover, increasing temperature would
increase the Henry’s Law constant and thus decrease gas solubility (Dassey and Theegala, 2011).

36

2.5.2 Gas holdup
In an oil-gas-water system, gas holdup can be represented by the volumetric proportion of
the gas phase within the total oil-water emulsion of the flotation unit (Prakash et al., 2018). Gas
holdup can be calculated as follows (Kumar et al., 2012):
=

∆

∆
∆

(2.9)

Where ε represents gas holdup, ΔP1 is the pressure difference between two points (lower
and higher ends) of the column after bubble generation (Pa), and ΔP0 is the corresponding
hydrostatic pressure difference between these two points before bubble generation (Pa).
The contact and attachment opportunities between oil droplets and gas bubbles will be
increased when the gas holdup increases (NETL 2017). As stated by Ran et al. (2013), higher gas
holdup in the flotation system led to better oil separation efficiency. Xia et al. (2011) investigated
gas holdup in a cyclone-static flotation column and found that gas holdup is higher in the top and
central part of the column and is lower at the column bottom and in the areas near the column wall.
Etchepare et al. (2017b) reported that the gas holdup is related to the operating pressure which
dissolves air into the water in a pressure tank. In their experiments, when the operating pressure
was in the range of 4 to 5 bars, the highest gas holdup value of 6.8% was achieved along with the
highest concentration of NBs. Rollbusch et al. (2015) studied the relationship between gas holdup
and pressure using nitrogen and DI water, and they found that gas holdup increased with the
increase of pressure and noted that higher pressure caused increased bubble breakage which
resulted in smaller bubbles. In terms of temperature effects, Pérez-Garibay et al. (2012) reported a
reduction in gas holdup with a temperature increase from 10 to 30 °C.

37

2.5.3 Recycle ratio
In DGF system, the recycle ratio is the percentage of treated wastewater that is introduced
back into the saturator vessel where it is pressurized and recycled to the flotation cell (Atarah,
2011). Fanaie et al. (2019) indicated that recycle ratio is a significant design parameter that will
influence the gas concentration in the flotation system which directly impacts the overall
performance of the treatment process. Li et al. (2007) stated that clarified effluent recycling can
reduce the use of clean water in the saturator vessel and reduce the overall volume of chemical
reagents added to the flotation process and their effectiveness. Wang et al. (2010) suggested that
the design range of recycle ratio can vary from 10–60% while Atarah (2011) suggested that the
typical recycle ratio is in the range of 15–50% for different wastewater treatment process. Li et al.
(2007) concluded that the increase of recycle ratio leads to better oil separation efficiency of
flotation for oily wastewater treatment and the recycle ratio should be controlled in the range of
20–30%.

2.5.4 Interfacial tension
IFT is a predominant factor that governs the system stability by controlling gas bubble and
oil droplet attachment (Posocco et al., 2016; Saththasivam et al., 2016). As indicated by Moeini et
al. (2014), IFT represents the surface free energy across the interface which has a force to hold the
surface of two different phases (e.g., oil, water, or gas) together. In the process of separating oil
from oil-water emulsion, it is necessary to lower IFT between oil and water phases to facilitate the
coalescence of oil droplets to enhance oil separation efficiency.

38

2.5.5 Spreading coefficient
In the gaseous bubble flotation treatment process for separating oil from oil-water
emulsion, the oil spreading coefficient can be expressed as (Rawlins and Ly, 2012):
=

−

−

(2.10)

Where γwg, γow and γog are water-gas, oil-water, and oil-gas IFT (N/m), respectively.
Spreading coefficient is an important factor regarding the contact of oil droplets with gas
bubbles. As illustrated in Figure 2.13, when the IFT at the water-gas interface is stronger than the
sum of the IFTs at the oil-water interface and oil-gas interface, the value of So will be positive and
gas bubbles will be completely surrounded by oil droplets. Otherwise, when So is negative, oil
droplets can only attach to gas bubbles at some contact points instead of forming continuous layers
over bubbles which makes the adherence quite weak (Radzi, 2016). To ensure the successful rise
of oil droplets to the wastewater surface, it is necessary to form a complete layer of oil droplets
over bubbles. This makes the oil particles robust enough to resist the impact of drag and
gravitational forces without breaking up in the course of rising (Radzuan et al., 2016). As a result,
in order to achieve a successful and effective flotation process, a positive So is required. Increasing
temperature and salinity will slightly increase the spreading coefficient because the IFT is
consequently lowered (Rawlins and Ly, 2012; Moeini et al., 2014). The spreading coefficient can
also be increased by using chemical surfactants that decrease the IFT at the oil-water interface
(Kumar and Mandal, 2018). Yan et al. (2020) summarized that the spreading time (typically < 10
ms) of the oil droplets on the bubble surface is reversely proportional to the spreading coefficient
and directly proportional to the oil viscosity.

39

Figure 2.13 Schematic diagram of two different contact modes between oil droplet and gaseous
bubbles (modified from Zhang et al., 2016)
2.6 Factors affecting oil separation efficiency in gas flotation
A variety of factors can affect the effectiveness of oil separation in gas flotation systems,
and they include initial oil concentration in wastewater, oil droplet size, pH, temperature, gas
pressure, salinity, and flotation time.
2.6.1 Initial oil concentration
Gas flotation is commonly used to treat oily wastewater with an initial oil concentration
less than 1000 ppm (Saththasivam et al., 2016). When the oil concentration exceeds 1000 ppm,
the efficiency of gas flotation could be reduced (Piccioli et al., 2020). Panneer Selvam (2018)
observed a decreasing trend in oil separation efficiency from 92% to 72% when the initial oil
concentration in wastewater was increased from 250 to 500 ppm. However, the majority of studies
indicated that oil separation efficiency would increase with the increase of initial oil concentration.
Van Le et al. (2013) treated finely emulsified palm oil using the combination of MBs and NBs
flotation method and they achieved a 9% increase in oil separation efficiency after 30 min when
they increased the initial oil concentration from 501 to 1009 ppm. Al-Dulaimi and Al-Yaqoobi
(2021) used MB flotation column for oil-water separation in medium crude oil-water emulsion,

40

and they found improved oil separation efficiency from 46.29% to 73.12% after 165 min flotation
when the initial oil concentration was increased from 200 to 300 ppm. As Alwared and Faraj
(2015) stated, the increase of oil separation may be due to the enhancement of collision probability
between gas bubbles and oil droplets in the emulsion.

2.6.2 pH
pH is an important factor for the emulsion breaking process (Figure 2.14). Using MB
flotation to treat emulsified palm oil, Van Le et al. (2012) observed a substantial increase (more
than 50%) in oil separation when the pH decreased from 8 to 3. Al-Dulaimi and Al-Yaqoobi (2021)
enhanced oil separation efficiency by lowering the pH from alkaline to neutral and achieved the
highest separation efficiency (75.19%) by further decreasing the pH to 3.32. Yasuda and Haneda
(2015) used a MB generator to separate soybean oil from emulsion and they found that the oil
separation efficiency increased with the decrease of pH. This effect was pronounced at pH levels
below 4.5 where the oil separation ratio doubled when pH was reduced from 4 to 3. Acidifying
emulsions with strong acid solutions such as H2SO4, HCl and HNO3 before demulsification can be
beneficial to the treatment process. According to Liu et al. (2021), oil droplets and gas bubbles
usually have negative ZP in water. With a decrease in pH, the ZP of gas bubbles increases and
reaches to zero when the pH is around 4.5, and further reducing the pH would result in positive ZP
(Takahashi, 2005). As for oil droplets, the ZP also increases with a decreasing pH and gradually
approaches zero (Yasuda and Haneda, 2015). Therefore, gas bubbles have a higher chance to attach
to oil droplets due to the reduced repulsive force in a solution with a pH around 4.5. Especially
when the pH is lower than 4.5, the positively charged gas bubbles can easily attach to negatively
charged oil droplets because of the attractive force.

41

Figure 2.14 The effect of pH on oil separation efficiency using MBs gas flotation

2.6.3 Temperature
The effect of temperature on gas flotation has not been sufficiently studied yet. Qi et al.
(2013) noticed an increase of oil separation from 83.4% to 92.2% when they raised the temperature
from 12 °C to 40 °C, and they concluded that the increase in temperature led to decrease in
elasticity and viscosity of the interfacial membrane. The decrease in elasticity and viscosity was
due to the decrease in intermolecular cohesive forces under a relatively high temperature, which
accelerated the coalescence of oil droplets. Radzuan et al. (2016) saw a slight increase in oil droplet
separation efficiency of the experiments conducted at a higher temperature (35 °C) compared to
that at room temperature for both vegetable oil and mineral oil. Jaji (2012) mentioned that when
the temperatures exceeded 75 °C, the solubility of some hydrocarbons will be remarkably
improved. Radzi (2016) noted that the viscosity of both the oil and water phase and surface
42

tensions were reduced at higher temperatures. Hasan et al. (2020) studied the effect of temperature
on the viscosity of heavy crude oil, and they observed a reduction in viscosity from 10 Pa·s to 6.3
Pa·s when the temperature was increased from 25 °C to 75 °C. Furthermore, Bera et al. (2021)
investigated the coalescence between oil droplets and observed higher coalescence frequencies at
elevated temperatures (from 20 °C to 70°C). Sadeghi and Vissers (2020) used a laboratory scale
flotation unit to investigate the effect of temperature on bubble size, and they found that the
increase in temperature slightly reduced the size of large bubbles from 96 μm to 81 μm; however,
it did not have significant effect on small bubbles (20 μm).

2.6.4 Pressure
DAF systems are usually designed and operated in the pressure range of 4–6 bar (Edzwald,
2010). According to Tetteh and Rathilal (2018), change of gas pressure that is utilized to dissolve
gas in the water can affect the oil separation process. Larger gas bubbles will be produced when
lower pressure is applied. The bubble size will affect flotation time which further influences the
oil separation efficiency (Radzi, 2016). Etchepare et al. (2017a) noticed an increase of oil
separation from 82% to 93% with the help of a flocculation polymer when the gas pressure
increased from 2.5 to 3.5 bar, and when the pressure was further increased to 5 bar and 6 bar, the
best results were achieved with separation efficiencies higher than 99%. In addition, they
emphasized that DAF (pressure = 3.5 bar) can well meet the USEPA standard oil and grease
emission level with a residual oil concentration of 28 ppm, which proved MBs and NBs-based gas
flotation can work effectively at low pressure. Radzuan et al. (2016) increased the oil separation
efficiency from 74.3% to 80.8% by increasing the pressure from 3 bar to 4 bar, and they indicated
that when the gas pressure increased beyond 3.5 bar, the quantity of bubbles generated would

43

increase, but there was no significant change in the resulting bubble size. Zheng et al. (2015)
investigated the performance of the DAF system under three different operational pressure (i.e.,
2.5, 3, and 3.5 bar), and they increased the oil separation efficiency from 67.6% to 87.7%. Tetteh
and Rathilal (2018) achieved improvement in oil separation efficiency with an increase in pressure
from 2 bar to 5 bar, but when they further increased the pressure to 6 bar, a slight decrease in the
efficiency was observed. As stated by Forero et al. (2007), even though the pressure can greatly
assist the oil separation process, the extra energy consumption and operation cost caused by the
increased pressure cannot be compensated by the increase in separation efficiency.

2.6.5 Salinity
Rajak et al. (2015) observed a significant increase in oil separation efficiency from 74.91%
to 98.58% when the sodium chloride concentration was increased from 1wt% to 2wt%. Younker
and Walsh (2014) investigated the oil separation performance by coagulation pre-treatment with
ferric chloride and DAF process in both saline and fresh water. They found that the oil separation
performance is better in saline water under different pH and coagulant doses, and this is because
electrolytes in solution increase the ionic strength which correspondingly reduces the repulsive
forces between oil droplets by double-layer compression. The addition of salt could decrease the
mean diameter of gas bubbles due to the reduction in chances of bubble collision and coalescence,
and the spreading coefficient could increase because of the decrease in oil-water IFT (Radzuan et
al., 2016). As noted previously, the oil capture efficiency of gas bubbles increases with smaller
bubbles (Balsley and Fitzpatrick, 2017). In addition, the dissolved oil concentration in the solution
can be reduced by increasing the salinity of wastewater (Jaji, 2012).

44

2.6.6 Flotation time
Flotation time plays an important role in the oil separation efficiency of gas flotation
systems (Figure 2.15). The increase in flotation time from 5 min to 25 min increased the oil
separation efficiency from 69% (oil concentration = 154 ppm) to 82% (oil concentration = 92 ppm)
when the initial oil concentration in the wastewater was 500 ppm (e Silva et al., 2018). Rajak et
al. (2015) used air flotation to treat light crude oil emulsion with 20 g/L salinity and they observed
that the oil recovery rate almost doubled when the flotation time increased from 10 min to 60 min.
They concluded that the increase in flotation time results in the enhancement of attachment
possibility between air bubble and oil droplets. Etchepare et al. (2017a) used isolated NBs with
flocculation polymer (polyacrylamide) to treat oily wastewater with an inlet oil concentration of
334 ppm. They found that the oil separation efficiency increased by 27% with the increase of
flotation time from 5 min to 10 min and further increase in flotation time had no significant effect
on the separation efficiency. Al-Dulaimi and Al-Yaqoobi (2021) investigated the effect of flotation
time on oil separation efficiency and found the separation increased by more than 60% when the
flotation time increased from 30 to 240 min at initial oil concentration of 200 ppm. Van Le et al.
(2012) increased the oil separation efficiency from 63% to 93% when they increased the flotation
time from 2 min to 60 min with the help of a cationic surfactant (cetyltrimethylammonium
chloride) at oil concentration of 1000 ppm.

45

Figure 2.15 The effect of flotation time on oil separation efficiency

2.6.7 Oil droplet size
Gas flotation performs efficiently without adding chemicals when oil droplets have a
diameter greater than 20 μm (Piccioli et al., 2020); however, it is not effective when the oil droplets
are in dissolved form with a diameter less than 5 μm (da Silva et al., 2015). It has been reported
that gas flotation is most effective when smallest possible gas bubbles are used to separate large
oil droplets (Moosai and Dawe, 2003). Li et al. (2016a) used DAF to treat heavy crude oil emulsion
and they observed a decrease in oil separation from 87.25% to 68.95% when the average oil droplet
size decreased from 46.42 μm to 8.48 μm. Huang and Long (2020) found that the increase of oil
droplet size from 22 μm to 41 μm led to an increase of oil separation efficiency by 7%. According
to Santander et al. (2011), the efficiency of gas flotation is significantly related to the degree of
emulsion destabilization. Demulsifiers are often used to destabilize water-oil emulsions to enlarge
46

the oil droplet size prior to the application of MBs and NBs based technologies (Zolfaghari et al.,
2016). The oil droplet size enlargement can also be achieved by using some specific separators.
For example, in the cyclonic separator, it is possible for oil droplets to coalesce due to speed
difference inside the separator (Li et al., 2016a). Oil droplet size can be determined by a variety of
procedures (Table 2.8).
Table 2.8 List of oil droplet size measurement methods
Methods

Reference

Mastersizer 2000 (Malvern, UK)

Kori et al., 2021

Zetasizer NanoZS laser diffractometer (Malvern, UK)

Salvia-Trujillo et al., 2013

Laser particle analyzer

Li et al., 2016a

Nuclear magnetic resonance spectrometer (Bruker, US)

Sommerling et al., 2016

Optical/Video microscopy + ImageJ software

Alade et al., 2021

AcoustoSizer II (Colloidal Dynamics LLC) instrument

Afuwape and Hill, 2021

2.7 Discussion and conclusions
Oil spills in the harsh, remote Arctic region would result in catastrophic consequences to
the fragile Arctic ecosystem, and the risk of oil spills in this region is expected to increase as a
result of the rapid climate change. It is important to develop effective and sustainable oil spill
countermeasures to enhance the preparedness for oil spills in the Arctic. MBs and NBs-based gas
flotation requires less energy consumption than some other wastewater treatment processes such
as filtration and centrifugation. Furthermore, it will not generate significant direct GHG emissions
or secondary pollution. Therefore, it is considered to be an environmentally friendly process that
is effective for oil-water separation from emulsions. Due to their small bubble size, MBs and NBs

47

have wide surface area and rather slow rising velocity which help to better separate oil droplets
from emulsions. The performance of MBs and NBs-based gas flotation treatment process is greatly
affected by many factors, such as initial oil concentration, gas pressure, salinity, flotation time,
addition of demulsifiers, and oil droplet size. A deep understanding of the inter-play of these
potential controlling factors is critical to achieve the best oil-water separation results. The
application of MBs and NBs in oily wastewater treatment is promising and the synergistic effect
of gas flotation with other treatment technologies (e.g., membrane separation, sorption) needs
further investigation. Future work is also needed in terms of the assessment of the environmental
impact (e.g., emissions) of the application of MBs and NBs-based flotation technology. The impact
assessment results would be helpful to the transition towards the sustainable oil spill response and
low-impact oily wastewater treatment.

48

Chapter 3 Materials and Methods
3.1 Materials
Fresh CHCO was recovered from the Western Canada Sedimentary Basin (WCSB) and
provided by Multi-Partner Oil Spill Research Initiative (MPRI). Table 3.1 lists the physiochemical
properties of fresh and weathered CHCO. Sodium chloride (NaCl, ≥ 99.0%) and sodium hydroxide
(NaOH, ≥ 97.0%) were purchased from Sigma-Aldrich. Tetrachloroethylene (≥ 99.0%, SigmaAldrich) was used for sample extraction. Silica gel (100-200 mesh, Sigma-Aldrich) activated at
215 °C for 24 h was used to clean up the extract. Anhydrous sodium sulfate (≥ 99.0%, SigmaAldrich) dried at 215 °C for 24 h was used to separate traces of water from the extract. Ultrapure
water (UPW) generated from a water purification system (Milli-Q ® Advantage A10) was used for
oily wastewater preparation.
Table 3.1 Physiochemical properties of fresh and weathered CHCO
Properties

Value

Units

Fresh

Weathered

API gravity

20.8

12.6

degrees (°)

Density (at 25 °C)

0.926

0.979

g/cm3

Dynamic viscosity (at 25 °C)

160.9

10222.0

mPa·s

Water content

599

427

mg/L

Saturates

52.6

50.9

wt.%

Aromatics

10.7

9.8

wt.%

Resins

24.5

20.8

wt.%

Asphaltenes

12.2

17.0

wt.%

49

3.2 Oil weathering
The oil weathering process was conducted by placing 5 g fresh CHCO under a wellventilated chemical fume hood at room temperature for six days (Hassanshahi et al., 2022). The
cumulative mass loss due to evaporation of volatile hydrocarbons at different times was recorded
and plotted in Figure 3.1. The cumulative mass loss reached 16% after three days, and further
weathering had no significant effect on mass loss (less than 1% in a day). Thus, CHCO with 16%
weathering was used in this research as weathered oil.

Cumulative mass loss (%)

25.0

20.0

15.0

10.0

5.0

0.0
0

1

2

3

4

5

6

Time (day)

Figure 3.1 Cumulative mass loss of CHCO at different times

3.3 Preparation of oily wastewater
Artificial seawater was prepared by dissolving 35 g/L of NaCl in UPW to mimic the
average salinity of real seawater (Lei et al., 2019). About 0.1 N sodium hydroxide (NaOH) solution
was used to adjust the pH to 8.2, and a Mettler Toledo pH meter was used to measure the pH.
Marine oily wastewater was prepared by dispersing the weighed amount of CHCO (fresh and
weathered) in 2 L artificial seawater using an Ultra-Turrax homogenizer (IKA®, T50 model, 700
50

watts) equipped with a dispersing tool (IKA Works model: S50N-G45G). It was mixed at 5,000
rpm for 2 min and then at 10,000 rpm for 15 min. The homogenizer was turned off for 20 min after
10 min of operation to prevent the increase in the wastewater temperature. In this work, oily
wastewater with initial oil concentrations of 200, 400, and 600 mg/L was prepared.

3.4 Experimental setup and procedure
All the experiments were carried out in a laboratory-scale gas flotation system (Fig. 2a).
The cylindrical flotation column was made from clear polyvinyl chloride (PVC) with an internal
diameter of 5.2 cm and a height of 100 cm. A fine bubble generator (LE5S, Living Energies &
Co., Japan) capable of generating both MBs and NBs was used in this research, and its
specifications are listed in Table 3.2. The existence of MBs can be seen from the milky appearance
of the test water (Figure 3.2b). For each experiment, 2 L of oily wastewater was added to the
flotation column from the top. Treated water was entirely recycled back to the bubble generator
for bubble formation, and the bubble solution was introduced at the bottom of the column. After
the flotation process, treated water samples were taken from sampling port 1 (Figure 3.2a) of the
column for analysis. Control experiments were carried out in the same experimental setup (Figure
3.2a) without the generation of MBs and NBs.
Table 3.2 Summary of bubble generator specifications
Property

Value

Outer dimensions

H360mm × W310mm × D130mm

Weight

Approx. 4.4 kg

Electric power

AC 100-110V

Power frequency

50/60 Hz

51

Power consumption

1.3A

Capacity

200-300 cc/min

Temperature range

0 °C to 80 °C

Viscosity max.

50 mPas
4mm (internal diameter)

Connecting tubing size
6mm (external diameter)

Figure 3.2 Laboratory MBs and NBs flotation setup (a) and appearance of MBs in test water (b)

3.5 Experimental design
Three experimental factors were investigated for their effects on oil separation efficiency,
including initial oil concentration (X1), flotation time (X2), and temperature of inlet wastewater
52

(X3). The selection of these factors and their levels was based on preliminary experiments, previous
studies, and ambient environmental conditions. During the Deepwater Horizon oil spill, the
average total petroleum hydrocarbon was 202 mg/L for all the seawater samples collected below
the ocean surface (Sammarco et al., 2013). According to Saththasivam et al. (2016), gas flotation
is commonly used to treat oily wastewater with an initial oil concentration of less than 1000 mg/L
Therefore, an initial oil concentration range of 200–600 mg/L was selected in this study. A
flotation time range of 10–30 min was selected based on the studies carried out by other researchers
(Etchepare et al., 2017a; e Silva et al., 2018). The observation data of NASA’s Aqua satellite
indicated that the sea surface temperature ranges from -2 °C in polar regions to 35 °C in equatorial
regions (Sea Surface Temperature, n.d.). Thus, a temperature range of 2–40 °C for inlet wastewater
was selected.
RSM is an effective statistical tool for the optimization of different operational factors as
well as for reducing the number of experimental runs (Wang et al., 2022a). A three-factor, threelevel central composite design (CCD) was developed using RSM (Design Expert ®, version 13.0).
Table 3.3 lists the coded levels of different factors and their actual values. A total of 17
experimental runs with 3 replicates at the center point (to evaluate the pure error) were required.
A detailed arrangement of experiments is shown in Table 3.4. The oil separation efficiency (Y)
was selected as the response to evaluate the performance of the flotation process. The statistical
significance of investigated variables and their interactions were determined by the analysis of
variance (ANOVA). A quadratic polynomial equation used for predicting optimal conditions is
expressed in Eq. (3.1).
=

+

+

+

(3.1)

53

Where Y is the predicted response, k is the number of independent variables (k = 3 in this
study), xi and xj are independent variables, β0 is the constant coefficient, βi is the linear effect, βii
is the quadratic effect, and βij is the interaction effect between xi and xj (Hu et al., 2017; Zubair et
al., 2022).
Confirmation experiments were performed at the optimum conditions to validate the
mathematical model generated by RSM. The effect of crude oil conditions (fresh and weathered)
was also investigated on the oil separation efficiency of the gas flotation system at the optimum
conditions based on RSM results. In addition, single-factor experiments were also conducted to
evaluate the influence of flotation time at wider levels on the oil separation efficiency. All the
experiments were repeated three times, and their mean values were reported.
Table 3.3 Experimental range and levels of independent variables
Independent variables

Symbol

Coded levels

Units

-1

0

+1

Initial oil concentration

X1

200

400

600

mg/L

Flotation time

X2

10

20

30

min

Temperature of inlet wastewater

X3

2

21

40

°C

Table 3.4 Experimental matrix of CCD design
Run

Initial oil concentration a

Flotation time a (min)

Temperature of inlet
wastewater a (°C)

(mg/L)
1

400 (0)

20 (0)

21 (0)

2

400 (0)

20 (0)

2 (-1)

3

400 (0)

30 (1)

21 (0)

54

a

4

200 (-1)

10 (-1)

2 (-1)

5

400 (0)

20 (0)

21 (0)

6

600 (1)

10 (-1)

2 (-1)

7

200 (-1)

30 (1)

40 (1)

8

200 (-1)

20 (0)

21 (0)

9

600 (1)

30 (1)

40 (1)

10

600 (1)

10 (-1)

40 (1)

11

400 (0)

20 (0)

40 (1)

12

400 (0)

10 (-1)

21 (0)

13

600 (1)

20 (0)

21 (0)

14

600 (1)

30 (1)

2 (-1)

15

200 (-1)

30 (1)

2 (-1)

16

400 (0)

20 (0)

21 (0)

17

200 (-1)

10 (-1)

40 (1)

Values of coded levels (in parentheses) and actual values of experimental factors

3.6 Microscopy analysis
The morphology of oil droplets in the prepared wastewater was obtained through a
compound microscope (Fisher Scientific AX800) with an objective magnification of 200 ×. The
images were captured by a digital camera (Fisherbrand™ C-Mount Digital Camera) using
SeBaView software (version 4.7) and were processed with ImageJ software to determine the oil
droplet size and its distribution. For each sample, the diameters of at least 300 oil droplets were
analyzed.

55

3.7 Oil concentration analysis
FTIR (Spectrum Two, PerkinElmer, USA) was employed to determine the oil
concentration in the oily wastewater and the treated water by absorbance measurement (Farmaki
et al., 2007). Tetrachloroethylene was used as an extraction solvent to extract oil from water
samples due to its low toxicity (Sun et al., 2021). For each measurement, 20 mL of water sample
was extracted following the standard ASTM D7066-04 (2017) method. The pure solvent was used
as a blank. Infrared spectra were acquired at the wavelength range of 3200-2700 cm-1. The oil
separation efficiency was calculated based on the difference between the initial and the final oil
concentration in the wastewater by Eq. (3.2):
=

× 100%

(3.2)

Where Y is the oil separation efficiency (%), C0 is the initial oil concentration (mg/L), and
Cr is the residual oil concentration (mg/L) in the treated water.

56

Chapter 4 Results and Discussion
4.1 Size distribution of NBs
The sizes of NBs were measured using NanoSight NS500 (Malvern Instruments Ltd.),
which uses nanoparticle tracking analysis (NTA) technology. As shown in Figure 4.1, the mean
diameter and concentration of NBs were 102 nm and 4.27×108 particles/mL, respectively.

Figure 4.1 Particle size distribution of NBs

4.2 Regression model generation and statistical analysis
Table 4. 1 Results for oil separation efficiency of CHCO
Run

1

Oil separation efficiency (%)
Actual

Predicted

93.3

93.1

57

2

86.6

87.5

3

96.7

98.6

4

64.3

64.3

5

92.8

93.1

6

88.7

88.9

7

93.9

93.9

8

82.1

82.0

9

97.1

97.2

10

95.6

96.3

11

96.9

95.4

12

88.2

87.5

13

96.4

95.9

14

95.4

94.9

15

86.2

85.6

16

93.7

93.1

17

76.9

77.6

Table 4.2 ANOVA results of the regression model for oil separation efficiency
Source

Sum of

df

Squares

Mean

F-value

p-value

Square

Model

1206.03

8

150.75

122.53

<0.0001

X1

487.20

1

487.20

395.98

<0.0001

X2

309.14

1

309.14

251.25

<0.0001

significant

58

X3

153.66

1

153.66

124.89

<0.0001

X1X2

117.81

1

117.81

95.75

<0.0001

X1X3

17.11

1

17.11

13.91

0.0058

X2X3

12.75

1

12.75

10.36

0.0123

X1 2

51.19

1

51.19

41.61

0.0002

X3 2

7.86

1

7.86

6.39

0.0354

Residual

9.84

8

1.23

Lack of Fit

9.44

6

1.57

7.73

0.1189

not
significant

Pure Error

0.4067

2

Cor Total

1215.87

16

0.2033

Fit Statistics
Std. Dev.

1.11

R2

0.9919

Mean

89.69

Adjusted R2

0.9838

C.V.%

1.24

Predicted R2

0.9538

Adequate

42.5053

precision

The corresponding experimental results regarding oil separation efficiency based on CCD
are shown in Table 4.1. It was found that the quadratic effect of X2 was not significant for oil
separation efficiency. Thus, this term was eliminated from the model. The following modified
regression model for oil separation efficiency in the investigated experimental range was
established:

59

= 23.86 + 0.16

+ 1.46

6.65 × 10

+ 0.68

− 1.92 × 10

− 1.03 × 10

− 3.85 × 10

− 4.46 × 10

−
(4.1)

Where Y is the oil separation efficiency (%), X1, X2, and X3 represent initial oil
concentration (200–600 mg/L), flotation time (10–30 min), and temperature of inlet wastewater
(2–40 °C), respectively.
The significance of the model and the importance of the effect of each parameter were
verified by ANOVA, and the associated results are shown in Table 4.2. A low p-value (<0.01%)
and a high F-value (122.53) indicated that the generated model was significant and could well
describe the oil separation efficiency. The lack of fit was insignificant, with a probability value of
0.1189 (>0.05), indicating that the developed model was suitably fitted to the experimental data
and sufficiently accurate to predict the response. The coefficient of determination (R2) reached
0.9919, while adjusted R2 and predicted R2 were 0.9838 and 0.9538, respectively. All the values
of R2 were high and very close to each other, which suggested a good fit of the regression model
with high accordance between the experimental data and the predicted outcome. The signal-tonoise ratio (adequate precision) was desirable (>4), indicating the existence of sufficient signal
and the capability of the generated model to predict results.

4.3 Effect of process parameters on oil separation efficiency
4.3.1 Effect of initial oil concentration
Based on ANOVA results, initial oil concentration was found to be the most critical factor
in influencing the oil separation efficiency (F-value: 395.98, p-value < 0.0001). It is shown in
Figure 4.2a that the increase of initial oil concentration in the oily wastewater could positively
affect the oil separation efficiency. As listed in Table 3.4, increasing the initial oil concentration
60

from 200 mg/L to 600 mg/L greatly enhanced the oil separation efficiency by 14.3% (experimental
runs #8 and #13), decreasing the effluent oil concentration from 36.8 mg/L to 23.7 mg/L.
Generally, the increase in initial oil concentration led to a higher oil separation efficiency.
However, a further increase in the oil concentration (> 500 mg/L) only brought a limited increase
in oil separation efficiency. At higher oil concentrations, the oil droplets are denser and more
uniformly distributed, which facilitates the bubble-oil aggregates to capture more oil droplets and
therefore enhance the overall separation efficiency (Wang et al., 2022b; Shen et al., 2022).

61

62

Figure 4.2 Predicted effects of experimental factors on oil separation efficiency, (a) flotation time: 20 min, temperature of inlet
wastewater: 21 °C; (b) initial oil concentration: 400 mg/L, temperature of inlet wastewater: 21 °C; (c) initial oil concentration: 400
mg/L, flotation time: 20 min

4.3.2 Effect of flotation time
From Figure 4.2b, a trend can be observed in which oil separation efficiency increased with
increasing flotation time in the experimental range of 10–30 min. A set of single-factor
experiments were implemented to further investigate the effect of flotation time on oil separation
efficiency, and the results are shown in Figure 4.3. Initial oil concentration and temperature of
inlet wastewater were set at 400 mg/L and 21 °C, respectively. The oil separation efficiency was
considerably enhanced in the first 15 min from 68.8% to 89.6%. The oil separation efficiency kept
increasing with the increase in flotation time; however, the increasing rate was much slower after
15 min, especially after 40 min. At 60 min of flotation, it reached the highest oil separation
efficiency of 98.7%. The positive effect of flotation time is mainly due to the increased encounters
and interactions between gas bubbles and oil droplets at longer flotation times (Larsen, 2022).
Although a longer duration of gas flotation helps to improve the oil separation performance, it is
worth mentioning that controlling the flotation time under a certain limit is desirable for reducing
the operational cost.

63

Figure 4.3 Effect of flotation time on oil separation efficiency

4.3.3 Effect of temperature of inlet wastewater
Temperature of inlet wastewater is also an essential factor that significantly affects the oil
separation efficiency in the MBs and NBs gas flotation process. As shown in Figure 4.2c, by
increasing the temperature of inlet wastewater, higher oil separation efficiencies were achieved.
Results of the same experimental conditions indicated (experimental runs #2 and #11 in Table 3.4)
that increasing the temperature of inlet wastewater from 2 °C to 40 °C led to an increase in oil
separation efficiency from 86.6% to 96.9%. Correspondingly, the residual oil concentration in the
treated water was reduced from 52.3 mg/L to less than 15 mg/L. There are several possible
explanations for why the temperature of inlet wastewater might enhance oil separation with MBs
and NBs gas flotation. First, as stated by Radzuan et al. (2016), the increasing temperature led to
64

a reduction in the viscosity of the fluids being treated, which increased the rising velocity of the
oil droplets. Second, the increase in temperature may also enhance the coalescence frequency of
oil droplets which will facilitate the oil separation (Piccioli et al., 2020).

4.3.4 Interaction of parameters
The interaction effects of experimental factors on the efficiency of MBs and NBs gas
flotation were investigated. It can be found in Figure 4.4a that increasing flotation time resulted in
enhanced oil separation efficiency at a low initial oil concentration, and this was attributed to
adequate time for gas bubbles and oil droplets to attach and float to the liquid surface. Figure 4.4b
shows the interactive reaction between the temperature of inlet wastewater and flotation time.
When the temperature of inlet wastewater was high (e.g., 40 °C), a short flotation time (10 min)
was sufficient to reach more than 90% of oil separation. A longer flotation time was needed to
achieve similar results when the temperature of inlet wastewater was low. Furthermore, Figure
4.4c demonstrates the effect of changes in initial oil concentration and temperature of inlet
wastewater on oil separation efficiency. As can be observed in the figure, the higher oil separation
efficiency was obtained when both the initial oil concentration and temperature of inlet wastewater
were kept at a higher value, which is consistent with the trends observed in Figure 4.4a and Figure
4.4c.

65

Figure 4.4 3D response surface graph showing the interaction effects of experimental factors on oil separation efficiency at (a)
temperature of inlet wastewater = 21°C; (b) initial oil concentration = 400 mg/L; (c) flotation time = 20 min
66

4.4 Response surface optimization and validation of optimized results
In this study, the optimization of operational conditions for oil separation in gas flotation
system was performed using Design Expert software version 13. To determine the optimum
operational conditions, the oil separation efficiency was selected at the maximum value, and the
target values of three independent variables were selected as in range. Based on the empirical
model, the predicted maximum oil separation of 98.4% can be obtained at an initial oil
concentration of 524.5 mg/L, flotation time of 28.6 min, and inlet wastewater temperature of
21.2°C. Under these conditions, the model’s degree of desirability was equal to 1. To confirm the
validity of the empirical model and the accuracy of the optimization results, three runs of
confirmation experiments were conducted under the predicted optimal conditions. As shown in
Table 4.3, an average oil separation efficiency of 97.3% was achieved with a standard deviation
of 0.75 under the optimal conditions, which was in good agreement with the predicted value of
98.4%. Thus, it is evident that the obtained RSM model in this study can reasonably predict the oil
separation efficiency by gas flotation system with MBs and NBs. All the experimental results from
the confirmation experiments fell into the 95% prediction interval, further validating the model.
Table 4.3 Validation results with the actual and the predicted efficiency
Run

Actual efficiency (%)

Predicted efficiency (%)

Error (%)

1

97.4

98.4

-1

2

96.5

98.4

-1.9

3

98.0

98.4

-0.4

Standard deviation

0.75

Mean efficiency 97.3

67

4.5 Control experiments
Control experiments were designed to investigate the effect of the buoyant force of oil
droplets in the prepared oily wastewater on oil separation efficiency. Three control experiments
were conducted by leaving the prepared oily wastewater in the flotation column for gravity
separation without flotation under the optimum experimental conditions obtained through RSM.
In addition, the duration of gravity separation was extended from 28.6 min to 2 hours while the
initial oil concentration and the temperature of inlet wastewater remained the same as the optimum
values. It was observed from Figure 4.5 that after 28.6 min of gravity separation, the oil separation
efficiency was 6.7%, and the oil separation efficiency reached 31.2% after 2 hours of gravity
separation. However, after 28.6 min of gas flotation, the oil separation efficiency was greatly
increased to 97.3%, which indicated that the application of MBs and NBs can significantly assist
the separation of CHCO in the flotation system.

Figure 4.5 Comparison of oil separation efficiency between gravity separation and gas flotation
68

4.6 Effect of crude oil condition on oil separation efficiency
Both fresh and weathered oil were used to prepare oily wastewater. The generated
wastewater was treated using MBs and NBs gas flotation under the optimum operational
conditions obtained through RSM. The oil droplet size distribution in the oily wastewater
generated by fresh and weathered CHCO was analyzed by ImageJ software. The microscopic
images of the prepared oily wastewater and their corresponding oil droplet size distribution plots
are shown in Figure 4.6. As presented in Figure 4.6, the average oil droplet size for the oily
wastewater prepared with fresh and weathered CHCO were 24.51 μm and 29.29 μm, respectively.

Figure 4.6 Microscopic images and corresponding oil droplet size distribution plots of the
generated oily wastewater (a) with fresh CHCO, (b) with weathered CHCO

69

The effect of crude oil condition (fresh and weathered) on oil separation efficiency using
MBs and NBs gas flotation was then studied, and the results are shown in Figure 4.7.

Figure 4.7 Effect of CHCO condition on oil separation efficiency
It can be seen from Figure 4.7 that there was no significant difference in oil separation
efficiency between oily wastewaters containing fresh and weathered oil. After 28.6 min of gas
flotation, the oil separation efficiency was 97.3% with fresh oil-contaminated oily wastewater. In
comparison, the oil separation efficiency reached 98.2% for oily wastewater prepared with
weathered oil after 28.6 min of gas flotation. Thus, it was suggested that gas flotation with MBs
and NBs was effective at separating fresh as well as weathered crude oil.

70

Chapter 5 Conclusions
5.1 Research summary
In this study, the performance of MBs and NBs gas flotation in separating oil droplets from
oily wastewater was investigated using RSM. Various initial oil concentrations, flotation times,
and temperatures of inlet wastewater were examined to explore their effects on oil separation
efficiency and the main findings of this paper are as follow:
(1) All three tested parameters were positively correlated with oil separation efficiency, and
the influential effects were ranked as initial oil concentration (X1) > flotation time (X2) >
temperature of inlet wastewater (X3). A higher initial oil concentration could favor the oil
separation process because of increased collision probability between oil droplets and gas bubbles.
The oil separation was improved through the increase of flotation time; however, longer flotation
time is not always desired considering the operational costs. The temperature of inlet wastewater
also turned out to have a positive effect on the oil separation performance. Higher temperatures
can reduce the viscosity of oil and water, which facilitates the rise and separation of oil from oily
wastewater.
(2) The optimum treatment conditions are initial oil concentration of 524.5 mg/L, flotation
time of 28.6 min, and inlet wastewater temperature of 21.2°C.
(3) In comparison to gravity separation, gas flotation remarkably improved oil separation. It
can be observed that the oil separation efficiency increased by 90.6% with the presence of MBs
and NBs when all the other conditions were kept the same.
(4) Oil separation efficiency was not affected by the crude oil condition. Thus, gas flotation
with MBs and NBs can be used to treat both fresh and weathered oil spills.

71

(5) The use of MBs and NBs gas flotation appears to be an effective approach that not only
helps significantly improve oil separation but also is chemical-free and scalable.

5.2 Limitations and future research
In this study, the laboratory-scale MBs and NBs gas flotation system was investigated to
separate oil droplets from oily wastewater with high efficiency and easy operation. Although this
method demonstrated promising results in the laboratory, its feasibility in large-scale application
needs further verification. Due to limitations of time and lab resources, there are still some
problems that need to be investigated and explored in depth. Recommendations for possible future
research related to this study are listed as follows:
(1) Only one type of oil (heavy crude oil) was tested in this research. In the future, other types
of oil including light and medium crude oil should also be investigated to compare if there is any
difference in oil separation efficiency using MBs and NBs gas flotation.
(2) Air was used as the gas source in the current study. Different types of gas (e.g., nitrogen,
ozone, and oxygen) should be used as the injection source in the future research.
(3) It is difficult to recover the separated oil (top layer) in the current flotation column. Once
we took the treated water samples from the bottom of the column, the liquid level would drop and
most of the separated oil would attach to the column wall. It is of great importance to design an oil
skimming device that can recover the separated oil so that we can analyze the properties of the
separated oil and possibly reuse the recovered oil afterwards.
(4) Future studies on the mechanisms of how NBs facilitate the flotation with MBs should be
considered. The interaction between pollutant particles (oil droplets) with MBs and inter-pollutant
particles when NBs can be observed should be focused in order to understand the reasons behind.
72

(5) When studying the effect of the temperature on oil separation, it is better to keep the
ambient temperature the same as the wastewater temperature. In the current study, only the
temperature of the oily wastewater going into the flotation column was controlled and the
experiments were conducted under room temperature. So, during the course of the flotation
experiments, the temperature of the wastewater definitely would gradually reach the room
temperature.

73

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