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AIR STRIPPING WlTH ELECTROMAGNETIC-VIBRATION
ENHANCEMENT FOR CLEANING UP SOlLS CONTAMINATED BY
PETROLEUM PRODUCTS
A Thesis Submitted to the Faculty of Graduate Studies and Research
in Partial Fulfillment of the Requirements for the Degree of
Master of Applied Science in Environmental Systems Engineering
University of Regina
by Linsen Zhang
Regina, Saskatchewan September 2000
@ Copyright 2000: L.S. Zhang
National Library I*l ofCanada Bibliothbque nationale du Canada
uisitions and Acquisitions et Bii iogrephk Setvices seMces bibliographiques 9
The author has granted a non- exclusive licence allowing the National L i i of Canada to reproduce, loan, distriiute or seil copies of this thesis in microform, paper or electronic formats.
The author retains ownership of the copyright in this thesis. Neither the thesis nor substantial extracts fiom it may be printed or otherwise reproduced without the author's permi-ssion.
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L'auteur conserve la propriété du droit d'auteur qui protège cette thèse. Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou autrement reproduits sans son autorisation.
ABSTRACT
Soils in many petroleurn-related sites have been contaminated with petroleum
products due to various activities in energy industries. In order to help solve this problem,
a number of innovative in-situ remediation methods have been developed to reduce the
volume and toxicity of petroleum-based wastes. However, difficulties exist in sites with
impermeable soils, where the efficiencies of many technologies are significantly reduced.
In this study, electrornagnetic-vibration-enhanced air stripping method was proposed, and
many related factors, such as soi1 type and air injection pressure were systematically
investigated through bench-scde expenments.
A z4 full factorial design was implemented for the expenments that involved four
factors (NO levels for each). The main factors that had significant effects on the toluene
removal were identified. A response surface mode1 was then fomulated based on the
factorial analysis results, reflecting interrelationships between the system conditions and
the toluene adsorption rate.
Continuous air injection experiments were also conducted to examine the fate of
benzene, toluene. ethylbenzene and (m+p)-xylene (BTEX) in different enhancement tests.
The effects of soi1 type, soi1 moisture, contaminant type and adsorption duration were
investigated.
The electrornagnetic-vibration-enhanced air stripping experhents were conducted
to compare efficiencies of different enhancement tests in improving toluene removal. The
effects of soil type, contaminant concentration and au injection pressure on toluene
recovery were studied. The results include that
1. The electromagnetic-vibration-enhanced air stripping technology could
significantly increase toluene removal efficiency in a system of fine sand with
different clay contents (40%, 50%, 60% and 70%).
2. The clay content was negatively correlated with toluene recovery under limited air
injection pressure. The higher the clay content, the lower the toluene removal
efficiency.
3. The air injection pressures within a limited range was positively correlated with
the toluene removal effciency. However, when the air-injection pressure
exceeded soil overburden, fiacture phenomenon may occur, resulting in reduced
removal efficiencies.
4. The effect of adsorption at different gasoline concentrations on the removal
efficiency was insignificant.
5. The effect of BTEX adsorption duration on their removal efficiency within a
certain range was also insignificant.
ACKNOWLEDGEMENTS
First of all, 1 would like to express rny deep gratitude to Dr. Gordon Huang and Dr.
Amitabha Chakrna, my supervisors, for their excellent supervision, inestimable guidance
and kind encouragement, which contributed to the successful completion of this thesis. The
knowledge, working philosophy and methods I learned from them would be an invaluable
asset for my future career.
I would like to thank my committee members Dr. M. Dong, Peter, Gu and Stephen K.
O'leavy for their technical assistance. My appreciation also goes to the following people
who helped me make this thesis successful. Dr. Paitoon Tontiwachwuthikul provided me
space For setting up my expenmentd apparatus. Dr. Xiang Rong gave me constructive
comments and insightful advises. 1 would also like to thank Mr. Yunfeng Hu, Mr. Amr
Henni Mr. Jason Dunbar and Mr. Ryan Sinfield for their technical assistance.
1 am also grateful to the Faculty of Graduate Studies and the Faculty of Engineering
at the University of Regina for providing scholanhips during my graduate study.
Finally, I would like to express my special thanks to my wife, Caizhen Hu, and my
son, Qiao Zhang, for their love, support, understanding and emotional encouragement
throughout the coune of my graduate study.
iii
CONTENTS
ABSTRACT
ACKNOWLEDGEMENTS
LIST OF FIGURES
LIST OF TABLES
CHAPTER 1 INTRODUCTION
1.1 Background
1.2 S tatement of Problems
1 .3 Objectives
CHAPTER 2 LITERATURE REVIEW
2.1 The Role of Air in Soil Remediation
2.1.1 Soi1 Vapor Extraction
2.1.2 Air Sparging
2.1.3 Bioventing
2.2 Enhanced Soil Remediation Technologies
2.2.1 HydrauliJPneumatic Technologies
2.2.2 Thermal Enhancement
i
iii
viii
xi
2.3 Parameter Affecting Volatilization
2.3.1 Soil Texture
2.3.2 Soil Moisture
2.3.3 Air Injection PressurJFlow Rate
2.3.4 Vapor Pressure and Boiling Point
2.4 Electrornagnetic Vibration and Application
2.4.1 Electromagnetic Vibration Phenornena
2.4.2 Application of Electromagnetic Vibration
2.5 Analytical Methods
2.6 Methods for Experimental Design and Result Analysis
2.7 Literature Review Summary
CHAPTER 3 MATERIAL AND METHOD
3. t Matenai and Instnunent
3.1.1 Material Preparation
3.1.2 Instrument
3.2 Experimental Apparatus
3.2.1 Electromagnetic Vibration Generator
3.2.2 Experimental Set-up for Continuous Air Injection
3.2.3 Experimental Set-up for Electromagnetic
Vibration Enhanced Air Stripping
3.3 Experimental Method
3.3.1 Continuous Air ln, ection
3.3.2 Electromagnetic-Vibration-Enhanced Air Stripping
3.4 Sarnpling Methods
3.4.1 Continuous Air injection
3.4.2 Electromagnetic Vibration Enhanced Air SQ$ping
3.5 Analytical Methods
3.5.1 Toluene Vapor Analysis
3.5.2 Analysis of Toluene in SoiIs
3.5.3 Data Analysis
CHAPTER 4 STATISTICAL ANALYSIS
4.1 Induction
4 . 2 Randomization
4 . 3 Variables
4.4 Response Surface Mode1
CHAPTER 5 RESULT AND DISSCUSSION
5.1 Testing Conditions
5.2 Testing Results
5.3 Statistical Analysis
5.3. L R d t Interpretation
5.3.2 Sensitivity Analysis
5.3.3 Analysis of Variance
5.3.3.1 Process Development Data
5.3.3 -2 Diagnostic Exaxnination
5.4 Surnrnary
5.5 Continuous Air Injection System for BTEX Removal
5.5.1 Effect of Water Content on BTEX Removal
5 S.2 Effect of Clay Content on BTEX Removal
5.5.3 Effect of Adsorption Time on BTEX Removal
5.6 Effect of Soi1 Type on Toluene Removal
5.7 Effect of Air Injection Pressure on Toluene Removal
5.8 Effect of Electrornagnetic Vibration
CHAPTER 6 CONCLUSIONS
6.1 Summary
6.2 Research Achievements
6.3 Recommendations for Future Research
REFERENCES
vii
LIST OF FIGURES
Figure 3.1 Size Distribution of Sand Particles
Figure 3.2 Schematic of Experiment Set-up for Continuous Air injection Tests
Figure 3.3 Schematic of Experiment Set-up for Electromagnetic-Vibration
-Enhanced Air Stripping Tests
Figure 3.4 Standard Calibration Cuve for Toluene Vapor Analysis
Figure 3.5 Standard Calibration Curve for Toluene Analysis in Soils
Figure 5.1 Toluene Adsorption Rates Under Various Experimental Conditions
Figure 5.2 Cumulative Toluene Removal efficiency vs. Time (Run 1 )
Figure 5.3 Cumulative Toluene Removal eficiency vs. Time (Run 2)
Figure 5.4 Cumulative Toluene Removal eficiency vs. Time (Run 3)
Figure 5.5 Cumulative Toluene Removal efficiency vs. Time (Run 4)
Figure 5.6 Cumulative Toluene Removal efficiency vs. Time (Run 5 )
Figure 5.7 Cumulative Toluene Removal efficiency vs. Time (Run 6)
Figure 5.8 Cumulative Toluene Removal efficiency vs. Time (Run 7)
Figure 5.9 Cumulative Toluene Removal efficiency vs. T h e (Run 8)
Figure 5.10 Cumulative Toluene Removal efficiency vs. Time (Run 9)
Figure 5.1 1 Cumulative Toluene Removal efficiency vs. Time (Run 10)
Figure 5.1 2 Cumulative Toluene Removal effciency vs. Time (Run I 1 )
Figure 5.13 Cumulative Toluene Removai efficiency vs. Time (Ru. 12)
viii
Figure 5.14 Cumulative To luene Removal efficiency vs. Time (Ru. 1 3)
Figure 5.15 Cumulative Toluene Removal efficiency vs. T h e (Run 14)
Figure 5.16 Cumulative Toluene Removai efficiency vs. Time (Run 1 5)
Figure 5.17 Cumulative Toluene Removal efficiency vs. Time (Run 16)
Figure 5.1 8 Detailed Examination for Effects of x2, x3 and x4
Figure 5.19 Normal Plot of Process Effects on Probability Paper
Figure 5.20 Normal Plot of Residual Effects on Probability Paper
Figure 5.21 Benzene Removal Efficiency vs. Air Injection Duration
for Different Soil Water Contents (Run 17)
Figure 5.22 Toluene Removal Efficiency vs. Air Injection Duration
for Different Soil Water Contents (Run 18)
Figure 5.23 Ethylbenzene Removal Efficiency vs. Air Injection Duration
for Different Soil Water Contents (Run 19)
Figure 5.24 (m+p)Xylene Removal Efficiency vs. Air Injection Duration
for Different Soil Water Contents (Run 20)
Figure 5.25 Benzene Removal Efficiency vs. Air Injection Duration
for Di fferent Clay Contents (Run 2 1)
Figure 5.26 Toluene Removal Efficiency vs. Air Injection Duration
for Different Clay Contents (Run 22)
Figure 5.27 Ethylbenzene Removal Efficiency vs. Air injection Duration
for Different Clay Contents (Run 23)
ix
Figure 5.28 (rn+p)Xylene Removal Eficiency vs. Air injection Duration
for Different Water Contents (Run 24)
Figure 5.29 Benzene Removal Efficiency vs. Air Injection Duration
for Different Adsorption Durations (Ru 25)
Figure 5.30 Toluene Removal Efficiency vs. Air Injection Duration
for Different Adsorption Durations ('un 26)
Figure 5.3 1 Ethylbenzene Removal Efficiency vs. Air injection Duration
for Different Adsorption Durations (Run 27)
Figure 5.32 (m+p)Xylene Removai Efficiency vs. Air Injection Duration
for Different Adsorption Duration (Run 28)
Figure 5.33 Cumulative Toluene Removal efficiency vs. Air Injection Duration for
Different Clay Contents Without Electrornagnetic Vibration 109
Figure 5.34 Cumulative Toluene Removal efficiency vs. Air Injection Duration for
Different Clay Contents With Electromagnetic Vibration 1 IO
Figure 5.35 Cumulative Toluene Removal efficiency vs. Air Injection Duration for
Different Air Injection Pressures Contents Without Electromagnetic Vibration 1 13
Figure 5.36 Cumulative Toluene Removd eficiency vs. Air Injection Duration for
Different Air Injection Pressures With Electromagnetic Vibration 114
Figure 5.37 Toluene Removal emciency vs. Soi1 Clay Content I l 7
Figure 5.38 E ffect of EIectrornagnetic Vibration Duration on Cumulative
Toluene Removal efficiency
X
LIST OF TABLES
Table 3.1 BTEX Concentrations in Gasoline
Table 4.1 Full Factorial Design of Four Variables at Two Levels
Table 4.1 Design Variables
Table 5.1 Experimental Conditions for the Factond Design
Table 5.2 Analysis of Toluene Adsorption Rate
Tab te 5.3 Main Effects and Interactions
Table 5.4 Sensitivity Andysis
Table 5.5 Result of Robability Analysis
Table 5.6 Values of y, 9 , and y- j for Factorial Design
Table.5 7 Physical and Chernical Properties of BTEX
Table 5.8 Experimental Conditions for the Different Expenment Runs
Chapter L
Introduction
1.1 Background
Soi1 and groundwater contamination at sites of landfill operation, agricultural
practice, and various activities in chemical and energy industries is acquiring more and
more attention by the public and govemments. The contamination can lead to a variety
of impacts on and nsks to the communities and the polluten themselves.
The public has recognized the need to greatly reduce the volume and toxicity of
contaminants and to develop safe, effective and economic alternatives for their
disposa1 (Nicholas, 1987). A number of remediation technologies have been developed
to cleanup soils contaminated by petroleum hydrocarbons, as s h o w in a survey of 169
rernedial actions (Neely et al., 198 1). However, those techniques have showed limited
success when they were used to sites with complex soi1 and groundwater conditions
(Brown et al., 1986). Traditional remediation efforts at contaminated sites were
partiaily effective 54% of the time and completely successful only 16% of the time
(NeeIy et al., 198 1 ; Lee and Ward, 1985). Most of these treatrnent schemes were not
completely effective and did not oKer permanent solutions for containment or
remediation. Some methods might even create additional uncontrolled hazards.
Therefore, more efficient and economicai technologies are desued for improving the
remediation performance (Catallo and Portier, 1992).
1.2 Statement of Problems
Numerous sites exist where soil has been contaminated with petroleurn products
due to spills or leaking underground storage tanks. In order to help solve this problem,
a number of in-sihi remediation methods have been developed. One such method,
known as in-situ air stripping, injects air into subsurface soil below the lowest known
point of contamination. As clean air replaces the contaminant-saturated vapor that is
removed, the contaminant rmaining as a residuai liquid and dissolved in pore water
ail1 be volatilized in the k h air, seeking to re-establish equilibrium. Due to
vaporkation of contaminants, the vapor of mixed air and contaminants will begin to
nse through the soi1 matrix and migrate toward the surface.
Several laboratory experiments involving convective transport due to air flow
inside soil pores have been reported since 1980. Marley and Hoag (1984) used soi1
columns to measure the removai rate of gasoline from contaminated soil. They
reported higher than 99% rernoval o f gasoline initially present in a reasonably short
time. Rainwater et al. (1988) reported large-size soil column expenments to study the
volatilization mechanism in porous media and provided removal rate data of
hydrocarbon mixtures with preliminary modeling effort. They concluded that the
presence of the residual water in porous media significantly retarded the diffision of
the hydrocarbon vapor and slowed the removal process. Most of previous studies have
focused on movement and distribution of air through the aquifer in laboratory mode1
and in the field (Ji et al.. 1993, Johnson et al., 1999). Laboratory studies have been
performed only to investigate air Bow patterns and to evaluate the removal rates of
contaminants in both grave1 and sand (Semmer et al., 1996; Semmer and Reddy,
1998). However, the effects of system variables particularly the soil type, the regime of
air injection on the removal efficiency have not been systematicaily investigated.
Most of the previous enhanced-remediation methods were carried out by
pneumatic fracturing and thermal enhancement (EPA, 1994, Brown et al., 1986, Chao
and Ong, 1995, Ehlers et al., 1994, Johnson, 1998). With varied system pressure and
temperature, many subsuface media conditions will be changed. However, their
efficiencies are not satisfactory £tom both environmental and economic points of view.
More effective technologies are thus desired.
Electromagnetic vibration was used for desorption of CO and NO from metal
(Pt) surface (Schott and Racz, 2000). The technique cm help to prornote mass transfer
in reaction systems. However, there has been no application of this method to the field
of soil remediation.
Soi1 composition and contaminant distribution in many contaminated sites could
be complicated with various contents of sand and clay. The clay content is a critical
factor related to soil permeability, and hence contaminant removal. The traditional
enhancement techniques might not be directiy suitable for such complicated sites.
Consequently, development electromagnetic-vibration-enhanced air stripping
technology for enhanced soil remediation would be of value for bringing improved
environmental and economic efficiencies.
13 Objectives
The objectives of this research are:
1. To develop an electrornagnetic-vibration-enhanced air stripping technology
for cleaning up petroleum-contaminated sites where soil conditions are complex and
disadvantageous (e.g. impermeable).
2. To build up several scaled experimental systems for evaluating the
effectiveness of the proposed technology under various experimental conditions.
3. To develop a multivariate analysis approach for studying complicated
interrelationships among various factors that affect the removal efficiency.
Chapter 2
Literature Review
The problem related to contamination of groundwater and soil From leaking
underground storage tanks is recognized as a major environmental concem in the
world. Most of the leaked petroleum products will remain trapped in the groundwater
and soil, posing major threats to underground aquifers that provide drinking water for
the surrounding comrnunities. Consequently, a number of techniques for soil
remediation at petroleum exploration, production and processing sites have been
developed (Huang et al., 1999).
2.1 The Role of Air in Soi1 Remediation
Based on the technologies that have been developed and used in conventional
water and wastewater treatment and in rnining, oil, gas, and chemical process
industries, a number of processes and systems have been developed for in situ clean-up
of soil contarninated with petroleum hydrocarbons and other organic solvents.
These methods use physical, biological, themal, and chemical processes to
extract, degrade, detoxify and immobilize contaminants. Among thern, air plays an
important role in sorne soil remediation pmcesses.
2.1.1 Soi1 Vapor Extraction
One of the most popular physical methods using for soil remediation is soil
vapor extraction (SVE) for remediating volatile hydrocarbon contamination fkom the
soils. Air flow is induced through contaminated soil by applying a vacuum to vapor
extraction vents and creating a pressure gradient in the soil. As the soil vapor migrates
through the soi1 pores toward the extraction vents, VOCs are volatilized and
transported out of subsurface soil.
Several laboratory expenments involving convective transport due to air flow
inside soil pores have been reported since 1980. Before that time, research involving
soil gas movements was restncted to diffbsion transport. Laboratory research is often
perfomed with mal1 soil colurnns. Marley and Hoag (1984) and Baehr et al. (1989)
used soil columns to measure the removal rate of gasoline from contaminated soil.
They reported expenments on the removal rate of partially saturated gasoline in the
capillary fiinge above the water table by steady air flow. More than 99% removal of
gasoline initially present was observed in a reasonably short time. Aware, Inc. (1987)
conducted soil column experiments to evaluate the SVE process with various
contaminant conditions and soil types. They reported removal rates of 40 to 90% of the
initial amount of VOCs applied in less than 8 days of operation in the temperature
controlled environment. They concluded that there is the possibility of success in
contaminated soil cleaning with SVE process. Rainwater et al. (1988 a, b) reported
large-shed soil column experiments to study the volatilization rnechanism in porous
media and provided removal rate data of hydrocarbon mixtures with a preliminary
modeling effort. They concluded that the presence of the residual water in porous
media significantly retarded the diffision of the hydrocarbon vapor and slowed the
removal process. Brown et al. (1986; 1991) and Johnson et al. (1982) described a
closed monitored field scale expenment. Each of these studies provided evidence that
soil vapor extraction methods are effective for control of higher vapor pressure
components from contaminant residual saturation.
The performance of SVE system, based on the mass removal rate, the tirne
required to achieve cleanup goals, and the cost of cleanup have also been studied
(Ghuman, 1995). These performance parameten depend on physical and chemical
factors, such as the rate and pattern of air flow through the affected soil characteristic,
contaminant type and properties, and the degree of partitioning among the vapor,
liquid, dissolved, and adsorbed phases.
in examining the role of mass exchange between vapor and water phases, both
one-dimensional diffision and one-dimensional advection experhents were
conducted. Johnson et al. (1993) stated that the injected air always travels in small,
continuous and discrete air channels. Pankow et al. (1993) reported that in moderately
permeable soils (e-g., sandy soil) and at low air injection rates, stable channels of air
are formed. However, SVE effect is dependent on the pmperties of both the
contaminants and the soil (Boulding, 1995).
VOCs, such as BTEX can be removed fiom unsaturated (vadose zone) soils by
use of SVE (Ram, et al., 1993). High concentrations of garoline vapors become mobile
when air is injected into soil (Downey et al., 1995). in the remediation of gasoline-
contaminated soils, total effluent hydrocarbon concentration for an SVE system ranged
up to 1121 ppmv. corresponding to a hydrocarbon removal rate of about 1.68 Ib/h
(Felten et al., 1992). SVE alone could provide excellent removal of VOCs adsorbed to
unsatwated soils.
A DPE system was successfbl in remediating hydrocarbon-impacted clays and
contaminated groundwater at a former service station in northem California
(Dockstader, 1994). AAer 76 days of operation, the soil total petroleum hydrocarbon
(TPH) concentrations went from 2500 ppm to 100 ppm.
The most important property affecting removal rate of contaminant for DPE is
volatility. Hydrocarbon compounds with high volatility are more likely to be removed
by DPE than those with low volatility. The contaminants to be removed by DPE must
have relatively low water solubility and must be above the water table or, in the case of
light non-aqueous phase liquids (LNAPLs), floating on it and the soil moisture content
must be quite low (Wilson, 1995).
2.1.2 Air Sparging
Air sparging, also known as in situ air stripping and in situ volatilization. is a
process in which air is injected into the saturated zone below or within the areas of
contamination through a system of wells. As the injected air rises through the
formation, it may volatilize and biodegradation adsorbed VOCs in soils. Air sparging
is an innovative treatment technology that expands the remediation capabilities of SVE
to the saturated zone.
Most recently, system effects on VOCs removal fkom saturated soils and
groundwater using air sparging were presented (Reddy and Adams, 1997). Semrner
and Reddy (1998) investigated air flow patterns and the removal rates of toluene in
tests using fine grave1 and medium sand as representative soils in the laboratory. In
addition, Adams and Reddy (1997) studied the effect of grain size and distribution on
the removal of benzene using in-situ air sparging.
Rutherford and Johnson (1996) performed a laboratory study to determine how
process control changes affect oxygenation rates during air sparging. Elder and Benson
(1999) analyzed air channel formation, size, spacing, and tortuosity during air
sparging. It was found that no appreciable benefit was achieved through the use of
pulsed air injection when compared to continuous air injection.
Effect of flow rate changes and pulsing on the treaûnent of source zones by in
situ air sparging was studied and it was indicated that pulsing the air can improve the
long-term cumulative removal efficiency (Johnson et al.. 1999). Laboratory
expenments were conducted to observe flow patterns as a fùnction of porous media
size and air flow rate (Brooks and Mcginty, 1987) and to investigate the behavior of
dense non-aqueous phase Iiquids (DNAPLs) during air sparging (Adams and Reddy,
1997). The primary rnechanisrns for removing mass during air sparging are
volatilization and biodegradation (Hinchee, 1994).
Volatilkation is the dominant removal mechanisrn during the early stages of
sparging, and is dnven by a gradient in Gibbs fkee energy that develops between the
aqueous and gaseous phase contaminants (Weber, 1972). Biodegradation can be a
signi ficant m a s tram formation process during the later stages of sparging, but
removes much less mass than volatilization (Boenma et al., 1995).
Air sparging stimulates aerobic biodegradation by increasing the dissolved
oxygen concentration of the soil and groundwater (Johnson et al., 1993). For the
pulsed tests, Baker (1996) rneasured temporal changes in air saturation and water table
elevation. Baker found that pulsing did not change the location of air channels or the
size of the air plume. He concluded that air remains in the formation following shut
down, and that air-filled pores become preferential flow paths once sparging is
resumed. Thus, pulsing can cause mixing within the plume, but not necessarily re-
distribution of air.
Column tests to determine mass transfer rate during air sparging were conducted
by Semmer et al. (1996) and Chao and Ong (1995). The results indicated that greater
m a s removal was obtained in the coarse sand at low rates, mass removal increased
with injection rate for soil, and contaminants with higher Henry's law constant were
removed at faster rates.
However, applicability of air sparging is limited to cases involving low
groundwater table and loose sand formation. It is not recornrnended for low hydraulic
conductivity soils where it is difficult to monitor or control treatment progress and
completeness.
2.1 -3 Bioventing
Soi1 venting rnay be either passive (with no energy input) or active (Lyman et al.,
1990). Passive venting consists of perforated pipes sunk into the contaminated area and
active venting uses vacuum to the subsurface to volatilize and remove contaminant.
Contaminants exist in the vapor, liquid, and/or dissolved phase in the unsaturated zone
(Lyman et al., 1990). Contaminants in the vapor phase or volatilized contaminants may
be removed by this method.
Bioventing is an in situ remediation technology that uses indigenous
microorganisms to biodegrade organic constituents adsorbed to soils in the unsaturated
zone. Soils in the capillary ninge and the saturated zone are not affected. In bioventing,
the activities of the indigenous bactena are enhanced by introducing air flow into the
unsaturated zone (using extraction or injection wells) and, if necessary. by adding
nutrients.
When extraction wells are used for bioventing, the process is similar to soi1 vapor
extraction (SVE). However, while SVE removes constituents primady through
volatilization, bioventing systems promote biodegradation of constituents and minimize
volatilization (generally by using lower air 8ow rates than those for SVE). In practice,
some degree of volatilization and biodegradation occurs when either SVE or bioventing
is used.
In contrast to SVE, bioventing is not constrained by contaminant volatility and is
therefore applicable to contaminants with moderate to low volatility (Hinchee, 1994).
Moreover, bioventing is also weil suited for conditions where SVE's application rnay
lead to lengthy processes with low removal efficiencies. Cost analyses suggest that
bioventing can be more cost-effective than SVE, since treatrnent of the off-gas is
required for SVE (Crocetti et al., 1993; Reisinger et al., 1994).
By managing air flow rate, it should be possible to increase the rate of
degradation to 85% (Miller, 1990; Miller et al., 1991). Bioventing is becoming
increasingly popular in soil remediation for removing VOCs and semi-volatile organic
compounds (SVOCs) fiom the vadose zone (Crocetti et al., 1993). while supplying
oxygen to the soil to increase the bioremediation process. However, like SVET it is
ineffective when the porosity and transmissivity are low, such as in silt and clay soils
(Burke and Rhodes. 1995). There may be little capital investment initially for this
procedure, but it cm be expensive to monitor the site for regulatory compliance.
2.2 Enhanced Soi1 Remediation Technologies
Enhancement technologies should be considered when contarninants or soil
characteristics limit the effectiveness of soi1 remediation operation, or when
contarninants are present in saturated soil. By creating Fractures in the subsurface, it is
possible to enhance permeability to improve the flow of carrier fluids for contaminant
removal or deliver nutrients or reactive agents (Kidd, 1996). The following section will
describe some soil remediation enhancement methods.
2.2.1 HydrauliJPneumatic Fracturing Enhancement
There are two types of fracturing: hydraulic (water-based) and pneumatic
fracturing (air-based). The main difference is in the penetrating fluids. in soil
remediation, The pneumatic hcturing is more popularly applied due to its low
operation cost and no chernicd contaminants.
Pneurnatic hcturing involves injecting air into low pemeability soils to create
fracture, and thus increasing the permeability of the soil. A pilot study of the integrated
pneumatic hchuing systern demonstrated enhanced removal of BTEX fiom a
gasoline-contaminated, low pemeability soil formation. Fractunng improved
subsurface permeability by over 3 6 times and established extra charnels (Venkatrarnan
et ai., 1995).
Pneumatic flacturing test was perfonned at Air Forced Base, Oklahoma City,
resulted in significantly hproved formation permeability by enhancing secondary
permeability and promoting removal of excess soi1 moisture fiom the unsaturated
zone. Post-fracture air flow was 500 to 1700 times after the treatment (Anderson et al.,
1995).
2-32 Themal Enhancement
Themal enhancement for soil remediation involves transferring heat to the
subsurface to increase the vapor pressure of VOCs or SVOCs or to increase air
permeability in the subsurface formation by drying it out. Thermal enhancement
technologies are normally used with hot air, hot water and stearn injection, radio
fiequency heating, electrical resistance heating.
Steam, hot air and hot water injection rely on contact between the injected fluids
and the contaminant for the transfer of heat to and recovery of the contaminant. Steam
injection will displace mobile contarninants in nont of the steam as well as vaporize
volatile residud contaminants, and therefore can recover volatile contaminants in both
the liquids and vapor phase. Past applications of s t e m injection technologies have
focused primarily on moving and vaponzing free petroleum product in the subsurface
toward extraction wells for removal. Tests have show that 99.5% of the
petrochemicals polluting soil and groundwater were removed by steam injection
(Baum, 1988).
Hot air injection has been used to increase the vapor pressure of VOCs and
SVOCs in the vadose zone, thus decreasing remediation tirne and increasing
contaminant removal. Normally, hot air injection is used to recover contaminants only
in the vapor phases. Hot water injection generally recovers contaminants only in the
liquid phase. Electrical energy has been applied to the soil in the low fiequency range
used for electricai power as well as in the radio frequency range, which have pnmarily
focused on increasing mass removal rates of contaminants in low penneability soil
(U.S.EPA, 1994). With radio frequency heating, soil is heated to high temperatures,
thereby desorbing most organic contaminants (Edesterin et al., 1994). When the
temperature is 150°C, 95% to 99% of VOCs and 90% of the SVOCs can be rernoved
(Johns and Nyer, 1996).
However, with increasing temperature, soil properties, such as microbial
populations, will be changed. Operation cost of thermal process is higher than other
processes.
2.3 Parameters Affecting Volatilhation
During physical operation, for volatilization from soil to occur, organic
compounds must move through a complex structure of solid particles and void spaces
io soi1 sudace (Bell et al., 1987). Affecting volatilization of organics in a soi1 matrix
include (1) contaminant physical properties, such as Henry's law constant. vapor
pressure, and contaminant solubility in soil organic matrix (Ehrenfeld el al., 1986). (2)
Soil physical properties, such as soil texture, water content and soil temperature; (3)
Enhanced process, such as air injection pressure or air flow rate and related to
transfemng energy into subsurface. Among them, the most important factors affecting
soil volatilization are soil texture, soil moisture and contaminant properties and air
injection pressure under limited environmental temperature ranges.
2.3.1 Soil Texture
The texture of a soil refers to the proportions of various particles size groups in
the soi1 rnass, typically caNed sana silt and clay (Devitt et al., 1987). Clay soils have
high voiumetric water content at saturation than medium-textured or coarse soils. As
the clay content increases, the water-holding capacity and the exchange capacity
increase, while the air-filled porosity and the rate of vapor dimision decrease. A high
clay content acts as a retarding layer to the vertical flux of VOCs. Clayey soils tend to
have a more unifom pore size distribution than do corner soils (Hillel, 1971), whereas
the coane soils tend to have large mean size, which will transfer fluids fmer under
saturated and unsaturated conditions.
Soil type affects the tirne of transit of a contaminant, as well as the potential for
biodegradation. It also influences the mobility of microorganisms ihrough the
subsurface. Bactena generally do not move farther in the fine-textured soil, but they can
travel much larger distances in coarse-textured or fractured materials (Romero, 1970).
Soil type has been found to have a strong effect on the rate of contaminant
removal fiom soils (de Percin, 1991; Lighty et al., 1988). Adsorption ont0 glas beads
and silica sands does not appear to fonn tight bonds; the adsorption is readily revenible
even at low temperatures. Experiments performed by Lighty et al. (1988) showed that
essential al1 of the xylene adsorbed by silica sands was removed rapidly. However, for
reactive media, the desorption process is much slower, which may be caused by
strongly adsorbed monolayer on the particle surface (Lighty et al., 1988; Tognotti et al.,
1991) or slow diffision from maIl inner pores to the surface of the particle (Keyes and
Silcox, 1994).
Soil composition influences infiltration rate and pemeability, water holding
capacity, and adsorption capacity for various waste components (Homick, 1983). Clay
soils have a greater capacity for physicochemical attenuation of contarninants than
coarse sands or fissured rock (Pye and PatrÎck, 1983). A predominance of clay and d t
particles in h e texhired soils can result in very srna11 pore sizes, with a slow infiltration
rate (Hornick, 1983). Coarse soils of sand and grave1 have large intercomecting pores
and allow rapid water and air rnovement.
A continuous air phase is established when it occupies approximately 80% of the
available pore spaces (Frendlund and Rahardio, 1994). The available pore volume or
porosity is dependent on grain size distribution of the soi1 matrix. As well, the porosity
can be an important controlling factor on permeability of the soi1 matrix. Clayey soils in
general have higher porosity but lower penneability than that of sandy soils.
Soil penneability is one of the most important variables for making possible the
delivery of air to contaminated regions. Diffision in low penneability soils plays an
important role in natural replacement of oxygen. However, clayey soils tend to retain
higher rnoisture content, which also inhibits air and contaminant vapor difision.
2.3.2 Soil Moisture
Soil moisture content provides an indication of VOCs removal efficiency and
possibly soil VOCs residuals (Mcdevitt et al., 1987). Soil moisture is important in
deterrnining the extent of adsorption of neutral, non-polar molecules like most VOCs
onto soil surface (Poe, 1998). VOCs are strongly adsorbed to soils at low moisture
contents. They are displaced fiom their adsorption sites as soi1 moisture increases, as a
result of competition for adsorption sites on the polar mineral surface fkom polar water
molecules. It is also shown that it will take longer to cleanup soils with high moisture
content than similar soils with lower moisture content. Dry air might be injected into
soils to reduce soil moisture content and produce tensiometric, or dry, barrier to
contain liquid-phase transport (Thomson et al., 1996). If large amounts of water were
withdrawn fiom the soil with the gaseous steam and contarninants during SVE, the
pneumatic soil permeability could change, the temperature could &op d o m to 10°C
(Garcia-Hemo et al., 1994). Thus, with decreasing temperature, the vapor pressure of
contaminant would be decreased as well as removal efficiency decreases.
2.3.3 Air Injection Pressure or Flow Rate
Air injection pressures are govmed by the static water head above the injection
point, the required air entry pressure of the saturated soils, and the air injection flow
rate. The lowest effective air injection pressure will correspond to the pressure required
to maintain a minimum continuous air flow through the saturated zone. Higher
pressures will produce higher air injection flow rates, and due to the random
distribution of air entry pressure in the soil, will likely produce additional air channels.
Ji et al. (1993) showed air travels through the saturated zone air channels that are
continuous and stable when air flow is maintained. Furthemore, when air flow rate
increases, existing air channels will be enlarged and few new air channels form.
The higher air injection pressures required in fine-grained soils cm cause the
formation of significant subsurface gas pockets. A gas pocket is essentially an
unsaturated volume that expands fiom the air injection point during the injection
process until pressure within the pocket is SuffiCient to overcome the vertical air entry
pressure of the overlying soils. Too high an air injection pressure may create fractures
in the injection point, which will result in a loss of system efficiency or in some case
rnay actually improve channel distribution.
Chao and Ong (1995) reported that greater mass removal was obtained in the
corne sand at low flow rates. Mass removai increased with injection rate for both
soils. However, as the flow rate was increased to approximately 50 Umin, the
difference in mass removal rate between coarse and fine soil became negligible. Chao
and Ong (1995) also reported that chernicals with higher Henry's law constants are
removed faster.
Air flow rates that are typically used in the field are in the range of 3 to 20 cubic
feet per minute. Pulsing of air flow into injection point is considered to provide a better
distribution of air flow channels and ground water mixing over the project duration.
2.3.4 Vapor Pressure and Boiling Point
Vapor pressure is a measurement of the equilibrium between the liquid and
vapor phases of a pure compound (Eckenfelder et al., 1993). Thus, at spill sites,
organic compounds with high vapor pressures would be expected to be present to some
degree in the vapor phase of soil pores. Highly volatile fuels, such as gasoline,
evaporate relatively rapidly, even in subsoil, forming an envelope of hydrocarbon
vapors around the core of the spill.
The major contaminant property affecting volatilization is its vapor pressure in
the soil air space (Shs, 1985). The vapor pressure of soil organic compound is the
most important factor at low water content (presumably due to the vapor-phase
dimision), while with greater water content, aqueous-phase diffision becomes most
important (Ehlers et al., 1969a & b). The vapor pressure of an organic compound in the
soil increases to an equilibrium vaiue that corresponds to its vapor pressure (Bell et al.,
1987). This is due to result of increasing concentrations of the cornpound in the soil
until there is saturation of adsorption sites on the soil minera1 and organic fraction
surfaces. Vapor pressure increases with increasing temperature. Several inches below
topsoil, the vapor pressure can drop below saturation, because of higher gas mixing
and exchange rates. The presence of electmlytes (often concentrated near the soil
surface from evaporation) cm also lower the vapor pressure.
The contaminants with the lowest boiling points also generally have lower heat
of vaponzation; thus these contaminants are relatively easy to volatilize. Normally, the
lower the boiling point, the higher the vapor pressure. Compounds with higher boiling
points have lower vapor pressure at ambient temperature and higher heat of
vaponzation; thus more energy is required to convert them to the gaseous phase.
Laboratory experiments have show that vaponzation of even highly volatile
compounds can cause a measurable decrease in the temperature of the system
(Lingineni and Dhir, 1992).
Reducing the vapor pressure in the soi1 pores will have a significant efFect on the
adsorption of organic vapors (Chiou and Shoup 1995). The minerai fraction of a dry or
slightly hydrated soil is a powerful adsorbent for organic vapors at lower vapor
pressure. However, some other properties of contaminant, such as Henry's Iaw
constant, water solubility, molecular weight, boiling point and viscosity also play an
important role during soi1 remediation.
2.4 Electromagnetic Wave Vibration and Application
Electromagnetic waves can be characterized by their wavelength, frequency, or
energy. These three parameters are interrelated. The fiequency is measured in cycles
per second, or hertz (Hz). The shorter the wavelength, the higher the frequency.
2.4.1 Electromagnetic Wave Phenornena
The electromagnetic radiation i ncludes radio waves, microwaves, in frared
radiation, ultraviolet rays, X-rays, and gamma rays. The only difference between them
is their wavelength, which is directly related to the amount of energy the waves carry.
The shorter the wavelength of the radiation, the higher the energy.
Radio waves are used to transmit radio and television signals. Radio waves have
wavelengths that range from less than a centimeter to tens or even hundreds of meters.
Microwave wavelengths range kom approximately one millimeter (the thickness
of a pencil lead) to thirty centimeters (about twelve inches). Ln a microwave oven, the
radio waves gmerated are tuned to fiequacies that cm be absorbed by the food. The
food absorbs the energy and gets warmer.
Infiared is the region of the electromagnetic spectnim that extends fiom the
visible region to about one millimeter (in wavelength). m a r e d waves include thermal
radiation.
Ultraviolet radiation has a range of wavelengths from 400 billionths of a meter to
about 10 billionths of a meter. Sunlight contains ultraviolet waves. Most of these are
blocked by ozone in the Earth's upper atmosphere.
X-rays are high energy waves which have great penetrating power and are used
extensively in medical applications and in inspecting welds. The wavelength range is
from about ten billionths of a meter to about 10 trillionths of a meter.
Gamma rays have wavelengths of less than about ten trillionths of a meter. They
are more penetrating than X-rays. Gamma rays are generated by radioactive atoms and
in nuclear explosions, and are used in many medicai applications.
An electromagnetic wave consists of very small packets of energy called
photons. The energy in each packet or photon is directly proportional to the frequency
of the wave: The higher the frequency, the larger the amount of energy in each photon.
2.4.2.Application of Electromagnetic Vibration
By application of recent advances in the generation of ultra-fast laser pulses,
researchers have now obtained direct measuements of the vibrational lifetime of
adsorbates on metal d a c e s (Budde et al., 1993). In its experiments, an adsorbate
vibration is resonantly excited by a strong ultrafast laser pulse at the appropriate
Uifrared kquency. Budde et ai. (1993) desorbed NO molecules fiom a Pd (1 11) surface
by laser pulses of 400s duration. The application of electromagnetic wave vibration is
growing continuously in the field of surface science. Tabulina et al. (1993) studied the
influence of static and aiternahg magnetic fields and of vibrating agitation of the
nickel-plating process in hydrophosphite solutions and showed that vibrating agitation
has a positive effect on the nickel-plating process within a narrow fiequency range, and
decreases the rate of Ni-P plating. The desorption processes of NO and CO from Pt
(1 11) and Pt (001) surface were described by a mode1 of substrate-mediated excitation
proposed by Gadzuk et ai. (1990). Montroll (1950) showed that vibrational specific heat
had an additional term proportional to the surface area of the crystal. The application of
electromagnetic wave vibration in soi1 remediation has not been reported.
2.5 Analytical Methods
The USEPA has developed a series of matrix-specific methods for VOC analysis
(e.g. EPA Methods 602, 624, and 8240). Although there are minor differences among
the methods, al1 employ dynamic headspace or purge and trap technique to separation
for gas chromatograph andysis was normally accomplished through a non-polar
packed column. Photo ionization detector (PD) and flame ionization detector (FID)
were often used for detecting BTEX and other volatile compounds.
An alternative solvent-ke extraction procedure emplo ying solid phase micro-
extraction (SPME) of organic compounds frorn aqueous sarnples was reported. This
new extraction rnethod integrattes samplhg, extraction, concentration, and sarnple
introduction Uito a single step (Rong, 1996). There is no simple and direct method to
determine BTEX concenbations in the soi1 samples contarninated by gasoline, because
of low boiling points and very volatile nature of BTEX.
When attempts were made to use experimentaliy developed equilibnurn models
to predict environmental VOC concentrations in a vapor and the buik soi1 matrix,
discrepancies of more than one order of magnitude have resulted between theoretical
and measured values (Smith et al., 1990). Similarly, most studies dealing solely with
environmental samples have failed to demonstrate significant correlations between
VOC concentrations in soil vapor and those in collected bulk or discrete soil samples
(Sextro, 1996). The major problem is the use of inadequate sampling procedures. For
example. current soil sampling and handling methods used for VOC characterization
are likely to underestimate their concentrations because of losses fkom volatilkation
between the time of collection and the time of sample analysis (Hewitt, 1995).
2.6 Methods for Experimental Design and Result Analysis
Fractionai factonal design is arnong the most cornmonly used methods for
designing experiments. Many successful applications of this method in the quest of
industrial quality and productivity are recent testimony to its importance. A key
question in selecting such desigos is how to develop a good criterion for it. It has been a
standard practice to choose a fiactional factorial design with maximum resolution. Since
desips with the same resolution are not equally go04 a more refined criterion cailed
minimum aberration was introduced by Fnes and Hunter (1980). When the
expenrnenter has little knowledge about the relative sizes of the factorial effects, the
minimum aberration criterion selects designs with good overall properties.
When designing sequential NO-level Fractional factorial experiments, there is a
wide choice of designs îhat could be used at each stage. In some designs, one of the
facton is fixed at a particular level after the first set of experiments is completed. This
may allow important effects to be estimated in fewer runs than would the standard
sequences of designs. The extensions to fixing more than one factor and to factors with
more than two levels were discussed by Gihour and Mead (1 996).
Luna et al. (1996) applied a factorial design to determine the stability of
methylmercury (MMHg) standard solutions in water. To detemine the effects of some
variables on the stability of MMHg standard solutions, a 2' factorial design was used
with a first-order model. It was concluded chat the factorial design was a tool that
allowed one to find, in a rapid and efficient way, the individual variables and
corresponding interactions îhat may influence the long-terni stability of MMHg
solutions.
A study of colurnn leaching to remove iron fiom quartz sands was conducted
using a complete factorial design (Ubaldini et al., 1996). The facton assumed to affect
dissolution of iron, such as temperature, oxalic acid concentration, pH, and flow rate.
were studied with a î4 full factorial design in order to assess the main effects and the
interactions among the facton.
The best material for use in analysis of dry atrnospheric mercury deposits was
determincd with a 252 hctional factonai design (Tong, 1998). Four materials and five
factors (two levels for each factor) were considered. By comparing results of the
fractional factorial design with a complete factorial design, it was shown that the
hctional approach was effective in reflecting interactions arnong different factors in
the study system. The successfbl experimental design for bioremediation (Wu, 2000) in
which two z6" fiactionai factorial designs were implemented for the experiments was
involved six factors (two levels for each). The main factors that have significant effects
on the bioremediation rate were identified. A response surface mode1 was then
formulated based on the factorial analysis results, reflecting interrelationships between
the system conditions and the biodegradation rates.
2.7 Literahire Review Summary
Most previous enhanced-remediation methods were carried out at relatively high
air flow rates (higher injection pressure for fiactunng) for the purpose of increasing
recovery rate. There have been not previous studies using electromagnetic vibration as
an enhanced process for soil remediation. The electromagnetic vibration was mainly
used for desorping NO and CO fiom metal surface. No application of electromagnetic
vibration to soil rernediation was reported. Factoriai design has been widely used in
expetllnental design and multivariate analysis. It can be extended to study of
remediation-process design and analysis.
Chapter 3
Materials and Methodology
Laboratory experiments in packed column were conducted to evduate both the
rernoval of BTEX by continuous air injection and the fate of toluene throughout the process
of electromagnetic-vibration-enhanced air stripping.
3.1 Material and Instrument
3.1.1 Material Preparation
(1) Soi1
To investigate the effect of the composition of soi1 on the efficiency of continuous air
injection and electromagnetic-vibration-enhanced air stripping system, a series of soils
were used by mixing fine sands with different content of clay (40%, 50%, 60% and 70%).
(2) Sand
Based on the manual of test sieving methods (USA Standard Sieve Series
Specification - E 11, E161, and E 323, 1998), the commercial sand was screened with a
#50 U.S.A. standard sieve. The particles passing through the sieve had diameters below
0.30 mm. Figure 3.1 shows the size distribution of the sand with 62% wt of the sand being
in the range of 0.3 to 0.25 mm in diameter and the rest being less than 0.25 mm in diameter.
(3) Clay
The clay (nom the Canadian Clay Products Inc.) was used in the experiments and had
the following physical properties:
Specific gravity: 2.5 @cm3;
pH value: 9
Particle diameter: < 0.20 mm
(4) Contaminant
Reagent grade benzene, toluene, ethylbenzene and (m+p)-xylene were used as the
expenmental contaminants for al1 continuous air injection tests.
Gasoline was used as the contaminant for those experiments involving
electromagnetic vibration. It was purchased from a commercial gas station (ESSO). The
gasoline had a dynamic viscosity of 1.71 Centipoise (cp) and a density of 0.73 @mL. The
concentrations of benzene, toluene, ethylbenzene, and (m+p)-xylene (BTEX) in gasoline
were analyzed using a gas chrornatograph (GC) and the results of the analyses are presented
in Table 3.1.
( 5 ) Reagent
Reagent grade methano1 was used to extract BTEX from the soil.
Table.3.1 BTEX Concentrations in Gasoline
Compound Concentration (wt) Concentration (wt)@
Benzene
Toluene
Ethylbenzene
(m+p)-Xylene
O-X ylene
Source: The State o f California, Leaking Underground Fuel Tank Field Manual, Academic Press, Orlando, FL, 1987.
A micro-processor controlled pump ( ~ a s t e r t l e x ~ ~ , mode1 7305-40), a soap film fîow
rate meter (Optiflow 650, Humonics Inc, U.S.A.), a DMA-4500 density meter, a balance
(Boulder Co., U. S. A. Max = 500 g and d = 0.001 g), and a Varian GC (CP-3800) were
used in this study.
3.2 Experimental Apparatus
There are a nurnber of routes one cm follow to gain a better understanding of how
process changes impact the performance of the in situ continuous air injection and
electromagnetic-vibration-enhanced air stripping. Field-scale studies, physical mode1
experiments, statistical analysis and numerical simulations were among the options. Each
had its advantages and limitations. In this research, scaled physical-modeling studies were
conducted, because:
( 1) Field-scale studies involved in Iengthy process and associated high costs, so that
the range of conditions that can be practically studied is limited;
(2) Proven numerical simulators have yet to be developed; and
(3) Relative to actual field studies, physical models can be more easily rnonitored and
characterized, and the expenments are of much shorter duration (Johnson et al., 1999).
3.2.1 Electmrnagnetic Vibration Generator
Two electromechanical reiays were comected together to generate electromagnetic
vibration waves. The electrornagnetic vibration facility had a direct current resistance of
284 ohm (a), electric current of 0.159 arnpere (A) in electric circuit as measured by a
heavy duty digital multi-meter (Model: HDI ISB, Wavetek Corp, USA) and a vibration
frequency of 60 Hz.
3.2.2 Expenmental Set-up for Conhuous Air Injection Pmcess
The schematic of the experimental set-up for continuous air injection is shown in
Figure 3.2. The holder consisted of two Teflon caps and a glass core holder with inside
dimensions of 5 cm in length and 1 cm in diameter. The soi1 was packed in a glas column.
The column was placed in a heat exchanger that was connected to a water bath for keeping
a stable temperature. The injection line consisted of a steel tube, needle valves, quick
connects (fiom Regina Valve & Fitting Ltd.), and a micro-processor controlled pump
( ~ a s t e r f l e x ~ , mode1 7305-40). The pump was used to supply stable air (4 mumin) and
calibrated with a soap film flow rate meter (Optiflow 650, Humonics Inc., U.S.A.). A
balance (Boulder Co., U. S. A, Max = 500 g and d = 0.001 g) was used to measure weight
difference. The outlet of the column was c o ~ e c t e d with another glass column, which was
packed with active carbon for adsorbing contaminant and purifjmg air.
3.2.3 Experimental Set-up for Electromagnetic-Vibration-Enhanced Air Stripping
The schematic of expenmental set-up for electromagnetic-vibration-enhanced air
sûipping system is shown in Figure 3.3. In this experimentai set-up, a stainless steel
cylindncal core holder column was used. The inside dimensions of the core holder were 45
cm in length and 5.5 cm in diameter. The injection line consisted of an au compressor, an
air desiccator, an air pressure gauge, a flow meter, a needle valve and a stainless steel tube
which was comected to a Bange cap. An air distributor was attached to the inlet flange. A
filter screen (#IO0 U.S.A. standard stainless mesh attached with a filter cloth) was placed in
the inlet of the column and a Teflon O-ring was put between the air distributor and the filter
screen.
The outlet of the column was welded with a stainless steel tube to prevent any VOC
leakage to the aünosphere. The outlet portion included a needle valve, an air pressure
gauge, a flow meter, a heat exchanger c o ~ e c t e d with water bath, a sarnphg point and a
cleaning system packed with activated carbon for adsorbing contaminant vapor and
purifying outflow air.
After the flange (together with the air distributor), Teflon O-ring and filter screen
were rernoved, a filter screen (#IO0 U.S.A. standard stainless mesh attached with a filter
cloth) was firstly placed inside the outlet of the column. Secondly, the test soi1 mixed with
water and gasoline was carefully placed into the column; and a second filter screen (#IO0
U.S.A. standard stainless mesh), a Teflon O-ring and a flange were placed at the inlet of the
c o i m . The flange was tightened up with a torque wrench. The electromagnetic generator
was fixed on a cylindricai core holder.
3 3 Experimental Method
3.3.1 Continuous Au injection
Tests of continuous air injection to remove benzene, toluene, ethylbenzene, (m+p)-
xylene in soils were conducted with different moisture contents, soil types and adsorbing
durations. The following experimental procedures were adopted:
(1) Weigh the empty glas column and the two Teflon caps by a balance;
(2) Mix sand, water and clay in the column according to the required proportions and
then weigh the loaded glass column together with two Teflon caps on the balance. This
weight was denoted as wo:
(3) Use a 50-mL gas tight syringe to add benzene, toluene, ethylbenzene, and (m+p)-
xylene separately into different core holders till the inside soil having required proportions.
Then measure the total weight of glass column, the two TeBon caps and the BTEX
compounds (Wo);
(4) Place the colurnn on a continuous air stripping set up, connect it with an air line.
and use the balance to weigh the loaded column (W,) at different time stages.
(5) Calculate cumulative removal efficiency (RE) using the following equation:
w here:
W, - W. is weight of contaminants leR in the column, mg.
Wo - wo is the initial contaminant weight, mg.
3 -3 -2 Electromagnetic-Vibration-Enhanced Air Stripping
To study the effects of electromagnetic-vibration-enhanced air injection on removal
of toluene in columns with different soil types, gasoline contents and air injection
pressures, the following experirnental procedures were employed:
(1) Ln the outlet of the column, a stainless steel mesh filter with a filter cloth was
included to prevent the soil from escaping and to ensure a uni form axial flow condition.
(2) The contaminated soils were packed in a cylindrical core holder according to
ASTM-D558 standard procedure (ASTM, 1986). The soils were carefully placed into the
column to avoid any segregation, density variation, or channeling within the column. The
column had a soil packed section being 37 cm long in the middle, and two additional
sections at the inlet and outlet ends. The section at the inlet end was filled with sand for
better air distribution, while that at the outlet end was a stainless mesh filter with filter
cloth.
(3) M e r finishing soi1 packing, sand @article size = 0.3 - 0.43 mm), the stainless
steel mesh filter, the Teflon O-ring and the flange including the air distribution groove were
put on the inlet of the column for injecting air homogeneously and for ensunng a unifom
axial flow condition.
(4) The colurnn for electromagnetic-vibration-enhanced air stripping was sealed for 8
hours to ensure that the contaminants were adequately adsorbed by soil.
(5) Switch on air supply and power, adjust air pressure and flow rate, take gas
sampies (for being analyzed by GC) nom the sampling point, and record the initial time.
(6) Mer finishing the experimenf use a sampler to get soil samples in the middle and
the two ends of the column to fil1 into 22ml headspace bottles for sample analysis.
(7) The cumulative removal efficiency (RE) was calculated using the following
equation:
RE = - y xKN% w , + R
where:
W, is the weight of effluent contaminant, mg.
R is the weight of residuai contaminant in soil, mg.
3.4 Sampling Method
3.4.1 Continuous Air injection
(1) Sample Preparation
In the glas column, the clay and sand were weighed precisely. Distilled water was
added into the sand to get different moisture contents, and then the sand and clay were
mixed at required ratios to f o m different soil types. The soi1 was weighed and imrnediately
"contaminated" with a BTEX compound. Then the column was seaied shacked by hand for
homogeneous contaminant distribution in the soil.
(2) Sample Preservation
The column containing contaminated soil was sealed and placed in the continuous air
stripping system for different durations (with sufficient adsorption time). During the
experiment, the leakage should be tested using leakage detector in al1 the connection parts
for tubes and valves. Blank experiment (with non-contaminated soil) was camied out at the
same time to subtract weight of water evaporated from the systern.
(3) Frequency of Sample Analysis
The variations of in column weights were measured every 4 hours.
3.4.2 Electrornagnetic-Vibration-Enhanced Air Stripping
( 1) Sample Preparation
In the sealed container, the clay and sand were weighed precisely. Distilled water was
added into the sand, which was then mixed with the clay at required proportions to get
different soil types and soi1 moishue contents. The soil was weighed and irnmediately
"contaminated" with gasoline of different weights. The soil was then agitated in the sealed
container (for exactly 5 minutes), and packed uito a stainless steel column.
(2) Effluent Sample Analysis
Samples of effluent air from the column were taken directly by a gas-tight
chromatograph syringe and injected into the Varian 3800 GC equipped with a FID for
analyzing toluene concentrations.
(3) Soit Sample Anaiysis
After nnishing experiment, soil samples were taken fiom middle and the two ends of
column, and then put into gas-tight bottles for analyzing toluene concentrations in soi1
vapor and soil rnatrix.
(4) Sample Preservation
The column containing contarninated soils was sealed and placed in the
electromagnetic-vibration-enhanced air stripping system for 8 hours to ensure sufficient
adsorption time. A leakage detector was used to test leakage.
(5) Test Duration
In the first hour of the tests, samples were collected every 15 minutes. After that,
samples were collected with time intervals of 30 minutes.
3.5 Aoalytical Method
3 S. 1 Toluene Vapor Analysis
A Varian mode1 CP-3800 GC equipped with a flame ionization detector (FID). a
photo ionization detector (PD), and a Chrompack WCOT fusedsilica 0.53 mm x 30 m
capillary column were used for analyzing contaminant contents in al1 gaseous vapon. The
GC was controlled by a computer system. The initial oven temperature was programmed at
6S°C. From 6S°C, the oven temperature was increased to 135°C at a rate of 10°C per
minute. The oven temperature was held at 135 O C for 5 minutes and temperatures of the
injector port and the detector were maintained at 250 OC and 200 OC during that time,
respectively. Helium, at an initial flow of 5.5 mL per minute, served as the carrier gas.
Hydrogen and air were used for detector flame with both of their pressures being set at 60
psi and the total mn time being 13 minutes.
Toluene concentrations within air samples from the electrornagnetic-vibration-
enhanced air stripping system was measured. A multi-p0ir.t calibration curve had been
prepared for detemining the arnounts of toluene in the sarnples. A standard caiibration
curve was obtained by taking the integrated area for each standard and linearly regressing
the values. The standard curve is shown in Figure 3.4.
3.5.2 Analysis of Toluene in Soils
Soi1 samples were taken from the column and injected into a 22-mL Varian
headspace bottle. First, the soil vapor was anaiped according to the method discussed in
section 3.4.1, and then the vapor was removed from the bottle through a 20-mL gas-tight
syringe. Methanol was used to extract soil and the contaminant concentration in methanol
was analyzed. Thus, the total of the above two concentration values was the actual toluene
concentration in soil. The GC was also used for analyzing contaminant concentration in
liquid.
The initial GC oven temperature was programmed at 6S°C. From 6S°C, the oven
temperature was increased to 135'C at a rate of 10°C per minute. The oven temperature was
held at 135 O C for 8.5 minutes, and temperatures of the injector port and the detector were
maintained at 250 OC and 200 OC during that tirne, respectively. Helium served as the
carrier gas with a flow rate of 5.5 W m i n , hydrogen and air were used for detector flarne
with both pressures set at 60 psi, and reagent grade methylene chlonde was used as the
solvent. The total run time was 15 minutes. A standard caiibration curve was obtained by
taking the integrated area for each standard and linearly regressing the values. The standard
c w e is shom in Figure 3.5.
3.5.3 Data Analysis
Graphs of BTEX removal efficiency versus time were constnicted based on data
obtained from the experiments. A 2' Full factorial design was used to determine whether or
not electromagnetic-vibration influenced toluene removal efficiency. The details are
discussed in Chapter 5.
O 50 100 150 200 250 300 350 400 450
Toluene Concentration (ppm)
Figure 3.4 Standard Calibration Curve for Toluene Vapor Analysis
1 OOOOOO
500000
O
O 50 100 150 200 250 300 350 400 450 500
Toluene Concentration (ppm)
Figure 3.5 Standard Calibration Curve for Toiuene Analysis in SoiIs
Chapter 4
Method of Statistical Analysis
The application of statistical methods to the electromagnetic-vibration-enhanced air
stripping studies included two aspects. The experiments were designed based on the
principle of factonal analysis. Then, based on the qerimental results, a modi fied response
surface model was developed to identify factors that had strong influences on the toluene
removal efficiency.
4.1 Introduction
Many expenmental variables are believed to have influences on the experimental
result, and it is desirable to know how these variables exert their influences. Interactive
effects are common when the reaction temperature is varîed. together with other factors that
may influence the kinetics of a reaction. To cl&@ such effects, it will be necessary to
determine the direct influence of the experimental variables as well as their interactive
eflects. For this, two-level factonal design is an appropriate tool.
Many experiments involve studies of the effects of two or more factors. It can be
shown that, in general, factorial designs are most efficient for this type of studies. A
factorial design is m a t to investigate possible combinations of the levels of the factors in
each complete trial or replication of the expenment.
The idea of a factorial design is to arrange the experiments in such a way that the
variation in response obtained with different settings from experimental factors can be
traced back to the variations of the factors. By proper arrangement of the factor settings, it
will be possible to determine the influence of the variation of each factor on the response in
the presence of simultaneous variations of al1 the other facton. Al1 these effects can be
detedned independently of each other. This means that the estimated value of any effect
does not depend on the estimated value of any other effects. These designs are of
importance for a number of reasons:
(1) They require relatively few mns per factor studied; and although they are unable
to explore fully a wide region in the factor space, they can indicate major trends and so
detemine a promising direction for furthet expenmentation.
(2) When a more local exploration is needed, they cm be suitably augmented to forni
composite designs.
(3) The interpretation of the observations produced by the designs can proceed
largely by using common sense and elementary arithmetic.
To allow the experimental erron to be anaiyzed by known statistical probability
distributions, such as normal distribution, t distribution and f distribution. the following
assumptions as to the experimental erron are made:
(1) The experimental errors should be independent, i.e. the disturbances leading to the
errors should occur independently of each other between expenmental runs.
(2) The variance of the experimental errors, 02, should be constant in the
experirnental domain.
However, a system can be influenced by disturbances which are not random and may
produce systematic errors. For example. as experimental skill of a researcher is improved
over time, the experimental erron will be gradually reduced. There is always a risk that the
experirnental result may be influenced by non-random time-dependent erroa.
Randomization of sequence of test nins protects against unknown or unrneasured sources of
possible bias. Randomization also helps validate the assumptions needed to apply certain
statistical techniques. This means that the order of executing the experimental runs should
be randomized; and the order of ana1yzing samples should also be randomized. These
precautions wili break time-dependent phenornena and transfomi systematic erron into
random errors.
4.3 Variables
In this study, four variables with two Ievels were considered. They were air injection
pressure, clay content in the soil, gasoline concentration and presence or absence of
electromagnetic vibration. For each experimental group, a full 2" factorial design would
need 16 experiments. Table 4.1 shows the design matrix of a two-level full factorial design.
Table 4.2 lists the design variables. Let +1 and -1 represents a higher and a lower level,
respectively. The four variables were denoted as follows:
s = clay content (+ 1, - 1 );
x2 = air pressure (+ 1, - 1 );
x3 = gasoline concentration (+ 1, - I );
.rd = electromagnetic vibration frequency (+ 1, -1 ).
4.4 Response Surface Mode1
Factorial designs estimate not only main effects of individual variables but also their
interactions. The measurement of interaction effect of AxB is defined as a half of the
difference of the effects of A when they are determined with factor B on its higher and
lower levels, respectively:
I AB = $, - A , )
w here:
AB+ is the effect of factor A with B at its higher level;
AB- is the effect of factor A with B at its lower level;
AB is interaction effect A and B.
Table 4.1 Full Factorial Design of Four Variables at Two Levels
Test No. x, (Clay) x2 (Air pressure) x3 (Gasoline) x4 (Vibration )
1 -1 -1 -1 -1
2 +1 -1 -1 -1
3 -1 + I -1 -1
4 +1 + l -1 - 1
5 -1 - 1 +1 - 1
6 + I -1 +l - 1
7 -1 +1 + 1 - 1
8 +1 + 1 +1 -1
9 -1 -1 -1 +1
IO +l -1 -1 + I
I l -1 + I -1 - 1
12 +1 +1 -1 -1
13 -1 -1 + 1 T 1
14 +l -1 + 1 +1
15 -1 +1 + l + i
16 + I +1 + l - 1
The significance of effects may be judged by (a) an estimate of variance obtained
from higher order interactions; and (b) by plotting effects on normal probability paper. The
presence of an interaction effect AB means that the influence of changing factor A will
depend on the setting of factor B. This cm be analyzed by comparing the effects of A under
different levels of B. The main effects of a variable should be individually interpreted only
if there is no evidence kat the variable interacts with other variables. When there is
evidence of one or more such interaction effects, the interacting variables should be
considered joint1 y.
A response surface model (RSM) is a collection of mathematical and statistical
techniques used for analyzing problems in which several independent variables influence a
dependent response. The response (y) is assumed to be a random variable.
Because the fomi of the relationship beh~een the response and the independent
variables is unknown, the first step in the response surface analysis is to identify a suitabie
approximation for the functional relationship between response y and the set of independent
variables. Usually, a fint-order model is employed, if the response c m be well-modeled as
a linear huiction of the independent variables:
where:
bo = average effect;
bi = main effect;
e = a random error component.
However, when there are evidences of one or more interaction effects, the interacting
variables should be considered. In this case, the response surface model is:
where:
bo = average effect;
bi = main effect;
bq = two-factor interaction;
bok = three-factor interaction.
Thus the model cm be written in a rnatrix form as follows:
y = X p + e
where Po = bo, pi = Kt b,, fi, = !4 bu, and fijk = Kbyk, and the columns in X correspond to the
variables. The modeling rnatnx is obtained h m the factorial design, by adding a column of
ones (corresponds to Bo) and columns of cross products (interaction among the variables).
Chapter 5
Results and Discussion
This section describes the experimental results, the response model, and the analysis
of variance for the experimental results. The relationships among toluene adsorption rates.
soi! types and air injection pressures were analyzed, such that the effectiveness of differeni
soi1 remediation methods were then evaluated.
5.1 Testing Conditions
The experimental conditions given in Table 5.1 were determined based on the
principle of z4 full factorial design as discussed in Chapter 4. Two injected air pressure
options were considered (Le. 15 psi air injection pressure for soi1 with 50% clay contents
and 5% wt gasoline; and 22 psi air injection for soi1 with 40% clay contents and 3% wt
gasoline) .
The two fiequency levels for the electromagnetic vibration system were 60 Hz and O
Hz, corresponding to presence and absence of electromagnetic vibration.
5.2 Testhg Results
Table 5.1 Experimental Conditions for the Factorial Design
Run ClayISand Vibration Gasoline Soi1 Water Air Injection Air Flow No. (wt%) Frequency Weighl Weight Weight Pressure Rate
(Hz) (B) (6) (g) (psi) (mumin)
The experimental results under various conditions are shown in Figures 5.1 to 5.17.
The removal efficiencies (RE) were calculated as follows:
where:
Ci = concentration of contaminant (mgk),
F = air flow rate (Umin),
t = time duration (min),
Cz = average residual concentration of contaminant (mg/g),
W = weight of soi1 (g).
Toluene adsorption rate (%) = 100 - Toluene removal efficiency
5.3 Statistical Analysis
5.3.1 Result Interpretation
An analysis of the toluene adsorption rate under various system conditions is shown
in Table 5.2.
There are two quicker methods for calculating the effects; one is a table of contrast
coefticients and the other is Yaks's Algorithm (Box et al., 1978). A table of contrast
coefficients is used for analyzing observations after they have been rearranged in what is
called order.
O 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7
Test Number
Figure 5.1 ToIuene Adsorption Rates Under Various Experirnental Conditions
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.2 Cumulative Toluene Rernoval Efficiency vs. T i e (Run 1)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.3 Cumulative Toluene Removal Efficiency vs. Time
O 60 120 180 240 300 360 420 480 540 600
Tirne (min)
Figure 5.4 Cumulative Toluene RemovaI Efficiency vs. Tirne (Run 3)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.5 Cumulative ToIuene Removal Efficiency vs. Tirne
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.6 Cumulative Toluene Removal Efficiency vs. Time (Run 5 )
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.7 Cumulative Toluene Removal Efficiency vs. T h e
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.8 Cumulative Toluene Removal Efficicncy vs. Time
O 60 120 180 240 300 360 420 480 540 600
Tirne (min)
Figure 5.9 Cumulative Toluene Removal Efficiency vs. T h e (Run 8)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5. IO Cumulative Toluene Removal Eficiency vs. Time (Run 9 )
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.1 1 Cumulative Totuene Removal Efflciency vs. Time (Run 10)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure S. 12 CumuIative Toluene Removal Efficiency vs. Time (Run 11)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.13 Cumulative Toluene Removal Efficiency vs. Time (Run 12)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5-14 Cumulative Toluene Removal Efflciency vs. T h e (Run 13 )
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5 . t 5 Cumulative Toluene Removai Efficiency vs. Time (Run 14)
O 60 120 180 240 300 360 420 480 540 600
Time (min)
Figure 5.16 CumuIative Toluene Removal Efficiency vs. Tirne (Run 15)
O 60 t20 180 240 300 360 420 480 540 600
Time (min)
Figure 5.17 CumuIative Toluene RemovaI Efkiency vs. The (Run 16)
The calculations performed to obtain the various effects cari be charactenzed by the
table of signs as shown in Table 5.2. In this table, a z4 factorial design was in a standard
order, when the k t column of the design matrix consisted of successive minus and plus
signs , the second column of successive pairs of minus and plus signs, the third column of
four minus signs followed by four plus signs and the last column of eight minus signs
followed by eight plus signs.
Table 5.2 shows the influence of the variables. Columns 1 to 4 (main effects) were
from a matrix of a 2" full factonal design. Based on columns 1 to 4, the signs for the two or
more variable interactions can be obtained in columns 12 to 1234 (interactive effects). The
remaining effects were identified by locating the plus and minus signs in the design rnatiix.
Based on the toluene adsorption rate (TAR), Table 5.2 also showed the calculated effects in
the bottom row, which were obtained as follows:
1 6, = -[27.95 + 33.44+ 16.89 + 2 1.89 + 29.77 + 36.22 + 20.78 + 24.56 + 21.72 +
16 29.21+8.91+15.72+18.96+ 26.45+10.11+16.01]
(5.6) = 22.41
where bi defines the effect of variable x,, b, represents the effect of interaction between i
and j, and bo is the average of toluene adsorption rate.
Multiplying the colurnn labels of the complete variable matrix by the generators gave
the confounding pattern. The identification of each effect including the confounding
patterns is summarized in Table 5.3.
A positive effect means that an increase in the variable would increase the toluene
adsorption rate (%); and a negative effect means that an increase in the variable would
decrease the toluene adsorption rate. If the absolute value of an effect is much bigger than
the others, it means that this variable (or the interaction between variables) has the
significant influence on the toluene adsorption rate. In Table 5.3, among the confounded
effects, b2 and b4 (main effect) were negative with their absolute values being much bigger
than the others, indicating that an increase in air injection pressure or electromagnetic
vibration would decrease toluene adsorption rate significantly.
The main effects of xl and x j were positive, with xi having the highest value and x,
the lowest value, which meant that xi rnight play the most significant role (while x, had the
least effects) on toluene adsorption rate among al1 the main effects. The interactive effect of
xi* was negative with its absolute value being much smailer than those of x2 and u, which
indicated that the interaction between xi and x2 had lower effect on the toluene adsorption
rate. More detaited discussions are provided as follows:
Table 5.3 Main Effects and interactions
Identity of Effects E ffec t
Average
1
2
3
4
23
34
12
14
234
123
24
1234
13
1 24
134
( 1) A change in the ratio of clay to sand Erom 40% to 50% (corresponding to -1 and
+l in Table 4.1) would increase toluene adsorption rate significantly, leading to a higher
effect value as shown in Table 5.2.
(2) A change in the air injection pressure fiom 15 psi to 22 psi (corresponding to -1
and +l in Table 4.1) would reduce toluene adsorption rate by almost 6%.
(3) A change in the gasoline concentration in the soi1 From 3% to 5% (corresponding
to -1 and +1 in Table 4.1) would slightly increase toluene adsorption rate.
(4) A change in the electromagnetic vibration fiequency from O Hz to 60 Hz
(corresponding to -1 and +1 in Table 4.1) would lead to reduction of toluene adsorption
rate.
(5) For the interactive effects, a change both air injections pressure and gasoline
concentration (corresponding to both air injections pressure and gasoline concentration a<
their lower level or higher level), would result in increasing toluene adsorption rate.
(6) A change both gasoline concentration and electromagnetic vibration frequency
(conesponding to both gasoline concentration and electromagnetic vibration frequency at
their lower level or higher level), would result in decreasing toluene adsorption rate.
5.3.2 Sensitivity Analysis
For the interactive effects, x z ~ and XN are rnost significant. To examine whether the
high effect levels are from the interactions, sensitivity analysis of relations between x2 and
x3 and between x3 and are desired. The detailed procedures is as follows (as shown in
Figure 5.1 8):
(1) For ~ 2 3 , the experimental domain is marked as a square in the plane spanned by x2
and xs Figure 5.18). The average response, 22.4, is given at the ongin;
(2) The corner in the lower left quadrant corresponded to the setting for x l equal to - 1
and x~ equal to - 1. There were four expenments corresponding to this setting (which reflect
variations of x2 and x~ ) with the toluene adsorption rates being 27.95, 33.44, 21.72 and
29.21 ( average = 28.08). This value was written in the lower left comer. The same
procedure was then used for other combinations of variable settings, i.e. (x2. x3) = (- 1, + 1 ).
(+ 1 ,-1) and (+l, +1), with the average toluene adsorption rates being 29.6. 15.85 and 17.87
respectively. Similarly, variable settings for (xJ, a) = (- 1, - 1). (- 1. + l ), (+ 1 ,-1 ) and (+ 1,
+ 1 ) were calculated.
Table 5.4 shows the sensitivity of response y (toluene adsorption rate) the variations
of variable xz, x3 and a.
It is indicated that the response y shows the lowest sensitivity to x~ When x i and x~
are at their lower leveis, the differences of y at lower and upper bounds of x i are 1.52 and
2.79, respectively. When xz and Q are at their upper levels, the differences are 2.02 and
- 1 .O 1, respectively. This meant that the toluene adsorption rate wouid not signi ficantiy with
the variation of x3. in cornparison, response y shows the highest sensitivity to x2 and Q. For
the effeîts of variable ~ 2 x 3 and x94, impacts from x2 and a need to be considered. This
could be malized through M e r analysis of variance
Figure 5.18 Detailed Examination For Effects of xz, x, and a
Table 5.4 Sensitivity Analysis
Variable Level Sensitivity (Ay)
X2 x~ at lower level
x3 at upper level
X 3 xz at lower level
x2 at upper level
at lower level
x4 at upper level
XJ ~3 at lower level
x3 at upper level
5.3.3 Analysis of Variance
5.3.3.1 Pmcess Development Data
Two problems arise in the assessrnent of effects from unreplicated factorials: (1)
occasionally real and meaningful high-order interactions occur; and (2) it is necessary to
allow for selection. The assessrnent of effects using a reference distribution scaled by an
error estimated fiom higher order interactions does not confiont the first of these problems.
However, Plotting the effects on a normal probability paper oRen provides an effective way
of overcoming both of the di fficulties (Daniel, 1959).
If the variables do not have any influence on the response, the response surface is
completely flat and the estimated effects in such cases would be nothing but different
average surnmations of experimental erron. Because ail the erperiments were executed in a
random order to avoid systematic enon, the set of estimated pararneten, [b,, b2. . . .. b,,. . . 1,
would be random sarnples, with appraxirnately normal distribution. Hence, those estimated
effects that fa11 on the straight line of the nomal distribution could reasonably be assurned
to be nothing but various summations of error terms. They do not represent any significant
effects of the correspondhg variables. On the other hand, effects derived From the straight
line in such a way that they are either too large to fit (upper right) or too small to fit (lower
lett) cm be assurned to represent real effects.
The significance of the estimated effects can be assessed from a normal probability
plot through the following steps (Box, 1978):
(1) Arrange the estimated effects in ascending order (not including the average bo).
(2) Count the number (m) of estimated effects. In this case, rn = 1 5.
(3) Calculate the probability as follows:
1 f: =100*(i--)lm, V i
2 (5-7)
For illustration, refer to the results fiom the process development experiment
considered before. Suppose that these data had occurred simply as the result of random
(roughly normal) variation about a fixed mean, and the changes in levels of the variables
had had no real effect at al1 on the percent conversion. Then the m = 15 eflects (main
effects and interactions), representing 15 contrasts between pairs of average containing 15
observations each, would have been roughly normal and been distributed about zero (as
shown in Figure 5.19). It happened that for these data the estimated main effect of factor 1
represents the fint 1/15 = 6.7% of the cumulative distribution and should therefore be
ploned against the value 1/2/15 = 3.3% (as shown in Table 5.5). An error distribution line
can be drawn by pivoting a straight line with effects of magnitudes close to zero.
Obviously, 10 of the estimated effects in Figure 5.19 fit reasonably well on the straight line.
Those corresponding to XI, .Y?, x4 and xg~ do not fit the line. Therefore, it can be concluded
that these effects are not easily explained as chance occurrences.
5.3.3.2 Diagnostic Examination
Normal plotting of' residuals provides a diagnostic check for any tentatively
entertained model. The plot in Figure 5.19 suggests that al1 effects. with the exception of
the average (22.41 ), XI (6.05), xz (-1 1.1 l), x4 (-8-05}, and ~ 3 x 4 (-1.90), can be explained by
noise. If this is tme, the estirnateci percent conversion for the process development data is
given at the venices of the design by:
6.05 -11.11 - 8.05 - 1 -90 y = 22.41 + (-)x, + (- 1x2 + (- ).Y, + (-)x3x4 2 2 2 2
where x,, xz , XI and xg4 take the value of -1 or + 1 according to their signs in Table 5 2.
Notice that the coefficients that appear in the equations are halves of the calculated effects.
This is so because a change from x = -1 to x = +1 is a change of two units along the x-ans.
The values of y, 9 , and y - j are shown in Table 5.6. The model was then checked by
plotting these residuals on a normal probability paper as shown in Figure 5.20. Unlike the
original plot of the effects, al1 the points ftom this residual plot lie close to a line.
According to the above analysis, x, (soi1 clay content), x2 (air injection pressure) and .r,
(electromagnetic vibration), and interaction . (interaction between gasoline
concentration and electrornagnetic vibration) are used to produce a response surface model.
It confïrmed that the conjecture effects other than xi, .n, x4, and . r ~ x ~ were readily erplained
by random noise. This residual check is valuable provided that the number of effects
eliminated (four in this case) is fairly small compared to m.
Thus the model is set up as follows:
Y = 22.41 + 3 . 0 3 ~ ~ - 5 . 5 6 ~ ~ - 4 . 0 3 ~ - 0 . 9 5 ~ ~ Q + e
Table 5.5 Result of Probability Analysis
Order No (i) Effects Identib of Effects
- 15 - 10 - 5 O 5 10
Effect
Figure 5.19 Normal Plot of Process Effects on Probability Paper
5.4 Summary
From the above analysis, the following surnmary cm be drawn for the experimental
studies.
xi: The clay content played a significant role to the toluene adsorption rate. The
positive effect meant that the toluene adsorption rate would increase as the clay content
increased. Thus lower clay content will lead to lower toluene adsorption rate.
XZ: The air injection pressure had a significant effect on toluene adsorption. A
higher level of air injection pressure would result in a lower toluene adsorption rate. and
thus a higher level of toluene removal eficiency.
XJ: The gasoline concentration is not critical under the experimental conditions. It
has little influence on toluene adsorption rate. However, the tendency is that higher
gasoline concentration is related to lower toluene adsorption.
Y : The effect of electromagnetic vibration on toluene adsorption rate is significant.
The higher the electromagnetic vibration frequency, the lower the toluene adsorption rate.
Table 5.6 Values of y, j , and y-? for z4 Factorial Design
Order No (i) Y
Effect
Figure 5.20 Normal Plot of Residual Effects on Probability Paper
5.5 Conthuous Air Injection System for BTEX Removal
A number of laboratory experiments were conducted on loose soi1 sarnples to
determine removal efficiencies under different experimental conditions. The experiments
were conducted to also examine the effects of clay content, water content and adsorption
t h e on the removal efficiency (for benzene, toluene, ethyl-benzene and (m+p)-xylene)
under the condition of continuous air injection. The results of these expenments served as
ba i s for designing the electromagnetic-vibration-enhanced air stripping system.
The soils were purposely contaminated by BTEX and then decontaminated with
continuous air injection. For each experiment the removal efficiency was expressed on a
cumulative basis. Table 5.7 contains some of the important characteristics of the BTEX
compounds.
5.5.1 Effect of Water Content on BTEX Removal
To study the effect of soil water content on removal efficiency, reagent-grade
benzene, toluene. ethyl-benzene and (m+p)-xylene (m-xylene : p-xylene = 1 : 1 ), were used
separately as contaminants. The BTEX removal efficiency (RE) was calculated as Follows:
Total Mass of Conta minants Removal RE(%) = x 100% Initial Mass of Contaminants in Soi1
The experimental results are shown in Figures 5.21 to 5.24. The column was initially
packed with coarse-grained soit (clay/sand = 112, total soil weight 30 g). The soil water
content was 3%, 4.5%. 6% (wt), and contaminants (BTEX) were 10% W. The pump
injection rate was fixed at 4 mL/min, the experimental temperature was 2S°C, and the
atrnosphenc pressure was 95 kPa.
It can be seen from Figures 5.21 through 5.24 that, as soil water contents increased,
the benzene, toluene, ethyl-benzene and (m+p)-xylene removal efficiencies decreased
slightly. Specifically, the removal efficiency decreased from 95.1% to 90.7% for benzene,
from 40.7 to 32.7% for toluene, from 16.8% to 14.2% For ethylbenzene, and from 14.1 % to
12.7% for (m+p)-xylene within 12 houn.
For a fixed air injection rate and the same soil weight, as the water content increased.
the soil pemeability decreased, leading to reduce air flow rate in the soil. This reduced air
flow rate would result in reducing energy input as well as reduced desorption of
contaminant from the surface of soi1 particles.
Volatilization is the main mechanism of contaminant removal during air injection.
The primary mechanism for mass transfer is volatilization, which occun when air passes
through the contaminated zones and VOCs evaporate into the air channels (Johnson, 1993).
It will take longer to clean soils with high moisture content than similar soils with
Iower moisture (Zwick et al., 1995). Dry air might be injected into the soil to reduce soil
moisture content and produce a tensiometric, or dry. barrîer to contain liquid-phase
transport (Thomson et al., 1996). If large amounts of water are withdrawn From soil with
the gaseous s t e m and contarninants, the pneumatic soil pemeability could change. and
temperature could drop down to 10°C (Garcia-heruzo et al., 1994). This will decrease
system energy and will result in di fficulty in BTEX evaporation.
+ 3% water
+ 4.5% water + 6% water
O 5 IO 20 25 3 0 3 5 40 45 50 Air Injection Duration (Iir)
Figure 5.22 'I'oluene Rernoval Efficiency vs. Air Injection Duration for Different Soi1 Water Contents (Run 18)
O 5 i O 15 20 25 30 35 40 45 50 Air Injection Duration (hr)
Figure 5.24 (m+p) Xylene Removol Efficiency vs. Air Injection Duration for Differen~ Soil Water Contents (Run 20)
However, when soil moisture is increased during bioremediation of contaminant, the
microbial activity can be significantly enhanced.
In addition, the lower the boiling point and Henry's Law Constant of a contaminant,
the higher the removal efficiency (Ji et al., 1993).
5.5.2 Effect of Clay Content on BTEX Removal
Three types of soils were used to study the effect of clay content on contaminant
rernoval efficiency. Benzene, toluene, ethyl-benzene and (m+p)-xylene (m-xylene: p-
xylene = l : 1) were used as contaminants.
The colurnn was initially packed with soils that had different clay contents (claykand
= 30%- 50% and 70% wt). The total soil weight was 30 g, and the water content was 3%
wt, and the BTEX concentration in soil was 10% wt. The air injection rate was fixed at 1
&min. The experimental temperature was 2S°C, and the atmospheric pressure was 95
kPa,
The experirnental results shown in Figures 5.25 through 5.28 indicate that, as clay
contents increased, BTEX removal efficiencies decreased. In detail, as the clay content
increased fiom 30% to 70% wt, the BTEX removal efficiency decreased from 99% to
85.6% for benzene, fiorn 54.1% to 37.9% for toluene, h m 16.8% to 14.1% for
ethylbenzene, and From 2 1.9% to 13.1% for (rn+p)-xylene with 12 hours of air injection.
o q q c. 0 0 0
Under the same air injection rate, as the clay content increased, the soi1 penneability
decreased, resulting in decreased air flow rate in the soil pore. This reduced air flow rate
would then lead to reduced energy input as well as reduced desorption of contaminant from
soil surface.
Clay in soils acts as a retarding layer to the vertical and horizontal flux of VOCs. The
stead-state vapor diffusion of benzene in soil under isothermal conditions and extremely
slow water flow is directly related to the soil's air-filled porosity (Goring, 1962). Clay soils
tend to have a more uniform pore size distribution than do coarser soils. The coane soils
tend to have larger mean pore sizes, which will transfer fluids faster under saturated
conditions and vapors faster under unsaturated conditions (Hillel, 197 1).
Clay particle had larger surface area per unit weight than that of sand. A material with
higher surface area had higher adsorption capability. It becarne more difficulty to desorb
contaminant frorn a system with higher surface energy. Thus contaminants in soils with a
high clay content are more difficult to be desorbed.
5.5.3 Effect of Adsorption Time on BTEX Removal
To study the effect of adsorbing time on removal eficiency, reagent-grade benzene,
toluene, ethylbenzene and (m+p)-xylene (m-xy1ene:p-xylene = 1:I) were used as
contaminants. The column was initially packed with clay/sand = 50%, total soil weight=30
g, and soil water content = 3% wt. The purnp injection rate was fixed at 4 W m i n , the
experimental temperature was 25 OC, and the atmosphenc pressure was 94.6 kPa.
-+ 12 hrs + 24 hrs
-O- 36 hrs
O 5 10 15 20 35 30 35 40 45 50
Air Injcciion Lhruiion (hr)
Figure 5.30 Tolueiie Removal Efficiency vs. Air injection Duration for Different Adsorption Durations (Run 26)
After the soil was contaminateci and sealed in column for 12, 24 and 36 hr, air
injection started. The experimental results are s h o w in Figures 5.29 through 5.32. It is
indicated that BTFX adsorption duration had slight effects on the removal efficiency. The
ultimate removal efficiency varies from 99.5% to 96.9% for benzene, from 98.9% to 96.8%
for toluene, fiom 53.1% to 51.7% for ethylberuene, and fiom 46.3% to 43.2% for (m+p)-
xy lene.
Adsorption cm be both physical and chemical in nature. However, under normal
environmental conditions and ambient temperanires, the predominant process is physical
adsorption (Valsaraj and Thibodeaux, 1987). This is due to the lact that chemical
adsorption requires actual chernical bonding between the adsorbate and the adsorbent,
which is an energy-intensive process only occumng at high temperatures.
For the same clay particle size and moisture of soil, BTEX adsorption rate varied
slightly when the adsorption duration was changed From 12 to 36 hr. However, too long
adsorption duration may lead to natural degradation of BTEX.
5.6. Effect of Soi1 Type on Toluene Removal
From the discussion in the previous section, the clay content plays an important role
in toluene removal. To investigate the effect of clay content in more detail, additional tests
were conducted under clay content of 60% and 70% wt, with and without electromagnetic -
vibration-enhancement. The detailed testing conditions of the four experirnents are s h o w
in Table 5.8. The air injection pressure was fixed at 22 psi for ail these experiments.
From Figures 5.33 and 5.34, it is indicated that under without electromagnetic
vibration, the toluene removal eficiency significantly decreased as the clay contents
increased fiom 40% to 70% respectively. Thus, the higher the clay content, the lower the
toluene removal e fficiency.
In detailed, without electromagnetic vibration. the toluene removal efficiency (after
LO tu), decreased from 79.61% to 58.65% (Figure 5.33) as the clay content increased from
40% to 70%. With electromagnetic vibration, the eficiency (after 10 hr) decreased fiom
89.85% to 69.97% (Figure 5.34) as the clay contents increased. The following are detailed
explanations of these facts:
(1) The main rnechanism of mass removal in air stripping is volatilization of the
VOCs, which occurs when air passes through the contaminated zones and results in VOCs
evaporation in the air channel. The injected air in the saturated porous media usually moved
in continuous air channels, with VOCs volatizing across the air-soi1 interface of channel
into the air phase. Soil physical properties (i.e. penneability, and surface areas) have
significant impacts on the remediation eficiency. The higher clay content results in less
and smaller air channels, and thus Iower removal efficiencies.
(2) Adsorption is a surface phenornenon, as such the extent OF adsorption is
proportional to specific surface area. Specific surface area is defined as that portion of the
total surface area that is available for adsorption. Desorption can occur between vapor
phase and soi1 surface. The equilibrium particle partial pressure of a volatile contaminant in
+- 40% Clay (R7) -+ 50% Clay (R8) 4 60% Clay (R29) + 70% Clay (R30)
O 60 120 180 240 300 360 420 480 540 600
Air Injection Duration (min)
Figure 5.33 Cumulative Toluene Removal Efficiency vs. Air Injection Duration for Different Clay Contents Without Electromagnetic Vibration
+ 40% Clay (R15)
+- 50% Clay (RI 6)
+ 60% Clay (R31) -x- 70% Clay (R32)
O 60 120 180 240 300 360 420 480 540 600 Air Injection Duration (min)
Figure 5.34 Cumulative Toluene Removal EfEciency vs. Air Injection Duration for Different CIay Contents With Efectromagnetic Vibration
the pore space and mass transfer boom the aqueous liquid or adsorbed phase will depend on
the properties of the contaminant and the soil environment in which it resides.
The more finely divided and the more porous the solid, the greater the arnount of
adsorption accomplished per unit weight of the solid adsorbent. Since clay has higher
surface area than sand, with clay content increasing, the surface area of particles increases.
Thus the media adsorption ability increased, resulting in decreased removal eficiency.
(3) With increasing clay content, the permeability of soil and the air flow rate will
decrease, which will result in less air channels. Thus less air will be held up in the channels
during the air injection period. This will also result in lower removal rate. Lower
permeability clay layers in the soil may restrict the horizon movement of contarninants and
thus allow them to accumulate on the top of the layer.
(4) Normally, during the desorption process, the system will need energy to overcome
bonding energy between two adsorpted componments. As clay content increases, the air
flow rate will decrease, leading to loss of input energy and more dificulty in recovenng
toluene fiom soil.
5.7 Effect of Air Injection Pressure on Toluene Removal
Based on the discussion of the previous section, the effect of air injection pressure on
toluene recovery is also an important factor. To investigate the pressure effect, two
additional tests were conducted with injection pressure settings of 26 and 41 psi without
electromagnetic vibration. For electromagnetic-vibration-euhanced process, one injection
pressure setting of 34 psi was used. The column was re-packed to ensure that air injection
provided sufficient clean inside column. The testing conditions for these experiments are
given in Table 5.8, and the experimental results are shown in Figures 5.35 and 5.36.
The air injection pressure within the tested range had a signifiant effect on toluene
removal efficiency (Figures 5.35 and 5.36). The toluene removal efficiency increased with
the increased air injection pressure. Without the enhancement of electromagnetic vibration,
the toluene removal efficiency increased fiom 66.56% to 75.35% as the air injection
pressure increased from 15 psi to 26 psi. However, as the air injection pressure increased to
41 psi (without electmmagnetic-vibration-enhancement), the toluene removal efficiency
decreased dramatically to 59.14%. Sirnilarly. in the tests with electromagnetic-vibration -
enhancement, the toluene removal emciency also decreased dramatically to 78.75% when
the pressure was raised to 4 psi. Detailed explanations for this phenornenon are provided as
follows:
(1) The higher air injection pressure would result in a higher air flow rate and a
correspondingly increase of energy input, resulting in more effective cleaning.
(2) nie higher air injection pressure will lead to increased system permeability, such
that more air cm be held in the soi1 channels and more toluene can be volatilized, leading to
increased the recovery rate. The higher injection pressure will also pmduce a higher air
flow rate, leading to additional air channels. In fine-grained soils, the higher injection
pressures can result in the formation of subsurface gas pockets, which will continue to
expand hl1 a steady-state condition of air inlet flow is achieved.
4 15 psi (Run 2) + 22 psi (Run 4)
-+ 26 psi (Run 33)
* 41 psi (Run 34)
O 60 120 180 240 300 360 420 480 540 600 Air Injection Duration (min)
Figure 5.35 Cumulative Toluene Removal Effîciency vs. Air Injection Duration for Different Air Injection Pressures without EIectromagnetic Vibration
-t- 15 psi (Run 9) -+- 22 psi (Run 11) -x- 34 psi (Run 35)
O 60 120 180 240 300 360 420 480 540 600
Air Injection Duration (min)
Figure 5.36 Cumulative Toluene Removal Efficiency vs. Air injection Duration for Different Air injection Pressures with Electromagnetic Vibration
(3) Too high injection pressure may create big channels or fractures in the soil. Most
of air will then quickly flow through these fractures, resulting in poor contact and poor
sweeping for the majority of soil. This irreversible Fracturing process could result in a
decrease in toluene recovery rate. Therefore, when using air stripping process in the field,
air pressure needs to be optimized for avoiding fracturing. According to Marley ( 199 1 ), 3 to
5 psi per foot of pressure difference may result in overburden of soil. However, this value
may change with soil types.
5.8 Effect of Electromagnetic Vibration
Figure 5.37 compares the toluene recovery rates with and without electromagnetic
vibration for different soil types. In order to investigate the effect of operational time (of
vibration) on toluene rernoval, comparative experiments were also performed (as shown in
Figure 5.38). the result of Figures 5.37 and 5.38 show that higher toluene removal
efficiencies were achieved with electromagnetic vibration than without it. in average, the
recovery rate with electrornagnetic vibration is 10% higher than that without
electromagnetic vibration. These results demonstrate that electromagnetic vibration
contnbuted significantly to the increase of toluene removal efficiency. More explanations
for this phenomenon are provided as follows:
(1) For desorption of toluene from soil, energy is needed to overcome interfacial
bonding on surface of soil particles. The electromagnetic vibration process increases the
system energy. resulting in easier desorption of toluene fiorn soil.
(2) The electromagnetic vibration will result in more turbulence in the air inflow.
Turbulent 80w compared with eddy fiow will allow air to have more contact area with the
contarninants and thus will increase removal efficiency.
Since the electromagnetic vibration generates a magnetic field, the mixture of air,
water and contaminant vapor would cut magnetic lines of force and produce curent. When
electric current flew fiom soil surface in the same direction as the air flow, the soils were
rnagnetized thus transporting the toluene molecules more quickly to the outlet of the
column.
(3) The electromagnetic vibration would promote movement of soii partic les. The
vibration direction was perpendicular to the air-flow direction. thus increasing air-
contaminant contact area and multing in increased evaporation of contaminants.
(4) Due to electrornagnetic vibration, the air flow became pulsed. The pulsed flow
would likely result in vibration of soil particles, which would produce heat and reduce bond
force between contaminant and soil surface, thus increasing contaminant removal
efficiency .
+ Electromagnetic-Vibration-Enhand Ait Sîripping
+Normal Ar Stripping
30 40 50 60 70 80
Clay Content (%)
Figure 5-37 ToIuene Removal Efficiency vs. Soi1 Clay Content
-x- O min (Run 3) +- 300 min (Run 36) -t- 600 min (Run 1 1 )
O 60 120 180 240 300 360 420 480 540 600
Air Injection Duration (min)
Figure 5.38 Effect of Elecrromagnctic Vibration Duration on Cumulative Tofuene Removal Effkiency
Chapter 6
Conclusions
The developed electromagnetic-vibration-enhanced air stripping technology is an
innovative rneans for remediating petroleum-contaminated soils. I t provides more rapid and
efficient removal of contaminants in soils. Although the initial capital cost for this process
is higher than those of othen, the accelerated removal rate and increased removal efficiency
c m eventually cesult reduced overall system cost.
Bench-scale experiments were conducted to examine (1) the removal of BTEX in soi1
under different experimental conditions using continuous' stable air injection; and (2) the
removal of toluene from soi1 under a variety of system conditions. A 2' factonal design was
used for the expenments with four factors being considered (two levels for each). The main
factors that have significant effects on toluene removal were identified. A response surface
mode1 was formulated based on the factorial analysis results, reflecting interrelationships
between the system conditions and the toluene removal efficiency. The following
conclusions can be drawn based on results of this study:
(1) Using continuous stable air injection can reduce BTEX concentration in soil. The
removal efficiencies are influenced significantly by soil water content and soil type, while
the BTEX adsorption duration has less influence on the efficiency.
(2) The electromagnetic-vibration-enhanced air stripping technology can effectively
remove toluene fiom fine-sand systems with 40%. SON, 60% and 70% clay content. This
method could result in increased removal rate for toluene and decreased operational time.
(3) Clay content, air injection pressure, and electromagnetic vibration have significant
effects on toluene removal efficiency.
(4) The effect of clay content (in fine sand) on toluene removal is significant at low
air injection pressures. The removal efficiency generally decreases with the increase of clay
content.
(5) Higher air injection pressure generally results in higher toluene remova
eficiency. However, when air injection pressure exceeds soil overburden pressure, the "soi
pocket" will form resulting in the lower removal eficiency. Also, the effect of air injection
pressure on toluene removal is insignificant in pure fine-sand systems with 40%, 50%, 60%
and 70% clay content.
(6) The developed electromagnetic-vibration device was made up of low-cost
commercial products. The entire system of electromagnetic-vibration-enhanced air
stripping is easy to set up and operate.
6.2 Research Achievernents
The following are the main achievements of this study fkom the environmental
engineering application perspective:
(1) Electromagnetic-vibration-enhanced air stripping is an innovative method that
wiil result in more rapid and more efficient removal of contaminants.
(2) This study provides a systematic analysis on facton that affect the performance of
the electromagnetic-vibration-enhanced air stripping system. Especially, impacts of soil
type and air injection pressure under a variety ofsysiem conditions were examined.
(3) Methods of factonal design and response-surface modeling were used for
comprehensively designing experiments and analyzing complicated interactions among a
nurnber of system facton and their impacts on the remediation performance.
6.3 Recomrnendations for Future Research
In this study, four factors were considered. In fact, the system is very complicated
and many additional factors and interactions may potentially exist. For example,
temperattue, soi1 moisture, pH and soil metal content may also affect the stripping process.
It is thus desired that more factors be considered in the friture research efforts. Besides,
examination of the systemts performance under vibration frequency other than 60 Hz would
be potentially helpfùl for further increasing system eficiency.
For each Factor, only two levels were considered. In reality, the response to each
factor's effect may not necessarily be linear, such that consideration of more than two
levels could be potentially beneficial.
in the absence of validated predictive models, quantitative results fiom physical
modeling studies cannot be easily extrapolated to any real-field setting. Thus, before
extrapolating physical modeling results to real-field applications, hrther pilot-scale
modeling and experimental studies are needed (Johnson et al., 1999).
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