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This is to certify that the
thesis entitled

The Impact of Pore-Water Velocity on Nonequilibrium
Transport of Nonionic Organic Compounds in Soil

presented by

John Richard Zimmerman

has been accepted towards fulfillment
of the requirements for

MS

 

degree in Environmental Engineering

Cﬂ’c‘ﬁ‘o @ M492;

Major professor

Date 8/18'I/98

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1M C‘JCIRCIDIbDquS-p.“

 

THE IMPACT OF PORE-WATER VELOCITY ON NONEQUILIBRIUM
TRANSPORT OF NONIONIC ORGANIC COMPOUNDS IN SOIL

By

John Richard Zimmerman

A THESIS

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Civil and Environmental Engineering

1998

l}|lll

 

ABSTRACT

THE IMPACT OF FORE-WATER VELOCITY ON NONEQUILIBRIUM
TRANSPORT OF NONIONIC ORGANIC COMPOUNDS IN SOIL

By

John Richard Zimmerman

Column studies were performed to investigate the impact of pore-water velocity
(v0) on transport of benzene, toluene, p-xylene and naphthalene in three nonaggregated
media: soils with organic carbon content (foe) = 0.30 and 1.0% and aquifer material with
f0c = 0.05%. To understand the effect of velocity variation on mass transfer rate
coefﬁcient (k), pore-water velocities ranging over almost two orders of magnitude (1.7 -
93.2 cm/hr) were evaluated. Consistent with the results of past investigators, v0 and k
were positively correlated. To determine if the effect was related to contaminant
residence time in the column, log(k) was plotted against log(LR/vo), where L is column
length and R is retardation coefficient. On the higher organic carbon content soil, log(k)
vs. log(LR/vo) relationships for individual compounds were linear (R2 = 0.89 to 0.97).
Regression line slopes plotted against log(Kow) values revealed strong positive linear
correlation (R2 = 0.99), indicating that k is increasingly dependent upon contaminant
residence time (and therefore v0) as compound hydrophobicity decreases. This study
indicates that there may be a quantiﬁable relationship between k and v0 which has a

mechanistic basis.

To my parents, Ken and Carol Zimmerman, and to my sisters and brothers, Kim,

Cindy, Dave, Pat and Adam.

iii

ACKNOWLEDGEMENTS

I wish to express my thanks for the many individuals who have made this work
possible, either directly or indirectly. First I thank each professor in the Department of
Environmental Engineering from whom I took classes: Dr. Susan Masten, Dr. Mackenzie
Davis, Dr. Roger Wallace, Dr. David Wiggert, Dr. Thomas Voice and Dr. Craig Criddle.
I also thank the many helpful staff members in the department who helped me during my
stay: Laura Taylor, Mary Wiseman, Linda Philipich, Dr. Ron Harichandran, Diane Cox
and Linda Steinman. I also thank from the US. EPA’s Hazardous Substance Research
Center at Michigan State University: Kirk Riley, who gave me the opportunity to assist in
preparing a report and presentation for the community of Whitehall, Michigan, and Pat
Miller for her help in that work.

Others assisting more directly in this work were Yanlyang Pan and Dr. Paul
Loconto, who on many occasions provided advice and assistance with laboratory
equipment. I am grateful to Dave Gwisdala, who helped at a critical time in the
experimental work, and Dave Berends who also helped extensively in the laboratory.
Most of all I thank Dr. Xianda Zhao, who gave me initial instructions in the laboratory

and also provided the experimental setup.

iv

Though I owe thanks to many, I would especially like to thank a few individuals.
Dr. Craig Criddle provided much needed encouragement, enthusiasm and a listening ear
throughout my two years at Michigan State. He is a great example of one who excels
professionally and still remains humble and kind to everyone. My dear friend Dr.
Munjed Maraqa also exempliﬁed an excellent researcher and one who freely gave of his
time and expertise. He also willingly provided me copious opportunities to assist in
teaching and thus in turn allow me to learn and grow. Of all my associations at Michigan
State University, none was as uplifting and helpful as that with Dr. Thomas C. Voice. He
provided me many opportunities I could have had nowhere else. He willingly shared his
expertise, but did so in ways that required me to grow and stretch myself. I will always

try to emulate his methods of ﬁrm but gentle guidance.

Finally I thank my parents, Kenneth and Carol Zimmerman, who have always
loved and supported me when I needed it most. Their quiet examples of work, love and

service have inspired me to reach higher and will continue to do so in the future.

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................... viii
LIST OF FIGURES ............................................................................................................ x
INTRODUCTION .............................................................................................................. 1
CHAPTER 1 THE IMPACT OF FORE-WATER VELOCITY ON NONEQUILIBRIUM
TRANSPORT OF NONIONIC ORGANIC COMPOUNDS IN SOIL .............................. 2
Abstract ........................................................................................................................... 2
Background ..................................................................................................................... 3
Materials and Methods .................................................................................................... 4
Parameter Estimation ...................................................................................................... 8
Results ............................................................................................................................. 9
Discussion ..................................................................................................................... 10

k vs. Kp Relationship ................................................................................................. 10

k vs. vo Relationship ................................................................................................. 10
Summary and Conclusions ........................................................................................... 19
References ..................................................................................................................... 21
APPENDIX A Literature Review .................................................................................... 23
Introduction ................................................................................................................... 23
Previous Determination of Mass-transfer Coefﬁcient .................................................. 27
Inverse relationship log(k) vs. log(Kp) .......................................................................... 27
Pore-water velocity variation ........................................................................................ 29
APPENDIX B Materials and Methods ............................................................................ 31

vi

Solution Matrix ............................................................................................................. 31

Chemical Compounds ................................................................................................... 31
Porous media ................................................................................................................. 32
Plate counts ................................................................................................................... 33
Experimental Setup ....................................................................................................... 34
Prevention of contaminant biodegradation ................................................................... 36
Prevention of volatilization ........................................................................................... 36
Porosity and bulk density determination ....................................................................... 37
Pore-water velocity ....................................................................................................... 40
General .......................................................................................................................... 41
APPENDIX C Data Tables .............................................................................................. 42
LIST OF REFERENCES .................................................................................................. 71

vii

LIST OF TABLES

Table 1. Properties of chemicals at 25°C. (Schwarzenbach et al., 1993) .......................... 5
Table 2. Soil sieve analysis ................................................................................................. 5

Table 3. Chemical properties of compounds at 25°C. (Schwarzenbach et al., 1993) ...... 31

Table 4. Soil sieve analysis ............................................................................................... 33
Table 5. Soil column properties summary ....................................................................... 39
Table 6. Model output parameters for Wurtsmith aquifer sand. ...................................... 42
Table 7. Model output parameters for Metea soil. ........................................................... 43
Table 8. Model output parameters for SPCF soil. ........................................................... 44
Table 9. Column data for Wurtsmith aquifer material with target v0 = 2 cm/hr. .............. 45
Table 10. Column data for Wurtsmith aquifer material with target v0 = 5.3 cm/hr .......... 46

Table 11. Column data for Wurtsmith aquifer material with target v0 = 14.1 cm/hr. ....... 47
Table 12. Column data for Wurtsmith aquifer material with target v0 = 37.5 cm/hr. ....... 48
Table 13. Column data for Wurtsmith aquifer material with target v0 = 100 cm/hr ......... 49

Table 14. Column data for Metea soil with target v0 = 2 cm/hr. ..................................... 50

viii

Table 15. Column data for Metea soil with target v0 = 5.3 cm/hr. .................................. 52

Table 16. Column data for Metea soil with target v0 = 14.1 cm/hr. ................................ 54
Table 17. Column data for Metea soil with target v0 = 37.5 cm/hr. ................................ 56
Table 18. Column data for Metea soil with target v0 = 100 cm/hr. ................................. 58
Table 19. Column data for SPCF soil with target v0 = 2 cm/hr. ....................................... 60
Table 20. Column data for SPCF soil with target v0 = 5.3 cm/hr. .................................... 62
Table 21. Column data for SPCF soil with target v0 = 14.1 cm/hr. .................................. 64
Table 22. Column data for SPCF soil with target v0 = 37.5 cm/hr. .................................. 66
Table 23. Column data for SPCF soil with target v0 = 100 cm/hr. ................................... 69

ix

LIST OF FIGURES

Figure 1. Experimental setup .............................................................................................. 7
Figure 2. log(k) vs. log(vo) for all compounds on SPCF soil ............................................ 12
Figure 3. log(k) vs. log(LR/vo) for all compounds on SPCF soil. .................................... 13
Figure 4. dlog(k)/dlog(LR/v0) vs. log(Kow) for all chemicals on SPCF soil. .................... 15
Figure 5. Experimental setup ............................................................................................ 34

INTRODUCTION

This thesis is comprised of four main sections: Chapter 1, which is essentially a
research paper to be submitted for publication; Appendix A, a more extensive literature
review than that found in Chapter 1; Appendix B, which describes in greater detail the
materials and methods used in the experimental work; and Appendix C, which includes

data tables which are too long to be included in the body of the paper to be published.

CHAPTER 1

THE IMPACT OF FORE-WATER VELOCITY ON NONEQUILIBRIUM

TRANSPORT OF NONIONIC ORGANIC COMPOUNDS IN SOIL

Abstract

Column studies were performed to investigate the impact of pore-water velocity
(v0) on transport of benzene, toluene, p-xylene and naphthalene in three nonaggregated
media: soils with organic carbon content (foe) = 0.30 and 1.0% and aquifer material with
f0c = 0.05%. To understand the effect of velocity variation on the mass-transfer rate
coefﬁcient (k), pore-water velocities ranging over almost two orders of magnitude (1.7 -
93.2 cm/hr) were evaluated. Consistent with the results of past investigators, v0 and k
were positively correlated. To determine if the effect was related to contaminant
residence time in the column, log(k) was plotted against log(LR/vo), where L is column
length and R is retardation coefﬁcient. On the higher organic carbon content soil, log(k)
vs. log(LR/vo) relationships for individual compounds were linear (R2 = 0.89 to 0.97).
Regression line slopes plotted against log(Kow) values revealed strong positive linear
correlation (R2 = 0.99), indicating that k is increasingly dependent upon contaminant
residence time (and therefore V.) as compound hydrophobicity decreases. This study
indicates that there may be a quantiﬁable relationship between k and v0 which has a

mechanistic basis.

Background

Public concern over extensive soil and aquifer contamination has led researchers
to investigate methods of modeling transport of hydrophobic organic compounds in these
environments. An essential part of any such model is the description of contaminant
distribution between solid and aqueous phases. As a ﬁrst approximation, it was assumed
that the sorption to and from soil solids occurs immediately and could be described an
equilibrium process. However, experimental results often showed a slow approach to
equilibrium or a dual sorption pattern wherein a period of fast (equilibrium) sorption was
followed by a slow period which could be described using a kinetic model. Lapidus and
Amundson (1952) are generally attributed with ﬁrst describing the slow approach to
equilibrium using a ﬁrst-order rate equation. Cameron and Klute (1977) later described
sorption as a two-site process, with part of the sites participating in rate-limited (slow)
sorption and the other part in instantaneous sorption. For an extensive review of non-
ideal processes in general, including two-site sorption, the reader is referred to Brusseau
and Rao (1989a).

The main purpose in developing the models has been to predict contaminant fate
(e.g., concentration proﬁle with depth) for a particular situation. In order to accomplish
this, model parameters must be determined independently and entered into the model.
Several investigators have attempted to provide methods for independently predicting k
values without using ﬁtting techniques. Brusseau and others have noticed an inverse
relationship between k and partition coefﬁcient, K, (Brusseau et al., 1991; Brusseau,

1992; Brusseau and Reid, 1991; Karickhoff, 1980) and some have stated that this may be

a method of predicting k for use in other soil/sorbate situations (Brusseau and Rao,
1989b)

One challenge, however, is understanding the effect of pore-water velocity (v0) on
that relationship between k and KP. Brusseau (1992) noted that values of k for a high
velocity were over one order of magnitude higher than values at a lower velocity. Other
authors have noted an effect of v0 on BTCs and degree of nonequilibrium exhibited
(Bouchard, et al., 1988; Brusseau et al., 1991). Maraqa (1995) reported that k increased
with v0 for benzene and dimethylphthalate in soil column studies. This then casts doubt
on our ability to predict k from a corresponding Kp without considering pore-water
velocity effects. What is needed is a relationship between v0 and k and an explanation for
that observed relationship. This work is an attempt to deﬁne such a relationship.
Materials and Methods

Column experiments were designed to study chemical desorption from soil solids.
First soil columns were ﬂushed with a solution containing all target compounds at a high
ﬂow rate until efﬂuent concentrations were near inﬂuent values. At this point, solution
ﬂow was stopped for approximately one day before ﬂushing the column again at a low
ﬂow rate. This allowed diffusion of chemicals into less accessible sorption sites. Matrix
solution was then ﬂushed through the columns and desorption phase breakthrough curves
were obtained. The compounds were mixed in one solution and co-eluted; it has been
shown in previous studies that competition effects are minimal at low contaminant
concentrations (Maraqa, 1995). The target pore-water velocities were 2.0, 5.3, 14.1, 37.5

and 100 cm/hr.

The solution matrix consisted of a 0.01 N solution of CaCl2 buffered with a 10
mM solution of KHZPO4 which was sterilized in an autoclave to inhibit biological growth.
Benzene, toluene, p-xylene and naphthalene were used in the study. Table 1 shows

properties of the compounds.

Table 1. Properties of chemicals at 25°C. (Schwarzenbach et al., 1993)

 

 

log K...
Mol. wt. -log P0 -log Cwsat CWsalt [(mol-L'l octanol)-
Compound (g/mol) (atm) (mol-L") (mg-L") (mol-L" water)"]
Benzene 78 0.9 1.64 1787 2.13
Toluene 92 1.42 2.25 517 2.69
p-xylene 106 1.93 2.77 180 3.15
Naphthalene 128 3.43al 3 .61 31 3 .36

 

 

 

a. Value shown is -logP°(L) for solid phase

Two soils, Metea and SPCF, with f0c = 0.30 and 1.0%, respectively, and one
aquifer material, Wurtsmith, with f0c = 0.05, were used in the study. Table 2 shows the
size distribution of the soils and sand. These were sterilized by z 2 Mrad of gamma
radiation, which has been shown to be an effective method of sterilization which does not

signiﬁcantly alter the soil characteristics.

Table 2. Soil sieve analysis

 

 

Soil or Organic Grain size

Sand Type Carbon, % (250-425 um) (150-250 um) (53-150 um) (0-53 urn)
SPCF 1.0 10.6% 22.8% 55.2% 11.4%
Metea 0.30 10.6% 22.8% 55.2% 11.4%
Wurtsmith 0.05 15% 70% 1 5% 0%

 

 

 

 

An example of the experimental setup for one column is shown in Figure 1.
Columns were 15.2 to 15.4 cm long and 1.1 cm inside diameter (id), and tubing was

1.27 mm id. The columns, diffusion disks, tubing and tee ﬁtting shown in Figure 1

were all stainless steel. The syringe shown in Figure l was glass, and the syringe plunger
head and three-way valve were all made of Teﬂon.

In order to prevent or inhibit microbial growth, the tubing, columns, tee ﬁttings,
and three-way valves were sterilized in an autoclave. The bottle was vented by placing a
needle in the rubber septum of the efﬂuent bottle, with a 0.22 um ﬁlter placed at the head
of the needle. In between the syringe and the soil column, the stainless steel tubing was
threaded through a small hole in a heating block which was maintained at z 60°C.

Samples were collected by depressing an air-ﬁlled syringe at A in Figure 1,
causing the solution in the sample loop to be ejected into a 22 mL headspace vial held at
B. Vials were then capped quickly in order to prevent sample volatilization. Compound
concentrations were measured using headspace gas chromatography.

Prior to saturating the columns with solution, CO2 was injected into the media-
ﬁlled columns in order to displace air in the void spaces. This prevented formation of
pockets of relatively water-insoluble air in these spaces. See Appendix B for further

details about experimental methods.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

B A
Filter Sample
3: / loop
V\l '
1 Stainless steel 117.3 diated
Three-way tee ﬁtting $011
valve
Efﬂuent
Soil column
Syringe
1 ﬂ——. ,7 000
Syringe pump Heating block

 

 

 

Figure 1. Experimental setup

Parameter Estimation

The desorption breakthrough curves were analyzed using the nonlinear least
squares inversion program CXTF IT (Parker and van Genuchten, 1984) to determine
nonequilibrium parameters. The advective-dispersion equations (including
nondimensional equations) describing l-D transport of sorbing solutes through a
homogeneous soil column under steady state conditions are found in the literature
(Brusseau, 1991).

Required model input parameters included pore water velocity (v0), dispersion
coefﬁcient (D), retardation coefﬁcient (R), column length (L), and relative inﬂuent
concentration (C*). The model then used least squares ﬁtting to determine
nonequilibrium parameters 0 (fraction of instantaneous retardation) and a). From the
model outputs of B and a), the fraction of instantaneous sorption sites, F, and the
dimensional mass-transfer rate coefﬁcient, k, were calculated. Parameters such as F, R
and B, which should be considered along with mass-transfer coefﬁcients in order to be

meaningful, are tabulated in Appendix C.

Results

The program was run in either equilibrium or two-site mode, depending on which
ﬁt the data better. In the equilibrium mode, it was assumed that sorption at all sites
occurred instantaneously and obeyed a linear sorption isotherm. The two-site model
described sorption as instantaneous at a portion of the sites and rate-limited at the other
sites. See Appendix C for data tables containing results.

Several trends were observed from the results. First, as expected, the equilibrium
model was used slightly more often at the lowest velocity (z2.0 cm/hr) than at any other.
This occurs because the characteristic sorption time is near the compound residence time
at that low pore-water velocity, leading to the equilibrium model more accurately
describing sorption.

Second, the equilibrium mode was also used more often for the Wurtsmith aquifer
material than the Metea and SPCF soils. This was probably due to the much lower
organic carbon content of the aquifer material. At this low level the partition coefﬁcients
were relatively low. Also the average Wurtsmith grain size was larger than the other
soils, and the 0-53 pm grain size was essentially absent in that sand. Ball and Roberts
(1991) state that the length scale for intraparticle diffusion is the particle grain size, so we
can conclude that either 1) intramineral diffusion was probably not a rate-limiting factor
in this case, or 2) columns were not given enough time for chemicals to diffuse deeply
into intraparticle sorption sites.

Third, the retardation factors for the SPCF soil are consistent until the highest

ﬂow rate, when R drops signiﬁcantly. The drop in R at higher ﬂow rates was noticed by

10

van Genuchten et a1. (1974) who explained that it occurred because of the decreased time

available for compounds to contact soil solids. This is important because one explanation
for increased k values at higher V0 is the decreased KP. Therefore, the effect of Kp on k in

. this case is not signiﬁcant.

Discussion

k vs. K, Relationship

The objective of this study was to move toward obtaining a quantitative
relationship between k and KP or v0 or both. In order to determine whether there was such
a relationship, plots of log(k) vs. log(Kp) were made of all compounds and soils for each
individual velocity. In all but one case, these plots showed no signiﬁcant correlation.
Therefore, at this point we cannot assume that there is a log(k) vs. log(Kp) relationship for
this study. However, it should be noted that K, values used here only covered a range of
approximately 2 orders of magnitude. Performing a similar study with compounds
covering a larger range of K, may have led to a signiﬁcant relationship.

k vs. v0 Relationship

Plots of the data for Wurtsmith aquifer material experiments showed a slight trend
of increasing k with increasing v0. However, there were too few points for this soil
because most of the data was ﬁt using an equilibrium model. The plot showing all
compounds in Metea soil columns showed a weakly positive correlation.

Values of log(k) were plotted against log(vo) for all compounds on the SPCF soil
as shown in Figure 2. The ﬁgure shows that k and v0 are positively correlated, as has
been found in past studies (Maraqa, 1995). One possible explanation for the observed

relationship is that k is dependent upon contaminant residence time in the column. This

11

would be evident from a plot of k vs. v0 because contaminant residence time is inversely
proportional to v0. In order to test whether the trend is related more to residence time or
to pore-water velocity alone, log(k) was plotted against log(LR/vo) (where LR/v0 is

contaminant residence time) for all compounds on SPCF soil as shown in Figure 3.

12

 

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Figure 3. log(k) vs. log(LR/vo) for all compounds on SPCF soil.

14

Comparison of regression lines from Figure 2 and Figure 3 reveals slightly better
correlation for plots of log(k) vs. log(LR/vo), which appears to indicate that the observed
trend of positive correlation between k and v0 is more related to contaminant residence
time than to pore-water velocity alone. Observation of Figures 2 and 3 revealed a trend
of increasing slope with decreasing hydrophobicity. To determine if there was a
quantiﬁable relationship, slopes from Figure 3 (slope = dlog(k)/dlog(LR/v0)) were plotted
against log(Kow). Figure 4 clearly shows that the slope becomes more negative for less
hydrophobic compounds. In other words, k is a stronger function of contaminant

residence time for less hydrophobic compounds.

15

 

 

 

 

 

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Figure 4. dlog(k)/dlog(LR/vo) vs. log(Kow) for all chemicals on SPCF soil.

16

The linear relationship observed in Figure 4 may be used with conﬁdence as a
predictive tool in the future only if it can be explained mechanistically. The following
discussion is an attempt to explain the trends observed. First we must acknowledge that
the mass-transfer coefﬁcient obtained is a lumped parameter, encompassing all sources of
slow desorption from soil solids. The three primary explanations for rate-limited sorption
are (Brusseau, 1989a): 1) chemical nonequilibrium, which would not apply because the
sorbates are nonpolar and essentially chemically nonreactive in this situation; 2) physical
nonequilibrium, which is not evident, as indicated by the symmetric, sigmoidal
breakthrough curves observed in nonsorbing tracer studies; and 3) intrasorbent diffusion,
which is the most likely cause. Intrasorbent diffusion is slow movement of sorbing
compounds in one or a combination of three different domains: 1) in intraparticle pore
water, 2) along mineral surfaces of pores, or intraparticle diffusion (IMD) and 3) within
the organic matter located on pore walls or grain surfaces, or intra-organic matter
diffusion (IOMD).

Film difﬁision, which some consider as contributing to physical nonequilibrium,
was determined to not be a factor in this study. This was determined by calculating ﬁlm
mass-transfer coefﬁcients for all compounds at each velocity using the method outlined
by Merk (1980) for chemical sorption in ﬁxed bed activated carbon adsorbers. Aqueous
diffusivities were estimated using the Wilke-Chang relationship as outlined in Weber and
DiGiano (1996). The differences between the mass-transfer rate coefﬁcients for the
highest and lowest velocities varied by less than 0.01% for the largest diameter particles

(worst case).

17

In light of the discussion of diffusion mechanisms mentioned above, the trends
seen in Figures 2-4 may be explained as follows. Brusseau et al (1991) presented an
interpretation of the ﬁrst-order mass-transfer model by deﬁning k in terms of a diffusion
coefﬁcient and a length scale, based on the assumption that intra-organic matter diffusion
was the rate-limiting mechanism. They stated that k = chy/(12(l-F)), where c is a shape
factor, Dpy is the diffusion coefﬁcient for the speciﬁc sorbate/sorbent pair (Lz/T), l is the
characteristic diffusion length (L), and F is the fraction of instantaneous sites. They also
cited the work of Ball (1991) who interpreted k in terms of retarded intraparticle
diffusion: k = [15Dp/(Rma2)], where Dp is the pore diffusion coefficient (Lz/T), Rim is the
retardation factor for sorption occurring inside the particle, and a is the particle radius
(L).

Based on these two interpretations, we may state that k oc D/lz, where D is a
diffusion coefﬁcient (Lz/T) and l is a characteristic diffusion length. Though one
diffusion mechanism may dominate, experimental techniques used in this study do not
allow us to make deﬁnitive conclusions regarding the absolute dominance of either
IOMD or IPD. Indeed, the former appears to be more important, but we cannot exclude
the latter as a contributor. Based on the proportionality shown, the mass-transfer rate
coefﬁcient, k, must be dependent upon two factors, D and I, and the inverse correlation
observed between k and v0 must be related to one of these two variables, or both.

The ﬁrst possibility is that contaminant residence time has an effect on D. Cussler
(1984) noted that diffusion coefﬁcients may change with changing concentration

gradients. The concentration gradients for this system change with velocity as follows.

18

When the soil column is ﬂushed with clean solution, the portion of contaminant-saturated
solution in larger pores is ﬂushed out immediately. However, in less accessible locations,
contaminant must ﬁrst diffuse into larger pores where it can be ﬂushed out of the column.
With high pore-water velocity the concentration gradient which drives the diffusion is
increased rapidly as clean water is ﬂushed through pores faster, ﬁlling the larger pores
with clean solution and driving the gradient up. At lower velocities the gradient is lower
because the ratio of the rate at which clean solution is replacing contaminated solution is
smaller. The smaller ratio occurs because diffusion of contaminants from smaller pores
occurs as clean water ﬁlls the larger pores. The additional contaminant in the large pores
lessens the effect of ﬂushing with clean solution.

This effect would be more evident for less hydrophobic compounds which are
preferentially partitioned to the aqueous phase. Diffusion coefﬁcients of compounds
strongly sorbed to organic matter on particle walls would be less affected by the changing
concentration gradient because their diffusion coeﬁicients are strongly affected by
diffusion within organic matter. Organic compound diffusion in organic matter has been
compared by some authors to that in polymers, where diffusivities are 2-8 orders of
magnitude lower than in the aqueous phase (Pignatello, 1989). Therefore, diffusion is
controlled by organic matter diffusion more for more strongly sorbed (more hydrophobic,
high Kow) compounds and less in less hydrophobic compounds (low KW). This would
explain the different slopes for each compound as shown in Figure 3, and the relationship

between dlog(k)/dlog(LR/v0) and log(Kow) shown in Figure 4.

19

The second explanation relates to a change in the characteristic diffusion length, I.
In order to understand the possible effect, one must understand that CXTFIT describes
the diffusion process as movement between two bulk phases of solution in pores. One
phase is the contaminated solution, and the other is clean solution. The concentration
gradient is the difference between the bulk concentrations of the clean solution and the
contaminated solution. As vO increases, the clean solution is forced through some pores
which are not accessed at lower velocities. As solution reaches these less accessible
locations, the distance between the bulk clean phase and the contaminated phase
decreases, and subsequently the diffusion path length decreases. This effect would be
more evident, again, for compounds which are partitioned more to the aqueous phase.
The effect on k would be less pronounced for compounds preferentially sorbed to organic
matter because diffusion within the organic matter into the aqueous phase would
dominate, as described above.
Summary and Conclusions

Column studies were performed with four nonionic organic compounds on three
different nonaggregated porous media at ﬁve velocities from z 2 to 100 cm/hr.
Desorption breakthrough curves were modeled using CXTFIT in order to obtain mass-
transfer rate coefﬁcients, k. Breakthrough curves for the Wurtsmith aquifer material were
best modeled in the equilibrium mode, indicating that nonequilibrium was minimal for
this very low organic carbon content medium.

Results from the SPCF soil columns indicated that k increased with increasing

velocity, which is consistent with the results of past investigators. The effect was more

20

pronounced for less hydrophobic compounds. A plot of dlog(k)/dlog(LR/v0) vs. log(Kow)
revealed a strong linear correlation. Two possible explanations of the observed trends
were presented. The ﬁrst explanation is that diffusion coefﬁcients, which are proportional
to k, were affected by the change in velocity. The second explanation is that clean
solution reached smaller pores as pore-water velocity increased, thus decreasing the
diffusion path length, which is inversely proportional to k V’.

These results indicate that we may have a predictive tool for determining k for the
range of velocities and compounds studied. Further studies would include compounds
covering a larger range of Kow and more soils with a wider range of organic carbon
contents. In addition, a study which allowed increased equilibration time would provide

insight into the validity of the explanation for the slope vs. log(Kow) relationship.

21

References

Ball, WP and RV. Roberts. 1991. Long-term sorption of halogenated organic chemicals
by aquifer material. 2. Intraparticle diffusion. Environ. Sci. Tech. 25: 1237-1249.

Bouchard, D.C., A.L. Wood, M.L. Campbell, P. Nkedi-Kizza, and P.S.C. Rao. 1988.
Sorption nonequilibrium during solute transport. J. Contam. Hydrol. 22209-223.

Brusseau, ML. 1992. Nonequilibrium transport of organic chemicals: The impact of
pore-water velocity. J. Contam. Hydrol. 92353-368.

Brusseau, ML. and P.S.C Rao. 1989a. Sorption nonideality during organic contaminant
transport in porous media. Critical Reviews in Environmental Control. 19:33-99.

Brusseau, ML and P.S.C. Rao. 1989b. The inﬂuence of sorbate-organic matter
interactions on sorption nonequilibrium. Chemosphere. 18:1691-1706.

Brusseau, M.L., R.E. Jessup and P.S.C. Rao. 1991. Nonequilibrium sorption of organic
chemicals: Elucidation of rate-limiting processes. Environ. Sci. Tech.. 25: 134-
142.

Brusseau, M.L., R.E. Jessup and P.S.C. Rao. 1990. Sorption kinetics of organic
chemicals: Evaluation of gas-purge and miscible techniques. Environ. Sci. Tech.
24:727-735.

Brusseau, ML. and ME. Reid. 1991. Nonequilibrium sorption of organic chemicals by
low organic-carbon aquifer materials. Chemosphere. 22:341-350.

Karickhoff, SW. 1980. Sorption kinetics of hydrophobic pollutants in natural sediments.
in Contaminants and Sediments. Ann Arbor Science. Ann Arbor, MI.

Maraqa, M. 1995. Transport of dissolved volatile organic compounds in the unsaturated
zone. Ph.D. Dissertation. Michigan State University, East Lansing, MI.

Merk, W., W. Fritz and EU. Schlunder. 1980. Adsorption kinetics in ﬁxed beds. Chem.
Eng. Sci. 36:743-757.

Parker, J .C. and M .Th. van Genuchten. 1984. Determining transport parameters from
laboratory and ﬁeld tracer experiments. Bulletin 84-3. Virginia Agricultural
Experimentation Station. Blacksburg, VA.

Pignatello, J .J . 1989. Sorption Dynamics of Organic Compounds in Soils and Sediments.
p. 45-79. In Reactions and Movement of Organic Chemicals in Soils, SSSA
Special Publication no. 22. Soil Science Society of America.

22

Pignatello, J .J . and B. Xing. 1996. Mechanisms of slow sorption of organic chemicals to
natural particles. Environ. Sci. Tech.. 3021-11.

van Genuchten, M.Th., J .M. Davidson and P.J. Wierenga. 1974. An evaluation of kinetic
and equilibrium equations for the prediction of pesticide movement through
porous media. Soil Sci. Soc. Amer. Proc. 38:29-35.

Weber, W.J. and F. A. DiGiano. 1996. Process Dynamics in Environmental Systems.
Wiley-Interscience. New York.

APPENDICES

APPENDIX A

APPENDIX A

Literature Review

Introduction

Extensive petroleum contamination of soils and groundwater has led researchers
to investigate fate and transport of organic contaminants in these media. This has led to
the development of models which attempt to describe mathematically the fundamental
processes occurring in such systems. These models use a mass balance approach with
such removal terms as biodegradation, volatilization and leaching. Sorption of
contaminants to soil solids affects each of those processes either directly or indirectly.
For example, studies have suggested that compounds entrapped in soil micropores are not
available for biodegradation (Alexander and Scow, 1989). Also, the amount of
contaminant leached from the soil with percolating rainwater depends upon the solution
phase concentration, which is directly related to sorbed concentration. Therefore, a
thorough understanding of sorption processes is essential to accurate modeling of fate and
transport of contaminants in soils and groundwater.

As a ﬁrst approximation, it was assumed that sorption of organic compounds to
soil or aquifer solids occurred instantaneously and could therefore be described by an
equilibrium distribution between phases. However, observations such as breakthrough
curves with extensive tailing, indicated slow sorption was occurring. Lapidus and

Amundson (1952) are generally credited with ﬁrst describing the slow approach to

23

24

equilibrium using a ﬁrst-order rate equation. An extensive review of nonideal processes,
including those related to sorption, is given in Brusseau and Rao (1989a).

In soil columns, three basic mechanisms could be responsible for the slow
sorptive uptake or release (Brusseau and Rao, 1989b). The ﬁrst possibility is chemical
nonequilibrium (CNE), which is caused by a slow reaction at speciﬁc sites on the sorbent
surface. This generally does not occur with nonionic organic compounds, but may occur
with ionic or polar organic compounds.

The second potential cause of sorption nonequilibrium is slow diffusion between
immobile and mobile pore water. The immobile water may be in one of several locations
such as internal porosity of soil aggregates, thin liquid ﬁlms surrounding soil particles or
at contact points between individual soil particles. This is called physical nonequilibrium
(PNE) and affects both sorbing and nonsorbing solutes. Symmetric sigmoidal
breakthrough curves of nonsorbing tracers such as tritiated water are evidence that PNE
does not contribute to nonequilibrium.

The ﬁnal potential cause of nonequilibrium is slow diffusion within the sorbent
matrix, which may be referred to as intrasorbent diffusion. Two basic mechanisms have
been proposed. These are intraorganic matter diffusion (IOMD) and intramineral
diffusion (IMD). Intraorganic diffusion (IOMD) is the movement of nonionic organic
compound (N 0C) molecules through a natural organic matter (N OM) matrix, which may
be ﬂexible or rigid (Brusseau and Rao 1989a; Brusseau et a1. 1991). For example, an
NOC molecule moves from the exterior to the interior of the NOM matrix under the
inﬂuence of a concentration gradient. On its way, it is detained at various spots by weak

bonding forces, such as van der Waals forces, with hydroxyl or other organic functional

25

groups on the NOM. It may also be subject to steric hindrance as it moves. The sorbate
would be hindered more in the more rigid portion of the NOM, where its shape and size
would affect movement. High concentrations of a cosolvent such as methanol would lead
to the rigid portions becoming more ﬂexible, thus increasing the rate of diffusion
(Brusseau et al., 1991).

Intramineral diffusion is movement of NOC molecules through a solid inorganic
aggregate (Ball and Roberts, 1991; Farrell and Reinhard, 1994a; Harmon and Roberts,
1994). The aggregate is formed by the cohesion of individual particles, leaving ﬁssures
where the particles come together, providing medium-size pores (mesopores).
Intraparticle micropores are also present within the primary particles. As an NOC
molecule moves toward the interior of the particle under the inﬂuence of a concentration
gradient, its movement is hindered as it adsorbs to surfaces along its path. Movement is
most restricted as it moves through the micropores, due to the enhanced adsorption as it
interacts with more than one surface. The tortuosity of pores increases resistance to
movement. Brusseau and Rao (1989b) cite several studies which indicate that IMD is not
likely to be important for NOCs. However, other investigators contend that for low
organic carbon porous media intramineral diffusion is the reason for slow sorption.

Pignatello and Xing (1996) summarize evidence supporting each theory.

Intraorganic Matter Diffusion:
1. Nonequilibrium behavior increases with increasing organic matter content.
2. Diffusion rates increase with presence of cosolvents.

3. Sorption is noncompetitive in most cases.

26

4. Diffusion rates decrease for those compounds capable of forming hydrogen bonds

with reactive surface sites found in organic matter.

Intramineral Diffusion:

1. Diffusion rates are almost always inversely dependent upon grain size.

2. Diffusion rates generally increase following acidiﬁcation of inorganic particles,
leading to dissolution of mineral oxides which cement the clays together. This

opens up pores and increases freedom of movement within the particle.

These different descriptions have been used by researchers in attempting to model
sorption of chemicals on porous materials. For example, Ball and Roberts (1991)
performed batch experiments to study adsorption rates of two chlorinated organic
compounds on aquifer sand and used a pore or radial diffusion model to ﬁt the data.
They concluded that the particle size may be an appropriate length scale for diffusion
based largely on their observation that uptake rates increased signiﬁcantly with
pulverization of particles. However, the pore diffusion model greatly overpredicted the
effect of decreasing the particle radius. A signiﬁcant difﬁculty in the modeling was
independent determination of the apparent difﬁisivity. This occurs due to the inability to
describe tortuosity and steric hindrance sufﬁciently. In addition, diffusion may occur
through organic matter sorbed to grain surfaces, and coefﬁcients of diffusion through
organic matter (as approximated by diffusion through polymers) can vary by 2-3 orders
of magnitude.

Farrell and Reinhard (1994a, 1994b) improved on the work of Ball and Roberts

(1991) by measuring desorption rates covering seven orders of magnitude for chlorinated

27

compounds on aquifer sand at 100% relative humidity. They noted that the pore
diffusion model could not ﬁt both the fast and slow desorbing portions of the data. They
proposed that sorption in intra-aggregate micropores may be responsible for the slow
release of contaminants.

Cameron and Klute (1977) described sorption as a two-site process, with part of
the sites participating in equilibrium distribution between solid and aqueous phases. At
the second type of sites, sorption is considered to be rate-limited (i.e., equilibrium is not
reached instantaneously, but is approached slowly). This description has been shown to
accurately model contaminant movement in many situations.

Previous Determination of Mass-transfer Coefficient

One current limitation is our inability to accurately determine the mass-transfer
coefﬁcient associated with the rate-limited sites. One method of determining the mass-
transfer coefﬁcient is to perform laboratory soil column tests and use a computer program
to perform least squares regression to ﬁt the breakthrough curve data. The coefﬁcient is
an output of the model. The major difﬁculty associated with this method is our inability
to directly apply coefﬁcients obtained in laboratory studies to ﬁeld situations. Perhaps
the greatest difference is that soil column studies are often performed at much higher ﬂow
rates than would be found in an actual ﬁeld situation.

Inverse relationship log(k) vs. log(Kp)

Several investigators have noticed the inverse relationship between mass-transfer
coefﬁcient and soil-water partition coefﬁcient (Karickhoff, 1980; Brusseau and Rao,
1989b, Brusseau and Reid, 1991; Brusseau, 1992). Brusseau and Rao (1989b) offer the

following explanation for the observed relationship. The mass-transfer coefﬁcient, k, is a

28

function of three parameters: 1) the diffusivity of the diffusing species, 2) the resistance
to diffusion associated with the sorbent matrix and 3) the diffusion path length. The
partition coefﬁcient, KP, is equal to Kocfoc, and K0c is a function of chemical structure and
size, and for intraorganic matter diffusion, f0c is related to diffusion path length. The
authors performed a linear regression of the data in an attempt to develop a predictive
tool for determining mass-transfer coefﬁcient. They compiled data from several studies
for both hydrophobic organic compounds (HOCs) and nonhydrophobic organic
compounds (N HOCs) and found that a line could be ﬁt through each data set. Data was
obtained from batch, column and gas-purge experiments. The correlation was good for
both, but higher for the HOCs.

However, the applicability of the equation describing the linear ﬁt is questionable
in light of later work performed, wherein various ﬂow rates were used in determining
mass-transfer and partition coefﬁcients. Brusseau (1992) showed that for low organic
carbon aquifer materials, an inverse relationship between the two coefﬁcients was present
for both high and low pore-water velocities (low velocity z 5 cm/hr and high velocity
between 45 and 90 cm/hr), but the line describing the relationship at high pore-water
velocity was shifted above that for the low velocity by about 2 orders of magnitude. The
correlation was poor for both lines. This indicates that the relationship found in the
previous study (Brusseau and Rao, 1989b) determined using data from all three
measurement techniques (batch, gas-purge and column studies) may have been somewhat
coincidental because variations in velocity for the experiments would have resulted in

increased scattering of data.

29

Pore-water velocity variation

Data presented by Bouchard et al. (1988) showed an increase in retardation with
decreasing pore-water velocity, and nonequilibrium was observed to increase with
increasing velocity. They attributed the sorption nonequilibrium to solute diffusion
within the organic matter matrix. Maraqa (1995) showed that mass-transfer coefﬁcient
increased with increasing pore-water velocity, noting that the dependence indicates that
mass-transfer coefﬁcient is a time-averaged parameter. As stated above, Brusseau (1992)
investigated the impact of pore-water velocity on nonequilibrium transport of nonionic
organic compounds in low organic carbon content aquifer materials. He found that
increasing velocity shifted the regression line of log(k) vs. log(vo) signiﬁcantly upward.

Therefore it has been shown that mass-transfer coefﬁcient is related to both
partition coefﬁcient and pore-water velocity. What is needed, then, is a relationship
describing the dependence upon pore-water velocity and partition coefﬁcient. And in
order for the relationship to be widely applicable, the mechanisms which control
contaminant sorption behavior must be understood. This study, which uses soils of
varying organic carbon content with pore-water velocities ranging over nearly two orders
of magnitude, provides additional data which may be interpreted in order to elucidate
rate-limiting processes occurring in transport of sorbing NOCs in soil columns.

The objective of this study is to elucidate the relationship between pore-water
velocity and mass-transfer coefﬁcient for soils with a range of organic matter contents.

Part of that objective is to discuss the processes which control rate-limited sorption, with

30

the eventual goal of developing a quantitative relationship among partition coefﬁcient,

pore-water velocity and mass-transfer coefﬁcient.

APPENDIX B

31

APPENDIX B

Materials and Methods

Solution Matrix

The solution matrix consisted of a 0.01 N solution of CaCl2 which is buffered
using a 10 mM solution of KHZPO4. The pH of the resulting solution was a: 4.5. This is
necessary to prevent dissolution of mineral grains and also to provide a solution which is
similar in ionic strength to what would be encountered in a ﬁeld situation. All solution
used in the columns was sterilized in an autoclave for at least 15 minutes. Autoclave tape
was used to verify complete sterilization in each batch autoclaved.
Chemical Compounds

The following compounds are used in this study: benzene, toluene, p-xylene and
naphthalene. These were chosen based on the following criteria: prevalence in
contaminated soil, potential for leaching into groundwater (i.e., water solubility and
volatility) and measurement detection limits. Table 3 shows properties of the

compounds.

Table 3. Chemical properties of compounds at 25°C. (Schwarzenbach et al., 1993)

 

 

log K...
Mol. -log P0 -log Cw"at Cwsat [(mol-L'l octanol)-
Compound Wt. (atm) (mol-L") (mg-L")b (mol-L" water)"]
benzene 78 0.9 1.64 1787 2.13
toluene 92 1.42 2.25 517 2.69
p-xylene 106 1.93 2.77 180 3.15
naphthalene 128 3 .43“ 3.61 31 3.36

 

 

 

a. Value shown is -IogP°(L) for solid phase
b. Values were calculated from compound molecular weight and aqueous solubility in mol-L".

32

Porous media

Because the main purpose of the study was to move toward obtaining a widely
applicable relationship among mass-transfer coefﬁcient and pore-water velocity or
partition coefficient, or both, one aquifer material and two soils with organic matter
contents of 0.05, 0.3 and 1.0%, respectively, were used. Media with varying organic
carbon were chosen because previous studies have indicated that the primary variable
affecting organic chemical sorption behavior is organic carbon (Voice, 1983).

The two soils were analyzed by the Department of Crop and Soil Science to
determine percent organic carbon. Percent organic carbon of the aquifer material was
measured using a Perkin Elmer CHN analyzer.

Ball and Roberts (1991) and Farrell and Reinhard (1994b) noted the dependence
of sorption rate parameters on grain size, so efforts were made to obtain soils with similar
grain size distributions. Table 4 shows the size distribution of each soil. Similar grain
size distributions were obtained by performing a sieve analysis on the SPCF soil,
calculating the particle size distribution and then separating other soils by size and
recombining fractions to obtain a similar distribution. The ﬁnest sieve used was No. 270,
which has an opening of 53 um. Therefore, the fraction collected by the bottom pan
contained grains up to 53 pm in diameter. This is noted because the ﬁnest fraction of the
Metea soil appeared ﬁner (i.e., it was more cohesive and poured less easily) than the
ﬁnest fraction of the SPCF soil. So though the same size is reported, the Metea soil

contains more ﬁne particles. It should also be noted that the Wurtsmith aquifer sand is

33

typical of low organic content material in that it lacks the ﬁnes usually present in surface
soil. Therefore, its grain size distribution varies from the Metea and SPCF soils.

Soils were sterilized by z 2 Mrad of gamma radiation for approximately 0.9 hour
at the Nuclear Reactor Laboratory at University of Michigan in Ann Arbor. Gamma
radiation is an effective method of sterilization which does not signiﬁcantly alter the soil

characteristics.

Table 4. Soil sieve analysis

 

 

Soil or Organic Grain size

Sand Type Carbon, % (250-425 um) (150-250 urn) (53-150 um) (0-53 pm)
SPCF 1.0 10.6% 22.8% 55.2% 11.4%
Metea 0.3 10.6% 22.8% 55.2% 11.4%
Wurtsmith 0.05 15% 70% 15% 0%

 

 

 

 

Plate counts

Plate counts were performed in order to test for the presence of microorganisms in
the soil-ﬁlled column. The method is as follows. First, 18.4 g of powdered general
purpose nutrient agar was mixed with 800 mL of deionized water in an Erlenmeyer ﬂask,
and the solution was brought. Foil was placed loosely over the mouth of the ﬂask, which
was then sterilized in an autoclave for 30 minutes. The solution was taken from the
autoclave and allowed to cool to about 60°C. It was then poured into commercially
sterilized petri dishes in the laminar ﬂow hood work area. The solution was cooled
overnight, allowing the solution to solidify.

As stated above, the purpose of the plate counts was to test for the presence of
microorganisms in the soil columns, but not necessarily the sample loops. Therefore, the

sample loops were removed and sterilized in an autoclave for 15 minutes to kill any

34

microorganisms which may be present. The loops were then re-attached to the columns,
and matrix solution was injected into the system with a syringe pump in order to ﬁll the
sample loop. Samples were collected by ﬁrst removing the efﬂuent spout from the
collection bottle, then connecting an air-ﬁlled plastic syringe to the tee at the beginning of
the sample loop, which was then depressed in order to force the solution out of the

sample loop. One mL samples were collected in commercially sterilized polystyrene
sample tubes, which were capped immediately.

These samples were taken to the laminar ﬂow hood where three 100 uL aliquots
from each sample were spread on the cooled agar plates. The plates were sealed with
paraffin wax paper and placed in an incubator at 30°C, where they remained for four
days, at which time the samples were inspected for microbial growth.

Experimental Setup

The proposed experimental setup is shown in Figure 5. Because this study is
focused on sorption processes alone, it is essential to account for all potential losses and
eliminate the sources when possible. Any losses which are not accounted for lead to
overestimation of contaminant sorbed by soil solids. The most probable losses are
volatilization, microbial degradation and sorption to equipment. In order to reduce
sorption to equipment, stainless is used wherever possible. The soil column, tubing and
tee ﬁtting shown in Figure 5 are all stainless steel. The syringe is made of glass. The
syringe plunger head and three-way valve are all made of Teﬂon, which has been shown

to absorb organic chemicals. Its use in these two cases was unavoidable.

35

 

Filter

 

Three-way
valve

 

 

 

Effluent

Syringe

7 PC}?

Syringe pMp

 

 

 

 

 

 

A

Sample
’/ 100p

Stainless steel :ﬁdlated
tee ﬁtting
Soil column

 

r—. (ill
1 1

 

 

 

 

Heating block

 

Figure 5. Experimental setup

 

36

Prevention of contaminant biodegradation

Extensive measures were required to ensure that microbial degradation of
compounds did not occur within the system. First, as much of the equipment as possible
(tubing, column, tee ﬁtting, three-way valve) and the matrix solution were sterilized in an
autoclave for at least 15 minutes. Second, when the system was set up, none of the
entrances to the system (e. g., tubing ends) were touched. Third, because it has been
observed that microorganisms can diffuse against the direction of solution ﬂow, measures
were taken to prevent them from entering the eﬁluent bottle and moving into the system.
The bottle needed be vented in order to prevent pressure buildup. Therefore, a needle
was placed in the rubber septum, and a 0.22 pm ﬁlter was placed at the head of the needle
in order to prevent invasion by microorganisms. The ﬁlter and needle were used directly
after opening from commercially sterilized packages. Fourth, microorganisms in the soil
are killed by treating the soil with gamma radiation. Finally, between the syringe and the
soil column, the stainless steel tubing was threaded through a small hole in a heating
block which was maintained at z60 °C. This is an added measure to prevent microbial
growth in the system.
Prevention of volatilization

Volatilization of compounds is only possible where the solution comes in contact
with air. Therefore, the system must be checked to ensure that leaks are not present and
that volatilization of compounds from the efﬂuent front are minimal. This was done by
performing a test of the system without the soil column. First, a solution was prepared

with target compounds at the proposed inﬂuent concentrations. The syringe was ﬁlled

37

with the solution, and then it was depressed until solution was seen emptying into the
effluent bottle. The syringe pump was then turned on in order to provide positive
pressure to the system. Next the three-way valve was rotated so that a sample could be
taken. The stainless steel cap on the tee at “A” in Figure 5 was removed, and an air-ﬁlled
syringe was connected to the tee via a stainless steel ﬁtting. Air was forced through the
sample loop, and a solution sample was collected at point “B” in Figure 5.

The volume was determined by weighing the sample vial and cap before and after
the sample was added. A sample was collected after the 100p was reﬁlled by the syringe
pump at the set volumetric ﬂow rate. This occurs after approximately one to two hours.
Another sample was taken at approximately three to four hours after the pump was turned
on. A ﬁnal sample was taken after the system had been ﬂushed for approximately one
day.

The compound concentrations were determined by headspace gas
chromatography. If the concentrations dropped from the initial sample to the second or
third, then there may be a leak in the system or a problem with volatilization at the front
of the solution ﬂow. If the concentration in the ﬁnal sample was much smaller than the
ﬁrst three, then chemical absorption by the Teﬂon plunger head or three-way valve may
have been present.

Porosity and bulk density determination

Two of the necessary input parameters for the CXTF IT program are porosity and

bulk density. Porosity (9) was determined as follows. First, a dry, empty steel column

with end ﬁttings and caps was weighed. Second, one cap was removed, the column was

38

ﬁlled with water, the cap was replaced, and the column weighed. The column was then
emptied and dried in an oven at 100°C. After the column was removed from the oven
and cooled, the end ﬁttings and caps were replaced and covered with foil. The columns
were then heated in an autoclave for 30 minutes. Following this the columns were
removed and cooled, and the foil was removed. Dry soil was then added to each column,
and the end caps replaced. The columns were then weighed. Following this, the end caps
were removed, and the columns connected to the system. A 50 mL plastic syringe was
ﬁlled with C02, which was then injected slowly into the soil column to displace air in the
pores. The use of CO2 enables complete saturation of the column by replacing relatively
insoluble pore air with the very water-soluble C02. Solution matrix was then ﬂushed
through the system for at least one day in order to fully saturate the column. The
saturated column was then removed from the system, end caps again replaced, and the
column weighed.

The porosity is equal to pore volume divided by the total volume. The column
volume (in mL) is simply equal to the difference between the water-ﬁlled column weight
and the empty, dry column weight in grams (1 mL of water weighs 1.00 g at 20°C). The
pore volume (in mL) is equal to the weight of the saturated soil column in grams minus
the weight of the dry soil-ﬁlled column. The porosity is then simply equal to the pore
volume divided by the total volume. In previous studies using the same columns, the
dead volume (volume in end ﬁttings and caps) is less than 1% of the total volume, and

therefore is negligible. Table 5 shows soil column properties.

39

Table 5. Soil column properties summary

 

 

 

 

 

 

 

 

 

 

Wurtsmith Aquifer Sand
Column
target velocity Pore
(cm/hr) Length (cm) volume (mL) p (g/cm3) 9
2.0 15.4 5.50 1.52 0.365
5.3 15.4 5.40 1.53 0.352
14.1 15.3 5.50 1.53 0.364
37.5 15.2 5.30 1.55 0.355
100.0 15.2 5.50 1.53 0.366
Metea Soil
Column
target velocity Pore
(cm/hr) Length (cm) volume (mL) p (g/cm’) 0
2.0 15.3 5.61 1.64 0.38
5.3 15.4 5.67 1.59 0.38
14.1 15.3 5.58 1.60 0.38
37.5 15.2 5.40 1.60 0.37
100.0 15.4 5.77 1.54 0.39
SPCF Soil
Column
target velocity Pore
(cm/hr) Length (cm) volume (mL) p (g/cm“) 0
2.0 15.2 7.61 1.35 0.50
5.3 15.2 6.02 1.43 0.41
14.1 15.2 6.93 1.36 0.47
37.5 15.2 6.31 1.38 0.42
100.0 15.2 6.98 1.30 0.46

 

 

40

Pore-water velocity

Because the primary variable of interest is the desorption rate (as opposed to
adsorption rate), only the desorption phase breakthrough curves were examined. In
addition, it is important that distribution of the compounds between soil and solution be
at or near equilibrium at the beginning of the desorption phase. As noted earlier in the
introduction, sorptive uptake usually consists of a fast period (from a few minutes to a
few hours) wherein roughly 50% of the solid sorptive capacity is reached, followed by
slow uptake of contaminant until equilibrium is reached. Due to this slow uptake, it was
decided that adsorption should be approached using a fast ﬂow rate until the
breakthrough front showed efﬂuent concentrations very near inﬂuent concentrations,
followed by a period of waiting and another period of ﬂushing at a lower ﬂow rate.

The high/low ﬂow rate is necessary for the following reasons. 1) The possibility
of biodegradation is always present, despite extreme care in preparation of system setup,
and therefore, the duration of the experiment should be limited as much as possible. This
is accomplished by rapidly approaching adsorption equilibrium 2) Intrasorbent diffusion
is commonly seen as the limiting factor causing nonequilibrium, in order to accurately
determine the mass-transfer rate must mimic the natural diffusive system (e.g., the
desorption rate from the inner layers of organic matter would be much lower than the rate
from the outer layers to the surrounding water layer).

The study used pore-water velocities of 2.0, 5.3, 14.1, 37.5 and 100 cm/hr. The
highest ﬂow rate, 100 cm/hr, was chosen because it is the maximum ﬂow rate at which
the column soil will not be pushed upward by the force of the water. For a sandy soil the

maximum inﬁltration rate is just over 2 cm/hr. This sets the lower limit. The

41

intermediate velocities were chosen so as to be logarithmically evenly spaced between the
two extremes.
General

The compounds were placed in one solution and co-eluted. It has been shown in
previous studies that competition effects are minimal at low contaminant concentrations
(Maraqa, 1995). The soil columns were run at saturated conditions in order to mimic the

worst case scenario in a ﬁeld situation.

APPENDIX C

APPENDIX C

Data Tables

.x 5 ,3 @8835 8 602650 8: 983 880888 6352335: 05 wow: 83 $88 825:3? 05 555 .m

 

 

 

32-93 3:. 2% 33 EN 88 :88 m8: :8 88 2.: 2:22:82 2:
22-03 2:. 4.2: $8 28 88 :88 82c 58 M28 8: 05:2: 2:
8:285 3:. 22: x x 8.8 :3: x x :3: 8: 802:2 2:
86285 m3 :2: x x 8:: 28:: x x :3 8: £8an 2:
2255 S: in 82° :8: N28 mod :8: 82¢ 22:: am: 05:22:22 22
882:8: S: 22 x x $8 :23 x x :88 8: 8:2: 22
88285 S: E... x x was 28:. x x :2 8: 88:02 22..
8:22:35 S: 2: x x 38 2:2: x x 2:: 8: 83:8 2%
3:29,: :3 2: 2:3 :2; :8 82¢ 82:: 88 £8 a: 052.282 2:
2:35 :8 2: :8 22:: 88 88 :2: 22¢ 88 G: 052: 3:
2253 :8 2: $8 as: mad 2:: 82o 82° :8 2.: 88:8 2:
2:35 :3 2: 2:8 :88 :8 :88 :3: 22¢ 82o :: 850m 2.:
82-93. mm; ”S ES 82¢ 88 «2:: 83 Ed 98 E: 82:28:52 2
22-93. 83 ”S 88 28:: 38 :3: :3: $8 «8:: X: 25:2: 2m
2:293 88 8: £8 :2: 38 :3: 22:: $8 82¢ a: 2528. 2m
8:22:35 83 ”S x x 38 so: a x was 2: 05.80: 8
3:53 38 as Ed 88 was 2.3 m8: 223 N88 8: 22888 N
822228: 98 am: 2 2 82¢ 58 x x 82o 2: 822: N
8:22:25 2.8 a: x x 88 M23 x x as: 2: 0828 m
8:22:25 2.8 an: x a $8 :88 x x :88 2: 83:8 N
082 a 2 :08: a: a: :2 m8 3 a .2 m 23888 .> case

 

 

.28 Shawn 5:83.53 :8 8308.88 59:0 3on .c 2an

42

43

.038 05 5 od ma 850% mm :5 62:3 gamma: 32 be, 2:8 .83 025, m Baum 05 £33 088 E :2: 802 .m

 

 

 

32-05 EN 2; 2:: 02¢ 23:. 2:3 $2 33 Q2: 22 0525232 2:
32-2: EN 2:: 32:: N2: 8% NE; mNS 3:: 83 8: 822: 2:
32-23 EN 2; 38 ONN 33 N28: 3:: 32¢ :23 N2N 252$ 2:
2255 EN 2; ES 2: 33 2:8: 32:: :3 22 RN 83:3 2:
2:33 3N EN RN: N: N3: 02:5 8:: N23 N8: NE 0825232 23
32-22:. EN EN 22:: :N 23.0 :83: N: Na: EN: 22: 2522 22
3255 EN EN 225 2.: N8: 8:: 3: NE: 02:: N2: 88:3 2m
3253 EN EN 2:: NE: 23:: N22; 8: $3 N23 NN: 835: 22
3:35 a: 2: N2; 2:: 32¢ 2:3 :22: SN: 33 m3 08252:“: 2:
3:33 a: 2: 2:: RN N8: 8:: 32¢ 82¢ 22:: :N: 082: S:
3:55 2: 2: 2:: 2: N23 MEN: mad $22: 2:: 2: ”82$ 3:
22.23. :N 2: 25:: c? was 2.8:. $3 32¢ 28:: 2: 850m 3:
32-05 $2 3:. N8: 2:: E2 :N:.o 82 NR: NE: 2:: vagina: 2
3:223. $2 v22 23 m3 3:. 8mm: 32:: Ed 25:: a2: 2.2»: 2
32-23 and :22 N23 SN 82:: NNNS :N $3 2.2:. N2: 082,; 2m
3:53 32° :3 2:: mNN 82 35: N2: :33 22° 2: 835m 2
22-93 $2 2:: 225 N23 23 :2; 2: 3N: 82 8:“ 05252:“: N
22-03 32 a2: .2: N2 32 N22: 83 N35 N23 8: 8222 N
8:22:23: :32 :2: x 2 32¢ 83:. x x as: S: 88:92 N
5:52ch :32 22: x x 33 :23 x 2 m8: 2: 838m N
252 a f :08: n: N N: :3 s n a: a 25.388 2 35

 

:8 882 8.: 382582 39:0 3on .n 033‘

 

44

 

 

 

£35 a: N3 83 8+ 443 $23 3.3 $23 $3 $2. £23222 2:
£35 ”44 N3 83 $34 $3 $23 84: $3 $3 £3 £2? 2:
£35 44.: N3 O3 9% 33 $43 83 $3 493 33 £2.45 84
£2.35 44.: $8 33 443m 33 33 83 $3 83 $4 £032 2:
£35 $3 3m $3 :3 $3 33 384 83 83 32 £032,432 3m
£295 $3 3m 33 a3 33 $23 $3 $3 82 23 £2? 3m
£35 $3 3m 33 $3 33 E3 493 £3 £3 83 £225 3m
£35 $3. 3m 53 N53 33 883 S3 83 33 m3 £032 2m
£35 $4 $44 $3 23 «.83 $443 83 33 $3 4a.: £2332 4.:
£35 $4 $44 23 :3 $3 $23 o$.o $3 83 :3 £2? 4.:
£35 $4 $44 33 $3 83 $83 $3 53 33 $3 £225 4.:
£35 $4 $44 $3 83 $3 433 a3 33 23 34 £35 4.:
£35 $3 $3 23 $3 $3 $23 23 $3 $3 8.3 £03233 3
£35 $3 $3 $3 $3 33 223 Ed 23 $2 83 £2? 2
£35 $3 $3 233 323 R3 $3 33 $3 83 Sm £225 3
£m-o5 $3 $3 $3 $823 33 $3 4433 $3 $3 83 £33 3
£35 £4 E 83 :3 $3 33 83 Q3 33 $44 £2332 N
4432 £4 E x 2 $3 $3 2 x 34 £3 £2? N
432 2.4 E x x :3 23 x 2 $3 43 £2.45 N
4432 ”N4 5 x x 33 $3 2 2 $3 $4 £03m N
£22 a f 4252 m 2 N2 2mm 3 a J 2 4252488 2, s35

 

dam mUmm 8m E80883 398 E52 .w 2an

 

45

Table 9. Column data for Wurtsmith aquifer material with target v0 = 2 cm/hr.

 

 

 

 

C/C0
Pore volumes Benzene Toluene Xylene Naphthalene
0.00 0.74 0.74 0.70 0.86
0.30 0.94 0.93 0.86 0.89
0.71 1.01 0.98 0.90 0.88
1.03 0.72 0.77 0.78 0.83
1.39 0.0209 0.0406 0.1437 0.3105
1.77 0.00415 0.00807 0.0234 0.0853
2.12 0.00307 0.00532 0.0131 0.0494
2.64 0.00212 0.00326 0.00867 0.0285
3.04 0.00169 0.00299 0.00705 0.0229
3.61 0.00143 0.00238 0.00512 0.0204
4.02 0.000887 0.00217 0.00485 0.0172
4.90 0.000817 0.00137 0.00371 0.0141
6.06 0.000505 0.000971 0.00255 0.0120
7.46 0.000396 0.000817 0.00196 0.0114

 

 

46

Table 10. Column data for Wurtsmith aquifer material with target v0 = 5.3 cm/hr.

 

 

 

 

C/C0
Pore volumes Benzene Toluene Xylene Naphthalene

0.00 0.977 1.012 0.975 1.046
0.32 0.946 0.972 0.914 0.978
0.75 1.064 1.101 1.059 1.103
1.11 0.612 0.729 0.866 0.999
1.42 0.0247 0.0512 0.156 0.363
1.89 0.00428 0.00914 0.0299 0.122
2.27 0.00280 0.00623 0.0163 0.0723
2.55 0.00199 0.00447 0.0112 0.0500
2.92 0.00160 0.00356 0.00856 0.0345
3.32 0.00125 0.00277 0.00748 0.0305
3.84 0.00115 0.00227 0.00576 0.0234
4.28 0.000951 0.00212 0.00518 0.0207
5.02 0.000835 0.00176 0.00423 0.0165
5.94 0.000760 0.00168 0.00346 0.0140
6.34 0.000607 0.00150 0.00328 0.0133
7.70 0.000766 0.00182 0.00342 0.0171
8.70 0.000537 0.00135 0.00269 0.0123
9.62 0.000350 0.00119 0.00262 0.0114
10.49 0.000307 0.00102 0.00217 0.00839
11.62 0.000496 0.00109 0.00228 0.01010
13.59 0.000372 0.000883 0.00185 0.00788
16.55 0.000279 0.000748 0.00166 0.00783
20.20 0.000228 0.000691 0.00149 0.00601

 

 

Table 11. Column data for Wurtsmith aquifer material with target v0 = 14.1 cm/hr.

47

 

 

 

 

C/CO
Pore volumes Benzene Toluene Xylene Naphthalene
0.00 1.175 1.171 1.232 1.279
0.30 1.154 1.184 1.212 1.279
0.67 1.155 1.158 1.221 1.307
1.03 1.067 1.120 1.185 1.311
1.39 0.0843 0.124 0.277 0.601
1.76 0.0150 0.0221 0.0454 0.126
2.12 0.00517 0.0101 0.0263 0.0721
2.48 0.00229 0.00532 0.0152 0.0476
2.85 0.00189 0.00398 0.0109 0.0383
3.21 0.00157 0.00327 0.00800 0.0358
3.58 0.00129 0.00279 0.00703 0.0260
3.94 0.00108 0.00249 0.00620 0.0226
4.30 0.00098 0.00189 0.00508 0.0189
4.67 0.00085 0.00189 0.00499 0.0173
5.03 0.00095 0.00157 0.00406 0.0187

 

 

Table 12. Column data for Wurtsmith aquifer material with target v0 = 37.5 cm/hr.

48

 

 

 

 

C/C0
Pore volumes Benzene Toluene Xylene Naphthalene
0.00 0.943 0.988 0.978 1.100
0.31 1.027 1.074 1.061 1.173
0.69 0.680 0.707 0.705 0.876
1.06 0.363 0.448 0.621 0.971
1.82 0.00406 0.00684 0.0165 0.0590
2.20 0.00285 0.00471 0.0108 0.0415
2.61 0.00199 0.00351 0.00770 0.0284
3.02 0.00163 0.00276 0.00635 0.0260
3.35 0.00146 0.00252 0.00554 0.0238
3.71 0.00142 0.00218 0.00483 0.0191
4.10 0.00106 0.00191 0.00416 0.0184
4.46 0.00105 0.00188 0.00381 0.0156
4.84 0.000869 0.00170 0.00335 0.0149
5.61 0.000674 0.00128 0.00273 0.0124

 

 

Table 13. Column data for Wurtsmith aquifer material with target v0 = 100 cm/hr.

49

 

 

 

 

C/Co
Pore volumes Benzene Toluene Xylene Naphthalene

0.00 0.930 0.946 0.951 1.004

0.28 0.911 0.942 0.977 1.032

0.64 0.914 0.943 0.974 1.015

1.00 0.763 0.820 0.924 1.050

1.37 0.0472 0.0695 0.1507 0.3155
1.73 0.00674 0.0110 0.0281 0.0639
2.09 0.00388 0.00610 0.0150 0.0371
2.46 0.00294 0.00397 0.00979 0.0265
2.82 0.00212 0.00335 0.00741 0.0215
3.19 0.00181 0.00285 0.00643 0.0196
3.73 0.00153 0.00243 0.00537 0.0171
4.28 0.00099 0.00177 0.00374 0.0131
4.82 0.000854 0.00161 0.00356 0.0132
5.37 0.000789 0.00135 0.00298 0.0114
5.91 0.001601 0.00213 0.00338 0.0111

 

 

50

Table 14. Column data for Metea soil with target v0 = 2 cm/hr.

 

 

 

 

C/C0
Pore volumes Benzene Toluene Xylene Naphthalene

0.00 1.065 0.837 0.646 1.032
0.29 0.921 0.741 0.619 0.917
0.65 0.908 0.648 0.580 0.868
1.06 0.733 0.616 0.448 0.775
1.36 0.105 0.314 0.362 0.555
1.72 0.0205 0.0893 0.28 0.640
2.08 0.00731 0.0236 0.20 0.590
2.43 0.00071 0.00135 0.0136 0.300
2.79 0.00288 0.00532 0.0650 0.437
3.14 0.00233 0.00390 0.0443 0.410
3.50 0.00162 0.00252 0.0247 0.320
3.81 0.00148 0.00224 0.0190 0.333
4.23 0.00119 0.00170 0.0123 0.304
4.92 0.000191 0.00029 0.00153 0.173
5.28 0.000912 0.00115 0.00629 0.220
5.64 0.000784 0.00100 0.00488 0.174
6.23 0.000686 0.000838 0.00377 0.147
6.48 0.00073 8 0.000799 0.00362 0.139
7.21 0.000603 0.000650 0.00281 0.1 14
7.58 0.000599 0.000628 0.00264 0.100
7.94 0.000985 0.000645 0.00249 0.1 18
8.35 0.000556 0.000536 0.00219 0.0866
8.65 0.000554 0.000505 0.00204 0.0793
8.79 0.000526 0.000506 0.00186 0.0709
9.33 0.000543 0.000467 0.00185 0.0744
9.77 0.000555 0.000474 0.00168 0.0982
10.31 0.000470 0.000447 0.00140 0.0743
10.86 0.000466 0.000400 0.00141 0.0792
11.38 0.000279 0.000325 0.00103 0.0516
11.63 0.000312 0.000381 0.00117 0.0639
1 1.93 0.000288 0.000383 0.00119 0.0584
12.43 0.000302 0.000334 0.00112 0.0538
12.89 0.000297 0.000327 0.00102 0.0495
13 .39 0.000263 0.000301 0.00095 0.0459
14.10 0.000234 0.000251 0.000847 0.0428
15.00 0.000263 0.000269 0.000819 0.0351
15.66 0.000292 0.000269 0.000749 0.0335
15.94 0.000221 0.000265 0.000749 0.0295
16.80 0.000184 0.000222 0.000723 0.0270

 

 

 

Table 14 (cont’d)

51

 

17.83
18.42
19.17
20.18
21.09

0.000091
0.000224
0.000227
0.000215
0.000193

0.000126
0.000216
0.000188
0.000208
0.000204

0.000333
0.000657
0.000591
0.000632
0.000600

0.0073
0.0259
0.0194
0.0233
0.0202

 

 

 

52

Table 15. Column data for Metea soil with target v0 = 5.3 cm/hr.

 

 

 

 

C/C0
Pore Volume Benzene Toluene Xylene Naphthalene
0.00 1.109 0.908 0.674 0.977
0.30 1.028 0.834 0.648 0.903
0.56 1.010 0.865 0.670 1.003
0.82 0.955 0.849 0.666 0.902
1.10 0.748 0.714 0.530 0.781
1.37 0.357 0.550 0.454 0.754
1.62 0.118 0.300 0.358 0.667
1.88 0.0317 0.1203 0.2548 0.549
2.14 0.0134 0.0545 0.1883 0.486
2.41 0.00712 0.0258 0.1316 0.416
2.67 0.00483 0.0151 0.0965 0.399
2.98 0.00353 0.00950 0.0712 0.401
3.24 0.00287 0.00719 0.0540 0.401
3.53 0.00221 0.00495 0.0365 0.312
3.78 0.00205 0.00432 0.0312 0.338
4.04 0.00175 0.00359 0.0235 0.271
4.31 0.00153 0.00286 0.0183 0.252
4.58 0.00146 0.00271 0.0159 0.247
4.91 0.00127 0.00229 0.0122 0.206
5.27 0.00115 0.00192 0.00992 0.222
5.62 0.00104 0.00170 0.00810 0.189
6.64 0.000821 0.00123 0.00525 0.149
6.94 0.000764 0.00118 0.00477 0.122
7.42 0.000712 0.00109 0.00415 0.114
7.67 0.000655 0.00097 0.00359 0.108
8.00 0.000658 0.00096 0.003 53 0.106
8.32 0.000643 0.00095 0.00324 0.134
8.59 0.000642 0.000879 0.00297 0.127
8.85 0.000616 0.000900 0.00296 0.122
9.19 0.000658 0.000923 0.00294 0.120
9.46 0.0005 84 0.000847 0.00280 0.108
9.87 0.000490 0.000767 0.00238 0.0900
10.31 0.000435 0.000695 0.00221 0.0940
10.56 0.000404 0.000649 0.00208 0.0832
10.89 0.000401 0.000668 0.00205 0.0824
1 1.40 0.000385 0.000587 0.00188 0.0749
12.52 0.000511 0.000568 0.00163 0.0615
14.74 0.000281 0.000395 0.00117 0.0419
15.02 0.000316 0.000426 0.00123 0.0386

 

 

Table 15 (cont’d)

53

 

 

15.37
15.81
16.80
17.74
18.48
20.33
21.17
22.60
24.12
25.44
26.10
26.92
28.23
29.46
30.77
32.66
33.87
35.11
36.84
37.58
39.22
40.42
44.14
45.27
46.08
47.91
48.69
49.98

0.000304
0.000279
0.000401
0.000254
0.000204
0.000166
0.000157
0.000176
0.000131
0.000168
0.000158
0.000127
0.000149
0.000141
0.000133
0.000144
0.0001 16
0.000119
0.000370
0.000067
0.000142
0.000111
0.000091
0.000055
0.000130
0.000045
0.000075
0.000062

0.000381
0.000343
0.000384
0.000296
0.000285
0.000281
0.000250
0.000257
0.000237
0.000217
0.000229
0.000275
0.000200
0.000221
0.000198
0.000243
0.000229
0.000148
0.000216
0.000166
0.000157
0.000150
0.000141
0.000129
0.000160
0.000137
0.000141
0.000113

0.001 15

0.00108

0.00108

0.00093

0.00096

0.000777
0.000735
0.000704
0.000648
0.000616
0.000483
0.000658
0.000529
0.000586
0.000491
0.000481
0.000470
0.000373
0.000342
0.000355
0.000439
0.000356
0.000359
0.000284
0.0003 70
0.000329
0.000251
0.000302

0.0391
0.0372
0.0306
0.0270
0.0293
0.0209
0.0175
0.0164
0.0160
0.0162
0.0123
0.0124
0.0139
0.0126
0.0103
0.0102
0.0087
0.0098
0.0103
0.00699
0.00678
0.00674
0.00502
0.00538
0.00615
0.00357
0.00513
0.00405

 

 

54

Table 16. Column data for Metea soil with target v0 = 14.1 cm/hr.

 

 

 

 

C/C0
Pore volumes Benzene Toluene Xylene Naphthalene
0.00 1.018 0.753 0.903 0.922
0.30 0.955 0.739 0.862 0.879
0.63 0.816 0.737 0.769 0.917
0.87 0.691 0.628 0.629 0.740
1.15 0.523 0.547 0.541 0.696
1.42 0.281 0.457 0.399 0.681
1.66 0.113 0.341 0.239 0.578
1.93 0.0379 0.2515 0.1170 0.521
2.22 0.0151 0.1772 0.0531 0.437
2.49 0.00797 0.1266 0.0278 0.390
2.74 0.00556 0.1030 0.0183 0.400
2.99 0.00395 0.0745 0.0117 0.342
3.35 0.00280 0.0518 0.007410 0.301
3.61 0.00236 0.0416 0.005866 0.300
3.85 0.00206 0.0328 0.004723 0.265
4.11 0.00182 0.0280 0.004143 0.284
4.35 0.00163 0.0229 0.003507 0.238
4.60 0.00158 0.0202 0.003265 0.239
4.96 0.00130 0.0153 0.002595 0.209
5.32 0.00113 0.0120 0.002170 0.199
5.68 0.00103 0.0100 0.001937 0.171
6.03 0.000895 0.00799 0.001618 0.153
6.41 0.000793 0.00712 0.001484 0.144
7.23 0.000645 0.00550 0.001193 0.1297
7.49 0.000610 0.00520 0.001175 0.1314
7.75 0.000579 0.00460 0.001052 0.1 180
8.11 0.000912 0.00625 0.001922 0.1302
8.38 0.000830 0.00618 0.001942 0.1218
8.65 0.000997 0.00574 0.001686 0.1210
9.03 0.000926 0.00560 0.001579 0.1284
9.53 0.000874 0.00487 0.001582 0.1128
9.90 0.000771 0.00472 0.001452 0.0950
10.16 0.000714 0.00425 0.001334 0.0892
10.44 0.000702 0.0041 1 0.001261 0.0966
10.82 0.000664 0.00406 0.001354 0.0891
11.76 0.000708 0.00347 0.001214 0.0651
12.65 0.000586 0.00334 0.001202 0.0538
13.51 0.000454 0.00324 0.001168 0.0456
14.47 0.000390 0.00304 0.001059 0.0437

 

 

Table 16 (cont’d)

55

 

 

15.28
17.79
18.31
18.60
19.81
20.66
21.50
22.34
23.20
23.99
24.58
25.41
26.46
27.54
28.18
28.78
29.67
30.51
31.55
32.36
33.20
34.21
39.31
39.67
40.01
40.53
40.94
41.73
42.04
43.04
44.26
47.31

0.000416
0.000392
0.000312
0.000244
0.000394
0.000330
0.000298
0.000419
0.000220
0.000202
0.000286
0.000168
0.000207
0.000178
0.000181
0.000218
0.000215
0.000173
0.000203
0.000138
0.000287
0.000181
0.000152
0.0001 19
0.000104
0.000256
0.000228
0.000091
0.000112
0.000121
0.000336
0.000105

0.00282
0.00208
0.00206
0.00210
0.00201
0.00178
0.00212
0.0021 1
0.00194
0.00168
0.00171
0.00155
0.00158
0.00142
0.00137
0.00137
0.00142
0.00140
0.00102
0.00105
0.00149
0.00122
0.00102
0.00126
0.001 19
0.00103
0.001 11
0.001 1 1
0.001 14
0.001 11
0.00098
0.00106

0.00101 1
0.000709
0.000603
0.000814
0.000712
0.000581
0.000834
0.000900
0.000781
0.000729
0.000723
0.000709
0.000653
0.000610
0.000591
0.000598
0.000614
0.000659
0.000569
0.000381
0.000633
0.000681
0.000515
0.000554
0.000665
0.000617
0.000584
0.000546
0.000560
0.000516
0.000483
0.000468

0.0640
0.0387
0.0323
0.0347
0.0331
0.0436
0.0388
0.0361
0.0250
0.0568
0.0392
0.0408
0.0268
0.0236
0.0257
0.0287
0.0222
0.0254
0.0243
0.0218
0.0201
0.0122
0.0217
0.0181
0.0093
0.0185
0.0174
0.0197
0.0256
0.0324
0.0239
0.0165

 

 

56

Table 17. Column data for Metea soil with target v0 = 37.5 cm/hr.

 

 

 

 

C/CO
Pore volumes Benzene Toluene Xylene Naphthalene
0.00 1.049 1.047 1.055 1.198
0.32 0.922 0.892 0.954 1.165
0.60 0.846 0.768 0.830 1.089
0.86 0.819 0.722 0.760 1.053
1.14 0.658 0.627 0.665 0.939
1.42 0.387 0.467 0.564 0.909
1.69 0.154 0.269 0.439 0.792
2.34 0.0221 0.0606 0.240 0.582
2.60 0.0135 0.0390 0.194 0.581
2.86 0.00798 0.0230 0.136 0.438
3.12 0.00593 0.0171 0.115 0.441
3.38 0.00438 0.0121 0.0863 0.393
3.67 0.00352 0.00924 0.0689 0.373
3.93 0.00320 0.00799 0.0590 0.371
4.20 0.00270 0.00642 0.0472 0.325
4.49 0.00239 0.00545 0.0385 0.321
4.75 0.00201 0.00441 0.0298 0.253
5.12 0.00177 0.00375 0.0244 0.263
5.49 0.00152 0.00324 0.0199 0.224
5.86 0.00138 0.00277 0.0161 0.242
6.23 0.00122 0.00247 0.0136 0.191
6.45 0.00115 0.00231 0.0124 0.202
6.97 0.00103 0.00208 0.0105 0.177
7.34 0.00095 0.00183 0.0088 0.160
7.71 0.00094 0.00181 0.0085 0.159
8.19 0.00147 0.00307 0.0135 0.196
8.56 0.00124 0.00297 0.0126 0.163
8.93 0.00116 0.00271 0.0150 0.151
9.30 0.00106 0.00267 0.0105 0.142
9.69 0.00106 0.00214 0.00952 0.150
10.06 0.00116 0.00231 0.00926 0.128
10.42 0.00106 0.00237 0.00885 0.115
10.79 0.00120 0.00218 0.00871 0.114
11.16 0.00116 0.00223 0.00869 0.105
12.08 0.00108 0.00230 0.00759 0.0971
13.08 0.00130 0.00192 0.00673 0.0837
13.93 0.00134 0.00216 0.00618 0.0789
14.88 0.00123 0.00376 0.00877 0.0971
15.79 0.000802 0.00173 0.00554 0.0593

 

 

Table 17 (cont’d)

57

 

 

16.71
17.64
19.67
20.09
20.42
21.34
22.30
23.25
24.12
25.06
26.03
26.90
27.82
28.77
29.73
30.62
31.66
32.62
33.43
34.86
35.36
36.23
37.08
38.14
38.93
39.90
40.88
41.67
47.79
48.99
49.69

0.000788
0.000401
0.000429
0.000349
0.000332
0.000366
0.000375
0.000349
0.000400
0.000291
0.000179
0.000215
0.000187
0.000238
0.000256
0.000156
0.000184
0.000127
0.000171
0.000144
0.000141
0.000188
0.000182
0.0001 16
0.000106
0.000126
0.000137
0.0001 13
0.000139
0.000100
0.0001 15

0.00151

0.00135

0.001 19

0.00109

0.001 13

0.001 12

0.00120

0.001 14

0.000939
0.000992
0.000880
0.000804
0.000824
0.000790
0.000807
0.000799
0.000823
0.000813
0.000799
0.000821
0.000827
0.000833
0.000804
0.000798
0.000848
0.000807
0.000815
0.000772
0.000770
0.000807
0.000812

0.00508
0.00500
0.00413
0.00390
0.00451
0.00382
0.00354
0.00389
0.00314
0.00288
0.00289
0.00317
0.00325
0.00312
0.00319
0.00315
0.00325
0.00321
0.00315
0.00324
0.00326
0.00329
0.00317
0.00315
0.00335
0.00319
0.00322
0.00305
0.00304
0.00318
0.00320

0.0983
0.0548
0.0224
0.0443
0.0204
0.0215
0.03 83
0.0353
0.0330
0.0308
0.0297
0.0280
0.0287
0.0275
0.0281
0.0278
0.0287
0.0283
0.0278
0.0286
0.0288
0.0290
0.0280
0.0278
0.0295
0.0281
0.0284
0.0269
0.0268
0.0281
0.0282

 

 

58

Table 18. Column data for Metea soil with target v0 = 100 cm/hr.

 

 

 

 

C/C0
Pore Volumes Benzene Toluene Xylene Naphthalene
0.000 0.88 0.88 0.87 1.03
0.28 1.03 1.01 1.01 1.00
0.54 1.05 1.04 1.05 0.99
0.80 1.01 1.01 1.02 1.12
1.06 1.0275 1.0300 1.0438 1.08
1.32 1.0642 1.0620 1.0789 0.954
1.58 0.9767 0.9979 1.0463 0.962
1.84 0.7619 0.8397 0.9720 0.990
2.10 0.4960 0.6265 0.8429 0.838
2.36 0.2963 0.4470 0.7480 0.821
2.62 0.1810 0.3062 0.6363 0.776
2.88 0.1062 0.1909 0.4841 0.682
3.14 0.0756 0.1403 0.4169 0.654
3.40 0.0521 0.0975 0.3232 0.592
3.66 0.0410 0.0765 0.2698 0.544
3.92 0.0244 0.0554 0.2056 0.464
4.18 0.0184 0.0445 0.1671 0.419
4.44 0.0160 0.0401 0.1541 0.455
5.13 0.0085 0.0184 0.0995 0.352
5.48 0.0067 0.0151 0.0863 0.364
5.83 0.0042 0.0093 0.0591 0.245
6.17 0.0045 0.0104 0.0666 0.318
6.52 0.0037 0.0089 0.0593 0.286
6.87 0.0029 0.0068 0.0492 0.277
7.21 0.0026 0.0059 0.0440 0.243
7.56 0.0023 0.0053 0.0410 0.262
7.91 0.0021 0.0048 0.0378 0.221
8.25 0.0020 0.0043 0.0355 0.215
8.60 0.0017 0.0039 0.0200 0.212
8.95 0.00279 0.00632 0.03234 0.297
9.29 0.00254 0.00563 0.02817 0.251
9.64 0.00232 0.00511 0.02641 0.250
9.99 0.00214 0.00459 0.02397 0.226
10.33 0.00154 0.00367 0.01829 0.176
11.20 0.00139 0.00338 0.01725 0.188
12.07 0.00098 0.00276 0.01444 0.160
12.93 0.00107 0.00224 0.01192 0.137
13.80 0.00072 0.00190 0.01015 0.126
14.67 0.000890 0.00207 0.00956 0.1 10

 

 

Table 18 (cont’d)

59

 

 

15.53
16.40
17.27
18.13
19.00
19.87
20.73
21.60
22.47
23.33
24.20
25.06
25.93
26.80
27.66
28.53
29.40
30.26
31.13
32.00
32.86
33.73
34.60
35.46
36.33
37.20
38.06
38.93
40.66
42.40
44.13
45.86
47.60
49.33
51.06
52.79
54.53
56.26
57.99
59.73

0.000646
0.000677
0.000778
0.000742
0.000466
0.000496
0.000470
0.000482
0.000410
0.000378
0.000493
0.000432
0.000346
0.000265
0.000276
0.000287
0.000298
0.000260
0.000207
0.000496
0.000266
0.0003 07
0.0003 95
0.000220
0.000364
0.000343
0.000518
0.000540
0.000248
0.000174
0.000180
0.000139
0.000123
0.000153
0.000135
0.000207
0.000339
0.000165
0.0001 19

0.0000947

0.00192
0.00206
0.00181
0.00171
0.00170
0.00159
0.00141
0.00147
0.00127
0.00122
0.001 14
0.001 1 1
0.00130
0.00123
0.00120
0.001 19
0.000969
0.000882
0.000972
0.000820
0.000818
0.000989
0.000930
0.001016
0.000976
0.000801
0.001276
0.001316
0.000892
0.000682
0.000788
0.000873
0.000575
0.000585
0.000645
0.000862
0.000978
0.001025
0.000832
0.000665

0.00865
0.0081 5
0.00778
0.00709
0.00656
0.00627
0.00545
0.00539
0.00460
0.00479
0.00444
0.00391
0.00372
0.00388
0.00396
0.003 67
0.00302
0.00289
0.00308
0.00289
0.00282
0.00287
0.00310
0.00316
0.00264
0.00269
0.00396
0.00394
0.00298
0.00266
0.00267
0.00292
0.00187
0.00206
0.00228
0.00264
0.00291
0.00296
0.00252
0.00208

0.114

0.101

0.106

0.103

0.0893
0.0775
0.0693
0.0624
0.0588
0.0556
0.0636
0.0463
0.0447
0.0358
0.0462
0.0474
0.0370
0.0336
0.0299
0.0313
0.0302
0.0346
0.0311
0.0297
0.0263
0.0359
0.0299
0.0270
0.0239
0.0204
0.0235
0.0168
0.0148
0.0180
0.0187
0.0109
0.0188
0.0187
0.0180
0.0120

 

 

60

Table 19. Column data for SPCF soil with target v0 = 2 cm/hr.

 

 

 

 

C/C0
Pore Volume Benzene Toluene Xylene Naphthalene
0.00 1.016 1.012 0.961 0.933
0.17 0.966 0.957 0.888 0.973
0.70 1.083 1.076 1.003 0.932
1.22 0.994 0.988 0.947 0.858
1.90 0.289 1.02 1.04 0.938
2.29 0.042 0.750 0.978 0.919
2.89 0.014 0.157 0.937 0.837
3.34 0.00821 0.03 87 0.900 0.811
3.93 0.00595 0.0177 0.822 0.881
4.43 0.00447 0.0105 0.551 0.798
4.82 0.00356 0.00790 0.362 0.726
5.43 0.00320 0.00626 0.188 0.646
5.77 0.00239 0.00471 0.133 0.604
6.04 0.00279 0.00503 0.099 0.701
6.36 0.00282 0.00487 0.0790 0.702
6.65 0.00486 0.00410 0.0576 0.609
7.58 0.00246 0.00380 0.0320 0.686
8.49 0.00902 0.00254 0.0139 0.441
9.32 0.00202 0.00309 0.0138 0.692
9.94 0.00181 0.00283 0.0115 0.676
12.31 0.00177 0.00236 0.00696 0.606
13.27 0.00175 0.00228 0.00654 0.574
13.92 0.00137 0.00197 0.00504 0.510
14.83 0.00085 0.00119 0.00392 0.400
15.78 0.00100 0.00142 0.00386 0.325
15.69 0.000579 0.000726 0.00234 0.176
19.90 0.000831 0.001139 0.00282 0.147
20.45 0.000709 0.001016 0.00264 0.138
21.24 0.000121 0.000421 0.00098 0.0230
22.88 0.000102 0.000333 0.00075 0.0822
27.09 0.000871 0.000888 0.00271 0.0976
29.21 0.007732 0.000770 0.00213 0.0705
34.19 0.000352 0.000542 0.00153 0.0440
35.05 0.000717 0.001225 0.00259 0.0446
38.21 0.000755 0.001089 0.00255 0.0468
39.46 0.000565 0.000996 0.00234 0.0426
40.32 0.000489 0.000954 0.00228 0.0412
41.44 0.000497 0.000875 0.00228 0.0395
43.61 0.002999 0.000118 0.00043 0.0180

 

 

 

Table 19 (cont’d)

61

 

46.19
47.55
48.64
51.34

0.000538
0.000152
0.000777
0.000401

0.001032
0.000268
0.001514
0.000719

0.00225
0.00076
0.00298
0.00167

0.0302
0.0175
0.0357
0.0212

 

 

62

Table 20. Column data for SPCF soil with target v0 = 5.3 cm/hr.

 

 

 

 

C/C0
Pore volumes Benzene Toluene Xylene Naphthalene
0.00 1.00 0.98 0.927 0.861
0.38 1.04 1.03 0.972 0.906
0.72 1.13 1.11 1.051 0.906
1.05 1.06 1.04 0.975 1.014
1.38 1.10 1.09 1.035 0.937
1.72 1.20 1.18 1.134 0.971
2.05 1.00 1.01 0.970 0.919
2.38 0.720 1.05 1.033 1.003
2.72 0.036 0.672 1.014 0.855
3.72 0.016 0.252 0.925 0.809
4.22 0.012 0.093 1.027 0.797
4.80 0.00766 0.029 0.853 0.940
5.47 0.00556 0.0149 0.627 0.793
6.13 0.00409 0.0096 0.429 0.780
6.68 0.00307 0.00642 0.251 0.667
7.35 0.00290 0.00553 0.158 0.628
8.05 0.00224 0.00394 0.0906 0.566
9.39 0.00183 0.00304 0.0413 0.596
10.44 0.00143 0.00242 0.0230 0.624
11.18 0.00139 0.00243 0.0184 0.628
12.04 0.00125 0.00203 0.0133 0.641
12.92 0.00118 0.00180 0.0102 0.617
13.66 0.00111 0.00170 0.00872 0.577
14.52 0.00106 0.00164 0.00759 0.555
15.24 0.00099 0.00153 0.00641 0.487
17.63 0.00101 0.00140 0.00482 0.372
20.04 0.000893 0.00129 0.00390 0.251
22.24 0.000771 0.00109 0.00314 0.177
23.86 0.000693 0.00100 0.00287 0.140
26.59 0.000670 0.00096 0.00256 0.097
26.89 0.071233 0.02456 0.03569 0.0788
29.41 0.001076 0.001570 0.00364 0.0922
31.15 0.000564 0.001051 0.00263 0.0661
33.56 0.000488 0.000799 0.00220 0.0543
36.08 0.000395 0.000559 0.00165 0.0421
47.06 0.000272 0.000399 0.00104 0.0231
48.57 0.0003 52 0.000638 0.00164 0.0217
50.44 0.000918 0.000954 0.00232 0.0370
54.80 0.001004 0.001072 0.00212 0.0347

 

 

63

 

 

Table 20 (cont’d)
65.92 0.000535 0.000391 0.00086 0.0222
67.53 0.000346 0.000391 0.00083 0.0194
71.49 0.000405 0.000440 0.00094 0.0177
76.30 0.000407 0.000602 0.001 14 0.0126
82.77 0.000484 0.000684 0.00106 0.0105
91.14 0.000798 0.000882 0.00138 0.0118
98.63 0.003348 0.002868 0.00284 0.0097
103.87 0.000205 0.000379 0.00055 0.0104
105.44 0.000266 0.000385 0.00071 0.0082
112.50 0.000266 0.000435 0.00088 0.0121
119.35 0.000030 0.000027 0.00008 0.0009
122.96 0.000070 0.000132 0.00024 0.0023
132.98 0.000110 0.000616 0.00218 0.0026

 

 

64

Table 21. Column data for SPCF soil with target v0 = 14.1 cm/hr.

 

 

 

 

C/CO
Pore Volumes Benzene Toluene Xylene Naphthalene
0.00 1.07 1.06 1.14 0.940
0.22 1.08 1.07 1.15 0.989
0.51 1.04 1.03 1.09 0.862
0.80 1.07 1.06 1.11 0.897
1.09 1.03 1.02 1.06 0.947
1.38 0.950 1.02 1.05 1.004
1.67 0.618 0.965 1.01 0.974
1.96 0.277 0.881 1.00 0.904
2.25 0.0863 0.659 0.944 0.877
2.54 0.0335 0.453 0.978 0.914
2.83 0.0167 0.240 0.887 0.851
3.12 0.0117 0.126 0.879 0.889
3.41 0.00867 0.0629 0.787 0.845
3.70 0.00725 0.0361 0.736 0.887
3.99 0.00631 0.0238 0.679 0.910
4.28 0.00558 0.0172 0.587 0.838
4.57 0.00447 0.0119 0.439 0.734
4.86 0.00456 0.0113 0.408 0.839
5.15 0.00388 0.00899 0.301 0.725
5.44 0.00368 0.00816 0.249 0.724
5.73 0.00320 0.00693 0.184 0.659
6.17 0.00286 0.00585 0.130 0.616
6.60 0.00251 0.00504 0.0925 0.595
7.03 0.00227 0.00447 0.0651 0.520
7.62 0.00219 0.00414 0.0479 0.562
8.20 0.00205 0.00372 0.0343 0.476
8.78 0.00203 0.00350 0.0271 0.521
9.36 0.00169 0.00297 0.0204 0.598
9.94 0.00148 0.00263 0.0162 0.546
10.52 0.00129 0.00228 0.0131 0.544
11.10 0.00207 0.00409 0.0194 0.594
11.91 0.00171 0.00322 0.0156 0.546
13.07 0.00170 0.00340 0.0139 0.475
14.23 0.00150 0.00255 0.0104 0.368
15.39 0.00111 0.00220 0.00862 0.318
16.55 0.00117 0.00198 0.00805 0.293
17.71 0.00113 0.00201 0.00720 0.247
19.74 0.00304 0.00414 0.00987 0.215
22.06 0.00116 0.00245 0.00684 0.156

 

 

Table 21 (cont’d)

65

 

 

25.53
29.01
32.49
35.97
39.84
45.92
51.42
54.92
58.11
61.30
64.63
67.82
71.01
74.20
77.39
80.58
83.77
86.95
89.85
92.46
95.65
99.13
102.32
105.65
108.84
112.03
115.21
124.49
130.00
133.19
136.37
139.56
142.75
145.94
149.13
152.32

0.00109

0.000987
0.000979
0.001008
0.000338
0.000284
0.000527
0.0003 85
0.000588
0.000483
0.000586
0.000510
0.000510
0.000480
0.000280
0.000230
0.000220
0.000194
0.000168
0.000174
0.000179
0.000281
0.000281
0.000217
0.000177
0.000144
0.000042
0.000170
0.000060
0.000231
0.000088
0.000000
0.000022
0.000025
0.000045
0.000549

0.00175

0.00173

0.00189

0.00160

0.000596
0.000494
0.000903
0.000681
0.001071
0.000869
0.001 108
0.000907
0.001009
0.000889
0.000367
0.000351
0.000336
0.000275
0.000271
0.000269
0.000348
0.000413
0.000462
0.000328
0.000333
0.000273
0.000088
0.000320
0.000141
0.000343
0.000151
0.000000
0.000098
0.000069
0.000062
0.000601

0.00541
0.00485
0.00483
0.00421
0.00179
0.00143
0.00227
0.00180
0.00275
0.00230
0.00237
0.00209
0.00215
0.00234
0.000635
0.000605
0.000632
0.000573
0.000447
0.000526
0.000610
0.000574
0.000773
0.000629
0.000630
0.000419
0.000179
0.000574
0.000205
0.000463
0.000224
0.000000
0.000164
0.000103
0.000104
0.000671

0.105
0.0880
0.0737
0.0590
0.0409
0.0347
0.0340
0.0301
0.0323
0.0284
0.0257
0.0223
0.0194
0.0185
0.0102
0.00725
0.00500
0.00492
0.00412
0.00348
0.00414
0.00358
0.00371
0.00320
0.00403
0.00265
0.00262
0.00153
0.00118
0.00320
0.00225
0.00000
0.00192
0.00252
0.00345
0.00194

 

 

66

Table 22. Column data for SPCF soil with target v0 = 37.5 cm/hr.

 

 

 

 

C/C0
Pore volume Benzene Toluene Xylene Naphthalene
0.00 1.12 1.11 1.03 0.982
0.21 1.12 1.11 1.03 1.012
0.52 1.07 1.08 1.00 1.051
0.84 1.09 1.10 1.03 1.019
1.16 1.14 1.13 1.06 1.024
1.48 0.911 0.98 0.93 0.924
1.79 0.601 1.02 1.00 0.977
2.11 0.213 0.949 1.03 0.979
2.43 0.0798 0.716 1.03 0.987
2.75 0.0398 0.431 1.00 0.968
3.06 0.0250 0.232 0.98 0.926
3.38 0.0181 0.130 0.94 0.928
3.70 0.0134 0.0729 0.86 0.902
4.02 0.0127 0.0499 0.79 0.895
4.33 0.00972 0.0330 0.66 0.815
4.65 0.00888 0.0255 0.56 0.783
4.97 0.00820 0.0214 0.47 0.794
5.29 0.00706 0.0175 0.38 0.772
5.60 0.00620 0.0148 0.30 0.741
5.92 0.00560 0.0135 0.25 0.730
6.24 0.00503 0.0119 0.20 0.713
6.56 0.00459 0.0106 0.16 0.701
6.87 0.00428 0.00968 0.14 0.696
7.19 0.00399 0.00915 0.11 0.673
7.51 0.00375 0.00839 0.09 0.653
7.83 0.00365 0.00752 0.08 0.622
8.30 0.00325 0.00699 0.06 0.648
8.78 0.00324 0.00670 0.05 0.626
9.25 0.00374 0.00709 0.05 0.634
9.73 0.00339 0.00633 0.04 0.598
10.21 0.00386 0.00724 0.04 0.696
10.68 0.00341 0.00649 0.03 0.685
11.16 0.00287 0.00561 0.03 0.673
11.63 0.00244 0.00539 0.02 0.642
12.11 0.00236 0.00509 0.02 0.636
12.59 0.00226 0.00485 0.02 0.607
13.06 0.00248 0.00471 0.02 0.594
13.70 0.00233 0.00445 0.02 0.528
14.65 0.00208 0.00387 0.02 0.512

 

 

67

 

 

Table 22 (cont’d)
15.29 0.00182 0.00355 0.01 0.457
15.92 0.00156 0.00299 0.0115 0.397
16.56 0.00168 0.00343 0.0118 0.378
17.19 0.00171 0.00307 0.0107 0.346
17.83 0.00169 0.00300 0.0107 0.331
18.46 0.00154 0.00284 0.00878 0.304
19.25 0.00128 0.00253 0.00861 0.276
20.05 0.00104 0.00232 0.00824 0.257
21.16 0.00100 0.00214 0.00732 0.223
22.11 0.00118 0.00220 0.00755 0.205
23.06 0.00108 0.00187 0.00614 0.182
24.33 0.000946 0.00180 0.00587 0.175
25.60 0.000773 0.00171 0.00561 0.151
26.87 0.000841 0.00147 0.00500 0.132
28.88 0.000626 0.00120 0.00421 0.116
31.90 0.000809 0.00133 0.00401 0.0906
34.76 0.000511 0.00104 0.00336 0.0802
37.93 0.000476 0.00103 0.00297 0.0632
42.06 0.000498 0.00090 0.00285 0.0571
45.23 0.000544 0.00089 0.00255 0.0448
53.49 0.001384 0.00156 0.00327 0.0397
65.79 0.000866 0.00200 0.00410 0.0456
66.27 0.000345 0.000756 0.00237 0.0408
80.55 0.000394 0.000709 0.00168 0.0275
87.69 0.000638 0.001053 0.00270 0.0163
94.84 0.000316 0.000574 0.00138 0.0255
101.98 0.000482 0.000855 0.00181 0.0240
109.12 0.000533 0.000930 0.00198 0.0249
118.23 0.000567 0.000577 0.00133 0.0255
124.63 0.0003 85 0.000568 0.00150 0.00894
133.30 0.000449 0.000632 0.00116 0.00763
142.03 0.000327 0.000579 0.00130 0.00638
146.98 0.000260 0.000447 0.00151 0.00641
155.71 0.000367 0.000587 0.00147 0.01176
164.44 0.000264 0.000456 0.00102 0.01062
173.17 0.000298 0.000659 0.00145 0.00944
181.90 0.000140 0.000422 0.00086 0.00735
190.63 0.000293 0.000503 0.00112 0.00791
199.36 0.000128 0.000283 0.000653 0.00787
208.09 0.000235 0.000470 0.000927 0.00665
216.82 0.000256 0.000431 0.000860 0.00645
225.55 0.000440 0.000601 0.001135 0.01018

 

 

68

 

 

Table 22 (cont’d)
234.28 0.000653 0.000400 0.000718 0.00555
243.01 0.000401 0.000377 0.000738 0.00466
251.74 0.000322 0.000370 0.000767 0.00503
260.20 0.000564 0.000390 0.00071 1 0.00588
267.60 0.000419 0.000285 0.000538 0.00710
276.49 0.000419 0.000367 0.000750 0.00514
285.53 0.000709 0.000594 0.000945 0.00473
295.53 0.000171 0.000194 0.000471 0.00596
304.27 0.000100 0.000196 0.000514 0.00604
313.31 0.000107 0.000151 0.000361 0.00180
322.04 0.000215 0.000402 0.000744 0.00840

 

 

69

Table 23. Column data for SPCF soil with target v0 = 100 cm/hr.

 

 

 

 

C/C0
Pore Volumes Benzene Toluene Xylene Naphthalene

0.00 0.963 0.941 0.905 0.870
0.56 0.967 0.945 0.899 0.895
1.11 0.836 0.902 0.855 0.912
1.89 0.169 0.668 0.836 0.834
2.44 0.0350 0.284 0.871 0.874
3.11 0.0114 0.0734 0.645 0.767
3.67 0.00710 0.0284 0.433 0.725
4.22 0.00526 0.0158 0.285 0.666
4.89 0.00430 0.0114 0.206 0.672
5.33 0.00358 0.00856 0.139 0.657
5.78 0.00322 0.00731 0.110 0.619
6.33 0.00260 0.00624 0.0798 0.623
8.00 0.00159 0.00300 0.0205 0.260
8.56 0.00153 0.00289 0.0174 0.278
9.11 0.00138 0.00248 0.0136 0.242
9.67 0.00135 0.00239 0.01 18 0.260
10.22 0.00113 0.00195 0.00859 0.216
10.78 0.00109 0.00177 0.00700 0.183

1 1.56 0.000896 0.00153 0.00560 0.154
12.44 0.000814 0.00137 0.00465 0.131
13.00 0.000710 0.00119 0.00376 0.111
14.33 0.000656 0.00106 0.00327 0.0892
15.56 0.000619 0.000927 0.00270 0.0633
16.44 0.000464 0.000667 0.00180 0.03 98
17.78 0.000535 0.000790 0.00205 0.0433
19.11 0.000513 0.000719 0.00169 0.0339
20.78 0.000470 0.000698 0.00161 0.0274
23.00 0.000350 0.000526 0.00115 0.0188
26.33 0.000387 0.000522 0.00110 0.0147
28.00 0.000442 0.000477 0.000969 0.0127
31.33 0.000390 0.000419 0.000863 0.00908
33.00 0.000425 0.000432 0.000845 0.00714
36.33 0.000224 0.000330 0.000636 0.00536
38.00 0.000274 0.000289 0.000541 0.00434
39.67 0.000324 0.000307 0.000610 0.00462
41.33 0.000153 0.000261 0.000501 0.00339
43.00 0.000148 0.000219 0.000442 0.00296
44.67 0.000118 0.000191 0.000356 0.00230
46.33 0.000127 0.000188 0.000385 0.00236

 

 

Table 23 (cont’d)

70

 

 

48.00
49.67
51.33
64.67
67.56
71.33
73.89
76.33
79.67
83.00
85.78

0.000224
0.000437
0.000209
0.000179
0.000164
0.000170
0.000149
0.000138
0.000161
0.000136
0.000438

0.000344
0.000477
0.000340
0.000283
0.000218
0.000313
0.000193
0.000159
0.000178
0.000176
0.000380

0.000564
0.000651
0.000539
0.000500
0.000407
0.000453
0.000408
0.000344
0.000374
0.000359
0.000463

0.00596
0.00419
0.00318
0.00298
0.00240
0.00229
0.00184
0.00155
0.00161
0.00138
0.00105

 

 

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