Sorption reactions of 1,4-dichlorobenzenein low organic carbon soils

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Authors Klein, Adam,1959-

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SORPTION REACTIONS OF 1,4-DICHLOROBENZENE

IN LOW ORGANIC CARBON SOILS

by

ADAM KLEIN

A Thesis Submitted to the Faculty of the

DEPARTMENT OF HYDROLOGY AND WATER RESOURCES

in Partial Fulfillment of the RequirementsFor the Degree of

MASTER OF SCIENCEWITH A MAJOR IN HYDROLOGY

In the Graduate College

THE UNIVERSITY OF ARIZONA

1986

Roger Bales, Professor ofHydrology and Water Resources

STATEMENT BY AUTHOR

This thesis has been submitted in partial fulfill-ment of requirements for an advanced degree at the Univer-sity of Arizona and is deposited in the University Libraryto be made available to borrowers under rules of thelibrary.

Brief quotations from this thesis are allowablewithout special permission, provided that accurate acknow-ledgment of source is made. Requests for permission forextended quotation from or reproduction of this manuscriptin whole or in part may be granted by the head of the majordepartment or the Dean of the Graduate College when in hisor her judgement the proposed use of the material is in theinterests of scholarship. In all other instances, however,permission must be obtained from the author.

SIGNED:

APPROVAL BY THESIS DIRECTOR

This thesis has been approved on the date shown below.

R4T/Ag 6Date

ACKNOWLEDGMENTS

I would like to thank my parents, who have always placed a

high value on my education; without their emotional and

financial support this would never have been possible. I'd

like to thank Pat Pascal, who provided the divine guidance

necessary to get our Varian 7630 working; this research is

only as good as its detection levels. Many thanks to

Mama's Pizzeria, for needed nutritional support and a good

space to think and to Bentley's, for lots of coffee, late

night crams, and a place to relax and sort this mess out.

I can't possibly thank Augusta Davis enough; in addition to

guiding me through the administrative mazes of both the

University and this department, she has the distinction of

being the only person to survive the front office for the

duration of my stay here. Finally, there are Jim, Kris and

Tom, who suffered through this entire process with me; U of

A water chemsistry program in its nascent stages is no fun.

Even though it was often the blind leading the blind, I

learned alot with you guys, and wish you the best of luck

in everything. Thanks for an ear to hear my gripes, ques-

tions, and realizations. This research was performed at

the University of Arizona under the guidance of Dr. Roger

Bales. Partial support for this work was obtained from the

Motorola Corporation. I would like to express my thanks to

R. Lee from Motorola inc., and Rebecca Pruitt from Dames

and Moore for their help on this project.

iv

TABLE OF CONTENTS

Page

LIST OF ILLUSTRATIONS vii

LIST OF TABLES viii

ABSTRACT ix

1. INTRODUCTION 1

2. BACKGROUND SORPTION THEORY 5

2.1 Hydrophobic Sorption 62.2 Sorption Forces 72.3 Sorption Isotherms 9

2.4 Sorption Kinetics 102.4.1 Physical Kinetic Processes 112.4.2 Chemical Kinetic Processes 122.4.3 Chemical Composition of Soils . . • 122.4.4 Comparison of Kinetic Models . . . • 13

2.5 Sorption Partition Coefficients 142.5.1 Effect of Soil Organic Matter

on Sorption 142.5.2 Kp /K oc Relationships 152.5.3 K oc /Kow Relationships 162.5.4 Effect of Aqueous Solubility on

Partitioning 192.5.5 Use of Empirical Equations for

Describing Partitioning 212.6 Soil Clays 23

2.6.1 Clay Sorption Mechanisms 23

2.6.2 Clay-Organic Interactions 24

3. EXPERIMENTAL PROCEDURES AND METHODS 27

3.1 Experimental Approach 27

3.2 Soils Description 283.3 Equilibrium Batch Procedures 293.4 Problems with Batch Procedures 323.5 Kinetic Batch Procedures 33

3.6 Desorption Batch Procedures 333.7 Soil Column Experimental Procedures . . 34

3.8 Chemical Analysis 37

TABLE OF CONTENTS--Continued

vi

Page

4. EXPERIMENTAL RESULTS 38

4.1 Equilibrium Batch Results 384.2 Kinetic Batch Results 414.3 Soil Column Results 44

4.3.1 Conductivity Data fromColumn Experiments 44

4.3.2 1,4-DCB Data 464.4 Anomalies in Column Experimental Results . . 48

5. DISCUSSION 52

5.1 Curve-Fitting Analysis of Column Experiments 535.1.1 Models and Input Parameters in CFITIM 535.1.2 Boundary Conditions in CFITIM . . . . 555.1.3 Column Experimental Analysis by CFITIM

Equilibrium Model 565.1.4 Analysis by non-equilibrium models . 64

5.2 Use of Empirical Equations to Predict Kp . . 705.3 Comparison of Koc Values 72

6. CONCLUSIONS 77

APPENDIX A 83

APPENDIX B: GRAPHS OF CHLORIDE AND 1,4 DCB EFFLUENT

APPENDIX C:

APPENDIX D:

DATA FROM COLUMN EXPERIMENTS . . . . 84

DIMENSIONLESS PARAMETERS FROMCFITIM MODELS 90

GRAPHS OF FITTED VS. OBSERVED EFFLUENTDATA FROM CFITIM EQUILIBRIUM MODELFOR 1,4-DICHLOROBENZENE 91

APPENDIX E: GRAPHS OF FITTED VS. OBSERVED EFFLUENTDATA FROM CFITIM EQUILIBRIUM MODEL FORCONDUCTIVITY 97

APPENDIX F: SUMMARY OF PARAMETER EXTIMATES FROMCFITIM MODELS D AND E . . . . . . 103

REFERENCES 104

LIST OF ILLUSTRATIONS

Figure Page

1 Schematic representation of columnexperimental setup 35

2 Sorption isotherm from batch experimentswith soil from borehole 2V2DB 39

3 Sorption isotherm from batch experimentswith soil from borehole 102SG 40

4 Graph of data from kinetic batch experiments 42

5 Graph of 1,4 DCB data fromsoil column experiments 45

6 Graph of chloride data fromsoil column experiments 45

7 Chloride Breakthrough Curves with fittedpoints from CFITIM equilibrium model analysis 57

8 1,4-DCB Breakthrough Curves with fittedpoints from CFITIM equilibrium model analysis 58

vii

LIST OF TABLES

Table Page

1 Physical characteristics of 1,4 dichlorobenzene 4

2 Koc/ Kow empirical relationships 18

3 Size fractions of soils used in the experiments 30

4 Parameters from column experiments 49

5 Parameter estimates from the CFITIMequilibrium model 60

6 Dispersion coefficients generated by theCFITIM equilibrium model 62

7 Summary of Alpha Values 69

8 Summary of Omega Values 69

9 Koc Values for 1,4-DCB 73

10 Summary of Kp Values from CFITIMNonequilibrium Models 76

v i i i

ABSTRACT

The rate and extent of sorption of 1,4-dichloro-

benzene (1,4-DCB) was studied using column and batch

experiments. Column experiments with a soil with fraction

organic carbon (foc) = 0.00086 yielded a soil/water

partition coefficient (K r ) of 0.41; mass balance on thesorption and desorption limbs of the breakthrough curves

gave similar Kp's, indicating sorption was readily rever-

sible. A computer program that fits column effluent data

to analytical solutions of the advection-dispersion

equation under different models of sorption behaviour gave

Kp = 0.46, assuming equilibrium sorption. The breakthrough

curves for 1,4-DCB showed slight tailing when plotted

against the fitted data, indicating some slow sorption.

The time scale for sorption/desorption estimated by this

program was up to 10-100 times larger than (physical)

transport times in the column, but was of the same order as

transport times in the field.

ix

CHAPTER 1

INTRODUCTION

Organic solvents are present in groundwater,

creating a possible hazard to the public's drinking water.

As the pollutant plumes are discovered and mapped, recla-

mation strategies will be formulated. Central to this

reclamation effort is determining how (and if) synthetic

organic compounds will be transformed, and their movement

retarded, as they travel in solution through aquifers.

Retardation of a solute as it travels through an aquifer

occurs due to sorption reactions. For sorption reactions

the questions become: 1) how much will the organics sorb to

aquifer solids, 2) what is the rate at which these com-

pounds desorb from the solids as the water is progressively

cleaned, and 3) what are the mechanisms responsible for the

sorption reactions.

Transport of chemicals (pollutants, salts, tracers,

etc.) in groundwater can be described by the advection-

dispersion equation. The one dimensional form of this

C))_1-(= - v - 240s r61- - b(z 3x

where C is the aqueous concentration of the sorbate (jig

equation is:

(1)

1

sorbate/cm 3 water), v is the average linear (Darcian)

velocity (cm/sec), and D is the dispersion coefficient

(cm 2 /sec). The term on the left hand side describes the

change in concentration in solution of the compound of

interest with time. The first term on the right hand side

describes diffusive transport of the compound, the second

term describes advective transport of the compound, and the

last term describes losses and gains of the compound due to

all chemical reactions. For transport of water or a

conservative tracer such as KC1, this last term is not

used. Equation 1 assumes steady-state water flow, a

constant diffusivity, and a constant soil-water content.

The chemical reactions term, Ekiri, refers to the

change in concentration of a chemical with time. Changes

occur because of interactions with other chemicals in the

water (such as complexation, degradation, or biological

transformations), or interactions with the solid matrix,

primarily sorption reactions. When the chemical reaction

term is limited to sorption reactions, equation 1 becomes:

_ „ e (2)3A" — X'

where S is the sorbed concentration (jig sorbate/g soil), p

is the soil bulk density (g soil/cm 3 soil) and 0 is the

total porosity of the soil in the column (cm 3 void space/

cm3 total volume). This current research is concerned with

determining the rate and extent of sorption reactions in

relation to groundwater contamination at a site in the

2

southwestern U.S.

The chemical under study is 1,4-dichlorobenzene

(1,4-DCB), a volatile, mainly nonpolar, organic compound.

A list of 1,4-DCB's relevant characteristics is given in

Table 1. Soils used in the sorption studies have a low

fraction organic carbon (foc), and were taken from bore-

holes near the Motorola 52nd St. production plant, in

Phoenix, Arizona.

The purpose of this research was to determine

equilibrium levels of 1,4-DCB sorption onto a variety of

soils from the field site in order to obtain sorption

isotherms, and to determine if those isotherms are linear.

An additional objective was to determine if partitioning

between the liquid and solid phases takes place within

seconds, hours, days or weeks, and to obtain an estimate

for the reaction rate coefficient if partitioning is

kinetic. Desorption was also examined, to determine if the

sorption reactions are completely reversible.

3

TABLE I

Selected Physical Properties of 1,4-Dichlorobenzene

Molecular Weight 147.01(Weast, 1977)

4

Melting Point(Weast, 1977)

Boiling Point at 760 torr(Weast, 1977)

Vapor Pressure at 25 °C(Weast, 1977)

Solid solubility in Water at 25 °C(Verschueren, 1977)

Supercooled Liquid Solubility(Chiou, 1981)

Log octanol/water partition coefficient(Leo et. al., 1971)

Henry's Law Constant

53.1 °C

174 °C

1.18 torr

79 mg/1

137 mg/1

3.39

0.34 atm/M

CHAPTER 2

BACKGROUND SORPTION THEORY

In general, sorption refers to a process by which

ions or molecules accumulate more in one phase than

another, typically at the boundary between those phases

(Sposito, 1984). According to Adamson (1982) two pictures

of liquid/solid sorption exist. In the more simplified

two-dimensional picture, adsorption is confined to a

monolayer next to the surface. The more complex picture is

that of a three-dimensional interfacial layer, multimolecu-

lar in depth, over which several different sorption

processes may be occuring simultaneously. Sorption from

solution in this case is a partitioning between a bulk and

an interfacial phase of the solution.

The two driving forces for sorption onto a solid are

the lyophobic (solvent-disliking) characteristics of the

solute with respect to the solvent, and a general affinity

of the solute for the solid (Weber, 1972). For aqueous

solutions, the first force is termed hydrophobicity (water

repulsion) or hydrophyllicity (water attraction). Sorption

which occurs due to the first process is often called

partitioning, while sorption due to the second process is

5

6

often called adsorption. Collectively, these two processes

are called sorption.

2.1 Hydrophobic Sorption

The more hydrophobic a compound is, the more

likely it is to partition into the solid phase. Since

water is a polar molecule, and non-polar organics, such as

1,4-DCB are relatively hydrophobic, compounds such as these

will move out of water and towards organic compounds in

soil. This is primarily due to water-water interactions.

Introduction of an organic molecule into water disrupts the

configuration of water molecules. In order to achieve

maximum entropy, water-water interactions will "push" the

organic out of aqueous solution. As the solute moves from

the aqueous to the solid phase, a large positive entropy

develops, due to the dehydration of the solute molecules

(Schwarzenbach et al., 1981). This type of hydrophobic

interaction is largely responsible for the sorption of 1,4-

DCB onto organic material in soil, and is often called

hydrophobic sorption (Voice and Weber, 1983, Hamaker and

Thompson, 1972), although more accurately might be termed

hydrophobic partitioning. Hydrophobic sorption increases

as compounds become less polar (larger carbon chains or

fewer substituents), or as water solubilities decrease

(Hassett and Means, 1980).

2.2 Sorption Forces

The second force behind sorption reactions is the

surface-solute attractive force. This force is generally

divided into three types: physical, chemical and electro-

static. For hydrophobic solutes (predominantly non-ionic

neutral compounds), large-scale electrostatic forces do not

play a part in sorption reactions (Voice and Weber, 1983).

However, for slightly polar molecules in soils with a high

clay/organic matter ratio, these forces may be important

for sorption (Hassett and Means, 1980), and will be discus-

sed more thoroughly in section 2.6.

For a completely nonpolar compound, physical

sorption is due to van der Waals forces, nonspecific, weak,

electrostatic attractions between molecules. Values for

van der Waals-type interactions for small molecules are

generally on the order of 1 to 2 kcal mo1 -1 (Hamaker and

Thompson, 1972).

Chemical sorption involves electronic interactions

between specific sites on the sorbent surface and solute

molecules. The solute typically will form a monomolecular

layer over the sorbing surface. This can result in bonds

that have a large energy of sorption, 15-50 kcal mol -1

(Hamaker and Thompson, 1972). However, a substantial

activation energy may be required in order for the reaction

to occur. Consequently chemisorption is slowly reversible,

in contrast to physical sorption, which is readily revers-

7

ible.

The partitioning of organic solutes out of aqueous

solution onto soil organic components is primarily due to

both hydrophobic partitioning and van der Waals interac-

tions, although it is often difficult to distinguish

between chemical and physical sorption (Voice and Weber,

1983). It is important to remember that sorption is a

surface phenomenon, and as such will also be a function of

the surface properties of the sorbent. Because of this,

sorption onto clay minerals as well as sorption onto

organic carbon must be considered. In the present context

of sorption, one must not forget that we are dealing with

the three-dimensional, multimolecular depth surfaces

mentioned before.

For the purposes of the rest of this paper, sorption

will be defined as the transfer of a solute (contaminant,

i.e. 1,4-DCB) from the liquid phase (groundwater) to the

solid phase (soil particles). Desorption is the corre-

sponding transfer of a solute from the solid into solution.

The main effect of sorption is to retard the mean rate of

the movement of a solute through an aquifer, relative to

the Darcian velocity of the water, as measured by a

conservative tracer (one which does not interact with the

soil particles or the other solutes). In addition,

sorption may catalyze or inhibit the breakdown of organic

compounds (Mortland, 1970).

8

9

sorption may catalyze or inhibit the breakdown of organic

compounds (Mortland, 1970).

2.3 Sorption Isotherms

One of the major goals of this research project was

to determine sorption isotherms for 1,4-dichlorobenzene on

soils from the field site. A sorption isotherm is a ratio

between the concentration of a solute on the solid phase

vs. the concentration of a solute remaining in the liquid

phase, at equilibrium at a given temperature. There are

several types of equations for describing sorption iso-

therms; most common are those developed by Langmuir and

Freundlich, which are nonlinear isotherms. However, for

modelling contaminant transport in groundwater, the most

frequently used isotherm is a linear isotherm. While this

widespread use is generally attributed to the mathematical

simplicity of the linear isotherm, it should be noted that

the Langmuir isotherm reduces to linear partitioning

relationships under conditions of dilute solutions (low

concentrations of the solutes) (Voice and Weber, 1983).

Because the present work deals with concentrations in the

part per million (PPM) and part per billion (PPB) range, a

linear isotherm is postulated. This isotherm is of the

form:

K xC=S

(3)

where Kp is the equilibrium partition coefficient (cm 3 /g),

S is the concentration of solute adsorbed to the solid

10

phase at equilibrium (ug solute/g soil), and C is the

equilibrium concentration of the solute remaining in

solution (pg solute/cm 3 water).

2.4 Sorption Kinetics

Historically, when the chemical reaction term of the

advection-dispersion equation has been considered, the

kinetics of the reaction(s) have been ignored. Instaneous

equilibrium was assumed, with the reaction following a

linear isotherm (equation 3). Within the last twenty

years, however, more complex models of the sorption

reaction have been developed, which look at the kinetics of

the reaction. Central to these models is the mechanism of

the sorption/desorption reaction and the determination of

the rate limiting step of the reaction. Kinetic sorption

necessarily implies competing processes of sorption and

desorption, which are occuring at the same time. This is

given as:

A(aq)-..?.-A(s) (4)

where A(aq) is desorption into solution, and A(s) is

sorption onto the sorbate. First order kinetic descrip-

tions of these reactions are of the form:

èS ,i,--,----- f x C/rsw - kb x S (5)Oi.

where kf (sec -1 ) is the forward (sorption) reaction rate

constant, kb (sec -1 ) is the reverse (desorption) reaction

rate constant, and rsw is the soil/water ratio (g soil/cm 3

water).

1 1

Kinetic sorption models are divided into two basic

categories; in one, physical processes are assumed respon-

sible for the kinetic rate of the reaction, and in the

second category chemical processes are assumed to be the

rate controlling step.

2.4.1 Physical Kinetic Processes

The physical process models partition soil water

into mobile and immobile regions (Rao et al., 1979).

Convective-dispersive transport of solutes through the soil

takes place only in the mobile region, although diffusion

through the stagnant region is also taking place. The

sorption reactions are assumed to be instantaneous. It is

the rate at which the sorbate approaches active sites on

the soil surface in the stagnant region that controls the

rate at which the solute will sorb onto the soil. The

solute must first diffuse through stagnant water films to

reach soil surface sites before the instantaneous sorption

reaction can occur. According to the model of Rao et al.

(1983), solute transfer between the mobile and stagnant

regions is described by Fick's second law for diffusion.

van Genuchten (1981) divides sorption sites into two

fractions, one which is in close contact with the mobile

liquid, and one which is in contact only with immobile

water. It is hypothesized that the larger pores contain

the sites in contact with the mobile liquid, and therefore

these sites will experience instantaneous sorption, while

12

the smaller intraaggregate pores are in contact with the

immobile liquid fraction, and therefore these sites will

experience diffusion-controlled sorption. Rao et al.

(1983) point out that most laboratory column experiments

are conducted with sieved soil, which will have no aggre-

gates and small particle sizes. However, no matter how

much processing the soil undergoes before it is used in

experiments, it appears that it will always contain some

microaggregates. Thus it seems that the physical process

model cannot be eliminated from the discussion describing

the results from these experiments.

2.4.2 Chemical Kinetic Processes

The chemical process models (Cameron and Klute,

1977) divide sorption sites on soils into two types: type 1

sites, where chemicals sorb rapidly, producing an instanta-

neous equilibrium at that site, and type 2 sites, where

chemicals sorb more slowly, resulting in a kinetic reac-

tion. A subset of this model is one where all sites are

assumed to undergo kinetic-type reactions. Conceptual

justification for this type of model is based on the

heterogeneous nature of soil.

2.4.3 Chemical Composition of Soils

The soil solid phase consists of crystalline

primary and secondary minerals (mostly layer silicates and

metal hydroxides), mineral colloids (mostly oxides and

13

hydroxides of silicon, iron, manganese and aluminum) and

organic particles (Ahlrichs, 1972). Soil organic matter

consists of carbohydrates, proteins, fats, waxes, resins,

pigments, and low molecular weight compounds physically

associated with humic acids (Kenaga and Goring, 1983);

together these components form amorphous humic colloids.

Typically these are characterized by high molecular weight,

aromatic structures, and acidic hydroxyl and carbonyl

functional groups (Kenaga and Goring, 1983). See Ahlrichs

(1972) for a functional group analysis of organic matter

from two soils. These components are present in different

combinations and ratios in different soils. Thus, a

chemical moving through the soil/water environment may

react instantaneously with organic matter and slowly with

mineral clays, or rapidly with one type of humic substance

and slowly with a different type. The fraction assumed

responsible for kinetic sorption reactions has not been

isolated.

2.4.4 Comparison of Kinetic Models

Rao et al. (1979) evaluated one model from each

category, to determine how well they predict experimental

results. Both models evaluated assume a two-site sorp-

tion/desorption system, where sorption onto the type one

sites is instantaneous, and sorption onto the type two

sites is nonlinear, and kinetically significant. These

authors concluded that both models can adequately describe

14

the assymetrical breakthrough curves(BTCs) obtained

experimentally for their solute, but that different sets of

parameters were required to predict the BTCs at two

different input concentrations. van Genuchten (1981)

contains a mathematical description of both types of

models; he notes that mathematically, they both reduce to

the same partial differential equation.

2.5 Sorption Partition Coefficients

Researchers have long sought to demonstrate rela-

tionships between fundamental characteristics of organic

compounds and soil components. Lambert et al. (1965) and

Lambert (1967,1968) were some of the first to emphasize the

importance of the soil organic matter fraction (OM) to

sorption reactions.

2.5.1 Effect of Soil Organic Matter on Sorption

Lambert presumed that all of soil sorption was a

partitioning of the solute onto soil organic matter and,

with that assumption, calculated a Kp based on soil OM

rather than total soil mass:

Kp = Cp m /C w (6)

where Cm is the concentration of solute on soil organic

matter (jig solute/g soil OM), and C w is the concentration

of solute in water (pg solute/g water)(Lambert, 1965). His

experimental results showed that this partition coefficient

is relatively constant for a given solute across a range of

15

different soils, and thus is a characteristic of that

solute. Deviations from this model will occur if 1) all of

the soil OM (as determined by standard TOC analysis) does

not participate in the sorption reactions, or 2) if the

chemical exhibits some anomalous behaviour, such as a pH

dependance or ion exchange reactions. This type of

behaviour is primarily a function of a chemical's struc-

ture, and its substituent groups. Kenaga and Goring (1979)

expanded on this by stating that deviations from this model

will occur because a) there are inherent differences

between soils in the sorption characteristics of its

organic matter, and h) there may be an impact on sorption

due to other soil properties (i.e. swelling clay content.

By restricting the model to uncharged, organic molecules,

deviations due to ion exchange reactions are eliminated.

2.5.2 Kp /K oc Relationships

Work by later researchers (Schwarzenbach et al,

1981, Karikchoff, 1979) has verified Lambert's research;

the more common form of the relationship is:

Koc = Kp/foc (7)

where K oc is a partition coefficient normalized for organic

carbon, or alternatively is the partition coefficient onto

a hypothetical 100% organic sorbent, and fo c is the

fraction organic carbon of the actual sorbent. Karikchoff

(1984) states that "(based on available documentation) it

can be safely generalized that for uncharged organic

16

compounds of limited water solubility (

17

log K e = a(log Ke l ) + a (9)where Ke and K e l are the distribution coefficients between

a solute and two different, immiscible liquid phases. a

and a are constants.

Several researchers have derived empirical K oc /K ow

relationships for different compounds. These are given in

Table 2; note that they are all of the same form as

equation 8. Schwarzenbach et al .(1981) state that their

relationship is valid only for dilute solutions, and for

soil with f oc > 0.001, and that the constant a in equation

9, giving the slope of the linear regression for equation 8

is a function of the free energy of transfer of the solute

from the aqueous to the nonaqueous phase.

Karickhoff (1981) demonstrates the thermodynamic

basis for equation 14, showing that for sufficiently dilute

systems, the proportionality constant for K oc /K ow is the

ratio of the fugacity coefficients for the solute dissolved

in octanol, and the solute bound in natural organic matter.

For this linear relationship to be valid, the fugacity

ratio must be independent of the solute; thus compounds not

showing this independence may not be amenable to this type

of treatment. The earlier work by Karickhoff (equation 10)

as well as the work of Kenaga and Goring (equation 11) were

not justified by the authors on the basis of any physico-

chemical theory. In fact, the work by Kenaga and Goring

was only a log-linear fit of Kp vs. Kow values obtained in

18

TABLE II

EMPIRICAL KOW/KOC RELATIONSHIPS

Equation

No. Ref.

log K oc = 1.00 x log Kow + 0.21 (10) Karikchoff(10 aromatic and chlorinated (1979)

hydrocarbons)

log Ko c = 0.544 x log Kow + 1.377 (11) Kenaga and(45 assorted organic compounds) Goring (1979)

(12) Hassett and(22 polynuclear aromatics) Means (1980)

10 9 Koc = 0.72 x log K ow + 0.49(13 halogenated alkenes and

benzenes)

log Koc = 0.989 x log Kow - 0.346(5 polynuclear aromatics)

log K oc = 1.029 x log Kow - 0.18(13 pesticides)

(13) Schwarzenbach(1981)

(14) Karikchoff(1981)

(15) Rao (1982)

10 9 Koc = 1.00 x log K ow - 0.317

19

the literature for 45 different compounds; this included

the data from Karickhoff (1979).

2.5.4 Effect of Aqueous Solubilityon Partitioning

Chiou et al. (1982,1983) developed a linear regres-

sion for log K ow and log S, where S refers to aqueous

solubility. Theoretical considerations in this derivation

centered on innaccuracies in reported K ow and S values.

Determination of K ow from octanol/water mixtures will

create an aqueous phase saturated with octanol. This will

result in higher than actual aqueous solubilities due to

the presence of the organic in the aqueous phase. This

will lead to a decrease in the actual Kow. This effect

will not happen in soil/water mixtures, because very little

of the soil organic matter is soluble in water. Under

ideal conditions (i.e. solubility in water and octanol-

saturated water are the same) the linear regression should

be:

log K ow = -1.0 x log S + 0.92 (16)

Nonideal conditions will produce a downward deviation from

the ideal line; the effect is most pronounced for compounds

with very low water solubilities.

Further deviations will occur for solutes which are

solids at room temperature (1,4-DCB is in this category).

The solubilities used in the log-linear regressions in

Table 2 must be the solubility of the supercooled liquid

20

(Karickhoff, 1981, Chiou, 1982, 1983) and not the solubil-

ity of the solid, due to the nonideal solution behaviour of

the supercooled liquid. This is often termed the melting

point effect. Downward deviations from ideal behaviour

will occur because supercooled liquids have reduced aqueous

and solvent solubility. Thus, while the aqueous solubility

decreases, the octanol/water partition coefficient remains

the same. For 16 aromatic compounds, Chiou (1982) found

the linear regression under the assumption of ideal

behaviour to be:

log K ow = -1.004 x log S + 0.34 (17)

Taking into account the non-idealities the equation

becomes:

log Kow = -0.862 x log S + 0.710

(18)

Karickhoff (1981) sought to compensate for the

melting point effect by addition of a "crystal energy

term":

log Koc = -a 10 9 X501 + b + "crystal energy term" (19)

where X so l is the mole fraction solubility of the solute in

water. This term is a function of the melting point and

the entropy of fusion for the solute; for the compounds in

Karickhoff's study this term was empirically determine to

be -0.00953(mp-25), where rap is the melting point of the

solute in °C. Note that for compounds which are liquids at

room temperature, this term vanishes. The regressions for

21

5 condensed ring aromatics without and with the crystal

energy term are:

log K oc = -0.594 x log Xsol - 0.197 (20)

log K oc = -0.921xlog X s0 1-0.00953 (mp-25)-1.405 (21)

Not only does this term improve the fit of Karickhoff's

data to a linear regression, it also moves the slope

(-0.921) much closer to unity, the coefficient under ideal

conditions. After applying equation 21 to literature data,

it was found (Karickhoff, 1984) that the equation worked

well for both aliphatic and aromatic chlorinated hydro-

carbons of low molecular weight, but for highly chlorinat-

ed, high molecular weight compounds (such as DDT), the

equation tended to overestimate sorption.

2.5.5 Use of Empirical Equations forDescribing Partitioning

Variations in the equations in Table 2 are due to

several factors. The logK oc /logK ow linear dependence is

predicated on strict hydrophobic sorption; polar group or

ionic interactions are assumed negligble. Soil organic

carbon is presumed to be the dominating component governing

sorption; the impact of swelling clays in the soil on

sorption is also assumed to be negligble. Hamaker et

al.,(1972) suggest that variations in Koc values for

different soils may be due to variations in the composition

of the organic matter complex. High organic matter soils

22

may see a reduction in the sorption surface per unit weight

of organic matter, due to a "piling up" of the organic

matter. Conversely, soils with a very low organic matter

content may show a significant amount of sorption by the

mineral phase. Thus, high organic matter soils may show

low K oc values, while very low organic matter soils may

show a high K oc value. Finally, computations of Kow for

large molecules based on addition of K ow 's for the substi-

tuents may overestimate the actual K ow for these larger

molecules (Karickhoff, 1984). Despite this variability, we

have seen that the coupling of linear regressions with

thermodynamic or linear free-energy theory can improve the

fit of experimental data, and allow for the extrapolation

of the regression to different classes of compounds.

The importance of the equations is that an a priori

estimate of the sorption partition coefficient for a given

compound can be developed, based on information that is

available in the literature. This can then be used as a

very good first approximation to determine if the mobility

of a given organic chemical poses a threat to water

sources. In doing this, care must be taken in choosing the

appropriate relationships from listed equations; this

choice must be based on a careful consideration of both the

physical properties of the compound of interest, and the

properties of the sorbing medium.

23

2.6 Soil Clays

Because of the high surface areas of clays and col-

loids, these parts of the soil may also play a role in

sorption of organics. There are extensive data available

that show that sorption of pesticides onto pure clays is

significant; however it must be remembered that both

organic matter present in soils and exchangeable cations

present in the soil solution may profoundly modify the

sorption properties of the clays with respect to organics

(Hamaker, 1972).

2.6.1 Clay Sorption Mechanisms

Sorption of organics onto clays happens by a variety

of mechanisms (Mortland, 1970). Ion exchange reactions may

occur with the exchangeable cations on the clay mineral

surface; this mechanism is pH dependent, and is significant

primarily for organics with amine or carbonyl groups.

Sorption of polar, nonionic organics can occur through ion-

dipole interactions. Again, cations in the exchange

complex serve as sorption sites for this mechanism. The

greater the cation's affinity for electrons, the greater

the energy of interaction with polar groups on organic

molecues; polyvalent cations are more electrophilic than

monovalent cations, and thus transition metals will form

the strongest bonds by this mechanism. For cations with

high solvation energies, sorption occurs through a "water

bridge"; functional groups on the organic will hydrogen

24

bond with water that is part of the solvation sphere of the

cation.

These mechanisms are much more important for sorbing

organics than the classical view of clay-organic sorption,

that held that sorption is due to hydrogen bonding between

oxygen atoms and hydroxyl groups of the silicates. These

weaker hydrogen bonds become important only for large

organic molecules, which will form many hydrogen bonds, and

when the cation exchange complex of the clay is saturated

with cations of low solvation energy. In this latter case,

organic molecules are in competion with water for sorption

sites. Compounds that are not polar enough to hydrogen

bond with clays in the presence of water may complex on the

clay surface when water is removed, i.e. by drying in the

air, or by alternate wetting and drying conditions in the

field. Under these conditions, water content is a very

important factor in determining whether or not clay-organic

interactions take place.

2.6.2 Clay-Organic Interactions

Perhaps the most significant alteration in the

sorbing properties of clays occurs when either organic

compounds in the soil organic matter itself, or in solution

sorb to the mineral surface. The mechanisms for this

reaction have already been discussed. Ahlrich (1972) notes

that clay crystals are often coated or mixed with decompos-

ing organic matter. McBride et al. (1977) observed that

25

smectite clay, which first underwent exchange reactions

with different alkylammonium ions, sorbed 12 times as much

phenol as the untreated clay; benzene sorbed to an even

greater extent than phenol. The mechanism of interaction

was with the interlamellar oxygens in the silicate layers.

1,2-dichlorobenzene and 1,2,4-trichlorobenzene were not

sorbed by this system, presumably because of their large

size. Larger alkylammonium ions may provide enough silicate

layer separation to allow this mechanism to work on

chlorobenzenes.

While it has been demonstrated in the laboratory

that mechanisms exist for sorption of organics to mineral

surfaces, in natural environments, organics are more likely

to partition onto organic components than onto clay

surfaces, due to hydrophobic sorption, and the hydrophilic

nature of the clay surface. Thus, the most important

factor in the field determining sorption onto clays is the

clay/organic matter ratio. Alternatively, we have seen

that clay-organic complexes may sorb compounds that didn't

sorb to pure clays. (Hasset and Means, 1980) studied

sorption of 1-napthol, a 2 ring aromatic with an OH group,

onto many different soils. Their findings indicated that

sorption onto one group of soils produced a reasonable fit

to a log Koc = alog Kow + b equation, while sorption onto

another set deviated from this relationship. This second

set had a much lower organic carbon/montmorillonite ratio

than the first set, indicating that for soils with low

organic carbon contents, sorption of organics onto clays

may be important.

26

CHAPTER 3

EXPERIMENTAL PROCEDURES AND MATERIALS

The techniques employed for studying sorption

reactions in this research were batch and column experi-

ments.

3.1 Experimental Approach

In the batch method, a sorbent (soil) is suspended

by agitation in a sorbate solution (1,4-DCB dissolved in

water), until equilibrium is reached. The suspension is

separated by centrifugation, and the solution analyzed for

changes in concentration, presumably due to sorption of the

sorbate (1,4-DCB) onto the sorbent. Initial concentrations

are determined by blanks, tubes containing the sorbate

solution without the sorbent, that undergo the same

treatment as the soil/solution suspension. This method is

used to determine sorption isotherms. By analyzing the

aqueous solution prior to equilibration, this method can

also be used to determine the rate of sorption.

The column method involves a continuous flow of

sorbate solution through a column packed with the sorbent.

Effluent at the bottom of the column is collected and

analyzed for sorbate concentration. When the sorbate

27

concentration in the effluent reaches the initial concen-

tration of the influent, the system is at equilibrium. At

this point, either the influent solution is changed to

contaminant-free water (to determine desorption characte-

ristics of the system) or the experiment is terminated.

Results of column experiments are commonly expressed in

dimensionless variables C/Co vs. pore volumes. A pore

volume is equal to the total pore space in the column and

C/Co is equal to the exit concentration of the sorbate

divided by the influent concentration.

Because of the volatile, hydrophobic nature of 1,4-

dichlorobenzene, care was taken at all points in the

experiments to avoid headspace in any solution containing

1,4-DCB, and thereby eliminate volatilization losses. For

this work, it was found that use of screw-cap bottles with

teflon-faced silica septa were most suitable for minimizing

headspace.

3.2 Soils Description

Soils near the Motorola 52nd street site are derived

from colluvium-alluvium and lie on Precambrian and Tertiary

bedrock. The colluvium-alluvium ranges in thickness from a

few centimeters to more than nine meters. In general, the

upper materials are clayey sand with gravel, which are

either very dense or cemented. Soil porosities range from

23 percent to 32 percent. Results from pumping tests

indicate that the average hydraulic conductivity of the

28

colluvial-alluvial aquifer is 42 feet per day (1.5 x 10 -2

cm per day), and average linear velocities in the aquifer

were determined to be between 0.25 and 2.5 feet per day.

For this research, all of the solid material used

for experimentation will be referred to as soils. Soils

were taken from drilling cores in both the saturated and

unsaturated zones; the depths of the cores used ranged

between 15-39 feet below the ground's surface. Soil

DM104SG was two miles from the field site, and had very

little clay, while soil DM102SG was from the courtyard of

the Motorola plant, and had a larger amount of fine sand

and clay. The soils were air dried for several days, and

then oven dried at 105 °C for 24-48 hours. The soils were

deaggregated and decemented by repeated hitting and

grinding with a mortar and pestle. Finally, the soils were

sieved using Soil Conservation Service soil sieves, ranging

between a size 250 sieve (0.061 mm mesh size) and a size 5

sieve (3.96 mm mesh size). A breakdown of the size

fractions of the soils is given in Table 3. Fraction

organic carbon was determined only for soil DM104SG, and

was 0.00086.

3.3 Equilibrium Batch Procedures

Equilibrium batch experiments were conducted with

soil and 1,4-dichlorobenzene to determine sorption iso-

therms. The size fraction of the soil that was less than

29

TABLE III

Soil Size Fractions from various boreholes and depths

SIZE FRACTIONS(mm)

Percent in stated size range

DM102SG 2V2DB 2V2DB DM104SG

15-16 16.5-18.3 18.3-20.5 39feet feet feet feet

X > 3.96 50.0 75.8 72.1 29.2

3.96 > X >1.98 15.8 7.9 12.7 23.5

1.98 > X >0.991 10.8 6.1 7.5 16.3

0.991 > X >0.495 7.8 4.1 3.7 10.6

0.495 > X >0.124 12.2 4.5 2.5 15.1

X < 0.124 3.3 1.5 1.5 5.2

TOTAL 99.9 99.9 100.0 99.9

30

0.124 mm (Table 3) from boreholes 2V2DB 16.5-18.3 feet,

2V2DB 18.3-20.5 feet, and DM102SG 15-16 feet were used for

the equilibrium batch experiments. A concentrated stock

solution was prepared by dissolving a weighed amount of

1,4-DCB in a 40 ml screw-capped bottle filled with a known

weight of methanol, typically giving concentrations between

500 and 2000 PPM. Use of methanol facilitates the dissolu-

tion of 1,4-DCB in water. A known volume of the concen-

trated methanol stock (20-300 pl) is then added to to 250

ml of water in a screw-capped bottle. Both the volume of

methanol and volume of water were multiplied by their

respective densities (0.794 and 1.0 g/cm 3 ); this procedure

gave concentrations between 0.1 and 2 ppm. This solution

is added to a known mass of soil in 35 ml screw-capped

centrifuge tubes and reweighed; the soil-to-water ratio

(g soil/g water) was between 0.4 and 0.6. The soil and

water are mixed for time periods ranging between 5 and 7

days. The tubes are centrifuged for 20 minutes at 4000

RPM. The liquid is then poured into 2 dram (7.4 ml) vials,

filling approximately half the vial, and weighed. Pentane

is added to fill the remaining volume, and the vial was

reweighed, giving a water/pentane ratio of 1.65-2.5:1; the

pentane is used to extract the organic compounds from the

water. The 2 dram vials are shaken for 1 minute (150

shakes), and then the pentane is analyzed in a gas chromat-

ograph for the presence of 1,4-DCB.

31

3.4 Problems with Batch Procedures

Volatilization losses occured in pouring the 1,4-

DCB-water stock into the centrifuge tubes. By sampling the

stock solution before and after the decanting, it was

determined that losses were less than five percent. Major

difficulties were encountered in trying to eliminate

headspace within the centrifuge tubes. In order to ensure

complete saturation of the soil, the tubes were filled

approximately 90 percent full of water, and were shaken

until all the soil in the tubes went into suspension. The

caps were removed, and the tubes were then filled to the

top with water. The maximum soil/water ratio compatible to

good mixing was used. Since the caps of the sample tubes

were removed after the 1,4-DCB was added (in order to fill

the tubes with water and thereby eliminate any headspace),

it is likely that some losses of 1,4-DCB occured in the

sample tubes, both through displacement of the air in the

sample tube and due to partitioning from the liquid to the

air. However, no other method was developed that accom-

plished the tasks of complete mixing of the soil with the

solution, and elimination of the headspace in the centri-

fuge tubes. Henry's law can be used to determine the

partial pressure of 1,4-DCB from the headspace in the

vials, and combining this with the ideal gas law, the

amount of 1,4-DCB lost from the headspace can be determin-

ed; this turned out to be 1.5 percent, using the highest

32

33

concentration (2 PPM) used in the experiments. The

calculations for this are given in appendix A.

Because 1,4-DCB sorption was measured by looking at

the disappearance of the compound from solution, losses

during an experiment would result in an overestimation of

total sorption. However, these calculations show that the

total loss of 1.4-DCB during the mixing should not have an

impact on sorption calculations. Additional complications

may arise due to the presence of suspended soil particles

in the soil water after centrifugation, possibly leading to

an understatement of the extent of the sorption.

3.5 Kinetic Batch Procedures

The kinetic batch experiments were prepared in the

same manner as the equilibrium batch experiments. The

soil/water suspension was mixed for time periods ranging

between 1 hour and 1 week, with centrifugation and sampling

typically occurring after 1 hour, 1 day, and 1 week. 1,4-

DCB/water solutions used ranged from 0.1 to 2.0 ppm. In

addition to the soils mentioned above, soil from borehole

DM104SG was used for the kinetic batch experiments.

3.6 Desorption Batch Procedures

An attempt was also made to run desorption batch

experiments. The procedure was the same as for the

equilibrium batch experiments. After one week the tubes

were centrifuged, and the liquid solution was decanted.

The tubes were then filled with distilled, deionized water,

remixed (through the use of a sonicator), and allowed to

equilibrate for another week. The decanted solution was

analyzed for the presence of 1,4-DCB, in order to determine

the equilibrium level of sorption, as well as to aid in a

mass balance accounting of the 1,4-DCB. After one week,

the tubes were analyzed in the same manner as the equili-

brium sorption experiments. Mass balance revealed that in

almost all cases, the 1,4-DCB in solution at the end of

desorption equilibrium exceeded the amount of 1,4-DCB which

was calculated to be present in the entire tube at the

beginning of the desorption experiment. These problems

could not be resolved, and further work along these lines

was discontinued.

3.7 Soil Column Experimental Procedures

Column experiments (see schematic, figure 1) were

conducted at various concentrations of 1,4-dichlorobenzene,

and at different flow rates. The concentrations ranged

from 0.15 ppm to 1.5 ppm., and the flow rates were typi-

cally 1 ml/min although they did dip as low as 0.5 ml/min.

A concentrated solution of 1,4-DCB and methanol was

mixed in a 40m1 vial; this solution was then added to a 20

liter bottle, nearly full with distilled, deionized water.

In addition, the 20 liter bottle had 30 grams of KC1 in it

(a 2 x 10 -2 M solution), which acted as a conservative

tracer. This bottle was then topped off with distilled,

34

li fll

STOGY\

Sc L v.-rzoN

SAMPLTAG-Loota

C...OL.utflN

sprrItumCrLOOP

1 ,i,

35

C.OND M.-C1r_vi.T1DZTEC:roK

Figure 1. Schematic representation of the soil columnexperimental setup

deionized water, and sealed with a rubber stopper that had

been wrapped with teflon. The stopper had two 1/8" ID

stainless steel tubes through it; one reaching near the

bottom of the stock bottle, and the other only partially

through the rubber stopper, acting as an air vent to admit

air as water is pumped out. The stock solution was mixed

for at least 24 hours with a stirrer and magnetic bar

before running any of the experiments.

The solution was pumped into the column using a

peristaltic pump and 1/16" ID tygon tubing. A "t" fitting

was at the head of the column, which allowed flow both into

the soil column, and into a 2.3 ml sampling loop before the

soil column. This allowed monitoring of the feed (in-

fluent) solution before it entered the column. At the

outlet of the column was a conductivity detector, which

measured the breakthrough of the KC1. After the detector

was a 2.3 ml sampling loop made of 1/8" ID stainless steel

tubing. This sampling loop was used to collect samples for

GC analysis. The soil column was a 30.5 cm long by 2.7 cm

ID glass column, for a total volume of 174 cm 3 ; the cross-

sectional flow area was 5.7 cm 2 . For flow rates between

0.5 and 1.0 ml/min, this will give a Darcian flow velocity

through the column of between 0.09 and 0.17 cm/min, or 4.1-

8.2 feet per day. By contrast, the average linear velocity

of groundwater in the shallow colluvium-alluvium underlying

the field site was estimated to be between 0.25 - 2.5 feet

36

37

per day. The column was packed with the fraction of soil

from borehole DM104SG 39' that passed through a 0.991 mm

soil sieve, but which was retained on a 0.246 mm soil

sieve. The weight of the soil used in the packing was 167

grams, for a bulk density of 0.96. 98 cm 3 of water was

required to fill all the pore space in the column; thus,

for these experiments, one pore volume was equal to 98 cm 3 .

Total porosity was 0.56.

3.8 Chemical Analysis

All chemical analyses were conducted on a Varian

3760 gas chromatograph, using an Ni63 electron capture

detector. A Hewlett Packard integrator integrated the

electronic detector signal. The column in the GC is a 6

ft., 1/4 in. ID Supelco glass column, with a 3% 0V-17

packing. The carrier gas was nitrogen, at a flowrate of 40

ml/min. The column was run at 75 °C, the detector at 300

°C and the injection port at 130 °C. A Hamilton 1710 10 ul

syringe was used; all injections were 3 pl. Settings on the

integrator were typically: chart speed = 0.5 cm/min, peak

width = 0.04, threshold = 0 and attenuation = 2, although

for lower concentrations of 1,4-DCB, a lower attenuation

and threshold were used. Under these conditions, 1,4-DCB

peaks occurred between 4.15 and 4.3 minutes, depending upon

how long the packing had been in the column.

CHAPTER 4

EXPERIMENTAL RESULTS

4.1 Equilibrium Batch Results

The results of the equilibrium batch experiments are

shown in figures 2 and 3. The formulas used to calculate

points along the sorption isotherm were as follows:

C = Co x E (22)

S = Co x (1-E)/r sw (23)

where C = Equilibrium concentration of 1,4-DCB insolution (pg 1,4-DCB/cm 3 water)

Co= Initial concentration of 1,4-DCB in solution(big 1,4-DCB/cm 3 water)

E = Fraction of total 1,4-DCB remaining in solutionat equilibrium

S = Equilibrium concentration of 1,4-DCB on thesoil (pg 1,4-DCB/g soil)r sw = Soil/water ratio in the centrifuge vials

(g soil/g water)

The partition coefficient for 1,4-DCB calculated from the

sorption isotherm for the soils from borehole 2V20B is

1.40. At the soil/water ratios used (0.4-0.6 g/cm 3 ) this

was approximately 40 percent of the total 1,4-DCB added to

the sample tubes. The partition coefficient for the soil

from borehole 102SG is 3.33.

It is apparent from Figures 2 and 3 that equilibrium

partitioning for these experiments is linear, as was

38

SORPTION ISOTHERM FOR 1,4—DCBSOIL 2V2DB

Cb.0 0.5 1.0 1.5 2.0ug 1,4—DCB/cm3 water

Figure 2. Sorption isotherm for 1,4-dichlorobenzene insoil 2V203

SORPTION ISOTHERM FOR 1,4—DCBSOIL 102SG

ociho 0.5 1.0 1.5

ug 1 ,4—DCB/cm3 water

C71

Figure 3. Sorption isotherm fOr 1,4-dichlorobenzene in

soil 102SG

41

originally postulated. A Freundlich isotherm is given by:

S = KC 1 / n (24)

where 1/n and K are the parameters. When S and C are

plotted on a log-log scale, the slope is equal to 1/n.

This procedure was carried out for the data from Figure 2,

and gave a value for 1/n of 1.05, further confirming that

sorption of 1,4-DCB at these low concentrations is linear.

f oc was not measured for the isotherm soil samples. The

foc for the soil used in the column experiments (DM104SG)

was 0.00086. Using this value, soil 2V2DB had K oc for 1,4-

DCB of 1400 cm 3 water/g soil and soil DM102SG had K oc of

3300 cm 3 water/g soil.

4.2 Kinetic Batch Results

Results from the kinetic batch experiments are shown

in Figure 4. Sorption takes place fairly rapidly, with

most of the sorption occuring within the first day.

However, it does appear that there is a small amount of

time-dependent (kinetic) sorption.

Sorption was 20-50 percent complete on the samples

after 1 hour, and almost 100 percent complete after 24

hours. Thus, in some cases, over half of the total

sorption occured within the first hour. However, a

significant amount of sorption occured after the first

hour, sorbing at a different rate. This indicates a

kinetic sorption process is operating here.

47

SORPTION KINETICS OF1,4—DCB1.0

0.8

0 . 0 o 50 100 150

D---SOIL FROM 102SG TIME (hrs.)

A---SOIL FROM 2V2DB4,---60IL FROM 2V2DB0---SOIL FROM DM104, CONC. = 1.0 PPM----CONCENTRATION = 0.2 PPM

CONCENTRATION = 2.0 PPM

Figure 4. Results of kinetic batch experiments with 1,4-dichlorobenzene

Five of the seven kinetic batch experiments show an

increase in 1,4-DCB in solution between times of 24 hours

and 120 hours (the last two data points on the graphs).

This increase ranges between 4 and 12 percent of Co for

these five experiments. This is too high to be accounted

for by experimental and analytical uncertainty, although

this uncertainty could have contributed to the rise. The

rise also cannot be attributed to volatilization losses of

1,4-DCB during the soil saturation and experimental mixing

part of the experiment, since volatilization losses would

result in an overestimation of sorption (see chapter 3),

not a decrease in sorption. An exception to this would be

if the 24 hour samples experienced more volatilization

losses than the 96 hour samples; in this case, the 24 hour

samples would have overestimated sorption, and the later

(96 hour) samples would indicate the actual levels of

sorption. However, the rise in 1,4-DCB in solution for the

96 hour samples is too systematic to attribute it to

something as random as volatilization losses; apparently

some other mechanism is operating here.

Despite these problems with the kinetic data, Figure

4 does indicate a small amount of time-dependent (kinetic)

sorption. Except for the experiments with soil 102SG

(which has a higher partition coefficient), the equilibrium

levels of sorption in these experiments were 60-75 percent

of Co. This is in good agreement with the equilibrium

43

batch experiments, which gave equilibrium sorption levels

of 60-67 percent of Co. This includes soil DM104, the soil

used for the column experiments. This indicates that there

may be a similarity between soil DM104 and soil 2V2DB, the

soil used for the equilibrium batch experiments. Visual

inspection of Figure 4 indicates the kinetic part of the

sorption process beginning somewhere between 70-90 percent

of Co.

4.3 Soil Column Results

The 1,4-DCB data from all five column experiments

are shown in Figure 5, and the conductivity data are shown

in Figure 6. At all the concentrations, the rising limbs

of the breakthrough curves for 1,4-DCB were nearly identi-

cal, indicating that sorption of 1,4-DCB's at these

concentrations is not concentration dependent. Appendix B

contains the breakthrough curves for both 1,4-DCB and

conductivity from each experiment.

4.3.1 Conductivity Data from Column Experiments

Since KC1 is a conservative (nonreactive) tracer,

the sorption term in the advection-dispersion equation

drops out. Under these conditions, the exact analytical

solution to equation 2 shows that the breakthrough of a

conservative solute at the end of a column (i.e. the

appearance of the solute in the effluent solution) will

follow a normal distribution. Thus the time for the

44

45BREAKTHROUGH CURVES FOR

—DCB1.2

0 --EXP. 10 --EXP. 3A—EXP. 41

0—EXP. 113 — EXP. 3A—EXP. 4Q—EXP. 54-EXP. 6

0.0

0.8 0—EXP. 541k—EXP. 6

04

40.4 21

0.0

Figure 5. Breakthrough curves for 1,4-DCB from columnexperiments 1,3,4,5,6

BREAKTHROUGH CURVES FORCONDUCTIVITY1.2

Figure 6. Breakthrough curves for KC1 from columnexperiments 1,3,4,5,6

effluent KC1 concentration to reach 50 percent of Co is the

time when one pore volume (98 cm 3 ) has eluted from the...

column. Compared to this value the rising limbs of the

conductivity curves give C/Co of 0.5 at times ranging

between 0.94 and 1.15 pore volumes, with an average of 1.05

for the five column experiments. The same calculations

were carried out on the descending limbs (desorption part)

of the breakthrough curves; the number of pore volumes

eluted ranged between 0.96 and 1.21, with an average of

1.07 for the five experiments. Thus both the sorption and

desorption parts of the conductivity curves give estimates

of a pore volume close to the measured value of 98 cm 3 .

4.3.2 1,4-DCB Data

Soil-water partition coefficients for a sorbate can

be obtained from column experiments by simple mass balance

on breakthrough curves from the experiments. For a sorbate

(1,4-DCB in this case), the area above its breakthrough

curve when C/Co = 1.0 is equal to the total mass of sorbate

contained in the column. For this analysis, pore volumes

must be expressed in cm 3 and Co in ug sorbate/cm 3 water.

When C/Co is equal to 1.0, the sorbed phase in the column

is at equilibrium, and the solution phase concentration is

equal to Co. Since the total void space is equal to one

pore volume (98 cm 3 for these experiments), the total

sorbate in aqueous solution is equal to one pore volume

times Co, expressed as mass of sorbate. As noted in

46

section 4.3.1, the conductivity of the effluent should be

50 percent of Co at the 1 pore volume point; if this

conductivity curve is symmetric, then the area above the

conductivity curve is equal to one pore volume times Co,

i.e. an area corresponding to the amount of sorbate in

aqueous solution in the column at equilibrium. Thus the

area between the breakthrough curves for conductivity and

sorbate is equal to the total sorbate in the column minus

the sorbate in solution, which is the total mass of sorbate

retained on the soil phase (sorbed). Dividing this sorbed

mass by the mass of soil in the column gives S, the sorbed

concentration at equilibrium. Dividing this by Co, the the

aqueous solution concentration at equilibrium (C) gives K p ,

the equilibrium soil-water partition coefficient. The same

analysis was done on the sorption and desorption fronts of

the breakthrough curves.

Areas above the breakthrough curves were determined

by a Keuffel and Esser compensating polar planimeter, for

both the sorption and desorption portions of the break-

through curves. Soil-water partition coefficients cal-

culated by this technique were between 0.38 and 0.48 for

all five column experiments for the sorption part, and

between 0.34 and 0.51 for the desorption part. The

similarities between the sorption and desorption partition

coefficients indicates that these sorption reactions are

47

48

almost completely reversible. Table 4 gives a listing of

some important parameters from the column experiments.

4.4 Anomalies in Column Experimental Results

One problem encountered in running the column

experiments was that the concentration of the stock

solution varied over time (see Appendix B). It is unlikely

that the stock concentration varied directly in the feed

bottle; since stock concentration sampling was carried out

after the stock passed through the peristaltic pump, it is

reasonble to assume that the change in concentration over

time is due to either sorption onto the tygon tubing in

the pump, or diffusion of 1,4-DCB through the tubing. The

Co value used for calculating the dimensionless concentra-

tion was the highest concentration of 1,4-DCB recorded by

sampling the feed solution at the head of the column.

Graphs using a Co value that was the average of the

concentrations of 1,4-DCB recorded by sampling the feed

solution at the head of the column did not differ signifi-

cantly from the graphs in Appendix B.

Because of the change in stock concentration over

time, it was difficult to determine when the breakthrough

curves for 1,4-DCB had reached equilibrium. This is the

reason the declining limb of the breakthrough curves (the

desorption portion) for the different experiments are not

identical. Each experiment ran for a different amount of

time once it reached "equilibrium", in an effort to

TABLE IV

Summary of Parameters from Column Experiments

Column Conc.Exp. (ppm)

SORPTION

FlowRate(ml/min)

KD(cmsig)

PORE VOLUMESwhen C/Co when influent

= 0.50 pulse stops

1 0.25 0.85 0.44 1.02 3.123 0.50 1.3 0.38 1.15 3.244 1.00 1.1 0.38 1.02 4.715 1.50 1.1 0.39 1.10 5.876 0.50 1.0 0.48 0.94 5.57

AVERAGE 0.41 1.05

DESORPTION1 0.25 0.70 0.34 1.213 0.50 0.81 0.44 1.144 1.00 0.79 0.51 0.965 1.50 0.85 0.51 0.966 0.50 0.55 0.34 1.06AVERAGE 0.43 1.07

49

determine the actual point in time when equilibrium was

reached. The actual desorption lines have the same slope

and degree of tailing; they are simply offset from each

other by the amount of time each experiment ran once it

reached equilibrium. This is also true for the break-

through curves for the conservative tracer, KC1. These

curves are nearly identical, and the offset of the desorp-

tion parts are again due to the length of time the system

was allowed to remain at equilibrium. However, it does

appear that experiments 1 and 3 may not have run for a long

enough time.

The jaggedness of the breakthrough curves near

equilibrium creates another problem in analyzing the data.

Since the mass balance approach to calculating partition

coefficients requires integration of the area above the

breakthrough curves, it was important to determine when

these curves were at equilibrium, in order to know where to

integrate. The graphs from experiments 3, 4 and 5 (see

appendix B) have the conductivity and 1,4-DCB curves

crossing each other near C/Co = 1.00, and the area between

these curves was used for the integration. The Kp's gene-

rated from these experiments were similar. The break-

through curves for experiments 1 and 6 for 1,4-DCB never

reached C/Co = 1.00, resulting in some uncertainty in the

area integrated; this may have caused the variability in

the partition coefficients calculated for the column

50

experiments using the mass balance approach. The jagged-

ness of the breakthrough curves near equilibrium also makes

it difficult to visually determine if there are any kinetic

effects involved in the sorption. While the conductivity

and 1,4-DCB curves have nearly parallel rising and falling

limbs (see appendix B), some tailing does occur at the top

of the rising 1,4-DCB limb and the bottom of the descending

1,4-DCB limb. The nearly parallel rising and falling limbs

indicate that sorption is mostly an equilibirium phenome-

non, and the slight tailing indicates there may be some

kinetic effect involved in sorption of 1,4-DCB onto the

column soil.

51

CHAPTER 5

DISCUSSION

When equation 2 is coupled with equation 3, we get:

DY-c-c (25)-cY -7( 2 - -5 19 3the one-dimensional advection-dispersion equation for

equilibrium sorption. As explained in chapter I, the first

term on the right hand side is a dispersion term, the

second term is an advection term, and the third term is a

sorption term. As before, C refers to the aqueous concen-

tration of the sorbate, p is the soil bulk density and 0-is

the total porosity of the soil in the column. The two

parameters in this equation, D, the dispersion coefficient

(cm 2 /sec) and Kp, the partition coefficient ( cm 3 /g), must

be either measured or estimated before the equation can be

used to simulate solute transport in groundwater. One of

the reasons for generating sorption isotherms in the

laboratory is to determine the partition coefficient, which

can then be used with equation 25. Equation 25 is often

written as:

P, 3c_ D y)—(2, - v-b7c (26)where R, the retardation factor given by:

R = 1 +(pK)/Q (27)

52

53

For a linear sorption isotherm, a retardation factor is the

ratio between the time it takes 50 percent of Co of the

solute to pass through the exit point of the column', and

the time it takes 50 percent of Co of the conservative

tracer (1 pore volume) to pass through the exit point. The

inverse of the retardation factor is often called the

relative velocity, relating the velocity of the sorbate to

the velocity of the conservative tracer.

5.1 Curve-Fitting Analysis of Column Experiments

van Genuchten and coworkers (1980, 1981, 1984) have

developed a nonlinear least-squares curve-fitting procedure

that can be used to estimate the different parameters in

the analytical solution to the one-dimensional advection-

dispersion equation directly from observed effluent data

from column experiments. In addition to the equilibrium

sorption case (van Genuchten, 1980), newer versions of

their computer programs handle kinetic sorption (van

Genuchten, 1981) and sorption experiments conducted in the

field (Parker and van Genuchten, 1984). Analysis of the

present research was done with the 1981 program, called

CFITIM.

5.1.1 Models and Input Parameters in CF1TIM

CFITIM works with analytical solutions to equation

26, for five different conceptual models of sorption

behaviour. A different set of dimensionless variables for

54

each model is introduced into equation 26, and the trans-

formed equation is solved for the exit concentration of the

pollutant as a function of time. These fitted values are

compared with experimentally derived data, and parameters

in the analytical solution are adjusted for a best fit of

the observed data. A list of the dimensionless variables

is given in Appendix C.

The 5 models are labeled A-E. Model A is an

equilibrium model, model B is a physical nonequilibrium

diffusion model, model C is a physical nonequilibrium with

anion exclusion model, model D is a nonequilibrium two-site

chemical kinetics model, and model E is a nonequilibirum

one-site chemical kinetic model. Models B and D were based

on the two models already discussed in sections 2.4.1 and

2.4.2. Once the dimensionless variables are introduced

into equation 26 the analytical solutions to models B,C,D

and E mathematically reduce to the same equation. This

equation has five dimensionless parameters; R is the

retardation factor, P is the Peclet number, Beta (a) is a

parameter related to the ratio of the different types of

sorption sites (kinetic vs. equilibrium, mobile vs.

immobile), Omega is a parameter related to the rate

constant for the kinetic portion of sorption and Pulse is

the length of time (in pore volumes) the influent solution

flowed into the column. Even though the analytical

solution for these four models is the same, the dimension-

55

less variables a and Omega take on different meanings in

the different models. The equilibrium model (A) solution

requires just three parameters as inputs; the retardation

factor, the Peclet number, and the pulse. The one-site

kinetic model only requires four parameters as inputs, as a

is always set equal to the inverse of the retardation

factor (see Appendix C). For any one of the models, only

one of the parameters must be known; the others are

estimated using the least-squares curve-fitting technique.

5.1.2 Boundary Conditions in CFITIM

Two different column exit boundary conditions are

available in CFITIM. The first was used, which is that the

change in concentration (concentration gradient) of the

pollutant at any time at an infinite distance from the

inlet is zero; this assumes the presence of a semi-infinite

soil column. The second one (not used) is that the

concentration gradient at the lower end of the column is

zero. While the second condition may intuitively seem to

be the correct approach, this leads to a condition of a

continuous concentration distribution at x = L, the lower

boundary. The upper boundary condition leads to a situation

where there is a discontinuous concentration distribution

at the inlet position, which would contradict the physical

model presented by the second lower boundary condition.

56

5.1.3 Column Experimental Analysis by CFITIMEquilibrium Model

As discussed in section 5.1.1, CFITIM requires only

one of five (one of three in the equilibrium model)

parameters as a known input. In addition to the known

variable, CFITIM also requires estimates of the remaining

parameters as inputs. The only other data CFITIM requires

is the observed effluent concentration data, given as

dimensionless values in the form of C/Co vs. pore volumes.

5.1.3.1 CFITIM Equilibrium Model Graphs. Figure 7

contains conductivity breakthrough curves generated with

the equilibrium model of CFITIM with pulse input as the

known variable; both observed data and fitted points are

plotted on each graph. Looking at Figure 7, we see again

that the experiments are internally consistent. Except for

the dip in conductivity concentration that occurs in each

experiment at the same time the system starts to reach

conductivity equilibrium, the model provides a good fit to

the observed conductivity data.

The 1,4-dichlorobenzene breakthrough curves gene-

rated under the same conditions are given in Figure 8; they

show the observed data tailing off from the fitted data.

The tailing is indicative of a kinetic effect; this

observation is in agreement with the qualitative observa-

tions of the kinetic batch experiments (Figure 5, section

4.2). Visual inspection of the graphs indicates that with

1 and fitted conduc-xperiments 1,3,4,5,6model. Only the

Figure 7. Comparison of experimentativity data from column eusing CFITIM equilibriumobserved data is plotted.

•

1.0

0.8

0.6o

0.4

0.2 -

0.0 1-r- r LT 111- 1-1 I 1- 1-r1 1 -1 • -14 8PORE VOLUMES

12

0.2

-1 r r-r- r- r 1 Tr r" rrl0.0 {Minh r 1 -1 r-r r-r r .:111111f if

0 4 8 12PORE VOLUMES

1.0 -

0.8 -

0.6 -o0 -...

0.4 -

0.2 -

0.0

0.0 ri r-r-r -r-r-r r-r- r-r tn-1-1

4 8 12PORE VOLUMES

1.0

0.8

0.50o

0.4

0.2

0.012

40 —EXP. 10—EXP. 3A—EXP. 4O—EXP . 5*—EXP. 6

57

0.8

58

0.60 7 00 0

0.4

0.2

0.0 -r ri j I T-1' j 7 1-1-1-14 8 12PORE VOLUMES

Lc:

▪

r—m-st

1.0 -1

0

a- r

0.8

0.6 -_(-4 -

C.4 -

(?

-

'0.2 7

0 4 8 12PORE VOLUMES

40

1.0 -1

C.2 - ,-1-. (

**L. ] *

Co*

r

I_

0.8 - 12 **1

O• 0 r- .$1--rl-r-r-l-r, f T -r-r-, 7 7-1 IT 111g n f4 8 12 --.1a 1***

0.6 ikt *I

PORE VOLUMES-1

"....o

1.0 7 4(....)

3(----Y_I--, (...)! p

0.8 14'-1

3 "i

0.6 3o

C.-3 -.'--- -(..3

O4- A

0.4 -11

:40.2

-n\

0.0 471** 'i *

0 4 8 1::FORE: VOL UMES

0—EXP. 1D— EXP. 3L.—EXP. 4.0—EXP. 54.-EXP. 6

0.2-

0.00.0 4fil41.1, I 1- 1 Ij rI12 4 8

POP.L \'01.L1M LS

Figure 8. Comparison of experimental and fitted 1,4-dichlorobenzene data from column experiments1,3,4,5,6 using the CFITIM equilibrium model.Only the observed data is plotted.

59

the exception of experiment 6, the kinetic effect seems to

occur after sorption is 80-90 percent complete. This is

the point where the rising limb of the breakthrough curves

for the observed 1,4-DCB concentrations begins to tail off

from the breakthrough curves for the fitted 1,4-DCB

concentrations, and is roughly the same point at which the

kinetic batch experiments began to show kinetic sorption,

as discussed in section 4.2. Tailing in the graph from

experiment 6 occurs much earlier; inspection of the graph

shows that this is probably due to the 1,4-DCB concentrat-

ion never reaching the Co level, perhaps because of

sorption of the influent solution by the tygon tubing.

Despite this, the same kinetic effect is in evidence,

before the concentration of 1,4-DCB in the effluent reaches

an equilibrium level.

5.1.3.2 CFIT1M Equilibrium Model Parameter Estimates.

Estimated parameters for the equilibrium model runs are

shown in Table 5. As noted in section 5.1.1, this model

requires only estimates of the retardation factor and the

Peclet number as inputs, if the influent pulse is known.

The equilibrium model was run under several different

conditions. First, both 1,4-DCB and conductivity data were

run with only the pulse input as a known variable (case

numbers 1 and 3, respectively, in Table 5). The conduc-

tivity data were also run with the retardation factor (R)

TABLE V

DATA FROM EQUILIBRIUM MODEL

CASE

COLUMN EXPERIMENT NUMBER 1

NAME VALUE S.E.COEFF.

1 Conductivity data,pulse known

PECLETR

21.5321.132

9.0920.040

2 Conductivity data R=1.0 PECLET 8.784 2.7233 DCB, pulse known PECLET 14.685 2.678

1.796 0.0404 DCB, with Peclet from 1 R 1.817 0.0365 DCB, with Peclet from 2 R 1.757 0.048

COLUMN EXPERIMENT NUMBER 31 Conductivity,

pulse knownPECLET

R191.921

1.14928.3820.005

2 Conductivity R=1.0 PECLET 25.193 14.1583 DCB, pulse known PECLET 157.203 2.300

R 1.801 0.0254 DCB, with Peclet from 1 R 1.793 0.0045 DCB, with Peclet from 2 R 1.616 0.000

COLUMN EXPERIMENT NUMBER 41 Conductivity data,

pulse knownPECLET

R149.025

1.05116.4900.004

2 Conductivity R=1.0 PECLET 122.944 27.9783 DCB, pulse known PECLET 157.207 2.713

1.799 0.0304 DCB, with Peclet from 1 R 1.548 0.0035 DCB, with Peclet from 2 R 1.502 0.001

COLUMN EXPERIMENT NUMBER 51 Conductivity data PECLET 69.629 17.504

pulse known R 1.030 0.0152 Conductivity R=1.0 PECLET 71.743 19.1143 DCB, pulse known PECLET 58.802 0.657

R 1.769 0.0194 DCB, with Peclet from 1 R 1.506 0.0025 DCB, with Peclet from 2 R 1.500 0.001

COLUMN EXPERIMENT NUMBER 61 Conductivity data,

pulse knownPECLET

R96.0421.102

26.1750.014

2 Conductivity R=1.0 PECLET 42.899 15.7763 DCB, pulse known PECLET 59.713 1.047

R 1.746 0.0304 DCB, with Peclet from 1 R 1.503 0.0025 DCB, with Peclet from 2 R 1.500 0.000

60

61

input as a known variable (case 2). R was assigned a value

of 1.0, the theoretical value for KC1 in the absence of ion

exclusion effects. The 1,4-DCB data were then run twice,

with the Peclet number input as a known variable. The

first run (case 4) used the value for the Peclet number

generated from the conductivity data with only the pulse

input as a known variable (case 1). The second run (case 5)

used the value for the Peclet number generated from the

conductivity data when that data had R input with a value

of 1.0 (case 3). The table gives the estimates of the

different parameters generated by the equilibrium model,

and the standard error coefficient involved in the estima-

te.

With pulse as the only known input variable, 1,4-DCB

data from all five experiments gave a retardation factor

between 1.77-1.80. Converting the average value to Kp

using equation 26 with p=0.96 and 0=0.56 yields a partition

coefficient of 0.46. This agrees well with the sorption

partition coefficients generated by mass balance on the

breakthrough curves (see Table 4); these coefficients were

between 0.38 and 0.48.

The Peclet number is one of the dimensionless

variables introduced into equation 26; its conversion into

the dispersion coefficient is given by:

D = vL/P (28)

62

TABLE VIo

Dispersion coefficients generated by CFITIM equilibriummodel, ordered by velocity

COLUMNEXPERIMENT

D for KC1data

(cm 2 /sec)

D for 1,4-DCBdata(cm 2 /sec)

Velocity(cm/sec)

1 3.39x10-3 4.98x10-3 2.43x10-3

6 0.92x10-3 1.47x10-3 2.86x10-3

4 6.48x10-4 6.15x10-4 3.14x10-3

5 1.37x10-3 1.63x10-3 3.14x10-3

3 5.95x10-4 7.20x10-4 3.72x10-3

AVERAGE 1.38x10-3 1.88x10-3 3.06x10-3

63

where D is the dispersion coefficient (cm 2 isec), v is the

Darcian velocity (cm/sec), L is the column length (cm) and

P is the Peclet number. Darcian velocities for the column

experiments can be obtained by dividing the flow rate by

5.7 cm 2 , the cross-sectional , area of the column. Veloci-

ties and dispersion coefficients for each column experiment

are given in Table 6. For each column experiment, disper-

sion coefficients generated with the 1,4-DCB data and those

generated with the conductivity data are similar. The

dispersion coefficients for the column experiments vary

over an order of magnitude, between 6.0 x 10 -4 and 5.0 x

10 -3 cm 2 /sec.

The dispersion coefficient is usually represented by

D =vxa (29)

where a is the dispersivity (cm). Comparing equations 28

and 29 we see the dispersivity is equal to the column

length divided by the Peclet number. The dispersion

coefficient is linearly related to velocity, while the

dispersivity is a property more intrinsic to a flow system,

conceptually thought of as a characterisitic mixing length.

Thus dispersivity is more often reported in the literature;

Anderson (1979) gives typical values of the dispersivity in

column experiments of 0.1-1 cm; all the values for the

CFITIM runs fall within this range.

Inputting different parameters as known variables

during the equilibrium model runs had only a small effect

64

on the model results. Inputting R = 1.0 for the conductiv-

ity data (case 2) resulted in lower estimates for the

dispersion coefficients, and a higher ratio of standard

error to parameter value. With the exception of experiment

3, the change in dispersion coefficient was not more than a

factor of 3. Inputting the Peclet number as a known

variable for the 1,4-DCB data also had only a small effect.

With the exception of experiment 1, the major effect was to

significantly reduce the standard error of estimation of

the retardation factor. However, for each column experi-

ment, the R calculated for all three cases involving 1,4-

DCB data (2,4 and 5) varied at most 17 percent. The

largest change in Kp under these conditions was for column

experiment 4, cases 3 and 5, which had Kp of 0.46 and 0.29,

respectively.

5.1.4 Analysis by Non-equilibrium Models

The data were also analyzed using the nonequilibrium

models in CFITIM. Model E, the one-site chemical kinetic

model, assumes all sorption sites are equal, with the rate

of sorption onto the sites controlled by a first-order

chemical process. The first-order kinetic rate equation

for this model is:

a(kC - S) (30)

where C and S have already been defined. Comparison of

equation 30 with equation 5 (section 2.4) reveals that k in

equation 30 is equal to the sorption (forward) rate

65

constant divided by the desorption (reverse) rate constant

times the inverse of the soil/water ratio (rs w ):

k = (kf/kb)/rsw (30)

k has dimensions of cm 3 water/g soil, and by definition,

is equal to the soil-water partition coefficient, K. a

then, is equal to the desorption rate constant, kb (sec -1 )

in equation 5. rs w is equal to the soil bulk density

divided by the porosity; for the column experiments this

was equal to 1.71.

Model E was used with the Peclet number from the

first conductivity data analysis (case 1 from Table 5)

input as a known variable. The partition coefficients

generated by this model varied between 0.4 and 0.55, with

an average of 0.46. This is the same average obtained from

the equilibrium model, indicating that the kinetic effect

on sorption is small.

Pulse values obtained from this analysis deviated

slightly from the experiment