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POLYCYCLIC AROMATIC HYDROCARBONS:
PARTITIONING TO LAKE MICHIGAN SEDIMENT

By

Leif Krag Rowles

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

1994

ABSTRACT

POLYCYCLIC AROMATIC HYDROCARBONS:
PARTITIONING TO LAKE MICHIGAN SEDIMENT

By

Leif Krag Rowles

Experimental batch absorption studies were completed to
evaluate the apparent solid phase organic carbon partitioning
coefficient of four PAH compounds to Lake Michigan Sediment. The
experiments were conducted over a range of solid concentrations to
study the concept of a solid effect. Additionally, partitioning
coefficients for phenanthrene and benzo-a-pyrene were determined
for the aqueous phase distribution in terms of "free" and "bound" by
using the reverse phase and the fluorescence quenching techniques

which have been developed by other researchers.

Data obtained for benzo-a-pyrene using both a constant and
varying solid technique suggested that heterogeneous sorption was
occurring. This data was calibrated to the Solute Complexation Model
developed by Voice, 1985. A non-linear parameter estimation
technique was attempted to estimate both the aqueous "free" and
"bound" solid phase sorption coefficients which are conceptualized in

the model.

TABLE OF CONTENTS

List of Tables

List of Figures

List of Symbols

Introduction

Chapter 1: Theory and Background

1.1

1.2

1.3

1.4

1.5

1.6

Introduction

Hydrophobic Sorption and Evaluation of
Partitioning Data

The Relationship Between Observed Partitioning
and Solids Concentration

Three Phase Modeling
Equilibrium partitioning

Solute Complexation Model

Chapter II: PAH sorption Experiments

2.1

2.2

Introduction
Materials and Methods
2.2.1 Sediment Sampling

2.2.2 Batch Sorption Experiments

iii

vi

viii

15

16

17

23

26

26

28

2.3

2.4

TABLE OF CONTENTS (continued)
Results and Discussion: Solid Phase Sorption

Conclusions: PAH Sorption Experiments

Chapter III: Measurement of Phenanthrene and
Benzo-a—pyrene Binding to Lake Michigan
Sediments
Introduction

3.1

3.2

3.3

3.4

Quantifying DOC Released from Lake Michigan
Sediments

3.2.1 Materials and Methods

3.2.2 Results and Discussion

Fluorescence Quenching

3.3.1 Methods and Materials for Fluorescence
Quenching Measurements of Phenanthrene

and Benzo-a-pyrene

3.3.2 Results and Discussion: Calculation of Kdoc

3.3.3 Conclusions: Fluorescence Quenching
Reverse Phase Separation

3.4.1 Materials and Methods: Emporer Disk
Extraction

3.4.2 Results and Discussion: Emporer Disk
Extraction

3.4.3 Conclusions: Emporer Disk Extraction

Chapter IV: Modeling Benzo-a-pyrene Sorption to Lake

Michigan Sediments Using the Solute
Complexation Model

iv

54

56

56

58

59

66

69

74
79

83

85

89

92

95

TABLE OF CONTENTS (continued)

4.1 Introduction
4.2 Results and Discussion
4.2.1 Model Calibration
4.2.2 N on-linear Parameter Estimation
4.2.3 Conclusions
Future Research

Reference List

95
96
96
112
115
117 .

118

LIST OF TABLES

Introduction
Table 1.1: Polycyclic Aromatic Hydrocarbon Properties 3

Chapter II: PAH Sorption Experiments

Table 2.1: Radiolabelled PAH Data 31
Table 2.2: Phenanthrene Partitioning Data 35
Table 2.3: Fluoranthene Partitioning Data 36
Table 2.4 Pyrene Partitioning Data 37
Table 2.5 Benzo-a-pyrene Partitioning Data 38
Table 2.6 Benzo-a-pyrene Partitioning Data 39

Table 2.7 Confidence in Benzo—a-pyrene

Activity Measurements 41
Chapter H1: Measurement of Phenanthrene and Benzo-a-pyrene
Binding to Dissolved Organic Carbon from Lake
Michigan Sediments
Table 3.1 Fluorescence Quenching, Phenanthrene 75
Table 3.2 Fluorescence Quenching, Benzo-a-pyrene 77
Table 3.3 Reverse Phase Separation, Phenanthrene 90

Table 3.4 Reverse Phase Separation, Benzo-a-pyrene 91

vi

Appendices
Table A.1

Table D.1
Table D2

Table E.1

Table E.2

Table E.3

Benzo-a-pyrene Timed Fluorescence Data

Benzo-a-pyrene, Non-linear parameter
Estimation

SystatR Parameter Estimation,
K1 and K2

Phenanthrene Dialysis with AldrichR
Humic Acid

Photometric Data, Phenanthrene Dialysis

l4C Activity Measurements, Phenanthrene
Dialysis

vii

124

144

145

148

151

152

Chapter I:

Figure 1.1:

Figure 1.2:
Figure 1.3:
Figure 1.4:

Figure 1.5:

Figure 2.1:
Figure 2.2:
Figure 2.3:
Figure 2.4:

Figure 2.5:

Figure 2.6:
Figure 2.7:

Figure 2.8:

LIST OF FIGURES

Theory and Background

Grand Calumet River Data: PAI-I‘s, K0c vs foc

Grand Calumet River Data: PAH‘s, K0c vs foe

Grand Calumet DOC vs foc

Schematic of Solute Complexation Model

Effect of Isothenn Procedure for
Heterogeneous Solute

Chapter II: PAH Sorption Experiments

Sampling Locations

Procedure Flow Chart

Radiolabelled Compound Purification
Pyrene Kinetic Data

K0,; vs Sediment Concentration:
Fluoranthene

Recovery of Fluoranthene from Sediment
Fluoranthene sorption Data .

PAH Sorption Data

viii

11
12

14

18

2O

27
29
30

33

43

47

48

List of Figures (continued)

Figure 2.9: Effect of Isotherm Procedure on Observed

Partitioning for a Heterogeneous Solute 50

Figure 2.10: Phenanthrene Absorption Isotherm 51

Figure 2.11: Benzo-a-pyrene Absorption Isotherm 53
Chapter III: Measurement of Phenanthrene and Benzo-a-pyrene

Binding to Dissolved Organic Carbon from Lake Michigan Sediments

Figure 3.1: Release of Organic Carbon from Sediments 61
Figure 3.2: Absorbance at 255 nm vs

Sediment Concentration 62
Figure 3.3: TOC vs Absorbance at 255 nm 64
Figure 3.4: TOC and Turbidity vs Absorbance 65
Figure 3.5: Phenanthrene Fluorescence Spectra 71
Figure 3.6 Benzo-a-pyrene Fluorescence Extrapolation 73

Figure 3.7: Phenanthrene Reverse Phase
and Fluorescence, Kdoc 81

Figure 3.8: Benzo-a-pyrene Reverse Phase

and Fluorescence, Kdoc 82
Figure 3.9: Flow-rate through Empore Disk 87
Figure 3.10: Benzo-a-pyrene, Corrected K0c 94

Chapter IV: Modeling Benzo-a-pyrene Sorption to Lake Michigan
Sediments Using the Solute Complexation Model

Figure 4.1: Schematic of Solute Complexation Model 97

ix

Figure 4.2:

Figure 4.3:

Figure 4.4:

Figure 4.5:

Figure 4.6:

Figure 4.7:

Figure 4.8:

Figure 4.9:

Figure 4.10:

Figure 4.11:

Appendices

Figure 13.1

Figure E.2

List of Figures (continued)

Effect of Isotherm Procedure for
Heterogeneous Solute

Sensitivity of Solute Complexation
Model to Kr

Sensitivity of Solute Complexation
Model to K2

Sensitivity of Solute Complexation
Model to K"

Model and Experimental Koo Data,
Benzo-a-pyrene

Benzo-a-pyrene Sorption Isotherm,
Model and Experimental Data

Model Free and Bound Concentration
Ben zo-a-pyrene

Model Kdoc, Benzo-a-pyrene

Model and Experimental Kdoc,
Benzo-a—pyrene

Model and Experimental Koc,
Benzo-a-pyrene

Dialysis of Phenanthrene, l4C Activity
on Outside of Bag

Dialysis of Phenanthrene, 1“C Activity
on Inside of Bag

99

101

102

103

105

106

108

110

111

114

149

150

1/n

Csb
Csf
Cw
Cwb

er

List of Symbols:

Freundlich Sorption Intensity
Concentration in solid

"bound" concentration in the solid

"free" concentration in the solid
Concentration in water

"bound" concentration in the water
"free" concentration in the water
Dissolved organic carbon

Fluorescence in presence of quencher
Fluorescence in absence of quencher
fraction of organic carbon

Hydrophobic Organic Contaminant
Freundlich Sorption Capacity

"free" compound partitioning coefficient
"bound" compound partitioning coefficient

Partitioning coefficient to dissolved organic
carbon

Organic carbon partitioning coefficient

octanol water partition coefficient

xi

PAH

[PAHlbmmd
[PAHJfrec

[PAHIW

List of Symbols (continued)
Apparent partitioning coefficient
Quantum yield of PAH-DOM complex
Polycyclic Aromatic Hydrocarbon
Total organic carbon
DOM Bound PAH in solution
Free PAH in solution

Total PAH in solution

xii

Introduction

This thesis develops methods for evaluating the partitioning of
phenanthrene, fluoranthene, pyrene, and benzo-a-pyrene between
solid and aqueous phases. Measurements of the partitioning of
polycyclic aromatic hydrocarbons to sediments are made using batch
sorption experiments. Additionally, phenanthrene and benzo-a-
pyrene partitioning to dissolved organic carbon is measured using
fluorescence quenching and reverse phase techniques. The results
are evaluated under equilibrium partitioning assumptions and
partitioning coefficients are calculated in terms of the solid phase
organic carbon and the aqueous phase dissolved organic carbon.
Finally, the solute complexation model (Voice 1983) is used to
evaluate the data obtained for benzo-a-pyrene partitioning to Lake

Michigan Sediments.

The objectives are as follows:

1. To measure the partitioning of phenanthrene,
fluoranthene, pyrene, and benzo—a-pyrene to Lake

Michigan Sediments in laboratory batch sorption studies.

2. To measure the partitioning of phenanthrene and benzo-
a-pyrene to dissolved organic carbon from Lake Michigan
Sediments using fluorescence quenching and reverse

phase techniques.

2

3. To evaluate a correction technique which has been used
for the "particle concentration effect" and to apply the
Solute Complexation Model (Voice 1983) to benzo-a-

pyrene sorption data.

Polycyclic Aromatic Hydrocarbons (PAH's) were the chosen
compounds to evaluate partitioning to Lake Michigan sediments from
offshore Muskegon. PAH's are one class of hydrophobic organic
contaminants (HOC's) which are of environmental concern. They are
formed from the incomplete oxidation of fossil fuels, and are present
as byproducts of the petrochemical industry. Wood treating, oil
recycling, and incineration facilities have been the source of PAH
contamination for many sites across the US. (Booth and Jacobson
1992). Many of the PAH's are known or suspected carcinogens and
mutagens and have been shown to bioaccumulate when exposure

occurs in environmental systems (Giesy 1986).

Because PAH's are nonpolar and characterized as hydrophobic
organic compounds (HOC's, operationally, Log K0W > 103, Voice 1983),
they are present in water systems in trace quantities. Sorption

dominates PAH fate in sediments and soils. (Karickhoff 1981)
developed the following expression to predict K0c values for PAH‘s:

Km = 4.9x10‘7 * Kowl-OO

Selected solubility data and octanol water partitioning coefficients for

a range of PAH compounds are included in Figure l.

Figure 1.1

Polycylic Aromatic Hydrocarbon Properties

Napthalene

Fluorene

Phenanthrene

Anthracene

Pyrene

Fluoranthene

Chrysene

3—4 benzopyrene

age

3
Q
Q

Q
©8

to
Q8

©© to
Go ©©
@ ©

Molggglar Weigh;

128.19

166.23

178.24

178.24

202.26

202.26

228.3

252.32

(1) Handbook of Environmental Data on Organic Chemicals

(2) McKay. 1980

Ibili ml! (2)

30

1.9@25C

0.816 @ 21 C

1.29 @ 25 C

0.16@26C

0.265 @ 25 C

0.006 @ 25 C

0.003

Magma)

3.37

4.18

4.46

4.45

4.88

5.22

5.91

6.50

Chapter 1: Theory and Background

1.1 Introduction

The fate of chemicals once they are released into the
environment is very complex. Many mechanisms exist which
describe how a chemical will interact with environment. For
hydrophobic organic chemicals (HOC's) which have a distaste for
water (or more appropriately, for which water has a distaste)

sorption to sediment and soils is a primary fate process.

The following chapter is a review of hydrophobic sorption and
literature partitioning data from contaminants which undergo
hydrophobic sorption. The chapter describes the relationship
between observed partitioning and solid concentration and presents
the dissolved/particle-bound/dissolved organic carbon bound system
for hydrophobic contaminants. Additionally, this chapter presents
the solute complexation model as a possible description of the
distribution of hydrophobic compounds among the

dissolved/particle-bound/dissolved organic carbon bound system.

1.2 Hydrophobic Sorption and Evaluation of Partitioning Data

Hydrophobic sorption is a mechanism which is driven by the
incompatibility of nonpolar compounds and water (Stumm, 1988). It
has been described by some researchers as an entropically driven

dissolution reaction (Voice, 1983). Sorption of a hydrophobic

5

contaminant is favorable because of the increase in entropy which
occurs when the tetrahedral ordering of water molecules around
molecules of the contaminant in solution is broken (Voice, 1983).
The bonding force of hydrophobic chemicals is due to amplified van
Der Waals interactions as well as the thermodynamic gradient
driving the molecules out of solution and on to the sorptive surface
(Voice, 1982). Other researchers reason that the mechanism of
hydrophobic sorption is really a partitioning process similar to
dissolution. In environmental systems, soil organic matter acts as a
solvent which is more compatible with the hydrophobic compound

than water (Chiou, et. al., 1977, 1983).

Partitioning, as it is used in our study, is the distribution of a
hydrophobic contaminant among solid and liquid phases.
Partitioning relates to solute as well as sorbent properties, and for
HOC's, the degree of sorption is related to the compound
hydrophobicity in terms of the octanol/water partitioning coefficient
(Km) and the fraction of organic carbon (foe) on the sorbent. Total
organic carbon content appears to be the major factor in determining
a solid’s sorptive potential, while the octanol-water partition
coefficient is the best known indicator of the extent to which a

compound will sorb (Briggs, 1973; Voice, 1983).

Many correlations have been developed to describe HOC
partitioning in relation to Kow and foe (Means 1980, Swarzenbach and

Westall 1983, Karickoff 1981). Swarzenbach 1983, correlated

6

polycyclic aromatic hydrocarbon (PAH) sorption to several different

sorbents using the following expression:

Log Kp = a*Log K0W + Log f0c + b

Where the coefficients a and b vary for different solute/sorbent
systems, f0c denotes sorbent organic carbon fraction, and K0‘” is the

octanol/water partitioning coefficient.

A sorption isotherm is a way of describing graphically, the
distribution of a compound between the aqueous and absorbed
phases. A typical experiment would involve spiking varying
amounts of a compound into equivalent volumes of water and
sorbent. Alternately, the amount of sorbent could be varied and the
amount of compound kept constant. After equilibrium is reached,
the amount of compound sorbed and the amount of compound in
solution is measured. The data is then plotted as amount sorbed vs.
amount in solution. Models are used to describe this relationship by
fitting the data to mathematical equations. Early studies noted that
the absorption isotherm, was linear at solute concentrations less than
50 % of the aqueous solubility. Karickoff (1983), identified that at
pollutant concentrations common to aquatic systems, (low ppm or
less), the assumption of linearity would be expected. He reasoned
that constant aqueous phase activity coefficients would be expected

unless pollutant levels approached solubility limits.

7

The simplest isotherm model which describes absorption data

is that of linear adsorption or constant partitioning:
Cs = Kp * Cw

In the linear absorption isotherm, Cs defines the concentration in the
soil or sediment, CW defines the concentration in the water, and Kp
defines the distribution between the water and sediment. Although
linear partitioning may be convenient due to its mathematical
simplicity, caution is recommended, since it may not be applicable

over large ranges of solute and sorbent concentrations.

The Freundlich isotherm is an alternate way to describe

sorption data:
C = K * C 1’“
S W

It is often used for heterogeneous systems such as soils and
sediments to describe partitioning data which exhibit an exponential
mathematical form (Voice, 1983). The exponential form of the
Freundlich equation allows it to be linearized on a logarithmic scale,
and therefore it is useful to describe partitioning data from large
ranges of solute and sorbent concentrations. K can generally be
thought of as sorption capacity, while 1/n is a measure of sorption

intensity (Voice and Weber, 1985).

8
In the Freundlich equation, linear partitioning occurs when n=1
and it is often observed for sorption studies involving soils and
sediments at low solution concentrations (Karickoff, 1979). Using the

logarithmic form of the Freundlich equation,

Long=LogK+1/n*Long

the Freundlich sorption capacity parameter, K, can be determined by
extrapolating the plot of log Cs vs. log Cw to Cw=1 (Log CW = 0). The
sorption intensity parameter, lln, can also be determined by the

slope of the plot.

In order to compare partitioning among different soils and
sediments, the observed partition coefficient, Kp’ can be normalized

to the fraction of organic carbon, foe:

Koc=Kplfoc

Lambert (1968) demonstrated that this term normalized the linear
partition coefficient for a wide range of soils with different organic

carbon contents.

1.3 The Relationship Between Observed Partitioning and Solids

Concentration

One of the difficulties in the evaluation and prediction of

hydrophobic sorption arises as a consequence of the "particle

9

concentration effect". The relationship of solids concentration to
observed partitioning in laboratory studies has been well established
(Voice 1983, O'Connor and Connolly 1980). It is noted that apparent
partitioning coefficients for HOC's which have been normalized to the
fraction of organic carbon, foe, decrease with increased solids
concentration. The effect is present in data from partitioning
experiments which use a varying solids to solution ratio. Partition
coefficients have been observed to increase as much as an order of
magnitude for every order of magnitude decrease in solids
concentration. Voice, 1983, noted that this observation is in conflict
with the predictions of many partitioning models and appears to

contradict fundamental thermodynamic principles.

Although linearized partitioning may be applicable over
relatively small ranges of sorbent concentrations in partitioning
studies, many researchers have noted that the observed Koo values
decrease at high solid concentration for many solute/sorbent systems
(O'Connor and Connoly 1980, Voice 1983). This observation is often
noted even in apparently linear sorption isotherms. Reasons for this

apparent anomaly have been developed by many researchers:

1. Equilibrium has not been achieved, (Karichoff,
1984)
2. Binding to dissolved organic matter has not been

corrected for in the calculation of K1) (Gschwend and

Wu,l985, Hoke and Giesy, 1992 prepublication)

10

3. The system is not a true two-phase system, rather
it includes additional compartments that are not
measured independently in the isotherm procedure
(Voice, 1985).

4. Competitive sorption between pollutant and an
implicit adsorbate initially on the sorbent (Curl and
Keoleian, 1984).

5. Presence of both reversible and resistant

components (Di Toro, 1986)

These developments are the subject of on-going research, and
irrefutable descriptions of the relationship between observed

partitioning and solids concentration are not available.

In actual environmental systems, little data is available to
study the affect that increasing foe or the "particle concentration
effect" has on observed partitioning. However, a field study
conducted by Hoke and Giesy (1992 prepublication) on the Grand
Calumet provided a range of sediment foc's and partitioning data for
HOC's. The DOC in Hoke's experiments was derived from centrifuging
wet sediments sampled from the Grand Calumet and filtering the

supernatant. The DOC was defined as pore water within the study.

Our reduction of Hoke's data shows that the value of the

partitioning coefficient for all of the PAH compounds decreased over

the range of sediment f0c which was sampled (Figures 1.1 and 1.2).

At the very least, these data suggest that measured Koc values may

11

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not be linearly correlated to sorbent oc%. Other factors are present
including sorbent and solute heterogeneities--a conclusion which was

hypothesized by Voice 1985.

Additionally, further reductions of the data from Hoke's study
were completed to evaluate the DOC to f0c ratio. It was hypothesized
that the DOC may by a function of foe, since as the organic carbon
within the sediment increased, the organic carbon in the dissolved
state is expected to increase. As indicated in figure 1.3, DOC shows
little relationship to increasing foc. This may be an indication that
the dissolution of sediment organic material within the Grand

Calumet has reached a limiting value even at low foe.

The data reduction from Hoke's study simply indicate the site
specific nature of field Koc evaluations regardless of using a
coefficient normalized to organic carbon content. Complications
include the fact that sediments in the Grand Calumet contain high
levels of grease and oil, and composition is specific to sampling
location. However, they demonstrate that in environmental systems,
Kp adjusted for f0c and corrected for aqueous phase DOM to eliminate
the effect of binding to DOM, does not describe fully the partitioning
relationship to oc% and DOM. And, although details regarding the
exact nature of these relationships are not available as yet, they

demonstrate the need for further lab studies.

14

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1.4 Three Phase Modeling

Much of the current research which addresses the distribution
of HOC's within environmental systems relies on the concept of a
three phase system. Pertinent environmental systems which
correspond to a three phase model include partitioning of HOC's from
contaminated sediments into the water column (Voice, 1983; Eadie,
1990) and partitioning between sediments and pore water (Hoke and
Giesy, 1992). Additionally, the movement of HOC's within
contaminated aquifers is described by retardation factors which
relate to solid phase sorption and desorption. Organic colloidal
material has been shown to facilitate transport by binding with
hydrophobic contaminants in experimental soil columns and field

studies (McCarthy, 1989; McGee, 1991).

The following conceptual schematic shows compartments which
may be considered in environmental systems. Actual interactions
between each compartment are conceptualized differently by
different researchers. It is generally felt that the free fraction of
environmental contaminants are significant in that they are
bioavailable and can enter the food chain (McCarthy, 1985; Giesy,
1983).

16

 

 

Free ‘ . Bound
fraction fraction

 

 

 

 

 

 

 

Sediment

 

 

 

1.5 Equilibrium Partitioning

By conceptualizing environmental systems as boxes where the
distribution of HOC's is defined by partitioning coefficients, exposure
and fate analysis can be simplified. Equilibrium partitioning is a
concept which has been proposed to estimate biouptake from various
compartments in environmental systems (DiToro, 1991) Its success

depends on the following assumptions:

1. Equilibrium is achieved
2. Kinetics are rapid in all phases

3. Only "Free" compound is bioavailable

The first and second assumptions are related in that rapid

kinetics will permit equilibrium to be reached quickly. However, as

17

noted by some researchers (DiToro, 1986; Karickoff, 1983), sorption
kinetics can be slow and true equilibrium is not rapidly attained.
The third assumption has been tested by many researchers.
McCarthy 1985, found that biouptake of PAH's in bluegills was
reduced when the PAH's were bound to dissolved humic material.
Giesy 1983, found that in some cases the bioavailability was reduced
for PAH's bound to humics. Although the assumption of equilibrium
partitioning is reasonably achieved under controlled experimental
conditions, it is not feasible to suggest that the assumptions are met
in environmental systems at all times. None-the-less, partitioning
models provide a basis for extrapolating measured data to real

systems.

1.6 Solute Complexation Model

A model was developed by Voice, 1985, to describe three
phase partitioning. The model conceptualizes a phase transfer of HOC
binding material from organic solids and a distribution of the
aqueous phase between "free" and "bound" constituents. A schematic
of the model system is shown in figure 1.4. Concentrations of HOC's
within each compartment can be predicted by using equilibrium

partitioning.

The aqueous HOC species within Voice's model are defined by a
partition coefficient between the dissolved organic carbon (DOC) and
water. Each constituent in the liquid phase is in turn distributed to

the solid phase by distinct partition coefficients, K1 and K2. The

118

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19

overall partition coefficient or apparent Kp determined

experimentally is then defined as:
Kp= (Csf + Csb)/(er + Cwb)

Where, Csf = mass fraction of free compound in solid
Csb = mass fraction of bound compound in solid
er = mass fraction of free compound in solution

Cwb = mass fraction of bound compound in solution

Although Voice did not propose a distinction between Csf and
Csb, we have developed it in this way since K1 and K2 are equilibrium
coefficients. Voice proposed that the observed decrease in the
partitioning coefficient with changes in solids concentration be
attributed to transfer of a sorbing, or solute binding material from
the solid to the liquid phases. The amount of (the binding material
released to solution would increase with increasing solids, resulting
in values of Koc which decrease as a logarithmic function of solids
concentration. In order to evaluate the amount of a contaminant at
equilibrium within each phase, the solid phase partitioning
coefficient as well as the free/bound distribution within the aqueous

phase must be measured.

The solute complexation approach also incorporates solute
heterogeneity in its development by allowing for different
equilibrium sorption coefficients for the "bound" and "free" phase in

solution. Figure 1.5, adapted from Voice, shows a hypothetical chart

24 587821

111102

SOLID PHRSE CONCENTRRTION (NC/G)

l J ALL
1

r
r
L
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20

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Figure 1.5: Effect of Isotherm Procedure for Heterogeneous Solute

21

indicating the effect of the isotherm procedure on observed
partitioning for a heterogeneous solute. The curves represent a
system with two compounds having partition coefficients of 104 and
102. Each initially comprises 50 % of the mixture. The curves are
developed assuming both the constant and varying solids
experimental techniques. As can be seen, the varying procedures
result in different isotherms. The constant sediment isotherm is
linear while the constant concentration isotherm is non-linear even
on the log-log plot. Voice (1983), experimented with humic and
fulvic acid sorption to activated carbon and showed data trends
similar to the hypothesized heterogeneous solute curves. He

interpreted the results as examples of heterogeneous solute sorption.

Several researchers have experimented with systems
consisting of an inorganic surfaces coated with humic and fulvic acids
to simulate natural organic coated aquifer material (Murphy, 1990;
Slautman, 1992). Slautman found that the PAH binding properties of
humic and fulvic acids were reduced when the organic material itself
was bound to a synthetic solid. Koc values for anthracene which were
obtained by Murphy, decreased with increasing foc for both peat
humic acid and Suwannee humic acid. The sorption enhancement
due to coated humics was not linear and the anthracene sorption was
most dramatically increased for low foc's. Murphy attributed his
results to heterogeneities in the sorbent phase due. to alternate
configurations of the humics or size exclusion in sites available for
HOC's with increasing foe. The possibility of phase transfer or solute

heterogeneities, however, was not considered.

22

The models developed by Voice and the abundance of data
showing a decrease in K0c with increasing sorbent in terms of both
foe and solids concentration, suggest that solute complexation is a
plausible explanation of observed and natural conditions. This is not
to say that sorbent heterogeneities do not play a role in sorption
phenomena, however, the decreases in Koc with increasing foc or
solids concentration observed in our study and seen in several
published experiments is not described adequately by sorbent

conditions alone.

23

Chapter II: PAH sorption Experiments
2.1 Introduction

The objective of the following chapter is to measure PAH
sorption to Lake Michigan Sediments in laboratory batch partitioning
experiments. The degree of sorption is described as a partitioning

coefficienth defined as follows:

Where C8 is the concentration of the PAH in the sediment and CW is
the concentration of the PAH in water. Lambert (1966, 1967, 1968)
and Karickoff (1983) found that the observed partition coefficient Kp
remained essentially constant over a wide variety of soils and
sediments when it was normalized to the percent organic carbon.
The partition coefficient is normalized to the organic carbon content
of the sediment by dividing Kp by % organic carbon. The organic

carbon partition coefficient is then defined as:
Koc = Cs/(CW * %TOC)

Batch isotherm experiments have the advantage of being
relatively simple to study PAH sorption over a range of compound
concentrations and sediment concentrations. Within this thesis, PAH

partitioning over a range of sediment concentrations from 500 to

24

40,000 mg/l and PAH concentrations at ng/l levels is measured in

batch experiments.

The solid to water ratio has been shown to play an important
role in the evaluation of partition coefficients. The absorption
isotherm can be obtained by two experimental methods. The first
involves keeping the solid to solution ratio constant and varying the
initial amount of solute, while the second involves varying the solid
to solution ratio and keeping the initial solute concentration constant.
The effect of this change in experimental technique on Koc is

evaluated in this Chapter for phenanthrene and benzo-a-pyrene.

Absorption data is modeled by plotting an isotherm. The
isotherm is a graph of the solution equilibrium concentration vs. the
solid phase equilibrium concentration. Many models are available
for fitting absorption data, however, the Freundlich model can be
used for large ranges of solid and solution concentrations and for this
reason it is used to model the PAH sorption data found in our study.

The Freundlich Equation is defined as follows:
Cs = chwl’n
Where, Cs is the equilibrium solid phase concentration

Cw is the equilibrium solution phase concentration

K and 1/n are fitting constants

25

The following objectives will be met in this chapter:

To develop an experimental procedure for PAH batch
sorption studies.

To establish the relationship between solids
concentration and the partitioning of phenanthrene,
fluoranthrene, pyrene, and benzo-a-pyrene.

To determine whether correcting the apparent water
concentration for the amount of PAH bound to aqueous
organic matter as total organic carbon is adequate to
eliminate the dependence that partitioning has on solids
concentration.

To establish any differences in using a constant and
varying sediment batch sorption technique for
phenanthrene and benzo-a-pyrene.

26
2.2 Materials and Methods

2.2.1 Sediment Sampling

Sediment samples were obtained on May 30, 1991 from four
locations offshore Lake Michigan at Muskegon harbor. NOAA
(National Oceanic and Atmospheric Administration) provided
transport and equipment for the sampling trip. A Ponar sampler was
lowered at each location shown on attached figure 2.1 and a grab
sample was collected. The top 1 inch layer of the sediment sample
exhibiting dark, organic color was retained for laboratory

experiments.

The sediment samples were processed by sifting wet through a
200 mesh screen. They were subsequently centrifuged at 5000 rpm
for 1 hour to remove residual water and freeze dried at - 40 ° C for
12 hours. The dry material was pulverized in a mortar and stored at
room temperature for experimentation. An evaluation of the organic
carbon content was completed by the Standard Methods, 1990, solids
determination. Additional samples were tested for TOC by the

Michigan State University Crop and Soil Science laboratory.

Because of the turbulence at the entrance of Muskegon Harbor,
most of the silty organic material was scoured at the shallower
sampling points. This was evident by the organic carbon percentages
as well as visually within each sample. Testing of PAH binding was

only conducted on the samples collected at 100 and 75 meter depths,

27

mg

‘m.
m
a

S

Figure 2.1

’40 1

r

:\_

:imn 3m
.:.\
3:

 

28

since they had the highest organic carbon fractions and therefore
would exhibit the greatest binding effects for PAH's. The organic

carbon content of the samples along with the station location is as

follows:

WM Station motion “at“ long,) % organio Q
100 43°-13.89', 86°-13.23' 5.6
70 43°-l4.11', 86°-30.56' 4.8

2.2.2 Batch Sorption Experiments

A flow diagram of the procedure which was used is shown in
Figure 2.2. Initially, Corex brand #4664, 25 ml centrifuge tubes were
spiked with radiolabelled PAH standards prepared in acetonitrile.
The radiolabelled PAH's obtained from Sigma chemical were purified
by using reversed-phase high pressure liquid chromatography
(HPLC). An example of the fraction chromatogram is shown in figure
2.3. The instrument specifications which were used for this
procedure are included in Appendix 11. Only the fraction
corresponding to the peak at 9 minutes was retained for
experimentation. Selected information regarding the 14C labelled

PAH's is included as Table 2.1.

After the carrier solvent was permitted to evaporate under a
fume hood, about 25 g of purified water (deionized, carbon filtered,
reverse osmosis) with 0.02% NaN3 as an antibacterial agent was

added to each tube. Known quantities of the freeze-dried sediments

Figure 2.2: Procedure Flow Chart

  

25 ml Aqueous Sample/
Sediment Slurry

    
 

 

 

Centrifuge at 12,000
RCF, 10000 RPM

 

 

 

 

 

 

 

 

Supernatant Sediment
Count 5 ml of Rinse through
" Aqueous 0.45 um millipore
filter

 

 

 

 

 

 

l

 

 

 

 

 

 

 

:mpor e titration Dissolve filter in
everse 359 10 ml of LSC Cocktail
Techm ue ,

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I ' Count
Count Fultrate Count Extract Sample
p. Fluorescence Quenching Finally, rinse tube with

 

 

 

20% MeOH, 80% MeClZ
Two washes 5 ml
Count entire rinse

 

H Absorbance at 255

 

 

 

 

 

 

 

29

30

Figure 2.3: Radiolabelled Compound Purification

Integration time 15.00 min
Peak width 1.30 min

Peak sensitivity 2.0%
Minimum area 3000

----Area percent report----

RT Area Area% Peak Name
7.764 3053 0.058
9.908 5066905 96.935
11.173 65093 1.245
12.584 6367 0.122
13.355 85716 1.640

9 Peaks integrated

 

 

 

 

 

 

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u-Overlay Channel B, Min

0.0 Max

31

Table 2.1: Radiolabelled PAH Data

Phen Flrntn Pyrene BAP
Product # 31,528-1 F6147 P4185 B9776
Lot # O49F9271 O61H0151 O61H0152 O8OH9216
Molecular Weight. 178.2 202.3 202.2 . 252.3
Purity" >98% 98% 98% >98%
Activity, mCi/mmol 13.1 S S S S 16.2
Concentration, mCi/ ml --- 1 0.5 6 1
Solvent --- Benzene Benzene Toluene

* determined by radiochromatography

32

were added to each centrifuge tube. The tubes were then covered
with opaque adapters and permitted to equilibrate for 24 hours on a
wrist action shaker to allow dissolution and absorption equilibration

of the PAH spike with the sediment.

A kinetic experiment was initially conducted using pyrene as a
model compound. Pyrene was chosen because it has an intermediate
hydrophobicity in the range of compounds which we studied. A
series of batch systems spiked with pyrene were permitted to
equilibrate over increments of one hour. After this time the same
procedure was followed as previously described. The majority of the
pyrene, approximately 90 %, was absorbed in 2 to 4 hours, reaching
an apparent equilibrium over an extended period (Figure 2.4). Voice
(1983) found in his experiments that an equilibration time of 4 to 6
hours was necessary. Karickoff (1980), hypothesized that sorption
kinetics were described by a short and long term coefficient, the
latter limited by diffusion into the soil matrix. For the purposes of

this study, equilibrium was operationally defined at 24 hours.

Each tube provided a point for the absorption isotherms at
varying sediment concentrations and constant initial spike for the
varying solids isotherms. A range of sediment concentrations from
about 500 mg/l to 40,000 mg/l was studied. For the constant solids
isotherm procedure, equal amounts of sediments were used in each
tube and the concentration of PAH was varied. After the 24-hour
equilibration time, the tubes were centrifuged at 12,000 RCF, (10,000

RPM) for 2 hours to separate solid and liquid phases. Five grams of

33

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34

the supernatant was drawn off the top of each tube and counted with
10 ml of LSC cocktail for 10 minutes. Three counts were taken for
each sample and average values are reported. The instrument
specifications which were used for this experiment are included in

Appendix II.

The remainder of the supernatant in the phenanthrene and
benzo-a-pyrene experiments was used for reverse phase separation
and fluorescence quenching procedures. These techniques were
described in detail in Chapter 111. After separating the supernatant,
the residual solids in each tube were flushed with DI water through
Millipore 0.45 um filters. The filters with retained solids were then
dissolved in 10 ml of LSC cocktail. The vials were shaken vigorously-
-2 to 3 minutes and allowed to set for 12 hours. Subsequently, each
vial was analyzed on the Beckman LSC counter for 10 minutes to
determine 14C activity. The centrifuge tubes were then rinsed with
10 m1 of MeCL2 (in two 5 ml washes) to remove glass sorbed PAH.
The entire rinse was combined with 5 ml of cocktail and counted for

10 minutes.

Tables 2.2 through 2.6 show the data which was generated
using the batch isotherm procedure. The tables are spreadsheets of
the calculation of solid concentration, PAH water concentration, and
PAH concentration. Additionally, the PAH sediment concentration is
adjusted based on the recovery efficiency. This calculation is
possible in the procedure since the total initial activity of the spike is

known and the glassware sorbed concentration, water concentration

35

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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40

and sediment concentration are measured. If these three measured
quantities did not equal the total initial spike, the sediment
concentration was increased correspondingly. The material balance
recovery then indicates the sediment extraction procedure.
Appendix 4 includes a key to tables 2.2 through 2.6 which explains

how the column calculations were made.

2.3 Results and Discussion: Solid Phase Sorption

In some cases, the aqueous phase measurement of PAH was
close to background levels. In order to test whether the data was
significantly above background, an hypothesis test was completed

under the following assumptions:

1. Ho: u< or = O

2. Ha: u>O

3. Test Statistic: Student t, t = (x-u)/(s/sqrt n)
4. Alpha = 0.05

5. Critical value @ n=3, 2 degrees of freedom
6. Reject H0 if computed D or = 2.92

Based on this test, only one data point was not significantly
greater than a background of O dpm. The results are included in
Table 2.7. The data on background counts is included in Appendix
five. Since the data points were background corrected, the

hypothesis test compared the data to zero.

41

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Figure 2.5 is an example of the K0c values which were obtained
for the varying sediment isotherm procedure. As shown, the K0c
value for fluoranthene exhibited a logarithmic decrease with
increasing sediment concentrations. The results observed are similar
to the work completed by Voice (1983) for several solutes using
Lake Michigan sediment as the binding phase. Generally, a one order
decrease in the partitioning coefficient is observed with a two order
increase in solids concentration. Voice, 1983, noted that at very high
solids concentrations, the Koc appears to reach a limiting value. This
is not apparent in the range of concentrations that were used in this
study. Use of the Freundlich isotherm model, although appropriate
for fitting the PAH sorption data, would not be appropriate for
identifying a limiting Koc value because of the exponential form of

the equation.

For the procedure which we used, it was necessary to identify
solid phase recoveries and correct the data for extraction
inefficiencies. Figure 2.6 is an example of the recovery which was
obtained for fluoranthene. It is a plot of the material balance %
recovery vs. sediment concentration. The values also appear in table
2.3. Generally, the recoveries decreased with increasing solids in the
system. Karickhoff (1980), observed that the ease of extraction of
the sorbed phase was dependent on the equilibration time. Longer
equilibration times resulted in reduced recoveries. These
observations led to the conclusion that sorption continued over time
from the surface of the soil into the soil matrix. It is suspected in our

study that decreasing extraction efficiency related to the increase in

43

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45

organic material which was available to bind the pollutants more

fighdy.

As noted, the observed dependency of Koc on the solids
concentration may be the result of binding to solution phase DOM.

Several researchers have suggested the use of a corrected apparent

K0c which can be determined from calculations similar to the

following equation (Hoke and Giesy 1992, Gschwend and Wu 1985):

Corrected Koc = Cs/(Cw - K doc*Cw*DOC)

Where K doc = partitioning coefficient to DOC

DOC = Dissolved Organic Carbon

The intent of the correction is to make a distinction between the

"free" and "bound" forms of the HOC. The measurement of Cw does

not make this distinction. The measured value is the total HOC in the
water. By assuming that Kdoc= Koc, the value of the "bound"

contaminant in solution can be estimated and subtracted from the

measure total to obtain "free" HOC.

In order to assess this correction for use with our data, we

applied it to the apparent partitioning data for fluoranthene. Kdoc

was assumed to equal K0c which is defined as a function of K0W from

the approximation (Lake 1990):

Loglo K0c = 0.00028 + O.983*Log10 K0c

46
As shown in Figure 2.7, the K0c values are increased as expected due

to the correction which was applied to the measured aqueous phase
concentration. However, the decrease in Koc which is observed over
the range of solid concentrations is still present in the corrected
values. The correction equations which were implemented by Hoke
(1992) do not correct for the solid concentration effect which was

observed in this study.

Figure 2.8 shows varying solid partitioning coefficients for all
of the PAH compounds which were used in Our study. As indicated
in the figure, the decrease in apparent K0c with increasing solid
concentration is observed for each .PAH compound. Generally, the
effect is the greatest for the compounds of higher hydrophobicity.
This is apparent in the slope determined by logarithmic regression
for each series of data. It increases (negatively) for the more

hydrophobic compounds.

Considering the hypothesis suggested by Voice (1983), these
results are expected since DOC binding would be the greatest for

increasing hydrophobicity. In our data set, benzo-a-pyrene, as

expected, exhibited the greatest decrease in Koc over the

experimental range of solid concentrations. Voice (1983)
conceptualized a solute complexation model to describe these

observations. The model relied on two major occurrences:

1. Phase' transfer of solute complexing material

(DOC) from solids to the aqueous phase.

47

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2. Heterogeneous solute in the aqueous phase made

up of "free" and "DOC-bound" constituents.

Under these hypotheses, a sorption isotherm resulting from constant
and varying solids techniques would produce a graph similar to the
hypothetical plot shown in Figure 2.9. Data shoWing the absorption
of humic and fulvic acids (Voice 1983) on activated carbon indicated
behavior similar to that shown in Figure 2.9. It was suggested that
these results are examples of heterogeneous solute absorption where
the analytical technique does not distinguish between the various

components in solution.

In order to assess the suggestion of heterogeneous solute
sorption, varying and constant sediment isotherms were constructed
for phenanthrene and benzo-a-pyrene to model both relatively low
and high hydrophobicity compounds. The Freundlich isotherm was
used to model the data. Figure 2.10 shows the results obtained using
phenanthrene. As indicated, separate logarithmic regressions on the

constant and varying solids data did yield different slopes, however

mfi

SOLID PHRSE CONCENTRRTION (NC/G)

 

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Figure 2.9: Effect of Isotherm Procedure on Observed
Partitioning for a Heterogeneous Solute

51

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the difference in the results was not as evident as the difference
observed using benzo-a-pyrene. For phenanthrene which is less
hydrophobic than benzo-a-pyrene, the data may suggest that little
binding occurred in the solution phase, thus there is little difference

in the constant and varying sediment concentration isotherms.

Figure 2.11 shows the results obtained using benzo-a-pyrene.
As indicated, the isotherms obtained using the constant and varying
solid techniques were strikingly different. The BAP experiment
incorporated three constant solids isotherms including 4,000, 10,000,
and 20,000 mg/l solids concentrations and two varying solids
isotherms in which different initial concentrations were spiked. The
constant solids isotherms are parallel on a C; vs CW plot. Additionally,
the Freundlich sorption intensity coefficient for constant solid data is
less than 1. Logarithmic regressions on the varying solids isotherms,
however result in Freundlich intensity constants greater than 1,

consistent with Voice's (1983) results.

The general form of the data shown in Figure 2.11 is consistent
with results obtained for humic and fulvic acid sorption to organic
carbon using the varying sorbent and varying initial concentration
techniques (Voice, 1983). Simple linear partitioning would have
modeled the data as a straight line and the slope would be used to
predict the partition coefficient. However, as noted by Voice and
paralleled in this study, our results suggest that a full description of

the data requires at least one additional variable, C0 or S, to describe

equilibrium conditions. Additionally, extrapolation of data from

53

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experimental to field conditions without designating experimental

design conditions is questionable.

2.4 Conclusions: PAH Sorption Experiments

The relationship between solid concentration and Koc is evident
in figures 2.5 and 2.8. As the concentration of solids in the system
increases, the partitioning coefficient Koc decreases exponentially.
For the range of PAH's studied, the effect is increased for the more
hydrophobic compounds. The following summary identifies the

Range of Koc values which were found for each PAH studied.

(mg/l)
Phenanthrene 4.3 - 4.6 190 - 33,000
Fluoranthrene 4.2 - 5.5 228 - 40,000
Pyrene 5.0 - 5.4 551 - 27,306
Benzo-a-pyrene 4.5 - 6.6 305 - 37,051

By varying the conditions needed in the batch sorption studies
by using a constant and varying solids technique, the data produced
considerably different isotherms for benzo-a-pyrene. The effect was
not as readily apparent in the phenanthrene data. For BAP the
following data summarizes the Freundlich parameters which

described BAP sorption.

55

W. W W
(mg/1)
4,000 3.33e4 0.88
10,000 2.82e4 0.83
20,000 1.89e4 0.82
I .. 1 2511 s .1 ’
(ppb)
10 7.21e-7 3.60
50' 4.62e-4 2.34

As previously noted, the Freundlich K is an indicator of the
amount of absorption while l/n is an indicator of absorption
intensity. For the varying solids technique, l/n remained relatively
unchanged while the Freundlich K decreased with increasing solids.
for the constant solids technique, K increased while 11 decreased with

increasing initial BAP spike.

The significance of this data is that simple predictions of BAP
concentration in one phase of the system, either solid or water, by
knowing the partition coefficient should be used with caution since,
the results depend on isotherm procedure. Additionally, as noted by
Figure 2.7, correcting the observed partition coefficient value by
using a technique similar to Gschwend and Wu‘s or Hoke and Giesy
may not be adequate for data which is generated by techniques

similar to ours.

56

Chapter 3: Measurement of Phenanthrene and Benzo-a-
pyrene binding to Dissolved Organic Carbon from
Lake Michigan Sediments

3.1 Introduction

A number of researchers have shown that hydrophobic organic
compounds (HOCs) exist in "bound" forms associated with either
dissolved or colloidal organic matter. Chiou et a1. (19) showed that
the water solubility of HOC‘s was enhanced by humic and fulvic acid
addition. Compounds with high water solubility exhibited no
detectable solubility enhancement, however, more hydrophobic
compounds such as DDT showed significant solubility enhancement.
Other researchers have demonstrated the ability of organic colloids
to alter the subsurface transport of contaminants (Schwarzenbach et.
al., 1981; McCarthy et. al., 1989; Magee et. al., 1991, Bertsch, et. al.,
1993) The role of particulate organic matter in decreasing
accumulation of polynuclear aromatic hydrocarbons in aquatic biota
has also been shown (McCarthy, 1983). Other researchers have
identified the binding of HOC's as a reason for decreasing bio-

availability of HOC's (Geisey, 1981).

In order to evaluate the extent of binding of PAH‘s to dissolved
organic carbon, it is necessary to measure the "free" and "bound"
distribution of the compound as well as the amount of binding
material in solution. The objective of this chapter is to describe two
experimental techniques, fluorescence quenching and reverse phase
separation, which have been developed by researchers for measuring

PAH binding to dissolved organic carbon. Additionally, the chapter

57

describes the experiments which .were used to measure
phenanthrene and benzo-a-pyrene binding to dissolved organic

carbon from Lake Michigan Sediments.

Fluorescence quenching is a technique originally presented by
Gauthier (1986) for measuring the equilibrium constant which
describes the interaction that hydrophobic fluorescent compounds
have with dissolved organic carbon. The procedure is based on the
observation that the fluorescence of the hydrophobic compound
decreases proportionally to its association with organic carbon. The
organic carbon inhibits the fluorescence of PAH's when it is present
in solution. It is believed that this is due to binding with the PAH
molecules. One researcher describes the process as a cage-like
structure around the PAH which absorbs the energy normally

dissipated as fluorescence (Morra, 1990).

Fluorescence quenching has continued to be developed through
other researchers including Gschwend and Backhus (1990), Morra, et.
al. (1990), and Slautman (1992). The binding of hydrophobic
chemicals to organic carbon is important in assessing the fate and
transport of pollutants in environmental systems. The fluorescence
quenching technique has been used to describe binding of PAH to
organic carbon to assess the colloidal transport of PAH's in

groundwater (Backhus and Gschwend, 1990; Magee, 1991)

Reverse-phase separation was used by Landrum, et. al., (1984)
to measure pollutant binding to dissolved organic carbon by

physically separating the organic carbon bound and free phase of

58

pollutants at equilibrium. It was developed from the observation
that humic-bound benzo-a-pyrene and other PAHs could be
separated from the "freely dissolved" benzo-a-pyrene using XAD-4

resins (Landrum and Giesy, 1981).

3.2 Quantifying DOC Released from Lake MI Sediments

In order to quantify PAH distribution in the aqueous phase, it
“is necessary to quantify the sorbent transfer of solute binding
material (in our case DOC) to solution. Voice (1983) noted the
difficulties associated with defining the components of the aqueous
phase. Experimental techniques are hindered by the fact that
complete phase separation is difficult if not impossible to achieve.
Under these conditions, operational definitions for "free" and "bound"

compound must be set forth in experimental techniques.

Eadie (1990) conducted a study of HOC distribution between
particle bound, dissolved organic matter bound and freely dissolved
constituents. Operational definitions were achieved by glass fiber
filtration and reverse phase separation using SepPakr cartridges. His
results indicated that for most compounds including benzo-a-pyrene,
the free fraction was dominate. However, these studies were
undertaken for natural water column conditions 1-5 ppm TOC and

0.2 to 5 ppm of total suspended matter.

59

In our experiments it was necessary to correlate TOC to some
other measurable parameter since radiolabelled chemicals were used
in the sorption experiments. The following experiments describe the

correlation which was developed to quantify the aqueous DOC.

3.2.1 Materials and Methods

Batch bottle point experiments were set up for the DOC transfer
measurement similar to the experiments used for PAH sorption in
chapter 1. A known quantity of sediment was placed in a 25 ml
centrifuge tube and combined with a known quantity of deionized,
reverse osmosis, and filtered water. The mixture was shaken on a
wrist action shaker for 24 hours to allow equilibrium to be achieved.
Initially, a kinetic study was performed by adding the same amount
of sediment to several tubes and equilibrating for varying amounts

of time.

For the purposes of this study, the sediment was separated
from solution by centrifugation at 12,000 RCF for 2 hours. Residual
organic matter in solution both in the form of micro-particulates and
dissolved material was defined as the sorbing phase resulting from
sediment transfer. The instrument specifications which were used

for this study are included in Appendix II.

The quantification of the amount of total organic matter

transferred from the sediment to the solution was accomplished

60

through a series of experiments. After solid separation by
centrifugation, a portion of the supernatant was used to measure
absorbance at 255 nm. Additional portions of the supernatant were
used to evaluate the total organic carbon, TOC, by using a Shimadzu
TOC analyzer. A separate experiment was conducted to evaluate
turbidity in several of the samples by removing a 15 ml portion of

the water from the tube and measuring on a turbidity meter.

3.2.2 Results and Discussion

Kinetics of TOC desorption from freeze dried Lake Michigan
Sediments were determined to be relatively fast. As shown in figure
3.1, greater than 80 % of the material desorbed in less than 5 hours.
The remainder of the DOC slowly entered solution over an extended
period (30 hours in this study). These kinetics, however, are slower
than the time required for binding of PAH's to dissolved organic
material as modeled by humic and fulvic acids using fluorescence

quenching (Gschwend and Backhus 1990, Gauthier 1986, Slautman
1992).

As shown in figure 3.2, the absorbance values correlated to the
sediment concentration using a logarithmic regression. The
regression equation, y = a * Xb, found to provide the best fit for the
data, was the same form of equation used by Voice relating TOC to
sediment concentration. Approximately 94 % of the scatter in the

data is described by the logarithmic regression. The deviation from

61

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linearity is possibly the result of readsorption by organic material at
the higher solids concentration or alternately, an approach to

solubility limits of the organics.

Figure 3.3 shows that TOC can be determined as a function of
absorbance. The correlation that we found was subsequently used in
the DOC binding experiments to evaluate the amount of solute

binding material in solution at equilibrium as TOC.

An additional measurement was made to determine solution
turbidity. This was done since other researchers have identified that
incomplete phase separation of dissolved and particulate material

can affect the measurement of Kdoc values for HOC's (Gschwend and

Wu 1985, Voice 1985).

Figure 3.4 shows the results obtained by correlating TOC and
turbidity to absorbance. Under ideal assumptions, turbidity, defined
as a- measure of the light scattering properties of a solution, measures
particulate material. Absorbance, however, is a measure of the
absorption of light at specific wavelengths and relates to dissolved
material. The absorbance readings in our data from about 0.05 to 0.5
relate to a range in TOC of about 5 to 45 mg/l. This range in
absorbance allows much more measurement ability than the 15 to 25

NTU range on a turbidity instrument.

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The regression:
TOC (mg/l) = 1.5522 + 73.064 * Abs R2 = 0.825

was subsequently used in the study to estimate DOC values from

absorbance.

3.3 Fluorescence Quenching

Fluorescence .quenching has been used by many researchers to
study PAH partitioning to aqueous-phase organic material (Gschwend
and Backhus, 1990; Gauthier, 1986; Slautman, 1992). Its advantage
is that a physical separation of "free" and organic carbon "bound"
components in solution is not necessary. Hence recovery and
separation efficiencies do not hinder its use. Fluorescence quenching
is founded on the assumption that the measured fluorescence
intensity is decreased in proportion to the fluorescent compound's
binding to a quencher (Gauthier, 1986). In natural waters, the

principal quencher is believed to be dissolved organic carbon.

Three mechanisms of fluorescence quenching are defined in the
literature. Apparent quenching, referred to as the inner filter effect
is due to attenuation of light at the excitation wavelength and
absorption of light at the emission wavelength during a fluorescence
measurement. Additionally, the fluorescent molecule can interact
with a quencher by either association or collision mechanisms. The

first is referred to as static quenching and the latter as dynamic

67

quenching (Gauthier 1986). All of the mechanisms may be present
when measuring the decrease in fluorescence associated with a
quencher. The mechanisms involved in binding of organic carbon

with PAH‘s is static and dynamic quenching.

Gauthier's method makes use of a fluorescence correction
coefficient which defines the proportion of exciting and emitting light
which is lost through absorption. Any remaining losses in the
presence of the quencher are assumed to result from interactions
with the quencher, either by binding deactivation (static quenching)
or by collisional de-excitation (dynamic quenching) of the fluorescent

molecule.

The procedure relies on the assumption that the decreases in
fluorescence which are observed in the presence of organic material
are directly proportional to the extent of binding. A simple
derivation of this interaction as a conditional equilibrium equation is
included in Appendix 1. The Stern-Volmer equation is an expression
which relates the ratio of fluorescence in the presence to
fluorescence in the absence of a quencher with the partitioning
coefficient, Kdoc, and the concentration of quencher (DOC) in the

sample.
Fo/F = 1 + Kdoc * DOC

Corrections for absorption of the excitation and emission

radiation are obtained by measuring absorption at the fluorescence

68

excitation and emission wavelengths. Miller, 1981, has derived the
correction factor for perpendicular cell geometry. A summary of this
derivation is also included in Appendix I. The decrease in
fluorescence intensity after the correction has been applied is due to
interaction with a quencher. Miller reports that for a correction
factor greater than 1.8, the correction is increasingly inaccurate. Due
to the relatively low absorbance values for the DOC used in our

experiments, this value was not exceeded.

Gschwend and Backhus (1990) identified two possible
problems to the Gauthier procedure. The first suggested that the
DOM-PAH complex may fluoresce. The second identified the need to
correct for glassware sorption when compounds with high
hydrophobicity are used. Slautman (1992), experimented with these
ideas for a number of PAH compounds absorbing to humic and fulvic
acids. He noted that the quantum efficiency of the PAH-DOM
complex approached zero for all the PAH's that were studied.
Additionally, he found that the technique of Gauthier was

satisfactory for PAH‘s of moderate hydrophobicity.

In order to correct for the fluorescence of the DOM-PAH
complex, the following equation can be developed (Gschwend and

Backhus, 1990):

Fo/F = (1 + o*Kdoc*DOC)/(l + K doc*DOC)

where, o = quantum yield of PAH—DOM complex

69

This equation is essentially a modified Stern-Volmer expression with

the Fo/F ratio defined as follows:
Fo/F = [PAlem/i [PAmfmmflPAmbml

Additionally, Gschwend and Backhus, (1990) note that by measuring
the fluorescence of a sample over time, glassware sorption can be

eliminated by extrapolating to time zero.

3.3.] Methods and Materials for Fluorescence Quenching
Measurements of Phenanthrene and Benzo-a-pyrene

For the purposes of this study, the phenanthrene binding
coefficients to dissolved organic carbon from Lake Michigan
sediments were estimated using Gauthier's technique. It was
assumed that little or no glassware sorption took place. Slautman
(1992) indicates that this approach is valid for the moderately
hydrophobic PAH's. The technique for benzo-a-pyrene, however,
implemented the procedure developed by Backhus and Gschwend

(1990) to correct for glassware sorption.

The instrument specifications and settings are included in
appendix ll. For measurement of phenanthrene, a Perkin Elmer LS
50 spectrafluorimeter with a xenon arc lamp for the source was used.
limitation and emission wavelengths were set at 255 nm and 365 nm
respectively since a high intensity peak occurred at these

wavelengths. The excitation and emission slits were both set at 5 nm

70

in order to maintain the resolution of the peak while allowing
maximum intensity readings. Activity of 14C in the samples was
measured on a Beckman liquid scintillation counter. Absorbances

were measured on a Shimadzu UV spectrophotometer.

The samples which were measured in this portion of the study
came from the sediment sorption studies which were completed in
chapter 1. The initial step in the procedure was to estimate the 14C
activity and the fluorescence intensity of the blank sample in order
to relate the two measurements. ‘This procedure was necessary to
estimate the total PAH in solution by fluorescence in the absence of
the quencher. Accordingly, the disintegrations per minute of 1“C
activity and the fluorescence of each sample was measured on a
small portion of aqueous sample which had been separated from the

sediments by centrifuging.

The sample was withdrawn from the centrifuge tubes by
disposable glass pipettes and placed in a quartz cuvette. Initial
experiments were conducted to identify the appr0priate excitation
and emission wavelengths for the fluorescence measurements. The
goal was to choose wavelengths which resulted in an intensity peak

from the PAH fluorescence. Figure 3.5 demonstrates the fluorescence

71

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72

intensity of phenanthrene over a range of excitation wavelengths
from 200 to 350 nm and emission wavelengths from 300 to 500 nm.
The phenanthrene peak at 250 nm excitation and 365 nm emission

was chosen for the measurement.

Similar experiments were conducted for benzo-a-pyrene and
an emission and excitation wavelength of 380 and 445 nm were
chosen respectively. The fluorescence measurements of the benzo-a-
pyrene solutions were measured over a time period of 15 minutes.
Time zero was determined at the point of filling the cuvette with the
sample. Figure 3.6 shows an example of the data from this
procedure. The measured fluorescence was determined by
extrapolating the data by linear regression to time zero and reading

the intensity value.

The absorbance of each sample was measured at both the
fluorescence excitation and emission wavelengths to be used for the
fluorescence correction factor. Also, the absorbance of the sample
was measured at 255 nm to correlate the total organic carbon from

Figure 3.3.

In the fluorescence measurement of phenanthrene, several
samples had concentrations high enough to exceed the instrument
range. These samples were diluted by adding a known amount of
distilled water to the sample cuvette. A dilution factor was obtained
by taking the sample weight divided by the sample plus dilution

water weight.

73

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74

About five ml of additional sample was taken from each tube
and placed in liquid scintillation vials. The weight of each sample
was determined to the nearest tenth of a gram by tarring the vial
and measuring the sample weight. Ten ml of high performance
liquid scintillation cocktail was then added to each vial. The vials
were capped, shaken and counted for three ten—minute repetitions

on the Beckman liquid scintillation counter.

3.3.2 Results and Discussion: Calculation of Kdoc

Table 3.1 shows the data reduction and calculations which were
used for the Kdoc of phenanthrene. The 14C activity of the aqueous
sample is shown in column 2. The fluorescence intensity in the
absence of a quencher was estimated by multiplying the 1“C aqueous
activity by the equivalent fluorescence intensity shown at the top of
the table. This calculation was necessary to determine F0. The
fluorescence intensity estimating the amount of free compound in
the samples is shown in column four. The free fluorescence was
multiplied by the dilution factor where necessary to determine the
actual sample fluorescence. The value for the actual fluorescence

was entered as F total.

The absorbances at the emission and excitation wavelengths
were then used to estimate the factor which corrects for the inner
filter effect. The full derivation of this equation is included in

Appendix 1. As shown, the corrected "free" fluorescence is obtained

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76

be multiplying the correction factor by F total. Knowing F0 and the

corrected fluorescence, F, the Stern Volmer equation could be

evaluated.

The procedure for determining the Stern-Volmer constant is
also included in appendix 1. In our experiments, this constant is
equal to the binding constant when the dissolved organic carbon
concentration is substituted in the Stern-Volmer expression. For
these experiments, the dissolved organic carbon content is estimated
by substituting the absorbance measured at 255 nm into the

regression equation shown in Figure 3.3.

Table 3.2 shows the data reduction for benzo-a-pyrene. The
procedure was similar to phenanthrene except that the fluorescence
at time zero was extrapolated from fluorescence measurements
taken over fifteen minutes. The benzo-a-pyrene timed fluorescence

data is included in appendix 1.

Referring to Table 3.1, the measured 14C activity for the 11
phenanthrene spiked samples is consistent with the varying and
constant sediment isotherm procedures discussed in Chapter 1. The
first five samples represent constant sediment trials with varying
phenanthrene spike. Accordingly, the measured disintegrations per
minute per liter of sample increased with increasing spike. Ftotal
after adjustment for dilution also increases over the five samples

with increasing spike. Column 12 demonstrates that the estimated

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78

TOC values for the constant sediment procedure ranged from 9.5 to

12.1, indicating a range of variability of 2.6 mg/l of TOC

Similarly for the varying sediment procedure, the estimated
TOC increased with increasing sediment concentration. Accordingly,
the measured fluorescence of the constant phenanthrene spike
decreased for samples 6 through 11. This decrease was due to the
three mechanisms described previously, including apparent, static
and dynamic quenching. After the correction for absorbance
measurements at 250 and 365 nm (apparent quenching), column 10
shows the corrected fluorescence representing the concentration of

free phenanthrene in each sample.

Referring to Table 3.2, the measured l4C activity of the benzo-
a-pyrene and the fluorescence values were consistent with the
constant and varying sediment experiments. Column 5 shows the 14C
activity in the aqueous portion of the sediment water mix. Samples
1 through 5 are varying sediment experiments with constant benzo-
a-pyrene spike. The TOC values estimated in column 15 increased
with increasing sediment concentration and F0 decreased. Samples 6
through 11, 12 through 14, and 17 through 19 represent constant
sediment procedures which resulted in TOC values on average of 14,

8.5 and 22.3 mg/l TOC respectively.

79

For the benzo-a-pyrene experiments, the dilution factor and
correction factor were both one for all samples. This occurred
because the undiluted samples were within the measurement range
of the fluorimeter (less than 1000 intensity units). Additionally, the
absorbance at the emission and excitation wavelengths of 380 nm
and 445 nm respectively, was negligible, indicating that all

quenching was either static or dynamic and not apparent quenching.

As shown by Backhus and Gschwend (1990), the fluorescence
measurement for‘ extensively hydrophobic compounds must be
corrected for glass absorption. A linear regression was applied to
extrapolate the measured fluorescence to time zero. The
fluorescence at time zero was the value tabulated in the spreadsheet,
Table 3.2. Apparent from the Figure 3.6 is the fact that the
measured fluorescence changed little over the 15 minute time period

indicating little absorption to the glassware on that time scale.

3.3.3 Conclusions: Fluorescence Quenching

In both the phenanthrene and benzo-a-pyrene data, using the

results for Fo/F, Kdoc was calculated from the Stern-Volmer

expression by the formula:

The Kdoc values which were calculated for phenanthrene and

benzo-a-pyrene varied widely with sediment concentration. This

80

variation is demonstrated in Figure 3.7 and 3.8. The range of Kdoc

values obtained using the fluorescence technique is shown below.

BAH MW, 1.22.1919,
(mg/l)

Phenanthrene 5.20 - 25.60 1.6 - 3.6

Benzo-a-pyrene 5.02 - 25.74 3.7 - 6.0

For both phenanthrene and benzo-a-pyrene, the Kdoc calculated
by fluorescence quenching shows a decrease with increasing sorbent
concentration. Although the dependence of Koc on sorbent
concentration has been shown by a variety of researchers, the
relationship of Kdoc with changing sorbent concentration has not been
well documented. This apparent dependence on solids concentration
or dissolved organic matter concentration has been noted by other
researchers. McCarthy and Jimenez, 1985, found that the binding

affinity of benzo-a-pyrene, anthracene and

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benzanthracene decreased with increasing dissolved humic material.

Landrum, 1984, found similar results for benzo-a-pyrene and

anthracene.

3.4 Reverse Phase Separation

The reverse phase separation method for determining pollutant
binding to dissolved organic carbon was developed by Landrum et.
al. (1984). The organic carbon bound pollutant was separated from
”freely dissolved" pollutant by using a Sep-Pak C-l8 cartridge.
Organic carbon bound pollutant passed through, while the unbound
pollutants were retained by the column. The partition coefficient
was calculated as (grams of pollutant bound/grams of organic

carbon)/(grams of pollutant freely dissolved/milliliter).

This technique was developed from the observation that an
anomalous breakthrough of benzo a pyrene occurred during
concentration with Amberlite XAD-4 resin from aqueous solution
(Landrum and Giesy, 1981). These resins among many absorbing
materials were used to concentrate pollutants at trace concentrations
within environmental samples. The breakthrough of the pollutants
was determined to be the result of binding to dissolved minerals and

organics.

In the experiments with benzo-a-pyrene using the reverse

phase column (Landrum, 1984), it was noted that minimal contact

84

time between the column and humic-pollutant complex minimized
the potential for pollutaanOC complex dissociation because of
column interactions. The procedure used a flow-rate of about 12
ml/min. Where breakthrough of free compound occurred in the
absence of DOC, an empirical correction was used. It is thought that
pollutants bound to dissolved organic matter pass through the
cartridge at pH sufficiently high (greater than 5) to polarize the

humic substances.

In the following experiments, we have used EmporeR extraction
disks as an alternate sorbent to study reverse phase separation of
free and bound phenanthrene and benzo-a-pyrene. The filter disks,
enmeshed in special fibrils, are made of C-18 moiety bonded
particles. A filtration apparatus, consisting of a vacuum flask
stoppered with a glass frit and filter clamp and attached to a vacuum

meter and pump were then used to perform the extractions.

It is suspected that the C-18 coated disk will eliminate the
potential for erroneous data due to short circuiting. Short circuiting
was noted to be a problem for some pollutants using the Sep-Pak
column even at low flow conditions. As previously noted a correction
was applied to the "bound" concentration to adjust for the amount of
"free" compound passing through the column (Landrum, 1984).
Additionally, the enhanced contact provided by the even particle
distribution within the EmporeR disk should permit much higher flow

rates and reduce the potential desorption of the "bound"

85

contaminant. This condition of increasing bound contaminant with

increasing flow was also noted by Landrum, 1984.
3.4.1 Materials and Methods: EmporeR Disk Extraction

The initial experiment was designed to determine whether
breakthrough of a solution of 14C labelled pyrene would occur at high
flow rates. The vacuum filter apparatus described above was
connected to a vacuum source metered by a Vacu-trol pressure
gauge. A range of pressures from 200 to 600 mm of Hg were
supplied to filter 10 ml of sample prepared at about 10,000 dpm.
The disks were pre-conditioned using the following procedure as

described by the manufacturer:

1. Flush with 10 ml MeC12
2. Flush with 10 ml MeOH
3. Flush with 10 ml D1

The elution solvent was MeC12 and it was used initially to flush
contaminants from the disk. Methanol was then flushed through to
remove the MeC12 and prepare the disk for a DI water flush. After
rinsing the disk with DI water in the final step, the disk was not
allowed to dry prior to extracting the samples. For each sample, the

procedure was repeated with a new disk.

Immediately following the preconditioning step while a

meniscus of DI water was still visible, 10 ml of sample were filtered

86

through the EmporeR disk at varying flow rates, corresponding to
varying pressure. The disks were filtered until dry, and the
supernatant was combined with 5 ml of LSC cocktail and counted
using the method described in Appendix II. Subsequently, 10 ml of
a MeC12/MeOH mixture in a 80/20 ratio was used to extract the disk.
The extractant was transferred to a scintillation vial, combined with
5 ml of LSC cocktail and counted for 1“C activity.. After the
extraction, the disk itself was also transferred to an LSC vial,

combined with 5 ml of LSC cocktail and counted.

Figure 3.9 identifies the flowrate/pressure calibration curve
determined for the EmporeR disks using DI water. This curve was
completed to approximate the flow rate which corresponded to a

given pressure.

For the breakthrough experiment, the flow rates were varied
between 6 to 20 ml/minute by adjusting the pressure in order to
determine if breakthrough would occur. Over this pressure range,
however, no significant change occurred. Greater than 99% of the

pyrene was absorbed to the disk at all pressures which were tested.

With these results, a pressure of 400 mm Hg was chosen to
extract the DOM complexed samples using the procedure described
above. The "bound" constituent was determined .by counting the 14C
activity of the filtrate, while the "free" constituent was determined

by extraction absorbed PAH from the disk and counting the 14C

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activity. The following equation was used to determine the

partitioning coefficient to aqueous DOM:

Where DOC was estimated using the correlation shown in Figure 14.
Extraction efficiencies were necessary to adjust the concentration of
the "free" compound because not all of the absorbed PAH could be

removed from the disk.

The following steps detail our laboratory experiments:

1. Ten ml of water sample was removed from the PAH
batch sorption experiments and filtered through the
EmporeR disk at 15 ml/min, 400 mm Hg.

2. The filtrate was combined with 5 ml of LSC cocktail
and counted using the method described in appendix
II.

3. After filtering the disk to dryness, the disk was
extracted using 10 ml of 80/20, MeC12/MeOH mixture.
The extractant was combined with 5 ml of LSC cocktail

and counted.

4. The disk was then combined with 5 ml of LSC cocktail
and counted.

5. The "free" measurement obtained from the disk
extraction was then adjusted to reflect the extraction
efficiency.

6. DOC was estimated using absorbance at 255 and Cbound

was normalized to the organic carbon.
7' Kdoc = C bound, C free

89

3.4.2 Results and Discussion: Emporer Disk Extraction

Tables 3.3 and 3.4 show the data reduction which was used for
the EmporeR disk extraction method. The supernatant was the
material passing through the disk. It represented the organic carbon
bound PAH. The elution of the disk itself using MeC12 was counted
for the free compound measurement. Additionally, the disk itself
was placed in scintillation cocktail and counted because the

extraction was not fully efficient.

Since the total aqueous 14C activity was previously measured in
the PAH sorption studies, a recovery estimate was calculated by
adding the activity from the supernatant, the eluant, and the disk,
and dividing the sum by the total activity. The recovery percentage
is shown in the tables. It was assumed the estimated "free" activity
determined from the disk extraction should be adjusted by the
recovery efficiency since its value was measured directly by the
Emporer extraction. The value was entered as adjusted "free"

concentration in the tables.

Knowing the activity of the "bound" portion which passed
through the disk and the "free" concentration which was extracted
from the disk, a partitioning coefficient was calculated from the

following expression:

Kdoc = [PAHmemdn [PAHlfm’kDOC]

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Figures 3.7 and 3.8 show the Kdoc values determined from the
above expression and plotted as a function of solids concentration.
As apparent in these figures, the Kdoc for phenanthrene did not
exhibit a dependence on solid concentration while the Kdoc for benzo-
a-pyrene decreased with increasing solids in the system. This
apparent dependence on solids concentration or dissolved organic
matter concentration has been noted by other researchers. McCarthy
and Jimenez, 1985, found that the binding affinity of benzo-a-
pyrene, anthracene and benzanthracene decreased with increasing
dissolved humic material. Landrum, 1984, found similar results for

benzo-a-pyrene and anthracene.

3.4.3 Conclusions: EmporeR Disk Extraction

A summary of the Kdoc values obtained using the Empore

Extraction technique appears in the following table:

BAH Wanna. 108 Km;
(mg/l)

Phenanthrene 2.42 - 30.15 3.1 - 3.3

Benzo-a-pyrene 5.02 - 25.74 3.9 - 4.9

To demonstrate a correction technique for the solid phase K0c values
which were obtained in Chapter 1, the Kdoc values which were
measured by reverse phase were applied to the benzo-a-pyrene

sorption data using the following equation:

93

Koc = (Cs + C"bound")/C"free"

This correction includes the amount bound in solution as part
of the total amount bound to the sediments and includes only the
”free" concentration in the aqueous term. Figure 3.10 shows that the
corrected K0c value is higher because of the correction, however, the
corrected K0c still shows a decreasing trend with increasing solids

concentration.

The significance of this data is that we have demonstrated the

range of Kdoc values which may be obtained by the fluorescence

quenching technique and the reverse technique. It also

demonstrates that. measured values of Kdoc using current techniques

are not sufficient to describe the dependence that Kdoc has on solid

concentration by correcting for the amount bound in solution.

94

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Chapter IV: Modeling Benzo-a-pyrene Sorption to Lake Michigan
Sediments by the Solute Complexation Model

4.1 Introduction

The first three chapters of this Thesis have sought to develop
the idea that the interaction of HOC's with sediments and dissolved
organic matter is not simple. Typical techniques like linear
partitioning models and simplified corrections for binding to DOM are
not sufficient to describe what is happening when a system of water,
solids, and HOC's is mixed. Rigorous analytical technique for
experimental data and reasonable models which describe both
experimental and natural observations under simplifying
assumptions are necessary to evaluate some of the observations

which were described in chapters one through three.

For HOC's, the primary process which controls the distribution
within environmental systems is absorption to soils and sediments.
Consequently, models which describe the fate and transport of HOC's
rely on experimental techniques to provide sorption data which can
be extrapolated to environmental systems. The variation in
partitioning data which is obtained by using constant and varying
solid isotherm techniques is currently of interest in its relationship to
actual environmental partitioning. The concept of a heterogeneous
solute was developed by Voice to explain these observations. This

model is applied to the benzo-a-pyrene data obtained in this study.

96

4.2 Results and Discussion:

4.2.1 Model Calibration

A model was developed by Voice, 1985, to describe three
phase partitioning of HOC's between solid, aqueous free and aqueous
bound sinks. The model conceptualizes a phase transfer of HOC
binding material from organic solids and a distribution of the
aqueous phase between "free" and "bound" constituents. A schematic
of the model system is shown in Figure 4.1. Concentrations of HOC's
within each compartment can be predicted by using equilibrium

partitioning coefficients.

The aqueous HOC species within Voice's model are defined by a
partition coefficient between the dissolved organic carbon (DOC) and
water. Each constituent in the liquid phase is in turn distributed to
the solid phase by distinct partition coefficients, K1 and K2. The

overall partition coefficient or apparent Kp determined

experimentally is then defined as:
Kp= (Csf + Csb)/(wa + Cwb)
Where, Csf = mass fraction of free compound in solid

Csb = mass fraction of bound compound in solid
wa = mass fraction of free compound in solution

Cwb = mass fraction of bound compound in solution

97

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Although Voice did not propose a distinction between Csf and
Csb, we have developed it in this way since K1 and K2 are
equilibrium coefficients and as such define two separate and distinct
compartments. Voice proposed that the observed decrease in the
partitioning coefficient with changes in solids concentration be
attributed to transfer of a sorbing, or solute binding material from
the solid to the liquid phases. The amount of the binding material
released to solution would increase with increasing solids, resulting
in values of Koc which decrease as a logarithmic function of solids
concentration. In order to evaluate the amount of a contaminant at
equilibrium within each phase, the solid phase partitioning
coefficient as well as the free/bound distribution within the aqueous

phase must be measured.

The solute complexation approach also incorporates solute
heterogeneity in its development by allowing for different
equilibrium sorption coefficients for the "bound" and "free" phase in
solution. Figure 4.2, adapted from Voice, shows a hypothetical chart
indicating the effect of the isotherm procedure on observed
partitioning for a heterogeneous solute. The curves represent a
system with two compounds having partition coefficients of 104 and
102. Each initially comprises 50 % of the mixture. The curves are
developed assuming both the constant and varying solids
experimental techniques. As can be seen, the varying procedures
result in different isotherms. The constant sediment isotherm is
linear while the constant concentration isotherm is non-linear even

on the log-log plot. Voice 1983, experimented with humic and fulvic

99

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Fl.gure 4.2: Effect of Isotherm Procedure for Heterogeneous Solute

100

acid sorption to activated carbon and showed data trends similar to
the hypothesized heterogeneous solute curves. He interpreted the

results as examples of heterogeneous solute sorption.

The equations developed by Voice for the solute complexation
model were used to analyze the data obtained for benzo-a-pyrene.
The idea was to describe the partition coefficient in terms of the solid
concentration and three distribution coefficients. K1,, the apparent

partitioning coefficient, was evaluated by the following expression:

Kp = M5 + 111:1) + K *IIDSEKS +132)
1/(K1*S + l) + KX*TOC/(K2*S + 1)

Where S = solids concentration in kg/l

K1, K2, Kx = unitless partitioning coefficients

TOC = total organic carbon in kg/l

Under the proposed modeling scheme, Kl represents the solid
phase partition coefficient of the "free" contaminant; whereas, K2
represents the solid phase partition coefficient of the "bound"
contaminant. The coefficients K1 and K2 represent partitioning at
equilibrium. By definition, however, Kx, is the initial distribution of
the free and bound contaminant in the aqueous phase. Kx is not,

therefore, defined by Kdoc.

Voice presented a sensitivity analysis which demonstrated the

effects that each distribution coefficient had on Kp, the observed

overall partition coefficient. As indicated in Figures 4.3, 4.4, and 4.5,

101

6.0

-- a) log K1 = 14.0
b) log K1 = 8.0

5.0

c) log K1 = 7.0

1
0"”

2.0 3.0 4.0

LOG PRRTITION COEFFICIENT

 

D 1 1 n n 1 J r 41
C v V 1 Y I

°0.0 1.0 I 2.0 3.0 4.0
LOG SOLIDS CONCENTRHTION (HG/L)

Figure 4.3: Sensitivity of Solute Complexation Model to K1

102

 

5.0

L

4.0

3.0

 

LOG PRRTITION COEFFICIENT

 

 

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LOG SOLIDS CONCENTRRTION (HG/L)

Figure 4.4: Sensitivity of Solute Complexation Model to K2

103

.. a) log KX = 1.4
a b) log xx = 2.4

    

c) log K" '-

l
v

4.0

2.0

l
U

LOG PRRTITIQfi COEFFICIENT

 

°.o‘tia‘£o*£o‘7.'o
LOG SOLIDS CONCENTRHTION (MG/L)

Figure 4.5: Sensitivity of Solute Complexation Model to K,(

104

increasing Kx decreased the apparent partition coefficient at low
solids concentration, whereas increases in K2 increased the apparent
coefficient at high solids concentration. Additionally, increases in Kl
also increased the partition coefficient at low solids concentration,

however, it was not as sensitive as the other parameters, K1 and K2.

The first step in our procedure was to model the observed data

using the equations developed by Voice. Accordingly, values of Kx,

K1, and K2 were chosen and altered to see whether the model could

be calibrated to predict results which were obtained for benzo-a-

pyrene. The model and experimentally determined KP values are

plotted vs. solids concentration in Figure 4.6. The values which were

chosen for each coefficient are as follows:

1g: 1.61 x 104
K1: 2.51 x 106

K2: 1.35 x104

As indicated, the model can be calibrated for the results obtained
using benzo-a-pyrene over the experimental range of solid

concentrations.

Figure 4.7 shows the experimental data overlain on the model

data obtained using the terms for Csb, wa, Cwb, and wa which

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represent each term in the KP equation. The values figure 4.7 were

calculated from the following equations:

Co = wa + Cwb
Cwb = Kx * er
Substituting, wa = Co/(l + Kx)
Csf = K2 * C0/(1 + K)
Cwb: Kx * Co/[S *(1+ Kx)]
Csb: K1* Kx * Co/[S * (1 + Kx)]

The graph is a plot of (Csf-£51,) vs (wa + Cwb) showing both
variable and constant solid isotherm data. As shown, the
experimental results are reasonably described by the model
equations over the solids range and initial concentration values used
in our experiment. Deviations at low solid concentrations may be the
result of estimates for organic carbon transfer from the solid phase
and the difficulty in fully separating particulate material from

solution.

Since the value of KK used in Voice's model does not correspond
to the equilibrium Kdoc, the model values for Cf,“ and Chowd were
evaluated using each term in the numerator of the Kp equation with
the intent of ultimately identifying how the model predicts
equilibrium Kdoc. The results are graphed in Figure 4.8. As
indicated, the model predicts that the amount of bound compound

will decrease only slightly over the experimental range of solid

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concentrations. The solution phase of the free compound however,
decreases significantly over the solids range. Also seen on the curve
are the points which form a vertical line above a constant solid value.

These are the varying solute/constant solid model predicted points.

From these results the Kdoc value which is "hidden" within the
model can be determined. Figure 4.9 shows that the model predicts
an increasing distribution of HOC in the bound form with increasing
solid concentration. This observation suggests that the binding
constant of solution phase HOC to dissolved organic mater increases
with increasing solid concentration. It appears from a log-log plot of
the data that the constant is most affected at low solid concentrations
and reaches a plateau at high solids concentrations. The results are
obviously dependent on chosen values for Kx,Kl and K2, however as
more data becomes available on solution phase partitioning to DOM,

this prediction can be tested.

Model prediction and experimental results for Kdoc of benzo-a-

pyrene are shown in Figure 4.10. The model predicted results are
the same as shown in Figure 4.9, and they are shown again in Figure
4.10 so that we can compare them to the experimental data. The
experimental results were obtained from the fluorescence quenching

and reverse phase techniques. The model predicts Kdoc results which

are generally higher than the experimental data.

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4.2.2 Non-Linear Parameter Estimation

The final procedure in modeling the benzo-a-pyrene data was

to develop an expression for observed Kp which eliminated the non-
equilibrium Kx present in Voice's model and allowed a regression to
estimate K1 and K2. In order to accomplish this, the equation was
intended to be written in terms of the Cf,“ which was determined

experimentally in our system. The expression for KP is then:
Kp= (Cm*Kl "l' Cfree*Kdoc*DOC*K2)/(Cfree+ Cfree*Kdoc*DOC)

Where: Cm,e = "free" benzo-a-pyrene in solution
Kdoc = aqueous distribution coefficient

DOC = dissolved organic carbon
K1, K2: model parameters

This expression describes the same sink model which was developed
by Voice, however, it is written in terms of the experimentally

determined Cfrec value.

The equation for K1) was then applied to the SYSTAT Non-linear
Parameter Estimation technique to determine K1 and K2. The
residuals and regression information are included in Appendix V. K1
and K2 were determined to be:

K1: 5.9x 103
K2: 3.6x 103

113
Using the K1 and K2 estimations, the values for K0c at each Cf,“

measurement were then calculated with the intent of showing how
model predicted K0c values varied with solid concentration.
Experimental and calculated K0c values are shown in Figure 4.11 as a
function of solid concentration. The experimental values are shown
as graph points and the model values are shown as a line. As can be
seen, the heterogeneous solute model with the modification for the

Cfme term does not describe a decrease in K0c which approximates

that which is observed experimentally. The presence of the non-

equilibrium Kx value in Voice's model appears to make a significant-

contribution in describing the observed data. The additional degree
of freedom provided by the term Kx allows the data to be fit better.

114

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Conclusions

An understanding of the distribution of PAH compounds in
sediment/water systems is a complex process. Laboratory
sorptionstudies provide at best only a partial view of actual field
phenomena. Interpretations of experimental results are obscured
by inefficient compound recovery procedures, operational definitions
for "free" and "bound" contaminant, and limits in defining

particulate as opposed to freely dissolved organic material.

Within this study, an attempt was made to evaluate sediment
sorption of four PAH compounds exhibiting a range of

hydrophobicities. We found that apparent K0c values determined by

a varying solid sorption technique showed a dependence on solid
concentration. The observed value of apparent K0c decreased with
increasing solid concentration. Generally, this dependence appeared
to increase for increasing compound hydrophobicity. A similar
effect is noted in field data from a study undertaken within the

Grand Calumet River (Hoke and Giesy 1992), however, the evaluation

was based on foe as opposed to solid concentration.

An approach to adjust the apparent K0c by subtracting the
amount of "bound" compound from theaqueous phase did not correct
for the solid dependence observed in the phenanthrene and benzo-a-
pyrene data. This procedure was completed using values of "free"
compound which were determined by the fluorescence quenching

and reverse phase techniques.

116

The varying solid and constant solid isotherm techniques for
benzo-a-pyrene produced a series of curves which are similar to
those produced for heterogeneous solute partitioning (Voice, 1984).
Model data obtained using the solute complexation model developed
by Voice 1985, was capable of describing the experimental data.
When we introduced a term for Cf,“ into the solute complexation
model equations and applied a non-linear parameter estimation for
the coefficients K1 and K2, however, the model failed to adequately
describe the data. This observation suggests that either the non-
equilibrium distribution coefficient which is incorporated in the
derivation of Voice's model is a significant factor in the ability of the
model to describe heterogeneous solute partitioning, or that
experimentally determined values of "free" compound were not
capable of calibrating the model to the observed solid phase

partitioning data for benzo-a-pyrene.

117

Future Research

In terms of experimental techniques, future research to
provide a more rigorous separation of particulate and aqueous
dissolved organic material should continue. Additionally, techniques
which are intended to estimate the "free" and "bound" contaminant
in the aqueous phase should continue to be refined. Typically, these
techniques provide operational definitions which need to be
evaluated in order to define their limitations and applicability to

different compounds and different sorbents.

With respect to modeling, many approaches and hypothesis
have been suggested by different researchers. Our research used the
solute complexation model to evaluate experimental partitioning
data. Other models are available, however, and the applicability of

these models needs to be evaluated.

Although the solute complexation model could be calibrated to
the experimental sorption data for benzo—a-pyrene, it is not known
how closely model data predict similar environmental systems. The
variation in observed partitioning with foe which was apparent in
data from the Grand Calumet may be a phenomena parallel to
laboratory data. More field studies of this effect should be
conducted.

118
REFERENCELIST

WWW, Edited by Werner Stumm, John Wiley and
Sons, New York 1987, pg 7-9.

Bertch, P.M., J.M. Novak, (1993), Pyrene sorption by Water Soluble
Organic Carbon, Environ. Sci. Technol., 27, 398-402.

Booth P.N., M.A. Jacobson, (1992) Development of Cleanup Standards
at Superfund Sites: An Evaluation of Consistency, J. Air Waste
Manage. Assoc., 42, 762-766.

Briggs, G. G., (1973), A Simple relation Ship Between soil Sorption of
Organic Chemicals and Their Octanol/Water Partition

coefficients WW II
475- 478.

Carter, C.W., I.H. Suffet, (1982) Binding of DDT to Dissolved Humic
Materials, Environ. Sci. Technol., 16, 735-740.

Chiou, C.T., V.H. Freed, R.L. Kohnert, (1977) Partition Coefficient and
Bioaccumulation of Selected Organic Chemicals, Environ. Sci.
technol., 11, 475-478.

Chiou, C.T.; P.E. Porter, D.W. Schmeddling, (1983), Partition Equilibria
of Non-ionic Organic Compounds Between Soil Organic Matter
and Water, Environ. Sci. Technol., 4, 227-230.

Curl, R.L.; G.A. Keolian, (1984) Implicit-Adsorbate Model for
Apparent Anomalies with Organic Adsorption on Natural
Adsorbents, Environ. Sci. Technol., 18, 916-922.

DiToro, D.M., (1991), Technical Basis for Establishing Sediment Quality
Criteria for Nonionic Organic Chemicals Using Equilibrium
Partitioning, Environ. Toxicol. Chem 10, 1541-1583

DiToro, D.M., J.D. mahoney, P.R. Kirchgraber, A.L. O'Byrne, L.R.
Pasquale, D.C. Piccinilil, (1986) Effects of Non-reversibility,
Partcle concentration, Ionic Strength on Heavy Metal Sorption,
Environ. Sci. Technol., 20, 55-61.

119

Eadie, BL (1990), Three-phase Partitioning of Hydrophobic Organic
Compounds In Great Lakes Waters, Chemosphere, 20 Nos 1-
2 pp 161-178.

Gauthier, T.D., E.C. Shane, W.F. Guerin, W.R. Seitz, C.L. Grant (1987),
Fluorescence Quenching Method for Determining Equilibrium
Constants for PAH Binding to Dissolved Humic Materials,
Environ. Sci Technol. 20, 1162-1166

Gschwend P.M., D.A. Backhus, (1990) Fluorescent Polycyclic Aromatic
Hydrocarbons as Probes for Studying the Impact of Colloids on
Pollutant Transport in Groundwater, Environ. Sci. Technol, 24,
1214-1223.

Gschwend, P.M. and S. Wu (1985), On the Constancy of Sediment
Water Partition coefficients of Hydrophobic Organic
Pollutants, Environ. Sci. Technol., 19, 90-96.

Handbook of Environmental Data on Organic Chemicals

Hoke, R.A., J .P. Giesy, M.J. Zabik, 1992(Prepublication), A Field
Evaluation of Equilibrium Partitioning in the Grand Calumet
River, and Indiana Harbor

Karickoff, S.W., D.S. Brown, T.A. Scott, "Sorption of Hydrophobic
Pollutants on Natural Seidments", Water Research, 13, 1979,
pp 241-248

Karickoff, S.W., "Semi-Emperical Estimation of Sorption of
Hydrophobic Pollutants on Natural Sediments and Soils,
Chemosphere, 10 1981 pp 833-846

Karickoff, S.W., "Sorption Kinetics of Hydrophobic Pollutants in
Natural Sediments", Contaminants and Sediments, Vol. 2, Ann
Arbor Science Publishers, Inc., Ann Arbor MI, 1980, pp 193-
205

Lake, J.L., N.I. rubinstein, H. Lee 11, CA. Lake, J. Heishe,
Spavibnano,l990, Equilibrium Partitioning and Bioaccumulation

of Sediment associated Contaminants by Infaunal Organisms,
Environ. Toxicol. Chem 9: 1095-1106

120

Lambert, S. M., (1967), Functional Relationship Between Sorption in
Soil and Chemical Structure, LAW" 15, 572- 576.

Lambert, S.M., (1968), Omega, A Useful Index of Soil Sorption
Equilibria, J. Agric. Fd. Chem., 16, 340-343.

Lambert, s.M., (1966) the influence of soil Moisture on Herbicidal
Response, Weeds, 14, 273-275.

Landrum, P.F., Giesy, J.P., "Advances in Identification and Analysis of
Organic Pollutants in Water”, Keith L. H., Ed., Ann Arbor Science:
Ann Arbor, MI, 1981, I, pp 345-355

Landrum, P.F., S.R. Nihart, B.J. Eadie, W.S. Gardner, 1984, Reverse
Phase Seperation Method for Determing Pollutant Binding to
Aldrich Humic Acid and Dissolved Organic Carbon of Natural
Waters, Environ Sci. Technol, 18, 187-192

Magee, B.R., L.W. Lion and A.T. Lemley (1991), Transport of Dissolved
Organic Macromolecules and Their Effect on Transport of
Phenanthrene in Porous Media, Environ. Sci. Technol., 25, 323-

331.

McCarthy, J.F., (1983), Role of Particulate Organic Matter in
Decreasing Accumulation of Polynuclear Aromatic
Hydrocarbons by Daphnia magna, Arch. Environ. Contam.

Toxicol. 12, 559-568 (1983).

McCarthy, J.F., J.M. Zachara, (1989), Subsurface Transport of
Contaminants, Environ. Sci. Technol., 23, 496-502.

McCarthy, J.G., B.D. Jimenez, (1985), Interactions between Polycyclic
Aromatic Hydrocarbons and Dissolved Humic Material: Binding
and Dissociation, Environ. Sci. Technol., 19, 1072-1076.

McKay D., A. Bobra, W.Y. shiu, Relationships Between Aqueous
Solubility and Octanol-Water Partitioning Coefficients,
Chemosphere, 9 1980 pp 701-711

Means, J.C., S.G. Wood, J.J. Hassett, W.L. Banwart, (1980), Sorption of
Polynuclear Aromatic Hydrocarbons by Sediments and Soils,
Environ. Sci. Technol., 14, 1524-1528.

121

Morra, M. J.; M.O. Corapcioglu, P.M.A. von Wandruska, D.B. marshall,
and K. Topper, (1990), Fluorescence Quenching and Polarization
Studies of Naphthalene and l Napthol Interaction with Humic
Acid, Soil. Sci. Soc. Am. J., 54, 1283-1288.

Murphy, E.M., J.M. Zachara, S.C. Smith, 1990, Influence of Mineral
Bound Humic Substances on the Sorption of Hydrophobic
Organic Compounds, Environ. Sci. Technol., 24, 1507-1516

O'Connor DJ. and LP. Connolly, 1980, The effect of concentration of
Absorbing Solids on the Partition Coefficient, Water Resources
14, 1517-1523.

Slautman, M., Mineral Surfaces and Humic Substances: Partitioning
of Hydrophobic Organic Pollutants, PhD Thesis, 1992

MW. 1981. IN. Miller. Chapman
Hall, New York

.10.. trio! 0 '1' 5|! 0 11' .10 1..

(1990)

Swarzenbach, R.P., J. Westall, Transport of Nonpolar Organic
Compounds from Surface Water to Groundwater, Laboratory
Sorption Studies, Environ. Sci. Technol., 15, # 11, 1360 - 1367.

Voice, T.C., C.P. Rice and W.J. Weber Jr. (1983), Effect of Solids
Concentration on the Sorptive Partitioning of Hydrophobic
Pollutants in Aquatic Systems, Environ. Sci. Technol., 12, 513-

518.

Voice, T.C., W.J. Weber, Jr., (1985), Sorbent Concentration Effects in
Liquid/Solid Partitioning, Environ. Sci. Technol., 19, 789-796.

Weber, W.J. Jr., T.C. Voice, A. Jodellah, (1983), Adsorption of Humic
Substances: The Effects of Heterogeneity and System
Characteristics, J.AWWA, Dec., 612-619.

APPENDICIES

APPENDIX A: Fluorescence Quenching

Appendix 1: Fluorescence Quenching
Stern-Volmer Equation and
Correction Coefficient

Stern-Volmer Equation

PAH + DOM = [PAH-DOM]

complex

Defining, Fo -- Fluorescence in absence of quencher
F = Fluorescence in presence of quencher

Kdoc- [PAH-DOM] ex/{IPAHHDOMJ}

compl

and assuming [PAH] 1001/ [PAH] free = Fo/F
Mass balance on the PAH, [PAH] total= [PAH] free + [PAH] bound
Dividing by [PAH1m.

[PAH] t‘ml/ [PAH] he: 1+[PAH] bound/ [PAH] he: [DOM] / [DOM]

[PAIHtotal/[PAmfree = 1 + KdochM] .
Substituting to obtain the form of the Stern Volmer plot,

Fo/F = 1 + Kdoc[DOM]

Q . : tfi‘ t
Fo = on: I= Io*10 "*1 Beer Iambert law

I0 = intensity of excitation at sample surface

122

A = Absorbance per cm pathlength at relative wavelength
d = depth in cm of nominal path length of excitation
If F = c*I

F = Fo*10’Ad, C= Fo/F = 10“

For emrnission absorbance, C=10(Ad+A'd')

The assumptions for this derivation include the following:
Optical pathlength can be defined
Finite widths of beams is ignored
Reflection is insignificant
Bandwidth of light is infinitely small

Since F is porportional to light absorbed between d1 and d2

'Ad 1 - 'AdZ)

F = Ky( 10 10

As A approaches 0, F approaches F0 and d1 and d2 are

approximated by the first term in series expansion.
Fo = Ky‘2.3f"A*(d2-d,)

c = 2.3*A*(d,-d,)/(1o-Ml-ro-W)

123

Benzo-a-pyrene Timed Fluorescence Data

 

 

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MOD: sun-a

Tm: SPECTMU

W 0: 1111895141.?!»

00- 7m: BINARY

We 10: FLO“ (V2.00)
M

Clan-0: 00:07:07. I“
LII 1100000; 0097317. 02101‘2
OI- 001 1

xtssq Y (WT)

10
20
00
00
70

100
120
120
100
100
100
100
210
220
200
200
270
200
200
210
220

200
270
200
000
020
020
000
000
000
000
010
020
000
000
070
000
000
010
020

000
070
000
700
720
720
700
700
700
700
010
020
000
000
070
000
000
010
020

000

070

000
1000
1020
1020
1000
1000
1000
1000
1110
1120
1100
1100
1170
1100
1200

120.020
110.007
120.120
120.200
120.200
120.222
120.200
120.217
120.100
110.002
110.070
120.002
120.100
120.200
120.201
120.002
120.001

120.112

120.20
120.207
120.020
110.002
110.070
120.000
110.002
110.002
110.702
110.700
110.002
120.000
120.020
110.000
110.020
120.000

120.00
110.002

110.02
110.002
110.000
110.070

110.01
110.012
110.020
110.002
110.002

110.07
110.012
110.702
110.000
110.070
110.071
110.071
110.702
110.020
110.700
110.011
110.712
110.001
110.700
110.722
110.700
110.000
110.020

110.00
110.700

110.72
110.000
110.000
110.010
110.070
110.017
110.020
110.020
110.000
110.272
110.200

110.02
110.021
110.220
110.000

WEBEHLMO

124

7W:

Mu: Sun-a

1m:

PE ETD

SPECTRA!

W D: DUEBENIJUP

On 190:

NW

Sal-c010: PLDMMJO)

m
Clubd’:

00:07:07. am
LII 1100000; @9717. 021022

 

Oat-out

 

I559

10

20

00

00

70

00
100
120
120
100
100
100
100
210
220
200
200
270
200
200
210
220
200
200
270
200
000
020
020
000
000
000
000
010
020
000
000
070
000
000
010
020

000
070
000
700
720
720
700
700
700
700
010
020
000
000
070
000
000
010
020
000
000
070
000
1000
1020
1020
1000
1000
1000
1000
1110
1120
1100
1100
1170
1100
1200

VP")

120.020
110.007
120.120
120.200
120.200
120.222
120.200
120.217
120.100
110.002
1 10.070
120.002
120.100
120.200
120.201
120.002
120.001

.110.000

120.112

120.20
120.207
120.020
110.002
110.070
120.000
110.002
110.002
110.702
110.700
110.002
120.000
120.020
110.000
110.020
120.000

120.00
110.002

110.02
110.002
110.000
110.070

110.01
110.012
110.020
110.002
110.002

110.07
110.012
110.702
110.000
110.070
110.071
110.071
110.702
110.020
110.700
110.011
110.712
110.001
110.700
110.722
110.700
110.000
110.020

110.00
110.700

110.72
110.000
110.000
110.010
110.070
110.017
110.020
110.020
110.000
110.272
110.200

110.02
110.021
110.220
110.000

TNEBENLWKI

124

1W:

Mu: Sum-at

1m:

PE FLTO

”EON“

w & TWEBEDQJHP

M111»:

01W

my. 10: m (450)

MIL
0"“:

00:00:10. am
LII 1100000: 00:00:10. mom

 

Duo-t1

 

“SEQ

10

20

00

00

70

00
100
120
120
100
100
100
100
210
220
200
200
270
200
200
210
220
200
200
270
200
000
020
020
000
000
000
000
010
020

000
070
000

010
020
000
000
070
000
700
720
720
700
700
700
700
010
020
000
000
070
000
000
010
020

000

070

000
1000
1020
1020
1000
1000
1000
1000
1110
1120
1100
1100
1170
1100
1200

Your)

100.007
100.210
100.020
100.200
100.270
100.002
100.270
100.000
100.010
100.022
100.000
100.727
100.100
100.200
102.070
102.007
102.000
102.070
102.002
102.200
102.200
102.000
102.020
102.221

102.20
102.027
102.202
102.220
102.000
102.000
102.100
102.120

102.10
102.211
102.210
102.100
102.201
102.200

102.12
102.020
102.002
102.201
102.200
102.122
102.000
101.002
101.700
101.722
101.202
101.112
100.000
100.070
100.021
100.200
100.212
100.000
100.101
100.000
100.002
100.100
100.220
100.022

100.07
100.220
100.002
100.021
100.001
100.000
100.007
100.000
100.007
100.011
100.000
100.200
100.010
100.027

100.00
100.200
100.200
100.002
100.020

7101585121100

125.

1m:

w u TIMEBEMJHP

01-1790:

03W

swan D: m MJO)

km
Clo-9‘:

00:00:10. won/22
u: Heel“: 00.00:". 0mm

 

Dan-d1

 

“SEQ

10
20
00
00
70
00
100
120
120
100
100
100
100
210

200
200
270
200
200
210
220
200
200
270
200
000
020
020
000
000
000
000
010
020
000
000
070
000

010
020
000
000
070
000
700
720
720
700
700
700
700
010
020
000
000
070
000
000
010
020
000
000
070
000
1000
1020
1020
1000
1000
1000
1000
1110
1120
1100
1100
1170
1100
1200

mm

100.007
100.210
100.020
100.200
100.270
100.002
100.270
100.000
100.010
100.022
100.000
100.727
100.100
100.200
102.070
102.007
102.000
102.070
102.002
102.200
102.200
102.000
102.020
102.221

102.20
102.027
102.202
102.220
102.000
102.000
102.100
102.120

102.10
102.211
102.210
102.100
102.201
102.200

102.12
102.020
102.002
102.201
102.200
102.122
102.000
101.002
101.700
101.722
101.202
101.112
100.000
100.070
100.021
100.200
100.212
100.000
100.101
100.000
100.002
100.100
100.220
100.022

100.07
100.220
100.002
100.021
100.001
100.000
100.007
100.000
100.007
100.011
100.000
100.200
100.010
100.027

100.00
100.200
100.200
100.002
100.020

WEBEIQJVKI

125.

1W:

Mei-142.13: Sum-d1

TnI:

PEFLTD

SPECTRJH

W0 IO: TIMEBEIOJHP

0"- '71»:

IflHARY

5913-41410: MM”)
WWW

C133b0:

023230.0y02Q2
LII 34401443: 02:1220. 32mm

 

DIN a! 1

 

“seq

10
20
00
00
70
00
100
120
120
100
100
100
100
210
220
200
200
270
200
200
210
220
200
200
270
200
000
020
020
000
000
000
000
010
020
000
000
070
000
000
010
020
000
000
070
000
700
720
720
700
700
700
700
010
020
000
000
070
000
000
010
020
000
000
070
000
1000
1020
1020
1000
1000
1000
1000
1110
1120
1100
1100
1170
1100
1200

71"")

244.333
245.445
234.444
244.334
245.331
234.374
244.571
244.331
244.143
244.134
243.344
243.472
243.741
243.511
243.423
233.532
243.444
243.213
243.237
242.332
242.541
242.443
242.523
242.431
242.151

231.34
242.213
242.334
241.754

201.10
243.343
243.437
243.211
273.434
273.343
273.334
273.433
273.553
274.354
274.421
274.424
274.232
273.134
277.735
277.414
277.322
277.335
277.353
277.337
277.144
277.344
274.343
274.573
274.233
274.343
274.151
274.234
274.231
274.221
274.227
274.342
275.444
275.731
275.543
275.432
275.253
275.374
275.332

275.33
275.317
274.442
275.257
275.144
275.133
274.357
274.743
274.343

"270.007

270.000
270.000
270.000

WEBEFQVIKI

126

Typo:

PE FLTD

W4 ID. TIUEBEMJUP

0413 7,143:

BINARY

3.1-... 10: non n53)

Andra:
034144:

02:40.04. 32mm
LI“ “00030: 02:40.04. 3mm

 

MHI

 

1(SEC)

I0
00
40
00
70
00
100
I20
I00
I00
I00
I00
I00
2I0
220
240
200
270
200
000
0I0
000
040
000
070
000
400
420
400
400
400
400
400
0I0
020
040
000
070
000
000
0I0
000
040
000
070
000
700
720
700
700
700
700
700
0I0
020
040
000
070
000
000
0I0
000
040
000
070
000
I000
I020
I000
I000
1000
I000
1000
IIIO
II20
II40
II00
II70
II00
I200

VP”)

40I.002
402.244
402.000
400307
400.020
400.044
400J00
400.000
404.I24
404.000
404.704
404.700
404.202
400.00I
404.I00
404.0I7
404.000
400M042
400.I04
404.770
404.0I7
404.00I
404.00
404.777
404.020
404.0II
404.0II
404.407
404.020
404.04
404AIO
404.200
404.40
404.000
404.0I0
404.070
404.070
404JIO
404.002
404.404
404.00I
404.0I7
404.000
404.I00
404.24I
404.000
404.I02
404.002
404.I47
400.020
400.040
404.040
404.000
404.I00
404.40
404.004
404.0
404.470
404.200
404.I40
404.20I
404.000
404.004
404.200
404.I24
404.IIO
404.02
404.4I2
404.020
404.000
404.I7
400.720
400.02I
400.000
400.7I0
404.002
404.20
404.000
404.00
404.000
400.000

THJEBEN4VVKI

127

1W:

Mon: 040.501

In»:

PE FLYD

SPECTRJU

W0 IQ “US$06.11”

o«-1744:

004M?

0313-3130: 41014 «2.53)

MI.
03350:

002190. 3m
LII 1143144. 002190. 021003

 

DIIIKI

 

01583

10

00

40

00

70

00
100
120
100
I00
100
100
100
210
220
240
200
270
200
000
010
000
040

000 '

070
000
400
420
400
400
400
400
400
010
020
040
000
070
000
000
010
000
040
000
070
000
700
720
700
700
700
700
700
010
020
040
000
070
000
000
010
000
040
000
070
000
1000
1020
1000
1000
1000
1000
1000
1110
1120
1140
1100
1170
1100
1200

71"“)

000.010
000.047
000.770

000.14
000.020
000.271
000.010
007.470
000.102
000.140

007420

000.24
000.774
000.001
000110
000.001
000.000
004.704
000.100
000.400

000.00
000.042
000.100
000.027
000.000
004.010
004.020
004.001
000.201
000.400
000.040
004.004
004.700
004.072
004.702
004.420
004.022
000.040
000.000

000.00
004.000
004.470

004.00
004.102

000.70
000.400
000.000
000.011
002.770
002.022
000.010
000.271
000.000
000.401
000.270

000.02
002.001
000.070
000.104
000.004
002.000

002.07
002.070
001.004
002.01 1
002.020
001.000
001.000

001.00
001.700
001.000
001.402
001.000
001.014
001.427

001.00

001.20
001.040
001.407
001.207
000.000

WEBEhéml

128

134233.33: PE ETD
330133713”: 51.313371
1173: “CTN“
W 10. 1144606710314?
0333 1133: BINARY
0373-373 10: RD“ ((2.50)

 

 

471-7744.
0441.3: 33.47:". 321mm
L441 14431144; 3347:14. own:
0413 331 1
11583) Y (M)
3 351.334
15 351.455
33 351.345
45 351.451
43 351.333
73 333.725
33 353.514
135 353.431
123 353.734
135 353.331
153 353.752
145 353.44
133 303.435
134 353.514
213 353.453
225 353.322
243 353.423
253 353.542
273 353.334
235 343.342
333 343.733
310 343.471
333 343.434
345 353.114
343 353.137
375 353.341
333 343.313
435 353.324
423 353.247
435 353.313
453 353.345
445 343.772
433 353.343
435 353.325
513 343.354
525 343.741
543 343.714
555 343.453
573 343.574
545 343.535
433 343.445
415 343.4
433 343.447
445 343.13
443 344.375
375 344.33
433 344.754
735 343.35
723 343.374
735 343.214
753 343.24
740 343.377
743 343.334
735 343.312
313 344.751
323 343.533
343 343.444
355 344.543
473 344.431
435 344.471
433 343.234
315 343.373
333 347.733
345 347.533
343 347.774
370 343.121
333 344.237
1335 347.322
1323 347.434
1335 347.533
1353 343.331
1345 344.335
1333 347.735
1335 347.53
1113 347.342
1125 347.153
1143 347.42
1155 347.772
1173 347.341
1145 347.331
1233 347.443

“HEBEMNfKI

129

130v33n:

8333303393: 5303461

In»:

PE ETD

SPECTRJU

W U. TIUEBEWJ'HP

0314 11113:

BINARY

5373-473 D; FLO“ 90.50)

Andri:
0338‘:

0421290, 0210012
L31 1408034: 0431200, IMJfl

 

0313341

 

0155C)

15
33
45
53
75
30
135
120
100
153
145
133
135
210
225
243
255
273
235
333
315
330
340
330
375
330
435
423
435
453
445
430
435
013
525
543
555
573
530
030
315
503
445
030
475
003
735
723
705
753
745
733
735
413
325
343
455
370
445
000
315
030
345
000
375
000
1330
1320
1335
1353
1345
1333
1300
1113
1120
1140
1155
1170
1145
1233

*0”)

020.7
020.014
020.07
020A00
020.024
020.110
020.007
020.000
020.040
020.000
020.004
020.720
020.000
020.40
020.002
020020
020.717
020.000
020.000
020.040
020.000
020.014
020.240
024.700
024.404
024.44
024102
024.044
020.00
020.14
024.721
024.001
024.007
024.400
024.201
024.441
024.000
024.420
024.070
024.000
024.002
024.10
020J71
020.720
020100
024.200
024.110
020.004
020.004
020.700
020.001
020.001
020.021
020.010
020.010
020.004
020500
020J00
020.000
020.700
020.020
020.220
022.001
020.021
020.242
020.400
020.00
020.100
022J07
022.001
020.220
020.10
020.177
020.002
022.000
022.042
022.000
020.001
020.10
022.040
022.000

THJEBENIVWKI

130

1m: PE F'LTO
313-nevi": mm
1173: SPECTRA!
W D: “BEBE H.714?
Dc- Typo: BINARY
Soft-n IO: FLO“ (V2.00)

C134“: 04:0491. 42mm
LII “M30: 0434.01. 42mm

 

Dunn

 

0155C)

10
00
40
00
70
00
100
120
100
100
100
100
100
210
220
240
200
270
200
000
010
000
040
000
070
000
400
420
400
400
400
400
400
010
020
040
000
070
000
000
010
000
040
000
070
000
700
720
700
700
700
700
700
010
020
040
000
070
000
000
010
000
040
000
070
000
1000
1020
1000
1000
1000
1000
1000
1110
1120
1140
1100
1170
1100
1200

71”")

000.477
000.000
000.000
000.101
000.000
004.714
004.000
000.007
000.400
000.401
000.20
002.000
002.000
001.040
002.100
002.000
000.001
000.001
002.000
002.070
002.470
002.047
002.004
002.740
002.010
000.004
000.210
002.072
002.000
000.000
000.020
000.120
000.204
002.701
002.020
002.402
002.000
002.722
002.701
0020
002.000
002.002
001.000
001.010
001.17
001.000
001.010
000.700
000.017
000.001
001.27
001.212
000.001
001.007
001.200
000.01
000.100
000.274
000.722
000.711
000.040
000.070
000.022
000.000
000.041
000.000
000.100
000.210
000J040
000.000
000.100
000.120
000.000
000.000
000.000
000.071
000.227
000.000
000.710
000.000
000.000

TNEBENAWKI

'131

1m:

W IQ TIMEOEHJUP

04- Mo:

BINARY

0309-3 10: RD“ V2.00)

m
Clubdt

00.00.02. cm
L”! “$030: 009492. 0210M

 

04100311

 

X15831

10
00
40
00
70
00
100
120
100
100
100
100
100
210
220
240
200
270
200
000
010
000
040
000
070
000
400
420
400
400
400
400
400
010
020
040
000
070
000
000
010
000
040
000
070
000
700
720
700
700
700
700
700
010
020
040
000
070
000
000
010
000
040
000
070
000
1000
1020
1000
1000
1000
1000
1000
1110
1120
1140
1100
1170
1100
1200

Hum

040.042
040100
040.001
044.00
044.274
044.022
044.000
044.20
040.021
040.002
040.004
040.700
040.070
040.000
040.707
040.02
040.2
040.102
040.110
042.024
042.700
042.004
040.107
040.007
042.710
042.010
042.004
042.040
042.101
042.270
041.070
041.000
042.070
042.402
042.00
042.04
042.000
042.104
042.100
042.101
041.700
041.070
041.020
042.040
042.070
041.040
041.01
041.002
042.100
042.007
041.700
041.00
041.700
041.004
041.047
041.000
041.020
042.000
042.200
042.121
041.020
041.200
041.200
041.040
041.001
042.000
042.022
041.400
041.000
041.222
041.471
041.040
041.410
041.707
041.000
041.100
041.000
041.100
040.000
041.000
041.244

TNEBEMMIKI

132

1nd":

mm”: Sum-ct

Two:

PE FLTO

VGCTRJH

w D: 711109410114?

04‘7"”:

BINARY

sour-nu. noun”)

m
Clu- 4:

0421000. 32mm
Lu 11941434: 0421454. 112/om

 

DIIM1

 

"SEQ

10

00

40

00

70

00
100
120
100
100
100
100
100
210
220
240
200
270
200
000
010
000

000
070
000
400
420
400
400
400
400
400
010
020

000
070
000
000
010
000
040
000
070
000
700
720
700
700
700
700
700
010
020
040
000
070
000
000
010
000
040
000
070
000
1000
1020
1000
1000
1000
1000
1000
1110
1120
1140
1100
1170
1100
1200

V out)

101.022
101.047
102.041
102.147
102.200
102.404
102.001
102.000
102.704
100.001
100.270
100.000
100.702
100.701
100.421
100.017
102.740

102.07
102.027
102.102
101.000
102.002
102.124
102.107
102.000
102.000
102.001
102.040
102.200
101.041
102.104
102.207
102.200
102.011
102.204
102.102
102.007
101.000
101.002
101.000
101.004
101.700
102.010
101.007
101.021
101.721
101.010
101.001
101.000
101.710
101.000
101.072
101.001
101.400

101.01
101.007
101.070

101.00
101.477
101.041
101.701
101.707
101.002
101.704
101.000
101.000
101.740
102.004
102.107
101.000
101.001
101.070
101.700
101.007
102.011
101.004
101.041
101.004
101.047
101.070
101.002

7114057410.le

133

1w": PE FUD
mm": sum-ch
typo: syscmuu
W 10: nuaem LN?
00' 13'": DNA!"
SUI-m 10: FLDU 04.00)

 

 

W:
Oubdz “1000. 02mm
L441 04061000: 00:40.00. 02100‘8
D‘- M 1
X1583) Y (”‘71
0 040.041
10 040.420
00 040.400
40 040.401
00 040.001
70 040.002
00 040.100
100 040.011
120 040.710
100 040.440
100 040.070
100 040.000
100 040.404
100 040.004
210 047.0
220 047.001
240 047.010
200 047.00
270 047.002
200 047.74
000 047.004
010 047.200
000 047.272
040 047.010
000 047.102
070 040.000
000 040.704
400 040.074
420 040.400
400 040.020
400 040.01
400 040.70
400 040.000
400 040.400
010 040.000
020 040.007
040 040.200
000 040.021
070 040.72
000 040.771
000 040.040
010 047.040
000 040.040
040 040.00
000 040.004
070 040.400
000 040.400
700 040.404
720 040.000
700 040.400
700 040.010
700 044.00
700 040.40
700 040.4
010 040.200
020 040.110
040 040.107
000 040.000
070 040.200
000 040.110
000 040.120
010 040.207 .
000 040.000
040 040.100
000 040.007
070 040.070
000 040.012
1000 040.000
1020 040.01
1000 040.000
1000 040.02
1000 040.000
1000 040.004
1000 040.000
1110 040.410
1120 040.404
1140 040.010
1100 040.120
1170 044.004
1100 044.000
1200 044.070

“1185141113410

134

Tm:

PE FLTD

sumo to: 'nuaemz‘mr

04!: 7pc:

01W

son-co ID: ED“ M00)

Mam.
Can-4:

0711097. om
LII 0400000: 07:1097. swam

 

Dlhtdl

 

X(SEC)

10

40

00

70

00
100
120
100
100
100
100
100
210
220
240
200
270
200
000
010

1 000

040
000
070
000
400
420
400
400
400
400
400
010
020
040
050
070
000
000
010
000
040
000
070
000
700
720
700
700
700
700
700
010
020
040
000
070
000
000
010
000
040
000
070
000
1000
1020
1000
1000
1000
1000
1000
1110
1120
1140
1100
1170
1100
1200

V out)

200.000
100.071
200.007
200.700
200.010
100.007
100.000
100.707
200.100
200.101
100.207
100.702
100.077
10010
200.000
200J00
200J47
100.011
100.000
100.0
100.020
100100
100.012
100.170
100.200
100.004
100.010
100.20
100.400
100.120
107.770
107.007
107.001
107.007
107.007
107.042
107.401
107.000
107.700
107.070
107.040
107.000
100.12
100.21
100.127
100.020
100.021
107.070
107.744
107.00
107.007
107.200
107.007
107.001
107.011
107.201
107.200
107.000
107.001
107.040
107.211
107.000
107.000
107.241
107.20
107.000
107.02
107.002
107.102
107.12
107.047
107.02
107.00
107.004
107.144
10L00
107.001
100.720
100.040
100.041
100.700

“USEN12.WK1

135

7pc:

W1 10: “BERNIE?

cum-1191:

01W

saw. to: H.011 n10)

Annfifit
C11 18‘:

07:00:11, 1210322
L001 11mm 07:10:11. 02100fl

 

OIIMI

 

useq

10
00
40
00
70
00
100
120
100
100
100
100
100
210
220
240
200
270
200
000
010
000
040
000
070
000
400
420
400
400
400
400
400
010
020
040
000
070
000
000
010
000
040
000
070
000
700
720
700
700
700
700
700
010
020
040
000
070
000
000
010
000
040
000
070
000
1000
1020
1000
1000
1000
1000
1000
1110
1120
1140
1100
1170
1100
1200

'0’")

111.111
117.111
117.111
117.117
117.011
117.017
117.121
107.170
111.711
111.111

117.11
117.177
111.111
111.122
117.111

117.11
117.117

117.11
117.211
117.271
111.112
111.111
111.211
111.111
111.211
111.111
117.111

100.71
111.111
111.111
117.111
111.701
111.311
111.111
111.111
111.112
111.171
111.111
111.111
111.121
111.111
111.111
111.111
105.011
111.111
111.111
111.111
111.110
111.112
111.111
111.127
111.711
111.121
100.740
111.121
111.111
111.127

111.11
111.121
111.111
111.121
100.021
111.117
111.111
111.111
100.004
100.000
111.11:

111.11
111.111
111.121
111.111
111.111
111.111
111.111
111.121
111.111
111.117
111.121
111.111
111.117

“11851111le

136

7'0“": PE FLTO
Mu: Sun-d1
1m: SPECTKJH
$111911 10: 1111001117111!
0111 7,111: EMMY
00101111 10: RD“ (V2.00)

 

 

Mum:
011.11; 111112. 02”“
[J11 11.11111; 11.1112. 1271222
0111 111 1
1118:) Y MT)
1 211.11
11 212.171
21 212.111
11 212.17
11 212.711
71 212.111
11 212.111
111 212.21
121 212.212
121 212.22
111 212.111
111 212.211
111 212.121
111 212.121
211 212.221
221 212.111
211 211.111
211 211.111
271 211.712
211 211.111
211 ‘ 211.211
211 ‘ 211.111
221 211.112
211 211.111
211 211.112
271 211.21
211 211.111
111 211.121
121 211.172
121 211.117
111 211.112
111 211.111
111 211.172
111 211.111
111 211.172
121 211.127
111 211.11
111 211.112
171 211.117
111 211.171
111 211.111
111 211.111
121 211.772
111 211.121
111 211.11
171 211.111
111 211.172
711 211.121
721 211.112
721 211.117
711 211.211
711 211.111
711 211.111
711 211.111
111 211.12
121 211.121
111 211.111
111 211.12
171 211.117
111 211.711
111 211.111
111 211.111
121 211.111
111 211.112
111 210.751
171 211.112
111 211.121
1111 211.111
1121 211.112
1121 211.111
1111 211.212
1111 211.221
1111 211.112
1111 211.727
1111 211.111
1121 211.172
1111 211.711
1111 211.11
1171 211.22
1111 211.111
1211 211.711

“BEEN“.WKI

137

 

11069.11:

3111-1111": 1111-111

7m:

05 FLYO

SPECTRA]

W ID: “USENUJMP

01- 7,91:

HWY

31111-1710: RD“ 0450)

Mum:
011.0:

0022217. 1mm
LII 0400010: 0022217. 021023

 

“III-(I

 

MW

405
510
525
540
555
570
505
000
015
020

000
075
000
705
720
725
750
705
700
705
010
025

055
070
005
000
015
020
045
000
075
000
I005
I020
I025
0050
1005
1000
I005
II00
1025
1140
1055
1170
1105
1200

YMT)

500.20
400.04
400.204
400.500
400.427
400.002
400.550
400.075
407.524
407.210
407.407
407.000
407.770
407.400
400.000
400.247
400.545
400.54
400.2 I2
400.020
405.007
405.772
405.027
405.022
405.720
405.072
400.202
405.057
405.721
405.040
405.440
405.2 [2
405.405
405.040
400.2
400.024
405.022
405.222
405.210
405.227
405.242
405.201
405.407
404.025
404.402
404.022
405.770
405.204
405.227
405.024
404.015
405.122
404.775
404.240
404.405
405.074
405.450
405.242
404.745
404.500
404.20
404.42!
404.00
404.022
404.22
404.050
404.120
404.240
404.255
404.100
404.025
404.051
402.072
404.025
402.001
402.705
402.517
402.404
402.447
402.200
402.”

138

“MBENWAVKI

 

00:45:42, 0M
04:45:42, 1mm

 

111101.11: PE 1170
1.111-cup: 1.111-a1
Tm: mama
W1 10: 111185711ka
0111 1,91: BINARY
210-171 10: RD“ 0450)
Ma:

011110:

U11 1110114:

0111 111 1

 

1111111

15
20
45
00
75
00
105
120
125
150
I05
100
105
210
225
240
255
270
205
200
215
220
245
200
275
200
405
420
425
450
405
400
405
510
525
540
055
570
505
000
015
020
045
000
075
000
705
720
725
750
705
700
705
010
025
040
055
070
005
000
015
020
045
000
075
000
1005
1020
1025
1050
1005
1000
1005
1110
1125
1140
1155
1170
1105
1200

520.000
520.242
527.22I
520.051

025J5
525014
524.005
524.425
524.10!
522170
522.025
522.055
022.010
522.400
522.102
522.240

022.20
522.201
521.000
52L701

522.15
522.102
52L200

521.15
521.042
521.021
521.170
521.022
521.270
521.274
520.074
521.001
521.244
021.024
521.200
521.050
521.422
521.502

521.40
020.717
520.202
520.055
520.702
520.770
521.022
521.102
520.040
520.750
520.040

521.005 ,

521.050
020.002
520.005
520.222
020.274
520J10
020.040
521.214
521.520
521.240
520.700
520.500
520.542
520.757
521.220
521.100
520.052
521.501
021.042
521.575

521.22
521.212
521.524
021.520
521.104
520.700
521.150

521.25
521.074
521.200
521.021

TIUBENII.WK1

139

7W:

Mann: Snot-as

Tran:

PE R70

SPECTRA!

w. 10: 711-189410.711?

04h 7m:

UNAHY

2a.." 10: ADM V2.50)

w.
0441-0:

00.00110, 02M
LII 010G100; 00.00210. 0mm

 

04140011

 

1155C)

10
20
45
00
75
00
105
120
125
150
105
100
105
210
225
240
255
270
205
200
215
220
245
200
275
200
405
420
425
450
405
400
405
510
525
540
550
570
505
000
015
020
040
000
075
000
705
720
725
750
705
700
705
010
025
040
055
070
005
000
015
020
045
000
075
000
1005
1020
1025
1050
1005
1000
1005
1110
1125
1140
1155
1170
1145
1200

YONT)

407.201
400.205
405.212
405.170
405.075
404.550
404.242
404.045
404.045
404.007
404.102
402.515
402.074
402.000
402.154
402.040

402.22
401.744
401.220
401.247

' 441.427

401.404
401.070
401.107
401.77
401.020
401.002
402.202
402.057
402.207
402324
402.500
402J02
402157
402.014
402.005
402.124
401.500
401.020
401J41
401175
401.210
401.070
402.202
402A01
492.100
401.040
402.077
402.220
402.201
402.01
402.101
402.224
402.020
402J00
402.015
402.020
401.722
411
401.102
401.270
401.104
401.270
401.402
401.440
401.00
491.000
401.011
402.227
402.002
401.000
40L02
401.022
401.022
442.42
442.457
402.000
402.14
491.051
402.044
402.020

“1189110 WKI

140

 

APPENDIX B: Instrument Specifications

 

APPENDIX B: Instrument Specifications

Instrument Specifications

I. Fluorimeter

Instrument: Perkin Elmer LS 50 Spectrafluorimeter

Source: Zenon Arc Lamp
Phenanthrene B-a—P

Excitation Wavelength 255 nm 380 nm
Emmission Wavelength 365 nm 445 nm
Excitation Slit 5 nm 15 nm
Emmission Slit 5 nm 15 nm
Time Drive - 20 minutes
Frequency - 15 seconds

II. Total Organic Carbon Analyzer

Instrument: Shimadzu Total Organic Carbon Analyzer
Catalyst: Low Sensitivity

Acid Purge: 5 minutes at pH of 3

Sensitivity: 10x

141

III. High Performance liquid Chromatography

Instrument: Gilson HPLC

Column: C1 8, reverse phase

Mobile Phase: 1 minute, 50% acetonitrile, 50% water
Ramp to 100% acetonitrile
' 8 minutes, 100% acetonitrile
15 minutes, 50% acetonitrile, 50% water
' 16 minutes, end
Flow Rate: 2.5 nil/minute
Dectector: UV 116, 0.01 AUFS
Injection Vol.: 20 ul

IV. Liquid Scintillation Counting

Instrument: Beckman LS Counter
Time: 10 minutes

Region a: LL-UL 0.0-12.0

Region b: LL-UL 12.0-156.0

QIP : tsie/AIC
Conventional DPM

142

 

APPENDIX C: Key to Tables 2.2 through 2.6

APPENDIX C: Key to Tables 2.2 through 2.6

 

Key to Tables 2.2 through 2.6

 

 

Column

1

2

Definition
Sample identification

Grams of sediment (freeze dried) placed in 25 m1
centrifuge tube

Grams of Dl/RO water placed in 25 ml centrifuge tubes.

Concentration of sediment ln 25 ml centrifuge tubes in
mg/l. Calculated as (column Z/column 3) x 105

Amount of radiolabelled compound placed in the 25 m1
centrifuge tube from stock solution, in discharge per
minute (dpm). .

6 Absorbance of supernatant in 25 ml centrifuge tube
after equilibrium.

7 Grams of supernatant used for a liquid phase 14C
activity count.

8 14C activity in liquid portion , in dpm.

9 14C activity in liquid phase, in dpm/l. (Column
8)/ (Column 7)

10 ml of methylene chloride used to extract the 14C
activity in the sediments.

1 1 14C activity in the sediments, in dpm.

12 14C activity in the sediments in dpm/ kg. (column
1 1)/(column2)x1000x’l‘0TAL MECLz/Sample Volume
MECLZ.

13 14C activity extracted from the glass tube, in dpm.

14 [(Column 8) x (Column 3)/(Column 7) + (Column 11) +
(Column 13)]/ (Column 5)

15 (Column 12)/ (Column 14)

16 (Column 12)/(Colu=ma 9)/foc; where foc‘ 5%

17 (Column 15)/ (Column 9)/foc; where foc" 5%

 

143

 

APPENDIX D: Modelling Data

BaP Nonlinear data

 

 

 

Non-linear Parameter Estimation

 

 

BAP

BAP

Total

 

Estimated Koc

 

BAP solutions

Reverse Phase

Reverse Phase

DPM/1

UsinLNonlinear

 

Estimated

Adjusted

aqueous

K1. and K2 estimates

 

Koc

DOC, mgli

Free, bdpmll

Kdoc

 

Solids. rug/1

 

212626.358

5.02220355

226662.074

50328.4126

293076.923

105881.371

1462.45059

 

153634.694

7.5885197

117462.909

79460.8657

200591.716

95104.239

3308.03036

 

81193.0803

11.5353651

127411.169

27884.7344

190737.24

95210.7293

7255.36993

 

562407795

17.: 823911

102566.539

20504.7512

163915.547

90109.0009

13324.0446

 

53643.4925

25.7424683

57082.7415

20924.1459

98461.5385

91439.7799

25608.7824

 

72894.3311

14.366444

79856.4314

45173.124

149139.579

88755.0017

10035.8566

 

69935.2324

14.2275727

145643.656

64391.3966

298301.887

90428.7712

9875.9209

 

550432205"

14.1989641

273245.361

31898.0271

438811.881

94326.6002

9843.07572

 

83187.4284

14.4011358

463689.32

10075.9392

 

48374.2807

14.294134

507808.21

25269.1998

832035.398

88376.0358

9952.47525

 

60152.9608

14.2566202

492397.957

43941.6021

965354.331

83711.9825

9909.30599

 

163587.012

8.53721139

97145.6415

74614.8012

166730.402

96071.296

4102.35906

 

130418.497

8.43872069

329133.858

4017.36385

 

115003.546

8.57680758

329190.276

43311.5847

507976.654

94323.0636

4136.69065

 

140033.894

8.42954099

627800

4009.47119

 

139451.623

8.38274681

366038.183

82094.7582

698148.148

88403.7046

3969.3155

 

45399.6482

22.4804 786

64370.2692

28037.258

136039.604

77788.597

20684.4409

 

35878.4849

22.3318182

209232.145

28005.7873

438195.777

78328.2052

20468.1873

 

33500.9646

22.1458734

507126.48

7803.74697

767039.106

86666.4786

20198.7281

 

 

 

 

 

 

42102.7622

 

 

 

 

 

144

1.

Date:
Time:

085

mmqmmari-I

24-AUG-92

14:13:13
File: SYSTAT Data Editor

has 5 variables and
KOC DOC
212626.358 5.022
153634.694 7.589
81193.080 11.835
56240.780 17.082
53643.493 25.742
72894.331 14.366
69935.232 14.228
65043.221 14.199
48374.281 14.294
60152.961 14.257
163587.012 8.537
115003.546 8.577
139451.623 8.383
45399.648 22.480
35878.485 22.332
22.146

33500.965

19 cases printed out of

19 cases.

FREE

226662.074
117462.909
127411.169
102566.539

57082.742

79856.431
145643.656
273245.361
507808.210
492397.957

97145.641
329190.276
366038.183

64370.269
209232.145
507126.480

KDOC

50328.413
79460.866
27884.734
20504.751
20924.146
45173.124
64391.397
31898.027
25269.200
43941.602
74614.801
43311.585
82094.758
28037.258
28005.787

7803.747

19 cases in the file.

145

CT

293076.923
200591.716
190737.240
163915.547

98461.539
149139.579
298301.887
438811.881
832035.398
965354.331
166730.402
507976.654
698148.148
136039.604
438195.777
767039.106

ITERATION LOSS PARAMETER VALUES

0 0.1657391D+12 0.lOOOD+OOO.IOOOD+OO
l 0.3457568D+11 0.6222D+040.3026D+04
2 0.3454619D+11 0.5925D+040.3641D+O4
3 0.3454619D+11 O.5925D+O40.3641D+04

DEPENDENT VARIABLE IS KOC
MISSING DATA OR ESTIMATES REDUCED DEGREES OF FREEDOM
SOURCE SUM-OF-SQUARES DF MEAN -SQUARE

REGRESSION .131198E+12 2 .655990E+11
RESIDUAL .345462E+ll l4 .246758E+10

TOTAL .165744E-I-12 16
CORRECTED .420935E+ll 15

RAW R-SQUARED (l-RESIDUALfFOTAL) = 0.792
CORRECTED R-SQUARED (l RESIDUAL/CORRECTED) = 0.179

PARAMETER ESTIMATE
Kl 5924.718
K2 3640.774

Koc, = CFKI + (F km AOL 'Kl

 

Ck/c.’ in flrcousflqx ' fig,

146

APPENDIX E: Dialysis Experiment

Appendix 6: Dialysis Experiment

Equilibrium dialysis was studied using the technique of Carter and
Suffet, 1983, to physically seperate the free and bound forms of
phenanthrene in solution. Phenanthrene at 0.5 mg/ 1, or about 50 %
of its aqueous solubility was placed inside and outside of a 500
molecular weight cut-off bag (Millipore). A high concentration was
required since we expected a significant portion of the phenanthrene
to absorb to the bag. Varying concentrations of a humic acid solution
. (AldrichR) were introduced to the outside of the bag. Both the inside
and outside concentrations of phenanthrene were measured over

time as 14C activity. The concentration of humic acid was measured
using absorbance at 255 nm.

As demonstrated in Figures 1 and 2, we found that both the inside
and outside concentration of phenanthrene decreased as the amount
of humic acid in solution increased. The total amount of
phenanthrene as determined by what is inside and outside of the bag
should have remained the same. The inability to provide a complete
material balance suggested that one of several things was happening:

1. A considerable amount of phenanthrene was absorbing to the
dialysis bag over time and equilibrium was not achieved.

2. The measurement technique (14C activity) was being hindered
by the presence of humic acid both inside and outside of the

bag.

'The bag itself was not counted since it was not completely soluble in
the scintillation fluid. Therefore the material balance could not be
verified as in the other techniques which we tried (ie: fluorescence
quenching and empore disk filtration).

The data for this failed experiment is provided in the following
pages.

147

 

 

 

 

 

 

 

 

 

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151

Protocol #: 9

1‘? MAY 92 20:;-

Time = 10.00
Radionuclide: H3/Cl4
Region A: LL-UL= .0— 12.0 Bkg= .00 22 Sigma=
Region B: LL-UL= 12.0-1Sé.0 8kg: .00 22 Sigma:
Region C: LL-UL= .0- .0 Bkg= .00
QIP = tSIE/REC
Conventional DPM
DPMI = 200900
DPNZ = 106700
810 S4 . 115E CPHA 252A CPHB 2328 DPMl/K BENZ/K $18 1518 FLAG
1 2 nissing vials)
8 3 10.00 426.40 3.06 2720.90 1.21 .00 3399.14 58.696 343
8 3 10.00 426.90 3.06 2740.60 1.21 .00 3423.52 58.731 344
8 3 10.00 425.60 3.07 2722.30 1.21 .00 3401.37 58.514 343
426.30 3.06 2727.93 1.21 .00-3408.04 58.647 343 A
8 4 10.00 387.30 3.21 2426.30 1.28 17.31 3031.77 58.091 341
8 4 10.00 383.10 3.23 2455.80 1.28 .00 3068.40 58.562 343
8 4 10.00 379.60 3.25 2385.70 1.29 14.08 2980.45 58.380 342
383.33 3.23 2422.60 1.29 8.36’3026.86 58.345 342' A
8 5 10.00 356.70 3.35 2249.70 1.33 11.16 2808.48 58.864 346
8 5 10.00 354.50 3.36 2261.10 1.33 .93 2822.16 58.874 348
8 5 10.00 358.60 3.34 2245.60 1.33 18.47 2802.43. 59.291 348
356.60 3.35 2252.13 1.33 10.1835811.02 59.010 347 A
8 10.00 259.60 3.93 1654.70 1.55 .00 2083.00 53.197 309
8 10.00 262.40 3.90 1659.10 1.55 .00 2038.61 52.982 308
8 6 10.00 266.90 3.87 1668.00 1.55 5.57 2099.83 52.999 308
262.97 3.90 1660.60 1.55 .00 2090.48 53.059 308 A
8 7 10.00 236.00 4.12 1502.00 1.63 1.21 1875.88 58.947 345
8 7 10.00 240.80 4.08 1481.90 1.64 '22.97 1849.92 58.774 345
8 10.00 238.00 4.10 1515.00 1.62 1.24 1891.90 58.936 345
238.27 4.10 1499.63 1.63 8.47 1872.61 58.886 345 A
8 8 10.00 196.20 4.52 1203.30 1.82 14.34 1515.95 52.329 304
8 8 10.00 194.10 4.54 1212.20 1.82 3.90 1527.15 52.412 305
8 8 10.00 194.20 4.54 1224.30 1.81 .00 1543.10 52.267 304
194.83 4.53 1213.27 1.82 5.46 1528.74 52.336 2304 A
8 9 10.00 180.60 4.71 1117.20 1.89 14.88 1394.49 58.834 346
8 9 10.00 178.10 4.74 1119.80 1.89 7.19 1397.66 58.648 347
8 9 10.00 177.10 4.75 1118.50 1.89 5.17 1395.89 59.307 348
178.60 4.73 1118.50 1.89 9.07 1396.01 58.930 347 A
8 10 10.00 194.90 4.53 1160.80 1.86 29.13 1467.97 49.563 289
8 10 10.00 195.80 4.52 1178.50 1.84 22.66 1491.74 49.450 286
8 10 10.00 193.20 4.55 1167.50 1.85 20.11 1477.55 49.205 287
194.63 4.53 1168.93 1.85 23.98 1979.08 49.406 287 A
8 11 10.00 159.10 5.01 1001.20 2.00 5.68 1250.24 58.850 345
8 11 10.00 161.10 4.98 992.10 2.01 15.10 1238.45 58.276 345
8 11 10.00 160.40 4.99 986.30 2.01 15.63 1231.27 58.503 345
160.20 5.00 993.20 2.01 12.14 1239.99 58.543 345 A
8 2 10.00 167.10 4.89 1076.60 1.93 .00 1366.60 421343 237
8 12 10.00 159.90 5.00 1078.30 1.93 .00 1370.68 42.360 235
8 12 10.00 163.70 4.94 1079.30 1.93 .00 1370.61 42.228, 237
163.57 4.95 1078.07 1.93 .00 1369.28 42.311 236 A
4 ' 10.00 142.20 5.30 900.40 2.11 2.59 1124.64 58.340 344
4 10.00 152.00 5.13 901.40 2.11 29.11 1124.64 58.115 345
4 10.00 143.00 5.29 891.40 2.12 8.59 1113.27 58.76! 343
145.73 5.24 897.73 2.11 13.44 1120.85 58.405 344 A

152

Lcr=
Lcr=

DiviK)=1.00
DiviH)=1.00

.00

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16
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10.00
10.00
10.00

10.00
10.00
10.00

10.00
10.00
10.00

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140.20
145.50
136.10
140.60

26.00
23.40
127.60
125.67
17213.6
17333.6
17263.7
17270.3

2520
5.34
5.24
5.42
5.34

5.63
5.69
5.60
5.64
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1036.70
1013.60
1004.60
1018.30

803.20
805.70
798.00
802.30
111067
110890
111022
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133470
133694
133634

153

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37.356
37.569
37.423
37.449
59.179
59.314
59.068
59.187
158.73
158.45
158.39
158.52

151E FLAG

196
196
196
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343
344
344
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