Pates and Biological Effects of
Polycyclic Aromatic Hydrocarbons in
Aquatic Systems
Savannah JUver Ecology Lab., Aiken, SC
Prepared for
Environmental Research Lab., Athens, GA
Jul 83
PB83-250191
US. tf
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TECHNICAL REPORT DATA
(Ftteu read liusmdiont on the rmne I* tan coniplritngj
i REPORT NO.
T
t
i
3. P.F.CI,
4. TITLE ANOSUBTITLE
Fates and Biological Effects of Polycyclic Arotratlc
Hydrocarbons in Aquatic Systems
6. REPORT DATE
6. PERFORMING ORGANIZATION CODE
TJS ACCESSION-NO.
~ 250191
July 1QB3 ...„
7. AUTHORlS)
John P. Ciesy, Steven M. Barteil, Peter F. Landrum,
Gordon J. Leversee, and John W. Bowling
». P ERFORMINQ ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Savannah River Ecology Laboratory
U.S. Department of Energy
P.O. Drawer E
Aiken SC 29801
10. PROGRAM ELEMENT NO.
CCULIA
78-0-X0290
12 SPONSORING AGEf.CY NAME AND ADDRESS
Environmental Research Laboratory—Athens GA
Office of Research and Development
U.S. Environmental Protection Agency
Athens GA 30613
13. TYPE OF REPORT AND PERIOD COVERED
Final, 6/78-5/81
14. SPONSORING AGENCY CODE
EPA/600/01
IS. SUPPLEMENTARY NOTES
16. ABSTRACT
This research project was conducted to test the hypothesis that fates of poly-
cyclic aromatic hydrocarbons (PAH) in ecosystems can be predicted by mechanistic sim-
ulation models based on easily measured properties of the compounds in this homolog-
ous series. To accomplish this goal our research efforts were in four major areas:
(I) development of a mechanistic, predictive simulation model based ort kinetic rather
than thermodynamic considerations; (2) development of analytical and quality assuranc
protocols forthe extraction and quantification of PAH associated with biological and
geological matrices; (3) laboratory studies to determine the vectors of and rate
constants for uptake, depuration and biotransformation of PAH by aquatic organisms
and sediments; (These studies also examined the effect of PAH concentration, temper-
ature and other exogenous factors on rata constants and determined whether rate
constants were first order.) and CO a microcosm study to compare the results of
simulation and laboratory scale studies to a larger scale ecosystem study.
KEY WOHOS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lOENTIF I6RS/OPEN IKDfO TEBMS C COSATI i icld/Gfcmp
TIGN STATEMENT
19, 61CUHITY CLASS
UNCLASSIFIED
5. VI t'AOtS
245
RELEASE TO PUBLIC
JO. StCuntTY CLASS (nil (mgef
UNCLASSIFIl'D
23. PRICE
EPA farm iJJO-l (»-7J)
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PB83-250191
EPA-600/3-83-053
July 1983
FATES AND BIOLOGICAL EFFECTS OF POLYCYCLIC AROMATIC
HYDROCARBONS IN AQUATIC SYSTEMS
by
John P. Giesy, Steven M. kartell, Peter P. Landruo, Gordon J. Leversee, John W. Bowling
Savannah River Ecology Laboratory
University of Georgia
P.O. Drawer E
Aaken, South Carolina 29801
Inteiegency Agreement
7B-D-X0290
between
U.S. Department o£ Energy
and
Environmental Protection Agency
Project Oflicor
Harvey W. Holes
Environiaental Systems Branch
Environmental Research Laboratory
Athens, Georgia 30613
RESEARCH LABORATORY
OFFICE OK RESEARCH AND DEVEI,OPMENT
U.S. EMVIRO5JMKNTAL PROTJX^TION AGENCY
ATHENS, GEORGIA 30613
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DISCLAIMER
This report has been reviewed by the Savannah River Ecology Laboratory,
U.S. Environmental Protection Agency, and approved for publication. Ap-
proval does not signify that the contents necessarily reflect the views and
policies of the U. S. Environmental Protection Agency, nor does mention of
trade names or commercial products constitute endorsement or recommendation
for use.
ii
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FOREWORD
Environmental protection efforts are increasingly directed towards
preventing adverse health and ecological effects associated with specific
compounds of natural or human origin. As part of this Laboratory's research
on the occurrence, movement, transformation, impact, and control of envi-
ronmental contaminants, the Environmental Systems Branch studies complexes
of environmental processes that control the transport, transformation, degra-
dation, and impact of pollutants or other materials in soil and water and
assesses environmental factors th?'. affect water quality.
Polycyclic aromatic hydrocarbons (PAH) from natural and man-made sources
are widely distributed in the environment and pose potential health problems
to aquatic animals and humans. An important phase in addressing these pro-
blems is developing an understanding of the cycling and fate of these compounds.
This report presents the development and evaluation of a theoretical, predic-
tive nodel of the fate of PAH based on easily measured characteristics of
the compounds and the environments to which they may be released.
William T. Donaldson
Deputy Director
Environmental Research Laboratory
Athens, Georgia
ill
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ABSTRACT
This research project was conducted to test ~he hypothesis that fates
of polycyclic aromatic hydrocarbons (PAH) in ecosystems can be predicted by
mechanistic simulation models based on easily measured properties of the
compounds in this homologous series. To accomplish this goal our research
efforts were in four major areas. 1) Development of a mechanistic, pre-
dictive simulation model based on kinetic rather than thermodynamic con-
siderations; 2) Development of analytical and quality assurance protocols
for the extraction and quantification of PAH associated with biological and
geological matrices; 3^ ^iborutory studies to determine the vectors of and
rate constants for uptake, depuration and biotransformation of PAH by
aquatic organisms and sediments. These studies also examined the effect of
PAH concentration, temperature and other exogenous factors on rate con-
stants and determined if rate constants were first order; and A) A micro-
cosm study to compare the results of simulation and laboratory scale stu-
dies to a larger scale ecosystem study.
Laboratory studies indicated that anthracene and benzo (a) pyrene are
rapidly biotransfonned by fish and dipteran larvae but not by periphyton
communities. Biotransformation had a significant effect on the steady
state concentrations of parent compound and biotransformation products.
These results demonstrated that predictions of steady state concentrations
based on C-labeled parent compound and the octanol-water partitioning
coefficient of the parent compound would be in error. Thus, the octanol-
water partitioning coefficient would not be a good predictor of the be-
havior of PAH in aquatic organisms. Uptake and depuration rate constants
were first order for fish but not dipteran larvae. Induction of biotrans-
formation and changes of this rate over time means that results frou
short-term pharmacokinetic studies, using radio-labeled compounds, will be
misleading for compounds which are biotransforratd.
Anthracene (approximately 12 Jig*?. ) was acutely t.oxic to bluegill
sunfish dosed in outdoor channels microcosms. This mortality was not
observed in laboratory studies and was shown to be a photo-toxic mechanism.
Therefore, laboratory studies must be conducted under the same lighting
conditions if the results of these studies arc to be realistic represen-
tations of field conditions.
Ihe modeled processes that influenced PAH tjranfiport included losses to
volatilization, photolytic degradation, sorption to suspended particulate
taattcr and sediments and net uptake by biota. The biota in the raodel
included phytoplankton, periphyton, rooted enacrophytes, bacteria, zoopiank-
ton, two functionally defined benthic invertebrate components and two
functionally defined categories of fish. Model simulations were compared
to results of experiments conducted in artificial streams. A 0.6 ptnolar
iv
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solution of Anthracene in ethanol was continuously added into the headwaters
for IS days folio-red by termination of anthtacene input. The Booel accu-
rately predicted the dissolved anthracene concentration through time and
space. Uptake by periphyton was overestimated by the model) however, the
rate of depuration ot anthracene by peripnyton was reasonably simulated.
Photolytic degradation appealed to be the most important pathway ot flux
within the channels, both experimentally and in the simulations.
This report was submitted in fulfillment of Interagency Agreement No.
EPA-7w-l>-X0230 by the Savannah River Ecology Laboratory with the U.S.
Environmental Protection Agency. This report covers the period June 1,
1978 to Hay 31, 1981, and work was completed as ot Hay 31, 1981.
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CONTENTS
Foreword ..... iii
Abstract iv
Figures vii
Tables xiii
Acknowledgments xvii
1. Introduction 1
2. Conclusions 5
3. Recommendations 7
4. Laboratory Studies 8
4.1 Introduction 8
4.2 Anthracene Sorption by Organic Sediments 9
4.3 Effect of Hufflic Acids on Bioavailability and Transport
of PAH 28
4.4 Uptake, Depuration and Biotransformation Kinetics of Benzo
(a) Pyrene and Anthracene by Periphyton Communities ... 40
4.5 Uptake Depuration and Biotransformation of Benzo(a)pyrcne
by the Midge (Chironomous riparius) 56
4.6 Effects of Temperature and Anthracene Concentration
on Uptake, Depuration and Biotransformation of
Anthracene bv Chironomus riparius 70
4.7 Uptake, Depuration and Biotransforraation of Anthracene
By the Claea (Anodonta imbecillis) 86
4.8 Uptake, Depuration and Biotransfontiation of Anthracene
and Benzo(a)pyrene by the Bluegill Sunfish
(Lepoais raacrochirui.) 96
5.0 Simulation Model for Predicting the Fates of PAH in
Aquatic Systems 113
5.1 Introduction 113
5.2 Model Structure Description 115
5.3 Sub«odel Descriptions 123
5.4 Simulation of Anthracene in Channels Microcosms -
Resi'itc and Discussion 152
6.0 Channels Microcosms Studies 169
6.1 Facility Description and Methods 169
6.2 Water 182
6.3 Sediments 190
6.4 Periphyton 193
6.5 Clams 200
6.6 Fish 202
Appendix I 209
References 210
vi
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FIGURES
Figure 4.2.1 Flow diagram of procedures used to spike, extract
and analyze anthracene in stream sediment 10
Figure A.2.2. Relative ion intensities of anthracene. OV101
capillary column, 2 C min. increase in temperature . . 14
Figure 4.2.3. Relative ion intensities of anthtaquinnne. OV101 •
capillary column 2 C min. increase in temperature ... 15
Figure 4.2.4. High pressure liquid chromatograms of anthracene
and anthraquinone extracted from sediment with
35/65 ml acetonitrile/benzene. 254 nm UV detec-
tion. I = interferring peak, AN = anthracene,
Aq - antbraquinonc 15
Figure 4.2.5. Relative ioo intensities of 7 mass fragments
of anthrace- e in benzene 18
Figure 4.2.6. Relation ion intensity of anthracene in sedi-
ment extracts 19
Figure 4.2.7. Relative ion intensities of mass fragments of
anthraquinone standard in benzene 20
Figure 4.2.8. Relative ion intensities of mass fragments from
anthraquinone in sediment extracts 21
Figure 4.2.9. Relative ion intensities of mass fragments from
anthraquinone in sediment extracts 22
Figure 4.3.1. Accumulation of B(a)P <»nd anthracene by D. magna as
a function of time 33
Figure 4.3.2. Salting-out of BaP at six salinities in the pres-
ence of Aldrich huraics 36
14
Figure 4.4.1. Accumulation of C B(a)P by periphyton commu-
nities from UTRC and Castor Creek which had been
colonized for 3 or 5 weeks. Accumulation is nor-
malized to a surface area (a and b) and dry weight
basis (c and d). Each point represents the mean
of 3 replications with confidence interval = 1 SD ... 45
vii
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Figure 4.4.2.
Figure 4.4.3.
Figure 4.4.4.
Figure 4.6.5.
Figure 4.4.6.
Figure 4.4.7.
Figure 4.5.1.
Figure 4.5.2.
Autoradiographs illustrating the deposition of
14C B(a)P in A) Desmidium coarctatum, B) Spondylosimn
pulchrum, C) Netrium digitus, D) Neiilium iridis, and
E) Eunotia sp. All autoradiographs are 500X magni-
fication
14
Percent of recovered C as B(a)P, shaded, and
non-B(a)P, unshaded, extracted from Castor Creek
periphyton. The upper figure represents periphyton
from three week colonization, while the lower
figure represents periphyton from six week coloni-
zation period. Samples of both live and dead
periphyton were taken after 0.25, 4 and 24 h
14
Percent of recovered C ar> B(a)P, shaded and
non-B(a)P, unshaded, extracted from Upper Three
Runs periphyton. The upper figure represents
periphyton from a three week colonization while
the lower figure represents five weeks of coloniza-
tion. Samples of both live and dead periphyton
were taken after 0.25, 4 and 24 h
Histograms of quantities of F>(a)P shaded and
non-B(a)P, unshaded, 14C in Upper Three Runs and
Castor Creek periphyton. Samples of live and
dead periphyton were taken after 0.25, 4 and 24 h
14
Accumulation of C-anthracene by periphyton which
colonized glass slides in LTTRC. Mean bioraass/slide
= 0.4 mg, dry weight-cm . Anthracene concentra-
tion in water = 22 pg • £ . Concentrations are
normalized to an area basis but can be converted to
a biomass basis with the conversion factor given.
Each point represents the mean of 3 slides. Confi-
dence intervals are i SD
Dcsorption of anthracene fro» UTRC periphyton which
had been exposed to 14C-anthracene for 24 h. Each
point represents the mean of three slides. Confi-
dence intervals are ± SD. ?Mean periphyton biomnss
= 0.4 mg, dry weight " ~~
cm
Distribution of B(a)P and metabolites in static
uptake test
14
Depuration of C by C. ripariua with and without sub-
strate. Concentration is expressed os.pg B(a)P • g
(wet weight) chironomid, assuming all C is 8(a)P.
Each point '.i> the mean of 3 determinations ± SD . . .
46
48
49
50
51
52
60
63
viii
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14
Figure 4.5.3. Uptake and loss of C in whole C. riparius, cxo-
skeleton and viscera. Each point represents the
mean of 3 determinations t SO 65
14
Figure 4.5.4. Accumulation of C B(a)P (A) as determined Ly
TLC, and B(a]P plus netabolites (o) expressed as
ng b(a)P • g (vet weight) chironomid. Each
point represents the mean of .1 determinations
± SD 67
14
Figure 4.6.1. Accumulation of C anthracene by C. riparius at
25 and 22 yg • £ . Each point represents the
mean ± 2 SE of 3 replicates. The line represents
the least squares fit of equation 2 72
Figure 4.6.2. Log K for C. riparius at 4 different concentra-
tions of anthracene in water. Estimate ± asymp-
totic 951 CI 76
14
Figure 4.6.3. Depuration of C anthracene by C. riparius in
uncontaninated water and paper towel substrate at
30°C. X ± SE, n = 3 79
Figure 4.6.4. Biotransformation rate after 1 h exposure as a
function of temperature. X ± 2 SE, n = 4 81
Figure 4.6.5. Biotransformation rate as a_function of time of
exposure and temperature. X .+. 2 SE, n = 4 82
14
Figure 4.6.6. Biotransformation of C anthracene at 10, 25 and
30°C. X ± 2 SE, n = 4 83
Figure 4.7.1. Accumulation of anthracene by A. Hnbecillis shell
as a function of time. The fitted line is based on
the first 5 h of uptake only because of Iocs of
anthracene from the water, which did not go to
the clams. This results in a decrease in the
amount of anthracene associated with the shells
(points after 24 h) 90
Figure 4.7.2. Accumulation of anthracene by soft tissues of A.
imbcci 11 is as a function of time 91
Figure 4.7.3. Depuration of anthracene from the clam A.
imbcci His. The data have been fit to two compo-
nent depuration model (Equation 4.7.4) 93
14
Figure 4.8.1. Accumulation of C-anthracene and benzo(a)pyrene
from well water with and without humic ncids.
Humics present (solid circles), no humics (op^n
circles) 101
ix
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14
Figure 4.8.2. Accumulation of C-anthracene by fish and dep]--
tion of C--
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Figure 5.4.5. Simulation of dynamics of anthracene in herbi-
vorous fish , 161
Figure 5.4.6. Simulation of anthracene dynamics in carnivorous
fish 162
Figure 5.4.7. Relative importance of non-advective physical/
chemical processes (solid dots, dashed line) and
biological processes (open circles, solid line)
in total transport of (a) anthracene, (b) naph-
thalene, and (c) benzo(a)pyrene through artifi-
cial streams 164
Figure 6.1.1. View of channels microcosm facility 170
Figure 6.2.1. Anthracene concentrations in reach 1 during the
input period of the abiotic study. The closed
circles represent samples taken st dawn, while
closed triangles represent samples taken at
noon. Each point represents the m°an of repli-
cate samples. The confidence interval is 1 SD 186
Figure 6.2.2. Histogram representing anthracene concentra-
tions in water from reaches 1,3, end 5, during
the biotic study 187
Figure 6.2.3.
Figure 6.3.1.
Concentrations of anthracene associated with
plastic liner during the two channel microcosm
studies. The points which represent samples
taken during the abiotic study are labeled as
such. The other points are from the biotic
study. Earh point represents the mean of 6
samples. The confidence interval is 1 SD . .
189
Uptake and depuration of anthracene by organic
sediments in petti dishes in the channel micro-
cosm. Closed squares represent the concentra-
tion of anthracene on a dry weight basis while
closed circles represent the same data normal-
ized tc au areal basis
193
Figure 6.4.1.
Figure 6.4.2.
Anthracene concentrations in peripLyton in reach
1 as a function of time. Upper figure represents
anthracene'cm
anthracene-g
while the lower figure represent*
, dry weight, pcriphyton
Anthracene concentrations in periphyton in reach
3 as a functiot) of tin.e. Upper figure represents
while the lower figure represents
dry weight, periphyton
anthracene'cra
anthracene'g
197
198
xi
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Figure 6.4.3.
Figure 6.5.1.
Figure 6.6.1,
Anthracene concentrations in periphyton in reach
5 as a function of time. Upper figure represents
anthracene-cm
antbracene*g
-1
while the lover figure represents
dry weight, periphyton
199
Uptake of anthracene by soft tissues of clams
during the period of anthracene input to the
channels. Each point represents the mean of 6
clams. Confidence intervals of 2 SE are present-
ed. The least squares predicted regression curve
for the indicated model is given
Cumulative mortality of bluegill sunfisb in the
channels microcosm. Mean drawn anthracene concen-
trations were 12 (JR*^ • Two cages at each reach
with 8 fish per cage. Time is given as cumulative
exposure to anthracene. Periods of light and
dark are given. *denotes time at which all fish
vere dead
201
203
Figure 6.6.2.
Cumulative mortality of bluegill sunfisb in shaded
and unshaded reaches of the channels microcosms.
The weighted averages (day-night) of anthracene
vere 13 pg-iv-l
n = 13; noon = 7.4, n = 21) and 9.5 dawn = 12.5,
n = 42: noon = 5.6, n = 33) for caches 1,3, and
5 respectively. Two cages with 8 fish per cage
were placed in each reach. *denotes time at which
all fish were dead
204
Figure 6.6.3.
Figure 6.6.
Cumulative mortality of bluegill sunfish after 72
hr of exposure to anthracene in shaded or unshaded
reaches. After 72 hr of anthracene dosing, anthra-
cene inputs were stopped and fish exposed to light . , . 206
Cumulative mortality of bluegill sunfish as a
function of time. Fish vere exposed to 14.6 (Jg
anthracene•£ for 48 h in the dark. Sets of 8
fish were allowed to depurate into clean water
for 24, 48, 72, 96 and 144 h then placed in
clean water in the light. Each set of fish
were placed in the light 0800 hrs and observed
for 48 h 207
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TABLES
14
Table 4.2.1. Extraction of C-anthracene from direct and slurry
spiked UTRC sediment 12
Table 4.2.2 Experimental design to determine effects of sediment
type, equilibration time, moisture content and polarity
of solvent on extraction efficiency of anthracene from
sediment 13
Table 4.2.3 Effect of time of equilibration, mositure content,
sediment type and solvent polarity on extraction of
14C-anthracene from Steel Creek and UTRC sediment ... 24
Table 4.2.4 Anova of experimental results given in table 4.2.1 ... 25
Table 4.3.1 Radio-labeled PAH used in bioavailability studies ... 29
Table 4.3.2 Inorganic salts added to test water and resulting
water quality parameters 30
A
Table 4.3.3 Effect of Aldricb humic acids on PAH accumulation by
D. yagna , 32
Table 4.3.4 Effect of Aldrich htunic acids on PAH accumulation
by D. oajjina . . . 35
Table 4.3.5 Effect of Skinface Pond and Upper Three Runs Creek or-
ganics and particulates on B(a)P accumulation by
Daphnia magna 37
Table 4.3.6 Salting - out of PAH in water with and without humics . 38
14
Table 4.5.1 Bioaccuraulation parameter estimates for total C in
Chironomoua riparius using one and two • compartment.
models 62
14
Table 4.5.2 Biotransformation of C - B(a)P by Chironomous ripart-
us " 66
Table 4.6.1 Uptake (Ku) and depuration (Kd) rate constants in
C. riparius at four concentrations and three tem-
peratures (estimate ± 95% CI) 77
14
Table 4.6.2. Bioconcentration factors (BCF) for C-anthracene in
the midge C. riparius. BCF for total C wa* calcu-
xiii
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lated from K -K " after 10 and 30 h of uptake. BCF
for anthracene was calculated from concentrations of
anthracene at 4 hr. X ± 95% CI . '. 84
Table 4.7.1. First order rate constants for uptake and depuration
of anthracene by A. imbecillis from 31 pg anthracene.
Estimated by Marquardt iterative least squares
procedure 92
Table 4.8.1. Effect of varying exposure concentration on the rate
of uptake of 14C anthracene by bluegills 105
14
Table 4.8.2. Rates of uptake and elimination of C activity in
bluegills exposed to anthracene or bcnzo(a)pyrene
(B(a)P) in stream water 107
14
Table 4.8.3. Distribution of C activity in bluegills exposed to
5.8 pg*£ anthracene (An) or 0.70 |Jg'£ benzo(a)pyrene
(B(a)P) for 4 hours 108
Table 4.8.4. Rates of biotransformfiion in bluegills exposed to
8.9 pg*£ anthracene of 0.96 Mg'ji benzo(a)pyrene
(B(a)P) 109
Table 4.8.5. Comparison of bioconcentration factors determined by
three methods 109
Table 5.2.1. Output from FOAM. Each variable is simulated hourly . . 121
Table 5.J-1. Parameter estimates for consumer components of fates
of aromatic model (FOAM). See Table 5.3.3 for expla-
nation of abbreviations 126
Table 5.3.2. Parameter estimates for primary producer components of
fates of aromatic model (FOAM). See Table 5.3.3 for
explanation of abbreviations 127
Table 5.3.3. Key to parameter abbreviations used in FOAM for con-
sumer and producer components 129
Table 5.3.4. Contribution of light of 10 nm increments to total
spectrum between 300 and 500 not 132
Table 5.3.5. Comparison of observed quantum yield coefficients
for reaction of PAH in air saturated water to pre-
dicted quantum yields based upon regression with
molecular weight 133
Table 5.3.6. Feeding preference (W ) for predator i feeding on
prey (food) items j, and a , fraction PAH assimi-
lated by predator i per unit of PAH ingested in the
form of prey (food) j 141
xiv
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Table 5.3.7. Initial bioroass conditions for simulations reported
here g • dry weight-m
Table 5.3.8. Biological state variables for simulation of anthra-
cene dynamics. See Table 5.3.3 for explanation of
abbreviations 149
Table 5.3.9. Biological state variables for anthracene dynamics
simulation 150
Table 5.3.10. Parameters for the simulation of volatilization
of anthracene 151
Table 5.3.11. Parameters for photolytic degradation.of anthracene.
Quantum yield coefficient = 7.5 X 10~ 151
Table 5.4.1. Predicted and observed concentrations of dissolved
anthracene in channels microcosms 152
Table 5.4.2. Comparison of predicted and observed concentrations
of anthracene in stream sediments 156
Table 6.1.1. Mean water quality of treated well water 171
Table 6.1.2. Recovery and precision of anthracene and anthra-
quinone from various matrices 177
Table 6.1.3. Background and limits of detection for analysis of
Anthracene And Anthraquinoae from various matrices . . . 178
Table 6.2.1. Percent recovery of anthracene and anthraquinonc
from control water samples in abiotic channels
experiment 182
Table 6.2.2. Calculated input of anthracene to channel and
measured values in reach one 183
Table 6.2.3. Concentration (Jg*£ of anthracene and anthraquinone
in water • 184
Table 6.2.4. Percent accountability nM anthracene + nM anthra-
quinone/actual anthracene input (nM) 185
Table 6.2.5. Input and mass balance of anthraccne/anthraquinone
in reach one 188
Table 6.3.1. First order rate constants for uptake and release
of anthracene from organic sediments during the
channels microcosm experiment based on dry weight
of pediment. Data was fit by n = 3, PF < 0.001 for
all regressions 192
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Table 6.3.2. First order rate constants for uptake and release
of anthracene from organic sediments, based on area
of sediment. Data was fit by the marquardt itera-
tive least squares procedure. X ± SE, n = 3, PF
< 0.0001 for all regressions 194
xvi
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ACKNOWLEDGEMENTS
The cooperation and support of the staff of the University of Georgia's
Savannah River Ecology Laboratory (SREL) is much appreciated. The research
and report preparation weve supported, in part, by interagency agreement
No. DE-AC09-76SR00819 between the United States Department of Energy and
SREL. We wish to acknowledge the technical support ot James Cheatham and
Susan Giddings. We wish to thank Hs. Jean Coleman, Tonya Willingham and
Debbie Perks for their help in preparing this report. Karen Brown assisted
with sampling and statistical analyses of experiments on sediment studies.
xvii
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SECTION 1
INTRODUCTION
Polycylic (polynuclear) aromatic hydrocarbons (PAH or PNA) are a
homologous series of compounds composed of 2 or more condensed benzene
rings with occasional incorporations of cyclopentene rings, such as in the
fluorenes or "hetero-octanes" (N, 0 or S). PAH derived from natural
(Andelm&n and Snodgrass, 1974) and man-made sources are widely, distributed
in the environment. PAH occur as natural products in plants and microbes
and natural pyrolytic processes, such as forest fires and volcanic activi-
ty, and human activities such as manufacturing and fossil fuel conversion
(Braunstein et al. , 1977; Harrison et a±., 1975; and Suess, 1976). Inputs
to aquatic systems are due to human activities, as found in east coast
near-shore marine sediments (Kites, et al., 1977) or of natural origin in
sediments of pristine lakes (Brown and Starnes, 1978) and marine sediments
(LaFlamme and Kites, 1979). LaFlamme and Kites (1978) reviewed the sources
of PAH in the environment and concluded that while some of the PAH could be
from natural sources, most of the PAH were from pyrolytic processes due to
human activities. PAH released to the environment by human activities are
due to oil spills and fossil fuel conversion (Neff, 1979). Over 230,000
metric tons of PAH enter the oceans and surface waters of the world each
year (Neff, 1979). The American Petroleum Institute (1978) has compiled a
lengthy review of the sources and environmental concentrations of PAH in
the environment. Inputs of PAH into aquatic systems are expected to in-
crease with the commencement of the synthetic fuels program and emphasis on
coal combustion as a primary energy source (Gehrs e_t al., 1976). After
reviewing the available literature on projected effluent concentrations,
solubility, degradation waste treatment efficiency and acute and chronic
effects of coal conversion effluents, Herbes et al. (1976) concluded that
higher molecular weight polycyclic and heteroaromatic compounds possess the
greatest potential for bioaccumulation, carcinogenic and mutagenic effects
in aquatic animals and man, and acute toxicity to aquatic organisms. Thus.
the importance of developing predictive models of PAH fate in aquatic
systems must be emphasized (Baughman and Lassiter, 1978). For this reason
we undertook two lines of research: 1) to develop an understanding of the
cycling and fate of these compounds including bioaccumulation, sorption,
degradation and transformation in a quasi-natural environment and 2) to
determine effects of PAH compounds on aquatic ecosystems.
Toxic, mutagenic, and carcinogenic properties of PAH have been much
studied (LaVoic et aj.., 1979; Norden, ejt aj.. , 1979). Many PAH arc carcino-
genic or have carcinogenic biotransformation products (Christensen ej. al. ,
1975; Neff, 1978) and may be hazardous to man through bioraagnification or
be directly mutagenic to aquatic organisms (Neff, 1979).
-------
Mechanisms of PAN biotransformation, mode of action, and analyses in
biological and geological matrices have been much studied and this litera-
ture has beec reviewed (Braunstein e_t al., 1977; Jones and Leber, 1979;
Neff, 1979; Bjorseth and Dennis, 1980). However, few studies have attempted
to integrate laboratory, field and simulation studies.
Arsessment of health risks, associated with introduction of PAH into
the environment, depends in part upon quantification of environmental
transport and subsequent dose concentrations experienced by inhabitants
(Crawford and Leggett, 1980). Estimates of transport and dose are inde-
p*ndent of the specific nature of the threat to human health, either di-
rectly through contamination of potable water, for example, or indirectly
through damage to ecological life support systems.
We have the recent experiences, for example, of worldwide distribution
of DDT and PCB in aquatic life of many rivers and bays, mercury and cadmiua
poisonings of the populations in certain industrial areas, and vinyl chlo-
ride exposure of industrial workers. These experiences arose from acci-
dental release, uncontrolled industrial releases, and unsafe overuse. In
order to avoid these types of experiences in future years with the thou-
sands of new chemicals being released to the environment, a toxic effects
testing strategy is needed which will "flag" potential problem contaminants
prior to their widespread dispersal. This testing strategy should cover
both plant and animal species and be concerned with acute and chronic
exposures. Because of restrictions on time, resources and tiuraan cognitive
capacity, a number of techniques have been established to assess probable
effects of trace contaminants. These techniques include toxicity tests on
individual or standard organisms, individual bioaccumulation tests, mea-
surement of physical properties of the chemical, environmental monitoring,
studies in simple systems and investigation of transport and degradation.
To depend only on retrospective environmental studies to elucidate the
knowledge required to avoid adverse effects is to court disaster. Rather,
what is urgently required is a systematic program of investigation the
scale of which time and resources permit expeditious acquisition of the
essential data and understanding. While the tests listed above provide
useful information, they do not consider complex interactions between
biotic and abiotic components of the environment and do not allow for
evaluation of complex biological interactions. Over time, very subtle
effects may have serious impacts on populations or communities as they
aodify complex interdependences.
The so-called "benchmark11 techniques have been developed on the as-
sumption that the chemical and physical characteristics of a trace contami-
nant will deteimine its effects on the biocenose and how it fluxes and
cycles through the environment and that the fate of a compound can be pre-
dicted by simple first or second principles. While this assumption has not
been tested and may, in fact, be untestable, correlative studies indicate
that the assumption is somewhat valid. However, low predictability and
high variability indicate that the correct parameters are not being mea-
sured for each compound or that the interactions between the compounds cf
interest with biotic and abiotic components are non-additive. That is,
-------
there are significant interaction terms which can not be evaluated by
staple tests or knowledge of the first principles of trace contaminants.
Because of the vast difference between simple laboratory tests and
complex field situations, scientists have formed conceptual and operational
bridges between the two systems. These include models of theoretical con-
ceptualization of how complex systems operate. Computer science has pro-
vided the bookkeeping .capacity to describe these systems with complex
linear and non-linear functions. The science of modeling and environmental
predictability suffers from a lack of steady state conditions, rate con-
stants and an Mnderslanding of the most important parameters for increasing
the power of predictability. If the correct physical and cheaical param-
eters of both an organic compound of interest and the environment to which
it is being released are known, a model could be constructed to predict the
gross movement of the compound of interest within that environment. This
model could also include degradation and transformation due to hydrolysis,
photolysis and by biota. Another useful type of model of ecosystems are
the simplified subsets of ecosystems called microcosms (Metcalf et al.,
1971; Lee and Takahashi, 1*77; Lu et al.., 1977; Giesy, 1980). We feel that
a microcosm approach (artificial streams) allowed us to evaluate a predic-
tive model under more natural, complex conditions with control of inputs
and replication of the experimental conditions.
For example, most information on plutonium indicated that it was not
ecologically hazardous since it was not readily taken up by plant roots or
assimilated through the intestinal wall of animals. Hence, its presence in
the environment was more a problem of physical transport in air and coils,
end its biological significance, with regard to effects, was limited to
inhalation or movement into wounds. Later, field data showed quantities of
plutonium in trophic levels and tissues where it was not expected. Studies
were conducted which showed that in the environment plutonium can be or-
ganically complexed by microorganisms in the soil, and that it was then
much more available for transfer through food chains all the way up to
vertebrate consumers of the vegetation. Effects within the system could
then be predicted based on new modes of entry within the intact system, and
a change in rate constants for transfers between components within the
system.
Thousands of different PAH compounds are chemically possible. There-
fore, application of elaborate screening protocols (Duthie, 1977) to indi-
vidual PAH in order to estimate major processes of transport, accumulation,
and .degradation is impractical for purposes of rick analysis. However, it
IB important to answer questions about these compounds such as: Can human
exposure be limited by more rigorous drinking water treatment aimed at
removing organics? Do the various compounds become concentrated in and
magnified by trophic levels culminating in human exposure? Is concentra-
tion in various trophic components proportional to time and concentration
of exposure? What are the rates of accumulation and elimination from
various components? What are the rates of uptake and elimination relative
to immobilization rates by sorption processes and photo- and roicrobial
-------
degradation rates. Because of the large number of compounds and environ-
ments to be evaluated a certain level of predictability must be achieved.
This study tested the hypothesis that a theoretical predictive model
of the fate of PAH compounds or classes of compounds in a given environ-
ment, or class of environments, can be constructed based on characteristics
of the compound of interest and the environment to which it is released.
This report describes a test of the hypothesis that the transport of three
PAH, anthracene, naphthalene, and bcnzo(a)pyrene, in lotic systems
(streams, rivers, reservoirs) could be predicted from the fundamental
chemistry of individual PAH which embodies sufficient information for
prediction. While we do not feel that a simple characteristic, such as
nolecular weight is necessarily the best parameter, from which to predict
environmental fates, we feel that the law of parsimony dictated t'at we try
a simple parameter, such as molecular weight, to try to make predictions
from and determine where this simplification fails to predict accurately.
Many modeling efforts rely on measured properties, such as octanol-water
partitioning coefficients, which are a function of first principles of a
compound. These measured parameters often integrate several properties of
compounds, which is an advantage because more information can be included
in a single empirically measured value. However, Ihese coefficients must
be measured, which is time-consuming and they may be less accurate than
molecular weight measureoients.
We feel that a coordinated synthesis of information on ecosystem
structure and function is required to assess environmental impacts of any
technology which must ultimately be interfaced vith the environment. While
this research was on PAH compounds (anthracene and benzo(a)pyrene specific-
ally) it tested the hypotheses that valid generalizations about the be-
havior of general classes of organic compounds in complex environments can
be made from knowledge about the compounds obtained in relatively simple
laboratory studies and the environments to which these compounds p.re re-
leased. Knowledge of this type can be transferred to other orgar.ic com-
pounds and has broad applicability.
Anthracene was chosen as a model PAH for laboratory, field and simu-
lation studies because it is a commercially important PAH which is produced
in large quantities and used extensively as a reagent in organic synthesis
(Archer et al., 1979). Anthracene has also been used frequently as a model
PAH for studies of environmental fate and transport in aquatic syotetrs
(Ausmus et al., 1980) or physiological disposition in aquatic biota (Roubal
cj. a1., 1977). Anthracene is non-carcinogenic (MAS, 1972) and relatively
uon-toxic (HAS, 1972; Dcickman and Gerarde, 1969).
-------
SECTION 2
CONCLUSIONS
The results of the laboratory studies demonstrated that PAH are rapid-
ly biotransformed by bluegill sunfish and chironomid larvae but not unionid
clams or periphyton assemblages. Biotransformation rates were affected by
temperature and time of exposure. The rates of biotransfonnation also
affected the bioconcentration factors predicted from short-term pharmaco-
kinetic studies. Temperature and food ration also affected rates of uptake
and depuration. Uptake and depuration were first-order with respect to
forcing function concentrations. Depuration was generally multiphasic with
some of the biotransformation products bound to tissues, such that they
were very slowly depurated.
Recovery of PAH from geological materials such as sediments, was
inversely proportional to time of exposure. Internal standards added at
the time of extraction did not allow accurate determination of extraction
efficiencies. Drying of sediments resulted in reduced recovery of anthra-
cene from sediment. Capillary gas-liquid chromatography coupled to mass
spectrooetry (GC/MS) showed that anthracene could be extracted from sedi-
ments and separated from interfering peaks but anthraquinone (a transforma-
tion product of anthracene) could not.
Dissolved, naturally occurring organic acids (humic acids) reduced the
availability of anthracene, benzo(a)pyrene and dirccthylbenzanthracene to D.
magna but increased the availability of 3-roethylcholanthracene and dibenz-
anthracene. The presence of particulates also reduced the availability of
PAH to D. magna.
The simulation model, Fate of Aromatics Model (FOAM), was developed to
predict the fates of PAH from molecular weight of the PAH of interest and
parameters of the ecosystem to which it is to be released. FOAM accurately
simulated and predicted the flux along physical-chemical pathways. How-
ever, the model was less accurate in predicting the accumulation and bio-
tmnsformation of PAH by aquatic biota. Future versions of predictive
simulation models shoulu be kinetically based, os FOAM is, if accurate
information on cycling is to be predicted. However, this type of model
requires a great amount of information. Because of the scale of the input
parameters, models such as FOAM will be useful in describing overall pro-
cesses and fluxes along different pathways but will not be very n ful in
simulating the concentrations of PAH and PAH transformation [not.jcts in
individual biotic components. Also, some of the physical processes, which
are important in determining the fates of PAH in natural syntens, are
discontinuous functions or catastrophic events, such as stonas, which do
not lend themselves to mathematical simulations. Therefore, models of the
-------
type developed here will always be limited to relatively gross predictions.
Accurate predictions or concentrations in individual types of organisms may
not be attainable.
The channels microcosms were useful for testing the reliability of
FOAM to simulate the behavior of PAH in a complex ecosystem. However, the
greatest utility of the-channels microcosm was in allowing studies to be
conducted under more natural conditions than allowed by laboratory systems.
From these studies we learned that exposure to sunlight during exposure to
anthracene was acutely toxic. Thus, laboratory studies do not accurately
predict toxicity observed under more natural conditions. While microcosms
may not be used as a central monitoring tool, they are useful in studies of
classes of compounds and to verify laboratory and sinulation conclusions.
Because of their scale, however, microcosms will never be useful in vali-
dation of long-term or global simulation models. The test of the benchmark
hypotheses was only partly supported by our studies. Future simulations
will need to consider more complex measures of chemical behavior. The
proposed use of octanol/ water partitioning coefficients shows promise for
predicting uptake by organisms but not biotransformation. Thus, the bench-
mark approach will probably not give adequate predictions of the dynamics
of organic compounds in complex environments.
-------
SECTION 3
RECOMMENDATIONS
Future studies of the fates and effects of trace contaminants should
be conducted in laboratory, field and siraulat.lcn modes concurrently. All
three modes of investigation added to the overall understanding of the
dynamics of PAH in aquatic ecosystems.
Simulation models should be developed to predict general behavior of
PAH in aquatic systems. That is, to determine when the greatest mass of
PAH accumulates and where the most sensitive ecosystem components are.
Where physical and chemical processes dominate, simulation models will be
able to accurately predict the overall dynamics of PAH, but tare events of
large nagnitude will reduce the accuracy of predictions on a short-tt;rm
basis. Optimization of time step duration relative to sy:.teu> level vari-
ability needs t.o be further investigated to increase the accuracy of pre-
dictive models.
The current state of predictive simulation models will not allow the
accurate prediction of concentrations of single P^H in individual species
but can be useful in simulating overall procc< . es in a gross manner.
Future simulations should be kinetic in nature but the relationships used
to predict rate constants ne~d to be based on structure-activity relation-
ships.
The channels nicrocosms used in this study were sufficient to test
some simulation processes and we recommend tne use of this type of a system
in future studies. However, microcosms of this magnitude will not he-
useful as screening tools. The utility of the realism of such systems was
demonstrated by the photo-toxir effect observed in the microcosm, which was
not observed under laboratory conditions. We suggest this type of system
needs to be used to validate processes which are indicated by laboratory
and/or simulations because they allow testing in a more complex and more
natural system than that of the laboratory, while not releasing trace
contaminants to the biosphere.
-------
SECTION 4.0
LABORATORY STUDIES
SECTION A.I
INTRODUCTION
A series of laboratory studies was conducted to determine rate con-
stants for uptake, depuration and biotransformation of PAH in several iso-
lated components of aquatic systems. The components studied were water,
sand, organic sediments, peripbyton, dapnnia, chironomids, fish and clams.
Beside determining rate constants for uptake, depuration and biotransfor-
nation, these studies investigated the effects of factors such as tempera-
ture, presence or absence of substrate, and concentration of PAH on rate
constants. The goal of these studies was to supply independent estimates
of rate constants and to determine the precision with which these rate
constauts could be measured in the laboratory. The rate constants could be
used to parameterize the simulation model as well as to develop statistical
relationships between rate constants and first principles of the compounds
of interest.
Subsequent comparison of rate constants and state variables measured
under controlled laboratory conditions could be compared to those observed
in microcosm studier and those predicted from simulation models. Such
comparisons can provide estimates of relative variability as well as rela-
tive importance of pathways and interactions to be used in formulating and
modifying the predictive simulation model.
-------
SECTION 4.2
ANTHRACENE SORPTION AND DESORPTION BY ORGANIC SEDIMENTS
INTRODUCTION
When PAH are added to aquatic systems they rapidly become associated
with suspended and bottom sediments (Dunn, 1976; Lee and Takahashi, 1977;
Huller and Bohnke, 1977; Lee et al., 1978; Ciddings et aJL., 1978; Herbes
and Schwa 11, 1978; Teal e_t al_., 1978; Prahl and Carpenter, 1979; Gearing et
al., 1980; Hinga et al. , 1980). A number of techniques for extracting
organic compounds from solid matrices arc available and different extrac-
tion efficiencies have been reported for each (Kookc e_t al., 1981). There-
fore laboratory studies were designed to determine the best extraction
conditions and quantification techniques. Rate constants for sorption of
anthracene by organic sediments were also determined.
MATERIALS AND METHODS
Extraction Procedures
The first set of experiments was conducted to determine the best ex-
traction protocol (Figure A.2.1). The methods which were common to these
two experiments are given first, with the methods which were specific to
each experiment afterward.
Two different sediments were used in these studies. Upper Three Runs
Creek (UTRC) sediment is a fine, silty sediment high in organic matter (•>•
20% by weight). Steel Creek sediment is a coarse, sand-clay mixture with
little organic matter. Sediment from the two streams was collected with a
glass beaker and sieved through 5 ma opening stainless steel screen into a
stainless steel bucket. C-anthi_acene used to spike the sediments had a
-1
specific activity of 3.3 mCi'mmol . All soxhlet extractions were done for
18 h. Liquid scintillation counting was done using 12 mis of Research Pro-
ducts International 3d70b counting cocktail. Counting time was 10 minutes
per sample witti a Beckman Model LS 8100 liquid scintillation counter.
High pressure liquid chromatography analyses were don? on a Varian
Model 5000 LC, which was equipped with a V» -ian 30 cm HCH-10 reverse phase
column operated at 30°C, and a flow rate of 1 ffil-min . Solvents were 35%
acetonitrile in water initially, programmed to 100% acetonitrile in 40
minutes, held at 100% for 10 minutes, with a return to initial conditions
for 5 minutes before the next injection. Injections were done automatic-
-------
ILVftKT ]*OO »f 0<«*
-------
ally by a 25 pi sample loop. The detector was a 254 OJD fixed-wavelength uv
detector, connected to a Varian CDS 111-L integrator, and a strip chart
recorder. A fluorescence detector with 360 ma excitation and > 460 nm
emission wavelength filters, connected to a second strip chart recorder was
operated downstream from the UV detector. Quantitation was by the internal
standards method with chrysene as the internal standard.
14
Combustion of sediment, for unextracted C was done on a Packard
Tricarb sample oxidizer. C-CG was trapped in 7 ml cf a CO trapping
agent and added to 12-15 ml of counting cocktail. Prior to combustion,
sediment samples, ^ 250 mg each, were mixed with cellulose powder and
Combustaid to improve -combustion efficiency.
The first experiment was conducted to determine the solvent system
which allowed the greatest recovery of anthracene from sediment, while
minimizing the extraction of interfering compounds. In addition, we wanted
to determine if direct spiking and more natural incorporation gave similar
estimates of extraction efficiency. The flow diagram for this experiment
is given by the solid line in Figure 4.2.1 Three solvents were used to
extract UTRC sediment, which had been slurry spiked. Three aliquants of
lOg, wet filtered weight were soxhlet extracted with each of three solvent
systems (Table 4.2.1).
The second experiment was conducted to compare variation in extraction
efficiency due to sediment type, time of equilibration between sediment and
anthracene, the effect of sediment moisture on the extraction of anthracene
from wet or dry sediment, and solvent type (p'.larity). The flow diagram
for this experiment is given by the dashed liiy? in Figure 4.2.1. The
experimental design was a completely randomized 2 factorial with 3 repli-
cations per treatment combination (Table 4.2.2). Spiked sediment slurries
were mixed for 24 h or 1 wk before extraction. Wet sediment samples were
soxhlet extracted immediately after filtration. Dry sediment was air-dried
in a hood for 24 h. Extraction time was 18 h with either 100 ml of benzene
or 35 ml of acetonitrile + 65 ml of benzene. Crude extracts were sampled
for quantification of C activity.
Anthracene and anthraquinone peaks were separated on an OV101 capil-
lary column and mass spectra recorded to determine if the compounds which
were being spearated and identified were anthracene and anthraquinone. The
relative ion intensities of the peaks wnich we had identified as anthracene
and anthraquinone are given in Figures 4.2.2 and 4.2.3 respectively. The
retention indexes (RI) vene calculated with equation 4.2.1. The HPLC
protocol separated anthracene, anthraquinone and chrysene well (Fig.
4.2.4). However, sediment extracts often contained a compound which eluted
very near Anthraquinone (Fig. 4.2.4). This peak was almost always present
but often obscured the anthraquinone in spiked samples. The retention
indices of the anthracene standard and an anthracene sample extracted from
sediment were 1717 and 1712 respectively. The retention indices of anthra-
quinone standard and raasple were 1807 and 1789 respectively. The retention
indices indicated that the peaks we had chosen as anthracene and anthraqui-
none in our chromatograms of sediment extracts were accurate. However, to
11
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TABLE 4.2.1. EXTRACTION OF 14C-ANTHRACENE FROM DIRECT AND SLURRY SPIKED UTRC SEDIMENT
Fraction Recovered
Treatment
1 Direct Spike
2 Slurry Spike
3 Slurry Spike
4 Slurry Spike
N
3
3
3
3
Solvent System" x
35 ml ACN * 65 ml $H .976
35 ml ACN + 65 ml H .808
35 ml ACN + 65 ml Chex .771
16 ml MEOH + 42 ml ATN + ml CHEX .898
SD CV
.020 2.05
.030 0.37
.015 1.95
.027 3.01
ACN = Acetonitrile
$H = Benzene
ATN = Acetone
CHEX = Cyclohexane
MEOH = Methanol
-------
TABLE 4.2.2 EXPERIMENTAL DESIGN TO DETERMINE EFFECTS OF SEDIMENT TYPE,
EQUILIBRATION TIME, MOISTURE CONTENT AND POLARITY OF SOLVENT
ON EXTRACTION EFFICIENCY OF ANTHRACENE FROM SEDIMENT
Main Effects
Sediment Type Spike Time Moisture
Steel Creek 24 hr Vet
Dry
1 wk Vet
Dry
UTRC 24 hr Vet
Dry
1 wk Vet
Dry
Solvent
System
«H
4>H/ACN
4H
$H/ACN
JS/ACN
«H
4>H/ACN
«>H/ACN
.„
(|iH/ACN
<>H
(J>H/ACN
<»H
$H/ACN
* Benzene, ACN = Acetonitrile.
13
-------
lOO-
ts 80-
0s
*" 60-
H 40-
co
Z 20-
UJ
h- 0-
- 100-
g 80-
i- eo-
-» 40-
UJ
K 20-
n-
ANTHRACENE
1
2
., ,J
T I i i T i i ; ; r \ i i i •
!0 40 60 80 100 120 140 160
!,
180 200 220 240 260 280
MASS OF FRAGMENT
300 320
Figure 4.2.2. Relative ion intensities of anthracene. OV101 capillary
column, 2°C min. increase in tcmprr.iturc.
-------
too-
5 80
> 60
t 40
CO
2 2G-
LU
~ 100
UJ
> 80
20
ANTHRAQUINONE
40
60
80
100
120 140
160
180 200 220 240 260 280 300 320
MASS OF FRAGMENT
Figure 4.2.3. Relative ion intrnsitirs of anlhraquinonc.
column 2°C min. increase in temperature.
OV101 capillary
15
-------
0 4 8 12 16 24 32 40 48 56
TIME (min)
Figure 4.2.4. Hij;h pressure lirjrji! chrcmaloRrams of anthracene nti'l .inthr.i-
quino/ic exlr.irtcd from scdimont with 35/65 ml .icelonitrilc/
bcnr.cnc. 254 nm UV dctrctioti. 1 = inLt-rfcrrinR pe.ik, AN =
anthracene-, A(| = anthr.iqiiinono.
16
-------
check the accuracy of our determinations further we examined the mass
spectra of these peaks.
The retention indices and matching coefficients were calculated using
equations A.2.1 end 4.2.2.
SU - SRI „„„ 4.2.1
RI = SR2 - SRI X 2°°
where: RI = Retention Index
SU = Scan Number of unknown peak
SRI = Scan Number of first hydrocarbon standard peak
SR2 = Scan Number of second hydrocarbon standard peak
The matching coefficient of our sample peaks and standard peaks were calcu-
lated from the mass spectra of anthracene ana anthraquinone (Figs. 4.2.5 -
4.2.9) and equation 4.2.2. The matching coefficients for anthracene and
anthraquinone were 81.4 and 99.9% respectively.
- RISA)/J x 100% 4-2-2
MC =
n
Z(RIST + RISA)
1=1
where: MC = Matching Coefficient
RIST = Relative intensity of each mass fragment in the standard
peak
RISA = Relative intensity of each mass fragment in the sample
peak
l - ith ion fragment
n = Number of confirming ions
A laboratory study was performed to determine the rate constants for
uptake and depuration from a quiescent sediment. Upper Three Runs Creek
sediments were .placed in crucibles with a volume of 4.8 ml and top surface
area of 4.2 cm . Crucibles were placed in a flow through exposure system
and exposed to 35 pg'£ of C-anthracene. The flow rate through the
system was adjusted so that the concentration of anthracene in the water
was not significantly depleted due to uptake by the sediment. The uptake
rate constant was calculated by assuming first order kinetics and initial
rates conditions.
17
-------
ANTHRACENE STANDARD IN BENZENE
CO
UJ 100
Z 50^
— 0
Z
o
UJ
UJ
o:
100% = 10376
100% = 18320
100% =7172
100% =7948
100% = 13160
A
100% =1143803
177
100% = 17664
100% =119616
179
178
176
152
151
89
/\
T"
i 1 ] 1 1 —, , ,
950 1000 1050 1100 1150 1200 1250 1300 1350
SCAN NUMBER
Figure 4.2.5. Rcl.'it ivo ion intensities of 7 mass fr.i>;mcnts of anthracene
in benzene.
18
-------
ANTHRACENE IN COMBINED SEDIMENT EXTRACTS
cn
z:
LU
\-
o
LJ
UJ
ce
100
50 ^
0
100% =13600
f
100% = 81088
100%= 7724
100% = 13288
100% =
100% = 6768
y\
100% =444928
s^ ^
100% =6283264
179
178
177
176
152
151
Til
900 9oO 1000 1050 1100 1150 1200 1250
SCAN NUMBER
Figure 4.2.6. Relation ion intensity of anthracene in sediment extracts,
19
-------
ANTHRAQUINONE STANDARD IN BENZENE
1250
1300 1350
1400 1450 1500
SCAN NUMBER
1550
1600
Figure 4.2.7. RolaLivc ion intriisi tirs of ni.iss fragments of ant Iir.'ujui nono
staiid.iril in brnzcuc.
20
-------
ANTHRAOUINONE IN COMBINED SEDIMENT EXTRACTS
LU
o:
__— \_ --v _ _s*~ \^_ . ,
100%
= 6340508 Til ^
1300 1350 1400
SCAN NUMBER
1450 1500 1550
Figure ft. 2. R RrKitivo io:i inLcn.siLicr of .nnss f r.ij-.int'iiL:; from •intlir.T
ii) sediment extract:;.
21
-------
ANTHRAQUINONE IN COMBINED SEDIMENT EXTRACTS
100
CO
z
UJ
2
o
LJ
UJ
a:
50-
; 1 1 1 1 1 1 r
1050 1100 1150 1200 1250 1300 1350 1400 1450
SCAN NUMBER
Figure 4.2.9. Relative ion intensities of mass fragments fiom antlirj-
quiuonc in sediment extracts.
22
-------
RESULTS AND DISCUSSION
Solvent Systems
*
1A
The recovery of C-anthracene added to the samples immediately before
extraction did not give the same extraction efficiency from samples, which
had been spiked as a slurry (Table A.2.1). Thus, spikes added just prior to
sediment extraction are not useful in determining the efficiency of an
extraction procedure for extracting anthracene from a particular sediment.
The greatest extraction efficiency of "naturally incorporated" anthra-
cene was by the most polar solvent system, which was methanol, acetone and
cyclohexane (Table A.2.1). However, this solvent mixture extracted much of
the polyphenolic humic substances from the sediment which could not be
easily separated from anthracene before analysis. The mixture of aceton-
trile and cyclohexane yielded anthracene in two solvent phases and was not
practical when all of the relative merits of the solvent systems were
considered. We adjudged the acetontrile-benzene solvent mixture to be the
most practical extraction system. The recovery of anthracene, using the
•cetonitrile-benzene mixture was only slightly less than that with the more
polar mixture but the selectivity for anthracene was greater.
The results of the factorially designed experiment are presented as
mean recovery and standard deviations of the factorial main effects (Table
4.2.3) and analysis of variance (Table A.2.A). All of the main effects
were statistically significant. This indicates that all of the factors
examined significantly affect the efficiency of extraction of anthracene
from sediment. The two-way interaction terms between equilibration time
and moisture content and equilibration time and solvent polarity were also
significant so that the exact magnitude of the main effects of these treat-
ments can not be interpreted directly. The three-way interaction terra was
also statistically significant. Thus, any discussion of the two-way inter-
actions must be guarded. The two-way interaction between moisture content
and solvent polarity was highly significant for Steel Creek sediment but
not statistically significant for the more organic sediment from UTRC
(Table A.2.A).
Similar generalizations could be made for both the sediment types
studied. The longer anthracene is equilibrated with sediments, in an
aqueous slurry, the lower the recovery (Table A.2.3). This is probably due
to partitioning into clay IntXice spaces and sediment organic matter.
Incomplete extraction of PAH fro.n sediments has been a continuing
problem and has affected the qualitative as well as quantitative analytical
results (Gearing et al. , 1978). Lake £t al. (1980) reported that because
of varying extraction efficiencies clos
-------
TABLE 4.2.3. EFFECT OF TIME OF EQUILIBRATION, MOISTURE CONTENT, SEDIMENT
TYPE AND SOLVENT POLARITY ON EXTRACTION OF C-ANTHRACENE
FROM STEEL CREEK AND UTRC SEDIMENT
Treatment >C
24hr,
24hr,
24hr,
24hr,
Iwk,
Iwk,
Iwk,
Iwk,
Main
Wet,
Wet,
Dry,
Dry,
Wet,
Wet,
Dry,
Dry,
*H
(>H/ACN
4>H
(|iH/ACN
H
4>H/ACN
_a
X
.9?!
.879
.454
.707
.315
.547
.455
.533
Steel Creek
SD
.037
.024
.047
.026
.017
.032
.003
.010
3
2
10
3
5
5
0
1
CV
.83
.72
.4
.73
.23
.77
.58
.82
_a
X
.796
.783
.819
.860
.253
.470
.719
.741
UTRC
SD
.040
.061
.026
.012
.130
.035
.038
.004
CV
4.
7.
3.
1.
51.
7.
5.
0.
97
81
12
34
5
49
31
59
Effects
Spike time-24hr
Moisture-
Solvent-
System
Iwk
Wet
Dry
H
H = Benzene, ACN = Acetonitrile
24
-------
TABLE A.2.4. ANOVA OF EXPERIMENTAL RESULTS GIVEN IN TABLE 4.2.1
ro
Source
ACSpike Time)
B(Moisture)
C(Solvent System)
A x B
A x C
B x C
AxBxC
Error
Total
DF
1
1
1
1
1
1
1
16
23
SS
.5049
.1192
.0832
.2452
.0075
.0138
.0980
.0110
1.0830
Steel Creek
MS F
.5049 695. 45a
.1192 164. 19a
.0832 114.60*
.2452 337. 74a
.0075 10.33a
.0138 19.018
.0980 134.99°
.0007
SS
.4334
.2623
.0269
.1525
.0166
.0074
.0235
.0520
.9746
UTRC
MS F
.4334 133. 75a
.2623 81.003
.0269 8.30a
.1525 47.07a
.0166 5.12b
.0074 2.29 NS
.0235 7.25b
.0032
Significant at P < 0.01
Significant at P < O.fj
NS = Not significant at P < .05
-------
PAH are generally extracted from wet sediments (Windsor and Kites,
1979) because it has been observed that drying sediments reduces the. re-
covery. This effect may be due to volitalization or to other physical
processes which cause the PAH to bind more tightly to sediments upon dry-
ing. In this study we observed greater extraction efficiercies from wet
Steel Creek sediments and dry UTKC sediments. This nay be due, in part, to
the different organic contents of the two sediment types. This accounts
for the equilibration time-moisture interaction term. After being equi-
librated for a longer period of time the extraction efficiency was. no
longei affected by sediment moisture because of migration of anthracene
into organic and donon spaces. The benzene-acetonitrile solvent system was
significantly better at recovering anthracene from both sediment types.
From the mass fragment spectrum for anthracene (Fig. 4.2.3) we select-
ed masses 179, 178, 177, 176, 152, 151 and 89 and monitored the relative
ion intensity of a standard in benzene (Fig. 4.2.5) and determined chat our
standard was pure. We then monitored the relative ion intensities of
masses 179, 178, 177, 176, 152, 151 and 57 in a sediment extract. The fact
that the onset of all of these peaks was in the same scan number indicates
that all of the material which eluted in this peak was anthracene. An
analysis of our anthraquiaone standard in benzene was done for mass frag-
ments 209, 208, 188, 152, 151, 150 and 76 (Fig. 4.2.7). This analysis
showed that our anthraquinone standard was also pure. A similar analysis
of mass fragments 209, 180, 152 and 57 (Fig. 4.2.8) and mass fragments 209,
208 and 160 (Fig. 4.2.9) in sediment extracts in benzene demonstrated an
impurity in the peak in our samples which we had tentatively identified as
anthraquinone. The 209 mass fragment peak in scan 1390 is not in the same
scan as the 208 aau 160 mass fragments, which have peaks in scan 1375 (Fig.
4.2.9). This information indicates that there is a unknown compound which
also has 208 and 160 mass fragments, as does anthraquinone, which elutes
slightly sooner than those from anthraquinone. This compound does not seem
to have a very intense 209 mass fragment. Therefore, we did not report
anthraquinone recoveries from our sediment. Maher e_t a\. (1978) also found
colored organicE were extracted from sediments which interfered with subse-
quent quantification of PAH compounds. In a study of extracts free marine
sediments, Overton et al. (1977) found that capillary column chromatography
was able to distinguish between indigenous hydrocarbons of contemporary
origin and those known to be associated with fossil hydrocarbon pollution
of marine sediments.
First-Order Rate Constants
The first order rate constant for sorption was reported on both a mass
and area of sediment basis. Based cm mass of sediment the rate constant
for uptake was 0.04 min , assuming a density of approximately 1 for the
cilty sediment used in this study. While the sediment density is slightly
greater than 1, this will not significantly affect the rate constant. The
first order rate constant for sjorptionj. based on surface area of sediment
was found to be 0.009 ml • cm • min . These values relate to the rate
26
-------
of sorption as well as diffusion into the quiescent sediment and are not
the rate constants which would be derived for sorption in completely mixed
systems.
27
-------
SECTION 4.3
EFFECT OF HUHIC ACIDS ON BIOAVAILABILITY AND TRANSPORT OF PAH
INTRODUCTION
Evidence suggests that the most important pathway of bioaccumulation
of PAH is direct uptake from water by simple partitioning into lipids
(Neeley, et al., 1974). It has been demonstrated that humics in freshwater
bystems may form stable complexes affecting the transport of trace organic
compounds including pesticides (Wershaw, et al., 1969) and cholesterol
(Hassett and Anderson, 1979). In marine systems, dissolved organic matter
(DOM) reportedly increased the solubility of n-alkanes (Boehm and Quinn,
1974) and decreased the uptake ot aromatic and other petroleum hydrocarbons
by the vivalve Mercenaria mercenaria (Boehm and Quinn, 1976). It is gener-
ally believed that DOM in rivers is precipitated on exposure to seawater
and deposited in estuarine and nearshore marine sediments (Gardner and
Kenzel, 1974; Hedges and Parker, 1976). The potential for deposition of
trace contaminants in estuarine sediments is largely unknown.
The effects of humics on direct uptake of PAH by Daphnia magna and the
potential for salting-out or co-precipitation of PAH-humics at estuarine
salinities were determined in laboratory studies. Studies on humics as
they affect PAH accumulation in D^ magna were conducted to detinaint ]) if
a "standard" htunic acid (Aldrich ) at one concentration (2 mg'£ DOC)
affected the bioaccumulation of several PAH, 2) if observed effects in some
PAH varied predictably with humic concentration, 3) if observed effects
changed over a range of PAH concentrations, some of which exceeded limits
of water solubility, and 4) if humics in natural waters behaved similarly.
In addition, the potential for salting-out of PAH-humics was determined for
six PAH at one concentration of Aldrich humics in 20 /oo artificial
seawater.
METHODS AND MATERIALS
Benzo(a) pyrene, napthalene, anthracene, 1, 2, 5, 6 - dibenz anthra-
cene, dimethyl benz(a)anthracene and 3-raethylcholanthrene (Table 4.3.1)
were studied. Stocks of PAH were diluted in solvents as shipped and added
to water in volumes of 1-30 pl'£ . The H - dibenzanthracene specific
activity was adjusted to 1027 mCi'mmol by addition of uiilabeled dibenz-
anthracene (Aldrich, 97% pure) to water at the time of labeling. Water was
labeled in bulk (1-2 £) and thoroughly shaken for one to two rain.
28
-------
Table 4.3.1. Radio-labeled PAH used in bioavailability studies.
to
vO
Compound Label Specific
Activity
benzo(a)pyrpne 7,10-14C 21.7
naptbalene 1-'*C 8.8
14
anthracene 9- C 3.3
1,2,5,6-
dibenzantbracene H(G) 30.3x10
7,12-diusethyl dimethyl 14C 97.4
benzo (a) anthracene
3-methylcholanthrene 6- C 57.0
Solvent Radiopurity Source
toluene > 96 Amersham
Batch 29
ether > 98 California
bionuclear
lot 2545
acetone > 98 California
bionuclear
lot 770824
benzene > 97 New England
Nuclear
lot 1253-021
benzene > 98 New England
Nuclear
lot 1267-176
benzene > 98 New England
ethanol 9:1 Nuclear
lot 1231-171
-------
Test water was prepared by adding inorganic salts to deionized water
(Milli-Q ) (Table A.3.2).
Table 4.3.2. Inorganic salts added to test water and
resulting water quality parameters.
Added Salt
NAHCO,
3
CaSO • 2H 0
MgS04
KC1
mg-£
48
30
30
2.0
Water Quality Parameters
pH 7
hardness 20 mg-£ as CaCO_
Alkalinity 120 mg'£~ as CaCO
_2
Conductivity 130 (Jmhos-cm
A humic stock solution was prepared from Aldrich humic acid (H-1675-2,
Lot #082091) as follows: 1) humics dissolved in 0.1 N NaOH; 2) centri-
fuged at 13,000 x g for 30 min; 3) pH adjusted to 2 with 6.0 N HC1 and
allowed to stand for 18 h; 4) humic acid precipitate was collected by
centrifugation (4000 x g for 20 min). The above steps were repeated three
times, the final humic solution adjusted to pH 7, and dialyzed repeatedly
against deionized water until conductivity was < 10 (jmho. Stock humics
were added to labeled test water- to a final, nominal concentration of 2.0
mg • £ DOC. Total carbon and inorganic carbon were determined by a
Beckman Model 915B Carbon Analyzer and DOC was calculated by differences.
Daphnia magna from laboratory cultures (Athens Environmental Research
Laboratory, U.S. EPA, Athens, GA.) were exposed to PAH in paired one liter
beakers with and without humics (60-70 Daphnia £ ); for six h. Five
sanples of ten animals v/ere removed by pipet from each test water, collec-
ted on nylon netting, rinsed quickly in 50 ml deionitr.ed water, and poured
through a Millipore filter apparatus. Animals were collected on tared 25
IMI Type HA cellulose acetate filters, dried over desiccant for 24-48 h and
sample dry weights determined on a Cahn Model 4700 Electrobalance. Animals
30
-------
14
and filters were combusted in a Packard Model 306 sample oxidizer, CO.
and H.O collected in suitable trapping agents, and counted by liquid
scintillation counting.
To evaluate the importance of natural particulates and DOC on B(a)P
bioavailability, similar experiments were conducted using water from Upper
Three Runs Cree1' (UTRC) and Skiuface Pond on the Department of Energy's
Savannah River Plant, near Aiken, SC. B(a)P uptake was determined in water
directly from the creek, in water filtered through Whatman GFC precombustcd
(550 C, 8 h) glass fiber filters (0.45 pm) to remove particulates, and in
filtered water UV photo-oxidized (f.aJolla Scientific Co.) to remove DOC.
Salting-out of PAH - Humic Complexes:
Each of the six PAH was dissolved in 0.5 L of water in paired beakers
containing Milli-Q water with humics (8.5 mg-£ DOC) and without huwics
(0.2 rag • £ DOC). Initial PAH concentrations were determined from
triplicate assays of activity in 1 ml water samples. A nominal salinity of
20 o/oo was obtained by adding sea salts (Instant Ocean, Aquarium Systems,
East Lake, OH.) to each beaker and PAH in solution after 24 h was deter-
mined as above.
RESULTS AND DISCUSSION
Bioconcentration in Daphnia magna
Concentrations of five PAH >fere f*.eterminea in Daphnia jnagna after 6 h
exposures in water with Aldrich humics (DOC = 2.0 tng'£ ) and in water
without hiusics (DOC £ 0.2 mg-£ ). Daphnia in huroic waters had signifi-
cantly lower concentrations of benzo(a)pyrene (BaP) (-24.5%) than compar-
able animals in non-humic waters (Table 4.3.3). On the other hand, humics
increased daphnia concentrations of methylcholanthrene (MC) (+210%).
Huraics had little effect on dimethylbenzanthracene (-13.1%) or dibenz-
anthracene (-t-19.1%), and while the effect on anthracene (-46.7%) appeared
large, it was not significant due to large sample variance. Results re-
ported assume that all radioactivity was parent compound. These results
are significant for two reasons: 1) they demonstrate that hiunics at low
concentrations affect bioaccumulation of some PAH; 2) they demonstrate that
huaiics may either increase or decrease bioaccumulation.
Evidence from this1, and other studies suggest that results reported for
the 6h uptake tests were not transient differences but were representative
of steady state differences for all PAH tested. In preliminary 24 h uptake
studies, steady state radioactivity in D. magna was reached within 6 h for
naphthalene, anthracene: and Bap. Approximately 60-80% of steady state was
reached after 6 h with DMBA, DBA and MC. In no case did the relative
difference between daphnia PAH in humic and non-humic waters change after 6
h. In Daphnia pulex, Southworth, e_t a 1. , (1978) reported that 6-h expo-
sures produced steady state concentrations of naph uaiene and anthracene,
while up to 24 h were required for benzanthracene, results consistent with
31
-------
fit
Table A.3.3. Effect of Aldrich humic acids on PAH accumulation by D. magna.
PAH
Anthracene
row 178.2
Benzo(a)pyrene
aw 252.3
Dimethylbenz-
anthracene
mw 256.3
Methyl
cholanthrene
mw 268.3
Dibenzanthracene
mw 278.4
Bioaccumulation:
Bioconcentration
a b
PAH Concentration Humic Concentration Bioaccumulation Bioconcentration
(Mg-A~ ) (DOC in mg-£ ) (6 h) Factor
1.96 0.2
2.0
1.15 0.2
2.0
0.33 0.2
2.0
1.29 0.2
2.0
0.73 0.2
2.0
(nmoles PAH • g dry wt. D. ma;
factor: ng PAH • g" wet wt D.
82.3 (19.7)
A3. 9 (4.0)
131.6 (7.3)
99.4 (7.7)
64.2 (23.2)
55.8 (30.0)
34.0 (7.4)
105.5 (10.8)
20.3 (0.8)
24.2 (2.4)
;na; Dry wt/Wet wt Ratio = 0.06)
magna
607
319
2745
2158
968
666
667
2064
652
773
ng PAH • ml
-1
C X (SE) n - 5.
-------
10
0
X
3
w.
CT
O>
c
X
D.
50
40
30
20
10
°c
a-Benzo(o)pyrene BCF = I7I6
O-Anthrocene BCF = 389
o
o
o
-
o
o
0
'ee ° ° ° °
! 1 1 1 1 1 1 1 1
) 1 23456
HOURS
Figure 4.3.1.
Accumulation of Ii(.i)P and antliracene by D. m.igna as a func-
tion of time.
33
-------
our observations. Previous studies have shown that daphnia have relatively
slow PAH biotransformation rates relative to accumulation rates (Herbes and
Risi, 1978; Leversee, et aK , 1981). In this study with C-BaP, after 6
h, parent compound represented 91.3 + 2.1% of test water activity and 92.8
+ 0.8% of D. magna activity respectively. Active biotransfonnation and
excretion of PAH reported for some invertebrates and fish are probably not
important factors in D. magna PAH accumulation.
' £\
The effect of varying Aldrich humic acid concentrations (0.3-5.7
mg*£ DOC) on daphnia accumulation of BaP, anthracene, and naphthalene was
determined. Humics significantly reduced the accumulation of BaP and
anthracene, but did not affect naphthalene (Table 4.3.4). In this simple
unsubstitutcd PAH series, the effect of hiunics was greatest for BaP >
anthracene > naphthalene, which is consistent with the order of reported
octanol-water partition coefficients. This suggests that hydrophobic PAH
may be partitioned competitively between daphnia lipids and humics. Al-
though the effect of humics on BaP and anthracene was greatest at highest
humic concentrations, there was not a simple linear relation between huaic
concentration and daphnia PAH concentration. The. greatest effect was found
between no humic (0.2 mg-2 DOC) and 1-2 mg'2~ DOC. Additional data at
several concentrations of PAH and humics will be necessary before dismiss-
ing the possibility that predictive sorption isotherms can be developed for
PAH like BaP and anthracene, but these data suggest that such a possibility
is unlikely.
34
-------
^_ wV
Table 4.3.4. Effect of Aldrich hukic acids on PAH accumulation by D.
PAH
Huinic Concentration
(DOC in
Bioaccumulation
(6h)
Bioconcerit ration
Factor
Benzo(a)pyrene
mw 252
Anthracene
mw 178
Naphthalene
mw 128
0.3
1.5
5.7
0.3
1.5
5.7
0.3
1.5
5.7
139.2 (14.2)
90.9 (7.6)
72.6 (5.7)
F ,,=12.19 (P<.005)
2,12
37.2 (2.0)
34.9 (2.0)
31.0 (1.1)
F .,=3.16 (P<0.1)
2,12
1.7 (0.2)
1.6 (0.?.)
1.8 (0.1)
F, ,=0.95 (NS)
2,6
1716
579
8?8
,
389
362
340
61
74
57
a -1 -
Bioaccumulation: n moles PAH-g dry wt D. magna. X (SE), n=5. Naphthalene
n=3.
Bioconcentration Factor: ng PAH'g wet wt D. magna
-1
ng PAH'inl water
Initial B(a)P water concentration was 1.5 Mg'£ (6.0 mM); Anthracene was
7.2 aM; Naphthalene was 6.6 mM.
Salting - out
An initial study was conducted with BaP to determine the range of
salinities producing a salting-out effect and the time to steady state
water concentrations. Initial concentration of Aldrich huraic acid was
8-10 mg-£~ DOC in all studies. At 17-?5°/oo salinity, 70% of BaP was lost
from the water column aftei 24 h (Fig. 4.3.2). Below 5 /oo, no salting out
was apparent. In beakers where significant salting out occurred, a fine
organic floe was evident on bottom and sides of the beaker. PAH mass
balance was greater than 95% in all cases, indicating that unaccountable
losses were minimal.
Co-precipitation of all six PAH studied was determined at 20°/oo
salinity after 24 h. In the presence of humic acids. PAH concentrations at
24 h were reduced significantly (5-79%) below initial values for all PAH
35
-------
o
h-
cc
r-
2
o
Z
O
o
a.
o
m
u
o
a:
LJ
a.
120
100
80
60
r- 40
20
SALTING OUT OF BaP HUMICS
Initial Humic = 8.5mg/L DOC
Initial BaP = 1.2/J.g/L
\2 18
HOURS
SALINITY (ppt)
0
25.5
24
48
Figure A.3.2. Salting-out of B.iP at six salinities in thn presence of
Aldrirh humics.
36
-------
(Table 4.3.6). la water without humics, salting out was found only for MC
(-12.5%) and DBA (-15.2%). Mass balances were all in excels of 93%, and no
losses were observed from control beakers (PAH in Milli-Q water). DOC at
24 h was not determined.
Table 4.3.5. Effect of Skinface Pond and Upper Three Runs Creek organics
and particulates on B(a)P accumulation by Daphnia magna.
Water Source and Organic Carbon Bioaccumulation Bioconcentration
Treatment (mg • 8,' ) (6 hour) Factor
Upper Three Runs
Creek
Untreated
Filtered (O-ASpm)
Filtered-oxidized
Skinface Pond
Untreated
Filtered (O.ASpm)
Filtered-oxidized
10.0
5.5
0.2
12.2
—
0.2
227.4
304.4
367.2
70.4
156.2
206.7
(12.0)C
(7.1)
(13.9)
(2.6)d
(5.6)
(13.1)
2571
3581
4656
903
2312
3292
Mean (SE), n=5. Values = runole • g dry weight
mg BoP-g wet weight Daphnia
ng BaP-ml water
°ANOVA: F = 37.87 p < .001.
i, \.i
dANOVA: F. . = 67.84 p < .001.
37
-------
Table 4.3.6. Salting - out of PAH in water with and without hunics .
PAH (Hg'*') PAH
PAH Time (H) Without Humics With HumicsC
Naphthalene
mw 128.2
Anthracene
nw 178.2
Benzo(a)pyrene
mw 252.3
Dimethylbenzanthracene
mw 256.3
Methylcholanthrene
mw 268.3
Dibenzanthracene
mw 278.4
T =
T =
T =
T =
T =
T =
T =
T =
T =
T =
T =
T =
0
24
0
24
0
24
0
24
0
24
0
24
2
o
*»
2
2
1
1
0
0
1
0
0
0
.10
.13
.81
.90
.21
.18
.91
.96
.04
.91
.72
.61
(0
(0
(0
(0
(0
(0
(0
(0
(0
(0
(0
(0
.02)d
.16)
.01)
.05)
.04)
.05)
.01)
.03)
.04)
.10)
.01)
.01)
2
1
2
2
1
0
0
0
1
0
0
0
.21
.56
.81
.55
.26
.39
.78
.39
.02
.25
.72
.15
(0
(0
.07)
.04)
(0.10)
CO. 04)
(0
(0
(0
(0
(0
(0
(0
(0
.01)
.03)
.05)
.01)
.04)
.00)
.02)
.00)
Salinity in all cases 20o/oo, Instant Ocean Salts.
Water without huuics: Dissolved Organic Carbon = 0.2 mg-£ at T = 0.
CWater with Aldrich humic acids: DOC = 10.0 mg-2"1 at T = 0.
values = X (SE), N = 3.
While the importance of PAH sorption to suspended mineral and en ganic
particulates has been recognized (Karickhoff, ejt al. , 1979), the role of
dissolved organic matter has received little attention. Hassett and Ander-
son (1979) reported that DOM in river water reduced the efficiency for
solvent extraction of cholesterol. Boehm and Quinn (1976) found that
dissolved organic matter (DOM) in sea water increased the solubility of
n-alkanes and isoprenoid hydrocarbons, but had no effect on the solubility
of the PAH phenanthrene and anthracene. Landrum and Giesy (1981) reported
that sorption of B(a)P to XAD-4 resins is reduced by the presence of hu-
mics.
The importance of humics on the environmental fate of hydrophobic PAH
like B(a)P is clear from this study. Our results show that B(a)P bioaccu-
taulation is significantly reduced by huraic concentrations of 2.0 mg'£
DOC. Downstream transport of hydrophobic PAH may be increased by humics
38
-------
depending on particular*" load, character of humics, and partitioning among
these compartments. Precipitation of humic PAH complexes by increasing
salinity, as reported here for B(a)P, may represent a significant pathvay
for accumulation of PAH in estuarine sediments. Thus, this work demon-
strates that fresh water humics may significantly affect results of studies
on PAH bioavailability and environmental transport.
39
-------
SECTION 4.4
UPTAKE, DEPURATION AND BIOTRANSFORMATION KINETICS OF
BENZO(A)PYRENE AND ANTHRACENE BY PERIPHYTON COMMUNITIES
INTRODUCTION
Algae are the foundation of most aquatic food webs, thus, changes in
the size, structure or metabolic activity of the algal community may have
important effects on the structure and function of the entire aquatic
community. While many stream systems are not autotropbic, the periphyton
community may be important to critical species or at critical periods
during the growing season. Also, the periphyton community can be an im-
portant accumulator of organic compounds. Thus, periphyton communities may
be an important component of simulation models by removing organics from
solution, biotransforming trace organics or acting, directly or indirectly,
as a source of these compounds to foraging insects and other components of
the food web, directly or indirectly.
The effects of hydrocarbons on algae have been investigated (Soto et
a_l., 1975; Schindler et al., 1975; Soto et al., 1979a and 1979b; and
Giddings, 1979} but few studies have been made of the uptake, depuration
and biotransfonnation, which are needed for dynamic simulation models
(Payer and Soeder, 1975; Walsh et al., 1977).
Evidence suggests that the most important pathway of bioaccumulation
by periphyton is direct uptake from water by simple partitioning of B(a)P
into lipids (Neeley, et al., 1974). Elimination from biota includes par-
titioning of parent compound into clean water and active biotransformation
and excretion of metabolites (Neff, 1979). Reported biotransfonnation
potential is great in midge larvae (Leversee, et. al., 1981a) and fish (Lee,
et al., 1972b; Bend et «!., 1979), and is ninor in Daphnia (Southworth, et
al., 1978). The potential for food chain bioaccumulation is still not
resolved. It has been shown that there is significant accumulation of
naphthalene by Chlamydomonas angulosa with no apparent bictransformation
(Soto, et al., 1975). In marine microcosms, Lee, ejt al. (1978) reported
accumulation, and no apparent biotransformation, of B(a)P and other PAH by
phytoplankton. Accumulation of B(a)P from algal food by hardshell clam
larvae is reported to equal that of direct uptake from water (Dobroski and
Epifanio, 1980). In freshwater lotic systems, periphyton represents an
important primary producer for food chains and may serve as the functional
organic substrate for PAH accumulation.
-------
A series of studies was conducted, under laboratory conditions, to
determine the rates of uptake, depuration and biotransformation of the PAH
compounds, benzo(a)pyrene and anthracene by periphyton communities on glass
slides. These studies were designed to provide information not only on
rate constants and biotransformation but also on community seasonal differ-
ences, as well as length of colonization time.
MATERIALS AND METHODS
Periphyton Communities
Natural periphyton communities were collected from two streams on the
U. S. Department of Energy's Savannah River Plant near Aiken, South Caro-
lina. Upper Three Runs Creek (UTRC) is a deep, fast-flowing, blackwater
stream in which diatoms comprised approximately 90% of the winter periphy-
ton community. Eunotia incisa and Eunotia sudetica were the dominant forms.
The water quality of UTRC is given in Giesy and Briese, 1978. Castor
Creek, by comparison, is a shallow, partially beaverdam-impounded system in
which the periphyton community was more diverse. Species of filamentous
and non-filamentous desmids from the genera (Hyalotheca, Desmidium, Spon-
dylosium, Netrium, Euastrum and Pleurotaenium) accounted for approximately
50% of the Castor Creek attached flora. Various diatom species, particu-
larly Anomoeoneis serians var. Apiculata and Frustulia rhomboides, were
representative of the remainder of the community.
Exposure
Naturally colonized glass microscope slides (7.62 x 2.54 cm) in plexi-
glass slide holders were harvested after 3 or 5 weeks colonization from
UTRC and after 3 or 6 weeks colonization frora Castor Creek, beginning in
January of 1980. .These slides, .with their attached communities, were
exposed to 7,10 C;Benzo(a)pyre^'i (B(a)P) (Amersham-Searle, specific
activity 21.7 mCi-mmol ) in a labci».-•story flow-through system. The anthra-
cene used in these studies was !5, C labelled (Cal. Biochem., specific
activity J.3 mCi-mmol" , Lot #770624'-. Millipore filtered (0.45 \m) stream
water was labelled in bulk witb C-EaP approximately one hour before
exposure was begun. Labelled water was gravity fed from a 40£ glass head
tank, via stainless steel tubing and micrometer valves, tp each of six 250
ml glass staining dishes. Flow rates averaged 100 ml-h and were suffi-
cient to maintain a constant B(a)P water concentration of 1.0 pg'£ . They
did not simulate stream flow conditions. Six slides, supported in stain-
less steel wire mesh baskets, were placed in each staining dish. Experi-
ments were performed under gold fluorescent light (X 5^ 500 nm) to minimize
photolysis of B(a)P anthracene. Uptake, biotransformation and autoradio-
graphic studies were conducted simultaneously.
-------
Uptake and Depuration Rate Constants
Slides used in the determination of uptake rates were removed from the
flow-through system after 0.25, 1, 2, A, 8 and 24 h of exposure. One slide
from each of three reservoirs was harvested at each of the six sampling
times. After removal from the dosing system, each slide was allowed to air
dry and the periphyton were then scraped into a tared paper thimble.
Samples were dried in a dessicator for 24 h and weighed on a Mettler Model
HL52 Balance. , They were then combusted in a Packard Model 306 sample
oxidizer and CQ& collected in a scintillation cocktail consisting of IS
ml of Permafluor and 5 ml of Carbosorb . C activity was subsequently
measured in a Beckman Model LS-8100 liquid scintillation counter with
quench correction using the sample channels ratio method.
Uptake data were fit to linear least squares regressions on a concen-
tration (ng PAH-g dry weight) and a slide surface area (ng PAH-cm )
basis. Data were analyzed using Procedure GLMr Statistical Analysis System
(Barr, et al., 1979). First order uptake rate constants were calculated
from the flux of the initial uptake rate and depuration rate constants from
the slope of the log-linearized depuration regression.
Autoradiography
Dipping emulsion autoradiographic techniques were used to visualize
sites of C-B(a)P accumulation. Two slides were removed at each sampling
time, dipped in 2% Lugol's solution for ca. 30 seconds and then allowed to
air dry overnight. Standard autoradiographic techniques using Kodak KTB-2
dipping emulsion were used in processing the samples (Gude, 1968). Slides
were stored in light-tight boxes for 5 days, then developed and mounted in
Permount. Resultant autoradiographs were examined and photographed on a
Zeiss Model IM-35 inverted microscope.
Biotransformation
The biotransfonsation potential . of periphyton communities was de-
termined by analyzing^ periphyton for C as B(a)P and B(a)P-transformation
products (non-B(a)P C). Periphyton were assayed by a combination of
solvent extraction, thin layer chromatography (TLC) and liquid scintilla-
tion counting (LSC). More specific methods are given in section 4.3. In
order to demonstrate that any observed breakdown of B(a)P was the result of
•some living cellular process and not of phenomena such ax photooxidation, a
"dead cell control" was used in the study of biotransformation. Two slides
each of living and dead periphyton (fixed for 0.5 h in 4% Lugol's solution
and rinsed prior to exposure) were sampled after 0.25, 4 and 24 h exposure.
Living periphyton were immediately placed in Lugol's solution (4%) to
insure cessation of snv .ongoing biotransformation of B(a)P. Since subse-
quent measurements of C activity of this Lugol's solution revealed C
concentrations at or below background, it was felt that no appreciable loss
of activity occurred during this step. Following overnight storage
(-20°C), periphyton were scraped from slides and sample wet weights were
42
-------
measured. Samples were stored in glass scintillation vials at -20°C under
benzene: ethyl acetate (1:1, V/V). Samples were warmed to room tempera-
ture and extracted by grinding in a Ten Broeck glass homogenizer with
benzene: ethyl-acetate (1:1, V/V). Horaogenates were centrifuged at 1000
rpm for 0.5 Jy and (IEC model HN-S centrifuge) supernatant volumes adjusted
to 10 ml. C activity in pellets WAS determined as a measure of bound
compound.
For TLC analysis, the supernatant was sampled (0.5 ml) to determine
activity, and the volume was reduced to 100 jjl by N_ evaporation. It was
ihen co-chromatographed with B(a)P standards on Merck Silicanized Silica
Gel 60 channel plates. Plates were developed in 9:1 hexane:benzene and
visualized using ultraviolet light. Each sample channel was divided into a
B(a)P section (the standard B(a)P spot + 1 cm), R, > B(a)P (less polar) and
R < B(a)P (more polar). Each section was scraped from the plate and
transferred to^a scintillation vial with cocktail (Research Products Inter-
MB 1 £*
national 3a70B ) for C activity measurement.
In addition to determining levels of these compounds in periphyton,
the breakdown of B(a)P dissolved in experimental water was monitored as
well. Water samples (3 x 100 ml) were collected at time "0" and subsequent-
ly at 0.25, 4 and 24 h and frozen (-20°C). Samples were thawed, acidified
to pH 4, and extracted sequentially with benzene (3 x 50 ml) and ethyl
acetate (3 x 50 ml). Extracts were combined, dried over anhydrous Nfc-SO.,
reduced in volume and run on TLC plates as described above.
RESULTS
Periphyton Communities
The Castor Creek and UTRC periphyton communities differed markedly in
both species composition and amount of biomass accumulation after 3 or 6 wk
colonization of glass slides. Approximately 50% (relative abundance) of
the Castor Creek attached flora consisted of desmids, including such ornate
species as Desmidiura coarctaturo (6%), Hyalotheca sp. (14.5%), Spondylosium
pulchrum (16%) and Euastrum pjnnatum (4%). Diatoms, particularly Anomoeo-
nesis serians var. apiculata (32%) and Frustulia rhomboides (12%), repre-
sented the remainder of the community. Mucilaginous secretions are common
in members of the Desmidiaceae, and extensive sheaths surrounded D. coarc-
tatum and S. pulchrum. In comparison, the diator-dominated UTRC community,
consisted primarily of Eunotia incisa (40%) and Eunotia sudetica (21%).
This diatom conanunity appeared to provide less in the way of both adsorp-
tive surface area and mucilage secretion. Periphyton biomass on Castor
Creek slides was greater than UTRC after both 3 wk (X = 2.99 vs. 1.72 mg
dry weight/slide) and 6 wk of colonization (X = 6.88 vn. 5.36 mg dry
weight/slide).
43
-------
Uptake
B(a)P was rapidly accumulated from water by both UTRC and Castor Creek
periphyton communities. Uptake of C-B(a)P was linear during the first 24
h of accumulation when expressed as a function of concentration (r =
.59-.93) and slide surface area (r = .85-.93) (Fig. 4.A.I). Biphasic
uptake, consisting of a rapid surface sorption followed by slower accumu-
lation during the first 24 h was suggested by the positive y-intercepts in
all cases (Fig. 4.4.1). Approximately 37% of the total B(a)P present in
the UTRC samples after 4 h was accumulated within the first 15 minutes of
exposure. For Castor Creek periphyton, this value was 26%. The uptake
rates determined on a surface area basis from regression plots differed
significantly between the two streams after similar colonization periods (P
< .01), and between colonization periods within streams (P < .01). Uptake
rates, on a concentration basis, were more variable than those normalized
to surface area so significant effects were more difficult to demonstrate.
Accumulation by periphyton which had been colonizing for 6 wk in Castor
Creek was significantly greater (P < 0.01) than by that which had only been
colonized for 3 wk. The slides which were colonized in UTRC had the lowest
biomass and were the only ones which approached steady state concentrations
of B(a)P (Fig. 4.4.1). The comparatively low regression r (C.59) of
accumulation of B(a)P by the UTRC peripbyton after 3 wk of colonization
suggests a departure from linearity. A semi-log plot of the same data only
slightly improved the fit (r = 0.66) (Fig. 4.4.1C).
The uptake flux can be determined as the initial slope of the linear
regressions. The first-order rate constants can then be calculated with
equation 4.4.1.
where
J. = initial uptake flux
C = water concentration
K = uptake rate constant
Autoradiography
Autoradiographs suggest surface sorption and s'-.catn complexation as
the principal mechanisms ol B(a)P accumulation by algae of both communi-
ties. Although it is not possible to differentiate conclusively between
intra vs. extracellular accumulation without the use of ultre-thin sec-
tioning techniques (R. Knoechel, per.s. comm.), label did appear to consist-
ently acjumulate on cell surfaces. There is virtually no label associated
with the shrunken p.-«.toplast of Netrium digit.us (Fig. 4.4.2). The exten-
sive mucilaginous sheaths surrounding Desmidimn coarctatum nud Spondylosimn
pulchrum readily complexed B(a)P (Fig. 4.4.2). Dense labelling of the
diatom Neidium viridis var. amphigorophus was unique (Fig. 4.4.2). Unla-
belled controls did not show concentrations of silver grains within or
around algae, although a background level was apparent.
44
-------
? ».ooo
^ 4.0OO
1
o
21
t> 2.0OO
z
UPPER THREE RUNS CREEK
UD'e*r Oo'o ot Function of tm^ of
Siiqt S^fTaet A^to
I tcce
^\\-
CASTOR CREEK
UplQX Dora o* function of
mii e' Siiet
0»> 24 6 • 10 12 14 it l> 20 22 24 2* 025 I 2 •» » » K> 12 14 It i« 2O 22 24 2*
TIME Ihra)
Figure A.4.1. Accumulation of C B(a)P by periphyton communities from
UTRC and Castor Creek which had been colonized for 3 or 5
wk. Accumulation is normalized to a surface area (a and b)
and dry weight basis (c and d). Each point represents the
mean of 3 replications with confidence interval = + SD.
-------
I M
Figure A.A.2. Autoradiograplis illustrating the deposition of C B(a)P in
A) DCS mi (Hum coarctatum, B) Spondyl osium pulrliriiin, C) Netrium
di[;i tus, D) Ncidi uiii i ri <\ i s , and E) Lunotia sp. All auto-
radiographs are 500X magnification.
A6
-------
Biotransformation
Neither UTRC nor Castor Creek periphyton communities exhibited sig-
nificant biotransformation of C-B(a)P within 24 h. In both.living peri-
phyton and dead cell controls, approximately 85-90% of total C after 24 h
was B(a)P (Figs. 4.4.3 and 4.4.4). Histograms representing the percent of
C activity as B(a)P and B(a)P-transformation products at 0.25, 4, and 24
h exposures reveal no substantial differences between living and dead peri-
phyton communities for either stream or either colonization period (Fig.
4.4.5). Significant apparent transformation of C-B(a)P occurred over 24
h/in flasks containing experimental water only. Approximately 90% of total
C was B(a)P after 0.25 b, while only 62% remained as B(a)P after 24 h.
In previous studies with fish, exposure water analyzed the same day without
freezing never contained more than 12% B(a)P transformation products after
24 h.
Anthracene
A set of studies was conducted to determine the uptake and depuration
rate constants for anthracene in periphyton communities colonized in UTRC.
The accumulation of anthracene during 24 b was linear, except for en ini-
tial rapid accumulation (Fig. 4.4.6). Thie initially very rapid uptake
results in a positive y-intercept for linear regressions. The uptake flux
was estimated as the slope of the overall linear regression. The first-
order uptake rate constant was O.OAh
After 24 h exposure to anthracene, plates and the associated periphy-
ton were transferred to clean water and desorption followed (Fig. 4.4.7).
Desorption was rapid. The rate constant for depuration was 0.17h which
means that the half time for elimination was 4 h. However, there was a
residual of approximately 4 ng anthracene*cm which was not eliminated
after 30 h of depuration.
DISCUSSION
Results of our study suggest that community species composition can
significantly affect uptake rates of PAH by periphyton. This conclusion is
consistent with our observations that !) Castor Creek periphyton had signi-
ficantly greater B(a)P uptake rates, 2) Castor Creek periphyton, dominated
by structurally ornate desmids with extensive gelatinous sheaths, differed
markedly from the diatom-dominited UTRC community, and 3) autoradiographs
demonstrated the relative importance of B(a)P sorption to cell surfaces,
especially to sheath material. The larger biomass on Castor Creek slides
did not appear to cause the greater uptake rates observed, since results
expressed on an area basis were not significantly different between peri-
phyton from the two streams.
Our results suggest that uptake rates vary as a function of coloni-
zation period, or community biomass. One would expect an increase in
biomass to yield a concomitant increase in the concentration of PAH per
47
-------
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Figure 4.4.3.
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figure represents peripliyton t rom .1 three week colonisation,
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Figure 4.4.5. Histograms ^f quantities of B(a)I» shaded, and non-B(.i)P,
unshaded, C in Upper Three Huns and Castor Creek pcri-
phyton. Samples of live and dead peripliyton were taken after
0.25, 4 and 24 h.
50
-------
I 1 1 L. I I I I 1 I I _J
0.25
10 12 14 16
TIME (h)
Figure 4.4.6.
Accumulation of C-anthracenc by periphyLon which colonized
gloss slices in UTRC. Mean liiomass/s 1 i(\c - 0.4 mg, dry
wciglit'cm *". Anllir.iccne concent i~J t i on in w.itcr = 22 (ig'Al
Concentrations are norni-lizoil to an JTCM basis but can bo
converted to a biomass basis with the convo!sion factor
given. Each point represents ttic mean of 3 slides. Confi-
dence intervals are + SD.
51
-------
27r
E 23
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a:
o>
24
28
32
36
4O
TIME
48
52 54
(h)
Figure 4.4.7. Desorption of,anthracene from UTKC periphyton which had been
exposed to C-anlhraccne for 24 h. Each point represents
the mean of three slides. Confidence .intervals are + SD.
Mean pcriphyton biomass = .4 nig, dry weighfcm . ~
52
-------
unit substrate surface area as more of a given substrate is covered by
periphyton growth. The maximal effect.of bionfass on uptake rate should be
realized when the entire substrate becomes covered by a layer of periphyton
growth. As the community becomes more layered with time, only the upper-
most strata should actually be exposed to levels of PAH within a .24 hour
period. Any further increase in biomass should not increase uptake rate,
but rather, should increase the length of time necessary for a particular
community to achieve steady state, and the absolute capacity of that commu-
nity for accumulation of compound. Thus, uptake rates, on a concentration
basis, would be expected to decrease after a critical minimum thickness, or
mass, of periphyton has been reached. Our data show slower uptake rates,
on a concentration basis, after longer colonization times. Similar results
have been-.reported for 'the accumulation of selected radionuclides (Co ,
Zn , Ru , Cs ) by periphyton (Neal et aj.., 1967). Uptake was linear
over a certain range of biomass, but as mass increased, accumulation was
not proportional. Uptake rates are best expressed on a surface area rather
than a concentration basis.
The statistically significant differences in B(a)P uptake rates be-
tween UTRC and Castor Creek periphyton must be interpreted cautiously since
no steady state equilibrium was achieved. The steady state bioconcentra-
tion factor (BCF) can be estimated from the ratio of uptake rate coeffi-
cient (K ) to depuration rate coefficient (K.). Preliminary depuration
results "for Castor Creek) were too variable to accurately estimate K,;
however, .the relatively slow B(a)P depuration observed (only a 25% reduc-
tion in C activity after 24 h) indicates that B(a)P will not be quickly
released from periphyton once complexed. The range of expected values for
K , K., and BCF for periphyton from other streams, such as northern hard-
waters, would be of interest.
The achievement of steady state is most probably' linked to the rate at
which the compound can diffuse through the multi-layered periphyton commu-
nity. The plateau observed in the low biomass UTRC three week old community
suggests an approach to saturation of this thin periphyton layer. In con-
trast, the 5 week old UTRC community, and both the 3 and 6 week old Castor
Creek communities, are still in a linear phase of uptake after 24 h. These
findings are in agreement with those reported for Zn adsorption by peri-
phyton communities where accumulation was largely a surface phenomenon and
ultimate biomass saturation was diffusion-dependent (Rose and Gushing,
1970). Complete saturation of periphyton will be a function of community
thickness and exposure time. Exposure times of several weeks may be re-
quired to achieve steady state for various PAH in mature periphyton commu-
nities.
Biotransformation has been suggested as 'a significant degradative
pathway for PAH in aquatic environments. Pseudomonad bacteria in culture
have been found to trani.form B(a)P and fluoranthene (Barnsley, 1975), as
well as anthracene (Evans et al. , 1965). Bacteria.in petroleum-contain-'nat-
ed stream sediments have been found to transfora C-labelied naphthalene,
anthracene, B(a)P and dibenzanthracene to CO *, polar trahsformation
products and bound material (Herbes and Schwall, 197."; Herbes e_t al.,
1977). In general, both freshwater (Soto et al. , 1975) and marine phyto-
53
-------
plankton (Lee et al., 1977) have not demonstrated an ability to biotrans-
fona PAH, but do accumulate considerable amounts. Our data indicate-that
the periphyton communities examined did not actively biotransform B(a)P in
24-h exposures. The, non-B(a)P C material present in periphyton (as much
as 20% of total C) was attributed to non-specific B(a)P breakdown or
binding since no difference between living periphyton and that fixed in
Lugol's solution was observed. No separate measure of viability or enzyme
activity in fixed controls was made, but apparent active bit-transformation
of methyl parathion by sediment bacteria autoclaved up to 20 minutes has
been observed (David Lewis, pers. comm.). The experiments reported here
weie conducted under low intensity gold fluorescent light (X > 500 nm) to
reduce photolysis of B(a)P. The importance of photosynthetically coupled
B(a)P uptake and transformation in natural exposures remains to be deter-
mined.
The deposition of B(a)P in heterotrophically dominated communities may
differ from the trend reported above. Biotransformation of 8(3)^ may be
significant in environments such as densely canopied stream areas where P/R
ratios are redu:ed. Mclntire (1975) observed the tendency for periphyton
developing on rocks in a stream to exhibit characteristic layering with
time. He noted an outer, photosynthetically active, layer and in time the
development of a heterotrophic layer between this outer layer and the sub-
stratum surface. Thus, the biotransformation capabilities of a given commu-
nity may not be uniform throughout. The concentration of B(a)P transforma-
tion products may vary along a vertical transect down through the commu-
nity. The growth of Chlorella vulgaris #29, a heterotrophic variety, has
reportedly been stimulated by exposure to crude oil (Graham and Hutchinson,
1975). Chronic low level exposure to PAH, such as B(a)P, may work to
restructure the periphyton community and favor heterotrophic growth.
Where periphyton cover a significant area of stream bottom, this com-
munity may equal or exceed the importance of organic sediments in determin-
ing the fate of B(a)P and other PAH. The observed property of composition-
dependent rates of uptake for periphyton communities may serve to signifi-
cantly alter the responses of distinct lotic systems to B(a)P perturba-
tions. Rates of accumulation and capacity for accumulation to B(a)P input
will vary between streams supporting divergent periphyton flora and within
the same stream as seasonal changes in periphyton composition occur. On a
smaller scale, variations in response to B(a)P input between reaches of a
particular stream, e.g. pool vs. riffle area or canopied vs. open area,
will occur due to associated variation in algal species composition. The
phenomenon of patchiness in the microdistribution of algal species has been
frequently reported (Bruno and Lowe, 1980; Douglas, 1957; Duthie, 1965).
This property of periphyton distribution ensures that local variations in
B(a)P concentrations will occur.
ieriphyton may represent a significant pathway for food chain bioac-
cumulation. While direct uptake from water is usually considered the most
important pathway, trophic transfer of B(a)P from the diatom Thalassiosira
pseudonana to larvae of the marine hard clam Hercenaria mercenaria was
reportedly equal to that of direct uptake from water (Dobroski and Epi-
-------
fanio, 1980). Grazing benthic invertebrates may accumulate 6(a)P in »
similar manner.
When uptake and'depuration rate constants, which were derived in these
laboratory studies, were used in the simulation model, the predicted con-
centrations of anthracene in periphyton were very similar to those observed
in periphyton in the channels.microcosm (see section 5.4).
•In summary, periphyton represent a significant and previously unex-
amined sink for B(a)P in stream systems. Clearly, additional work is
needed to confirm the observed low biotransformation rates, as well as to
determine the physical or physiological basis of community differences in
B(a)P uptake rates.
55
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SECTION A.5
UPTAKE DEPURATION AND BIOTRANSFORMATION OF BENZO(a)PYRENE
BY THE MIDGE, CHIRONOMUS RIPARIUS
INTRODUCTION
Larval midges (Chironomidae) are abundant benthic organisms which bur-
row *.a sediments and have been shown to accumulate trace contaminants
(Kawatski and Bittner, 1975; Derr and Zabik 1972). Chironomids are a major
food source for larger macroinvertebrates and smaller fish, and link both
aquatic and terrestrial food chains through emergent adults.
*
This study of B(a)P kinetics in chironomids was conducted to 1) con-
struct descriptive models of B(a)P uptake and elimination kinetics, 2) com-
pare uptake and elimination coefficients determined using one and two com-
partment models, 3) determine the ability of chironomids to metabolize
B(a)P and the effect of biotransformation on bioconcentration factor, A)
determine the contribution of exoskeleton to total bioaccumulation and 5)
determine the effect of bottom substrate on depuration rate.
MATERIALS AND METHODS
Uptake and Depuration
Chironomus riparius larvae were collected from a sewage outfall on
Badfish Creek near Madison, Wisconsin, and reared in the laboratory at the
Savannah River Ecology Laboratory for several generations. Cultures were
maintained in gallon glass jars that contained well aerated substrate of
previously washed and fermented ground paper towels. Approximately one
gram of a mixture of dog biscuits, TetraMin flake fish food shrimp pel-
lets, and Cerophyll (powdered nettle leaves) was added to the jars every
three days during the three week larval stage. After two days as pupae,
adults emerged, mated and oviposited in the jars. Fourth instar larvae had
G mean dry weight of 0.39 mg (SD = 0.2, n = 50) and a dry to wet weight
ratio of 0.095.
1A
Benzo(a)pyrene (7,10- C) was used as purchased from Amersham/Searle
in two lots, CFAA72 Batch 26 (specific activity 60.7 mCi-1131101" ) and Batch
29 (specific activity 21.7 mCi-mmol ). The specific activities were con-
firmed with a Varian Model 5000 high pressure liquid chromatography system.
Radiochemical purity determined by thin layer chromatography was greater
than 99%. All preparative, analytical, and experimental procedures* were
56
-------
performed I'uder gold fluorescent light (\ > 500 run) to minimize photodegra-
dation of B(a)P.
Well water (pH 7.1) was aerated and centrifuged to remove particulates
(> 0.15 M)- Wacer was labeled in bulk (7-10 £) and dispensed into repli-
cate test chambers after a 1 to 2 h equilibration. Actual water concentra-
tions were determined from calculations based on dpm-ml and known B(a)P
specific activity. Concentrations ranged between 0.6 - 1.5 |Jg B(a)P-£ .
Uptake experiments (in triplicate) were performed in 1) 0.35 £ stain-
ing dishes which contained 0.2 £ of water and 20 chironomids; 2) 6.0 £
aquaria which contained 1-2 £ of water and 100 - 200 chironomids. Samples
of 10 chironomids were taken after 0.25, 0.5, 1.0, 1.5, 2, 4, and 8.h.
Each staining dish provided a single sample of 10 chironomids for total C
and 10 for analysis of biotransfonnation products. The biomass to volume
ratios ranged from 0.020 - 0.039 mg dry wfml water. The range of bio-
mass to volume ratios in both uptake and depuration experiments was due to
differences in water volume. The chironomid larvae were approximately the
same size in all experiments.
Depuration experiments were performed by transferring 100-200 chirono-
mids, labeled for eight hours, into 6 £ glass aquaria, which contained 1 to
2 £ of clean water. Ten chironomids as well as one ml of water were taken
from the aquaria after 0.5, 1.0, 1.4, 2.0, 4, 8, 15,__24 and 48 h. Mass to
volume ratios ranged from 0.035-0.070 mg dry wfml water. Addition of
paper towel with associated microflora provided a food source, to avoid
starvation effects, and a substrate allowing normal behavioral patterns.
Substrate was not used in uptake •experiments, because sorption and micro-
bial biotransfonnation would have confounded exposure calculations.
Samples of 10 chironomids were combusted in a Packard Model 306 sample
oxidizer aiid collected in a -scintillation cocktail consisting of 17 ml
Penra-afluor and 5 ml Carbosorb . Internal and external standards indicated
a CO. recovery greater than 99% and no carry-over. Water and solvent
samples were placed directly into a preraixed commercial cocktail (Research
Products International 3»70B ). All sample activities were measured with a
Beckman Model LS8100 liquid scintillation counter and corrected for quench
using internal and external standards and the sample channels ratio method.
Biotransfonnation
14
Both animals and water were analyzed for C- fl(a)P and transformation
products. Chironcraids were assayed by a combination of solvent extraction,
thin layer chroraf.tography (TLC), and liquid scintillation counting (LSC).
•Thirty chironomids (10 from each replicate) were homogenized in a Tea
Broeck tissue homogenizer with five dropu of concentrated HC1. The acid
homogenate was extracted sequentially by homogenizing with benzene (5 ml
nanograde), diethylether (2 x 10 ml, anhydrous), and ethylacetate (5 ml
nanograde). The organic solvents were combined, a 2 x 0.5 ml aliquot
counted, and the remaining volume determined. The samples were dried with
anhydrous sodium sulfate and the volume reduced to approximately 100 pi by
57
-------
rotary flash evaporation and evaporation under a nitrogen stream. The
samples were brought to 500 pi vith diethylether and activity determined on
a 25 \tl aliquot. Recovery of C-B(.a)P from spiked chironomids was 92.3 ±
3%.
Samples were spotted onto thin layer plates and chromatographed in
pentane:diethylether (9:1, V/V) in an unsaturated system. Developed plates
were divided into five sections corresponding to B(a)P, hydroxylated metab-
olites, the. origin, and two others. The sections were scraped from the
plate and C activity measured. Chironomid extracts were also analyzed by
high pressure liquid chromatography (see below). All scmples were kept
frozen (-20°C) prior to analysis.
Water from an eight hour uptake experiment was analyzed for metabo-
lites by 2-dimensioual TLC. The pH was adjusted to 4.0 with glacial acetic
acid and water was passed through 100 ml of wet XAD-4 resin precleaaed by
the method of Garnas (1975). No breakthrough of radioactivity was detected
by counting aliquots of water which passed through the resin column. The
resin column was eluted sequentially with 250 ml each of diethylether and
acetone. The solvents were combined and C activity of one ml subsamples
determined. Solvents were dried by the addition of 50 ol petroleum ether
followed by passage over anhydrous sodium sulfate. Volume was reduced as
previously described and metabolites were isolated by 2-dimensional TLC
with pentane:ether (9:1, V/V) and toluene:methylene chloride:methanol
(25:10:1, V/V/V) (Pitts et al., 1978). The spots were identified with UV
.light and quantified by LSC. Standards of B(a)P metabolites for TLC co-
chromatography were obtained from the National Cancer Institute's Standard
Chemical Reference Repository.
Water was also analyzed for B(a)P by high pressure liquid chroma-
tography (HPLC). After chironomids were removed, 200 ml water samples were
taken from uptake aquaria and uptake controls (no chironomids) and extrac-
ted with hexane (3 x 50 ml). The three hexane extracts from each water
sample were combined and dried with anhydrous sodium sulfate. Extract
volumes were reduced to < 0.25 ml as previously described, diluted to 0.5
ml with methanol and analyzed by a Varian Model 5000 HPLC system with a 254
nm fixed wavelength detector. Recovery of C - B(a)P from spiked water
was 77.6 ± 6%. Separations were made with a Micro-Pak MCH-10 reverse-phase
column (35 cm long) equipped with a Whatman guard column of Co-Pel C.-ODS
on 35 pm particles Ufing gradient programmed elution conditions at 28 C
(Johnson et al., 1977). The gradient was from 75% acetonitrile:25% water
to 90% acetonitrile. Acetonitrile (90%) was pumped through the column for
five rain before recreating the initial conditions.
Chironomid extracts were analyzed by HPLC with a Var.^an Fluorichrome
detector with 7-54 and 7-60 ewcitat, ->c filters (bandpass 230-390 nm, peak
360 nm) and 4-76 and 3-72 emission filters (bandpass 430-6'iO nm, peak 525
nm). Gradient elution was from 30% acetonitrile to 90% acetonitrile in
water at 2%'min
bft
-------
Data Analysis
Distribution of B(a)P and metabolites in a static uptake test is
represented schematically in Figure 4.5.1. The data supported the assump-
tions of 1) constant water B(a)P concentration, 2) low water metabolite
concentration (K. ~ 0)- Under these conditions, bioconcentration of total
C was describedoy equation 4.5.1.
d C
_
— :
at
where
K • C - (K . + K , ) • C (4.5.1)
= u w d dm a
14 -1
C = C concentration in animal (ng-p , wet wt)
C = C concentration in water (ng-ml )
K = B(a)P uptake rate constant (h ;
K. = B(a)P depuration rate constant (h )
K, = Metabolite depuration rate constant (h )
Low metabolite concentration in water and high metabolite concentration in
chironomids suggested that K. « K , and a single overall depuration rate
constant designated K, was assumed. Equation 4.5.2 is the integral form of
equation 4.5.1 using these assumptions.
c "(Kd't}
a u d w
This is the familiar first order equilibrium model, and at steady
state, the bioconcentration factor (BCF) can be calculated as shown in
equation 4.5.3.
Cg/Cw = Ku/Kd = BCF (4.5.3)
A simple two compartment model (equation 4.5.4) which uj'd not assume con-
»tant water concentration but does assume constant mass within the
uysteoi was also used to estimate ,1 and K, (Giesy et al., 1980).
u d — —
"a = I(Ku ' 'total' ' (VKd» (1-e"(Ku * KdH) <*'*.4)
where
14
Q = mass of C in animals
14
Q . = total mass of C in experimental system
to ta L
59
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B (o)P
METABOLITES
KU
KD
KD
m
B(a)P
Km
METABOLITES
WATER
ANIMAL
Figure A.5.1. Distribution of B(a)P and nielnbolites in static uptake test.
60
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Large concentrations of metabolites in chironomids indicated a large bio-
transformation rate. There were insufficient data to merit independent
estimates of K using a model analagous to equation 4.5.1 for chironomid
metabolite accumulation. The importance of biotransformation was.,shown
instead by comparing calculated BCF (K /K ) with steady state total C and
B(a)P. Loss of C in depuration experiments was biphasic. Rate coef-
ficients were estimated from semi-log plots by linear least-square fits.
Rate constants, steady state concentrations and asymptotic 95% confi-
dence limits were estimated by the Marquardt iterative least squares pro-
cedure (Procedure NLIN, Statistical Analysis System, Barr et al., 1979).
RESULTS AND DISCUSSION
Data from triplicate uptake experiments were fit to. one compartment
and two compartment models (Table 4.5.1). Kinetics of C accumulation
were accurately described by the one compartment model. Bioaccumulation
was rapid and steady state activity was approached after eight hours.
The uptake rate constant (K ) for the one compartment model was 214 ±
20 li when calculated from water and animal concentrations. A one compart-
ment model is only appropriate if water concentration is constant. When
calculated from activity measurements, water concentration was 1.38 ± 0.32
ng -ml (X± SE, n = 3) initially and did not decrease^ significantly
during the course of the experiment (1.11 ± 0.25 ng-ml after 8 h).
Analysis by TLC and HPLC indicated no measurable amounts of non-B(a)P
materials in the control water (no chironomids) or after two hours in water
containing chironomids. After eight hours, water containing chironomids
had 86% of C as B(a)P and 14% as unidentified metabolites. It was con-
cluded that water activity through eight hours was an acceptable measure of
B(a)T concentration.
If water concentration changes significantly, and observed losses are
into the animals, a two compartment model is required. Two compartment
models have a major advantage in not requiring a constant source term;
however, a knowledge of total mass is required. They can be used in ex-
perimental systems where mass additions can be controlled but may be of
limited use in natural systems with unknown mass additions.
.1
The depuration rate constant (K = 0.22 ± 0.04 h ) was estimated
jsing the one-compartment model from data collected during the exposure
phase. The time required for loss of 50% of C was between 3-4 h. The
two compartment model estimate of the same constant (K^. = 0.15 ± 0.001 h )
was in good agreement.
Depuration rate constants were also estimated by placing exposed
animals in clean water (Figure 4.5.2). A semi-log plot of depuration shows
a slope change between four and five hours, which suggests biphasic depura-
tion. Animals in chambers containing cubstrate depurated about 60% of
initial.activity within 4 L. The initial depuration rate constant (K. =
0.22 h ) agrees well with the overall depuration rate constant calculated
61
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Table 4.5.1. Bioaccumulation parameter estimates for total l C in Chironomus riparius using one
and two - compartment models.
~~~~ ~^~ ~~ ~ Depuration
Model and Assumptions Parameter Estimates Half-life (hr)
One Compartment K K^
-CK.-t) "
C = (K /KJ • C • (1-e ) 214 ± 20 0.22 t 0.04 3.1
a u d w
Assumes Constant Infusion
B(ajP Concentration Units (ag-g wet
weight in animal; ng-ml in water)
Two Compartment K K.
S -(K +K.)t " h
Q =l(K -Q ,)/(K -HK,)](l-e U d ) 0,039 ± 0.003° 0.15 ± 0.001 4.8
, ,
a u total u a
Assumes constant B(a)P Mass Balance
within experimental system
Assumes density of water is 1 g • ml
In concentration units 0.039 ± 0.003 h" = 190 ± 15 h" , which compares favorably with one com
partment m<">del.
All parameter estimates = Mean ± SE, for pooled data from triplicate experiments.
-1 -1 14
K = Uptake rate constant (h ); K = Depuration rate constant (h ) ; Qa = Mass C as B(a)P
(ng) in experimental system; t = hr.
-------
1000
800
600
E?
I 400
£
C7>
200
K-l=0.06 hr'1
o No Substrote
• Substrote
] X ± S. D.
100' 1'' ' ' ' .',
0245 810 15 20 25 30 35 40 45 50 55
HOURS
Figure 4.5.2. Dopurytion of C by C. £_ilKirj_ns wiLli and witliput subst IM Lt;.
ConconlrnLion is cxprc-usotl . ,>s ng B(o)P • fc (wot vcight)
cliiroiioniid, assuming all C is B(.i)P. Eacli point is the
mo;in of 3 determinations + SO.
63
-------
from the accumulation data. The initial depuration includes a component
due to K- from 4-24 h. This component was comparatively small (K. = 0.04
h ) and accounted for 22% of initial activity released. Between 24-55 h,
19% of the maximum C concentration attained remained as bound B(a)P and
metabolites. Animals exposed to clean water in the absence of substrate
also exhibited biphasic depuration but the rates were consistently slower.
Approximately 23% of the initial activity was rapidly released. The slower
depuration was not complete when the experiment was terminated after 55 h.
As noted, the initial depuration rate constant was similar to the overall
depuration constant derived from a monophasic model and that for B(a)P the
monophasic model was adequate to summarize the data. This initial rate
constant gives the best overall estimate of net flux of B(a)P and metabo-
lites from chironomids for ecological fate studies.
The mechanism by which substrate increased depuration in chironomids
is unknown but may involve increased biotransfonnation of B(a)P related to
gut processes, an active role by bacterial food, behavioral changes by
chironomids ,on the paper towel substrate, or increased gut contents into
which the C labeled compounds can partition. Simple clearance of gut
contents was probably not important in observed initial depuration since
animals were starved for eight hr prior to exposure and for eight hr during
exposure. More rapid depuration by feeding animals may be due to par-
titioning of B(a)P from the animal into uncontaminated food. Synthesis and
excretion of the peritrophic membrane has been shown to facilitate excre-
tion of DDT by mosqaito larvae (Abedi and Brown, 1961) and may be impor-
tant. Alternatively, Herbes and Risi (1978) reported that feeding de-
creased the rate of depuration of anthracene from Daphnia pulex. Only 10%
of activity in chironomids was associated with exoskeleton (Figure 4.5.3).
Therefore, surface losses were probably not important in the initial depu-
ration rates we observed. Exoskeleton may influence initial uptake rates
in chironomids since nearly 50% of activity after 0.5 h was in the exo-
skeleton.
BID-TRANSFORMATION
Information on biotransfonnation is important in hazard assessment
because some metabolites of B(a)F are mutagenic and carcinogenic (Lehr et
al. 1978). The biotransfonnation of I?(a)P by C. riparius was raj.id. After
1 h 43 ± 2% (X ± SE) of chironomid C activity existed as non-B(a)P me-
tabolites, as determined by TLC, and after 8 h 72 ± 2% was non-B(a)P (Table
4.5.2 and Figure 4.5.4). The large percentage of metabolites was not due
to B(a)P oxidation on TLC plates as evidenced by a 92.3 ± 3% recovery of
C - B(a)P from spiked chironomid controls. Biotransfonnation of organic
compounds is common and has been reported for chironomids (Kawatski and
Bittner 1975, Estenik and Collins 1979). The rate of biotransformation,
calculated from metabolite activity and known B(a)P specific activity, was
3.2 ± 0.5 nmol • g dry weight • h (Table 4.5.2). This rate compares
favorably, with that for conversion of aldrin to dieldrin (1.44 nmol • g
• h ) reported by Estenik and Collins (1979). The large biotransformation
rate at 0.5 h is likely due to sampling time errors, as suggested by the
64
-------
o>
Whole Chironomids
Viscera
Exoskeleton
08 10
Uptake-* I Depuration
135
14
Figure 4.5.3. Uptake nnd loss of C in whole C. riparius, exoskclcton and
viscera. Each point represents the mean of 3 determinations
+ SD.
65
-------
O>
Table A.5.2. biotransformation of C - B(a)P by Chironomus riparius
HOURS
0.5
1.0
2.0
4.0
8.0
% RECOVERY*
1A2 ± 33 C
103 ± 23
97 ± 13
80 ± A
77 ± 6
14C - B(a)P
TLC
767 ± 137
1166 ± 199
13A9 ± 217
1935 ± 115
2085 ± 291
(ng • g )
KPLC
N.D.
N.D.
2180 ± 286
2372 ± 115
2760 ± 286
% METABOLITES1*
57 ± 9
A3 ± 2
57 ± 2
60 ± 2
72 ± 2
BIOTRANSFORM|TION_£ATE
(nmol • g • h )
TLC HPLC
7. A ± 3.0
3.6 ± 0.7
3.6 ± 0.9
2.7 ± 0.3
2.7 ± 0.6
N.D.
N.D.
1.9 ± 0.7
2.2 ± 0.3
2. A ± 0.9
DPM of sample extracted/DPM of sample combusted.
PPM Total - PPM B(a)P x 100.
DPM Total
Mean ± SE, n = 3.
-------
lOQOr
._ 800
0)
c
600
400
200
• TotalI4C
* I4C BaP
I X±S.D.
4 5
HOURS
8
Figure 4.5.4. Accumulation of C R(a)P (A) ns determined by TLC, and
B(a)P plus metabolites (o) expressed as ng Ii(a)P * g (wet
weight) chironomiu. Each point represents the mean of 3
determinations ± SD.
67
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large standard error. While the data are not sufficient for careful sta-
tistical analysis, it was concluded that there was no apparent change in
biotransfonnation rate with time.
The rapid biotransfonnation observed will cause the bioconcentration
factor (BCF) reported in terms of parent compound to be very low. Indeed,
Lu £t il- (1977) reported a BCF of "0" for B(a)P in fish due to complete
biotransfacmation. The high uptake rate constant and ACT reported here in
terras of C suggest very large accumulation of B(a)P metabolites, some of
which may be carcinogenic. Accumulation of metabolities may be the most
important aspect of environmental risk as? jsment for certain PAH. Tor
this reason we have reported both an apparent BCF (total C) and a true
BCF (parent compound only). The major metabolites depurated into water
during the uptake phase were polar compounds. Using co--chromatography of
authentic standards, the major metabolite was determined to be 3-hy-
droxy-B(a)P and represented 4.4% of water activity after 8 hr. This com-
pound has also been reported as the major metabolite in mammals (Nebert and
Gelboin 1968). The 3-hydroxy B(a)P was fluorescent blue on the original
TLC plate, but became a fluorescent red air oxidation product on co-chroma-
tography plates.
Small amounts of three other metabolites were detected. These had
relative abundances of I) 0.35, II) 0.06 and III) 0.015 compared to 3-hy-
droxy B(a)P. Metabolite I had en Rt value corresponding to 7-hydroxy-B(a)P
in the original 2-dimensional TLC plate, but apparently degraded and did
not move from the origin after transfer and co-chromatography with stand-
ard. Metabolites II and III were tentatively identified as the 9,10- and
7,8-dihydrodiols of B(a)P respectively. In general, the metabolites were
quite labile and degraded relatively rapidly, even in the dark at -20°C
under organic solvent. Some of the polar compounds observed may have
resulted from degradation during storage of both water and chironomid
extracts. Rapid analysis after sampling is recommended.
14
, It was assumed that all C was B(a)P and an apparent BCF (ng B(a)P •
g wet weight/ng B(a)P -ml ) of 650 was calculated from chironomid
steady state activity at eight h. An estimate of 970 was obtained using
the ratio K /K.. The presence of substantial quantities of non-B(a)P
materials in chironomids (Figure 4.5.4, Table 4.5.2) indicated fhat bio-
transformation was significant, and the actual BCF was about 200. B(a)P
was at apparent steady state after 4 - 8 h (Figure 4.5.4). Lu et a±.
(1977) reported a similarily low BCF of 107-149 for B(a)P in mosquito
larvae, with only 46% of the activity present as parent compound. South-
worth et &l. (1978) predicted a BCF of 13,000 for B(a)P in D. magna calcu-
lated from the octanol-water partition coefficient, but assumed no bio-
transformation. The difference in BCF between Daphnia and both chironomids
and mosquito larvae was probably related to active biotransfonnation and
excretion processes in the latter.
These studies demonstrate that donor controlled linear compartment
models may be used ^j> predict steady state bioaccumulation of B(a)P and
metabolites (total C) in Chironomus riparius. However, the BCF for
parent compound is reduced by a factor of three relative to that of C by
68
-------
active biotransformation of B(a)P in this species. The frequently used
correlations between octanol-water partition coefficient and bioaccumula-
tion may not be adequate for predictions of B(a)P fate in many species.
69
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SECTION 4.6
EFFECTS OF TEMPERATURE AND-ANTHRACENE CONCENTRATION
ON UPTAKE, DEPURATION AND BIOTRANSFORMATION
OF ANTHRACENE BY CHIRONOMUS RIPARIUS
INTRODUCTION
Midges, important inhabitants of a variety of aquatic habitats
(Oliver, 1971), often represent the largest number of tax and individuals
in Lenthic communities (Jonasson, 1978). Chironomus riparius is often
abundant (10 individuals-m~ ) in polluted streams (Gower and Buckland,
1978). C. riparius is able to metabolize aldrin (Escenik and Collins,
1979) and the PAH benzo(a)pyrene (Leversee et al. , 1981a). Thus, midges
living in periphyton and sediment may be important in the biotiansformation
of PAH and other lipophilic compounds which concentrate in those pub-
strates. Midges may also be an important vector of mobilization of PAH
from sediments to high trophic levels. Emergence of winged adults from
environments polluted with PAH may increase the export *rom aquatic to
terrestrial environments.
Anthracene was chosen for study as a representative of the homologous
series of PAH because of its relatively low volatility (Southworth, 1979),
intermediate water solubility (Leo, 1975), and presence in contaminated
aquatic systems (Sheldon and Kites, 1978).
Regulatory agencies' are faced with predicting the fates of large num-
bers of compounds. Mathematical simulation models may be useful for this
purpose. However, few rate constants for uptake, depuration or biotrans-
formation are available for use in mechanistic, predictive, simulation
models. Also, the effect of external forcing functions on conditional rate
constants is unknown. If conditional rate constants for up^ake, depuration
and biotransformation are not independent of the forcing function, a sta-
tistical relationship may be needed for prediction of these constants.
Two important forcing functions that affect the dynamics of compounds
within aquatic systems and organisms are temperature and concentration of
chemical. One aspect of our study was to determine the relationship be-
tween PAH concentration and the uptake and depuration rate constants and
bioconcentration factor (BCF) in midge larvae. The relationship between
concentration of PAH in water and in aquatic animals has beeu tudied in
Daphnia (Southworth et aj.., 1978) and Callinectes sapidus (Lee et al
1976).
70
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A second aspect of this study was to determine the effects of tempera-
ture on uptake, depuration, biotransfonnation, and BCF. Other authi s'have
observed a negative correlation between temperature and uptake or retention
of trace organic compounds in coho salmon, copepods (Collier et al. t 1978)
and clams (Fucik and Neff, 1977; Harris et al., 1977). However, Fossato
and Canzonier (1976) reported that BCF was not a direct function of tem-
perature in mussels. Also, a temperature optimum has been found for the
mixed function oxidase system which is responsible for tne biotransfonna-
tion of anthracene and other xenobiotics in aquatic organisms (Lee et al. ,
1979; Estenik and Collins, 1979).
MATERIALS AND METHODS
Chironomus riparius larvae were collected from a sewage outfall on
Badfish Creek near Madison, Wisconsin. Cultures were maintained using a
method similar to that described by Leversee et a_l. (1981a) at the Savannah
River Ecology Laboratory for over 20 generations at 25°C. Animals used for
experiments at different temperatures were acclimated for 2 to 3 days prior
to exposure to anthracene. Overall mean weight of 5 dry midges was 3.0 ±
0.1 mg (x ± 95% CI, n = 334) and ranged from 2.2 ± 0.2 mg (n=30) to 3.9 ±
0.2 (n=30). The mean wet to dry weight ratio was 8:1.
Water and Anthracene
Well water (pH^.l) was aerated for several days and filtered through
0.45 pm Milipoce filters to remove particulates. Anthracene
(3.3mCi'nmol , 9- C) was obtained from California Bionuclear Corp. (Lot
#770824) and used without further purification. Radiochemical purity was
determined by thin layer chromatogfaphy to be greater than 98%. All prepa-
rative analytical and experimental procedures were performed under gold
fluorescent light (\ > SOOmn) to minimize phototransformation of anthra-
cene.
Dosing and Sampling
Accumulation flux and uptake and depuration rate const.ants were mea-
sured at four concentrations (1.7, 8.7. 22.3 and 30.5 jJg-£ ) at 25°C, and
three temperatures (16, 25, and 30°C) at 22 pg-JZ . Uptake experiments
were conducted in flow-through systems with a flushing rate of 1-2 volumes
per hour to maintain a constant anthracene concentration and minimize the
accumulation of both C labeled biotransformation products and metabo-
lites. Anthracene concentrations were monitored throughout the study.
Three or four replicate samples of 5 midges were taken after approximately
0.5, 1, 2, 4, 8, 12, 20, and 30 h (Figure 4.6.1). While sampling intervals
varied slightly among experiments, actual length of exposure was used for
computations. For depuration of anthracene and biotransformation products,
midges exposed to anthracene for 9 h were transferred to uncontaminated
71
-------
2 ~ 40
go
cc —
ui
o
o •
o
UJ
z
o
IT
X
h-
z
0
20
10
Observed Volues X±95%C.I.
Predicted Values
_l 1 • 1_
2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
HOURS
Figure 4.6.1.
14
Accumulation of C anthracene by C. rip.-irius at 25°C amJ 22
MR*£ . Tach point represents the mean + 2 SE of 3 repli-
cates. The line represents the least squares fit of equation
2.
72
-------
aerated water containing paper tovel substrate. Three replicate samples of
5 midges and a sample of water taken after 1, 2, 4, 8, 16, 24, and 30 h.
Water was changed if activity was twice background.
Biotransfonnation rates of anthracene were measured at three tempera-
tures (16, 25, and 30°C) at 22 jJg-£~ . Four replicate samples of 30 midget
were taken after 0.5, 1, 2, and 4 h. At 30 C, samples were also taken
after 9 and 18 h.
Extraction and Analysis
£*>
Water samples were placed directly into the courting cocktail (3a70P ,
Research Products International) for C activity determination. Midges
were dessicated overnight at room temperature in glass dessication chambers
and weighed on a model 4700 Cahn Electrobalance. Jotal C in midges was
collected in a 4 ml Carbosorb and 15 ml RPI 3a70B scintillation cocktail
by combustion by a model 306 Packard sample oxidizer. Internal and exter-
nal standards indicated C recovery greater than 99% and no carryover of
*V
Biotransfonnation products of anthracene were measured in undessicated
midges which had been blotted dry. Samples were stored in a solution of
ethylacetate:acetone (4:1, V/V) at -40 C until they were extracted.
Samples were homogenized in a Ten Broeck homogenizer and extracted twice
with 5 ml of ethylacetate:acetone (4:1, V/V) and once with 5 ml of cyclo-
hexane. The extracts were combined and filtered through Whatman #40 paper.
The extract was evaporated to 0.5 ml under a stream of nitrogen. Activity
was determined from a 50-(Jl aliquant. The filter paper was burned, count-
ed, and reported as unextractable metabolite. Mean (± 95% CI) recovery of
spiked samples was 88 ± 11% (n=5).
Aliquants of 200 ul were spotted and chromatographed on precoated
silica gel thin layer chromatography plates (E. Merck) in hexane:benzene
(9:1, V/V) and pentane:ether (9:1, V/V). Developed plates were sectioned
into 4 to 5 parts corresponding to the origin, anthracene, and 2 and 5
o£her spots visualized by UV light. Spots were scraped into RPI 3a70B for
C activity determination. The origin, non-anthracene spots and filter
paper are reported as total metabolite (see Figure 4.6.6). Biotransfor-
mation rates were determined by dividing total metabolite by duration of
exposure (see Figure 4.6.5).
14
C activity of all samples was determined using a Beckman model 81Ci<
liquid scintillation counter. The samples were corrected for backsround,
quench and counting efficiency. The quench and counting efficiency were
corrected using a quench curve and the samples channels ratio method.
Counting efficiency for water and combusted insects were 85% and 8V?. re-
spectively.
73
-------
Data Analysis
Rate constants, BCF and asymptotic 95% confidence limits were esti-
mated by Harquardt iterative least squares proceedurcs (proceedure NLIN,
Statistical Analysis System, Barr et al . , 1979), with a one compartment
donor dependent model (equations 4.6.1 and 4.6.2) (Giesy et al,. , 1980;
Hamelink 1977).
dC
a (K -C ) - (K.-C ) (4.6.1)
— — = u w da
dt
where :
C = concentration of C in midge (anthracene equivalents)
d
C = concentration of C in water (anthracene equivalents)
K = uptake rate constant
u r
K, — depuration rate constant
t = exposure time (h) .
Since CW was constant and assuming 1 ml water = 1 g, the integrated analyti-
cal solution of equation 4.6.1 is given by equation 4.6.2.
Kn '(V^
C = — C (1-e d ) (4.6.2)
aw
Kd
At steady rate state the BCF can be related to the rate constants for uptake
and depuration by equation 4.6.3.
(4.6.3)
F = FT = BCF
w d
Since K and K, were estimated simultaneously by numerical methods,
the> were highly correlated. Bias introduced into one estimate by violat-
ing assumptions can affect the other. Therefore, we estimated K and K. by
several other techniques which made different assumptions.
Independent estimates of K were also calculated from slopes of tan-
gents to the uptake curve at 1 h. This initial rates technique assumes a
first order relationship with respect to CW and no initial depuration (K =
slope / C ). The overall depuration rate constant (K ) was also estimated
from data collected during the clearance period, when midges were not ex-
posed to anthracene. The overall depuration rate constant was estimated
from the slope of the first log-linear component of the depuration curve.
The component K, , contributing to the overall K, were estimated concur-
rently by equation 4.6.4.
74
-------
n -K..'t
C = Z C -e dl (4-6.4)
at ai
where:
C = concentration in midge at time t
t = time from cessation of exposure
C . = initial concentration in i component
i = individual depuration component
K.. = depuration rate constant for i component
n = number of independent depuration components
RESULTS AND DISCUSSION
Uptake of C-anthracene was rapid and approached steady state in 25
to 45 h (Figure 4.6.1). The uptake rate constant for C increased by_a
factor of approximately 3 over the. concentration range 1.7 to 30.5 pg'£
(Figure 4.6.2). Few studies have computed rate constants for the accumu-
lation of PAH by aquatic i'ivertebrates. However, Herbes and Risi (1978)
report a first-order uptaKe rate constant of 1.01 h for anthracene ac-
cumulation by Daphnia pulex.
14
As exposure time increased, K based on C generally decreased (Table
4.6.1). Since K and K, were estimated simultaneously from C data, they
may be biased by accumulation of biotransformation products. This will be
discussed more fully in the sections on depuration and biotransformation.
The decrease of K may also, be due to a decline in swimming and activ-
ity. The speed of the normal swimming motion of midges decreased as dura-
tion of exposure increased. Midges in uncontaminated water also showed the
same activity patterns. Slower swimming activity could be expected to
increase the boundary layer of less concentrated anthracene and thus reduce
exposure concentration. Respiration and metabolic rates, as manifested in
swimming rates (Walshe, 1949) could also influence uptake rate. K values
measured at 25° and 30°C were not significantly different, but were higher
than that determined at 16° (Table 4.6.1).
Depuration
Depuration rate constants were greater at higher anthracene concentra-
tions (Table 4.6.1). As exposure time increased, a larger fraction of the
C was in the bound than extractable pools. Therefore, K decreased with
75
-------
1000
100
10
In KU= 3.99 + 0.045 CW
1.7
(CW)
6.7
|4C-ANTHRACENE
22.3 30.5
CONCENTRATION
IN WATER (ng • mL~')
Figure 4.6.2. Lo£ K for C. ri par ins at 4 different concent r.it ions of
nnlhracenc in water. Futim:itc + .isymptotic 95% CI.
76
-------
Table 4.6.1. Uptake (K ) and depuration (K ) rate constants in C. riparius at four concentrations
and three temperatures (estimate 1 95% CI).
Concentra-
tion
t% ™ -*
Tempera- K
ture "
Kd
Ih
ab
lOh
30h
lOh
30h
3h
30h
1.7
8.7
22.3
30.5
22.2
22.3
22.7
25
25
25
25
16
25
30
82
79
193
2.»5
128
193
153
77±21
54±13
161112
222*32
116110
161112
157.114
68113
74110
155116
143120
io?.±n
155116
;52il6
0.07010.
0.10710.
0.27610.
0.09110.
0.10710.
0.08910.
073
021
070
023
021
026
0.03510
0.04110
0.08510
0.07810
0.05310
0.08510
0.08910
.019
.014
.014
.017
.011
.014
.015
0.07710.
0.21510.
0.15810.
0.09310.
0.14410.
0.15810.
0.26ciO.
023
078
176
014
027
018
139
0.31110.224
0.23610.098
0.24710.101
0.17710.120
0.25010.457
0.24710.102
0.36310.231
a. Duration of test. All values estimated from concentration of 143-anthracene in midges (ng-g
wet weight).
b. Estimated from tangent to slope at 1 h.
c. Estimated from C-anthracene uptake experiments using donor dependent uouel (equations 4.6.1
and 4.6.2).
d. Measured as slope during initial 3 /. depuration in uncontaminatcd water and paper towel sub-
strate after 9 >; exposure.
e. First component of overall depuration race constant calculat3vl-with equation 4.
-1
-------
time, since a smaller proportion of the * C material was available for
depuration. Polar biotransformation products have been shown to be elimi-
nated more slowly by many aquatic animals (Land runt and Crosby, 1981a and
198lb).
Depuration rate constant was not affected by temperature (Table
4.6.1). Because most metabolic functions are temperature dependent over
the normal temperature range encountered by animals one would expect that
both biotransformation and active elimination would be affected by tempera-
ture. The fact that we see no effect of temperature ou the depuration rate
constant, based on C activity, is probably due to a complex interaction
of temperature effects on metabolism, excretion and anthracene biotransfor-
roation.
When nidges, which had accumulated anthracene, were placed in water
with paper towel substrate, no effects of temperature or concentration on
K. were observed. K. values, calculated from the donor dependent model (Equa-
tion 4.6.2), were generally lower ia the abs-nce of paper towel substrate
than when paper towel substrate was present (Ttble 4.6.1). Leversee et at .
(1981) observed greater rates of depuration of benzo(a)pyrene, (B(a)P),
froa* C. riparius in the presence of paper towel than in the absence of
paper towel.
14
We observed biphasic depuration of Oanthracene (Figure 4.6.3). The
two phases may represent depuration of anthracene from two storage compart-
ments, or depuration ol anthracene and its biotransf onaation products which
are more polar. Herbes and Risi (1978) observed a multiphasic depuration
of anthracene from Daphnia puKx. Resolution of these questions would be
difficult in the midge and our studies were oot designed to resolve them.
However, we did resolve the overall depuration rate constant into
several component parts. In each case where we determined the overall and
more rapid depuration rate constants the overall rate constant estimate was
slower than the estimate of the rapid phase (Table '«.6.1). This indicates
that our estimate of the overall K, is intermediate between the more rapid
and slower rates. The overall depuration rate constant, *» estimated by
equations 1 and 2 should be a weighted average of the multiple rate con-
stants (equation 4.6.5).
(4.6.5)
where:
K. - overall depuration rate constant
78
-------
'0
CE ^^ C
H- —
Z ?
UJ .-
u «
z ^
o~
O1
Ul .
s -
u ,£.
ce
x
o
J_
J_
J_
10 12 14 16 18
TIME (h)
2O 22 24 26 28 30
Figure 4.6.3.
Depuration of C anthrjrene by C. rip .iritis in
water and pjpcr towel substr.ite at 30°C. X *
unconljminJLcd
2 Sc, n = 3.
79
-------
C = initial concentration of i component
K = i depuration rate constant
For predicting body burdens in populations we feel that this level of
resolution is not necessary and advocate use of the overall depuration rate
constant. If one needs to resolve depuration rate constants, we suggest
that estimates be made by fitting the data, using equation 4.6.4, by inter-
ative least squares techniques rather than the "back stripping" technique
of Wagner (1975). It can be seen tuat unless the sample size is large, the
confidence intervals for the estimates are very large (Table 4.6.1).
After two depuration phases had been identified, a residual of approx-
imately 20% of the initial C still remained bound in the animal at 30 C
(Figure 4.6.3). This residual was .depurated very slowly or not at all.
The slope of the log-transformed C concentration as a function of time
was not significantly different from zero.
Biotransformation
The biotransformation rate was maximum at 25°C (Figures 4.6.4 and
4.6.5). Because the biotransformation rate was high, percent anthracene
was minimum at 2S°C. The mass of anthracene itt the midges, however, was
maximum at 30°C because accumulation of C was as high, but biotransfor-
mation was lower at 30° than at 25°C.
The tetnperature effect indicates that the enzymes responsible for the
biotransformation are responding optimally at 25°C. Estenik and Collins
(1979) found in vitro aldrin expoxidation activity in C. riparius by mixed
function oxidase was greatest at 30°C. Thus, the decline in biotransforma-
tion froM 25° to 30°C was probably due to a decline in the overall physio-
logical state of the midges and cot due to enzyme efficiency. Additional
evidence for reduced physiological fitness at 30°C was seen in culture
growth. Cultures of midges maintained at 30°C did not remain viable,
whereas those at 25"C propagated successfully.
At 16°C, the overall biotransformation rate was slower than at higher
temperatures (Figure 4.6.6). Additionally, the proportion of biotr^nsfor-
mation anthracene that was unextractable was smalle: -„ at 16°C. This sug-
gests that biotransformation involves several processes which respond
differently to temperature. Likewise, Varinaui et aj_. (1981) found that
the relative concentrations of different naphthalene biotransformation
products in starry flounder also changed with temperature.
The bfotransformatioo rate decreased during the first 4 h (Figure
4.6.5). This stay have been due to a decline in respiration, as discussed
earlier, or to a build-up of biotraoBforniation products and end product
inhibition. Leversee et aj.. (1981a) found a similar decrease in biotrans-
formation rate in midges exposed to B(a)P. However, at 30°C biotransforma-
tion rate tended to increase after 4 h (Figure 4.6.5).
80
-------
I<+U
Ul
< ~i2o
a •
.e
| O.'00
< £• 80
S T>
o: -"
0 7 60
(^ 0>
< - 40
S o
£ 6
0 c 20
CD ~~
Q
16'C
25"C
, 30°C
V 1
u
1 l
r
1
•\
V
n
f
-\ , 4
\ ^.-•-"""'"'^
r^ ^.-— •• — '
^-k x^ .. -"
i -Os T 4— —
^ 1-
\ ',
i ~~~\
*
• I I t 1 1 1 1 t l l 1 t t ! f 1 1 1
0 2 4 6 8 10 12 14 16 18
TIME(h)
Figure 4.6.4. Biolransform.ition rate after 1 h exposure as a function of
tempera lure, X + 2 SE, n = 4.
81
-------
ui
5
o
,4
'2
to
«•« .0
O
« 6
•e
80 - % Recovery
- Unextroctoble metcbolito
- Exlroctoble metobolite
- Anthracene
78
73
92
80
66
79
76
73
76
76
Temp.CCne 25 30 162530 162530 162530 30 30
Length of
Exposure(h): 0.5 I 2 4 9 10
4.6.5. Biotrnnsfonn.TUon r.ttc .is A fnnclio.i of timo of cxjiosurc and
tempc 1.1 Lure. X + 2 SE, n = A.
82
-------
120
UJ ~-~
^ •
il
60
2 5 40
CD
20
10 20
TEMPERATURE (°C)
30
Figure 4.6.6. Biotr.inuforra.iliou of C .inllir.'iccno at 16, 25 anJ 30°C.
+ ?. SK, n - it.
83
-------
At 30°C, the percent of C that was anthracene decreased with length
of exposure from 48% at 0.5 h to 9% at 18 h (Figure 4.6.6). The trend was
less pronounced at the other temperatures^ Between 4 and 18 h, anthracene
concentration decreased by 2/3 while the C activity ro^ by a factor of
2.7. However, at all temperatures percent unextractable C increased with
time.
Bioconcentration Factor
-1 14
Bioconcentration factor (BCF), calculated using KU*K. based on C,
was not affected by temperature or concentration in the water (Table
4.6.2). Other studies with aquatic organisms, Canton et al. (1978),
Blanchard ct al.
Table 4
14
.6.2. Bioconcentration factors (BCf) for C-anthracene in the m^dge
C. ripai jus. BCF for total C wad calculated from K^K^
after 10 and 30 h of uptake. BCF for anthracene was calculat-
ed from concentrations of anthracene at 4 hr. x ± 95% CI.
Concentration
Temp
BIOCONCENTRATION FACTORS
(ng-ml )
1.7
8.7
22.3
30.5
22.2
22.3
22.7
(C)
25
25
25
25
10
25
30
10 h
9151532
15031206
8041104
12771245
15031206
16971384
14C
30 b
19641722
18171388
18201136
18431180
1915*228
18201136
17021119
Anthracene
4 h
132139
47115
9515
(1977) and Wilkes and Weiss (1971) have likewise shown that BCF was con-
stant at different concentrations. Similarly, bioaccuamlation was found to
be unaffected by temperature in Mytilus edulia (Fossoto and Canzonier,
1976). Bioconcenlration factor predicted from the 30 h data set was usual-
ly higher than BCF from the 10 ^ data. The difference is probably due to
accumulation of non-anthracene C. The BCF calculated for anthracene in
b£otransfonnation studies was more than an order of magnitude lower than
C-BCF, due to rapid biotransformation of anthracene. Steady state had
not been reached by 4 h so a true BCF can not be calculated. Intcresting-
84
-------
ly, at 30°C, the concentration factor lit 18 h was 68 ± 17, which is 2/3 of
the concentration factor at 4 h. Concentration factor was lowest at 25°C
and reflected the biotransformation rate.
BCF was more strongly affected by differences in biotransformation
rate due to temperature than by differences in uptake rate due to tempera-
ture. For example, BCF was highest at 16°C because biotransformation was
lowest, even though uptake rate and concentration were also lowest at 16°C.
Consequently, caution must be exercised in comparing BCF for roetabolically
transformable compounds. As we found with anthracene in chironomids,
C-BCF leads to overestimation of bioconcentration potential.
Benzo(a)pyrene and Anthracene
Since octanol:water partitioning coefficient has been positively cor-
related with BCF (Neely et aK, 1974), benzo(a)pyrene (BaP) would be expec-
ted to have a larger BCF than anthracene. The C-BCF of anthracene (915
at l.J ng-ml" ) was similar to BCF for B(a)P in C. riparius (970 at 1.0
ng-ml" ) (Leversee, et. al., 1981a). Though both K and K. were slower for
anthracene, the C-BCF \alues were similar for anthracene and B(a)P be-
cause their relative proportions remained constant. The A h accumulation
factor based on parent compound was approximately 4 times greater for B(a)P
(200) than for anthracene (47), as might *>e expected from the octonol:water
partitioning coefficient predictions. Bioaccumulation was calculated using
parent compound at 4 h, since steady: .state was not easily recognizable.
The difference between BCF based on C and BCF based on parent compound
for anthracene compared respectively to those for B(a)P indicates a slower
eliminaticn of anthracene biotransformation product. Relative rate.s of
biotransformation on a molar basis were similar for B(a)P (2.7 mnol-g -h
at 4 nraol'Jfc ) and anthracene (51 nmol-g 'h at 125 nux>l'£~ ) considering
the-difference in concentration.
CONCLUSIONS
dC
14 a 1.
Accumulation of C-anthracene is described by the model dt = (K -C )
- (Kd-Ca) (Equation 4.6.1). u w
2. Uptake rate constants are temperature and concentration dependent.
3. Bioconcentration factor based on C is not affected by concentration
or temperature.
4. Bioconcentration factor based on anthracene is minimum at 25°C and iu
inversely proportional to rate of biotranaforroation.
85
-------
SECTION 4.7
UPTAKE, DEPURATION AND BIOTRANSFORMATION OF ANTHRACENE
BY THE CLAM, ANODONTA IKBECILLIS
INTRODUCTION
Uptake and release of polycyclic aromatic hydrocarbons (PAH) and other
petroleum hydrocarbon compounds by marine bivalve molluscs have been the
focus of much research in recent years. Being sessile filter feeders,
clams are readily exposed to pollutants (Nunes and Bcnville, 1979), and it
has been suggested that these organisms could be used as worldwide monitors
of hydrocarbon pollution (Stegeman and Teal, 1973; Goldberg, 1975; Fossato
and Canzonier, 1975; Dunn and Stitch, 1975; DeSal/o et al., 1975, Bravo et
al., 1978). The general conclusions of past studies of hydrocarbon inter-
actions with clams have been that 1) uptake is rapid (Nunes and Benville,
1979), but can be highly variable (Jackira aud Wilson, 1977), 2) depuration
consists of several release compartments (i.e. fast and slow) (Dunn and
Stitch, 1976) and depuration half-life is directly dependent on the length
of exposure to a pollutant (Bochra and Quinn, 1977; Jackim and Wilson,
1977), and 3) biotransformation of hydrocarbons by molluscs is minimal or
nonexistent (Carlson, 1971; Lee et o_l., 1972; Dunn and Stitch, 1976; Nunes
and Benville, 1979). This lack of biotransformation is probably due to the
fact that molluscs are deficient in mixed function oxidase enzymes (Neff et.
al_., 1976; Bend et aj_. , 1977; Moore, 1979). Molluscs have also been found
to selectively concentrate PAH compounds relative to other hydrocarbons
(Lake and Kershrner, 1977).
PAH studies concerning freshwater invertebrates have centered on Daph-
ni£ sp. (Herbes and Risi, 1978; Southworth et aK, 1978) and chironomids,
which hive been shown to have a high biotrensformation potential (this
report). The primary objective of this study was to determine fluxes and
rate constants for uptake, depuration and biotransforroation of anthracene
by the freshwater clam Anodonta imbecillis. The symmetry of the anthracene
molecule lowers the number of possible metabolites compared to other PAH
compounds, such as benzo(a)pyrene, making the assessment of biotransfor-
mation readily feasible. An ideal freshwater monitor organism the paper-
shell clam, A. imbed 11 is, is a common member of the benthic community of
lakes and large rivers of North America, Europe, and Asia (Pennak, :953).
86
-------
MATERIALS AND METHODS
Anodonta imbectllis were collected August 4, 1980 by SCUHA from PAH
pond (on the Savannah River Plant, Aiken, S.C.) at depths from 1.5 to 3.0
meters. Clams were returned to the lab and held for 2 days in a tank con-
taining aerated, PAR pond water at 25°C. Twenty-four hours before the
experiment was initiated, eight clams of similar sii.-e (X valve length =
7.07 ±.315 cm) were cleaned externally, and placed in individual aquaria
containing filtered (0.45 M™). aerated, PAR pond water to allow for gut
clearance. The clams were blotted and weighed before transfer to experi-
mental chcmbers. Mean tissue weight was 17.41 ±.82 gm, wet weight.
14-C anthracene was added in bulk to > 0.45 uffl filtered PAR pond water
allowed to equilibrate for 2 hours, and then 1.1 £ was added to each of the
5.0-£ (covered) glass experimental aquaria. To allow for adsorption to the
walls, the aquaria were left for an additional hour. The fiaaljCquilibrat-
ed concentration of 14-C anthracene was 31 ug-£~ (0.68 uCi-£ ). Experi-
nents were conducted at 25 ± 1 C.
Water samples were taken after 0.0, 0.5, 1.0, 3.0, 5.0, 13.0, and 24.0
h and the anthracene concentrations were determined by liquid scintillation
counting (LSC). One ml of water was added to 12. ml of a premixed counting
cocktail (Research Products International 3a70B ). All activity measure-
ments were made by « Beckman Model LS8100 liquid scintillation counter, and
were corrected for quenching using internal and external standards and
sample channels ratio. All procedures involving anthracene were performed
under gold flourescent light (A > 500 run) to minimize photodegradation.
After 24 h of exposure to anthracene, three of the remaining six clams
(2 died during the experiment and were not used in the analysis) were i e-
moved and frozen for extraction and analysis. The other three clams w>,-re
placed in aquaria containing 2.0 £ of uncontaminited filtered PAR pjnd
water for depuration studies. Before transfer to :'reezer bags or depura-
tion chambers the clams were dipped in clean pond water and allowed to
drain to remove 14-C activity from loosely bound water on the surface of
the shells. Water samples were taken after 0.0, 0.5, 1.0, 1.5, 3.0, 5.0,
12.0, and 24.0 h, and water activity was measured by LSC to determine the
rate of depuration from the clams.
For tissue analysis, individual clams were homogenized in a Ten Broeck
tissue homogenizer. Emptied shells were blotted and wet weight determined.
14-C combustion analysis was used to determine the final total anthracene
tissue concentration. Tissue extracts were analyzed by thin-layer chroma-
tography (TLC) and HPLC to determine concentrations of possible biotrans-
fomuition products of anthracene. Clam horcogenate (0.25 ml) was combusted
in a Packard Model 306 sample oxidizet^ for 1 min., and was collected in
scintillation vials with 5 ml Carbosorb and 13 ml Permaflour . Previous
experiments showed, by use of internal and external standards, that recov-
ery of 14-O2 wao 90% but possible contamination of the oxidizer lowered
the percent recovery to 81% during this experiment. Oxidized samples
accounted for 95 ± 27% of the 14-C anthracene in tissues as was predicted
from water data and the mass balance assumption. Extractions for TLC, and
87
-------
extraction and analysis procedures for HPLC are, given in Section 4.6. TIC
separations were made on silica gel plates, one set with hexane-lenzene
(9:1, V/V) and another set with pentane-ether (9:1, V/V) as solvents. The
position of anthracene was determined by comparison to standards parallel
to the samples. Recovery by this technique was 70.7% ± 3.5 (95% C.I.) for
anthracene and 79.3% i 2.9 for anthraquinone, a possible biotransformation
product of anthracene. After "isualization with UV light, areas 1 cm above
and below the 14-C anthracene and metabolite spots were scraped from the
plates and placed in LSC vials containing counting cocktail for subsequent
analysis.
Since changes in water anthracene concentration were used to measure
uptake and depuration by A. imbecillis , it was necessary to determine the
contribution of the shells alone. Weighted and sealed shells were used in
an uptake and depuration experiment which duplicated that with live clams.
Surface area was determined for the shells in all experiments. Uptake and
depuration data obtained from living clams were corrected for calculated
contribution from shells.
A Marquardt iterative lear,t squares method was used to estimate first
order rate constants and asymptotic 95% confidence limits (PROC NLIN, Sta-
tistical Analysis System, Barr et al^. , 1979). Because the dosing system
used in these studies was closed, a two compartment model was used to esti
mate the first order rate constants for uptake and depuration (Equations
4.7.1-4.7.4).
dQa K (4.7.1)
-^ = uqw dqa
AO = Qw + Qa (4.7.2)
assuming equation 6.7.2 is tiue and integrating gives:
-OC+KJ-t
"
and
* A0(l * K - e'(Ku + Kd)
-------
K - first order uptake rate constant
K = first order depuration rate constant
d
AO = total mass of anthracene in system
t = time
t = time zero
o
RESULTS AND DISCUSSION
Shells
A two compartment rood--;! (Equation 4.7.4) was us_e^J to estimate KU and
K for shells. K and K were 0.092 h" ?\ud 0.362 h" respectively during
the first 5.0 h oi the experiment. Only data from the first 5.0 h of up-
take by shells wers used because of loss of anthracene from the water (>
20% aftei: 5.0 h). Liss was primarily attributed to adsoiptioa of compound
to dust particles which accumulated on the surface of the water during the
rarople period. After 2k h of depuration, steady state was reached, and
only 12% of 14-C anthracene hjd been released by the shells (Figure 4.7.1).
This type of almor.t irreversible adsorption raises doubt about the use of a
two compartment model to predict the uptake of this compound by the shells,
or at least in this case, the use of the term 'depuration rate constant'.
Instead of a depuration rate constant, K, reost likely represents a sab-
str.itc saturation rate constant.
After 24 h exposure to 31 fJR anthracene'£ , clams had accumulated
0.71 ± 0.098 pg anthracene/g wet weight (X t SD) of soft tissue (Figure
4.7.2). The predicted steady state concentration (CSS) of 0.75 had been
reached by this time. The first order rate constants for uptake and depu-
ration are given in Table 4.7.1. Uptake appeared to be biphasic for this
experiment (Figure 4.7.2). However, due to the absence of data points
between 13 and 24 h, where the phase shift is suggested to occur, short
term multicompart.mentalization for uptake in thest clams in merely specula-
tive. The literature on compartment theory ib incomplete for short term
uptake circumstances since no previous experiment has exhaustive'y studied
the first 24 h of exposure of clams to organic compounds. The overall
uptake rate constant was estimated as a single value. The two component
nature of the uptake may have beer, due to saturation of a pool such as the
extrapallial fluid, lollowed by partitioning into the soft tissue of the
clam. In otJer to estimate overall rate constants for the 24 h uptake
period, the 13 h data was omitted for use in the two compartment model
since in this experiment raultiphasic uptake was asciuited to be additive.
The model used here assumed that all of the anthracene accumulated by the
clams was from exposure to anthracene dissolved in the wjter. This assump-
tion is supported by the work of Dobrcpki and Epifanio (1980) which showed
that the hard clam (Mercinaria mercinaria) accumulated more B(a)P directly
from water than from B(a)P-containing food.
89
-------
J^~*
1
o
jC
(/)
•
O>
^.
*"•*
to
0
C..C.'
\ B-
1 • U
1.4-
1.0-
0.6
n ?
•
^______ £
* s"1^
/*
s
^
J
£ N ANTHR'ACEN E.'^I N PU J .'^
• - Observed
& - Predicted
tI I i i I r tT T t I ]i ( I i iT i i t I I *
2 6 10 14 18 22 26 30 34 38 42 45 50
TIME (h)
Figure 4.7.1. Accumulation of .mthr.iccnc by A. imln-fj 11 i:; :;lioll .1:: a
function of time. The- fitted line i.s h.ir.c-1 on tlio first 5 h
of upt.ike only because of loss of .-inthr.io'nc from the v.itor,
which ilid net p,o to the cl.ims. Tlii:; rrsulta in a ('ccrc.ise
in the .imounl of anthr.icone .issoci.itcil villi tli'? slu-lls
(points Mtcr 24 h).
90
-------
1.0
u
ui 0.8
o _
< .c
^ .? 0.6
»- 5
< ^ 0.4
^ 0.2
0.0
CA = CSS (
•Observed
- Predicted
ANTHRACENE INPUT
24 6 6 10 12 14 16 18 20 22 24
TIME (h)
Figure U.I.2. Arciimul.iliori of antlirarcnc by soft tissues of A.
a» a function of time. ~
91
-------
Table 4.7.1. First order rate constants for uptake
and depuration of anthracene by A.
imbecillis from 31 pg anthracene.
Estimated by Marquardt iterative
least squares procedure.
SHELLS ~~
Asymptotic
Estimate SE F and P of F
K * 0.092 0.015 F- , = 184
U 2,2o
P<0.0001
K.2 0.362 0.126
d
SOFT TISSUE
Kul 0.0052 0.0006 F - 215
P<0.0001
0.216 0.033
Kd 0.200 0.079 F2 ^ = 57
P<0.001
Overall uptake rate constant with units £'(h'g)~ ,
wet weight
2
Overall depuration rate constant estimated during
uptake phase, with units h .
Single component depuration rate constant esti-
mated during depuration phase, with units h .
Depuration studies showed that compound release is biphasic during a
24 h period with a shift in the depuration rate occurring between 1.5 and
3.0 h after removal from exposure to 14-C anthracene. A oultiphasic depu-
ration model (Equation 4.7.4) gave estimates of 0.118 h for K (0 - 1 5
hrs) and 0.011 h for K (3.0 - 24.0 hrs) (Fig 4.7.3). Theddepuration
rate constant estimate (O from the two compartment model was similar to
the overall depuration rate constant K l estimated from the two component
depuration model. The dispersion in tne data was such that we also used a
single component depuration model to estimate K phase (Table 471) The
overall depuration rate constant was similar to that estimated from data
collected during the anthracene exposure. However, it can be seen that
92
-------
0.2
c
o
O.lL-t
• Actual
— Predicted
10 12 14 16
TIME (hr)
18
20 22 24
4-7.3. D,-pur-iLion of anlhr.iccnc from the clim A
H.U., |,.,vc been fit to .1 two comnonnnT'
93
-------
this rate constant is too great and that there is a slow loss of anthracene
which is not accounted for by this model. Therefore tne best estimate of
the overall depuration rate constant is O.llSh" . However, even this
constant alone would predict the loss of anthracene from the clams to be
more rapid than it really is.
The rates of depuration of PAH from molluscs has been shown to be
non-selective, and slower than from fish or shrimp (Neff et aj.., 1976).
Several investigators have suggested multiphasic deouration of toxins by
aquatic organisms (Dunn and Stitch 1976, Herbes and Rishi 1978, Nunes and
Benville 1979, Boehio and Quinn 1977, Blumer et al., 1970, Stegemen and Teal
1977, Fossato and Canzonier 1976) but again none of these studies dealt
with short term components as in this study. The depuration half-life of
14-C anthracene in A. imbecillis had not been reached by the end of the
sample period and, assuming the occurrence of no asore phase shifts, the
estimated half-life is approximately two days. Hultiphasic depuration and
depuration times which are long relative to the length of the uptake period
are consistent with findings in the literature.
In_a study with Anodonta cataractae, McLeese et al. (1979) found Ky =
0.125 h" and K = 0.015 h for the uptake and depuration of an organo-
phosphate pesticide. While the depuration rate constant is similar to the
K. obtained in this experiment, the uptake rate constant in the HcLecse
paper is much laiger. A lowering of K could possibly be due to the ab-
sence of food in this experiment. It can be argued that a clam which is
actively feeding will accumulate more toxic burden, due to digestion and
assimilation of food material laden with the toxic substance, than a clam
which is siphoning for respiration only. This feeding effect is unknown
and deserves further study. The different natures of the chemicals used by
HcLeesc et a_l. (1979) and this study may also affect K . The predicted
concentration from 336 h exposure to 31 pg anthracene'Z , which was
the average concentration to which clams were exposed in the channels
microcosms, from uptake and depuration rate constants reported here for
laboratory studies is 1.2 pg anthracene'g , dry weight of soft tissue.
This value is more than an order of magnitude less than tl «• 16.7 pg anthra-
cene-g , dry weight, actually observed in clams collected from the channels
microcosms after 336 h exposure. The reasons for this difference could be
many. Foremost, is that the laboratory studies were conducted for short
periods of time and may underestimate the actual rate of accumulation. We
observed clams in the laboratory to remain closed much of the time. Be-
cause the laboratory studies were done for short periods of time the clams
may not have been able to acclimate rapidly enough to give rote constants
representative of those observed in the field. We conclude that laboratory
determined rate constants may not adequately describe the actual kinetics
of accumulation of PAH compounds in natural environments.
Biotrans formation
After 24 h of exposure, little nf the ^C-anthracene had been bio-
transformed. Only 0.9 ± 0.6% of the l\ had been biotransforaed after 24 h
94
-------
of uptake. After a subsequent 24 h depuration period only 1 ± 0.8X of the
C remaining in the soft tissues was biotransformed.
These findings are similar to those of Dunn and Stitch's (1976) sug-
gestion that bivalve molluscs do not possess the capability to m-»abo)ize
petroleum hydrocarbons, and that indeed "the organism's only defense
against toxins is slow depuration" (Nunes and Benville 1979; Carlson 1972).
Stegeman and Teal (1973) also found depuration from clams to bs slow, and
accumulation to be dependent on li, id content. Lake and Kerchner (..977)
reported that depuration of PHA from molluscs was non-selective.
It was observed during the uptake portioa of this study that the clams
were sporadically closing, and were remaining closed for periods up to 0.5
h. During depuration, the clams did not exhibit this behavior and were
rarely observed to be closed throughout the sample period. It appears that
A. imbecillis are sensitive to either the 14-C anthracene or the acetone
which was used as a solvent for the anthracene, la either case, the abil-
ity of these clams to detect small amounts of foreign substance (30 pg'£
14-C anthracene and 15 pl*£ acetone) is worth noting.
CONCLUSIONS
Sealed and weighted shells of Acodonta imbecillis adsorb 14-C anthra-
cene in what can be termed an irreversible fashion. Non-feeding clams take
up significant amounts of 14-C anthracene in 24 h, and this uptake may be
biphasic, although further study as needed to validate comparttncntalization
of uptake. A low uptake rate constant, compared to that from an experiment
with Anodonta cataractae, raay be due in part to the absence of food in this
study. The first order rate constants determined from short-term, simple
laboratory jccumulation studies, result in an overestimation of the concen-
trations attained by A. imbecillis when compared to clams in the channels
microcosms. This may be due t<> many factors, such as current, riltcriTg
time, temperature, suspended particulates or other factors. The important
fact is that the laboratory derived rate constants are poor predictors of
field observations (see Section 6.5).
95
-------
• SECTION 4.6
UPTAKE, DEPURATION, AND BIOTRANSFORMATION OF ANTHRACENE
AND BENZO(A)PYRENE IN BLUEGILL SUNFISH
Direct uptake from water to fish has been shown for several PAH in-
cluding naphthalene, alfcylated naphthalenes, anthracene, and benzo(a)pyrene
Oe
-------
stream within the U. S. Department of Energy's Savannah River Plant near
Aiken, South Carolina. Because of Its extremely low mineral content (60
umhos'cm ), the water was amended with salts to produce a standard soft
test water. Water quality characteristics were: pH 7.4-7.6, hardness A3
mg-« as CaCO , alkalinity 30 Dig-* as CaC(>3, -nd conductivity 140
umhos-cm . Well water, used for several uptake experiments, had similar
quality but lacked the colored organic material found in the blackwater
stream water ^nd was amended to give the same hardness characteilstics as
the amended stream water. Humic acids (Aldrich Chemical Co., molecular wt.
> 300,000: 3.6 g dry wfml" ) were added to well water at a concentration
of 1 mg-£ 1 for certain uptake experiments.
14
Uptake, depuration, and biotransformation were studied with 9- C
anthracene (California Bionuclear Corp., specific activity of 3.3
mCi-mmol ) and 7-10- C benzo(a)pyrene (Amersham-Searle, specific activity
of 21.7 mCi-maol ). The radiopurity of the coippounds vas determined by
two-dimensional, thin layer chromatography (TLC) The purities of anthra-
cene and benzo(a)pyrene were 97.4 + 2.6 and 96%, respectively.
Uptake Phase
Exposures were performed at 23-24.5"C in covered 5-1 all-glass aquar-
ia. All test water was aerated, passed through a Sorvall SS-1 continuous-
flow centrifuge to remove participates, and spiked directly with C an-
thracene or B(a)P. After mixing, the test water was distributed to the
aquaria. Fish were, sorted by size and introduced to the tanks at rates of
100-500 rag fish-£ . No aeration or feeding was provided during testing.
At appropriate time intervals, fish were netted, blotted dry, wrapped in
aluminum foil, and frozen at -20°C.
Depuration Phase
Fish used for depuration tests were transferred to clean flowing water
after 4 h exposure. The fish were held in 5-1 all-glass flow-through
chambers with uncontaminated, unfiltered test water fit a flow rate of 1 -
1.3 S.-h g Hydrocarbons eliminated by the fish were trapped on a 75 ml
Amberlite XAD-4 resin column (Rohm and Haas) placed downstream, as de-
scribed by Crosby et aj.. (1979). No significant radioactivity was detected
in the column eluent during any depuration experiment. The resin was
eluted with diethyl ether, acetone, and methanol according to the method of
Carna* (1975). Trapping efficiency of anthracene was 97 -f 3% and elution
efficiency was 89 + 10%.
Analysis
Fish to be analyzed were weighed before and after being freeze-dried
The dry weight to wet weight ratio was 0.235 (n=45). All concentrations
are expressed on a wet weight basis unless noted otherwise. Cried fish
vere conbusted for one minute in « Packard Sample Oxidizer Model 306.
97
-------
14
Carry-over during combustion was negligible. Recoveries of C activity
from injected dried fish were 46.9% for anthracene and 100% for B(a)P. The
relatively low recovery for anthracene suggested some loss by volatiliza-
tion during the freeze drying process. Therefore, all anthracene experi-
ments were repeated using fish dried in a desiccator (recovery 100%) to
minimize volatilization loss.
8
Water samples and solvent extracts were counted in 3a70B cocktail
(Research Products international Corp.). Samples were counted to a pre-set
time of 10 min on a Beckman LS-8100 liquid scintillation counter. The
samples were corrected for background, quench, and counting efficiency.
The quench and counting efficiency correction was made using a quench curve
based on the sample-channels ratio method. The counting error was SD < 7%.
Anthracene, B(a)P, and metabolites were extracted from dried fish in a
40 ml TenBroeck homogecizer. Each fish was ground with successive 10 ml
fractions of acidified benzene, diethylether (twice), and ethylacetate. The
fractions were decanted, filtered, combined, dried over anhydrous sodium
sulfate, and the volumes reduced. The remaining fish residue was combusted
and counted to determine unextractable C activity. Recoveries from the
extraction of injected samples were 82 + 9% for B(a)P and 93 + 11% for
anthracene.
Metabolites were determined by TLC using E. Merck silica gel plates
without fluorescent indicator. Two solvent systems, hexane:benzene (9:1,
V/V) and pentane:ether (9:1, V/V) were employed separately to resolve B(a)P
from its biotransformation products. Anthracene samples were developed
either in hexane .-benzene (9:1, V/V) or in a two-directional system with
pentane:ether (95:5, V/V) as the second solvent. Hydrocarbon spots were
visualized under UV light, scraped, and the C activity determined.
Extracts were also analyzed by high pressure liquid chromatography.
Separations were made with a tticro-Pak MCH-10 reverse-phase column (35 cm
long) equipped with a Whatman guard column of Co-Pel C RODS on 35 pm parti-
cles using gradient programmed elution conditions at ;28°C. The gradient
was from 45% acetonitrile in water to 90% acetonitrile iu water. Acetoni-
trile (90%) was pumped through the column for five min before recreating
the initial conditions.
Samples were detected by both fluorescence and 254 nm fixed wavelength
detectors. The percentage of metabolite was calculated from the noc^nthra-
cene activity in the extract, plus the unextracted residue determined by
combustion.
Rate Constants and Bioconcentration Factors
First-order rate constants for KC activity were calculated, assuming
a single animal compartment, according to the first-order model described
by Branson et aj.. (1975) and Neely (1979).
-------
dc --
-1 = Ku • Cw ' Kd ' Ca
dt
. (A.8.2)
C. . ^ Cw (1 - e-'V0)
Kd
where C = concentration in fish (ng • g )
t = time (h)
C = concentration in water (ng • g }
w
K = uptake rate constantjdnl • g"1 • h"1) or (h" ) assuming a tissue
U density of 1 g • ml
K, = depuration rate constant (h )
Underlying assumptions for the use of this model are discussed by Spacie
and Hamelink (1980). The initial uptake rate was estimated by a tangent to
the initial uptake curve (equation 4.8.3):
C = C + K • C • t (4.8.3)
a o u w
where C is the initial concentration in fish. This was estimated from a
linear regression and initial rates assumptions. For small values of t,
the value of C is constant and C is negligible (Xpnemann and vanLecuven,
1980). The apparent first-order elimination of C activity during the
depuration phase was calculated according to equation 4.8.4.
loge Cfl = loge (Ct - Kd) (4.8.4)
where C is the concentration in fish at the beginning of depuration. The
elimination half-life is described by equation 4.8.5.
(4.8.5)
^
*• L. — ^^___^__
* ~ ~K
Kd
Ideally, assuming the model described by equation 4.8.2, the bioconcen-
tration factor (BCF) at steady state las t •* ») is described by equation
4.B.6.
C K (L ft A>
a u vt.o.o;
nrp — — -
C K
Cw Kd
Since the kinetic behavior of hydrocarbons muy be more complex than this
model would suggest, the ratio (Ku/Kd) will be termed the "estimated" BCF.
The BCF values for anthracene and B(a)P were also calculated according to
the regression of Veith et aj.. (1979b):
99
-------
loglc BCF = 0.85 logjo P - 0.70 (4.8.7)
which relates bioconcentration to the n-octanol-w«ter partition coefficient
(P) of a chemical (Tulp and Hutzinger, 1978). This will be termed the
"predicted BCF." The partition coefficients were calculated according to
Leo et a_l. (1971).
The above BCF methods ordinarily relate to the bioconcentration of
parent material, not to total C activity which includes biotransformation
products. To find a "corrected" BCF, the BCF calculated from the (K/Kg)
ratio was corrected for the % parent material present in the fish at the
end of the 4 h exposure. The equations describing the models were fit to
the data by the Marquardt numerical methods (PROC NLIN, Barr et^ aK , 1979).
RESULTS
Uptake Rates
Fish ("mean weight 487 mgl.were exposed to 20.5 Mg'£~ anthrecene in
aquaria for up to 16 h. The C activity in the fish increasedlinearly
(r = 0.93) during the first 4 h with a flux of 1375 + 105 ng • g" • h~ ,
dry weight. (Figure 4.8.1). This represents an uptake rate constant (K ) of
67 + 5 h . The uptake rate declined after 4 h due to the depletion of a
significant proportion of the dissolved anthracene: 8% after 1 h, 121
after 4 h, and 42% after 16 h (Figure 4.8.2). By comparison, a control
tank without fish lost only 4.5% of initial activity in 16 h. Ad-
sorption to walls represented 0.2% of the activity. Accountability for
C-anthracene from water, walls, and fish was 96 + 2% and 98.3% for B(a)P
after 4 h. Subsequent exposures were ended after 4 h to avoid problems of
hydrocarbon depletion or water quality deterioration.
The effect of exposure concentration on K was investigated for an-
thracene concentrations of 0.7 to 16.6 pg'£ (figure 4.8.3). The results
(Table 4.8.1) show that K is essentially independent of the concentration
of anthracene in the water. This is always assumed to be true but seldom
tested. Another trialj using larger fish (5140 tng), at 6.7 Mg-JJ~ produced
a similar K of 31 h . A slower uptake rate constant (K = 14 h ) was
observed in a single group of 60 fish exposed to 11 pg-£ "anthracene in a
large 60-£ tank. In general, the fish in this group showed less swimming
activity than those in the smaller 5-£ test tanks.
A-cumulation of anthracene from well water (Figure 4.8.4) resulted in
an uptake rate constant similar to that of stream water. The addition of
humic acids does not affect the uptake rate significantly (p = 0.1). The
uptake rate constants for equimolar solutions of B(a)P and anthracene in
stream water were similar (Table 4.8.2). However, the accumulation of
B(a)P from well water was greater t.han from the stream water containing
refractory organics. The presence oi humic icids in well water signifi-
cantly reduced the rate of 6(8)1' accumulation by fish (Figure 4.8.4).
100
-------
Anthracene
1800
0
Benzo(a)pyrene
180-
TIME (hr)
14
Figure 4.8.1. Accumulation of C-antlirarcnc and bcnzo(a)|>yrcne from w«-JL
w.itor with and without humic acids. liumics present (solid)
circles), no htimirs (open circles).
101
-------
6r
Anthracene Uptake
x
en
u.
ui
o >»
X
h-
z:
o
TIME (hr)
o
r
1.5
15
"P o
ia m
rm
E
-i
m
;u
Figure it.il.2. Accumulation of "*C-niU hrjcene by fish ami depletion ol
C-.intliraconc from water in .1 clor.od system.
102
-------
12,000
10,000
S 8000
LL.
z
LJ
Z
Ul
o
<
a:
x
i-
•z.
<
i
o
6000
4000
2000
Y= 754.6X -15.44
T2=0.9985
n = 12
0' V ,,,,,, i ,,,.,-,,—, , , -
0 2 4 6*8 10' 12 14 16
I4C-ANTHRACENE IN WATER
(/ig/L)
r.vgurc 4.8.3. Conccnlr.-itioii of . / C-.»nt linicene in bluo^ills aflor four
hours exposure to C-.inthr.n cue JK J fui:clion of .inLhr.iccnc
CoiiccnLraLi on in w.ilcr.
103
-------
800
oo "o> 600
LL. QJ
400
o en
CQ x
' C*
o JE
200
0
Without Humics
K|= 27G ng/fj/hr
r2= 0.938
0
•^ With Humics
K| = 92.2ng/g/hr
~r
2
TIME (hr)
~T
3
~r
4
Acc,,m,,lJtioil Of
'- the
or
10/1
-------
TABLE A.8.1. EFFECT OF VARYING EXPOSURE CONCENTRATION ON THE RATE OF UPTAKE
r«p **r AUTWDAiTMT RV RT.IIFfiTl.T.S*
OF C ANTHRACENE BY BLUEGILLS.
Cone, in water
(Mg'*"1)
0.7
1.1
1.9
4.6
8.6
8.9
16.6
Cone, in fish at
, L / -l«b
4 hr (ng-g ;
94 + 4
170 + 9
328 + IS
786 + 26
1439 + 41
1591 + 48
2777 + 98
kl
(h"1)
36
39
43
43
42
40
42
8 Mean weight 620 mg.
b Mean + SE.
Elimination Rates
14
Both anthracene and B(a)P C activity in fish appeared to follow
first-order kinetics during the depuration phase (Figure 4.8.5). However,
the elimination of anthracene residues was approximately 4 times faster
(Table 4.8.2). Elimination half-lives for total C activity were 17 and
67 h for anthracene and B(a)F, respectively. The rate constants measured
here predict that bluegills would reach 90% of r.heir steady state concen-
trations in approximately 68 h for anthracene and 268 h for B(a)F.
Anthracene and metabolites excreted by the fish were tr^ped on resin
columns . placed below the depuration chamber. Approximately 47% of the
total C recovered from the colunns was anthracene, according to TLC; the
remainder was wore polar material. A similar trapping technique for B(a)P
was not completed because of the low concentration of excreted B(a)P in
water and its' slow elimination from exposed fish.
Tissue Distribution and Biotransformation
_^.arger bluegills (4633 mg mean wt., n = 6) were exposed to either 5.8
\tg-i anthracene or 0.70 pg-Jf! B(a)P for 4 h to determine C distri-
105
-------
e> 100
z
E 80
<
2 60
LU
cr
o 40
LU
cr 20
LJ
r = -0.789
L r=-
1 '
0
1
20
1
40
-x '
60
TIME
80
(hr)
100
120
14
Figure A.8.5. Depuration of C-.inthr.icene (open circles) and
benzo(a)iiyrcne (solid circles) followiiiR an initial A h
exposure x +; SE.
106
-------
TABLE 4.8.2. RATES OF UPTAKE AND ELIMINATION OF C ACTIVITY IN BLUEGILLS
EXPOSED TO ANTHRACENE OR BENZO(A)PYRENE (B(A)P) IN STREAM
WATER.
Anthracene B(a)P
Cone, in water* 0.7 1.0
(M8-D
Cone, in fish at 94 + 4b 207 + 15
4 h
kU (h"1) 36+3° 49+4
kD (h"1) 0.040 + .006C 0.010 + .002
Elimination half-life (h) 17 67
Approximately equitnolar solutions.
b Mean + SE.
Slope + standard deviation of regression coefficient.
buttons in tissues (Table 4.8.3). Although the carcaes had the largest
quantity of both hydrocarbons, the gall bladder contained the greatest
concentration on a weight basis. Liver, viscera, and brain all contained
similar concentrations of anthracene. However, B(a)P residues were pro-
portionately greatest in liver and least in brain. The very high rate of
accumulation of C-B(a)P in the gall bladder (14,000) suggests that B(a)P
is rapidly metabolized and conjugated in the liver before transport to the
bile.
The relative rate of biotransi. ,rmation, expressed as the percentage of
rT8K?UC /oT/^ PCr hOUr' WaS «reater for B(a>P than for anthracene
(Table 4.8.4). The proportion of non-B(a)P biotransformation products
increased from 36% after 1 h to 89% after 4 h. In contrast, only 7.9% of
the anthracene activity had been biotrans formed after 4 h. The rapid rate
of biotransfonnation of B(a)P indicates that its' slower rate of elimina-
tion is due to excretion of metabolites rather than simple partitioning of
the parent material. e
Predicted Rates and Bioconcentration Factors
f onn /o COD8tants Yield estimated BCF values
of 900 and 4900 for anthracene and B(a)P, respectively (Table 4.8.5). The
107
-------
o
CO
TABLE A.8.3. DISTRIBUTION OF UC ACTIVITY IN BLUEGILLS EXPOSED TO 5.8 pg-fc"
0.70 pg-£ BENZO(A)PYRENE (BaP) FOR 4 HOURS.
ANTHRACENE (An) OR
Tissue
Call bladder
Liver
Viscera
Brain
Carcass
% Total
An
3-° h
(0.7)b
3.2
(0.8)
20.3
(1.9)
1.5
(0.4)
72.0
(2.0)
Activity
B(a)P
16.7
(2.7)
7.8
(1.7)
17.2
(1.3)
0.3
(0.03)
58.0
(3. A)
Tissue
ng'S
An
A3, 800
(34,200)
13,000
(1,100)
14,900
(1,200)
12,900
(2,310)
962
(194)
cone.
dry
B(a)P
39,000
(14,000)
4,600
(640)
2,200
(270)
250
(16)
370
(26)
Uptake
Coefficient
An
1890
561
6A1
555
42
B(a)P
14,000
1,600
770
90
130
(Tissue cone, at 4 h)/(conc. in water at 4 h).
Mean (SE) for n = 6.
-------
TABLE 4.8.4. RATES OF BIOTRANSFORMATION IN BLUEGTLLS EXPOSED TO 8.9
'£ ANTHRACENE OR 0.98 M8'* BENZO(A)PYRENE (B(a)P).
Anthracene
Cone, of
residue
total
(nmol'g )
I metabolite
1 h
6.2
(1.2)*
3.9
(1.0)
2 h
6.8
(C.3)
4.6
(0.4)
3 h
13.0
(0.4)
7.9
(0.2)
1 h
0.122
(-)
36
(5)
B(a)P
2 h
0.255
(-)
69
(2)
3 h
0.369
(-)
89
(4)
Biotransformation 0.24 0.16 0.26 0.044 0.088 0.082
rate (nmol-g -hr ) (0.06) (0.01) (0.03) (0.007) (0.004) (0.009)
% transformed per hr 3.9 2.3 2.0 36 35 22
* Mean (SE) for n = 3.
TABLE 4.8.5. COMPARISON OF BIOCONCENTRATION FACTORS DETERMINED BY THREE
METHODS.a
Method
Predicted
(partition)
Estimated
Corrected
(parent only)
Anthracene
1209
900
675
B(a)P
28,250
4,900
490
See Methods section for definitions.
Using log P = 4.45 for anthracene and 6.06 for B(a)P (Leo, 1975).
109
-------
estimated value for anthracene is reasonably close to its predicted value
of 1209, based on partition coefficient. However, the estimated value for
B(a)P is considerably lower than that predicted from the partition coef-
ficient. Since the regression of BCF versus log P equation is derived
primarily from inert or poorly metabolized chemicals (such as the polychlo-
rinated biphenyls), it reflects an accumulation process dominated by a
reversible exchange of the unaltered material. B(a)P is a clear exception
to that pattern because of its rapid conversion to other products. In
fact, a true steady state condition between fish and water may never occur.
The true corrected BCF values for both anthracene and B(a)P are well
below the other estimates (Table 4.8.5). The % biotransformation product
(Table A.8.A) used to calculate the correct BCF may vary over time, depend-
ing on the length of exposure, enzyme activity, or other factors. If so,
the corrected BCF values based on parent material would also change.
Although there are many BCF values in the literature for comparison,
relatively few rate constants have been reported for fish. Spacie and
Hamelink (1980) reported correlations for K and Krf versus log P for a
series of chlorohydrocarbons and other organics. The correlations predict
a slight increase in K and a relatively large decrease in K. with Jugher
log P. The predicted" K values, 19 h for anthracene and 33 h for^
B(a)P, give reasonably good agreement with the measured values of 36 h
and 49 h . The predicted K. values based o . partition coefficient are
0.02 h for anthracene and 0.004 h for B(a)P . They suggest slower
rates of elimination and longer half-lives than were actually observed.
DISCUSSION
Anthracene and B(a)P were removed from water at similar rates from
equimolar solutions. The rate constants are proportional to the octanol-
water partition coefficient. This reflects the tendency of more nonpolar
components to partition out of water (Chiou et al. , 1977; Leo et al., 1971;
Southworth et aJL, 1978; Veith et aj.., 1979b; Kenaga and GoTiog, 3980).
Similarly, the elimination rite constants were inversely proportional
to the octanol-water partition coefficient. However, this cannot be total-
ly attributed to the partition coefficients since significant biotransfor-
nation occurred, particularly for B(a)P. The foruation of macromolecule-
bound and poLa^r biotransformation products will tend to reduce the depura-
tion of the C label. The bound material is not free to dissociate and
the polar components may, in many cases, be more slowly eliminated (Landrum
and Crosby, 1981a). Slow elimination of polar components by fish during
these studies may have been enhanced if concentrated metabolites were not
being emptied from the gall bladder due to the absence of feeding (Lech et
al., 1973). The relative tissue distribution of anthracene and biotrans^
formation products observed in the bluegill sunfish studied here were
similar to that observed for anthracene in young Cobo salmon (Roubal et
al.., 1977). In the study with salmon,j|all bladder was the tissue contain^
ing the greatest concentration of C-anlhracene and biotransformation
products.
11J
-------
The bioconcentration factor predicted from the log P relationship is
asuch greater than that determined from K /K , and much greater than that
corrected for biotransformation. This hasUalso been observed by Southvorth
et al. (1980) for ezaarenes in the fathead minnow and by Leversee et aK
(T981b) for B(a)P in Chironomus riparius. Fish show this discrepancy du«
to the relatively slow uptake in proportion to the biot:.«nsfonnation rate.
Thus, predictions of BCF from the log P ran be expected to be higher than
those actually found for compounds that undergo significant biotransfor-
nation.
Differences in the partition coefficients of the anthracene and B(a)P
nay account in part for the differences in observed biotransfonnation
rates. Since B(a)P has a faster uptake rate from equimolar solutions, a
greater concentration should be available for biotransfonnation. Addi-
tionally, B(a)P can be expected to be bound to serum proteins. This would
result in lower whole-body concentrations and greater relative distribution
to the liver. This could result in greater biotransfonnation, assuming the
enzymes for biotransfonnation are not saturated. The biotransfonnation of
B(a)P by fish on a dry weight basis was less than that found for either
Dapfania or Chironomus riparius (Leversee et al., 1981 a and b). This
reflects the comparUnentalization of the biotransformation enzymes in the
fish.
The rate of biotransformation appeared to increase in the case of
B(a)P between 1 and 2 h. While B(a)P is a known cytochrome P-A50 inducer
(Ahokas, 1979), the short exposures (A h) precluded the synthesis of more
enzymes. However, adsorption of B(a)P or its metabolic products by endo-
plasmic reticular membranes may alter the specific activity of the enzymes.
Such an apparent induction would affect K. by altering the pool size of
parent and biotransformation products. Induction would have its major
effect on K. if parent compound were the major excretion product and a
minimal effect for the excretion of biotransformation products (Lech and
Bend, 1980; Spacie and Hammelink, 1981). The length of exposure will tend
to decrease the depuration rate constant, however, the uptake rate constant
will not be affected by this induction. The decreased depuration rate
results from the accumulation of a bound, unexchangeable, biotransformation
product pool. This irreversible binding has been described for PAH as the
mechanism for toxic response. Irreversible binding was observed in the
kinetics of anthracene in Chironomus riparius (Gerould et al., 1981).
Thus, models used in describing the kinetics of uptake and depuration
of PAH become biased when there is significant biotransformation, induction
of PAH transforming enzymes, binding of biotransformation products, or
translocation. In this study, we used ehort-tena exposures and depuration
periods to estimate rate constants. This avoided many of the problems
mentioned above. Also, we chose to use simple one compartment, constant
infusion models instesd of two compartment mass balance models. The deple-
tion of anthracene from water after 4 h in the static uptake study could be
corrected for by a two compartment model. Howiver, the other problems
mentioned above would have resulted in a bias for both K and K . Thuu
the creation of a multi-compartment model would be raost appropriate, how-
ever, these models require large amounts of data for curve fitting.'Since
111
-------
the rate constants are highly correlated, many roots of the equation re-
gression solutions (toy not result in real values or mechanistically realis-
tic rate constants. Therefore, the use of simple models which fit one rate
constant at a time provide good approximations to the overall processes for
the fate of xenobiotics.
Veith et al. (1979a) suggested a technique for determining the log P
or partitioning coefficient for organic compounds. This technique uses the
retention time of the compound on reverse-phase, high-pressure liquid
chroaatography columns. This technique makes the measurement of this
secondary property of compounds accurate and rapid. Since the partitioning
coefficient is defined by several properties of compounds, such as molecu-
lar weight aud polarity, it has been suggested as a possible integrator,
which would be highly correlated with the bioconcentration factor (BCF) in
fish (Leo et al.., 1971; Chiou et a_l., 1977). However, the results of our
studies indicate that the BCF predicted from the log P is greater than the
observed BCF. This result is in agreement with those of Southworth et al.
(1980) for azaarenes in fish and is most probrbly due to biotransformation.
Therefore, if organisms are able to biotransform a compound of interest
such as bluegills can biotransform B(a)P and anthracene, the use of the log
P to predict steady state concentrations may result in error.
The biotransformation of PAH compounds, such as B(a)P and anthracene
in fish, has been widely studied (Pedersen e_t al., 1974; Payne and Penrose,
1975; Gerhart and Carlson, 1978; Schnell et a_l., 1980; James and Bend,
1980). Because the microsomal mixed function oxidases can be induced, the
rate of biotransformation can change with time of exposure. As discussed
earlier, if the biotransformation products are bound tightly to macromole-
cules, the apparent BCF will change as a function of time dee to: (1)
induction of enzyme activity; (2) changes in the ratio of biotransformation
products to parent compound; and (3) redistribution of both parent and
biotransformed compound. Therefore, the short-term pharmacokinetic tech-
nique for determining steady-state concentrations of organic compounds by
fish which was proposed by Branson et. al. (1975) is appropriate only when
biotransformation is minimal or the magnitude and rate of biotransformation
is well known and constant.
The uptake rate constant for B(a)P was altered by the presence of
dissolved humics. This reduced bioavailability was proportional to the log
P, indicating that the more nonpolar materials interact strongly with the
dissolved humics. Similar results have been observed for the uptake of
hydrocarbons by sole (McCain et a_l. , 1978) and for selected PAH by Daphnia
(this report, Section 4.3). —
112
-------
SECTION 5
SIMULATION MODEL FOR PREDICTING PAH FATES
SECTION 5.1
INTRODUCTION
It is desirable to be able to predict the concentrations of PAH to
vhicb aquatic organisms will be directly exposed and humans will be exposed
through food and drinking water. Thousands of different species of PAH's
are chemically possible; therefore, application of elaborate screening
protocols (Duthie, 1977) to individual PAH in order to quickly estimate
major processes of transport, accumulation, and degradation are impractical
for purposes of risk analysis. Assessment of health risks associated with
introduction of PAH into the environment depends in part upon quantifica-
tion of environmental transport and subsequent concentrations to which
aquatic organisms are exposed (Crawford and Leggett, 1980). Estimates of
transport and dose are independent of the specific nature of the threat to
human health, either directly through contamination of potable water, for
example, or indirectly through damage to ecological life support systems.
Several alternatives exist for the development of needed predictive
capacity. Monitoring PAH content of stream components of interest follow-
ing accidential pollution by PAH should provide sufficient data from which
to generalize, given enough accidents. Statistical analysis of these data
could facilitate prediction by providing regression models or correlation
between measurable properties of specific PAH compounds and their observed
fates in streams and rivers. Statistical models, however, depend solely
upon available data. In addition, coefficients in statistical models often
cannot be translated into mechanistic processes subject to control or mani-
pulation by environmental decisionmakers.
Simulation models based upon mechanistic processes of PAH flux and
accumulation represent a potentially more useful alternative to environ-
mental monitoring or statistical models. These m dels are based upon
"state of the art" understanding of processes, mathematical analogs of
which translate directly into parameters or coefficients that can be esti-
mated in the field or laboratory. Data collected in monitoring programs
remain useful for model validation.
This section describes a model (Fates of Aromatics Models, FOAM) which
simulates the transport of PAH co.j/ounds through lotic systems. Similar to
models developed by Baughman and Lassiter (1978) this model has been de-
signed to predict fates of PAH in
-------
ever, model structure permits parameterization for simulation of PAII dy-
namics it* specific streams.
114
-------
SECTION 5.2
MODEL STRUCTURE DESCRIPTION
Simulation of PAH transport in lotic systems requires an understanding
of basic structure and function of streams and rivers, as well as, the
physical, chemical and biological processes that govern PAH movement.
Basic ecological information concerning species composition, standing crop
and, in some instances, energy flow has accumulated for a variety of stream
systems (Coffman et al., 1971; Fisher and Likens, 1972; Mclntire, 1973;
Mclntire and Phinney, 1965; Minshall, 1978; Odum, 1957; Teal, 1957 and
Tilly, 1968). Yet streams have not received the degree of attention from
ecological modelers as have other aquatic systems (Patten, 1968). Models
of lotic systems have classically been the purview of sanitation engineers.
State variables in these models typically included dissolved oxygen, bio-
logical oxygen demand, ana total solids. Model form typically divided a
particular stream or river into a series of reaches, which individually may
be quite different in hydraulic characteristics, but were assumed to be
internally homogeneous. Reach models have become sophisticated in the
realm of sanitation engineering, but little has been done to enhance their
application to increase basic ecological understanding of stream structure
and function. However, ecologists have recently begun to simulate energy
and material flow through lotic systems, in some cases borrowing the reach
model approach (Chen and Wells, 1976; Knowles and Wakeford, 1978; Mclntire
and Colby, 1978; Sandoval et. al., 1976; Zalucki, 1978).
The major objective of this modeling effort wjs to predict the pat-
terns of flow and accumulation in aquatic systems based on easily deter-
mined parameters for the compound of interest and the receiving environ-
ment. In this study we used laboratory studies to ascertain the most
important vectors and mechanisms to be included in the simulation model.
The effects of potentially mitigating factors on pathways and rate con-
stants were also investigated. In some cases overall rate constants for
uptake, depuration and biotransformation by biotic and abiotic matrices
were determined in the laboratory for use in the anodel. Finally, the
simulation model was parameterized for the conditions existing in the SREL
channels microcosm faciiity (Ciesy et *±., 1979; Bowling et a].. 1980).
Simulation results were then compared to those of inputs of anthracene in
the channels microcosms.
The general strategy was to adopt the reach approach (Figure 5.2.1)
and to include fundamental biological production processes common to lotic
systems. Specific processes known to influence PAH flux somewhat inde-
pendent of ecological processes include photolytic degradation, volatiliza-
115
-------
GENERAL REACH MODEL
Segmented
Street
REACHi
Figure 5.2.1. Conceptualization of Keneralizc.il stream reach transport
model.
116
-------
tion losses and sorption to sediments and suspended participates. These
processes were, therefore, included in the model.
The fate of aromatics model (FOAM) predicted concentration of PAH in
phytoplankton, "periphyton, macrophytes, zooplankton, two benthic inverte-
brate compartments, bacteria, sediments, suspended particulate matter, and
fish (Figure 5.2.2). The overall simulation model is organized as a main
program (MAIN) which calls subroutines which calculate solar radiation
(SOLAR) movement of water (HYDRO), solubility of PAH, and resuspension and
calculates and graphs the relative and absolute mass of PAH in each com-
partment (Figure 5.2.3). Other submodels calculate the photolysis (PHOTO)
volatilization (VOL) and sorption to sediments (SORP). The biotic compo-
nents are coupled as in the representation given in F:.gure 5.2.4.
FOAM is programmed in FORTRAN. A modular structure was employed
wherein individual processes were separated into subroutines (Figure
5.2.3). For example, subroutine HYDRO generates the hydraulic history used
in subsequent calculations of state variable dynamics. Likewise, subrou-
tine SOLAR simulates hourly values of incident solar radiation. The physi-
cal-chemical processes importaut in PAH dynamics: photolysis, volatiliza-
tion and sorption, are modeled in routines PHOTO, VOL and SORP, respective-
ly. Biological equations are contained in routine EQUA. Each routir"
calculates part of the overcll derivative for change in biomass or PAH in
each state variable (eg. equation 5.2.1). Modular -structure facilitates
modification of the submodels as directed by comparison of simulation
results with observations to be made in the experimental streams.
Model Output
FOAM simulates the dynamics of biological production and PAH dynamics
through time and space (reach) (Table 5.2.1). Each state variable value is
printed in matrix form where row elements are values at a specific time for
each reach. Column elements are temporal values in a particulsr reach. To
assist in recognition of complex patterns in spatial-temporal dynamics,
each state variable can be plotted sirau)taneojsly against reach number
(distance downstream) and time (hour) to provide a three dimensional fig-
ure. A complete listing of the model code is beyond the scope of this
report but can be obtained from the authors. It should be noted that model
development is a dynamic process and FOAM is continually being updated. An
overall mass balance approach was taken to model changes of biomass and PAH
through time and space.
The first term on the right hand side of equation 5.2.1 represents
time dep-ndent changes in PAH concentration that result from processes such
as volatilization, photolysis, biological transformation and translcration,
and sorption to suspended particulate matter or sediments. The second term
on the right hand side of equation represents downscream convective trans-
port.
Ths general form of equation 5.2 1 implies independence between time
dependent change and ccnvective transport. However, as will be seen, cur-
117
-------
SIMULATION OF PAH FLUX THROUGH STREAMS
VOL*TI'.lI*TIOM
PHOTOLYSIS
SEDIMENT
REACH .,
REACH
REACH
Figure 5.2.2. Srhcm.it.ic rcprcsontaLion of F«iton of Aroni.itic Molecules
(FOA11) model.
113
-------
MODULAR PROGRAM STRUCTURE
Inputs
FATES OF AROMATICS MODEL (FOAM)
Figure 5.2.3. Schematic representation of modular subroutine st
FOAM.
ructure of
119
-------
t=0
uj t
2
I-
t-t-l
x=0
DISTANCE
x+l
Ax
Figure 5.2.4. Movement of w.iter m.iss Lhroii);h sp.icc and Lime.
120
-------
Table 5.2.1. Output from FOAM. Each variable is simulated hourly.
Irradiance langleys • h _2
Alloch;hanous organic matter 8 • drv w*2gbt ' m
Exteraal PAH loading 8 PAH-2 m
Periphyton biomass g * ">
Macrophyte biomass
Benthic Invertebrate Biomass
Clan biomass
Bacteria biomass
Fish biomass
Suspended particulate organics
Dissolved organics
Bottom Sediments
Suspended inorganic particulates
Settled detritus " _j
PAH in periphytoc M»°l PAH^ g , dry weight
PAH in macrophytes
PAH in Benthic Insects "
PAH in Clans "
PAH in Bacteria "
PAH in Fish
Predacious "
Herbivorous "
Suspended organic particulates "
PAH in dissolved organic matter "
PAH in bottom sediments "
PAH in suspended inorganic particulates "
PAH in settled detritus "
PAH dissolved in water pmol PAH • t~
PAH which has been transferred "
rent velocity directly affects some of the rates of time dependent process-
es, for example, rate of volatization of dissolved PAH or rates of settling
and resuspension of particulate PAH. Time and space are to an extent the
same thing coupled by current velocity.
Similar to Sandoval et al. (1976), a numerical approximatiou to the
solution of equation 5.2.1 was used wherein the (x,t) plane was divided
into an array and the derivatives approximated by differences (Figure
5.2.4).
P(x,t+l)
5.2.1
121
-------
8P P(''t*1) " P(x>t)
3t~ = At5.2.2
An element in the array represents the PAH concentration in a given
compartment, say periphyton, at a particular point in time and space. The
actual value is the sum of the time dependent change (vertical arrow) and
convective change (horizontal arrow). In another sense, the vertical arrow
represents — in equation 5.2.2 and the horizontal arrows, actually their
sum, represents U. „— in equation 5.2.2. The time step was determined
(x,t>dxn
by a necessary relationship At = l!/Ax = 0.01 H • S between reach length
(M, 18.28 ro) and current velocity (S ) (Bella and Dobbins, 1968).
122
-------
SECTION 5.3
SUBMODELS
Hydrological Sub-model
Application of the model was constrained to conditions of constant
reach morphometry under a constant discharge regime (Figure 5.3.1). Reach
dimensions and flow rates are summarized in the facility description. A
simple continuity equation was used to determine current velocity in rela-
tion to constant sectional area of each reach and discharge regime (equa-
tion 5.3.1).
Q = V • A (5.3.1)
whe re,
3-1 3-1
Q = discharge into reach, (M -t ), 4.53 m -h
V = current velocity (m't ), 18.3 m-h
2 2
A = cross sectional area of reach (m ), 0.12 m
This hydrologic submodel appeared reasonable for the artificial streams,
since the channels were of constant length, width, depth and flow rate.
Temperature Dependent Processes
In FOAM water temperature indirectly affected flow of PAH's through
the food web by directly modifying rates of photosynthesis, consumption and
respiration. An empirically derived equation (O'Neill et al., 1972; Shu-
gart et aj.., 1974) was used to calculate the effect of water temperature in
reach j at time t on rate estimates of photosynthesis and respiration for
biological state variables (equation 5.3.2).
f(T) = V* . ex(1-V) 5.3.2
where
V = (Tm - T)/(Tm - To)
123
-------
U-2AI =AX
U = m/time
t = time
ltllllt®tllil
=^§lf§; fcs5j§§;5 ;
^S^^S?'
X- meters
-
t+At
t+2Al
X X+AX
PLUG FLOW
Figure 5.3.1.
Schrm.itic r -prcsrntat ion of plug
w.itcr movement in reach model.
flow used to represent
124
-------
X = V2 (1 + (1 + 40/Y)^2/400
W - (ln V {T» ' To)
Y = Ce-'V 5.3.3
where
I_ = radiation at surface of reach (ly/min)
!_._ = direct beam solar radiation, slope dependent
XxO
is = scattered clear sky solar radiation
I,.- = direct beam radiation on a horizontal surface
C = percent cloud over
F = slope correction factor for scattered clear sky radiation
d = parameter for seasonal cloud effects
Model inputs included latitude of stream (33 degrees N), slope direction,
slope inclination (0) and daily estimates of mean cloud over. The model
was calibrated with measurements recorded in the vicinity of the streams
site. Figure 5.3.2 represents a simulation of the annual cycle of solar
radiation.
FOAM includes the capacity to attenuate surface light with depth as a
function of suspended sediments and phytoplankton biomass. Hyperbolic
125
-------
Table 5.3.1. Parameter estimates for consumer components of fates of aromatic model (FOAM)
See Table 5.3.3 for explanation of abbreviations.
Parameter
Component
Zooplankton
Benthic Invert
Macro Invert
Bacteria
Carnivore
DMAX
(h'1)
0.0375
0.0150
0.0125
0.0042
0.0021
Q10C
2.0000
2.0000
2.0000
2.0000
2.3000
TOPIC TMAXC RMAX
(°0 (°
25.000 30.
27.000 32.
25.000 30.
27.000 32.
27.000 31.
'0 (h'1)
000 0.0042
000 0.0042
000 0.0042
000 0.0083
000 0.0010
Q10R
1.8500
2.8500
1.8500
1.8500
2.1000
TOPTR TMAXR
(°0 (°0
30.000 35.000
32.000 37.000
30.000 35.000
32.000 37.000
30.000 34.000
•*
Component
Zooplankton
Benthic Invert
Macro Invert
Bacteria
Carnivore
EXCR
(h'1)
0.0042
0.0042
0.0042
0.0083
0.0021
MORT
(h-1)
0.0001
0.0001
0.0001
0.0001
0.0001
EGEST
(h-1)
0.0042
0.0042
0.0042
0.0042
0.0042
LIPID
(%)
0.13
U.13
0.13
0.13
0.13
DMAX
(h-1)
2.4xlO~5
0.00
0.00
0.00
0.00
QCi KP
(h'1) (g-m'2)
4x10 1.00
0.0004 1.00
0.0004 1.00
0.0004 1.00
0.0004 1.00
-------
Table 5.3.2. Parameter estimates for primary producer components of fates of aromatic model
(FOAM). See Table 5.3.3 for explanation of abbreviations.
Component
PSMAX
Q10P
TOPTP
TMAXP
RMAX
Parameter
Q10R TOPTR TMAXR
EXCR
Phytoplankton 0.0080 1.4900 20.000 35.000 0.0021 1.8000 30.000 37.000 0.0008
Periphyton 0.0060 1.4900 20.00 35.000 0.0021 1.8000 30.000 37.000 0.0008
Macrophytes 0.0050 1.4900 20.00 35.000 0.0021 1.8000 30.000 37.000 0.0008
Component MORT SINK RK
(h"1) (h'1) (FC)
Phytoplankton 0.0001 0.0021 5.
Periphy'.on 0.0001 0.0 5.
Macrophytes 0.0001 0.0 5.
LIPID DMAX QPi KP
(%) (h"1) (h"1) (g-m"2)
0.15 0.00 0.0042 l.OC
0.15 0.00 0.0042 1.00
0.15 0.00 0.0042 1.00
-------
CC 61
O
I
UJ 54
O
<
S 47
W 39
-T 1 r
37 74 110 147 IB3 219 256 292 329 365
DAY OF YEAR
Figure 5.3.2. Simulation of solar radiation by sub-modrl r.oljr.
128
-------
Table 5.3.3. Key to parameter abbreviations used in FOAM for consumer and
producer components.
DMAX - Maximum depuration rate
Q10C - Temperature dependence for consumption
TOPTC - Optimum temperature for consumption
TMAXP - Temperature of maximum photosynthesis
RMAX - Maximum respiration rate
Q10R - Temperature dependence for respiration
TOPTR - Temperature of maximum respiration
TMAXR - Temperature of which respiration goes to zero
EXCR - Rate of execution
MORT - Rate of mortality
EGEST - Rate of egestion
LIPID - Fraction lipid content
QC - Maximum PAH uptake rate by consumers
KP - Half saturation constant for uptake (half of max solubility)
PSMAX - Maximum photosynthesis rate
Q10P - Temperature dependence for producer
SINK - Sinking rate of phytoplankton
RK - Light saturation of photosynthesis
TMAXR - Temperature upper limit for respiration
QP - Maximum PAH uptake rate by producers
PUC - Uptake rate (flux) of PAH by consumers
PUP - Uptake rate (flux) of PAH by producers
functions provided partial extinction coefficients for each component which
were summed to estimate an overall extinction rate used in a first order
exponential decay function. Depth in past simulations was 0.21 m. Attenu-
ated light drove tLe photosynthetic submodel for periphytou. Surface light
intensity drove the phytoplankton photosynthesis submodel. Photolytic
degradation of PAH was calculated with light intensities at several depths,
integrated over the water column.
Photolytic degradation of PAH
Light dependent degradation of aromatic hydrocarbons represents a
potentially important mechanism for physico-chemical transformation of
these compounds in aquatic systems. Direct photochemical breakdown of
dissolved PAH and degradation of photosensitized PAH sorbed to suspended
particulates may both be iraport.ant, however, Zepp and Cline (1977) indicate
that indirect photolysis of sorbed PAH is minor ia comparison with direct
photolytic degradation of dissolved PAH. In the current version of FOAM,
only direct photolytic degradation is simulated.
129
-------
Incident light intensity, R , simulated by equation 5.3.3 is attenu-
ated by suspended particulates via a diffuse attenuation coefficient cal-
culated from a relationship (equation 5.3.4; based on published data (Zepp
and Cline, 1977).
t)
K = 0.20 + 0.00247 • SS (r = 0.77) 5.3.4
where
K = diffuse attenuation coefficient, cm
SS = suspended sediments, mg • £
In the subroutine that calculates phctol/tic degradation of PAH, dis-
solved PAH, assumed -available for photolysis, is converted from units of
grams per square meter to moles per liter for use in the equation for
photolytic loss (equation 5.3.5) adapted from Zepp and Cline (1977).
d PAH 5.3.5
/ = * ^ = yield coefficient
k. = light absorbed at wavelength X and
A
PAH. = dissolved PAH concentration
d
Reported yield coefficients range between 0.001 and 0.01 for polycy-
clic aromatic hydrocarbons (Zepp and Schlotzhauer, 1981). A linear re-
gression based upon data presented by Zepp and Schlotzhauer (1981) was
calculated to relate yield to molecular weight of PAH compounds with equa-
tion 5.3.6 (Figure 5.3.3) <)> = 0.0235 - 8.38x10 • molecular weight (r =
-0.62).
The value of k. reprerents light absorbance at wavelength X by the PAH
compound. Values oT absorbance (photons • cm • sec" ) were summed at 10
nra increments between wavelengths of 300 and 500 run, a region of peak
absorbance and intense photochemical breakdown for PAH compounds. Each k,
was calculated as the product ~>f simulated light intensity and a measured
molar extinction coefficient, e , at lembda. Values of e. must be supplied
as input to the model by the user.
Hourly light intensity simulated by subroutine solar is attenuated as
a function of wavelength following some assumptions concerning the quality
of light impinging upon the surface of each reach in the stream of inter-
est. First, we assume that only 12% of the simulated light intensity, R
is within the 300 to 500 nm range (Zepp and Cline, 1977). According to
data presented in Miller and Zepp (1979), we determine the relative compo-
sition of light at each 10 nm increment between 300 and 500 nm (Table
130
-------
-1
UJ
O
U.
U_
LJ
O
O
O
_l
UJ
-2.
CD
O
_J
-3
o
"100 200
MOLECULAR WEIGHT
300
Figure 5.3.3. Log ns a function of 1'AII moJociiJnr weight.
131
-------
Table 5.3.4. Contribution of light of 10 nm increments to
total spectrum between 300 and 500 nm.
Wavelength
(nm)
300
' 310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
Per Cent of Total
0.0050
0.1009
0.2749
1.7309
1.9876
2.1307
2.2715
2.5441
2.8167
3.3619
4.8157
6.3376
6.5193
6.2922
7.4279
8.3593
S.'iSOl
8.7227
8.9499
8.4501
8.6319
5.3.4). Twelve per cent of R is multiplied by the appropriate value in
Table 5.3.4 to estimate the incident light at each wavelength. Then, t'jis
quantity is attenuated according to an equation fit to the curve of light
attenuation versus wavelength (equation 5.3.6) for 12 southeastern rivers
(Zepp and Cline, 1979).
ax=0.42e(-4-4366xl0~3-X), (r2 = 0.96) 5.3.6
where a. has units of cm . A depth specific rate of photolysis is calcu-
lated at 1.0 cm intervals until either the depth of the reach has been
equalled or the depth specific rate is less than 10% the rate calculated at
the water surface. The depth specific rates are then integrated over the
water column and converted to g2PAH • m • h . Initial light intensity
was converted to photons • cm • sec from lyh~ by calculating the
joules per Einstein for each wavelength \ between 300 and 500 ma at 10 nm
increments. While as a constant for a
132
-------
given compound over all wavelengths. Differences in photolytic degradation
of specific compounds, as simulated by FOAM, occur as a result of a molecu-
lar weight dependent value of <}> and different absorbance characteristics of
each compound in the 300 to 500 nm region of the spectrum (Table 5.3.5).
Photolytically degraded hydrocarbons were added to the pool of transformed
PAH.
Table 5.3.5. Comparison of observed quantum yield coefficients for
reaction of PAH in air saturated water to predicted quantum
yields based upon regression with molecular weight.
Compound
Naptbthalene
Phenanthrene
Anthracene
9-Methylanthracene
9 , 10-Dimethylanthracene
Chrysene
Naphthacene
Benz (a) anthracene
Benz(a)pyrene
Mol. Wt
128
178
178
192
206
228
228
228
252
regression based upon data in Zepp and
omitted from regression
r2 = 0.87
Volatilization of PAH
analysis, log <(>
a
Predicted
.0219
.0075
.0075
.0055
.0041 "~""~
.0026
.0026
.0026
.0015
Schlotzhauer (1981)
= -0.465 - 0.0093 • mol.
Observed
.0150
.0100
.0030
.0075
.0040
.0028
.0130
.0033
.009
wt.
The submodel that quantifies losses of PAH through volatilization in
reach j at time t was adapted from Southworth (1981). The rate of volatil-
ization was modeled as a function of current velocity, wind velocity, reach
depth and molecular weight of the PAH according to a hyperbolic equation
involving Henry's Law (equation 5.3.7).
V(H
5.3.7
133
-------
where
H = molar concentration of PAH in air divided by molar concentra-
tion of PAH in water
K = gas phase exchange constant, cm-h
g -j
K = liquid phase exchangj constant, cm-h
The log of H can be estimated from molecular weight of the PAH compound
(Zepp and Schlotzhauer, 1979, equation 5.3.8). Similarly, Kg was estimated
from-equation 5.3.9.
log H = 0.7854 - 0.0191 • molecular weight 5.3.8
K
K = 1137.5 • (V+W) • (18/molecular weight)' 5.3.9
where
V = current velocity (m-sec )
W = wind velocity (in-sec )
Values of K. result from application of two regressions for different wind
velocity regimes (equations 5.3.10 and 5.3.11).
K£ = 23.51 (V°-S69/R°-673) • (32/molecular weight)* 5.3.10
if W < 1.9 ra-sec"1
K£ = 23.51 (V°-969/R°-673) - (32/molecular weight)* - (eO-526(W-1.9))
if W > 1.9 m-sec"1 5.3.11
where
R = water depth (m)
FOAM uses calculated current velocities plus a user supplied wind
regime in the volatilization model.
MicrobiajL Biotransformation of PAH
Metabolic degradation of assimilated PAH is modeled as a function of
respiration rate and was therefore indirectly affected by water tempera-
ture. Respiration was multiplied by DMAX. for compartment i. The units of
DMAX^ are grams PAH metabolized per gram dry weight respired per time. At
present, all DMAX values are set at zero.
134
-------
Sorption of PAH
Polycyclic aromatic hydrocarbons may' be quickly lost from solution as
a result of sorption to suspended particulate matter and settled sediments.
Sorption to particulate matter provides a possible entry to the aquatic
food web via filter feeding or sediment feeding animals.
The sorption sub-model in FOAM was based heavily upon data provided in
Karickhoff et a_l. (1979) where the sorption of PAH was modeled as a first
order relationship between dissolved PAH in the water and partitioning co-
efficient, Kp. The partition coefficient increased linearly as a function
of the organic content of the sorbent material. The partition coefficient
also correlated with the octanol/water partition coefficient (KQW) of the
PAH.
Depending upon available data, FOAM calculates rates of sorption in
one of three ways. First, if K and the organic fraction of the sorbent
were known, a partition coefficient is calculated from equations 5.3.12 -
5.3.15.
where
K = K • oc 5.3.12
p oc
Log (k ) = Log (K ) - 0.21 5.3.13
oc ow
oc = fractional organic content of the sorbent.
Second, if K is not known, k is estimated from the solubility of the
particular PAff: °C
Log (Koc) = -0.54 • Log(s) - 0.44 5.3.14
where
s = solubility of the PAH mole fraction
Solubility can be estimated from molecular weight (Figure 5.3.4). Third,
if neither k nor the organic fraction of the sorbeni, were known, a parti-
tion coefficient was estimated directly from:
Log(Kp) = 4.16 - 0.51 • Log(s) 5.3.15
where
s = solubility of the PAH, ppm
Equation 5.3.15 resulted from further analysis of data presented by Karick-
hoff et a_l. (1979).
Values of K were converted to units of inverse time by dividing by
the duration of experiments (24h) of the experimeuts which generated data
135
-------
I 3
m
o
CO
O 0
_j
-I
• Aromotics
y=6.50-.040X
A Cycloolfefms
y = 4.97-.030X
a Cyr.loparoffins
y = 4.M-.03IX
100
MOLECULAR WEIGHT
200
Figure 5.3.4. Log solubility of PAH in water as a function of PAH
molecular weight.
136
-------
for the regressions (equations 5.3.14 - 5.3-16). Because the experiments
were performed with PAH concentrations that approached the maximum solu-
bility of the compounds and because the sorbent was suspended by continuous
stirring, we assumed that the K values provided estimates of a maximum
rate of sorption, S . At eachpiteration of the model, the specific rate
of sorption is calculated from equation 5.3.16.
S = S • SBATE • SBENT • oc / [SBATE + (SBEKT *oc)l 5.3.16
max
where
-2 -1
S = rate of sorption, gPAH-m *h
S = maximum sorption rate, £*h
max .
SBATE = soluble PAH, g-n"2
-2
SBENT = sorbent, g*m
Biological Production Sub-model
* .
Primary producers
Rates of biomass change were determined by first order mass balance
differential equations. The overall biomass equation for producer i in
reach j at time t (puytoplankton, periphyton, and macrophytes) is repre-
sented by equation 5.3.17.
dPi
_ _ (FI^ - FO.) + P. (PSi - Ri - Mi - IL - S.) - G. 5.3.17
dt
where
_
P. = biomass, g dry wt • m
FIj = inflow of P from re-.ch j-1
F0i = outflow of P. from reach j
PS. = photosynthetic rate of P
R. = respiration rate of P
M. = non-predatory mortality rate
U. = excretion rate
S. = sinking rate
C. = grazing loss of P
137
-------
Photosynthesis
In FOAM, gross photosynthesis (of phytoplankton; periphyton and macro
phytes) was modeled after Smith (1936) (equation 5.3.18).
Pmax
where
P = photosynthesis per unit producer i in reach j at time t
P = light saturated photosynthetic rate for producer i
max
I = light intensity supplied by solar submodel
I = light saturation constant for producer i
f(T) = temperature function, (equation 5.3.2)
Values of parameters for three primary producers in FOAM are listed in
Table 5.3.2.
Consumption
Food consumption provided energy for biomass production and another
potential PAH source to the non-photosynthetic biological components of
FOAM. Consumption ic modeled as a function of predator and prey biomass
after DeAngelis et ai. (1975) (equation 5.3.19).
C . • B. • W. . • B.
C. . = f(T) - - - - 5.3.19
B. + J (Wij . B.)
where
C. . = input of prey j biomass to consumer i
*»J
C , = maximum feeding rate of consumer i (day )
_2
B. = consumer biomass (g • m )
_o
B. = prey j biomass (g • m )
W = Bayesian preference of predator i for prey j (unitless)
f(T) = temperature dependent modifier of consumption rate (equation
5.3.2).
The behavior and stability properties of this function have been studied
(De Angelis et al. , 1975). This equation has been usefully applied to
model feeding by zooplankton, benthic invertebrates and fish (Kitchell et
138
-------
ajl., 1974; O'Neill, 1976; Smith et al. , 1975). Figure 5.3.5 represents the
prey items allowed for each consumer by FOAM. When prey are plentiful,
consumption, C.., is proportional to predator biomass. Conversely, prey
abundance regulates consumption in equation 5.3.19 when prey are scarce.
The Bayesian parameter, W (Table 5.3.6) can be estimated from data quan-
tifying the relative abundance of prey j in predator i stomach samples and
the relative abundance of prey j in the environment (O'Neill, 1971).
Foodweb transfer of PAH was modeled as C. . multiplied by the PAH con-
centration in prey j summed over all j for consumer i. FOAM can therefore
be used to examine the relative importance of direct uptake of PAH by con-
sumers in association with respiration and trophic transfer of PAH through
the foodweb. Appreciable amounts of polychlorinated biphenyls have been
shown to accumulate from consumptive processes, especially at higher tro-
phic levels (Weininger, 1978). Behavior of PAH's in this regard was essen-
tialxy unknown. Calculation of the PAH derivative for P. results from
multiplying each terra in equation 5.3.17 by the fractional TAH concentra-
tion of P. and adding two terms that quantify PAH uptake and degradation as
functions of photosynthesis and respiration, respectively (equation 5.3.20)
H. = (Q. • PU. • PAH.) / (K. + PAH.) 5.3.20
ill d i a ,
-2 -1
In equation 5.3.21 H. (g • m • t ) was the rate, of PAH uptake mediated
by photosynthesis, PAH. was dissolved PAH (g • m ) available for uptake
and PU. was a linear function of photosynthetic rate (equation 5.3.21)
Plh = IP • PSi 5.3.21
where
PU. = g PAH assimilated per g producer i per time
PS = photosynthetic rate of producer i, g • g" • t
m = slope, of PAH taken up per g photosynthetically fixed biomass
Respiratory mediated PAH biotransformation is represented by equation
5.3.22.
Di = Ri ' di ' Pi ' hi 5.3.22
where
D. = rate of PAH degradation by producer i
d. = fraction of respiration used to degrade PAH
hj = fractional PAH content of P
R = temperature dependent respiration rate of P
1
139
-------
.#
. „
^ q£ ^£> ^0 <£«, ^C> ^C> Q\ ^ c*>
Zooplonkton
Benthic
1 nvertebrotes
Macro-
Invertebrates
Bacteria
Fish (Pred)
Fish (Herb.)
Figure 5.3.5. M.-itrix of cnn^tunei-.s and food items which arc considered by
the production portion of FOAM.
140
-------
-------
Table 5.3.6. Continued
10
Food Item j
Predator Predatory
Fish
Zooplankton
Benthic
Invertebrates
Clams
Bacteria
Fish (FRED)
Fish (Herb)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Herbivorous
Fish
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Suspended
Organics
0.1
0.9
0.9
0.0
0.0
0.0
0.25
0.90
0.0
0.0
0.0
0.0
Dissolved
Organics
0.0
0.0
0.0
0.0
0.0
0.0
0.25
0.90
0.0
0.0
0.0
0.0
Sediments
0.0
0.0
0.0
0.05
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.10
Suspended
Inorganics
0.1
0.01
0.01
0.01
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Settled
Detritus
0.0
0.0
0.0
0.4
0.2
0.2
0.5
0.75
0.0
0.0
0.15
0.40
-------
Consumer organisms
The overall mass balance equation for consumer compartment biomass is
given by equation 5.3.23
; = (FIt - FCh) + I C - N. (R. + F£ + IK + M.) - G.
5.3.23
dt j
where
_2
N. = biomass of consumer i in reach at 5, (g dry wt • m )
C.. = rate of consumption of prey j by consumer i
R. = temperature dependent respiration rate of consumer i
F. = fraction of ingested food that is egested
U = rate of biomass lost through excretion
M. = natural mortality rate of i
G, = predatory losses of i
FI-FO = net convective transport of consumer i
.".espi ration
For producers, a fraction of photosynthesis or for consumers, a frac-
tion of standing crop is lost through respiration. Respiration was modeled
as a temperature-dependent function by specifying an R value, which oc-
curs at T , for each biological compartment.
For consumers, a respiration dependent direct uptake of PAH was in-
cluded in FOAM. A limited amount of evidence suggests that Daphnia concen-
trate PAH in its lipid tissue (Southworth et al. , 1978). These data fur-
ther suggested an active uptake mechanism which resulted in steady-state
concentrations after approximately 24 h. In FOAM, a hyperbolic function
which relates respiratory rate and lipid concentration in the biomass is
used to simulate direct PAH uptake by zooplankton, benthic invertebrates,
macroinvertebrates and carnivores.
Biotransformation of PAH parent compound is modeled as a function of
respiration rate. A variable fraction of the body load is removed from all
biological compartments as a function of respiration rat», Biotransforma-
tion products are shunted to a dissolved pool of biot Transformation products
that acts as a final sink.
143
-------
Excretion
It is assumed that part of the biomass,of the plant and animal compo-
nents is lost through excretion. Secretion might be a more appropriate
interpretation of this process in plant metabolism. Excretion is modeled
in a linear fashion. It is further assumed that PAH is lost through excre-
tion in proportion to the concentration of PAH in the bioinass component.
Rates of excretion (Tables 5.3.1 and 5.3.2) mul£ipl^ed by the biomass
in each component to calculate g, dry wt excreted-m *h by each biologi-
cal component. Multiplication of these rates by the concentration of, PAH
in each biological .component, results in estimates of PAH excreted-m -h
by the biota. The model internally tracks the PAH concentration in each
compartment during the simulation.
Mortality
As for excretion, it is assumed that a constant fraction (Tables 5.3.1
and 5.3.2) of biomass is lost from each compartment as the result of non-
predatory mortality. Again, multiplication of mortality losses by the con-
centration of PAH in the biomass produces PAH losses to mortality.
Sinking losses
Phytoplankton sinking losses are modeled separately from settling of
suspended particulate matter. Future versions of FOAM could incorporate
more realistic coupling between hydraulic aspects of the model and net
suspension of both phytoplankton and suspended particulate matter. Peri-
phyton and macrophyte mortality are added to the sediment organic pool via
the KSTL parameter. The sinking rate used is 0.0021 h~ .
Egestion
A fraction of the consumed food is egested by the consumer components
of the- model (Tables 5.3.1 and 5.3.2). Egestion losses enter the suspended
particulate pools for bj^th biomass and PAH. Egested PAH is the product of
egestion rate (0.0042 h ) and PAH concentration of the food item.
Direct uptake of dissolved PAH by producers and consumers.
Uptake of PAH by plants was modeled as a second order, non-linear
.Michaelis-Henten process (equation 5.3.24).
PUi = Pi ' Qi ' PAH/CKPi + PAH) 5.3.24
144
-------
where
f
PUC or PUP. = uptake of PAH by producer (P) or consumer (C) i
_2
P. = biomass (g, dry wt'm ) of producer i
QP or QC. = maximum uptake rate of PAH by producer (P) or consumei
1 (C) i, (g PAH/g, dry r/t-b" )
_2
PAH = dissolved PAH concentration (g PAH-m )
2
KP. or KG. = analagous to a half-saturation constant (g PAH-m )
Direct uptake by the producers was assumed, in the model, to be^iude-
pendent of photosynthetic or respiration rates. Q. was 20 g PAH • g , dry
weight producers-h . This constant was derived from laboratory accumula-
tion studies and was specific for anthracene in this case. However, the
Monod model was used so that structure/activity relationships could Le used
in future versicus of the model. The Monod model is a relatively simple
relationship to describe the saturation phenomenon observed in periphyton.
Direct uptake by consumers was coupled to the rate of respiration with
the assumption that direct uptake takes place across respiratory membranes
and is an active process. The equation is similar to (O'Neill et al. ,
1972), except respiration rate, RSMAX., appears in the numerator as a
multiplier of Q. and Q. has units of g PAH t;cumuldted'g , dry wt-h . Q.
was 42 • h for all consumer components.
External loading
Polycyclic aromatic hydrocarbons enter the artificial streams by
external loading of dissolved PAH from the head tanks. This is reproduced
in the model structure, where dissolved PAH enters the uppermost reach as
the product of the pre-defined discharge regime (ra -day ) and the PAH
concentrations of the influent (g PAH-m ). Future versions of FOAM could
accomodate several point sources per reach.
A statistical relationship between solubility and molecular weight of
PAH compounds was derived from published data (Braunstein et al. 1977)
(equation 5.3.25 and Figure 5.3.4).
log (PAHd) = 6.50 - 0-04 • mol. wt., r2 = 0.77 5.3.25
This regression was used to estimate solubility of a specific PAH and
ensure that solubility constraints were obeyed throughout the simulation.
PAH in excess of solubility limits was shunted to the sediments.
145
-------
Initial conditions
—A
Estimates of initial conditions (g dry wt • m ) of the biota for
all 5 reaches were derived from previous experimental work at the channels
microcosm facility, located on the Savannah River Plant site (Giesy et aj..,
1979) (Table 5.3.7). Each biological component of the syrtem is discussed
in greater detail in this section. Simulations of other aquatic systems
would require parameterization for that system. Alternatively, for simula-
tion to compare fates among compounds a generalized system could be para-
meterized.
Table 5.3.7. Initial biomass conditions for simulations reported here
g dry weight • m
Compartment
Phytoplankton
Periphyton
Macrophytes
Zooplankton
Benthic Invertebrates
Clams
Bacteria
Predatory Fish
Herbivorous Fish
Suspended Organic Particulates
Dissolved Organic Matter
Sediments
Suspended Inorganic Matter
Settled Detritus
1
1
0.0
0.18
1.54
0.0
0.5
0.2
0.1
0.1
0.2
0.05
0.01
1.0
0.01
0.55
2
0.0
0.18
0.3
0.0
0.5
0.2
0.1
0.1
0.2
0.05
0.01
1.0
0.01
0.55
Reach
3
0.0
0.18
0.3
0.0
0.5
0.2
0.1
0.1
0.2
0.05
0.01
1.0
0.01
0.55
4
0.0
0.18
0.3
0.0
0.5
0.2
0.1
0.1
0.2
0.05
0.01
1.0
0.01
0.55
5
0.0
0.18
0.3
0.0
0.5
0.2
0.1
0.1
0.2
0.05
0.01
1.0
0.01
0.55
146
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Primary procedures; phytoplanktoa, periphyton. macrophytes
Phytoplankton contribute to the production dynamics of large, slow
moving rivers; however, previous experience with the SREL channels micro-
cosms indicated that phytoplankton do not contribute substantially to over-
all system p.-eduction. While parameters for phytoplankton growth and PAH
metabolism have been generated for this model component, initial biomass
was defined as zero for the current simulations (Table 5.3.7).
The algal component of the aufwuchs community was measured to be ap-
proximately 2 percent of the live volume (Giesy et aJL. , 1979), of which
members of the Chlorophyta and Cyanophyta comprised more than 95%. In
1977, algal volume collected from a reference channel ranged between 6 and
12 cm -ra^. Assuming a density of 1.0, this volume translated to 0.12 -
0.24 g-m . Initial conditions for current simulations were defined as the
midpoint of this observed range, 0.18 g-m
Macrophyte flora that commonly colonized the artificial channels in
past research included Juncus diffusissimusi, Gratiola virginiana, Calli-
triche heterophylla and Bacopa caroliniana. Colonization was assisted by
transplants of J. diffusissitnus which subsequently dominated the biomass of
the macrophytic vegetation in the channels. Estimates of standing crop
from the work of Giesy et al. (1979) suggested spatial heterogeneity in
distribution of J. diffusissimus, with the greatest abundance upstream.
Initial macrophyte biomass in the first reach was defined as 1.54 g dry wt
• m . The regaining reaches were each set at 0.03 g • m
Consumer components: zooplankton, benthic invertebrates,
macroinvertebrates, bacteria, fish
As in the case of phytoplankton, pelagic zooplankton were assumed to
be insignificant in the overall production dynamics of the SREL channels
microcosms. While parameters have been defined for the growth and PAH
metabolism by zooplankton, this component was initialized as zero for
current simulations.
The benthic invertebrate component in the model is derived to simulate
the growth and PAH dynamics of stream insects including the orders Ephe-
meroptera, Odonata, Coleoptera and families Notonectidae, Corixidae,
Centropogonidae and Chironomidae. An estimate of their combined standing
crop iu previous research in the channels (Giesy et al. , 1979) was 0.5 g
dry wt per m . This value was used as an initial condition for all five
reaches.
The macroinvertebrate compartment was defined to include larger in-
vertebrate organisms such as crayfish and clams that have been incorporated
in previous ecological studies involving the SREL channels microcosms.
This rompartment represents a complex fauna in natural systems; however,
species used in the channels included Corbicula fluminea (Asian clam)'
Anodonta irobecilus (papershell clam), and Procamberus acutus acutus (cray-
fish). In experimental tests of the model, individual C. flmninea were
147
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added and.constrained in each reach by wire mesh. Clam biomass was 0.2 g
dry wt-m in_each reach. Bacterial biomass was arbitrarily defined as 0.1
g dry wt • m . In experimental tests of the model, 10 juvenile bluegill
sunfish (Lepomis macrochirus) Mere caged in each reach. Fish biomass was
estimated as 0.1 g dry wt • m .
The biological state variable for simulations of the dynamics of
anthrcene in the channels microcosms facility are given in Tables 5.3.8 and
5.3.9. The physical parameters for simulating volatilization and photo-
lysis of anthracene in the channels microcosms are given in Tables 5.3.10
and 5.3.11.
148
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Table 5.3.8. Biological state variables for simulation of anthracene dynamics. See Table 5.3.3 for
explanation of abbreviations.
PRODUCERS PSMAX Q10P TOPTP TMAXP RMAX Q10R TOPTR TMAXR EXCR MORT SINK
(/HR) (C) (C) (/HR) (C) (C) (/HR) (/HR) (/HR)
Photoplankton 0.3000 1.4900 20.000 35.000 0.1000 2.3000 27.000 31.000 0.0300 0.0001 0.0021 5.4
Periphyton 0.0300 1.A900 20.000 35.000 0.1000 1.8000 30.000 37.000 0.0300 0.0001 0.0 5.4
Macrophytes 0.0200 1.4900 20.000 35.000 0.1000 1.8000 30.000 37.000 0.0300 0.0001 0.0 5.4
CONSUMERS CMAX Q10C TOPIC TMAXC RMAX Q10R TOPTR TMAXR EXCR MORT EGEST
(/HR) (C) (C) (/HR) (C) (C) (/HR) (/HR) (/HR)
Zooplankton 0.0375 2.0000 25.000 30.000 0.0080 1.8500 30.000 35.000 0.0042 0.0001 0.0042
Benth Invert 0.0150 2.0000 27.000 32.000 0.0042 1.8500 32.000 37.000 0.0042 0.0001 0.0042
Macro Invert 0.0125 2.0000 25.000 30.000 0.0042 1.8500 30.000 35.000 0.0042 0.0001 0.0042
Bacteria 0.0042 2.0000 27.000 32.000 0.0083 1.8500 32.000 37.000 0.0083 0.0001 0.0042
i
Fish (Pred) 0.0021 2.3000 27.000 31.000 0.0005 2.1000 30.000 34.000 0.0022 0.0001 0.0042
Fish (Herb) 0.0021 2.3000 27.000 31.000 0.0005 2.1000 30.000 34.000 0.0021 0.0001 0.0042
-------
Table 5.3.9. Biological state variables for anthracene dynamics simulation.
Lipid
Content
Maximum
Uptake
(QMAX)
Uptake half
Saturation
Constant
Minimum
Depuration
DMAX
Producers
Phytoplankton
Periphyton
Macrophytes
Consumers
Zooplankton
Benthic Invertebrates
Clams
Bacteria
Predatory Fish
Herbivorous Fish
15
2x10
-6
1.0
13
4.2x10
2.4x10
-5
a.-l
h
bg PAH-m~2
V1
150
-------
Table 5.3.10. Parameters for the simula-
tion of volatilization of
anthracene.
2
Gas phase constant. K = 3.6 x 10
g
liquid phase constant, K- = 1.8 x 10
overall rate constant, KL = 7.3 x 10
Table 5.3.11. Parameters for photolytic degradationxof anthracene.
Quantum yield coefficient = 7.5 x 10
Wave length
(nm)
300
310
320
330
3AO
350
360
370
380
390
400
Molar extinction coefficient
4.84 x 102
1.17 x 103
1.90 x 103
2.1 x 103
4.9 x 103
3.4 x 103
4.8 x 103
3.2 x 103
2.7 x 103
5.4 x 102
2.2 x 101
151
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SECTION 5.4
SIMULATION OF ANTHRACENE IN CHANNELS MICROCOSMS
RESULTS AND DISCUSSION
Water
FOAM was used to simulate a constant infusion of 0.056 pmol-£ of
anthracene into the uppermost reach of the experimental channels. Param-
eter estimates were based solely upon laboratory measurements or published
data; only the initial conditions were measured in the channels.
During daylight hours the model predicts a decrease from 0.056 to
0.036 (jmoles in a distance of 81 meters, between reach one and reach five.
At night, this concentration gradient is absent and all reaches exhibited a
concentration similar to the input concentration. Regardless of light
conditions, reach one exhibited a constant anthracene concentration of
0.056 [imol anthracene-£~ . The model predictions compared favorably with
the average day and nighttime measurements made in the channels vTable
5.4.1). Simulated values were somewhat lower, and the rate of loss down-
stream was slower in the model. Nevertheless, the general behavior of the
dissolved "pool" was predicted by the model. When the constant infusion
was stopped, the concentration of dissolved anthracene quickly decreased to
0.006 nmol-£ within 24 h.
Table 5.4.1. Predicted and observed concentrations of dissolved
anthracene in channels microcosms.
pmol anthracene-"
Time Reach 1 Reach 3 Reach 5
Dawn "
observed .066 .065 .063
predicted .056 • .056 .055
Noon
observed .067 .045 .028
predicted .056 .045 Io36
152
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Sediments
Simulations of anthracene dynamics in the channels microcosms predic-
ted that the bottom sediments would accumulate anthracene linearly.
Steady-state concentrations of 0.09, 0.004 and 0.0035 pmol-g , dry weight
were predicted for reaches 1, 3 and 5, respectively (Figure 5.4.1). The
simulation predicted a rapid desorption of anthracene from the sediments,
which was not consistent with the p "tern observed in the channels micro-
cosms (Table 5.4.2). FOAM also underestimated the rate of flux into the
sediments. The simulation model did, however, predict, a downstream gradi-
ent of anthracene concentrations in the sediments similar to the observed
gradient.
The routines to simulate sorption will need to be improved to give
better predictability in future simulation models. Sorption to sediments
is complicated by resuspension, transport and corrective processes, which
are difficult to represent by either deterministic or statistical models.
Long term simulations will be affected by large rainfall events, which may
cause great deviations from the patterns of sediment transport throughout
most of an annual cycle. The scaling of such events will probably be such
that good predictability will only be available on geologic time scales and
will cause large uncertainties in short-term simulations. Even beyond
this, differences in diffusion rates and^ micro-dynamics have not yet been
adequately described by FOAM to -predict anthracene dynamics in bottom sedi-
ments. Descriptious of thoroughly mixed suspended sediments are much more
adequately described by FOAM and other existing relationships. We suggest
that more research on sediment sorptive and desorptive processes as well as
interfacing to sediment transport models is required before PAH concentra-
tions ?n this important PAH accumulating matrix can be made.
Periphyton
The simulated anthracene dynamics in periphyton showed a rapid uptake
to a quasi-equilibrium concentration of about 0.17 pmol-g dry weight, by
day 3 (Figure 5.4.2). Anthracene concentrations in the periphyton de-
creased downstream and are greater at night in all reaches. These patterns
probably reflect both the greater concentration of dissolved anthracene at
night and the initial assumption that depuration rate is physiologically
coupled to photosynthesis. This assumption is probably violated because
some depuration is due to passive diffusion.from the surface and interior
of the cells. The day-night pattern results in the broad envelope of
anthracene observed in periphyton in the simulations represented in Figure
3» H • £ •
The steady state concentration of anthracene in periphyton predicted
by the simulation was similar to the results observed in the channels.
However, the great variability in measured anthracene concentrations made
comparisons difficult (see Section 6.4). The 2 SE confidence intervals for
the steady state anthracene concentrations measured in periphyton from the
channels microcosm ranged from 0.07 to O.lb [imol anthracene-g dry weight
which was in the same range as the simulated concentrations (Figure 5.4.2)'
153
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0.66
Reach 5
.'// ANTHRACENE
0 67 134 201 269 336 403 470 537 609 672
TIME (h)
Figure 5.A.I. Simulation of anthracene dynamics in bottom sediments of the
channel:; microcosms.
154
-------
LJ
Z
o
o
5
a.
o
0.20
0.16
0.12
0.08
0.04
0 67 134 201 268 336 403 470 537 604 672
SIMULATED HOUR
Figure 5.4.2. Simulated concentration of anthracene in periphyton through
time in reaches 1 and 5. Hatched area contains transient
concentrations for reaches 2-4.
155
-------
Table 5.A.2. Comparison of predicted and observed concentrations of
anthracene in stream sediments.
Anthracene Concentration
, dry weight)
Time
(h)
24
67
134
201
269
336
403
470
537
672
Reach
Obs
.0024
.0044
.0070
.0096
.0149
.0137
.0108
.0113
.0092
.0072
1
Pre
.00026
.00059
.0014
.0027
.0073
.0079
.0084
.0092
.0096
.0092
Reach
Obs
.0023
.0040
.0060
.0086
.0134
.0118
.0104
.0116
.0076
.0065
3
Pre
.00020
.00045
.00096
.0018
.0040
.0041
.0043
.0044
.0044
.0042
Reach
Obs
.0021
.0034
.0053
.0073
.0123
.0106
.0104
.0107
.0065
.0053
5
Pre
.00017
.00037
.00080
.0015
.0033
.0034
.0035
.0035
.0035
.0034
Parameter values for anthracene uptake were derived from experimental
work with cultures of periphyton grown on glass slides in natural streams
located on the SRP. The uptake kinetics were determined for these actively
growing cultures (see Section 4.4). Periphyton in the artificial channels
was comprised of less luxuriant growth. Extrapolation of laboratory deter-
mined uptake kinetics, via the model, to the field situation seems to be
justified in this case. However, the comoarison between half-lives of
anthracene in simulated periphyton and that measured for periphyton shows
the model results to be in close agreement. The depuration rate constant
determined in the laboratory studies with natural cultures appears to be i
reasonable estimate of the rate of depuration by periphyton in the chan-
nels. During daylight hours, photolysis reduced the dissolved anthracene
concentration, making less compound available for uptake. In addition, the
depuration process of the periphyton should be operating to reduce the con-
centration of anthracene in periphyton. In absolute terms, the equilibrium
concentration docs not agree within two orders of magnitude with the an-
thracene concentrations measured in the periphyton in the channels. The
half-time for elimination of anthracene in periphyton following termination
156
-------
of the constant input, however, agrees within 2-3 h with the measured
half-time for elimination of anthracene from periphyton in the channels.
Uptake might have been overestimated in the model, as parameters for uptake
rate were derived from actively growing cultures of periphyton that colo-
nized glass slides placed in streams located on the Savannah River Plant
site. -Vihereas, the periphyton in the channels microcosms did not appear to
be growing at the rate of the cultured plants and consisted of a different
flora.
Clams
The simulation of anthracene predicted that the maximum anthracene
concentration in clams would not be attained until after the anthracene
input was terminated (Figure 5.4.3). This is because the simulation model
assumes that the clams are accumulating anthracene both directly from the
water and from suspended particulates, which still had anthracene associ-
ated with them after the anthracene input was terminated. The naximum was
reached earlier in reach 1 than 3 or 5 because the amount of anthracene
•associated with suspended, particulates was greatest downstream. The maxi-
mum anthracene concentration was attained in claas in reach 3 because this
reach had the greatest exposure concentration between water and particu-
lates.
The concentration of anthracene predicted to be in the soft tissues of
clams at the time of termination of anthracene input was 4.16 pmol anthra-
cene- g ,dry weight of soft tissue (Figure 5.4.3). This is,equivalent to
740 (Jg'g , dry weight, which is greater than the 16.6 Mg'g, , dry weight,
actually observed in clams exposed to approximately 10 |Jg'£ anthracene in
the channels. This value is probably an overestimate of actual accumula-
tion because the simulation allows uptake from particulates, which have
been shown to be less important for accumulation of PAH by clams than
accumulation directly from water (Dobroski and Epifanio, 1980). Also the
model assumes that filtering is a continuous process, which was not observ-
ed in the channels microcosms. The clams living in the channels were also
under environmental stress (Giesy et al., 1979) because of factors other
than anthracene, whioh nay have reduced the frequency and rate of filtering
as well as metabolism.
FOAM considers a component which we have called benthic invertebrates.
This term is somewhat misleading and needs to be defined here. We have
considered only macroinvertebrates such as insects and oligochetes and not
protozoans in this class of organisms. FOAM also includes another macro-
invertebrate component which for the anthracene simulation is the clam
component. This component can also be used to include other macroinverte-
brates such as crayfish. If better precision of accumulation by clams is
desired, this component needs to be separated and better mechanistic pre-
dictions made.
The results of the simulation of anthracene dynamics in benthic macro-
invertebrates cannot be compared to analogous results from tne channels
microcosm because the benthic macroinvertebrate community had not developed
157
-------
UJ
Z
UJ
o:
x
<
en
Reach I
Reach 3
Reuc h 5
268 335 402 469 536 603 670
Figure 5.A.3. Simulation of anthracene dynamics in clams in channels
microcosm.
158
-------
to a great enough extent to allow sampling of enough biomass for represen-
tative, destructive sampling.
*
The results of the simulation of anthracene dynamics in the macroin-
vertebrate community (Figure 5.4.4) show that anthraceae concentration is
greater in the upstream reaches because the anthracene concentration in the
water and periphyton is greater. Also, it should be noted that tho anthra-
cene concentration in the benthic macroinverteurate component continues to
increase after tho anthracene input was terminated. This is a function of
the ingestion of anthracene-containing food (periphyton and detritus) after
the anthracene input period. Even though we cannot compare this simulation
to the macroinvertebrates in the channels microcosm study we feel that the
prolonged increase predicted by the simulation is unrealistic. The main
reason is that the relative importance of accumulation c PAH, anthracene
in this case, from food and directly from the water is not known. We
suggest further research be conducted to determine the relative importance
of flow materials along these pathways and determine better estimates of
KP., KC., QP. and QC. (equation 5.3.24).
fish
As with the macroinvertebrate organisms, we were unable to compare re-
sults from the simulation to results from the channels microcosms because
of anthracene induced mortality (fee section 6.6). The simulation model
includes components for both nerbivorous and carnivorous fish. The herbi-
vorous fish and carnivorous fish attain approximately the same concentra-
tions of anthracene during the input period (Figures 5.4.5 and 5.4.6).
However, after the input of anthracene was stopped the concentrations of
anthracene in the herbivorous fish stopped increasing while that of the
carnivorous fish continued to increase. This is a result of rapid depura-
tion from the periphyton, which was the major source to th? herbivorous
fish. Alternatively, loss from the macrcinvertebrates, which were the
source of ingestion for the carnivoious fish was much slower, which caused
the simulation to predict a continued accumulation of anthracene. Some
preliminary laboratory studies indicate that blueg?ll sunfish (see section
4.8) accumulate mo-^t of their body concentrations of PAH directly from the
water. Thus, to improve the prediction capabilities of FOAM we will need
to have better estimates of the maximum uptake rates and relative impor-
tance of various pathways under different conditions.
Relative Importance Along Biotic and Abiotic Pathways
We havrt calculated the relative importance of non-advective physical-
chemical processes and biological processes in determining the overall flux
of anthracene through the simulated lotic system. The periodic behavior of
anthracene corresponded to the light-dark cycle and emphasized the impor-
tance of photolytic degradation of anthracene in the overall dynamics.
During the c,.thracene simulations, the continued processes of photolysis
sorption and volatilization accounted for more than 50% of the total an-
thracene flux along pathway which allowed for either uptake and depuration
159
-------
57
Benthic Invertebrates
Reach 5
ANTHRACENE
INPUT
134 201 269
336 403
TIME (h)
470 537 604 672
Figure 5.4.4. Simulation of dynamics of antlicjcene in bcnthic macroinverte-
brates other tli.'in clams.
160
-------
-0.85
o
^0.68
o> 0.51
UJ
§0.34
(T
I 0.1
ANTHRACENE
INPUT
Reach 5
134 201
269 336 403
TIME (h)
470 537 604 672
Figure 5.4.5. Simulation of dynamics o£ antlir.iccne in lirrhivn.-
-------
en
o> 3
UJ
2
UJ
O
<
rr
in
H
•z.
<
Carnivorous Fish
Reach I
Reach 3
Reach 5
ANTHRACENE
INPUT
0
134 201
269 336 403 470 537
TIME (h)
604 672
Figure 5.A.6. SimulaLion of anthracene dynamics in carnivorous fish
162
-------
or transformation. As more anthracene entered biological components the
relative importance of the biological processes increased. This was es-
pecially true at night when the photosynthesis rate was zero. When the
anthracene input was terminated, the physical chemical processes became
unimportant and biological degradation processes assumed control over
the fate of anthracene. Of all biological processes, consumer egestion
and defecation of anthracene laden prey items accounted for more than 40
percent of anthracene flux. Plant uptake reprasented about 6 percent of
the total flux. The remaining anthracene moved fairly equally among the
Other biological pathways: depuration and excretion by plants, mortality
losses to plants and consumers, flux along the food web and uptake and
depuration of anthracene by consumers.
Comparison of Naphthalene Ben2o(a)Pyrene and Anthracene Simulations.
One of our initial premises for constructing a model from first prin-
ciples of compounds to be released to the environment stated that the
dynamics of PAH compounds could be predicted from a few readily available
pieces of information about a compound. These include molecular weight,
functional groups and molecular stereochemistry. There was given some
agreement between trends of the simulations and channels microcosms experi-
ments for anthracene, (mol. wt. = 178). The experiment was simulated again
with equal infusion rates of napthalene (mol. wt. = 128) and B(a)P (mol.
wt. = 252). The initial conditions and parameter estimates were identical
to the anthracene simulation. Only the molecular weight and absorbance
spectra were changed to correspond to naphthalene or B(a)P.
Without data for comparison with the FOAM simulation, discussion of
the dynamics of individual state variables becomes rather meaningless.
However, it is reasonable to examine the relative importance of various
pathways simulated in light of available information concerning observed
behavior of these compounds in natural or experimental systems. The simu-
lated fate of naphthalene was similar to anthracene with respect to the
relative importance of physical/chemical versus biological processes.
Physico-chemical processes accounted for more than 90% of the napthalene
flux through the channels in simulations (Figure 5.4.7). However, the
absence of periodic behavior corresponding to the light-dark cycle indicat-
ed that, unlike anthracene, photolysis was not the dominant process but
that volatilization was the dominant physico-chemical pathway of napthalene
loss from the channels, according to the simulations. These results are
similar to the conclusions of Lee et al. (1978), that volatilization was an
important process in the overall loss of naphthalene from large pelagic
enclosures. Similar to the anthracene simulation, the process of consumer
egestion and defecation assumed importance in the overall flux of naph-
thalene following the trrminatioc of naphthalene infusion in simulations of
naphthalene dynamics in the channels.
The transport of benzo(a)pyrene (B(a)P) in the simulation was domi-
nated by biological processes in contrast to the lighter weight anthracene
and naphthalene (Figure 5.4.7). Following an initial 8 h period of infu-
sion, where photolytic degradation was important, uptake by primary pro-
163
-------
10
o.e
0.4
0.2
V1 ll I
i H i
'
i i
i./1
(J)
AMI HH&CENt
5 ',
c.e
0.4
o.j -
0.8 -
0.6 -
0.4
0 67 154 20* 263 Jlfi 401 -170 SJ/ 604 6 7J
SIMULATED HOUB
Figure 514.7- Rcl.itive importance of non-advcctive physical/chemical
processos (solid dots, dashed line) arid biological processes
(open circles, solid liiie) in tot.il transport of (a) anLhra-
ccnc, (I)) naphthalene, and (c)- benzo(a)pyrenc through
artificial streams.
164
-------
ducers, movement through the foodweb, and consumer processes of egestion
and defecation played the determining role in the non-advective transport
and fate of B(a)P in the modeled stream. Lu et *I. (1977) measured bio-
magnification of B(a)P by biota in a simple aquatic microcosm that contain-
ed algae, mosquito larvae, daphnia, snails, and fish. Lee et al. (1978)
found 40 percent of B(a)P added to marine pelagic enclosures in samples of
sediments. Of the physical/chemical processes simulated, sorption to
suspended particulates and settled sediments was the most important vector
simulated for B(a)P by FOAM.
Discussion f
To be useful, a model of the transport of FAH should be capable of
several functions. The model should trace the entry of PAH into ecosystem
components potentially affected by, or involved in the transfer of, PAH
throughout the system. Second, the model should quantitatively charac-
terize the movement of PAH among system components and across system bound-
aries. Third, the disposition of PAH within components should result from
model application. Finally, transport through the system to ultimate sinks
following removal of the PAH input should be simulated.
Examination of initial results of FOAM simulations suggests that this
model could become a useful tool for synthesizing current understanding of
PAH dynamics and developing capacity to reasonably prodict the transport of
PAH in lotic systems.
Initial results of simulations showed that FOAM predicted the spatial-
temporal dynamics of dissolved anthracene with reasonable accuracy (Table
5.4.1). This success might reflect the observation that photolytic degra-
dation is the major pathway of degradation for this PAH. The photolysis
submodel has a firm foundation in theory and photolysis information for PAH
in general exists in greater amount and sophistication than for other
processes. Given that the photolytic submodel is perhaps the most realis-
tic process submodel within FOAM and photolysis appears as a key pathway
for degradation of anthracene, it is not surprising that FOAM predicts the
diurnal and downstream fluctuations measured for soluble anthracene in the
artificial stream channels.
The absence of rate coefficients for biological transport processes in
relation to molecular weight or other fundamental chemical properties of
PAH reflected the limited amount of data available for estimation of corre-
lations. Therefore, the model depended on extrapolation of rate constants
measured in the laboratory or published in the literature. As the number
of necessary rate parameters that must be directly measured in the system
of interest increases, specific application of the model becomes more
difficult. Lack of close agreement between simulated and measured concen-
trations of anthracene in peripbyton, clams, and sediments likely reflected
the difficulties in extrapolating laboratory determined rate constants to
the streams. For example, rate of uptake by periphyton was overestimated.
165
-------
The cultures of algae used in the laboratory experiments to determine
uptake did not resemble the flora that was growing in the experimental
channels.
•
While no data from the artificial streams are available to evaluate
the simulated transport of naphthalene and B(a)P, the agreement between
predicted and measured anthra-ene transport and several general aspects of
the simulated behavior of naphthalene and B(a)P generated some confidence
in the model's general applicability over a wide range of possible PAH
compounds. In the naphthalene simulation, volatilization proved to be the
single most important, process that determined transport of naphthalene.
This agrees favorably with general experience with this low molecular
weight PAH.
Photolysis initially accounted for 40 percent of the degradation of
B(a)P inputs to the simulated streams. The modeled importance of photo-
lysis agrees with the observations of Zepp and Schlotzhauer (1981) and are
consistent with expectations based upon the relatively high molecular
seight ot this compound. However, the low solubility of B(a)P in water
(~lpg-ial ) resulted in most of the external input being shunted to the
sediments where it entered the food web via the feeding activity of benthic
invertebrates. Given the observation that B(a)P was input in excess of its
solubility limits during this simulation, strict comparison with the an-
thracene and napthalene simulations may be unjustified. In future model
application, equimolar concentrations might provide results that are more
valid for purposes of comparison.
Initial results of application of the model indicated that molecular
weight carries considerable information concerning transport of PAH com-
pounds through, lotic systems. Nevertheless, much work is still required to
evaluate the overall utility of FOAM. Rigorous sensitivity analysis will
identify a set of parameters, of which the values must be measured with as
much accuracy as possible, as well as point out those parameters that need
only be estimated, say, within an order of magnitude. Systematic variation
of individual parameters in repeated simulations will accomplish this
aspect of the sensitivity analysis. From past experience with functional
forms used in FOAM (Bartell et al., 1981), likely candidates for sensitive
parameters in the production submodel are the Bayesian food prefeience
values, W.., and assimilation values, a...
The dynamics of PAH transport implicit in molecular weight are me-
chanically translated by several regressions into variable parameters
associated with the processes of photolysis, sorption, volatilization, and
solubilization. As a function of available data, each regression has its'
own band of confidence limits about the regression equation. For a parti-
cular molecular weight, regression derived parameters can be selected
randomly about the regression within the 95 percent confidence limits. Use
of these stochastic parameters in repeated simulations constitutes another
aspect of the necessary sensitivity analysis of FOAM. This analysis will
evaluate the robustness of the regressions and indicate which relationships
should receive additional attention or which ones require larger data
bases.
166
-------
Even without the results of rigorous sensitivity testing, there are
several aspects of the model that require modification. The version of
FOAM used in present simulations fails to link hydraulic power to net
suspension. Resuspension and settling rates of particulates are now inde-
pendent of current velocity, clearly an unrealistic assumption. Given the
importance of PAH sorption to particulates, dynamics of particulate sus-
pension are potentially important in terms of removing dissolved PAH from
the water column and introduction of PAH into organisms that either filter
feed or work the sediments. The submodel for net suspension should incor-
porate hydraulic power, reach dimensions, and size distributions of sus-
pended and settled particulates to more realistically simulate particle
processing in lotic environments.
The hydrologic routine is only capable of simulating constant flow
conditions. All reaches are identical in morphometry, and discharge into
the uppermost reach equals discharge between all reaches; the simulated
stream is hydrologically in a dynamic steady-state. While this limitation
does not constrain application of the model to the artificial channels,
model application to natural lotic systems depends upon the degree of
similarity between the stream segment of interest and the constant geometry
of the model reaches. Clearly, to make the model useful to the majority of
streams and rivers of interest, many of which are impounded, the hydrologic
submodel needs to be modified or replaced by an algorithm that can handle
variable reach dimensions and discharge regimes.
Simulation of B(a)P transport suggested, counter-intuitively, that
sorption was not an important process in determining the fate of this PAH.
Previous research (Karickhoff et al., 1979) indicated that this high molec-
ular weight, relatively insoluble PAH should readily sorb to particulats
matter. The regression was derived from analysis of data that described
sorption kinetics for a variety of PAH compounds and river sediments
(Karickhoff et al., 1979). The derived regression has an opposite slope
from a regression based upon sorption data from another source (SRI Report
in EPA file). Clearly, the analyses that lead to the present submodel must
be re-examined. It may be worthwhile to test the implication of the re-
gression based upon the SRI data base in the sorption submodel and overall
transport of compounds that appear readily sorbed to particulates, such as
B(a)P.
Another potential mechanical modification of FOAM resides in the
current integration scheme. The mass balance equations, while conceptual-
ized as a set of coupled partial differential equations (e.g., equation
5.3.1), are mathematically handled as a set of different equations with a
simple Euler integration routine. Results of simulations repeated at
different time steps should be compared in order to determine a time step
that optimizes precision and computing time. It might be necessary to
include a more sophisticated numerical integration algorithm (e.g., vari-
able step size Runge-Kutta method) to maximize precision at the expense of
increased computer costs per simulation.
A major conceptual weakness of the model lies in the production of
metabolic or degradation products of the particular PAH simulated. The
167
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current revision of FOAM directs a constant fraction of metabolized pareat
compound into the metabolite pool. We assume for the moment that
the metabolite pool does not undergo further degradation. No molecular
weight was assigned to the metabolite. In future versions of the model it
may be possible to simulate some characteristics of the degradation pro-
ducts based upon the structure of the parent compound. For example, the
number of rings and the kind, location, and number of functional groups
that comprise the parent compound might be used to predict the chemical
structure of degradation compounds that result from photolytic and metabo-
lic processes.
The physiological process structure of the equations for PAH transport
through the food web encourages linkage of lethal and suolethal toxicity to
the overall transport model. In the past, fate and effects have been
largely examined independently. As information accumulates concerning the
processes affected by toxic components of PAH, the component of the growth
derivative can be modified appropriately. For example, low molecular
weight fractions of certain oils have been shown to decrease the rate of
photosynthesis of marine algal species. This effect could be translated
into a concentration dependent term that multiplies the simulated photosyn-
thetic rate by the appropriate factor to model the toxic effect. Similar-
ly, rates of other processes (feeding, respiration, excretion, etc.) might
be adjusted to simulate toxic effects. Incorporation of these toxic effect
multipliers would directly link effects to transport through the food web.
Feedback between the modeling effort, analysis of published data, and
evaluation of laboratory and field microcosm experiments will result in
modification of FOAM to increase the model's usefulness as a management
tool for predicting PAH dynamics in lotic systems.
168
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SECTION 6
CHANNELS MICROCOSM STUDIES
SECTION 6.1
FACILITY DESCRIPTION
The channels microcosm facility used in this study is located on the
Department of Energy's (DOE) Savannah River Plant (SRP), a 507 km reserve,
including portions of Aiken, Barnwell and Allendale Counties in South Caro-
lina, U.S.A.
The channels microcosms facility (Figure 6.1.1) is a pass-through
system consisting of six separate cinder-block channels, each 91.5 m long,
0.61 m wide, and 0.31 m deep. Located at the upper end of each channel is
a pool 3.1 m long, 1.5 m wide, and 0.9 m deep. At the lower end of the six
channel facility is a single large pool 10.2 m l^ig, 3.1 m wide, and 1.0 x
deep. For these studies, the channels and headpools were lined with a 0.05
cm thick black polyvinyl chloride (PVC) film and covered with 0.05 meters
of washed quartz sand substratum.
Water for the channels was pumped from the Tuscaloosa aquifer via a
deep well located near the facility, treated to remove C0?, and hydrated
lime added to produce inorganic water quality similar to that of surface
waters in the local upper coastal plain (Table 6.1.1). Water flows were
monitored by v-notch weirs on each head pool where water enters the chan-
nel. Flow rates of 75.7 £*min were maintained manually by input valves
located above each headpool; this resulted j.n a current velocity
of 1.0 x 10 m'sec and a retention time of 2.5 h. The water depth in
each channel was maintained at 20 cm by use of control gates located at the
lower end of each channel.
Effluent water from the channels was pumped from the tail pool at a
rate of 108 gpm, into a large steel treatment tank where it was gravity fed
through a filter of activated charcoal and gravel prior to final release to
the local environment. At the point of release anthracene and anthracene
degradation, compound concentrations in the process water were at or below
background levels for water supplying the facility.
At the time water flow was commenced four channels were seeded with a
50-£ slurry of water, sediment and biological material (i.e., algae, zoo-
plankton, macroinvertebrates) from seven locations around the SRP site:
Brinkley Well, Skinface Pond, Ellenton Bay, Dicks Pond, Asphalt Pond and
Upper Three Runs Creek. Seeding was conducted weekly from March 11, 1979
169
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Figure 6.1.1. View of channels microcosms facility.
170
-------
Table 6.1.1. Mean water quality of treated well water
Total alkalinity
Hardness
pH
Specific conductance
Ionic strength (I)
DO
co2
so4'2
Total P
Nitrogen (N02 + N03>
Ca
Cu
Co
Cd
Cr
Fe
K
Mg
Mn
Na
17
21
6.
31
2.
8.
3.
1.
10
19
3.
3.
2.
0.
0.
1.
1.
.5 mg/£ as CaCO-
«J
.5 mg/£ as CaCO,
6
jj mho/ cm
5 x 10"4
5 mg/£
25 mg/£
9 mg/£
.1 pg/*
.2 vg/S.
17 mg/£
4 pg/£
5 pg/£
023 \ig/H
3 pg/£
7 |Jg/£
1 Mg/J^
246 |Jg/£
7.
1.
0 pg/£
8 mg/£
171
-------
through June 13, 1979 and daily from June 13, 1979 to July 16, 1979 after
which these channels were allowed 10 weeks of additional colonization prior
to the introduction of anthracene. Also, during the early stages of the
seeding processes the macrophytic angiosperm Juncus canadensis was trans-
planted to the system. Juncaceae represent the dominant inacrophytic group
which has naturally colonized the channels during past studies (Kania et
al., 1976, Giesy et al., 1979). £•'
METHODS AND MATERIALS
Anthracene (Aldrich Chemical Co.) was made up to 649±86 mg-£~ in
pharmaceutical grade ethanol. Stock was introduced via a peristaltic pump
at 2.1210.2 ml-min for a nominal anthraceneconcentration of 18.2 |Jg*^
and a nominal ethanol concentration of 23 mg-Ji . Fresh stock solution was
prepared daily and was introduced through stainless steel tubing (excepting
15 cm of silicon rubber tubing within tb° pump) directly into the turbulent
mixing zone of the channel. Nominal anthracene concentrations were not
obtained. The average observed input of anthracene was 16.2 and 13.8 |Jg*£
for the abiotic and biotic experiments, respectively.
Anthracene was introduced into a newly lined uncolonized channel
microcosm (abiotic study) for five days (August 18-22, 1980) and samples of
water, sediment (sand) and plastic liner material were taken from reaches
one, two and five. Samples cf water, sand and plastic liner were taken on
days two and four at dawn and 1530. Samples of water, sand and plastic
liner were taken at noon on day one and three and at 1030 on day five. No
samples were taken after the five day input period.
Anthracene was subsequently introduced into a biologically colonized
channel (biotic study) for 14 d of exposure (September 22 - October 6,
1980). Samples of water, organic sediment, periphyton, 'fish, clams and
plastic liner were takeu from reaches one, three and five on days 1, 2, 3,
5, 8 and is during the period of anthracene input. Samples were also taken
1, 2, 4, 8, and 14 days after anthracene input was terminated (October
6-20). For sampling and modeling purposes, the channels were divided con-
ceptually into five 8.3 m long reaches. Samples ware taken at 4.58, 9.15,
and 13.7 m from the beginning of each sampled reach. For the abiotic
study, water samples only were taken on days two and four at dawn and 1530
to evaluate photolysis losses. Water, sand, and plastic were also sampled
at noon on days one and three, and at 1030 on day five.
In the biotic study, water samples were taken at noon on days 1, 2, C,
5 and at dawn on days 2, 5, 8, 15, 16, 17, 19, 23 and 29 from reaches one,
three and five. Sediments and periphyton were sampled from reaches one,
three and five on days 2, 3, 5, 8, 15, 16, 17, 19, 23 and 29 at 0830.
Clams, fish and plastic were sampled from reaches one and five at 0830 on
the same days as the sediment and periphyton.
172
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Water
One-liter water samples were acidified with 1 ml of concentrated HC1.
Control and blank water samples were taken at the weir prior to the addi-
tion of compound. The control was spiked with 3135 ng (abiotic study) or
5371 ng (biotic study) anthracene and 4578 ng (abiotic study) or 5076 ng
(biotic study) anthraquinone in 30 pi acetonitrile. The water samples were
passed through ArcberliteTCAD-4 resin (Rhom and Haas, Philadelphia, PA)
macroreticular adsorbant for anthracene and anthraquinone. The resin
columns were 1.5 cm diameter x 25 cm long equipped with a 250 ml reservoir
and a stopcock. A plug of glass wool was placed in the column and 30 ml of
wet precleaned XAD-4 resin was added to the column. The resin was pre-
cleaaed with and stored under nanograde methanol. Prior to use the columns
were drained and rinsed with 10 bed volumes of deionized water. Water
samples were percolated through the resin at a flow rate of 0.8-1.2 £ •
hr . The columns were eluted sequentially with two bed volumes each of
anhydrous diethylether and nancgrade acetone. The solvents were combined
and dried over anhydrous sodium sulfate. The solvent volume was reduced to
~ 200 (Jl by a combination of rotary flash evaporation and evaporacion under
a stream of nitrogen. Acetonitrile (2.0 ml), containing the chrysene
internal standard, was added to each sample. This was mixed and 25 pi
analyzed by high pressure liquid chromatography (HPLC). The recovery from
fortified control samples was 62.319.8% (x ± SE) for anthracene (n = 7) and
84113% for anthraquinone (n = 7) in the abiotic study. For the biotic
study the recoveries were 89.212% for anthracene (n = 24) and 10513.4% for
anthraquinone (n = 24).
Sediment
Sand sediment to be sampled during the abiotic study was placed in the
channel in 3.3 cm deep crucibles. One crucible was removed from each sta-
tion at each sampling time. The interstitial water was removed by vacuum
filtration. Samples were extracted in a soxhlet apparatus for 18 h with
benzene:acetonitrLie (65:35, v/v). The samples were dried over sodium sul-
fate and prepared for HPLC analysis as previously described. Blanks and
control samples were removed from the stream prior to the addition of com-
pound, filtered and stored frozen under acetoniLrile. Prior to analysis,
controls were spiked with 1045 ng anthracene and 1526 ng anthraquinone.
Organic sediments for the biotic study were collected from a silt bank
at Box Landing on Upper Three Runs Creek. The sediment was sieved through
a 5 mm stainless steel screen, mixed and placed in 144, 15 x 60 mm glass
petri dishs. Twelve cf the sediment filled petri dishes were placed at
each sampling station in reaches 1, 3 and 5. One randomly chosen petri
dish from each sampling station was removed at each sampling time. Three
control sediments from an adjacent channel, which did not receive anthra-
cene, were removed per sampling time. Figure 4.2.1 (Section 4.2 this
report) shows a flow diagram of the extractiou and analytical procedure
utilized tor sediment camples during tne biotic study. Each sample was
filtered through Whatman number 4"! filter paper usir.g ^20 ml of distil] ed
water to rinse the petri dish. The sediment was weighed and MO g sub-
173
-------
sampled for extraction and analysis. The remainder was dried at •v50°C for
1 to 2 weeks and dry weight determined. Each subsawple for extraction was
mixed with MO g of granular anhydrous Na SO,, transferred to a Whatman 22
x 80 mo cellulose extraction thimble an/ stored under 35 ml of acetoni-
trile, at -20°C. The three control sediments were treated identically
except that one sediment was spiked prior to addition of sodium sulfate
with 1045 or 1790 ng of anthracene and 1526 ng or 1685 ng ^nthraquinone in
acetonitile.
One sample set corresponding to one sampling date consisted of 9 ex-
periraentcls, 2 background controls and 1 spiked control. The sediments and
acetonitrile for each sample set were placed in soxhlet extractors with 65
nl of benzene and extracted for 18 h. The crude extracts were rotary flash
evaporated to ^2 ml; passed through a 7 ca column of Florisil , eluted with
three benzene rinses (^2 ml each) of the round bottom flask and 10 ml of
901 Benzene:ieethylene Cl,(9:l, V/V). The sample volume *as reduced by
rotary flash evaporation "and evaporation under a stream of nitrogen to 200
pi. Two or four milliliters of acetonitrile containing a chrysene, inter-
nal standard was added to each sample. The samples were mixed and placed
in a freezer overnight. Precipitates that formed overnight were removed by
ceatrifugation and the superantant was transferred and stored at -20°C
until HPLC analysis. Recovery of anthracene from spiked sediment was 73.3
* 7%, n = 5. Anthrnquinone could not be quantified in extracts from sedi-
ments because of an interfering compound, which could not be resolved from
anthraquinone by HPLC (see Section A.2).
Poriphyton
2
A constant area of 75 cm of periphyton was scraped from the walls of
the channel. This was removed as an aqueous suspension. After all th<*
samples were taken, the water was removed by filtration and a wet weight
determined.
Subsaoiples from each reach were removed for subsequent species identi-
fication. Samples for identification were stored in a mixture of 60% deio-
nizcd water, 301 ethanol (95%) and 10% formalin, prior to microscopic
analysis. A second subsaraple was stored under ethylacetate:acetone (4:1,
V/V) at -20°C. Three controls and one blank were taken from a non-exposed
channel. The controls were spiked with 1790 ng anthracene and 1685 ng
anthraqulnone in 10 pi acetonitrile.
The samples were extracted by homofienixation in a TenBroeck tissue
grinder with 2 x 12 tal cthylacetate:acetone (4:1, V/V) and 2 x 12 ml cyclo-
hexane. The extracts were combined, dried over Na^SO, and the volume re-
duced to •*• 300 pi. The internal standard was «3ded initially in 2 ml
acetonitrile. However, problems of a two phase separation occurred; subse-
quently, 1 ml ethanol was used to add the internal standard. The samples
were analyzed by HPLC. The recovery of anthracene from fortified samples
was 70.1121. Samples were corrected for background, which averaged 107 ng
anthracene per sample.
174
-------
Fish
The conditions for the subsequent experiments on fish in the channels
were slightly different. Juvenile bluegills, Lepomis cmcrochirus, of mean
length 5.0 + 0.1 c» ( + 2SE, N = 58), mean wet weight 1.2 + 0.1 grams (N =
58), and with a dry to wet weight ratio of 0.222 (N = 45), were obtained
froa the National Fish Hatcheries at Millen, Georgia and Orangeburg,
South Carolina. Only fish appearing in excellent condition were used. The
fish were acclimated for 48 b in a control channel and then transferred to
glass and stainless steel mesh cages in the experimental channel 12 h
before the initiation of anthracene dosing. During both the acclimation
and experimental periods fish were fed with Tctra Hin staple food flakes
once a day.
Fish for anthracene assays were collected by dip net, wet weights were
determined and whole fish were placed into vials containing ethylacetate:
acetone (4:1 v/v) aud stored at -20°C until analyzed. Prior to analysis
fish were homogenized in 2 x 12 ml ethylacetate acetone (4:1, V/V) and 2 x
23 ml cyclohexane in a TenBroeck glass tissue grinder. Extracts were
combined, dried over anhydrous N'a.SO, and volume reduced to ~ 300 \il,
Control fish were spiked with 895 ng anthracene and 843 ng anthraquinor.e in
5 pi of acetonitrile. A chrysene internal standard was added to each sample
in 2 ml of acetonitrile. Analysis was by hPLC and anthracene recovery froa
fortified controls was 94.5 + 2.5%. Reported fish whole boay anthracene
concentrations after 24 - 144 h of depuration are freshly dead animals
collected when observed or taken at the end of the experiment. Analyris of
dead fish became necessary due to unexpected acute phototoxicity (see
Section 6.6).
Claras
Individual clams were sampled frota each sampling station and a wet
weight determined. The tissue and all fluid from the closed animal were
blended and a homogeneous subsomple taken for analysis. The weight of the
subsample and shell were determined. The sample was />ddcd to 40-60 ml of
anhydrous Na^SO, for desiccation and stored under either cyclohexane or
cycohexane:ethylacetate (1:1, V/V) at -20°C. Three controls and two blanks
were prepared in the same manner from an unexposed population. Tne con-
trols were spiked with 895 ng anthracene and 843 ng anthraquinone respec-
tively.
The sodiuaj fculf-Ue coaled with desiccated clats was extracted by shak-
ing with 2 x 50 Hi cyclohfx«ne:ethylacct,ite (1:1, V/V) and 2 x 50 sal cyclo-
hexane. The volume was reduced to ^ 200 pi «nd internal standard added in
acetonitrile. The recovery of anthracene from fortified samples was 8717%
(n = 6).
Plastic Liner
Plastic strips were placed at mid-reach in reaches one, two and five
(abiotic study) and one, three and five (biotic study). These were sampled
175
-------
2
using a cork borer which yielded plugs of / .45 cm . Six plugs were taken
«l each sampling time. The plastic was stored in the freezer prior to
Analysis. The plastic was extracted by shaking 5 min in (2 x 20 ml) ethyl-
acetate racetone (4:1, V/V). Recovery for fortified samples was 9117% for
anthracene. The samples were prepared for HPLC analysis as previously des-
cribed for water extracts.
Ueatber and Sunlight
Air tecperature', water temperature and general weather conditions were
recorded at each sampling time. Solar radiation was determined using a
Belfort Instrument Company Pyranograph Cat. No. 5-3850A located approxi-
mately 10 miles southwest of the channels microcosms.
Quantification
The samples were analyzed for anthracene and anthraquinone using a
Varian Model 5000 HPLC system with a 254 run fixed wavelength detector.
Separations were made with a 35 cm Micro-Pak HCH-10 reverse-phase column,
which was equipped with a Whatman guard column of Co-Pel C.,,ODS on 35 Mm
particles. Compounds were eiutcd from the column at 28°C by programing
the moble phase from a /5«% acetonitrile: 25% water mixture to 90% acetoni-
trile: 10% water (Johnson et ^1., 1977). Acetonitrile (90%) was pumped
through the column for five Bin before recreating the initial conditions.
The sediments required a gradient to 100% acetonitrile to remove late
cluting compounds.
Quality Control/Qua 1ity Assurance
The recovery and precision for each of the matrices was determined by
applying the proposed method to fortified samples (Table 6.1.2). Many of
these studies were performed with C-anthracene. The storage stability
was checked by storing fortified samples the same length of time as the
samples.
The background determinations were made from samples analyzed at the
same time as the environmental samples. The limit of detection was taken
to be 3 o * background (Table 6.1.3). The linearity of the analysis was
determined with each sample set by creating a standard curve.
The accuracy of the analysis was determined by analysing a standard
PAH mixture Alltech (PAH-I) which contained anthracene. The relative
amount of anthracene determined over several months was 96.5 + 8% (n = 10).
Double peaks at or near the retention time for anthraquinone for some
sediment samples were confirmed by GC-mass spectrometry (see Section 4.2^.
176
-------
Table 6.1.2. Recovery and precision of anthracene and anthraquinone from
various matrices.
MATRIX aX RECOVERIES
Anthracene Anthraquinone
Sediments
A) Sand
B) Organic
Fish
Periphyton
Clams
Water
Plastic Liner
15.5 ± 2
71.2 ± 12
87.7 ± 6
78.5 ± 2
78.9 ± 2
81 ± 2
91.1 ± 7
b
b
92.3 ± 8
82.2 ± 3
93.2 ± 2
97.6 ± 4
b
ax ± 1SU
not determined because of interferences
177
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Table 6.1.3. Background end Units of detection for analysis of Anthracene
and Anthraquinone from various matrices
Matrix
Background Limit of Detection
Anthracene Anthraquinone Anthracene Anthraquinone
Water
Input Phase
Depuration
Phase
Periphyton
Fish
Claa.s
Sediments
Plastic
56 + 44 ng-jT1
3.8 ± 8.5 ng-£-1
_2
0.68 ± .64 ng'cin
47.6 ng/fish
103 + 70 ng-R dry wt
53.3 ± 2(> ng-g dry wt"
KD
322 + 336
ND
ND
KD
m
1 ND
KD
188 ng-f"1 1330 ng'£~]
29.3 ng'i'1
_2
2.6 ng-cia
116.9 ng/fish
315.75 ng-g dry wt"1
131.6 ng-g dry wt
ND Not detected. Instrument Detection limit 0.25 ,ig = S x 2N
178
-------
Statistical Methods
Rate constants for accumulation and elimination from each geological
and biological matrix as well as steady state concentrations were estimated
by least-square fits of the data to first-order, donor-dependent models.
Each data set was fit independently by the methods of Ciesy et. al. (1980)
with the Marquardt iterative least square procedures (NLIN of the^Jtatisti-
cal Analysis System, Barr et aK , 19/9).
Dynamics of anthracene in each component were calculated by fitting
data to equations with the general form given in equation 6.1.1
dC 6.1.1
—- = K -C - K.-C
dt " W d a
where
K = uptake rate constant
u
K, = depuration rate constant
C = concentration of anthracene in the water
C = concentration of anthracene in the component
t = time
To avoid biases introduced by making inappropriate assumptions, most param-
eters were estimated by several different equations, which wade different
assumptions.
Accumulation of anthracene by the PVC liner was linear during th««
period which anthracene was input into the channels (Fig. 6.2.3). After
anthracene inputs were terminated, .nthracene desorbed slowly from the PVC.
Because organic compounds such an anthracene tend to partition into
organic matrices an estimate of the possible loss to the PVC liner was made
by exposing PVC strips, which were not colonized by periphyton. Sorptive
losses to PVC estimated in this manner are a conservative estimate. That
is, because the PVC extracted was not covered by periphyton, this number
represents a maximum loss to the liner that would be expected.
The uptake flux into any component can be described by equation 6.1.2
J = C • K 6.1.2
w u
179
-------
By making the initial rates assumptions, that the amount 01 anthracene in
the component of interest is small during the initial uptake period, one
can estimate the uptake rate constant by taking a tangent to the uptake
curve (J) and dividing by the water concentration.
Because the water concentration C is relatively constant for a given
period of exposure the equation which describes the dynamics of anthracene
in a given component can be simplified to
^n -(K 'tl 6.1.3
C = ~ • (C ) (1 - e (Kd t})
K
Kd
the concentration of anthracene in the component of interest approaches
steady state as t •» a. Thus, at t -» a
C K
BCF = — = — 6.1.4
Cw Kd
Equation 6.1.4 gives the relationship between the bioconcentration factor
(BCF) or steady state distribution between the water and component of inter-
est. Also, from equation 6.1.4 it can be seen that the steady state concen-
tration can be predicted from equation 6.1.5, when the water concentration is
constant '
C = C (1 - e"(Kd*°) * ' ' 6.1.5
a ss v
where
C = steady state concentration hi component.
We have given equations for estimating KU, KD and CSS during the
period of exposure. To test for biases in fitting equations to estimate KD
during only the uptake period, the concentration of anthracene in each
component was followed during the depuration period, whtn no anthracene wss
being added to the channels. Estimations of multiple depuration rate
constants were made by fitting the observed data to equation 6.4.1
n -(K.,'t)
C = Z Ca -e di 6.1.6
where
C = concentration in component at time t
C , = initial concentration in ith component
i = individual depuration component
18C
-------
K., = depuration rate constant for ith conponea'.
n - number of independent depuration components
181
-------
RESULTS AND DISCUSSION
CHANNELS MICROCOSM STUDIES
SECTION 6.2
WATER
In the abiotic study the control samples for the water had recoveries
of 62.3 ± 9.8% (x ± SE) for anthracene and 84 ± 13.1% for anthraquinone
(Table 6.2.1). These values were considerably lower than those determined
Table 6.2.1. Percent recovery of anthracene and anthraquinone from control
water samples in abiotic channels experiment.''
Saaple Set
1
2
3
A
5,
6
7
Anthracene
ng-£
1745
2960
1917
2172
674
2265
3096
% Recovery
56
94
61
69
22
72
99
Anthraquinone
ng'£~l
5442
5178
3192
3493
1451
4298
5705
« r, b
i Recovery
119
113
70
76
32
94
125
One liter control water samples were taken upstream of anthracene input
(weir) at each sampling period and spiked as follows: 3135 ng anthracene
and 4578 ng antbraquinone in 30 pi acetone. Blank water (no additions)
recorded anthracene (91.8 ± 78 ng-£ ) and anthraquinone (298 ± 213
1
Calculated .is: ngv? detected/ng*£ spiked.
182
-------
for samples of the same water fortified in the laboratory -- 81.1 ± 1.5%
for anthracene and 97.6 ± 3.9 for anthraquinone. This nay have occurred
due to the additional handling and transport time (30 minutes) in the heat
from the channels microcosms to the laboratory.
Aftrr correcting for recovery, some loss occurred between the input
aad the first sampling station which was not accounted for by the sum of
the anthracene and anthraquinone (Table 6.2.2). The average accountability
was
Table 6.2.2. Calculated input of anthracene to channel
and measured values in reach one.
Day Calculated Anthracene Measured Anthracene.
Input (jJg*£ ) Concentration
I
2
3
4
17.7
12.6
21.1
21.8
11. A ± 0.4a'b
11.4 ± 0.7C
K
7.3 ± 1.3°
18.4 ± 1.7C
x ± ISO, all values corrected for average control
recovery
Values recorded at noon
Values recorded at dawn (7:30 am)
76 i 5.3% and ranged from 48-95%. The average actual anthracene concentra-
just below theinput in both the biotic and abiotic studies were approxi-
mately 12 Mg'£~ • Anthracene concentrations in the water showed signifi-
cant diurnal variation. Maximum water concentrations (steady state) were
achieved and maintained during periods of darkness. However concentrations
decreased significantly with distance downstream during daylight periods.
Photolysis accounts for 100% of the loss down the channel, with the other
matrices falling in the experimental error of our ability to measure water
concentration. In the absence of photolysis (dawn samples) the anthracene
concentration in the water was at steady state within 24 h in both the
abiotic and biotic studies (Table 6.2.3 and 6.2.4) (Figs. 6.2.1 and 6.2.2).
Samples taken at noon or 1530 h had lower concentrations of anthracene than
dawn samples in reaches 3 and 5 (Table 6.2,3 and 6.2.4, Figs. 6.2.1 and
6.2.2 ). The loss, rate constant for all noon and afternoon samples was
0.016 ± 0.006 rain" which is a half life of 4T 3 ± 12 min. Siuce the loss
of anthracene was observed in both the abiotic and biotic study the most
probable cause is photolysis rather than photo-respiration by microbial
populations in the water and benthos.
183
-------
.-1
Table 6.2.3. Concentration (pg-J? ) of anthracene and anthraquinone in water.
Day Time Reach 1
Anthracene Anthraquinone
III.O"' lln.o"'
Reach 2
Anthracene Anthraqui
ue-£ uc«£
none
eac
Anthracene Anthraquinone
pg-2~ pg-1
CD
1 12:00 paj 7.7 ± 0.3 2.4 ± 0.3
2 8:00 am 7.7 ± 0.4 0.09 ± 0.05
2 3:00 pm 5.3 ± 0.8 0.8 ± 0.4
3 12:00 po 4.9 ± 1.0 3.0 ± 0.4
4 8:00 am 15.8 ± 13.3 0.8 ± 0.5
4 3:00 pm 14.1 ± 12.2 3.6 ± 1.2
5 10:30 an. 5.2 ± 3.4 1.5 ± 0.6
3.1 i 0.1 3.9 ±2 1.8 ± 0.1 2.A ± 0.7
8.2 ± 0.3 0.08 ± 0.03 7.9 ± 0.2 0.08 ± 0.05
3.4 ± 0.3 2.1 ± 0.5 !.7 ± 0.3 1.7 ± 0.3
3.4 ± 1.0 3.1 ± 0.4 1.3 ± 0.1 2.7 ± 0.3
13.1 ± 0.3 0.6 ± 0.3 11.7 ± 1.3 0.3 ± 0.08
4.7 ± 0.6 4.6 ± 1.4 0.9 ± 0.2 3.0 t 0.9
9.9 ± 1.5 4.9 i 1.5 9.0 ± 0.2 4.8 i 1.2
All values mean ± SD of three samr-ing stations in each teach.
-------
Table 6.2.4. Percent accountability nM anthracene + nM anth;jqui-
nonf/actual anthracene input (nM).
Reach 1 Reach 3 Reach 5
Dawn 102 106 103
Noon 96 77 48
Dry 8 Heavy
Cloud cover 110 95 80
Noon
Concentrations of anthraquinone were more variable than those of an-
thracene. Anthraquinone concentrations were near zero in raicples taken at
dawn (Table 6.2.5). Concentrations of anthraquinone in water samples taken
during the day ranged from 1-5 pg'£ • This suggests that the authraqui-
none was due to photolysis of anthracene.
Plastic Liner
Accumulation of anthracene by -he PVC liner was linear durirg the
period during which anthracene was input into the channels (Fig. 6.2.3).
Attei anthracene inputs were terminated, anthracene desoibed slowly from
the PVC.
Because organic compounds such as anthracene tend to partition into
organic matrices an estimate o* the possible loss to the PVC linear was
made by exposing PVC strips, which were not colonized by periphyton. The
estimate of sorptive losses to PVC estimated in this manner are a conserva-
tive estimate. That is, because the PVC extracted was not covere'l by
periphyton, this number represents a maximum loss t the liner that would be
expected.
185
-------
WATER ANTHRACENE CONCENTRATIONS
9000
8000
7000
6000
o»
c
Uj 5000
Z
UJ
o
< 4000
cc
I
\-
- 3000
2000
1000
• Doyl Noon
• Ooy 2 Down
3
REACH
—r
4
T"
5
Figure 6.2.1.
Anlhr.icene ronrentr.it ionr. in rojch 1 tlurinr, ti'f input
of tlic abiol ic stii
-------
o>
LJ
O
<
cc
x
BIOTIC STUDY
I5
10
1*1*
\\\v
DAWN NOON
REACH 1
= I5
dn
* ± a S.E.
DAWN NOON
REACH 3
Downstream
T
DAWN NOON
REACH5
Figure 6.2.2. lllstor.r.iin rcprcsmLittK .intlir.icc-nc concent r.i lions
from rr.ichcs 1, 3 ami 5, rluritij; ll>c l>iotic nlmly.
.'a I c r
187
-------
Table 6.2.5. Input and mass balance of anthracene/anthraquioone in reach one.
no
CD
Day
1
2
2
3
4
4
5
Sample Calculated Input Measured Concentration
Time Anthracene (nM) Anthracene (nM)
12:00 pea
7:00 am
3:30 pta
12:00 pm
7:00 pea
3:30 pm
10:30 amb
99
99
71
118
113
122
0
63.9
63-6
44.7
40.4
108-7
58.4
43.5
Measured Concentration Percent
Anthraquinone (nM) Accountability
13.1
O.A
4.3
15.8
3.3
19.2
8.1
77.8
64.7
68.7
47.7
94.7
63.6
«-t
Accountability - uM anthracene + nM anthraquinone/calculated anthracene input (nM).
Input stopped 1 h prior to sampling.
-------
PVC LINER - REACH I
1200
1000
o
»x
UJ
z
UJ
o
800
600
«" 400
200
I
Augutt 1380
' Abiotic
.Avguil 1980
*± ISO.
N =6
•UPTAKE-
, Abiotic
* Jvpait I9BO
-------
SECTION 6.3
SEDIMENTS
The rate constants for uptake and depuration from sediments were not
significantly different among the three reaches (Table 6.3.1 and Fig.
6.3.1). This indicates that the rates of accumulation were indeed first-
order with respect to water concentrations of anthracene because the mean
concentrations of anthracene in the water varied and fluxes into the sedi-
ments varied in proportion to the water concentrations. Depuration from
the sediments was also first order with respect to the concentration in the
sediment (Table 6.3.1 and Fig. 6.3.1). Because the rate of accumulation
could be related to the rate of diffusion into the sediment, we normalized
the concentration of anthracene in the sediments on both a weight (Ttble
6.3.1) and area basis (Table 6.3.2). The relative variabilities of the K ,
K. and C values from the three reaches were less when normalized to area
but not greatly so (Tables 6.3.1 and 6.3.2>.
The sorption and desorption of PAH are some of the most difficult
mechanisms to model and predict. Host previous models have used steady
state partitioning coefficients in completely mixed systems to predict the
proportion of PAH associated with the sediment. It is difficult to develop
a probabilistic model to predict the PAH sorbed to settled sediment or to
quiescent sediment. Also, the rate of sorption and desorption of PAH from
quiescent sediment may be determined by the rates of diffusion into and out
of the sediment as well as settling and resuspension processes.
The results of the experiments presented in Section 4.2 indicate that
PAH diffuse into organics and clay lattice spaces as a function of time and
become less available. One of the most difficult hydraulic processes to
Model is bed movement of sediment. This process may be potentially impor-
tant in determining the dynamics of PAH associated with sediments. Fur-
thermore, catastrophic (i.e., storm) events may be the most important
process in determining the overall movement of PAH associated with sedi-
ment. Bioturbatfon has been found to be an important process in determin-
ing the transport of PAH into and out of sediments. Even though many of
these transport and .-csuspension mechanisms are known and quantifiable,
developing a mathematical simulation model will be difficult. One of the
main reasons is the temporal sc.iling of catastrophic effects, relative to
the time steps required to attain adequate resolution of other processes.
For this reason we feel that simulation of the dynamics of PAH associated
with sediments will always be one of the least accurate components of
simulation models. This will be a severe limitation of simulation models
becaus' of the great affinity of sediments for PAH in aquatic systems
(Giddings et al., 1978). We suggest that for short-term simulations the top
190
-------
2 en be considered us a homogeneous completely mixed storage pool for which
the sorption and desorption fluxes are not diffusion limited.
191
-------
TABLE 6.3.1. First order rate constants for uptake and release of anthra-
cene from organic sediments during the channels microcosm
experiment based on dry weight of sedimeut. Data was fit by
the Marquardt iterative least squares procedure. X + SE,
n = 3, PF < 0.001 for all regressions.
Ka
u
Kb
Kd
K C
Kd
c d
ss
a . -1
ml'g
Reach
1
1.3 + 0.093
~~
0.0048 + 0.0007
C.0022 + 0.0003
3265 + 266
•h"
Reach
3
1.4 + 0.13
0.0049 + 0.0009
0.0022 + 0.0004
2980 + 298
Reach
5
1.4 + 0.11
0.0040 + 0.0007
0.0025 + 0.0003
2917 + 306
h , assuming density of sediment is near 1, estimated from data collected
during anthracene input.
C h" , estimated from data collected during period of no anthracene input.
ng aothracene-g sediment, dry weight
192
-------
SEDIMENTS: REAV.H i
41448
SEDIMENTS:REACH j
TIME (hr»)
SEOIWEHTS: REACH 5
JJ6 J444JJ
TIME ( I-..*!
672
Figure 6.3.1.
ion of jtithr.icrof l>y or^.inic ^nltmcnls in
pc-tri
-------
TABLE 6.3.2.
First order rate constaits for uptake and release of anthra-
cene from organic sediments, based on area of sediment.
Data was fit_by the Marquardt iterative least squares
procedure. X + SE, n = 3, PF < 0.0001 for all regressions.
Reach
1
Kua 0.22 + 0.014
K.b 0.0034 + 0.00056
d —
K.° 0.002 + 0.0003
d —
C d 800 + 86
S3 —
Reach Reach
3 5
0.27 + 0.016 0.26 + 0.019
0.0039 + 0.0005 0.0032 + 0.0006
0.0023 + 0.00033 0.0027 +. 0.00028
685 + 57 680 + 87
~
a , -2 . -1
ml* on -b
h" , estimated from data collected during period of anthracene exposure
h , estimated during period of no anthracene input
j _^
ng anthracene'cm sediscnt
194
-------
SECTION 6.4
PERIPHYTON
The anthracene concentrations reported are not corrected for extrac-
tion efficiency vhich was 71% + 0.1 (X + SD). Thus, the numbers reported
are approximately 30% less than the total amount of anthracene contained in
the periphyton. Since the reported values would be corrected by a constant
this does not affect the trends reported. Since there is an error associ-
ated with determining the extraction efficiency at each point we decided
not to confound this error with that of the extractions and quantifications
of anthracene in periphyton. The dry to wet ratio for periphyton was 0.034
+ 0.016 (SD, n = 11).
Concentrations of anthracene in the periphyton community were normal-
ized to both an crea and a wet weight basis. Similar crends were observed
for data reported in both ways (Figs. 6.4.1, 6.4.2, and 6.4.3). The coef-
ficient of variation was generally less when concentrations were reported
on an area basis but this was not always true. There was a general in-
crease during the first 48 h of exposure, however, there was some decrease
between 24 and 48 h in reach 1. Concentrations in periphyton from resch 1
were much greater than those in reach 3 which were in turn approximately
four times greater than those in reach 5. The trend of greater conc'«r>.-
trations at the upstream sites was consistent at all sampling times during
anthracene exposure.
Because of the variability of anthracene concentrations in periphyton,
no rate constants were calculated. Uptake of anthracene was rapid, and
reached steady state within 168 h. Furthermore, desorption of anthracene
was very rapid (Figs. 6.4.1, 6.4.2, and 6.4.3). The anthracene concen-
tration was not significantly different from b-ckground after 48 h. The
half-time for elimination was less than 1 day.
The concentration of anthraquinone in periphyton w.js variable and not
very different from background. An interferring peak could not be resolved
by HPLC so anthraquinone concentrations are not reported here.
Removal of anthracene from the water column by periphyton was not a
significant vrctor. After day 4 and 14, 0.09 and 0.04% of the anthracene
added to the channels had been removed by periphyton. While this is not a
significant reduction of the mass of anthracene added to the water, con-
sideration of the periphyton component could be much more important as a
potential for food web accumulation. While it is our opinion that the
vector of food is not as important as that of direct exposure from water,
195
-------
for aquatic organisms, more data are needed 'to determine the relative
importance of this vector.
196
-------
CM
E
^ PER1PHYTON- REACH 1
ui 30
2
UJ
< 20
ce
I .0
2
Ul
2 700
UJ
o
£ 500
tr
X
2 300
c" IOO
-
:A j>^— H
NM I •*• Ka'nr
^ 0 \»
II*| 1 | I 1
b ^
ANTHRACENE INPUT
•
Ax 1(± SO
/ \' N - 3
T f' ^
' " / X
. M / \
i T /* ^
/ \ / \
* 1 \\ * \
i Y \
. * i i
. [ V-
\ BO
42448 96 I&3 360J044CO
TIME (hrs)
Figure 6. 'i. 1.
AnLlir.iccnt! concent r.i t ions in ;icr i,>liyto.i in rr.ich 1 •1
funrtion of Lime. Upju'r Hptire rrprcsrnts .nithr.icrne -c
while the lower fiK'»'<-' rop resents .inthfJtcne 'K .
weight, pcriphyton.
197
«ifV
-------
e
c
I PERIPHYTON - REACH 3
ANTHRACENE INPUT
BG
1 1 f >
1000
8CO
Id-
's*
tr .
Xo
H-S
o»
c
200
/
/
4 24 48 96
X±SD
N- 3
x
L
-
BG
168
TIME (hrs)
360 304 408
6./».2. Anthr.icone conrcntr.it i on:; in prriphytoii in rc.irli 3 -is_2a
function of time:. Upper f inure represents .intlir.icene-cm ,
while. the lower figure represent.-. .intliracenfj; , dry
weight, pcri|.hyton.
198
-------
PERIPHYTON - REACH 5
9
8
7
N
S *
•^
LJ
Z 5
LJ
O
< 4
CC
X
£ 3
fc **
<
0- o
c ^
1
0
•^
UJ
2 - 300
LU •*"
o.?
< a>
Q: 5200
X :K
V- «-
z ^ ioo
*t
en
o
c 0
"i1
ANTHRACENE INPUT |
i '
,
/
ki •» /
N « 2 .
/
9/n ' 2
!
' I
ln*\
1
x±so |
1 1 ^
N - 3 . (I*
, I
• T
i
.
.
\ ^
\ ^^.-^N.I
\ ^^^^
V-^
N»l
S
3
s
^
^.
^
^
a
^
*•-! ; — i 1 r- • i '
_ H i 1
N »2 S
/n*2
_. fj a 1
f
A-
^ _v ^»
^^ N'l . — * \-
^^ , H • 1 \ C,
1 \
42448 96 169 360 384 40«
TIME (hrs)
Fipuro 6.A.3. Antl-r.icrnc concoiilr^L ions in pcfipliy ton in rcarl' 5 -TS.T'"1
Unction of Lime. Uppor fiRiiro represents ...it lir.icrnc-cm ,
while tlie lower figure n-i'>-csruts nnthr.iccne-R ,
-------
SECTION 6.5
CLAMS
After 336 h of exposure to anthracene, papershell clams, Anodonta
imbecillis, had attained 96% of the projected steady state concentration of
17,580 ng antarocene-g , dry weight of soft tissue which could be attained
at approximately 500 h of exposure (Fig. 6.5.1). The first order uptake
and depuration rate constants estimated simultaneously during the J36 h
exposure period were JL3.99 + 1.7 (asymptotic standard error, ml-g 'h )
and 0.0080 + 0.0015 h respectively. This depuration rate constant cor-
responds to a half time for elimination of approximately 88 h. See Section
4.7 for a discussion of PAH accumulation and depuration by molluscs and the
lack of oxidative biotransformation observed in most molluscs.
200
-------
20,000
o
23
< *»
_J •- I 5,000
— uj
IO.COO
o
CC =(KU/KD) CW(l-e"KD"T
F2.39 =302
P< 0.0001
5,000
4,000
3,000
2.0CO
I.OOC
n
> V
>• \f ANTHRACENE INPUT
l
1
0 2448 96 168
TIME (hrs)
336
Figure 6.5.1.
Uptake of .ml lir.i erne by soft tissues of cl.ims during tlic
poriocl of anllirjccnc input, to llio cli.innels. E.icli point
represents the mean of 6 clams. Confidence interv.ils ol 1,'GE
arc presented. Tlir le.isl squ.irrs predicted repression curve
for the indicated movie 1 is Riven.
201
-------
SECTION 6.6
FISH
During the channels microcosm study, we observed mortality of bluegill
Runfish. The first fish mortality was observed as early as 1530 hrs, 7 h
after the anthracene infusion was started. By 1700 hrs, 9 h of exposure,
all of the fish in reach 1 of the experimental channels were dead. In
reach 5, the reach farthest frora the input, no fish died during the first
day of the experiment. All of the fish in this reach were alive at 0800
hrs of day 2 of the experiment. Fish in reach 5 started dying at 1000 hrs
and were all dead within an hour.
Bluegills were collected just after death in reach 1 and alive from
reach 5 after 4 h exposure. Fish were also collected from reach 5 at 0800
hrs on day 2 (24 h after anthracene infusion was initiated), which was
prior to any observed mortality. The tojLal anthracene concentrations in
fish in reach 1 after 4 h was 2389, ng'g" , wet weight (SD = 275, n = 3).
Anthracene concentrations in reach five were 457 (SD = 182, n = 3) and 7763
(SD = 1325, n = 3) after 4 and 24 h exposure, respectively. Subsequent
•studies showed that the mortality was not due to the ethanol carrier.
From the anthracene concentrations measured at the times when fish
died, we suspected a photo-induced mortality of anthracene contaminated
fish. To try and elucidate this possibility we considered several experi-
ments. A brief description of the design as well as the results and dis-
cussion of each experiment are given in this section.
Initially, we repeated the anthracene exposure to determine if the
mortality observed during the channels microcosms study could be repeated
(Figure 6.6.1). Again all of the fish in both reaches were killed. The
onset of mortality was more rapid in reach 1 than in reach 5, as in the
first biotic channels microcosm experiment. However, in this second study
of fish mortality, which was conducted on 8-10 January, the mortality was
less rapid than in the first experiment. Also, the solar radiation was
less during the second experiment, due to pertly cloudy skies.
A second study was conducted to determine if the mortality observed
was due directly to light on the fish or indirectly frora a photo-product.
In this study fish in reaches 1 and 5 were shaded so there was no sunlight
and one reach (reach 3) which was between then was unshaded. In reaches 1
and 5, which were shaded, only 1 mortality was observed (Figure 6.6.2).
However, in reach 3, which was not shaded, all of the fish died between
0800 and 1800 hra of the second day of the experiment. These results
202
-------
a:
o
Reach
16
12
8
4
P'D'ARK
FDARK~~TI
UJ
_J
ID
O
16
12
8
Reach 5
E5
r
246 12 24 36 48 60 72
HOURS OF ANTHRACENE EXPOSURE
Figure 6.6.1. Ct:mi't ;il ivtj aiort.i 1 i ly of blurpill sin\finh in the ch.iiiiicls
microcor;m. Moan il.iwn anllir.iccne conconLr.it ions were 12
I'R-S. . Two cajjcs .it e.ich n-.icli with 8 fish |>cr capo. Time
is Riven ,TS cumulative i-xpopurc to .inlhraccnc. i'crioitr. of
lit;ht .infl d.irk nro gjvrn. * donolor. time at which all fish
were
203
-------
Reach
10
8
6
4
2
a:
o
ui
IV. DARK
16
12
e
4
24 6 12
Reach 5
Shaded
L.:. DARK
24 36
Shaded
48
60
72
{eocn o unsnoc
3
! X^
Tea
-------
support the hypothesis that the mortality observed was an anthracene-light
mortality.
In another experiment fish were dosed for 72 h in the dark (reaches 1
and 5) and in the light reach 3 (Figure 6.6.2). After 72 h of dosing at
0800 hrs the anthracene input was terminated and the fish which had been
shaded (reaches 1 and 5) were unshaded at 1000 hrs.
All of the fish which had been dosed in the unshaded reach 3 were dead
at the end of the 72 h dosing period. One fish had died in both reach 1
and 5 after the 72 h dosing period. Upon being exposed to light after
accumulating anthracene, all of the fish in reaches 1 and 5 died within 24
h (Figure 6.6.3). These results suggest that the mode of action is by
anthracene or an anthracene transformation product in the organisms since
we allowed a washout period to remove anthracene from the water coluran
prior to removing the shading.
An additional experiment was conducted to determine the tiate necessary
for fish held in clean water to depuratt photoactive contaminants. Caged
fish were dosed continuously for 48 h with anthracene (14.6 Mg-£~ ) at the
shaded 9 meter station. The anthracene infusion was stopped and fish were
transferred from the shaded 4ia station, after 24, 48, 72, 96 and 144 h of
depuration in shaded, unconf aminated water (eight fish) to an unshaded,
uacontaminated section.
After 48 h of exposure whole fish had attained an average anthracene
concentration of 318 Mg'g' , dry weight (n = 8, SD = 79). No fish had died
during dosing in the dark.
The first group was removed from the dark at 08CO (following 24 h
depuration in the dark). The mean anthracene concentration in whole fish
was 47.3 Mg'g" , dry weight (n = 6, SD = 18.9). All of these fish were
dead by 1500 h (7 h exposure to light) (Figure 6.6.4).
Fish which were allowed 48 h_pf depuretion in the dark had a mean
anthracene concentration 36.0 Mg'g" (« = 5, SD = 28.3) dry weight. The
mortality of fish in this group was less than those which had been allowed
only 24 h of depuration in the dark before exposure to light (Figure
6.6.4). After 48 h four of the eight fish were still alive. The fish
which were allowed 72 and 96 h of depuration in the dark exhibited rates of
mortality, which were similar to that observed tor fish which were allowed
to depurate for 48 h. After 72. h of depuration the anthracene concentra-
tion had decreased to 73 Mg'g • dry weight (SD = 37). After 144 h the
concentrations were not different from those in control fish. Some of
these fish were able to survive in sunlight and reduce the concentration of
anthracene in their bodies until they were undetectable. We observed no
mortality in fish which had been allowed to depurate until their whole body
concentrations had decreased to background (Figure 6.6.4).
The rapid depuration of anthracene from fish, which we observed, is
consistent with those reported for many different fish species and PAH (Lee
et a_l. , 1972; RoubaJ e^ a^. , 1978). Elimination mechanisms reported for
205
-------
16
12
8
> 4
O |6
12
Reach I
Shaded during anthracene dosing.
-i—i—r—
246
12
~T
24
36
Reoch 3
Unshaded during anthracene dosing.
All fish were dead at the end of
the anthracene dosing period.
Reach 5
Shaded during anthracene dosing.
246 iT~~ 24 36
HOURS AFTER DOSING WAS TERMINATED
Fic
6.6.3. Cmuul.-iLivc mortality of bliicnill r.untish after 72 he of
rxposiiro to .nithr.icrnc in sh.nli'd or itnsh.idrd readies. After
72 hi- of antlu-ici-nc dosing, .mtlir-icrnc inputs wero stoppoil
and fish oxpni.cd to lij;lit.
206
-------
0800 hr.
O
' 1 1 i ' i ii_
24 h
;iDA_FU<_^ KOARK :., ]
L ' ' 1 1 J J-l 1 1 1 1 •• 1 1 1 1 1 1 . t 1 1 . 1 1 1 1 1 1 1 ! 1 1 1 1 I I.
•^ 24 36 46
r Depurotion
JLATIVE MORT/
e
4
0
8
4
0
: 48 hr.
/~^~
/-"
T r— i j , 1 1
•72 hr.
^ /
96 hr.
O^r—r
8
4
n
: 144 hr. "
- • . . — A/ n F" i r A /7 / yr fi ...... ..
I 4 8 12 24 36
HOURS AFTER FISH
WERE PLACED IN UNSHADED
REACH OF CHANNEL
48
Figure 6.6.4. Cumul.it ive mortal i ty of bluer.! 11 sunfish as a function of
time. Fish wore rxpoard to 1A.6 \>% anlliraccno • £ for ^8 h
in the .lark. Sets of 8 fish wero allowed to depurate- into
cK-.in w.itcr for 2'«, AS, 72, 9C and 144 li then pl.icrd in
clean w.itcr in llic li^.tit. E.ich not of fish were placed in
the lir.lil- at 0800 lirs and obr.orvcd for 48 h.
207
-------
fish include partitioning of PAH into clean water as well as active- bio-
transfonnation and excretion (Neeley et al., 1974; Melancon and Lech,
1"79} . — —
The mechanism of anthracene phototoxicity is unknown, but can be
postulated to involve photooxidation of anthracene to form toxic products
wxthin fish or, more likely, to involve sensitized photooxidation of macro-
molecules binding anthracene. The oxidative photo-chemistry of anthracene
has been well studied. Solution phase formation of endoperoxides by sing-
let oxygen as well as further oxidation to anthraquinone has been reported
(Foote, 1968). Anthracene derived fluorescent dyes, used as environmental
probes of protein structure, cause photooxidation of histidine and other
amino acid residues (Harrington et ajl., 1956).
Photooxidation in the presence of sensitizing dyes has been reported
to cause cell death, in vitro and in vivo damage to nucleic acids, enzyme
inactivation and degradation of proteins and carbohydrates (Means and
Feeney, 1971; Spikes, 1977). Light is also known to increase fish activity
lev-Is and trigger many complex physiological processes which could contri-
bute indirectly to mortality under stress conditions of anthracene contami-
nation.
Phototoxicity effects may be widespread among PAH. Death of £. Coli
due to photodynamic action of benzo(a)pyrene in the presence of oxygen has
been reported (Harrison and Raabe, 1967). Mutagenic and potentially toxic
photoproducts have been farmed from fuel oil exposed to sunlight (Larson et
al., 1977) and on PAH contaminated atmospheric particulate matter (Fox and
Oliver, 1981). While many PAH are known to be photolabile, to our know-
ledge phototoxic effects in aquatic biota have not been reported previous-
ly. Tests of phototoxicity should be included in protocols for risk as-
sessment of compounds known to be photclabile. The common practice of
studying PAH fate and effects under laboratory conditions which minimize
photo-degradation should be re-examined until additional studies determine
the potential ecological significance of PAH phototoxicity in aquatic
biota.
208
-------
APPENDIX I
Open literature publications containing information collected during
this study are given below.
1. Bartell, S. M., P. F. Landrum, J. P. Giesy, and G. J. Leversee. 1981.
Simulated transport of polycyclic aromatic hydrocarbons in artificial
streams. in: Energy and Ecological Modeling Mitsch, W. J., R. W.
Bosserman and J. H. Klopatek (eds.), Elsevier, N. Y. 839 p.
2. Leversee, G.* J., J. P. Giesy, P. F. Landrum, S. Gerould, J. W. Bow-
ling, T. E. Fannin, J. D. Haddock, and S. H. Bartell. 1981. Kinetics
and Biotransformation of Benzo(a)Pyrene in Chironomous riparius.
Arch. Environ. Contain. Toxicol. 11:25-31.
3. Leversee, G. J., J. P. Giesy, P. F. Landrum, S. Gerould, M. Bruno, A.
Spacie, S. Bartell, J. Bowling, J. Haddock, and T. Fannin. 1981b.
Disposition of benzo(a)pyrene in aquatic systems components: periphy-
ton, chironomids, fish. pp. 357-366. In: Chemical Analysis and Bio-
logical Fate: Polynuclear Aromatic Hydrocarbons. M. Cooke and A. J.
Dennis (eds.), Battelle Press, Columbus, Ohio.
4. Landrum, P. F. and J. P. Giesy. 1981. Anomolous Breakthrough of
Benzo(a)pyrene During Concentration with Amberlite XAD-4 from Aqueous
Solutions. Chapter 22 in: Advances in the Identification and Analy-
sis of Organic Pollutants in Water, L. H. Keith (ed.), pp. 345-355,
Ann Arbor Science, Ann Arbor, Michigan.
5. Gerould, S., P. F. Landrua and J. P. Giesy. 1982. Anthracene biocon-
centration and biotransforniation in chironomids: Effects of tempera-
ture and concentration. Environ. Poll, (in press).
6. Bruno, M. G., T. E. Fannin and G. J. Leversee. 1982. The disposition
of benzo(a)pyrene in the periphyton communities of two South Carolina
streams. Can. J. Bot. (in press).
7. J. W. Bowling, G. J. Leversee, P. F. Landrura and J. P. Giesy. 1982.
Photo-induced Toxicity in Anthracene Contaminated Fish Exposed to
Sunlight. Aquatic Toxicol. (in press).
8. Leversee, G. J., P. F. Landrum, J. P. Giesy, and T. Fannin. 1982.
Effect of Humics on Polycyclic Aromatic Hydrocarbons: Accumulation by
Daphnia magna and Coprecipitation at Estuarine Salinities. Can. J.
Fish. Aquat. Scl. (submitted).
209
-------
9. Spacie, A., P. p. Landrum and G. J. Leversee. 1982. Uptake, Depura-
tion and Biotransformation of Anthracene and Benzo(a)pyrene in Blue-
gill Sunfish. Ecotox. Environ. Safety. (In Press).
210
-------
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