EPA/600/4-85/040
WASTOX, A FRAMEWORK FOR MODELING THE FATE OF
TOXIC CHEMICALS IN AQUATIC ENVIRONMENTS
PART 2: FOOD CHAIN
by
John P. Connolly
Robert V. Thomann
Environmental Engineering & Science
Manhattan College
Bronx, N.Y. 10471
Project Officers
Parmely H. Pritchard
Environmental Research Laboratory
Gulf Breeze, Florida 32561
Cooperative Agreement No. R807827
William L. Richardson
Large Lakes Research Station-Grosse Ille, MI
Environmental Research Laboratory
Duluth, Minnesota 55804
Cooperative Agreement No. R807853
ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
GULF BREEZE, FL 32561
AND
DULUTH, MN 55804
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Disclaimer
The information in this document has been funded wholly or in part
by the U.S. Environmental Protection Agency under Cooperative Agreements
R807827 and R807853 to J.P. Connolly of the Department of Environmental
Engineering and Science, Manhattan College, the Bronx, New York. It has
been subjected to Agency review and approved for publication. Mention of
trade names or commercial products does not constitute endorsement or
recommendation for use.
OCT I 51991
ii
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FOREWORD
The protection of estuarine and freshwater ecosystems from damage
caused by toxic organic pollutants requires that regulations restricting
the introduction of these compounds into the environment be formulated on
a sound scientific basis. Accurate information describing the potential
exposure of indigenous organisms and their communities to these toxic
chemicals under varying conditions is required. The Environmental Research
Laboratory, Gulf Breeze, contributes to this information through research
programs aimed at determining:
• the effects of toxic organic pollutants on individual species,
communities of organisms, and ecosystem processes.
• the fate and transport of toxic organics in the ecosystem.
• the application of methodologies which integrate fate and effects
information to predict environmental hazard.
The magnitude and significance of chemical contamination of aquatic
environments are increasingly evident. The potential persistence and
possible accumulation of those chemicals in aquatic food chains means
that the impact on the health and activities of man is more direct.
Therefore, the ability to predict exposure concentration, bioaccumulation,
and chronic toxicity is critical to our efforts in hazard assessment.
Mathematical models provide a basis for quantifying the inter-relationships
among the various physical, chemical, and biological variables that affect
fate, transport, and bioaccumulation of toxic chemicals. Such models
also provide a mechanism for extrapolating laboratory information to the
environment and a rationale and conceptually relevant basis for decision
making.
This report presents the mathematical framework of a generalized
model to estimate the uptake and elimination of toxic chemicals by aquatic
organisms. The model is part of a broader framework called WASTOX which
was supported by our EPA laboratories in Gulf Breeze, FL, and Duluth, MN.
It provides a means of modeling the fate of toxic chemicals in natural
water systems including fate due to food chain bioaccumulation. Part 1, a
user's guide for WASTOX (EPA-600/3-84-077) was published in August 1984.
Part 2 explains the use of the food chain component of WASTOX.
Henry F. Enos
Director
Environmental Research Laboratory
Gulf Breeze, Florida
N.A. Jaworski
Director
Environmental Research Laboratory
Duluth, Minnesota
iii
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PREFACE
WASTOX is a batch oriented computer program that solves the mass
balance equations that define the fate of toxic chemicals in aquatic
systems. This report documents the food chain component of the program
which analyzes the uptake and elimination of chemicals by aquatic organ-
isms. The exposure concentration component of the program which analyzes
the time-variable or steady-state, physical-chemical behavior of chemi-
cals is documented in a separate report (1). The model is generally
applicable to all types of water bodies.
WASTOX was developed under cooperative agreements with the Environ-
mental Research Laboratory, Gulf Breeze, Florida (CR807827) and the Large
Lakes Research Station of the Environmental Research Laboratory, Duluth,
Minnesota (CR807853). Application of the program to estuaries and to
lakes is being conducted through the Gulf Breeze and Duluth cooperative
agreements, respectively.
iv
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CONTENTS
Page
Foreword ill
Preface iv
Figures vi
Tables vii
Abstract viii
Acknowledgements ix
1. Introduction 1
2. Fundamental Equations 3
3. Modeling Framework
3.1 Approach 8
3.2 Application 9
4. Structure of Computer Code
4.1 Overview 12
4.2 Subroutines 12
5. Preparation of Data Input
5 .1 Introduction 15
5.2 Card Group A - Number of Species 15
5.3 Card Group B - Compound Related Parameters 16
5.4 Card Group C - Steady-State Species Parameters 16
5.5 Card Group D - Age Dependent Species Parameters 17
5.6 Card Group E - Migrating Species Parameters 19
5.7 Card Group F - Setup of Spatial Compartments 20
5.8 Card Group G - Integration Information 24
5.9 Card Group H - Exposure Concentrations 24
6. Example Applications
6.1 PCB in the Lake Michigan Lake Trout Food Chain 26
6.2 Kepone in the James River Striped Bass Food Chain 27
7. Operational Considerations
7 .1 Acquisition Procedures 35
7.2 Installation Procedures 35
7 .3 Testing Procedures 35
7.4 Machine Limitations 36
References 37
Appendix 1 - Glossary
Appendix 2 - Test Program Input and Output
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FIGURES
Number Page
1 Flow diagram for the model 13
2 Comparison between observed and calculated PCS concen-
trations in alewife and lake trout 28
3 Kepone concentrations observed in the lower James River
estuary (0-60 km) and the values used in the model for
a) the water column, and b) the surface sediment 32
4 Comparison between observed and calculated Kepone con-
centrations in white perch, atlantic croaker, and
striped bass 34
vi
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TABLES
Number Page
1 Input requirements for each species included in the food
chain model 11
2 Parameter values used for the Lake Michigan lake trout
food chain study 29
3 Parameter values, used for the James River striped bass
food chain study 33
Al Test program input parameters 43
vii
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ABSTRACT
This report describes a mathematical modeling framework for the ana-
lysis of toxic chemicals in aquatic biota. This framework is part of a
broader framework for modeling the fate of toxic chemicals in natural
water systems, entitled WASTOX, an acronym for Water quality Analysis
Simulation for TOXics. WASTOX is composed of an exposure concentration
component which computes the time-variable or steady-state concentrations
of a toxic chemical in the water column and bed of a natural water system
as well as the food chain component described in this report.
The food chain component is a generalized model of the uptake and
elimination of toxic chemicals by aquatic organisms. It is a mass bal-
ance calculation in which the rates of uptake and elimination are related
to the bioenergetic parameters of the species. A linear food chain or a
food web may be specified. Concentrations are calculated as a function
of time and age for each species included. Exposure to the toxic chemi-
cal in food is based on a consumption rate and predator-prey relation-
ships that are specified as a function of age. Exposure to the toxic
chemical in water is functionally related to the respiration rate.
Steady-state concentrations may also be calculated.
The concentrations of toxic chemical to which the food chain is ex-
posed may be specified by the user of the model or may be taken directly
from the values calculated by the exposure concentration component of
WASTOX. Thus the food chain component may be executed as a separate
model or as a post-processor to the exposure concentration component.
Migratory species, as well as non-migratory species, may be considered.
Separate non-migratory food chains may be specified and the migratory
species is exposed sequentially to each based on its seasonal movements.
The model may be applied to any type of natural water system. It
has been successfully used to model PCB in the Lake Michigan lake trout
food chain and the Saginaw Bay, Lake Huron yellow perch food chain, and
Kepone in the James River striped bass food chain.
viii
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ACKNOWLEDGEMENTS
The assistance of Rosella Tonelli in testing and applying a myriad
of preliminary versions of this framework and the programming assistance
of Paul Rontonini are greatly appreciated.
The support of the project officers involved in the food chain
research of which this work is a result; Parmely H. Pritchard and William
L. Richardson, was an important contribution to its successful comple-
tion.
The many and significant contributions of our colleagues at
Manhattan College; Dominic M. Di Toro, Donald J. O'Connor, and Richard
P. Winfield, are gratefully acknowledged.
Finally, we would like to thank Eileen Lutomski and Margaret
Cafarella who patiently and accurately typed this report. Their contri-
bution is greatly appreciated.
ix
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SECTION 1
INTRODUCTION
The hazard posed to a natural water system by a toxic chemical is
governed by the uptake of the chemical by the resident biota and subse-
quent acute and chronic health effects. Evaluation of the hazard in-
volves three steps proceeding from the specification of the rate of chem-
ical discharge to the system:
1) estimation of the chemical concentrations in the water and sed-
iment
2) estimation of the rate of uptake of chemical by segments of the
resident biota
3) estimation of the toxicity resulting from uptake of the chemical
Execution of each step in this hazard assessment requires considera-
tion of the transport, transfer, and reaction of the chemical and the
dependence of these processes on properties of the affected natural water
system and its biota. Based on experimentation and theoretical develop-
ment each process has been, or can be, described mathematically, specify-
ing its functional dependence on specific properties. These expressions
may be combined using the principle of conservation of mass to form a
mathematical model that addresses one of the steps in the hazard assess-
ment.
Steps 1 and 2 of this hazard assessment are addressed by the general
modeling framework entitled WASTOX, an acronym for Water quality Analysis
Simulation for TOXics. This modeling framework is composed of two parts
which may be termed the exposure concentration and food chain components,
respectively. The exposure concentration component of WASTOX is the com-
putational structure for applying step 1 to a specific natural water sys-
tem. The food chain component of WASTOX is the computational structure
for applying step 2 to a specific natural water system.
The purpose of this report is to describe the theoretical basis,
structure, and use of the food chain component. The exposure concentra-
-------
tion component is described in a separate report (1). Both components
of WASTOX were developed as part of projects to determine the fate of
toxic chemicals in estuaries (CR807827) and the Great Lakes (CR807853).
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SECTION 2
FUNDAMENTAL EQUATIONS
The concentration of a toxic substance that is observed in an
aquatic organism is the result of several uptake and loss processes that
include: transfer across the gills, surface sorption, ingestion of con-
taminated food, desorption, metabolism, excretion and growth. These pro-
cesses are controlled by the bioenergetics of the organism and the chemi-
cal and physical characteristics of the toxic substance. The equations
used to describe these processes were formulated and applied for a single
species by Norstrom, et al. (2) and Weininger (3) and for an entire food
chain by Thomann (4) and Thomann and Connolly (5).
For phytoplankton and detrital organic material representative of
the base of the food chain, sorption-desorption controls toxic substance
accumulation and the change in the concentration, v (yg/g(w)) may be
written as:
dv
-rr- = k c, - K v (1)
dt uo d o o v '
in which k is the rate of uptake directly from the water or the sorp-
tion rate (£/d-g(w)), cd is the concentration of dissolved toxicant
(yg/£). KQ is the loss rate or desorption rate (d~ ), and t is time (d).
Because the sorption rates are generally much faster than the uptake and
excretion rates of higher levels of the food chain and the transport and
transformation rates of the toxic substance, instantaneous equilibrium
may be assumed. Equation (1) then reduces to:
Vo - Vd (2>
in which NQ, the bioconcentration factor, is the ratio of the uptake to
the loss rate.
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For species above the phytoplankton/detritus level, uptake of toxi-
cant due to ingestion of contaminated food must be considered. This
uptake will depend on a) toxicant concentration in the food, b) rate of
consumption of food, and c) the degree to which the ingested toxicant in
the food is actually assimilated into the tissues.
The rate of consumption of food, C, (g/g-d) is dependent on meta-
bolic requirements and growth rate. It may be written as:
(3)
in which R is the respiration rate (g/g-d) , G is the growth rate (d ) ,
and a is the fraction of ingested food that is assimilated.
The uptake of toxicant from water by these species, k is determined
by the rate of transfer of toxicant across the gills. This rate of trans-
fer can be calculated from the rate of transfer of oxygen from water to
the blood of the fish.
The rate of mass transport of a substance by passive diffusion
across the gills is given by:
(4)
where M is the mass transport [pg/d] , D is the dif fusivity of the sub-
2
stance [cm /s] , 6 is the effective thickness of the gill [cm], and a
w
and a, are the activities of the substance in the water and blood,
respectively [yg/fc]. If the activity of the chemical in water is
assumed to be equal to its concentration, c, and the transport across
the gill from blood to water is parameterized into a whole body
excretion term, equation (4) may be reduced to:
„ DA fC.^
M = — c (5)
If it is assumed that the mechanism for uptake of the chemical is iden-
tical to oxygen uptake then:
-------
..- (6)
\ \\
where the subscripts C and C>2 are for the chemical and dissolved oxygen
respectively. From (6),
M°2
Mc = (B ^) c
c Co c
where g = D /D_9, the ratio of the diffusivity of the chemical to that
\*t \J L.
of oxygen. From (7) ,
where
ku
The quantity k' represents the mass uptake for the whole fish and
has units, A/d. Dividing k' by the fish weight gives the uptake rate
per unit weight, i.e.
k- w
The quantity MQ /w is the respiration rate, r, of the fish, i.e.
r = MO /w
where r has units [g02/g(w) - d] . The uptake rate for the chemical is
therefore related to the respiration rate of the organism by:
(11)
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The rate of loss of the toxicant from an organism is the sum of the
excretion and detoxification or degradation rates of the chemical. If
the organism is exposed to the toxicant in water only, this rate is re-
lated to the uptake rate by the bioconcentration factor, N, as specified
by Eq. (2). Assuming no significant weight change during the bioconcen-
tration test, the loss rate, K, may be written as:
This rate incorporates several excretory processes including renal and
hepatic excretion, diffusion from blood across the gill and diffusion
from blood across the gut wall. The relative importance of each of
these processes will vary depending on the metabolic rate of the animal,
the route of exposure to the chemical and the characteristics of the
chemical. Although the use of a single rate effectively lumps para-
meters from more fundamental processes, it is the only approach that is
empirically justifiable given the current state of knowledge.
In the model the excretion rate may be internally calculated from a
specified bioconcentration factor, as given by eq. 12 or it may be
specified directly. If it is specified directly the equivalent biocon-
centration factor will decrease during an age class. The uptake rate
decreases as a function of weight because the respiration is dependent
on weight (see eq. 17). If the excretion rate is constant for an age
class the result is a decreasing bioconcentration factor.
Combining the above uptake and loss rates, the general mass balance
equation for the whole body burden, v'(yg), may be written as:
~- = k we, + aCwv - KV (13)
dt u d p
in which w is the weight of the organism (g(w)), a is the fraction of in-
gested toxicant that is assimilated, and v is the toxicant concentration
in the prey (ug/g(w)). Because the whole body burden is the product of
the toxicant concentration and weight of the organism, the derivative in
Eq. (13) may be written and expanded as:
-------
dv' d(vw) dw dv
-; = , ' = V -r- + w TT
dt dt - * dt ' ' dt (14)
Equation (13) may then be rewritten in terms of toxicant concentration
as:
^- = k c. + ctCv - k'v (15)
dt u d p
where:
f^rj
k' = K + §^/w = K + G
at
and G is the growth rate of the organism (g/g/d).
The growth rate term in Eq. (15) accounts for the dilution of toxi-
cant caused by the increase in weight of the organism.
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SECTION 3
MODELING FRAMEWORK
3.1 APPROACH
The analysis of toxic chemicals in aquatic food chains using Eq.
(2) for phytoplankton and detrital organic material and Eq. (15) for
higher trophic level species requires the bioenergetic and chemical re-
lated parameters included in Eqs. (3), (11) and (12). In addition, the
variation of these parameters with age and the feeding habits of each
species modeled must be known.
Feeding habits are generally discontinuous functions of age The
prey size or prey species generallly change as an organism grows. Thus, Eq. (15)
may not be solved continuously over the life span of an organism. In-
stead the life span is separated into age classes over which the pred-
ator-prey relationships are assumed to be constant. Eq. (15) is then
applied to each age class with the term representing uptake through
feeding expanded to allow more than one prey for each predator age class.
The use of age classes also provides a convenient mechanism for
computing concentrations in all life stages simultaneously, rather than
the Lagrangian approach of following a single organism that results from
the direct solution of Eq. (15). The criteria for age class size is the
birth frequency of the organism, thus restarting the first age class of
an organism at the proper interval.
Species at the lower end of the food chain tend to exhibit a concen-
tration of chemical that does not vary with age. Their relatively rapid
uptake and excretion rates and the lack of a major diet change with age
cause them to achieve equilibrium with the chemical in a short time rel-
ative to their life span. This fact justifies the use of an equilibrium
or steady-state modeling approach for these species. The equation defin-
ing the equilibrium concentration is obtained from equation (15) by
assuming the uptake and loss rates are constant and setting the deriva-
tive, dv/dt to zero:
-------
+ aCv
E. (16)
K'
The use of equation (16) for appropriate species reduces the compu-
tation time of the model.
3.2 APPLICATION
Use of the model requires the determination of an appropriate food
chain for the natural water system being considered and the specification
of a number of bioenergetic and toxic chemical related parameters for
each member of the food chain. In general the top component of the food
chain is chosen first. The feeding habits of this species define addi-
tional species whose feeding habits, in turn, define still further spe-
cies until the base of the food chain is reached. Because most species
within a trophic level have similar growth and metabolic rates and carry
similar body burdens of the toxic chemical being studied, a first-cut
model may use a single species as representative of a class of species
at a given trophic level.
The specific parameter requirements for each species in the model
are listed in Table I. Growth rate may be obtained from the observed
weight-age relationship of the species. Respiration rate is derived
from laboratory studies of metabolic rate and its dependence on weight,
temperature, and activity level (swimming speed). Species for which a
steady-state concentration is appropriate require a single respiration
value representative of an average across age and its dependence on tem-
perature. Respiration is assumed to vary exponentially with tempera-
ture, T(°C), and the user must specify a coefficient, p(°C~ ), for each
species. Species for which concentration is calculated in time for sev-
eral age classes (i.e., age-dependent) also require specification of the
dependence of respiration on body weight and swimming speed. The rela-
tionship between respiration R(g/g/d), body weight W(g) and swimming
speed u(cm/s) is (6):
R = BWYepVU (17)
-------
where u = uW e*
Values for 3, y > P > v , u , 6 , and must be specified by the user.
The value of y is generally believed to be constant across species at a
value in the range of -0.2 to -0.3. The negative sign is inserted by the
model and the user should specify the absolute value of j. For salmonid
fish, Stewart (6) reported values of v(s/cm) ranging from 0.23 to 0.33
with a mean of 0.27, values of oj(cm/s) ranging from 9.7 to 12.4 with a
mean of 11, values of 6 ranging from 0.05 to 0.13 with a mean of 0.1,
values of p ranging from 0.055 to 0.086 with a mean of 0.067, and
<|)(0C~ ) constant at 0.0405.
To convert the respiration rate from units of g(w)/g(w)/d to the
units of g(02)/g(w)/d used in the uptake rate calculation (eq. 11); (1)
wet weight is converted to dry weight by a user supplied ratio, (2) dry
weight is converted to carbon assuming a carbon to dry weight ratio of
0.4, and (3) carbon is stoichiometrically converted to oxygen.
The assimilation efficiency of food is dependent on the type of
prey consumed as well as the consumption rate. As a general guide,
values for carnivores and herbivores may be assumed to range between 0.7
and 0.8 and 0.3 and 0.5, respectively. The chemical assimilation effi-
ciency and bioconcentration factor are estimated from laboratory tests
in which aquatic species are exposed to the chemical in food or water.
Bioconcentration factors are generally readily available. Excretion
rates have been measured for many chemicals and aquatic species. How-
ever, little information is available for the larger fish. The chemical
assimilation efficiency is difficult to determine and is rarely measured.
Available data suggest that for many chemicals the assimilation effi-
ciency is in the range of 0.5 to 0.9.
If migratory species are modeled then the spatial variability of
the toxic chemical and the seasonal movement of the species must be con-
sidered. This is accomplished through the use of "spatial compart-
ments." The water body or system is separated into compartments in
which the toxic chemical concentration is assumed to be constant. Non-
10
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migratory food chains are specified for each compartment reflecting the
predatorprey relationships in that region of the system. The migratory
species is exposed sequentially to each of these food chains in a pat-
tern reflective of its seasonal movement.
To facilitate interfacing the food chain model with the exposure
concentration component of WASTOX, the toxic chemical concentration in
each spatial compartment is computed as the arithmetic average of the
segments in the exposure concentration component that lie within the
spatial compartment. Water column and sediment segments are averaged
separately to provide concentrations for the pelagic and benthic
components of the food chain.
TABLE 1. Input requirements for each species included
in the food chain model
Bioenergetic Related Parameters:
growth rate
respiration rate
assimilation efficiency of food
predator-prey relationships
Toxic Chemical Related Parameters:
assimilation efficiency of chemical in food
molecular diffusivity of the toxic chemical
bioconcentration factor or whole body excre-
tion rate
11
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SECTION 4
STRUCTURE OF COMPUTER CODE
4.1 OVERVIEW
The food chain component of WASTOX is a general purpose computer
program for modeling the accumulation of toxic chemicals in any aquatic
food chain or food web. It is designed to be used as part of the overall
WASTOX model, although it may be used separately or as a post-processor
to other toxic chemical models.
Exposure concentrations can be inputted by the user or read from
disk files created by the exposure concentration component of WASTOX.
In both cases these concentrations are assumed to apply to segments of
the spatial compartments used in the food chain calculation. The segment
concentrations are averaged over the spatial compartment.
Chemical concentrations in the food chain are calculated at a user
specified integration interval and outputted at a user specified print
interval. The flow diagram for the model is shown in Fig. 1.
4.2 SUBROUTINES
FDCHAN
FDCHAN calls the input and computation subroutines. It prints
results at a user specified time interval.
FCINPT
FCINPT reads the input for the species and spatial compartments of
the model.
EXPOSE
EXPOSE reads the concentrations of dissolved and adsorbed chemical
for the segments that comprise the spatial compartments. This subroutine
is executed only if the food chain model is run separately from the expo-
sure concentration model.
12
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READ INPUT
YES
RUN
WITH EXP.
CONCENTRATION
COMPONENT
COMPUTE RATE
CONSTANTS FOR
EXCRETION.* UPTAKE
FROM WATER
COMPUTE RESPIRATION
AND CONSUMPTION
COMPUTE CONC. IN
EACH AGE CLASS
COMPUTE CONC.
IN EACH SPECIES
RUN
WITH EXP.
CONCENTRATION
COMPONENT
FINAL
TIME
REACHED
7
PRINT
CONCENTRATIONS
Figure 1. Flow diagram for the model
13
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FDCHN
FDCHN Is the main computation subroutine. It calls the other com-
putation subroutines and calculates the concentrations in each age-
dependent species. It also updates concentrations at the end of each
year to initialize the concentration in each age class for the next
year. Movement of migrating species between compartments is also per-
formed.
SSCONC
SSCONC calculates the concentration in each species specified to be
at steady-state.
KNETIC
KNETIC computes the rate constants for uptake from water and excre-
tion for each steady-state species and each age class of the age-depen-
dent species.
INTER?
INTER? reads chemical concentrations from the disk files set up by
the exposure concentration component of WASTOX and linearly interpolates
between the exposure concentration components print times to provide con-
centrations for each time step of the food chain calculation.
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SECTION 5
PREPARATION OF DATA INPUT
5.1 INTRODUCTION
Data input includes information about the chemical, the species,
and the spatial compartmentalization of the natural water system. The
structure of the input varies slightly depending on the inclusion of
benthic species and whether the model is run with or without the exposure
concentration component of WASTOX. If run with the exposure concentra-
tion component, the food chain component uses the concentrations out-
putted to disk by the exposure concentration component. Linear interpo-
lation is used to provide values between the outputting intervals. When
the food chain component is run alone the user must input the exposure
concentrations.
The input data should be structured as a card image file. The pro-
gram expects the input data file to have the name "WASTOX.INP". Output
is written to a file named "WASTOX.OUT". Depending on whether the food
chain component is executed with or without the exposure concentration
component, the input for the exposure concentration component must pre-
cede that for the food chain component. (See the exposure concentration
component documentation (Connolly and Winfield, 1983) for the necessary
additional input).
5.2 CARD GROUP A - NUMBER OF SPECIES
5.2.1 Number of Age-Dependent and Steady-State Species
5 10
NSP NSPSS
FORMAT(215)
15
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NSP - number of species for which concentrations are calculated
in relation to age.
NSPSS - number of species for which steady-state concentrations
are calculated.
(maximum number of species, i.e., NSP + NSPSS, equals 20)
5.3 CARD GROUP B - COMPOUND RELATED PARAMETERS
5.3.1 Compound Characteristics
10 20
KP _ DIFF
FORMAT (2F10.0)
KP - partition coefficient (bioconcentration factor) of
compound to plankton-detritus (ug/g *
w
2
DIFF - molecular diffusivity of compound (cm /s)
5.4 CARD GROUP C - STEADY-STATE SPECIES PARAMETERS
This card group is repeated NSPSS times; once for each steady
state species.
5.4.1 Identification
_ 5 _ 10 _ 22_
IFLG(I) IFLGl(I) TITLE
FORMAT (2 15, 3A4)
IFLG(I) - flag indicating that species I is either a pelagic or a
benthic species:
If IFLG(I) = 0, then species (I) is pelagic
If IFLG(I) = 1, then species (I) is benthic and
consumes only detritus.
IFLG(I) - flag indicating whether excretion rate for species I
will be entered or will be computed from a bioconcen-
tration factor
16
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If IFLGl(I) = 0, then a bioconcentration factor will be
entered
If IFLGl(I) = 1, then an excretion rate will be entered
TITLE - name of steady-state species.
5.4.2 Bioenergetic Parameters
10 20 30 40 50 60 7£
RESP(I) GROW(I) ASM(I) BCF(I) ASIM(I) FDRY(I) RHO(I)
FORMAT(8F10.0
RESP(I) - respiration rate of steady-state species I (g/g/day)
GROW(I) - growth rate of species I (d
ASM(I) - toxicant assimilation efficiency of species I
BCF(I) - bioconcentration factor of species I (yg/g * Pg/£)
or excretion rate (1/d) as specified in 5.4.1
ASIM(I) - food assimilation efficiency of species I
FDRY(I) - fraction dry weight of species I
RHO(I) - exponential coefficient for temperature dependence
of species I respiration.
5.5 CARD GROUP D - AGE DEPENDENT SPECIES PARAMETERS
This card group is repeated NSP times; once for each age dependent
species
5.5.1 Identification
5 10 22
IFLG(I) IFLGl(I) TITLE
FORMAT(215,3A4)
IFLG(I) - flag indicating that species I is either a pelagic or a
benthic species;
If IFLG(I) = 0, then species (I) is pelagic
If IFLG(I) = 1, then species (I) is benthic and
consumes only detritus
17
-------
NOTE: the current structure assumes that all benthic
species are steady-state. IFLG should always be
0.
IFLGl(I) - flag indicating whether excretion rate for species I
will be entered or will be computed from a bioconcen-
tration factor
If IFLGl(I) = 0, then a bioconcentration factor will be
entered
If IFLGl(I) = 1, then an excretion rate will be entered
TITLE - name of the age-dependent species
5.5.2 Bioenergetic Parameters
5 15 25 35 45 55 65_
NAC(I) ACS(I) ASM(I) BETA(I) GAMMA(I) ASIM(I) FT)RY(I)
FORMAT(15,6F10.0)
NAG(I) - number of age classes for age-dependent species I
ACS(I) - age class size of species I(d)
ASM(I) - toxicant assimilation efficiency of age-dependent
species I
BETA(I) - respiration coefficient for age-dependent species I
GAMMA(I) - respiration weight exponent for age-dependent species
I
ASIM(I) - food assimilation efficiency of age-dependent species
I
FDRY(I) - fraction dry weight of age-dependent species I
10 20 30 40 50
RHO(I) OMGA(I) DLTA(I) PHI(I) XNU(I)
FORMAT(5F10.0)
RHO(I) = exponential coefficient for temperature dependence of
species I respiration (°C )
OMGA(I) = swimming speed coefficient (cm/s) for age-dependent
species I
DLTA(I) = swimming speed weight exponent for age-dependent
species I
PHI(I) = exponential coefficient for temperature dependence of
species I swimming speed (°C )
XNU(I) = exponential coefficient for swimming speed (s/cm)
18
-------
5 L5
MFLG(I) SPBD(I)
FOKMAT(I5,F10.0)
MFLG(I) = flag indicating that this species is a continuation of
the last species inputted. Used when a species is
divided to separate non-migrating juveniles from
migrating adults:
If MFLG(I) = 0 then species I is a different species
than species 1-1
If MFLG(I) = 1 then species I is a continuation of
species 1-1
SPED(I) = numbers of Julian days after start of calculation to
the species birthdate.
10 20 30
WO(K) GROW(K) BCF(K)
FORMAT(3F10.0)
WO(K) - weight of age class K at beginning of run (g )
GROW(K) - growth rate of age class K
BCF(K) - bioconcentration factor of age class K (ug/g *
or excretion rate (1/d) as indicated by 5.5.1
This card is repeated NAC(I) times; once for each age-class of
species I
5.6 CARD GROUP E - MIGRATING SPECIES PARAMETERS
5.6.1 Numer of Migrating Species
NMIG
FORMAT(15)
NMIG - number of migrating species in model (maximum of 2)
19
-------
5.6.2 Identification and Migrating Pattern
Card group 5.6.2 is repeated NMIG times; once for each migrating
species
MIGSN(I)
FORMAT(15)
MIGSN(I) - species number of Ith migrating species
5 15 20 30 35 80^
NBRKS(I) TIMEM(I,J) COMPRT(I.J) TIMEM(I.J) COMPRT(I.J)
FORMAT(I5,5(F10.0,I5))
NBRKS(I) - number of breaks describing the migratory pattern
of the Ith migratory species.
TIMEM(I.J) - time of break J in the migratory pattern of the
Ith migratory species (d).
COMPRT(I,J) - spatial compartment occupied by the Ith migratory
species for the time up to TIMEM(I,J).
5.7 CARD GROUP F - SETUP OF SPATIAL COMPARTMENTS
5.7.1 Number of Compartments
NSC
FORMAT(15)
NSC - number of spatial compartments included in the model.
(Maximum = 12)
5.7.2 Compartment Characteristics
Card groups 5.7.2 through 5.7.4 are repeated NSC times; once for
each spatial compartment
a. Annual temperature profile
NBRKS2(I)
FORMAT(15)
20
-------
10 20 30 80
TIMET(I.J) TEMP(I,J TIMET(I.J) TIME(I.J)
FORMAT(SFIO.O)
NBRKS2(I) - number of breaks describing the annual temperature
cycle in spatial compartment I (maximum of 14)
TIMET(I.J) - time of break J in the temperature cycle in com-
partment I(d)
TEMP(I,J) - temperature at break J in the temperature cycle in
compartment I(°C)
b. Species in Compartment
NSPSI(I)
FORMAT(15)
NSPSI(I) - number of species above the plankton level in
compartment I
5.7.3 Characteristics of the Food Chain
Card group 5.7.3 is repeated NSPSI(I) times in each compartment
I: once for each species in the compartment
a. Species Number
SPNO(I,J)
FORMAT(15)
SPNO(I,J) - species number of the Jth species in compartment I.
If species J is age-dependent or pelagic and steady-state skip to
c.
b- Benthic Species Initial Concentration
10
CFC(I,J)
FORMAT(F10.0)
21
-------
CFC(I,J) = concentration of chemical in species J in compartment
I at the start of the calculation (yg/gw)
Skip to 5.7.4
c. Predator-Prey Relationships
i. Number of Prey
NPREY(I.J)
FORMAT(15)
NPREY(I,J) - number of prey of species or age class J in
compartment I. (maximum of 3)
ii. Consumption Split
5 15 20 30 7_5
PREY(I.J,L) PREF(I.J.L) PREY(1,J,L) PREF(I.J.L) ....
FORMAT(5(I5,F10.0))
PREY(I,J,L) - step number of the Lth prey of step J in
compartment I.
PREF(I,J,L) - fraction of step J's consumption that is
on its Lth prey in compartment I.
Note: Steps are counted for each compartment from the first
species above the plankton-detritus level and include
the steady-state species and each age class of age
dependent species.
For example, if a food chain consists of plankton, a
steady-state invertebrate, and an age-dependent fish
with 3 age classes the steps are as follows:
22
-------
Step
invertebrate 1
fish age 1 2
fish age 2 3
fish age 3 4
If fish age 2 preys on the invertebrate then for compartment
I PREY(I,3,1) = 1 and PREF(I,3,1) = 1.0.
d. Initial Concentration
10
CFC(I,J)
FORMAT(F10.0)
CFC(I,J) - concentration of chemical in steady-state species
or age-class J in compartment I at the start of
the calculation (pg/gw)
(Note; For each age-dependent species, (c) and (d) are
repeated for each class).
5.7.4 Interfacing Segments from Exposure Concentration Component With
the Spatial Compartments
a. Number of segments
10
NSEG(I).NBSEG(I)
FORMAT(215)
NSEG(I) - number of water column segments from exposure con-
centration model included in spatial compartment I.
NBSEG(I)- number of bed segments from exposure concentration
model included in spatial compartment I.
23
-------
10
SEGNO(I.l) SEGNO(I.2) ... SEGNO(I,NSEG(I))
FORMAT(16I5)
SEGNO(I,M) - segment number of the Mth water column segment
included in spatial compartment I.
5 10
BSEGNO(I,1) BSEGNO(I,2) ... BEGNO(I,NBSEG(I))
FORMAT(16I5)
BSEGNO(I.M) - segment number of the Mth sediment segment
included in spatial compartment I.
Note: if executing the food chain with the exposure concentration
component and it is desired to have a spatial compartment
with no toxicant set SEGNO to 0.
5.8 CARD GROUP G - INTEGRATION INFORMATION
5.8.1 Printing and Integration Information
10 20 30 40
DT TTIME PRNT T0
FORMAT(4F10.0)
DT - time step (d)
TTIME - total run time (d)
PRNT - print interval for outputting concentrations (d)
T0 - Julian date at beginning of run (typically 0 days)
5.9 CARD GROUP H - EXPOSURE CONCENTRATIONS
This card group read in only if the food chain component is
executed separately from the exposure concentration component
This card group is repeated for each segment specified in card
group 5.7.4 in sequence from segment 1 to segment N.
24
-------
5.9.1 Number of values describing the temporal distribution of
concentration
NCON
FORMAT(15)
NCON - number of values of concentrations to be inputted
5.9.2 Concentration Profile
8 16 24 32 40 48
DCON(L,1) PCON(L,1) TCON(L,1) DCON(L,2) PCON(L.2) TCON(Lt2)...
FORMAT(9F8.0)
DCON(L.M) - dissolved chemical concentration in segment L up to
time TCON(L.M) (wg/A)
PCON(L,M) - adsorbed chemical concentration in segment L up to
time TCON(L.M) (ug/A)
TCON(L.M) - time of concentration change in segment L (days)
(a maximum of 15 times may be specified)
25
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SECTION 6
EXAMPLE APPLICATIONS
6.1 PCB IN THE LAKE MICHIGAN LAKE TROUT FOOD CHAIN (5)
The accumulation of PCBs in the Lake Michigan food chain was
modeled assuming a four species food chain consisting of phytoplankton,
Mysis relicta, alewife (Alosa pseudoharengus) , and lake trout
(Salvelinus namaycush). This species linkage constitutes the major
energy transport route to the lake trout. Both Mysis and alewife were
viewed as representative species of the middle levels of the food chain
acknowledging that other invertebrates and small fish also contribute to
the observed PCB levels in lake trout. The phytoplankton component of
the model was assumed to represent nonliving particulate organic mater-
ial as well as living plankton.
Phytoplankton were represented by a single compartment that was
assumed to be in dynamic equilibrium with water column dissolved PCB.
The other species were separated into discrete age classes.
The food chain model was structured with four 4 month age classes
of Mysis reflecting life span and birth frequency. All classes consumed
phytoplankton exclusively. The alewife component was divided into 7
single year classes. The feeding structure reflected field observations
of stomach contents, young-of-the-year alewife consuming phytoplankton
and all other age classes consuming Mysis with a bias toward the larger
Mysis.
The lake trout component of the model was divided into 13 single-
year age classes. Reflecting stomach content, the first two age classes
consumed Mysis exclusively, the next class consumed Mysis and first and
second year alewife. Older trout consumed alewife exclusively, with an
age class distribution commensurate with the stomach content data. Move-
ment of the species was not considered and a single spatial compartment
representing the open waters of Lake Michigan was used.
26
-------
The final calibration was the result of a series of model runs that
determined a consistent set of parameter values that were in agreement
with observed values and reproduced the observed PCB concentrations in
Lake Michigan lake trout and alewife. Data for 1971 were used in the
calibration. A constant dissolved PCB concentration of 5 ng/ S, was
assumed. A constant value implies that the alewife and lake trout sam-
pled in 1971 were exposed to a constant PCB concentration for their
entire lives, which for the oldest trout represented is ten years. A
time variable dissolved PCB concentration was not used because no accur-
ate data history exists. The values assigned to the PCB assimilation
efficiency were adjusted to reproduce the observed PCB distribution.
This parameter was chosen as the calibration variable because of the un-
certainty of its value relative to the other parameters in the model.
The comparison between observed data and calculated PCB concentra-
tions in alewife and lake trout is shown in Fig. 2. The parameter values
used in the model are summarized in Table 2. The model reproduces the
observed data with the exception of the early age classes of lake trout.
No combination of parameters was successful at reproducing the high PCB
values in age class 2 and 3 lake trout while maintaining consistency with
reported parameter values and reproducing the observed concentrations in
the upper age classes.
6.2 KEPONE IN THE JAMES RIVER STRIPED BASS FOOD CHAIN (7)
Accumulation of Kepone in the striped bass food chain was modeled
using four trophic levels. Phytoplankton-detritus is the base of the
food chain. The invertebrate level is represented by Neomysis and
Nereis, reflecting the importance of both pelagic and benthic species to
the higher levels. Atlantic croaker (Micropogan undalatus) and white
perch (Morone americana) are the fish species representing the level
immediately below the striped bass (Morone saxatilis) .
Phytoplankton-detritus, Neomysis, and Nereis were represented by
single compartments that are assumed to be in dynamic equilibrium with
27
-------
£
"3
15
10
5
0
CD
3
25
-------
TABLE 2. PARAMETER VALUES USED FOR THE LAKE MICHIGAN LAKE TROUT FOOD CHAIN STUDY
NJ
VO
Species
Phytoplankton
Mysis
0-4 mo.
4-8 mo.
8-12 mo.
12-16 mo.
Alewife
0-3 yrs.
4-6 yrs.
Lake Trout
0-1 yrs.
2-12 yrs.
Growth Respiration Swimming Speed
G
d
0.0193
0.0107
0.0073
0.0056
0.00245
0.00047
0.0058
0.0012
WO R BETA GAMMA RHO XNU OMGA DLTA PHI
ff 1 1 1
Bw d °C s/cm °C
- 0.0157 0.25 00 -
0.00021
0.0022
0.0081
0.0198
0.047 0.2 0 0 -
2.5
36.85
0.03 0.295 0 0.022 2.79 0.1285 0
2.2
153.6
BCF Food Toxicant Fraction
Assim. Assim. Dry
, Efficiency Efficiency Weight
a W
90 . , , n i
50 0.3 0.35 0.2
100 0.8 0.7 0.25
100 0.8 0.8 0.25
-------
Kepone in the water column and in their food. The white perch, the
atlantic croaker and the striped bass were separated into year classes.
Neomysis americana is a mysid shrimp of considerable importance in
the estuarine food chain linking organic detritus to fish. As a filter
feeder it collects detritus and algae during diurnal migrations between
the bed and the surface of the water column. In the model it was assumed
to feed on the phytoplankton-detritus level only.
Nereis is an errant polychaete generally found in estuarine environ-
ments and may be classified as a deposit-feeder. Sediment particulate
material was assumed to be the diet of Nereis in the model.
The atlantic croaker was divided into three single year classes.
The first age class consumed photoplankton, the second age class consumed
phytoplankton as well as Neomysis and Nereis, and the third age class
consumed only Neomysis and Nereis. All age classes were assumed to be
migratory entering the James River in March and leaving in October.
The white perch component of the model was divided into 10 single-
year age classes. The first age class consumed phytoplankton, the second
age class consumed phytoplankton and Neomysis, and the remaining age
class fed on Neomysis and Nereis.
Eleven single-year age classes of striped bass were considered in
the model. The first age class consumed phytoplankton, the next two con-
sumed Neomysis and Nereis, and the older bass consumed the age classes
of white perch and atlantic croaker consistent with observed prey size
distributions. The first three age classes were assumed to permanently
reside in the James River. Older striped bass were assumed to be migra-
tory and present in the river from November to May. During the period
from November to March when the atlantic croaker is not in the estuary
the adult striped bass were assumed to prey on white perch only.
Kepone concentrations in the water column, sediment and fish of the
James River have been monitored routinely by the Virginia State Water
Control Board (SWCB) since 1976. These data provide a seven-year time
30
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history against which the model was compared and tested. The observed
water column and sediment concentrations and the values used in the model
are shown in Fig. 3. Spatially constant values were assumed because no
consistent spatial gradient is evident from the data. During the portion
of the year that atlantic croaker and striped bass were outside the James
River they were assumed to be exposed to no Kepone. In the calibration
procedure the Kepone assimilation efficiency and excretion rate were ad-
justed within their range of observed values to provide the best compari-
son of observed and computed Kepone concentrations. The parameters used
in the model are shown in Table 3.
The comparisons between observed data and calculated Kepone concen-
trations in white perch, atlantic croaker, and striped bass are shown in
Fig. 4. The data and calculated values are averages over all age
classes. The model reproduces the observed within-year and year-to-year
concentration variations for all species. The oscillation in atlantic
croaker and striped bass concentrations reflects the migration of these
species between the James River and the uncontaminated Chesapeake Bay and
Atlantic Ocean.
31
-------
en
01
Z
o
a.
<
H
Ol
Z
O
Q.
0.08
0.06
0.04
0.02
0
0.20
0.16
0.12
0.08
0.04
0
A. WATER COLUMN
- <
-
i (
01
I
SSOL VED KEPONE
[/,,!
T~
I
•
<
t/3
<
»
ED IN MOC,
i
i
"I
, 1
?£L
i
T
— K
1 ,
>-..-- -
1
I •
MAXIMUM
MEDIAN I
BELOW LIMIT
OF DETECTION
o.:
<
33
I
0.
,
25
4
1
|
1
1
SEDIME
TIONS
1
i
a SEDI
vr KEPON
USED IN 7
/I
L /I
i
MENT (0-9 cm)
£ CONCENTRA-
'HE MODEL
1 _
1
LIMIT OF
DETECTION
LIMIT OF
DETECTION
1976
1977
1978
1979
YEAR
1980 1981
1982
Figure 3. Kepone concentrations observed in the lower
James River estuary (0-60 km) and the values
used in the model for a) the water column, and
b) the surface sediment
32
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TABLE 3. PARAMETERS USED IN THE JAMES RIVER STRIPED BASS FOOD CHAIN STUDY
Species
Phytoplankto:
Polychaete
Neomysis
Atlantic
Croaker
0-1 yr.
1-2 yr.
2-3 yr.
White Perch
0-2 yr.
2-5 yr.
5-9 yr.
Striped Bass
0-2 yr.
2-3 yr.
3-6 yr.
6-9 yr.
9-11 yr.
Growth
G
d~L
ti — ~— ~—
0.007
0.01
0.0114
0.0032
0.0026
0.004
0.0016
0.0007
0.0069
0.0026
0.0014
0.00087
0.00039
WO
gw
-
-
1.0
65.
210.
1.9
33.
140.
2.
312.
808.
3759.
9770.
Respiration Swimming Speed BCF Food Toxicant Fraction
R BETA GAMMA RHO XNU OMGA DLTA PHI Assim. Assim. Dry
. , Efficiency Efficiency Weight
d"1 "C"1 s/cm °C l */8w
& n i
0.02 0 - - - - 6 0.3 0.3 0.2
0.102 0 - - - - 6 0.3 0.3 0.2
0.038 0.2 0 0 - - - 6 0.8 0.72 0.25
0.038 0.2 0 0 - - - 6 0.8 0.8 0.25
0.069 0.3 0 0.0176 1.19 0.32 0.0405 10 0.8 0.9 0.25
-------
2.4
1.6
0.8
n
- •
* 4
1 V-l . 1
1 1 1
WHITE PERCH
•
£""• — T*"*^1 , i • .r
1976 1977 1978 1979 1980 1981
1982
o
CL.
1976 1977 1978 1979 1980 1981 1982
1976 1977 1978 1979 1980 1981 1982
YEAR
Figure k. Comparison of observed and calculated Kepone
concentrations in the atlantic croaker, white
perch, and striped bass.
34
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SECTION 7
OPERATIONAL CONSIDERATIONS
This chapter describes how to obtain the computer program WASTOX,
how to install it on a DEC PDF mini computer, how to test the program
with a sample dataset, and what machine limitations limit the program.
7.1 ACQUISITION PROCEDURES
To obtain the program WASTOX along with a sample dataset and support
software, write to:
Center for Water Quality Modeling
Environmental Research Laboratory
U.S. Environmental Protection Agency
College Station Road
Athens, GA 30613
A nine-track magnetic tape will be mailed to you. Please copy the con-
tents and return the tape.
7.2 INSTALLATION PROCEDURES
The subroutines that comprise WASTOX must be compiled and linked into
a task image. This is accomplished on the POP IAS operating system by
running the command file "WXTCMP.CTL." If the compilation succeeds, then
linkage is automatically attempted with the command file "WXTLNK.CTL."
7.3 TESTING PROCEDURES
Once WASTOX is installed, the sample input dataset should be run and
compared with the sample output dataset to verify that the program is
calculating correctly. To perform a simulation on the POP, submit the
batch input sequence "WXTRUN.CTL."
35
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7.4 MACHINE LIMITATIONS
Currently. WASTOX is set up for the following configuration:
PDF 11/70 Hardware
RSTS/E operating system
FORTRAN IV
Physico-chemical
component:
Food Chain component:
60 segments - steady-state
75 segments - time-variable
4 systems
20 species
10 species in any spatial compartment
2 migrating species
12 spatial compartments
10 physico-chemical model segments per
spatial compartment
150 age classes + steady-state species
30 age classes + steady-state species in
any spatial compartment
The PDP 11/70 computer utilizing RSTS/E operating system allocates a
32k word (64k byte) user area for execution of programs. WASTOX occupies
at least 31k words of memory. Any enlargement of this program may result
in an overflow of the user area.
36
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REFERENCES
(1) Connolly, J.P. and R.P- Winfield. 1984. User's guide for WASTOX,
a framework for modeling the fate of toxic chemical* in aquatic
, Part 1? Exposure concentration. EPA-600/3-84-077.
(2) Norstrom, R.J., A.E. McKinnon, and A.S.W. DeFreitas. 1976. A
bioenergetics based model for pollutant accumulation in fish:
Simulation of PCS and methyl mercury residue levels in Ottawa River
yellow perch (Perca Flavescens). J. Fish. Res. Board Can.
33:248-267.
(3) Weininger, D. 1978. Accumulation of PCBs by lake trout in.Lake
Michigan. Ph.D. Thesis, The University of Wisconsin-Madison, 232 p.
(4) Thomann, R.V. 1981. Equilibrium model of the fate of microcontami-
nants in diverse aquatic food chains. Can. J. Fish. Aquat. Sci.,
38(3):280-296.
(5) Thomann, R.V. and J.P. Connolly. 1983. A model of PCB in the Lake
Michigan lake trout food chain. Environ. Sci. Technol.
(6) Stewart, D.J. 1980. Salmonid Predators and their forage base in
Lake Michigan: A bioenergetics-modeling synthesis Ph.D. Thesis, The
University of Wisconsin-Madison. 225 p.
(7) Connolly, J.P. and R. Tonelli. 1985. A model of Kepone in the
striped bass food chain of the James River Estuary. Estuarine,
Coastal and Shelf Sci.
37
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APPENDIX 1
GLOSSARY
I. Variables in
ACS(I)
ASIM(I)
ASM(I)
BCF(I)
BETA(I)
BSEGNO(I.J) •
CFC(I.J)
CNSMP(I)
DIFF
DLTA(I)
DT
FDRY(I)
GAMMA(I)
GROW(I)
IFLG(I)
KP
MFLG(I)
NAC(I)
Common Block MAIN
• size in days of each age class of age-dependent
species I
• food assimilation efficiency of species I
• toxicant assimilation efficiency of species I
• toxicant bioconcentration factor for species I (£/gm)
• respiration coefficient for age-dependent species I
• number of the J segment from the exposure concentra-
tion component included in the benthic region of com-
partment I
• concentration of toxicant in the J step of the food
chain in compartment I(yg/g). Steps are counted from
the first species above the plankton-detritus level
and include the steady state species and each age
class of the age dependent species
• consumption rate of the I step of the food chain
(g/g/d)
2
• molecular diffusivity of the toxicant (cm /s)
• swimming speed weight exponent for age-dependent
species I
• time step for the calculation (d)
• dry weight to wet weight ratio for species I
• respiration weight exponent for age-dependent species
I
• growth rate for step I of the food chain (g/g/d)
• flag indicating that species I is either pelagic or
benthic
• phytoplankton-detritus bioconcentration factor (fc/g)
• flag specifying whether species I is a continuation
of species 1-1
• number of age classes for age dependent species I
38
-------
NBSEG(I)
NPREY(I.J)
NSC
NSEG
NSP
NSPI(I)
NSPSS
OMGA(I)
PHI (I)
PREF(I,J,L)
PREY(I,J,L)
PRNT
RESP(I)
RHO(I)
SEGNO (I, J)
SPED (I)
SPNO(I,J)
TIME
TTIME
TO
WO(I)
XNU(I)
- number of bed segments included in compartment I
- number of prey of the J step in compartment I
- number of spatial compartments in the model
- number of water column segments included in
compartment I
- number of age-dependent species in the model
- number of species in compartment I
- number of steady-state species in the model
- swimming speed coefficient for age-dependent species
I
- exponential coefficient for temperature dependence of
species I swimming speed (°C )
- fraction of the consumption rate of step J in compart-
ment I that is on step L
- step number of prey L for step J in compartment I
- outputting interval in days
- respiration rate of step I (g/g/d)
- exponential coefficient for temperature dependence of
species I respiration (°C )
- segment number of the J water column segment
included in spatial compartment I
- date of birth for species I (Julian days from start
of run)
- species number of the J species in compartment I
- current time during the run (d)
- final time of the run (d)
- Julian date at the start of the run
- current weight of age class I in the food chain
(counting from the first age-dependent species) (g )
V/€ L
- initial weight of age class I (g )
- exponential coefficient for swimming speed (s/cm)
II. Variables in Common Block INIT
COMPRT(I,J) - spatial compartment occupied by the I
species for time up to TIMEM(I.J)
th
migratory
39
-------
MIGSC(I)
MIGSN(I)
MINDX(J.I)
NBRKS(I)
NCNT(I)
NMIG
TIMEM(I.J)
- compartment currently occupied by the I migratory
species
- species number of the I migratory species
- step number for the first age class of migrating
species J when it is in compartment I
- number of breaks describing the migratory pattern of
the I migratory species
- counter for the migratory pattern arrays COMPRT and
TIMEM for the I migratory species
- number of migratory species in the model
- time of break J in the migratory pattern of the I
migratory species (d)
III. Variables in Common Block SYSTRN
ITCNT(I) - counter for the time variable temperature function
for spatial compartment I
NBRKS2(I) - number of time-temperature pairs defining the I
spatial compartments annual temperature cycle
TEMP(I,J) - temperature at break J in the temperature cycle of
compartment I (°C)
TIMET(I.J) - time of break J in the temperature cycle of
compartment I (d)
IV. Variables in Common Block PHOTO
DISTOX(I) - current dissolved toxicant concentration in segment I
PARTOX(I) - current adsorbed toxicant concentration in segment I
(yg/g)
V. Variables in Common Block JUNK
DCON(I,J) - dissolved toxicant concentration in segment I up to
time TCON(I.J) (pg/A)
MX(I) - counter for the concentration profile in segment I
PCON(I.J) - adsorbed chemical concentration in segment I up to
time TCON(I.J) (pg/g)
TCON(I.J) - time of the JC concentration change in segment I (d)
40
-------
VI. Variables in Common Block MAINA
IN - unit number assigned to the input file
ISYS - variable used in exposure concentration component of
WASTOX
IREC - record counter used in reading the time output file
of the exposure concentration component
IRECL(I) - record counter used in reading the output file of the
I system of the exposure concentration component
NOSEG - number of segments in the exposure concentration
component
NOSYS - number of systems in the exposure concentration
component
OUT - unit number assigned to the output file
SYSEX(I) - array used in the exposure concentration component
VII. Variables in Common Block OPTION
PRGOPT - programming option specifying whether the exposure
concentration component is run alone, the food chain
is run alone, or they are run together
TYPE - variable used in the exposure concentration component
to indicate a time variable or steady state run
VIII. Variables in Common Block DUMP
MXDMP - number of variables written to output for each system
in the exposure concentration component
MXSEG - maximum number of segments permitted in the exposure
concentration component (75)
IX. Variables in Common Block UPTAKE
02 - dissolved oxygen concentration (g/£)
DRATIO - ratio of the molecular diffusivity of oxygen to the
molecular diffusivity of the toxicant
41
-------
APPENDIX 2
TEST PROGRAM INPUT AND OUTPUT
To test that the computer code for the food chain component of
WASTOX is working correctly on the user's computer, a simple test food
chain problem is provided. Three species are considered; two steady
state and one age-dependent. The steady state species are a pelagic
invertebrate that consumes phytoplankton and a benthic invertebrate that
consumes detritus. The age-dependent species is a fish divided into 3
single-year age classes, all of which prey equally on the two inverte-
brate species. A single spatial compartment is considered. The para-
meters used in the model are shown in Table Al.
42
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TABLE Al. TEST PROGRAM INPUT PARAMETERS
Species Growth Respiration
G WO R BETA GAMMA RHO
d-l gw d-l oc-l
Phytoplankton — — — ^— — — — — ^— — ^— — — — — — — — — — — —
Pelagic
Invertebrate 0.01 - 0.102 - - 0.0
Benthic
Invertebrate 0.01 - 0.02 - - 0.0
Fish* - 0.038 0.2 0.0
0-1 yr. 0.007 1
1-2 yr. 0.003 12.96
2-3 yr. 0.001 38.86
*
Birth Date = 0.0
£ 9
Compound Diffusivity = 4.55 x 10 cm /s
Water Column Concentration =0.01 yg/&
Bed Dissolved Concentration = 0.14 yg/£
Bed Adsorbed Concentration = 0.277 yg/g
Water Temperature = 15°C
Swimming Speed BCF Food Toxicant Fraction
XNU OMGA DLTA PHI Assim. Assim. Dry
, ., Efficiency Efficiency Weight
s/cm "C"1 */8w
10 0 1
U.I
- - - 10 0.3 0.3 0.2
- - - 10 0.3 0.3 0.2
0.0176 11 0.1 0.045 10 0.8 0.8 0.25
-------
INPUT FILE
WASTOX.INP
2
1 2
10.
0 0
0.102
1 0
0.02
0 0
3 366.
0.0
0
1
12.96
38.86
0
1
1
9999.0
3
1
1
0 1.0
0.0
2
0.0
3
2
1
0.0
2
1
0.0
2
1
0.0
1 1
1
2
2.0
1
0.01
1
0.14
;17 4-JAN-1985 16:13 Page
.00000455
PLG INVT
0-01 0.3 10.0 0.3 0.2 0.0
BNTH INVT
0.01 0.3 10.0 0.3 0.2 00
FISH
0.8 0.038 0.2 0.8 0.25
11.0 0.1 0.0405 0.01
0.0
0.007 10.0
0.003 10.0
0.001 10.0
15.0
•
0.5 2 0.5
0.5 2 0.5
0.5 2 0.5
366.0 30.0 0.0
0.0 366.0
0.277 366.0
12345678901234567890123456789012345678901234567890123456789012345678901234567890
1 2345678
44
-------
OUTPUT FILE
WASTOX.OUT;! 4-JAN-1985 16:05 Page 1
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA**A*
FOOD CHAIN INPUT
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA**
1 AGE DEPENDENT SPECIES 2 STEADY STATE SPECIES
PLANKTON BCF 10.0 COMPOUND DIFFUSIVITY = 0.4550E-05
STEADY STATE SPECIES
SPECIES 1 PLG INVT
RESPIRATION RATE PER DAY 0.1020E+00
GROWTH RATE PER DAY = 0.1000E-01
TOXICANT ASSIMILATION EFF. 0.3000E+00
BIOCONCENTRATION FACTOR 0.1000E+02
FOOD ASSIMILATION EFF. 0.3000E+00
FRACTION DRY WEIGHT = 0.2000E+00
RESPIRATION TEMP COEF,RHO O.OOOOE+00
SPECIES 2 BNTH INVT
RESPIRATION RATE PER DAY 0.2000E-01
GROWTH RATE PER DAY = 0.1000E-01
TOXICANT ASSIMILATION EFF. 0.3000E+00
BIOCONCENTRATION FACTOR 0.1000E+02
FOOD ASSIMILATION EFF. 0.3000E+00
FRACTION DRY HEIGHT = 0.2000E+00
RESPIRATION TEMP COEF,RHO O.OOOOE+00
SPECIES 3 FISH
3 AGE CLASSES OF 366. DAYS EACH AND BIRTH O.DAYS AFTER START OF RUN
RESPIRATION COEFFICIENTS: BETA =0.3800E-01
GAMMA =0.2000E+00
RHO =O.OOOOE+00
OMGA =0.1100E+02
DLTA =0.1000E+00
PHI =0.4050E-01
XNU =0.1000E-01
FOOD ASSIMILATION EFF. O.SOOOE-t-00
FRACTION DRY HEIGHT 0.2500E+00
TOXICANT ASSIMILATION EFF. =0.8000E+00
45
-------
HASTOX.OUT;! 4-JAN-1985 16:05 Page 2
AGE CLASS INITIAL WT. (CM) GROWTH RATE (I/DAY) BIOCONCENTRATION FACTOR (L/C)
1 0.1000E+01 0.7000E-02 0.1000E+02
2 0.1296E+02 0.3000E-02 0.1000E+02
3 0.3886E+02 0.1000E-02 0.1000E+02
$$$ 0 OF THE SPECIES MIGRATE $$$
**************************************** AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA**,..^
1 SPATIAL COMPARTMENTS CONSIDERED
*AAAAAAAAAAAAAA*AAAAAAAAAAAAAAAAAAAAAAAAA*AAA*AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA*A***.
COMPARTMENT 1
ANNUAL TEMPERATURE PROFILE DESCRIBED BY A STRAIGHT LINE FUNCTION HITH THE FOLLOWING BREAKS:
TIME TEMP TIME TEMP TIME TEMP TIME TEMP
9999.0 15.0
SPECIES 1
STEADY-STATE SPECIES WITH PREDATOR-PREY INDEX OF 1
PREY FRACTION OF TOTAL CONSUMPTION
0 1.000
INITIAL CONCENTRATION (UG/G) = 0.000
SPECIES 2
STEADY-STATE SPECIES WITH PREDATOR-PREY INDEX OF 2
BENTHIC SPECIES ASSUMED TOCONSUME DETRITUS
INITIAL CONCENTRATION (UG/G) 0.000
SPECIES 3
AGE CLASS 1 PREDATOR-PREY INDEX 3
PREY FRACTION OF TOTAL CONSUMPTION
1 0.500
2 0.500
INITIAL CONCENTRATION (UG/C) 0.000
AGE CLASS 2 PREDATOR-PREY INDEX 4
PREY FRACTION OF TOTAL CONSUMPTION
46
-------
NASTOX.OUT;! 4-JAN-1985 16:05 Page 3
1 0.500
2 0.500
INITIAL CONCENTRATION (UG/G) 0.000
AGE CLASS 3 PREDATOR-PREY INDEX 5
PREY FRACTION OF TOTAL CONSUMPTION
1 0.500
2 0.500
INITIAL CONCENTRATION (UG/G) 0.000
HATER COLUMN SEGMENTS INCLUDED IN COMPARTMENT 1 ARE:
1
BED SEGMENTS INCLUDED IN COMPARTMENT 1 ARE:
2
TIME STEP= 2.0 RUN TIME= 366. PRNTINTERVAL= 30. JULIAN DATE AT START= 0.
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA;.,
CHEMICAL CONCENTRATIONS FOR SEGMENT 1
DISS. CONC. PART. CONC. TIME DISS. CONC. PART. CONC. TIME DISS. CONC. PART. CONC. TIME
UG/L UG/G DAYS UG/L UG/G DAYS UG/L UG/G DAYS
0.1000E-01 O.OOOOE+00 366.
CHEMICAL CONCENTRATIONS FOR SEGMENT 2
DISS. CONC. PART. CONC. TIME DISS. CONC. PART. CONC. TIME DISS. CONC. PART. CONC. TIME
UG/L UG/G DAYS UG/L UG/G DAYS UG/L UG/G DAYS
0.1400E+00 0.2770E+00 366.
47
-------
HASTOX.OUT; 1 4-JAN-198S 16:05 Page 4
FOOD CHAIN MODEL
ACE CLASS 1 EXCRETION RATE 0.1528E-01
ACE CLASS 2 EXCRETION RATE 0.1264E-01
ACE CLASS 3 EXCRETION RATE 0.11B8E-01
YEAR 0 DAY 30.
$$$$$$SS$$$$$$S$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0 . 5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION *0.1089E+01
SPECIES 3
•u> I. W %« A. I* *^ J
-ACE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION ACE CLASS CONCENTRATION
1 0.1085E+01 . 2 0.7868E+00 3 0.6613E+00
AVERAGE CONCENTRATION FOR SPECIES 3 0.8445E+00
** A ******** * A A A A A AAAA AAAAAAAA ***** A A AA ****** A A A A A A A AA A A A Ai^A AAAAAiltA A AAAAA* ******** A A *A*A AAA A A A dk A A A Ik A * * A A A
YEAR 0 DAY 60.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E-K)0
SPECIES 2
STEADY-STATE CONCENTRATION =0. 1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1509E+01 2 0.1239E+-01 3 0.1099E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1282E+01
»***»* A* A A ***,., A,], A ****** A A A* A** A A * A A********* A* A* A * A* * * A* ***** A AA* A * *************** A A *********** ************************
YEAR 0 DAY 90.
$SS$$$$$$S$$$$$$S$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE t'ONCF-NTRATION =0 . *> 1 0 Lf>00
All Concentrations areyg/g(wet weight)
48
-------
WASTOX.OUT;! 4-JAN-1985 16:05 Page 5
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1670E+01 2 0.1498E+01 3 0.1387E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1518E+01
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA*
YEAR 0 DAY 120.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1731E+01 2 0.1645E+01 3 0.1578E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1651E+01
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA*
YEAR 0 DAY 150.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
. SPECIES 2
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1752E+01 2 0.1730E+01 3 0.1704E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1729E+01
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA**AAA*AAAAAAAAAAAAAAAAAAA**
YEAR 0 DAY 180.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
.TATC- rnwrFMTT. ATrnw -n.innqF>oi
49
-------
WASTOX.OUT;! 4-JAN-1985 16:05 Page 6
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1756E+01 2 0.1779E+01 3 0.1787E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1774E-I-01
YEAR 0 DAY 210.
$$S$$$$S$$$$$$$$$S$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0 . 5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0 . 1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1754E+01 2 0.1807E+01 3 0.1843E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1801E+01
YEAR 0 DAY 240.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1749E+01 2 0.1822E+01 3 0.1880E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1817E+01
******************** A* A****** A*** A******************************* **************************************************'*
YEAR 0 DAY 270.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$S
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0.10B9E+01
50
-------
WASTOX.OUT;! 4-JAN-1985 16:05 Page 7
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1743E+01 2 0.1831E+01 3 0.1904E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1826E+01
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA*
YEAR 0 DAY 300.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS 'CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1736E+01 2 0.1835E+01 3 0.1920E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1830E+01
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
YEAR 0 DAY 330.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1729E+01 2 0.1836E+01 3 0.1931E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1B32E+01
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
YEAR 0 DAY 360.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0.5101E+00
SPECIES 2
STEADY-STATE CONCENTRATION =0.1089E+01
SPECIES 3
51
-------
,(tSTOX.OUT;l 4-JAN-1985 16:05 Page 8
ACE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 0.1721E+01 2 0.1836E+01 3 0.1938E+01
AVERAGE CONCENTRATION FOR SPECIES 3 0.1832E+01
YEAR 1 DAY 24.
$$$$$$$$$$$$$$$$$$$$ SPATIAL COMPARTMENT 1 $$$$$$$$$$$$$$$$$$$$
SPECIES 1
STEADY-STATE CONCENTRATION =0. OOOOE+00
SPECIES 2
STEADY-STATE CONCENTRATION =0 . OOOOE-t-00
SPECIES 3
AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION AGE CLASS CONCENTRATION
1 O.OOOOE+00 2 0.1108E+01 3 0.1320E+01
AVERAGE CONCENTRATION FOR SPECIES 3 - 0.8096E+00
52
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