& EPA
           United States
           Environmental Protection
           Agency
               Office Of Air Quality
               Planning And Standards
               Research Triangle Park, NC 27711
EPA-453/D-99-002B
November 1999
Air
                         TRIM
              Total Risk Integrated Methodology
                      TRIMLFaTE
      TECHNICAL SUPPORT DOCUMENT
   Volume II: Description of Chemical Transport
           and Transformation Algorithms
                 EXTERNAL REVIEW DRAFT
            Environmental Fate
            Transport, & Ecc
             Exposure Mod
             (TRIM.FaTI
                         Risk Characterization
                          Module
                          fTRlM.Risk)
                        Exposure-Event Module
                        1 (TRIM Expo)
                                              Social,
                                             Economic,
                                             & Political

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                                                       EPA-453/D-99-002B
                              TRIM

                  Total Risk Integrated Methodology

          TRIM.FaTE TECHNICAL SUPPORT DOCUMENT

Volume II: Description of Chemical Transport and Transformation Algorithms
                 U.S. Environmental Protection Agency
                 Region 5, Library (PL-12J)
                 77 West Jackson Bpulevard, 12tn Floor
                 Chicago, IL  60604-3590
          U.S. ENVIRONMENTAL PROTECTION AGENCY
                     Office of Air and Radiation
              Office of Air Quality Planning and Standards
             Research Triangle Park, North Carolina  27711
                       External Review Draft
                          November 1999

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                                    Disclaimer

       This document is an external review draft.  It has not been fonnally released by the U.S.
Environmental Protection Agency and should not at this stage be construed to represent Agency
policy. It is being circulated for comments on its technical merit and policy implications, and
does not constitute Agency policy. Mention of trade names or commercial products-is not
intended to constitute endorsement or recommendation for use.
NOVEMBER 1999                              i              TRIM.FATETSD VOLUME II (DRAFT)

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                                                                     ACKNOWLEDGMENTS
                               Acknowledgments

       As described in this report, the Office of Air Quality Planning and Standards (OAQPS) of
the U.S. Environmental Protection Agency is developing the Total Risk Integrated Methodology.
The principal individuals and organizations in the TRIM.FaTE development effort and in the
preparation of this report are listed below.  Additionally, valuable technical support for report
development was provided by ICF Consulting.                               ~"
Robert G. Hetes, EPA, Office of Air Quality Planning and Standards
Deirdre L. Murphy, EPA, Office of Air Quality Planning and Standards
Ted Palma, EPA, Office of Air Quality Planning and Standards
Harvey M. Richmond, EPA, Office of Air Quality Planning and Standards
Amy B. Vasu, EPA, Office of Air Quality Planning and Standards

Deborah Hall Bennett, Lawrence Berkeley National Laboratory
Rebecca A. Efroymson, Oak Ridge National Laboratory
Steve Fine, MCNC-North Carolina Supercomputing Center
Dan Jones, Oak Ridge National Laboratory
John Langstaff, EC/R Incorporated
Bradford F. Lyon, Oak Ridge  National Laboratory
Thomas E. McKone, Lawrence Berkeley National Laboratory & University of California, Berkeley
Randy Maddalena, Lawrence  Berkeley National Laboratory
NOVEMBER 1999                              iii             TRIM.FATE TSD VOLUME II (DRAFT)

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ACKNOWLEDGMENTS
       The following EPA individuals reviewed a previous draft of this document.

                        EPA Models 2000 TRIM Review Team
Robert F. Carousel
National Exposure Research Laboratory
Office of Research and Development

*S. Steven Chang
Office of Emergency and Remedial Response
Office of Solid Waste and Emergency
Response

Ellen Cooter
National Exposure Research Laboratory
Office of Research and Development

Stan Durkee
Office of Science Policy
Office of Research and Development

Harvey Holm
National Exposure Research Laboratory
Office of Research and Development

John S. Irwin                   —
Office of Air Quality Planning and Standards
Office of Air and Radiation
* Team Leader
Linda Kirkland
National Center for Environmental Research
and Quality Assurance        —  -
Office of Research and Development

Matthew Lorber
National Center for Environmental
Assessment
Office of Research and Development

Haluk Ozkaynak
National Exposure Research Laboratory
Office of Research and Development

William Petersen
National Exposure Research Laboratory
Office of Research and Development

Ted W. Simon
Region 4

Amina Wilkins
National Center for Environmental
Assessment
Office of Research and Development
                           Review by Other Program Offices
Pam Brodowicz, Office of Air and Radiation, Office of Mobile Sources
William R. Effland, Office of Pesticide Programs
John Girman, Office of Air and Radiation, Office of Radiation and Indoor Air
Steven M. Hassur, Office of Pollution Prevention and Toxics
Terry J. Keating, Office of Air and Radiation, Office of Policy Analysis and Review
Russell Kinerson, Office of Water
Stephen Kroner, Office of Solid Waste
David J. Miller, Office of Pesticide Programs
NOVEMBER 1999
                                          IV
           TRIM.FATE TSD VOLUME II (DRAF-T)

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	PREFACE

                                   PREFACE

       This draft document, the TRIM.FaTE Technical Support Document, is part of a series of
documentation for the overall Total Risk Integrated Methodology (TRIM) modeling system.  The
detailed documentation of TRIM'S logic, assumptions, algorithms, equations, and input
parameters is provided in comprehensive Technical Support Documents (TSDs) for each of the
TRIM modules. The purpose of the TSDs is to provide full documentation of how TRIM works
and of the rationale for key development decisions that were made. This report, which
supersedes an earlier version (U.S. EPA 1998a), documents the Environmental Fate; Transport,
and Ecological Exposure module of TRIM (TRIM.FaTE) and is divided into two volumes. The
first volume provides a description of terminology, model framework, and functionality of
TRIM.FaTE, and the second volume presents a detailed description of the algorithms used in the
module.

       To date, EPA has issued draft TSDs for TRIM.FaTE (this report) and the Exposure-Event
module (TRIM.Expo  TSD, U.S. EPA 1999a). When the Risk Characterization module
(TRIM.Risk) is developed, EPA plans to issue a TSD for it.  The TSDs will be updated as needed
to reflect future changes to the TRIM modules.

       The EPA has also issued the 1999 Total Risk Integrated Methodology (TRIM) Status
Report (U.S. EPA 1999b).  The purpose of that report is to provide a summary of the status of
TRIM and all  of its major components, with particular focus on the progress in TRIM
development since the 1998 TRIM Status Report (U.S. EPA 1998b). The EPA plans to issue
status reports on an annual basis while TRIM is under development.

       In addition to status reports and TSDs. EPA intends to develop detailed user guidance for
the TRIM computer system. The purpose of such guidance will be to define appropriate (and
inappropriate) uses of TRIM and to assist users in applying TRIM to assess exposures and risks
in a variety of air quality situations.

       Comments and suggestions are welcomed.  The OAQPS TRIM team members, with their
individual roles and addresses, are provided below.

TRIM Coordination  Deirdre L. Murphy
                   REAG/ESD/OAQPS
                   MD-13
                   RTF, NC 27711
                    [murphy.deirdre@epa.gov]

TRIM.FaTE         Amy B. Vasu
                   REAG/ESD/OAQPS
                   MD-13
                   RTP,NC 27711
                   [vasu.amy@epa.gov]
NOVEMBER 1999                             v             TRIM.FATE TSD VOLUME H (DRAFT)

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PREFACE
TRIM.Expo         Ted Palma                     Harvey M. Richmond
                  REAG/ESD/OAQPS             HEEG/AQSSD/OAQPS
                  MD-13                        MD-15
                  RTF, NC 27711                 RTF, NC 27711
                  [palma.ted@epa.gov]             [richmorid.harvey@epa. gov]

TRIM.Risk         Robert G.Hetes                                   —  _
                  REAG/ESD/OAQPS
                  MD-13
                  RTF, NC 27711
                  [hetes .bob@epa. gov]
NOVEMBER 1999                           vi            TRIM.FATETSD VOLUME II (DRAFT)

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                                                                           ACRONYMS
                                 ACRONYMS

B(a)P          Benzo(a)pyrene
BW           Body weight
DOC          Dissolved organic carbon
EPA           United States Environmental Protection Agency
GI             Gastrointestinal                                              -
GIS           Geographic Information Systems
HAP          Hazardous air pollutant
IEM           Indirect Exposure Methodology
LSODE        Livermore Solver for Ordinary Differential Equations
NERL         National Exposure Research Laboratory
OAQPS        EPA Office of Air Quality Planning and Standards
OPPT          Office of Pollution Prevention and Toxics
ORD          Office of Research and Development
OW           Office of Water
PAH          Polycyclic aromatic hydrocarbon
R-MCM        Regional Mercury Cycling Model
SAB           Science Advisory Board
TOC          Total organic carbon
TRIM          Total Risk Integrated Methodology
TRIM.Expo     TRIM Exposure-Event module
TRIM.FaTE     TRIM Environmental Fate, Transport, and Ecological Exposure module
TRIM.Risk     TRIM Risk Characterization module
TSD           Technical Support Document
WASP         Water Quality Analysis Simulation Program
NOVEMBER 1999
                                         VII
TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                    TABLE OF CONTENTS
                          TABLE OF CONTENTS

Disclaimer	i
Acknowledgments 	iii
Preface	,	v
Acronyms  	 vii
Table of Contents	.T..".	ix

1.     Introduction	"	1-1

2.     Algorithm Overview  	2-1
       2.1    Multiple-phase Calculations 	2-1
       2.2    Converting Equations with Equilibrium Relationships to Dynamic Form ... 2-12
       2.3    General Fate and Transport Processes	2-13

3.     Air Algorithms	3-1
       3.1    Air to Air Algorithms	3-1
       3.2    Air to Soil Algorithms	3-4
       3.3    Air to Surface Water Algorithms	3-4

4.     Surface Water and Sediment Algorithms	4-1
       4.1    Conceptualization of the Surface Water and Sediment Compartments	4-1
       4.2    Advective Processes	4-4
       4.3    Derivation of River Compartment Transfer Factors 	4-8
       4.4    Dispersive Processes 	4-9
       4.5    Diffusive Processes T	4-14

5.     Soil Algorithms	5-1
       5.1    Introduction 	5-1
       5.2    Soil Compartments and Transport Processes	5-1
       5.3    Transformation in Soil Compartments	5-1
       5.4    Vertical Transport Algorithms	5-5
       5.5    Horizontal Transport Processes	_	5-11

6.     Groundwater Algorithms 	6-1

7.     Biotic Algorithms	7-1
       7.1    Selecting the Biotic Components of TRIM.FaTE 	7-1
       7.2    Algorithms for Terrestrial and Semi-aquatic Biota	7-1
       7.3    Algorithms for Aquatic Biota 	7-40
       7.4    Revisions in Biotic Algorithms	7-54

8.     References	8-1

Appendices

A.     Derivation of Mercury-specific Algorithms and Input Parameters

NOVEMBER 1999                             ixTRIM.FATE TSD VOLUME II (DRAFT)

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                                                                              CHAPTER I
                                                                           INTRODUCTION
 1.    INTRODUCTION

       This volume presents the algorithms used to describe the transport and transformation of
 chemicals in the TRIM.FaTE module. These algorithms are used to estimate the physical and
 chemical processes that drive chemical transport and transformation in the environment. As
 explained in Volume I of this report, the TRIM.FaTE framework can incorporate first-order and
 higher order algorithms. At the present time, however, only first-order algorithms have been
 implemented in the model.

       First-order transfer between compartments in TRIM.FaTE is described by transfer
factors, referred to as T-factors. This volume documents all of the T-factors currently
 implemented in TRIM.FaTE. A T-factor is approximately the instantaneous flux of the chemical
 in the receiving compartment normalized by the amount of chemical in the sending compartment
 (see Section 4.2 in Volume I of this report for more discussion about the units of T-factors and
 related issues).  That is, T * N(t) is the instantaneous flux in units of chemical mass/time, where
 N(t) is the chemical mass in the sending        	
 compartment at time t.  The compartment
that receives the mass lost from the sending
compartment is referred to as the receiving
compartment.
The transfer factor, or T-factor, is the
instantaneous chemical flux normalized by the
current chemical mass in the sending
compartment. That is, T-factors are time-
                                            dependent.
       Because it is a normalized flux, a
large T-factor in itself does not imply that the
flux is large; the actual flux also depends on the amount of chemical in the sending compartment
The T-factor is not the same as the fraction of mass lost in a given time interval, although the two
quantities are related. When the fraction of mass lost is small, these two quantities are generally
approximately the same, but they differ significantly when the fraction of mass lost is larger. In
particular, T= -ln(l-/>), where/? is the fraction of mass lost in one simulation time step, and the
units of time are the same as T.

       Chapter 2 presents a general description of how each of the different transport and
transformation processes are modeled in TRIM.FaTE. Chapters 3 through 6 present-the abiotic
algorithms for air (Chapter 3), surface water and sediment (Chapter 4), soil (Chapter 5), and
ground water (Chapter 6). For simplicity, the algorithms used to describe intermedia transport
are only presented in one of the chapters and referenced in the other.

       Chapter 7 presents the algorithms used to describe transport of chemical mass between
biotic compartment types and  between biotic and abiotic compartment types. Chapters 3 through
7 begin with a brief summary of the algorithms described in the chapter and then explain each
algorithm in greater detail. While Chapters 2 through 7 focus on the general algorithms used in
TRIM.FaTE,  Appendix A presents the chemical-specific algorithms for mercury and PAHs.
NOVEMBER 1999                              1-1              TRIM.FATETSD VOLUME II (DRAFT)

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                                                                           CHAPTER 2
_       ALGORITHM OVERVIEW

2.     ALGORITHM OVERVIEW

       In this chapter, algorithms that generally apply across a range of compartment types are
discussed. Algorithms specific to compartment types are presented in subsequent chapters.

2.1    MULTIPLE-PHASE CALCULATIONS                      ~ "

       This section describes how multiple phases within a compartment are currently modeled.
The most common phases considered in the prototype are liquid, gas, and solid, which are
assumed to be at chemical equilibrium.  Other phases may include biotic phases (e.g. , algae in
surface water). Because chemical equilibrium among phases in a compartment is assumed, the
ratios of the concentrations in the individual phases are constant, and mass balance need only be
tracked for the total amount of the chemical in all phases in a compartment.  The  amount of
chemical in the compartment in a particular phase can be determined from the total amount in the
compartment (described in the following text).  It is possible that, in future versions of
TRIM.FaTE, chemical equilibrium will not be assumed, in which case the amount of chemical in
different phases will need to be tracked as separate compartments.

       In any compartment, the total amount of chemical in a given compartment is made up of
the sum of the amounts in the different phases:
   N Total = Amount in gas phase + Amount in aqueous phase + Amount in solid phase
        — C' Sas ]/ Sas + f water i/ water f solid T/ solid                                     \    '
where:

       NTotal  =     total amount of chemical in compartment (g [chemical])
       Cgm   =     concentration of chemical in gas phase in compartment
                   (g [chemical]/m3 [gas in compartment])
       Vs"5   -     volume of gas in compartment (m3 [gas in compartment])
       Cwaler  =     concentration of chemical in aqueous phase in compartment
                   (g [chemical]/m3 [water in compartment])
       Vwaler  =     volume of aqueous matter in compartment (m3 [water in compartment])
       £*oiid  -     concentration of chemical in solid phase in compartment (g [chemical]/m3
                   [solid in compartment])
       V*ohd  =     volume of solid in compartment (m3 [solid in compartment]).

       If it is desired that the units of NTolal be in units of moles (chemical), then the preceding
equation must be multiplied by the molecular weight of the chemical (which has units of moles
[chemical]/g [chemical]).

       Because chemical equilibrium is assumed, the ratios of the concentrations are constant.
However, care must be used in specifying the units of the concentration.  This is because, in
NOVEMBER 1999                             2-1             TRIM.FATETSD VOLUME II (DRAFT)

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CHAPTER 2
ALGORITHM OVERVIEW
practice, it is more common to define notation for ratios of concentrations on a mass by mass
basis rather than that of mass by volume basis.

2.1.1  NORMALIZATION TO LIQUID PHASE

       This section describes the relevant formulas when the concentrations in othej_phases are
normalized to the concentration in the liquid phase. This  normalization is used for all soil,
surface water, and sediment compartments (including the  cases where: additional phases are
considered). Using the equilibrium assumptions:
                                                                                    (2-2)

                               Csas =(H/R T)CH'aler                               (2-3)
where:
       psollli   =      density of solid phase in compartment (kg [solid phase]/m3 [solid phase])
       Kd     =      equilibrium partition coefficient; ratio of concentration in solid phase (kg
                     [chemical]/kg [solid phase]) to that in liquid phase (kg [chemical]/liters
                     [L] [liquid phase])
       Cf     -      1 0~3  m3/L, conversion factor to convert m3 (liquid phase) to L (liquid
                     phase)
       //     =      Henry's law constant  for chemical (Pa-m3/mol)
       R      =      ideal gas constant (8.3 14 m3-Pa/mol-K)
       T      =      temperature (K)

Applying these relationships to the general equation in the beginning of this section yields:
                   Total = Cv,ate   __K«« +  V waler + 9 soM K dCfV iohd            -  '   (2-4)
                             I  RT                               I
       The volumes of each phase in the compartment can be expressed as fractions of the total
volume of the compartment, in which case the previous equation yields:
                                 Iir J/gas     T/water              y solid}
                                          j_         j.  r\    V f                     /TC\
                                	+ 	  +  0 ,  ,/L.C,.	               (2-J)
                                 "^ y Total    y Total    rsolld  d  •' y Total |              V
where:
NOVEMBER 1999                              2-2             TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                               CHAPTER 2
                                                                     ALGORITHM OVERVIEW
                               y Total _ ygas +  yuater + ysolid
       The term CTola/ = NT°'a'/vTolal is the total concentration of the chemical in the compartment.
Using the assumed equilibrium relationships, the concentrations in the individual phase;s can be
recovered from the total amount of mass in the compartment, as follows:
C water _
(^gas _
"• solid _

\j Total/y Total
If-f ygas y water
~*~ + o K
RT yTotal yTotal ^ solid ^d
H cwaler_ (H/RT)N'
RT \ H V ^as V water
[ RT vTotal VT°'al
/-> Y /~i /^ water ^rsol,d
P solid ^d *~/~ (
f H Vgas


T/ solid \
C '
^ yTotal
Total 1 y Tola,
+ P,0w^
KdC)N
y water
	 +
)
I
T/ solid \
' C
d J y Total 1
Total i y Total
y solid \
n K C y
                                                                                  (2-8)
                                  1  RT I/Total     yTotal    r*oia-
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CHAPTER 2
ALGORITHM OVERVIEW
where Cl is the concentration of the chemical in phase/ (units of mass [chemical]/volume [phase
7]), Cnorm is the concentration in the phase to which one is normalizing, and KJ is the equilibrium
ratio between the concentration in phase/ and the phase to which one is normalizing, with units
of (mass [chemicalj/volume [phasey])/(mass [chemicalj/volume [phase to which one is
normalizing]). These ratios KJ are generally expressed in terms of other environmental and/or
chemical parameters. The total mass of chemical in the  compartment, denoted by N^'"'^ is:
                               N Total =     jj



                                     ~~tv^Cnorm                              (2-10)
                                       7 = 1

                                        norm £-~t j  j
where F, is the volume of phase/ in the compartment, and    V - Vlota[. The fraction of mass of
chemical in phase/ is then given by:                    •/='


             Mass of chemical in phase j in compartment _ v „ .,, Totai
               Total mass of chemical in compartment      J J
                                                          FK
                                                           j j
                                                        V^  rr

                                                        /=!


 When applied to the previous section (and using the notation introduced there), we have that
 Cnorm=Cwaler, and the terms K are given by:
                                 *•--= !                                         (2-12)
water
                                  Kgas=H/(RT)                                    (2-13)

                                               Cf                                (2-14)
 NOVEMBER 1999                              2-4             TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                                 CHAPTER 2
                                                                       ALGORITHM OVERVIEW
       2.1.2.2 Form When Fugacity Concept Is Applicable

       It is sometimes convenient to apply the concept of fugacity (Mackay 1991) when
presenting the equations. For the chemicals modeled to date (PAH, B(a)P, elemental mercury,
divalent mercury, and methylmercury), the algorithms are presented using the fugacity notation.
Fugacity has units of pressure and can be linearly or non-linearly related to concentration through
the relationship fugacity (f) = (fugacity capacity [Z]) • (concentrations).  The fugacity capacities
for the pure phases of water, air, and solid are:
                                water
                                    =  1/ff                                          (2-15)
                               Zair  =  \'(RT)                                        (2-16)
                               ZSOl,d
defined by:

       Psoi,d   =      density of solid phase in compartment (kg [solid phase]/m3 [solid phase])
       Kd     =      equilibrium partition coefficient; ratio of concentration in solid phase (kg
                     [chemical]/kg [solid phase]) to that in liquid phase (kg [chemical]/liters
                     [L] [liquid phase])
       Cf     =      1 0~3 m3/L, conversion factor to convert m3 (liquid phase) to L (liquid
                     phase)      _
       H     =      Henry's law constant for chemical (Pa-m3/mol)
       R      =      ideal gas constant (8.314 m3-Pa/mol-K)
       T      =      temperature (K)

 The total fugacity capacity ZTolal for a given compartment is defined as:

                               T/ gas         {/ water        y solid                  _
                                       7   — _ +  Z
                              — _        — _        — _
                            fl'r Y Total    waler Y Total     sohd y Total
where phase is either the solid, liquid, gas, or other phase.

       It is fundamental to the concept of partition modeling that the concentration ratio between
two phases is equal to the ratios of the fugacity capacities of the two phases (Mackay 1991).
That is,
                                   ^ phase ,   Z ,
                                   C        phase {
                                     phase,  2 ,
                                            phase-,
                                                                                   (2-19)
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CHAPTER 2
ALGORITHM OVERVIEW
       Applying these relationships shows that:

                                    Z........ M Total  Z.
                            f~> water _   water £V	  water ^ total
                                     y total y Total  7 total                                 (2-20)


                                     y total y Total  y total                                 ^     '

                            s->solid_   solid N    _  solid £ total                     -       (2-22)
                                     7 total y Total  y total
where CTclal is the total concentration of the chemical in the compartment (units of
g [chemical]/m3 [total compartment]). From these relationships, in general, the amount of mass
in the different phases is given by:

                                           Z     \T Total       Z
                \jwater_ y water f water _  ywaler  water £V	 y water  water f-i total
                                            y total y Total       y total                     (2-23)
                                        Z    XI Total       Z
                ft gas = £gasygas_  ygas___air_ j_v	 ygas   gas ^ totol                      C
                                        •7 total  y Total       7 total                            ^

                \r solid _(^ solid y solid _  y solid solid  N     _ y solid  solid ^ total                  (2-25)
                                          y total  y Total       y total
where Waler^ N%a-\ and N*   are the mass in the water, gas, and solid phases, respectively.

        If there are other phases in equilibrium with the chemical dissolved in the water phase,
then the fugacity capacities of that phase can be defined in a manner consistent with that above.
For example, if  C her=Kother  Cwater, where Colher has units of g[chemical]/m3[or/?er phase], then
the fugacity capacity of the other phase is defined by:

                                    Bother ~  Kother Cwater                            -      (2-26)

and the total fugacity capacity of the compartment is given by:


                          T/ gas           y water         y solid          y other
               7 Total _ 7   J_	  + y   _{_	 + y	 +  7	              ,,
                          y Total      waler y Total     solldy Total      °''her y Total              ^
where V"hcr is the volume of the other phase, in units of m'[other phase].

        In the following sections, the general equations presented in this section for multiple
phase calculations are applied to specific compartment types. The use of these equations in the
NOVEMBER 1999                                 2-6               TRIM.FATETSD VOLUME II (DRAFT)

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                                                                              CHAPTER 2
                                                                     ALGORITHM OVERVIEW
following sections primarily involves only adhering to notation commonly used in the literature
for the different media.

2. 1 .3  APPLICATION TO SOIL, SURFACE WATER, AND SEDIMENT
       COMPARTMENT TYPES

       For soil, surface water, and sediment compartment types, the concentrations are
normalized to the concentration in the liquid phase, and the same notation is used to represent the
relevant parameters. In a soil compartment, the solid phase consists of the soil particles. In a
surface water compartment, the solid phase consists of the sediment suspended in the water
column.  In a sediment compartment, the solid phase consists of clay, silt, or sand particles as
opposed to the water phase that fills the interstitial space between the sediment solid particles.
Following common practice, the volume fractions of each phase are denoted as follows:
                                T/ water

                                     =                                          (2-28)

                                                                                (2-29)
                                y total
                                i/ solid
                                     -=l-0-e = l-d>                               (2-30)
                                V
                                  total
where:                          ^

       6      =     water volume fraction
       e      =     gas volume fraction
       1-6-e  =     l-
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CHAPTER 2
ALGORITHM OVERVIEW
where:

       Kj     =     equilibrium ratio of concentration of chemical in phasey and concentration
                    dissolved in water phase (g [chemical]/m3 [phase y'])/(g [chemical]/ m3
                    [water])
       i}f     =     volume fraction of compartment composed of phase j (      __ _
                    m3 [phase y]/m3 [total])

       Fugacity-based Notation

If fugacity-based notation is to be used, then the total fugacity for the compartment is given by:

                                                    l-4>)                        (2-33)
In the general case when there are additional equilibrium phases considered:

where Zj is the fugacity of phasey.

       Note that for the ground water, surface water, and sediment compartment types, the
volume fractions of the gas phase (e)are assumed to be zero.

       The soil-water partition coefficients (Kd) in each compartment (soil, surface water, and
sediment) may be either input or calculated. At present, they are input for mercury species, and
calculated for nonionic organic chemicals (Karickhoff 1981) by:


                                    Kd=Kocfoc                                    (2-35)
where:

       Koc    =     organic-carbon partition coefficient
       foc     =     fraction of organic carbon in the compartment

2.1.4  MULTIPHASE PARTITIONING IN THE AIR COMPARTMENT TYPE

       Because the volume of water in an air compartment is so small relative to the volume of
the solid and the gas phase, there has not been a historical development of Kd's (i.e., ratio of
concentration in solid phase to that in dissolved phase) for the atmosphere, although the concept
still applies. Instead, only the solid and gas phases are usually addressed. If chemical
equilibrium is assumed between the phases, then a normalization other than to the liquid

NOVEMBER 1999                             2^8             TRIM.FATE TSD VOLUML II (DRAFT)

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                                                                                 CHAPTER 2
                                                                       ALGORITHM OVERVIEW
concentration is required.  In an air compartment, the solid phase consists of the particulate
matter in the atmosphere.

        At present, the volume fractions of solids in each phase in an air compartment are given
by:
                                  i/ water                                     """^  ~
                                       -=0
                                    total                                            (2-36)

                                    	-D,/f>,                                     (2-37^
                                    total   L ^dusl                                   ^    '

                                           D./o,                                  (2-38)
                                    'total
where:
       D,     =      atmospheric dust load in air compartment (kg [aerosol]/m3 [air
                     compartment])
       pju,,    =      density of aerosols (kg [aerosol]/m3 [aerosol]).

       The dust load and aerosol density are specified properties of each air compartment.  To
normalize to either the gas or solid phase, the equilibrium ratio of the concentrations in the two
phases must be estimated. In the prototype, the fraction of the contaminant bound to particles,
denoted by cp, is estimated using a method developed in Junge (1977) for organics, and a more
recent method developed by Harner and Bidleman (1998) that is applied for mercury, both of
which are discussed in the subsequent sections. Use of this term in the current notation is:
                                 v solid Csoiid=  


-------
CHAPTER 2
ALGORITHM OVERVIEW
The total mass of chemical in the air compartment is then:

                                             solid

                 — (~* S
                     as I/ Total
    (1 -DL/p
                                            V(\-DL/pa
                                                                               (2-42)
                                               (1-cp)
       Fugacity-based Notation

For the air compartment, the fugacity capacity in the solid phase can be determined by use of the
relationship as follows.

                                     f solid
                             7   _7  _r	
                              solid  air
                                  z                                             (2"43)
                                 "
where Zair=l/(RT), R is the ideal gas constant (8.314 m3-Pa/mol-K), and T is temperature (K).

The total fugacity in the air compartment is then given by:
        VSas         -if solid
total _ 7   '            J_ _
     air
                                 _         _ _
                                 yTotal     sohd y Total                             (2-44)

                                 l~DL/pJ + ZsolidDL/pdm,
2.1.5   CALCULATION OF THE FRACTION OF CONTAMINANT BOUND TO
       AEROSOL

       In the prototype, the fraction of chemical bound to particulate in the air compartment,
denoted by cp,, is calculated using one of two methods.  The first method discussed here is
discussed in Harner and Bidleman (1998), while the second is due to Junge (1977). The current
TRIM.FaTE model relies on the method of Harner and Bidleman. Note that in each of these
NOVEMBER 1999                            2-10             TRIM.FATE TSD VOLUME II (DRAFT)

-------
                                                                                 CHAPTER 2
                                                                       ALGORITHM OVERVIEW
methods, any chemical with extremely low or essentially zero vapor pressure is assumed to be
100 percent bound to particulate matter in the air (e.g., cadmium, lead).

       2.1.5.1 KoA-based Method

       In Harner and Bidleman (1998), a "KoA absorption model" is shown to fit to_PCB data
better than a Junge-Pankow model similar to that discussed in the previous section.  Further, the
parameters needed are considered to be more easily measurable than the parameters for the
Junge-Pankow model.  Using the notation of that paper, this model first estimates the particle/gas
partition coefficient (KF) in terms of the octanol-air partition coefficient and the fraction of
organic matter attached to particles, and then one calculates the fraction of compound in the
particle phase via the relationship:

                                        Kp(TSP)
                                 


-------
CHAPTER 2
ALGORITHM OVERVIEW
       2.1.5.2 Junge's Method

       This method has been used in existing multimedia models ard is available as an
alternative.  This discussion is based on that presented in CalTOX (McKone 1993a,McKone
1993b, McKone 1993c). With this method, the fraction of chemical bound to aerosol is
calculated via the formula:
                                                                        "      (2'49)

where:

       VP    =     vapor pressure or subcooled vapor pressure of the chemical (Pa)
       c      =     empirical constant set to 0.173 as in Junge ( 1977) (m-Pa)
       6     =     total surface of aerosols per volume of aerosol (m2/m3).

       There is a range of values for 0, with Whitby (1978) reporting a range of values of 4.2 x
10"5 m2/m3 for a "clean" continental site to l.lxlO"5 nv/m3 for urban sites. The average of these
values is used as the default for 0.

       Following CalTOX (McKone 1993a,McKone 1993b, McKoie 1993c), the subcooled
vapor pressure (vapor pressure of subcooled liquid) is used if the temperature is below the
melting point (Tm) of the chemical. In particular:
                                      VP       if T>T
                       VP  = {                  J     m
                       ^     exp[6.79(r/r-l)]  ifT
-------
                                                                            CHAPTER 2
                                                                   ALGORITHM OVERVIEW
takes time ta in order to reach 100 or percent of the steady-state value when C2 is approximately
constant, then:
                                df-=k2C2-klCl                              (2-51)
where k, and k2 are defined as:
                                k{ = -ln(l -a)/rc                                (2-52)
                                k2=Kk^                                      (2-53)
The solution of the previous differential equation with initial condition C|(0) = 0 is given by:

                                      9  /    -k t\
                               C}(t)=-rC2(l-e  ')                              (2-54)
       The steady-state solution is C/() = (&/&/,) C2. and so K = k-/kt. This assumption that
lOOa percent of the steady-state value is reached at time ta means that:


                                       "*''-                                     (2-55)
Solving for k, yields:

                                 *, = -ln(l-a)/ro                                (2-56)



When k/ is determined, k2 = k, K, from which the general result (i.e., Equations 2-52-and 2-53)
follows.

2.3    GENERAL FATE AND TRANSPORT PROCESSES

2.3.1   ADVECTIVE PROCESSES

       In general, the advective flux in a given phase (e.g., attached to particles, or dissolved in
water) from compartment / to compartment / is given by:

   Advective flux from compartment i to compartment j = (Volume of phase that moves
   from compartment i to compartment j per unit time) x (Amount of chemical in phase   (2-57)
                      per volume of phase in compartment i)


NOVEMBER 1999                             2^3             TRIM.FATE TSD VOLUME II (DRAIT)

-------
CHAPTER 2
ALGORITHM OVERVIEW
or
                                                           N (t) x f (phase)
    Advective flux Compartment i-'Compartment j = Q(phase) x  —
                                                              Vfrhase)       (2-58)
where:
       g (phase)     =     volumetric flux of phase from compartment i to compartment/
                          (m3 [phase] /day)
       N,(t)          =     amount of chemical in compartment / a" time (moles [chemical])
      fr(phase)      =     fraction of chemical in compartment / that is in the moving phase
                          (moles [chemical in phase]/moles [chemical in compartment /])
       V (phase)     =     volume of phase that is in compartment / (m3[phase])
       T° v (phase)   =     phase transfer factor for advective flux from compartment / to
                          receiving compartment/ (I/day), given by:
                        Tadv, ,    .   Q(phase)
                        T,  (phase) = - — - — - -                        (2-59)
                                         Vt(phase)
       This formula for the transfer factor is valid for all advective processes from one
compartment to another, and does not rely on the fugacity concept. Application of the concept of
fugacity (as presented in Section 2.1.2.2) shows that:


                         s,  ,    ^    Z (phase)  V (phase)
                         f (phase) -  	x	                      -  (2-60}
                         J'^    '    Z^Total)  V^Totat)                   -     {    }
where:
       Z,(phase)     =     fugacity capacity for moving phase (mo 1/m3[phase]-Pa)
       Z,(Total)      =     total fugacity capacity for compartment / (mol/m3[sending
                          compartment /]-Pa)
       Vt(Total)      =     total volume of compartment / (sum of volumes of each phase in
                          compartment) (mj [compartment /]).

       Applying this shows that the fugacity-based form for the transfer factor for advective flux
NOVEMBER 1999                             2-14            TRIM.FATETSD VOLUME II (DRAM)

-------
                                                                                CHAPTER 2
                                                                       ALGORITHM OVERVIEW
                         -adv,  ,    .   Q (phase) x Zt(phase)
                         T.  ,(phase) =	
                            1           V[Total) x ZfTotat)
                                                                                   (2-61)
                                    v (phase) x At x Zt(phase)
                                       V[Total) x Zt(Total)                   	
       In most applications, the volumetric flow rate Q(phase) of the phase is calculated as the
product of a relevant area (AtJ) and the volumetric flow rate per unit area, or a flow velocity (vy).
Usually the relevant area is the interfacial area between the sending and receiving compartments,
but this is not always the case; e.g., erosion from surface soil to surface water is usually reported
in units of mass (soil)/area (soil layer)-time, in which case the relevant area is the area of the
surface soil layer.  Table 2-1 summarizes the velocities included for compartment types in the
prototype. These flows are discussed in more detail in the sections describing the specific
compartment types.

2.3.2  REACTION AND TRANSFORMATION PROCESSES

       At present, all reaction and transformation processes are modeled using a first-order rate
constant k (units of I/day).  The reaction/transformation flux within a compartment is then given
by k N(t), where N(t) is the mass of chemical in the compartment.  There are a variety of ways in
which the rate constant is determined, with the details depending on the compartment types and
chemicals involved. The simplest is the case where the rate constant is an input (e.g., for the
current mercury species transformation algorithms), hi other cases, the rate constant may be
calculated from other environmental and/or chemical parameters (e.g., from a half-life input by
the user).

2.3.3  BIOTIC PROCESSES

       The biotic processes in TRJM.FaTE are well characterized by the descriptions of abiotic
processes and conversions. Diffusive processes and advective processes are both included. The
primary instance of advection is dietary uptake.  Another prominent example is litterfall.
Fugacity is used as a descriptor in algorithms where it is convenient (e.g., in the uptake of
contaminants by foliage from air). Because mechanisms of uptake of contaminants by some
organisms are not well understood or are difficult to parameterize, some partitioning processes
are assumed to be equilibrium relationships according to the form described in Section 2.2.
These processes may be combinations of diffusion, active transport, and/or advection (e.g.,
transport of contaminants into the plant root), and it is not necessary for the user to specify the
mechanistic process, only the empirical relationship (bioconcentration factor or partition
coefficient and time to equilibrium).

       As with abiotic processes (Section 2.3.2), biotic transformation rates are also described as
first-order processes with respect to the average chemical concentration in the particular
compartment of concern.
NOVEMBER 1999                              2-15             TR1M.FATETSD VOLUME II (DRAIT)

-------
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-------
[This page intentionally left blank.]

-------
                                                                              CHAPTER 3
_           AIR ALGORITHMS

3.     AIR ALGORITHMS

       In this chapter the algorithms for the transport of chemical species within and among air
compartments and diffusion/volatilization between air compartments and surface water are
presented. A description of deposition from air compartments to surface water can_he found in
Chapter 4 and a description of the transport processes between the air compartments and soil cans
be found in Chapter 5. The text box on the next page provides a quick summary of the
algorithms developed in this chapter and provides a definition of all parameters used.

3.1    AIR TO AIR ALGORITHMS

       For a given wind speed and direction, there are two types of transfer considered from one
air compartment to another:

•      Advective transfer (bulk) due to the component of the wind vector normal to the
       boundary between the compartments; and

•      Dispersive transfer (bulk) calculated from the component of the wind vector parallel to
       the boundary between the compartments.

The total transfer factor from one compartment to the other is the sum of these two transfer
coefficients.

       Let AK and As denote the receiving and sending air compartments. If the boundary
between the two air compartments is composed of n distinct line segments, then the transfer
factor from the sending to the receiving air compartment is calculated as
                                                                                 p-
where:

       Vs    =      volume of the sending air compartment (m3)
       Area,  =      interfacial area across /th boundary (m2)
       ulD)   =      direct advective wind velocity across the /th boundary (m/day)
       ufLJ   =      lateral/dispersive wind velocity across the /th boundary (m/day)
NOVEMBER 1999                             3-1             TRIM,FATE TSD VOLUME It (DRAFT)

-------
CHAPTER 3
AIR ALGORITHMS
               Summary of Transport Algorithms Developed in this Chapter
 Air compartment to air compartment:


  T      = —
   AS~AR     ]/
            r s ' = '

 Diffusion/volatilization from air compartment to surface water compartment:


            =  A_    fa(vapor)
   air—>water    17    v   f///? T


 Diffusion/volatilization from surface water compartment to air compartment
   wale r—^air
              V.,
                 •KJw(liquid)
 where
  Vs
  Area,
  uf°>
  A
  fjliquid)
  Vw
  fa(vapor)
  R
  TK
  H
volume of the sending air compartment (m3)
interfacial area across rth boundary (m2)
direct advective wind velocity across the /th boundary (m/time)
interfacial area between the surface water and air compartments (m2)
fraction of chemical in the water compartment that is dissolved (unitless)
volume of water compartment (m3)
fraction of chemical in the air compartment that is in the vapor phase
(unitless)
volume of air compartment (m3)
volatilization transfer rate, m/day
universal gas constant (8.206x10"5 atm-m3/mole °K)
water temperature (°K)
Henry's law coefficient for the air-water partitioning of the chemical (atm-
m3/mole)
NOVEMBER 1999
                      3-2
TR' M.FATE ISO VOLUME II (DRAFT)

-------
                                                                                CHAPTERS
                                                                           AIR ALGORITHMS
3.1.1   Direct Advective Transfer

       The direct wind flow across an air compartment boundary (notation u(D) is used above) is
calculated by finding the projection of the wind vector onto the normal vector to the boundary
between the air compartments.

       Let P,=(x,,y,) and P2=(x2,y2) be the points defining the line that is the projection of the
boundary onto the xy-plane (i.e., the view from above of the vertical plane defining the
boundary). It is assumed that the points P, and P2 are ordered so that the receiving compartment
is on the right side of the directed line  segment starting at P, and ending at P2. The unit vector v
perpendicular to this line segment that is in the direction of the receiving compartment is given
by:


               v =	-> -*~*)   = (sirup, coscp)                  _
where q> is the angle measured clockwise from due north. If the wind is blowing with speed u
towards the direction ft (measured clockwise from due north), then the wind vector, denoted by
w, can be written:
                          w = { u. cos(7i/2 -0), u sin(7t/2 -
                                                                                    (3-3)
                             = u (sinO, cosft }
       The projection of the wind vector w onto v is just the dot product w • v of the two
vectors, which is given by:
                     _          u
                w •  v =	
                                                                                    (3-4)
                        u [sinfr sincp + cosd coscp]

                        u cos(fr-(p)
       Since v is a unit vector, the dot product in this case is the component of the vector w in
the direction of v.  The wind flow rate from the sending compartment to the receiving
compartment is defined to be the dot product if it is positive, otherwise it is zero; i.e.,

      Wind speed perpendicular to compartment boundary = u±= max{0,u cos(fr-cp)}       (3-5)
NOVEMBER 1999                              3-3              TRIM.FATETSD VOLUME 11 (DRAFT)

-------
CHAPTER 3
AIR ALGORITHMS
       If the wind is blowing perpendicular to the boundary (i.e., 
-------
where:
                                                                                 CHAPTER 3
                                                                            Am ALGORITHMS
         dissolved
       c
       D
       R
       TK
       H
         dissolved concentration of chemical (mass
         [chemical]/volume[water])
         vapor phase concentration of chemical in air (mass
         [chemical]/volume [air])                          ~- -
         volatilization transfer rate (m/day)
         water depth (m)
         universal gas constant (8.206xlO~5 atm-m3/mole °K)
         water temperature (°K)
         Henry's law coefficient for the air-water partitioning of the
         chemical (atm-mVmole).
       The transfer rate can range from near 0 to 25 m/day, depending on conditions (Ambrose
1995). Multiplying the above equation by the volume of the water compartment, denoted here by
Vw, yields:
                                                    is
        Net Flux air to water (mass[chemical\ltime) = Vv — (Cdlssolved - Ca/(H/RTK))
                                                                  (3-7)
       The term VJD will be equal to the area of the water compartment, if the depth of the
water compartment is approximately constant. This area is also the interfacial area between the
air and water compartments, and so that:
           Net Flux air to water - A K

                                             I (HIRTK)
 (3-8)
or, using the notation of transfer factors,
T      (diffusion/volatilization) = — K
 ar-wate*
                                                       fa(vapor)
                                                       — -
                                                        (HI RT K)
                   Twaler,air(diffusionlvolatilization) =  —- Kv
(3-9)


(3-10)
where:
       A

       ^(liquid)

       TV,,
         interfacial area between the surface water and air compartments
         (m2)
         fraction of chemical in the water compartment that is dissolved
         (unitless)
         total mass of chemical in the water compartment (g)
NOVEMBER 1999
                                         TRIM.FATE TSD VOLUME II (DRAFT)

-------
CHAPTER 3
AIR ALGORITHMS
      fjvapor)
       R
       TK
       H
volume of water compartment (m3)
fraction of chemical in the air comparment that is in the vapor
phase (unitless)
total mass of chemical in the air compartment (g)
volume of air compartment (m3)
volatilization transfer rate (m/day) [see below for details]-
universal gas constant (8.206x10"5 atm-mVmole °K)
water temperature (°K)
Henry's law coefficient for the air-waler partitioning of the
chemical (atm-mVmole).
       The two-resistance method assumes that two "stagnant films" are bounded on either side
by well mixed compartments. Concentration differences serve as the driving force for the water
layer diffusion. Pressure differences drive the diffusion for the air layer.  From mass balance
considerations, it is obvious that the same mass must pass through both films, thus the two
resistances combine in series, so that the conductivity is the reciprocal of the total resistance:
                                                                                   (3-11)
where:

       R,     =      liquid phase resistance, day/m
       KL     =      liquid phase transfer coefficient, m/day
       RG     -      gas phase resistance, day/m
       KG     =      gas phase transfer coefficient m/day.

       There is actually yet another resistance involved, the transport resistance between the two
interfaces, but it is assumed to be negligible (this may not be true in two cases: very turbulent
conditions and in the presence of surface active contaminants).

       The value of K^, the conductivity, depends on the intensity of turbulence in a water body
and in the overlying atmosphere. Mackay and Leinonen (1975) have discussed conditions under
which the value of K^, is primarily determined by the intensity of turbulence in the water.  As the
Henry's Law coefficient increases, the conductivity tends to be increasingly influenced by the
intensity of turbulence in water. As the Henry's La\v coefficient decreases, the value of the
conductivity tends to be increasingly influenced by the intensity of atmospheric turbulence.

       Because Henry's Law coefficient generally increases with increasing vapor pressure of a
compound and generally decreases with increasing solubility of a compound, highly volatile low
solubility compounds are most likely to exhibit mass transfer limitations in water and relatively
nonvolatile high solubility compounds are more likely to exhibit mass transfer limitations in the
NOVEMBER 1999
                3-6
TRIM.FATE TSD VOLUME II (DRAFI )

-------
                                                                                 CHAPTER 3
              _ _____ _ AIR ALGORITHMS

air. Volatilization is usually of relatively less magnitude in lakes and reservoirs than in rivers
and streams.

       In cases where it is likely that the volatilization rate is regulated by turbulence level in the
water phase, estimates of volatilization can be obtained from results of laboratory experiments.
As discussed by Mill et al. (1982), small flasks containing a solution of a pesticide dissolved in
water that have been stripped of oxygen  can be shaken for specified  periods of time.  The amount
of pollutant lost and oxygen gained through volatilization can be measured and the ratio of
conductivities (KVOG) for pollutants and oxygen can be calculated. As shown by Tsivoglou and
Wallace (1972), this ratio should be constant irrespective of the turbulence in a water body.
Thus, if the reaeration coefficient for a receiving water body is known or can be estimated and
the ratio of the conductivity for the pollutant to reaeration coefficient has been measured, the
pollutant conductivity can be estimated.

       The input computed volatilization rate constant is for a temperature of 20°C.  It is
adjusted for segment temperature using the equation:
                                                                                   (3-12)
where:

       K20    -      calculated volatilization transfer rate (m/day)
       0V     =      temperature correction factor
       T      =      water temperature (°C).

       3.3.2.2 Calculation of Volatilization Transfer Rates for the Whitman Two-
              Resistance Model

       There are a variety of options available for how the transfer rates KG and KL are obtained.,
each of which will be implemented in TRIM.FaTE. These options are summarized in Tables 3-1
and 3-2.
NOVEMBER 1999                              3-7              TRIM.FATETSDVOLtJMr.il (DRAFT)

-------
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-------
                                                                             CHAPTER 4
                                                   SURFACE WATER AND SEDIMENT ALGORITHMS
4.     SURFACE WATER AND SEDIMENT ALGORITHMS

       The surface water compartment is assumed to be well-mixed and composed of two
phases: pure water and suspended sediment material that contains the sorbed contaminants.
Similarly, the sediment is modeled as a well-mixed compartment consisting of a phase _sorbed to
the benthic solids and a phase dissolved in the benthic pore water or interstitial water. The gas
phase of the surface water compartment is considered to be negligible in terms of its impact on
the movement of chemicals. The text box beginning on the next page provides a quick summary
of the algorithms developed in this chapter and provides a definition of all parameters used.

4.1   CONCEPTUALIZATION OF THE SURFACE WATER AND
       SEDIMENT COMPARTMENTS

       The behavior of chemicals in surface waters is determined by three factors:  the rate of
input, the rate of physical transport in the water system, and chemical reactivity.  Physical
transport processes are dependent to a large extent on the type of water body under consideration
i.e., oceans, seas, estuaries, lakes, rivers, or wetlands.  Schnoor (1981) and Schnoor and
MacAvoy (1981) have summarized important issues relating to surface-water transport. Fugacity
models have been developed for lakes and rivers by Mackay et al. (1983a,1983b).

       At low concentrations, contaminants in natural waters exist in both a dissolved and a
sorbed phase. In slow-moving surface waters (e.g., lakes), both advection and dispersion are
important.  In rapidly moving water systems (e.g., rivers), advection controls mass transport, and
dissolved substances move at essentially the same velocity as the bulk water in the system. A
water balance is the first step in assessing surface-water transport. A water balance is established
by equating gains and losses in a water system with storage. Water can be stored within
estuaries, lakes, rivers, and wetlands by a change in elevation. Water gains include inflows (both
runoff and stream input) and direct precipitation. Water losses include outflows and evaporation.

       The accuracy of modeling fresh water systems depends on the ability to accurately
simulate the movement of water and sediment to and from the system (Schnoor 1981). There are
two primary categories for fresh water: rivers and lakes. This model is based on that described
in Mackay et al. (1983a,1983b).  Table 4-1 summarizes the gains and losses considered from the
surface water compartment considered in the TRIM.FaTE prototype.  Losses from the sediment
due to colloidal diffusion, bioturbation, or  reaction/transformation are not considered at this stage
of the TRIM.FaTE model.

       The general manner in which the model is presented is intended to assist the flexibility of
future prototypes and to facilitate implementing different algorithms to describe specific
processes. The use of the fugacity terminology is used to describe the advective process for
simplicity of notation and consistency.
NOVEMBER 1999                            4-1              TRIM.FATE TSD VOLUME II (DRAFT)

-------
CHAPTER 4
SURFACE WATER AND SEDIMENT ALGORITHMS
               Summary of Transport Algorithms Developed in this Chapter
 Dry deposition of particles to surface water (solid phase):
             A        O Z
  rp dd    _   airsw    ra  solid
    air-m> ~  y      d n  7
              V air      Pp^ total
 Wet deposition of particles to surface water (solid phase):

             A           n Z
  T "d    _   airsw TT7    r a   solid
  '•air— >sw ~  T/    ** "I d  _ 7
             V air        Pp^ total
 Advective flux from rainfall:
                   .
                      air     total
 Deposition of suspended sediment to sediment bed (solid phase):

  yd     _ ™swsed  d

sw ^r solid 0>T~T"~~v T ~ V sw Pss V sed Pbs Advection from one river compartment to another river or lake compartment: Dispersive exchange flux between two surface water compartments: E • A F - ->J i-j NOVEMBER 1999 4-2 TRIM.FATE TSD VOLUME II (DRAFT)


-------
                                                                                  CHAPTER 4
                                                      SURFACE WATER AND SEDIMENT ALGORITHMS
           Summary of Transport Algorithms Developed in this Chapter (cont.)
 where:
   air~s\v

    >d
 T.
 Tr
   total
  Wetd
  Rain

  "swsea
  ^
 As

 •"
 Pt,s
 Outflow
  * CVLJ
  C,,C,
  M,,M,
advective transfer factor of particles from air to surface water (1/day)

advective transfer factor of wet particles from air to surface water (1/day)

advective transfer factor for deposition of suspended sediment to sediment bed
(1/day)
advective transfer factor for resuspension of sediment to surface water (1/day)

net advective transfer factor for deposition and resuspension of sediment to surface
water (1/day)

area of surface water/air interface (m2)
volume of air compartment (m3)
dry deposition velocity of particles (m/day)
atmospheric dust load in air compartment (concentration of dust in air) (kg
[particles]/m3 [atmosphere])
density of air particles (kg [particles]/m3 [particles])
wet deposition velocity of particles (m/day)
rainfall rate (m/day)
area of surface water/sediment interface (m2)
volume of surface water compartment (m3)
deposition rate of suspended sediment to sediment bed (kg [suspended
sediment]/m2 (area)-day)
density of suspended sediment (kg [suspended sediment]/m3 [suspended sediment])
area of surface water/sediment interface (m2)
volume of sediment compartment (m3)
resuspension rate of benthic sediment to water column (kg [benthic
sediment]/m2 (area)-day)
density of benthic sediment (kg [benthic sediment]/m3 [benthic sediment])
outflow of water from surface water compartment to advection sink (m3/day)
volume of surface water compartment (m3)
fugacity of the solid phase (Pa)
total fugacity (Pa)
fugacity of the water phase (Pa)
averaged river flow between river compartments i and j (m/h)
concentration of chemical in water compartments / and j (g/m3)
dispersive flux from water compartment / to water compartment/ (mass
[chemical]/day)
mass of chemical in water compartments / and j mg/L (g)
dispersion coefficient for exchange between water compartments /' and j (m2/day)
interfacial area between water compartments /and j (m2)
characteristic mixing length between water compartments / and / (m)
NOVEMBER 1999
                             4-3
TRIM.FATE TSD VOLUME II (DRAFT)

-------
CHAPTER 4
SURFACE WATER AND SEDIMENT ALGORITHMS
                                     Table 4-1
  Summary of the Gains and Losses for Surface Water Compartments Considered in the
                                    Prototype
Gains
From Surface Soil
Erosion
Runoff
From Air
Diffusion from air
Dry deposition of aerosols from air
Wet deposition of aerosols from air
Wet deposition of vapor from air
From Sediment
Diffusion from sediment
Resuspension of sediment
From Rivers
Compartment to compartment
advective flow
From Aquatic Biota
Elimination from fish
From Surface Water Transformations


Type of
Process

Advective
Advective

Diffusive
Advective
Advective
Advective

Diffusive
Advective

Advective

Exchange



Relevant
Phase

Solid
Aqueous

Vapor
Solid
Solid
Vapor

Aqueous
Solid

Total

Total



Losses



To Air
Diffusion to air



To Sediment
Diffusion to sedinent
Deposition to sediment
To Lake
River to lake adv«'Ctive
flow
To Aquatic Biota
Uptake by fisii
To Sink(s)
Decay/transformal ion to
Reaction/Advection sink
Outflow to
Reaction/Advection sink
Type of
Process

-


Diffusive




Diffusive
Advective

Advective

Exchange

Transformation
Advective
Relevant
Phase




Aqueous




Aqueous
Solid

Total

Total

Total
Total
4.2    ADVECTIVE PROCESSES

       A generalized description of advective processes is provided in Section 2.3.1. This
section focuses on the advective processes simulated in the prototype specific to the surface
water compartment.

4.2.1   ADVECTIVE PROCESSES BETWEEN AIR AND SURFACE WATER

       The advective processes considered between air and surface water are wet and dry
deposition of solid phase particles and wet deposition of vapor that is dissolved into the water
phase.  For all of these processes, the air compartment is the sending compartment and the
surface water compartment is the receiving compartment.
NOVEMBER 1999
4-4
TRIM.FATE TSD VOLUME II (DRAFT)

-------
                                                                                  CHAPTER 4
                                                      SURFACE WATER AND SEDIMENT ALGORITHMS
       Following is a summary of advective processes between air and surface water, and
algorithms used to calculate phase flow velocities:

       Dry deposition of particles to surface water (solid phase):

                                       A         n 7                         — -
                             Tdd     __ nairsw     Pa ^ solid
                                     -  v    Vd    7
                                        Vair      Pp^total
where:
        Tair-w =     advective transfer factor of particles from air to surface water (I/day)
       Aa!rsw  =     area of surface water (m2)
        Vair    =     volume of air compartment (m3)
        \>d     =     dry deposition velocity of particles (m/day)
       pa     =     atmospheric dust load in air compartment (concentration of dust in air) (kg
                     [particles]/m3 [atmosphere])
       p,j     =     density of air particles (kg [particles]/m3 [particles])
       ^sohd   =     fugacity of the solid phase (Pa)
       Zlola,   =     total fugacity (Pa).

        Wet deposition of particles to surface water (solid phase):

                                      A           o Z
                            Twd  ^    a.™ ^     Va  sohd
                            1 fl/r-MW    y        d n  7
                                      V air         Pp^ total

where:

        Tair-sw =     advective transfer factor of wet particles from air to surface water (I/day)
       Aairw  =     area of surface water/air interface (m2)
        Vair    =     volume of air compartment (m3)
        Wetd  =     wet deposition velocity of particles (m/day)
       pa     =     atmospheric dust load in air compartment (concentration of dust in air) (kg
                     [particles]/m3 [atmosphere])
       pr     =     density of air particles (kg [particles]/m3 [particles])
       Zw/:j   =     fugacity of the solid phase (Pa)
       ZIIMal   =     total fugacity (Pa).

Additionally, there is advective flux from rainfall. As the rain falls, it gathers chemical from the
air, coming into equilibrium with the fugacity of the air compartment.
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CHAPTER 4
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Advective flux from rainfall:
                     ^
si  /  ;j  \  A          water  xr
flux(g/day)=A   --  N
•>    v°   J '   I]   -IT   -y      a
                                           -IT
                                           V i     Total
                                T  (rain}=A
                                 /-;v       IJ
                                              V   7
                                                /   ^ Total
where:
       Rain   =      rainfall rate (m/day)
       Na     =     total mass of chemical in the air compartment (g)
       Zwaler   =     fugacity of the water phase (Pa)
       ZMal   =     total fugacity (Pa).

4.2.2  ADVECTIVE PROCESSES BETWEEN SEDIMENT AN D SURFACE WATER

       The two advective processes between sediment and surface water involve the transport of
the chemical from the surface water to the sediment or from the sediment to the surface water via
movement of sediment particles. "Sediment deposition" refers to the transport of the chemical
from the surface water to sediment, and "sediment resuspension" refers to the reverse process.
Both processes involve only the solid phase.

       Following is a summary of advective processes between sediment and surface water, and
algorithms used to calculate phase  flow velocities:

       Deposition of suspended sediment to sediment bed (solid phase):
                            -d     _   swsed   dep   so                               , . .,
                             S*->s
                                       V SH<   K
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                                                                              CHAPTER 4
                                                    SURFACE WATER AND SEDIMENT ALGORITHMS
       Resuspension of sediment to surface water (solid phase):


                                              e   7
                                             O .  L, „
                             y. r        ~~jfaitv ~r  ^ olid
                                       V     n   7
                                       v sed  Pfcj  ^w/a/

where:

       Tsed-sw ~     advective transfer factor for resuspension of sediment to surface water
                    (I/day)
       Asedsw  =     area of surface water/sediment interface (m2)
       Vsed    =     volume of sediment compartment (m3)
       Sr     =     resuspension rate of benthic sediment to water column (kg [benthic
                    sediment]/m2 (area)-day)
       pbs     -     density of benthic sediment (kg  [benthic sediment]/m3 [benthic sediment])

       Zsolld   =     fugacity of the solid phase (Pa)
       Zlolai   =     total fagacity (Pa).

4.2.3  ADVECTIVE PROCESSES BETWEEN SEDIMENT/SURFACE WATER AND
       ADVECTIVE SINKS

       The surface water advection sink represents outflow of the chemical from the study area.
For sediment, the advection sink represents the burial of the chemical beneath the sediment layer.

       Burial is calculated so that the net flow of sediment into the sediment layer is zero.  That
is, there is no loss of sediment mass due to burial, only loss of pollutant. This is done by setting
the amount of sediment buried equal to the sediment deposition rate minus the sediment
resuspension rate, both of which are specified input parameters. If the resuspension rate is larger
than the deposition rate, then the burial flow is set to 0. A more sophisticated approach may be
implemented in which the sediment layer depth could change, depending on the deposition and
resuspension rates. Further, the deposition rates can be calculated to correspond to the suspended
sediment concentration, which could change depending on the erosion of soil to the water body
and the outflow.

       Following is a summary of advective processes between sediment/surface water and
advective sinks, and algorithms used to calculate flow  velocities:

       Outflow from surface water to surface water advection sink (total phase):


                                                                                  (4-6)
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CHAPTER 4
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where:
Outflow
                          outflow of water from surface water compartment to advection
                          sink (m3/day)
                          volume of surface water compartment (m3)
      Resuspension of sediment to surface water (solid phase):

                                  \     S     A      f  ^ 7
                    'T total
              ;;;;; = max  o,-
                                Pa
                                               sed
                                                   Pbs )
                                                                                (4-7)
where:
       p total
       ' seds\v
       A
        .secMr
       Pbs
       Pss
       7
       ^lotal
                   net advective transfer factor for deposition and resuspension of
                   sediment to surface water (I/day)
                   area of surface water/sediment interface (m2)
                   volume of sediment compartment (m3)
                   resuspension rate of benthic sediment to water column (kg [benthic
                   sediment]/m2 (area)-day)
                   density of benthic sediment (kg [benthic sediment]/m3 (benthic
                   sediment])
                   volume of surface water compartment (m3)
                   deposition rate of suspended sediment to sediment bed (kg
                   [suspended sediment]/m2 (area)-day) (Mackay et al. 1983b; use
                   0.096 mVhr for a lake of volume 7 x 10"6 m)
                   density of suspended sediment (kg [suspended sediment]/m3
                   [suspended sediment])
                   fugacity of the solid phase (Pa)
                   total fugacity (Pa).
4.3    DERIVATION OF RIVER COMPARTMENT TRANSFER FACTORS

       The transfer factor from one river compartment to another, or to a lake compartment, was
derived based on advective flow rates of a total pollutant mass between two compartments as
developed in Section 2.3.1. By substituting river flow velocity for the total volumetric flow
velocity, the following transfer factor is derived.

       Advection from one river compartment to another river or lake compartment:

                                                                               (4-9)
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                                                  SURFACE WATER AND SEDIMENT ALGORITHMS
where:

       utj     =     annual averaged river flow between river compartments / and/ (m/day)
       A     =     area of interface between compartments / and/ (m2)
                   volume of compartment / (m ).
Because advection is being simulated for the total phase, no phase partitioning is applied in this
equation.

4.4    DISPERSIVE PROCESSES

4.4.1   DISPERSIVE TRANSPORT BETWEEN SURFACE WATER COMPARTMENTS

       Dispersive transport between water compartments can be approximated  as a first order
process using the method describe in the WASP water quality simulation program (Ambrose et
al. 1995). Dispersive water column exchanges significantly influence the transport of dissolved and
particulate pollutants in such water bodies  as lakes, reservoirs, and estuaries.   Even in rivers,
longitudinal dispersion can be the most important process diluting peak concentrations that may
result from unsteady loads or spills.

       Based on the WASP model, the dispersive exchange flux  between two surface water
compartments / and/ at time is modeled by:

                                H  • A
                              *, jL/    yi

                                                                             (4-10)
where:

       F,^   =     dispersive flux from water compartment / to water compartment j (mass
                   [chemical]/day)
       C,, Cj  =     concentration of chemical in water compartments / and j (g/m3)
       M,, Mj =     mass of chemical in water compartments i and/ (g/m3)
       Ey    =     dispersion coefficient for exchange between water compartments / and/
                   (m2/day)
       A,!    =     interfacial area between water compartments / and/ (m2)
       Ly    =     characteristic mixing length between water compartments / and/ (m)
       Vt     =     volume of compartment / (nr)
       Vt     ~     volume of compartment/(nr').

       The distance between  the  midpoints of the two water compartments is used  for the
characteristic mixing length. Values for dispersion coefficients can range from 10"'° nr/sec (8.64x

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10"6 m2/day) for molecular diffusion to 5xl02 m2/sec (4.32x107 m2/day)for longitudinal mixing in
estuaries (Ambrose et al. 1995, p. 35). A value of 2.25X10"4 nr/day is chosen as the default value;
this is median of the range cited in Ambrose et al. (1995) (p. 112) from a study of Lake Erie
conducted by Di Toro and Connolly (1980).

4.4.2  DISPERSIVE TRANSPORT BETWEEN SURFACE WATER AND SEDIMENT
      COMPARTMENTS

      As for dispersive transport between surface water compartments, dispersive transport
between surface water and sediment compartments is approximated as a first order process using
the method described in the WASP water quality simulation program (Ambrose et al. 1995).

       Based on the WASP model, the net dispersive exchange flux between a surface water
compartment / and sediment compartment j is modeled by:


                                                 fnC,'

                                                                               (4-11)
where:

       Fj. ,   =      Net dispersive flux between surface water compartment  / and sediment
                    compartment j, mass[chemical]/day
       C,,Cj =      Bulk concentration of chemical in surface water compartment /and
                    sediment compartment j mg/L (g[chemical]/m3[compartment])
       M,, Mj =      Mass of chemical in surface water compartment i and sediment
                    compartment j (mass[chemical])
       Ev    =      Dispersion coefficient for exchange between compartments / andy, m2/day
       Ay    =      Interfacial area between compartments i and j, m2
       Ly    =      Characteristic mixing length between compartments / andy, m
       V,, Vj =      volume of compartments / andy, m3
       foi-fpi =      dissolved fraction of chemical in compartments / and/ (calculated)
       n,, rij  -      porosity of compartments z andy
       riy    =      average porosity at interface ( (n, + n)/2 )

       The resulting transfer factors (units of /day) between the surface water / and sediment
compartmenty are given by:
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                                                   SURFACE WATER AND SEDIMENT ALGORITHMS
                             T  -  	'L
                                     LJn,J
                                               fD,
(4-12)
                                                                               (4-13)
Following the method used in WASP (Amborse et al., p. 25), the sediment compartment height is
used as the characteristic mixing length L .  The porosity of the sediment compartment («,) is
calculated from the specified benthic solids concentration and solids density.  The porosity of the
surface water compartment is set to the volume of water compartment that is water.  Values for
dispersion coefficients can range from 10"'° m2/sec (8.64xlO~6 mVday) for molecular diffusion to
5xl02 mVsec (4.32xl07 m2/day)for longitudinal mixing in estuaries (Ambrose et al. 1995, p. 35).
A value of 2.25e-4 m2/day is chosen as the default value; this is median of the range cited in
Ambrose et al. 1995 [p.  112] from a study of Lake Erie conducted by DiToro and Connolly
(1980).

       4.5   DIFFUSIVE PROCESSES

       4.5.1  DIFFUSIVE EXCHANGE BETWEEN SURFACE WATER AND AIR

       The algorithms describing the diffusive exchange of chemical mass between surface
water and air are presented in Section 3.3.2.
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                                                                            CHAPTER 5
                                                                       SOIL ALGORITHMS
5.     SOIL ALGORITHMS

       In this chapter the algorithms for the transport and transformation of chemical species
within and among soil compartments and between the soil compartments and the lower
atmosphere and between the soil compartment and surface water are presented.  The text box on
the next page and continued on the following pages provides a quick summary of tfie algorithms
developed in this chapter and provides a definition of all parameters used.

5.1    INTRODUCTION

       Two of the primary processes in subsurface soil are exchange by diffusion and advection.
These are key components of the overall rate constant. The transport occurs both in the  gas and
liquid phase for organic chemicals.  The predominant transport mechanism in the aqueous phase
is advection, and that in the gas phase is diffusion. The advective transport of contaminants in
the liquid or gas phase is dependent on the velocity of that phase. In this application, the total
contaminant mass is estimated for each soil compartment. Important physicochemical properties
include solubility, molecular weight, vapor pressure, and diffusion coefficients in air and water.
The important landscape properties include temperatures of air, rainfall rates, soil properties
(bulk density, porosity), and depth of each soil compartment.

       There are three advective processes considered in the prototype that can potentially
transport a chemical from a soil domain to surface water: erosion of surface soil, runoff from
surface soil, and recharge from ground water. Erosion applies to the solid phase, while runoff
and recharge applies to the dissolved phase.

5.2    SOIL  COMPARTMENTS AND TRANSPORT PROCESSES

       In the TRIM.FaTE model, soil is modeled as three distinct compartment  types — surface
soil, rooting-zone soil, and vadose-zone soil above the saturated zone. In TRIM.FaTE these
three regions can be sub-divided into one or more compartments for the  purpose of assessing
mass transfer. Among these compartment types there are two kinds of transport considered —
diffusion and advection. In addition, the uppermost surface soil compartment exchanges mass
with the lowest compartment of the atmosphere by a combination of diffusion and advection
processes.

5.3    TRANSFORMATIONS IN SOIL COMPARTMENTS

       The transformation of contaminants in soil layers can have a profound effect on their
potential for persistence. Chemical transformations, which may occur as a result of biotic or
abiotic processes, can significantly reduce the concentration of a substance. For all chemical
reactions, knowledge of a compound's half-life for any given transformation process provides a
very useful index of persistence in environmental media. Because these processes determine the
persistence and form of a chemical in the environment, they also determine the amount and type
of substance to which a human or ecological receptor could be exposed.  In the TRIM.FaTE soil
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CHAPTER 5
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              Summary of Transport Algorithms Developed in this Chapter
 Lowest air compartment to upper surface soil compartment:

  r_. =
U^xArea,  xZair
               V xZ
                 a    a
 First soil compartment to lowest air compartment.
  TV   =
 Downward flow from soil compartment /to soil compartment/
  r   _      ,
   '->'    dZ
 Upward flow from soil compartment./ to soil compartment /:

           Y.
  T    =
       ~
 Horizontal runoff from compartment /to compartment/

  T,^, (runoff) = Runoff x frun (ij) x Z, (rain) I (Z,d, *)
 where
 Area   =
       mass transfer coefficient on the air side of the air/soil boundary, m/d (It is typical to
       represent the mass transfer coefficient in air as ratio of the diffusion coefficient in
       air, Dair, divided by the turbulent boundary compartment thickness, 6air. For many
       compounds, Da,r is on the order of 0.4 m/d and 6air is on the order of 0.0005 m, so
       that Uair is on the order of 800 m/d.)
       horizontal area of the soil compartment, m2  (This is the area assumed to be shared
       between  the top soil compartment and the atmosphere: and between any two
       adjacent  soil compartments)
       volume of the air compartment, m3.
       fugacity capacity of pure air, = 1/RT, mol/(m3-Pa)
       total fugacity capacity of the air compartment (includes gas and particle phase of
       the atmosphere), mol/(m3-Pa).
       fugacity capacity of air particles, mol/(m3-Pa).
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            Summary of Transport Algorithms Developed in this Chapter (cont.)
  Vd     =        air-to-soil deposition ratio, mol/m2/d per mol/m3 (includes only deposition that is not
                  intercepted by plants, and is calculated as the total deposition velocity times one
                  minus the plant interception fraction), ~ 400 m/d.
  PC     =        particulate matter concentration in air, ~ 6.0 x 10"8 kg/m3.
  pp     =        density of particulate matter in air, ~ 2600 kg/m3 (Wilson and SpenglerT996).
  rain    =        rate of rainfall, m/d.
  Zwater   =        fugacity capacity of the moving phase, water, mol/(m3-Pa).
  Area,   =        area of contact between the surface soil compartment and the lowest air
                  compartment, m2.
  Z,      =        total fugacity capacity of soil compartment /, mol/(m3-Pa).
  Zs,     =        fugacity capacity of soil compartment /', mol/(m3-Pa),
  d,      =        thickness of soil compartment;', m.
  YtJ     =        fugacity-capacity adjusted mass transfer coefficient between compartments / and j,
                  mol/(m2-Pa-day), and is given by:


                             y =•
  De,     =        effective diffusion coefficient in soil compartment /, m2/d.
  ve,     =        effective advection velocity of a chemical in the soil compartment /, m/d, and equal
                  to the rate of soil-solution movement, v,, multiplied by the fugacity capacity of soil
                  compartment /; ve, = vZ^JZ,.
  v,      =        average velocity of the moving phase (assumed to be water) in the soil
                  compartment/, m"1.
  Y,      -        gradient of soil concentration change in soil compartment /, m"1. Obtained from the
                  inverse of the  normalized or characteristic depth X*, that is y, = 1/X*
                  X* is obtained as follows:
                       If X, > 0 then X* = Minimum (DX,, DX2)
                              Otherwise, if A, = 0, then X* = DX2.

                       DX, is the Damkoehler distance (the distance at which the soil concentration
                       falls by 1/e based on the competition among diffusion, advection, and
                       reaction) and is given  by:
                                        ve + Jve, + 4De
                                DX,=—  ^
                                     i
                                                2A,.
                       DX2 is the depth that establishes the concentration gradient in soil in the
                       absence of any reaction or transformation processes.  It is obtained as
                       follows:

                              If ve, > 0, then DX2 = Minimum (4De/ve,, DXsat)
                              If ve, = 0, then DX2 = Minimum (2d,, V(n), DXsat)
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           Summary of Transport Algorithms Developed in this Chapter (cont.)
 A,       =     removal rate constant for a chemical in soil compartment, based on chemical
               transformation, day"1.
 Respnd -     rate at which dust is resuspended from the soil surface, kg/m2/d.
 Ps,      -     density of dust particles, kg/m3.                                   _  _
 a      -     volume fraction of the soil compartment that is gas, unitless.
 /?      =     volume fraction of the soil compartment that is water, unitless.
 

= a + (3 Rh - hydraulic radius of water flowing over surface soil during a rain event, assumed to be 0.005 m. d, - depth of surface soil compartment during periods of no rain, m. d* - effective depth of saturated surface soil during a rain event, m, d,* = Rh + d, Runoff - flux of water transported away from surface soil compartment/, m3/m2-day. frun(ij) ~ fraction of water that runs off of surface soil compartment / that s transported to compartment;, unitless. NOVEMBER 1999 5-4 TRI M.FATE ISO VOLUME II (DRAFT)


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_ SOIL ALGORITHMS

layers, all transformation processes are modeled as first-order processes; that is, linear with
inventory (i.e., the quantity of chemical substances contained in a compartment). The rate of
mass removal in a first-order transformation is calculated as the product of the total inventory
and the transformation rate constant. The transformation rate constant is the inverse of the
residence time with respect to that reaction.

5.4    VERTICAL TRANSPORT ALGORITHMS

       The transfer factors in the subsurface are a function of the advective flux (gas phase plus
liquid phase) and the diffusive flux (gas phase plus liquid phase). In the sections below, upward
and downward transfer factors are developed for the soil compartments. No provisions are made
for preferential flow regions in the vadose zone that could lead to higher concentrations in the
ground water because in most cases, the proportion of exposure from ground water is minimal
for air  pollutants.

5.4. 1  THEORETICAL BASIS FOR THE TRANSPORT ALGORITHMS

       The algorithms below are developed by assuming that chemical concentration in each
compartment decreases exponentially with depth in that compartment.  This type of
concentration gradient has been demonstrated as the correct analytical solution of the one-
dimensional, convective-dispersive, solute-transport equation in a vertical layer with a steady-
state concentration maintained at its upper surface (ARS 1982). With the assumption of
exponentially decreasing vertical concentration for each soil compartment, /, the variation in
concentration with depth in that compartment is given by:
                                   = C1(0)exp(-y,A:)                             (5-1)

where:

       x      =     distance into the soil compartment measured from the top of the soil
                    column (m);
       C,(0)   -     peak chemical concentration in soil compartment i (mol/m3), which is
                    related to the total inventory A', (moles) in this soil compartment (this
                    relationship is provided below):
       Y,      -     the gradient of soil concentration change in soil compartment / (m"1), and
                    is obtained from the inverse of the normalized or characteristic depth X*,
                    that is Y, = 1/X*.

              X* is obtained as follows:

                    If A, > 0 then X* = Minimum (DX,, DX2)
                           Otherwise, if A, = 0, then X* = DX2.                        (5-2)

                    DX, is the Damkoehler distance (the distance at which the soil
                    concentration falls by  1/e based on the competition among diffusion,
                    advection, and reaction)  in units of meters and is given by:

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                                   ve, + Jve,
                                         ^-                           (5-3)
                    DX2 is the depth that establishes the concentration gradient in soil in the
                    absence of any reaction or transformation processes, in units -of meters. It
                    is obtained as follows:

                           If ve, > 0, then DX2 = Minimum (4De,/ve,, DXsat)
                           If ve, = 0, then DX2 = Minimum (2d,, V"(n), DXsat)            (5-4)
       ve,     =     the effective advection velocity of a chemical in the soil compartment, /
                    (m/day), and equal to the rate of soil-solution movement, v,, multiplied by
                    the fugacity capacity of the moving phase and divided by the fugacity
                    capacity of soil compartment /;

                                     ve>, = v,ZMUK/Z,                                 [5-5]

       v,      =     the average velocity of the moving liquid phase (assumed to be water) in
                    the soil column / (m/day);
       DXsal  =     depth to saturation in the soil column (m);
       d,      =     the thickness of soil compartment / (m);
       Zwaler  =     the fugacity capacity of the moving phase, water (mol/[m3-Pa]);
       Z,      =     the total fugacity capacity of soil compartment / (mol/[m3-Pa]);
       2,      =     removal rate constant for a chemical in soil compartment /, based on
                    chemical transformation (day"1); and
       De,    =     effective diffusion coefficient in soil compartment / (nr/d), and is derived
                    below.

       Compartments such as soils and sediments are neither homogeneous nor single phase.
When air and water occupy the tortuous pathways between stationary particles in a porous
medium such as a soil or sediment, Millington and Quirk (1961) have shown that the effective
diffusivity, Defr, of a chemical in each fluid of the mixture is given by:

                              Dtff =(a>lon/4r)D_                              (5-6)

where co (a for gas fraction and ft for water fraction) is the volume fraction occupied by this
fluid, (p is me total void fraction in the medium (the volume occupied by all fluids) , and Dplire is
the diffusion coefficient of the chemical in the pure fluid.  Jury et al. (1983) have shown that the
effective tortuous diffusivity in the water and air of a soil compartment, such as the root-zone
soil(s),  is given by:
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                                                                          CHAPTER 5
                                                                     SOIL ALGORITHMS
                                   )D8ir
                                                    )DW
                                                                              (5-7)
where De, is the effective tortuous, mixed phase diffusion coefficient in the root-zone seil
compartment, the Z's are the fugacity capacities derived previously.

5.4.2  RELATIONSHIP BETWEEN INVENTORY, Nw AND PEAK CONCENTRATION,
      The assumptions of a peak chemical concentration and an exponential gradient of
chemical concentration within a soil compartment makes it possible to define C,(0) in terms of
N-
                             ,
                 N, =  Area, Jc,(0)exp(-7(jt)djc
                                                                              (5-8)

                                                                              (5-9)
where:
N,     -
C,     =
d,     =
Area   =
                   compartment inventory (mol)
                   compartment-eoncentration (mol/m3)
                   thickness of soil compartment / (m); and
                   horizontal area of the soil compartment (m2).
Rearranging the right term of Equation 5-9 gives:
                 C (0) =
                                        Nj
                                                                             (5-10)
5.4.3  VERTICAL MASS EXCHANGE BETWEEN AIR AND THE UPPER SURFACE
      SOIL COMPARTMENT

      The algorithm for representing diffusion exchange at the air/soil interface is based on
defining the flux from air to soil in terms of the concentration gradient at the point of contact
between air and soil.
                        Flux = U
                                    Cair-C.(QY
                                                                       (5-11)
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where:

       Uair    =     mass transfer coefficient on the air side of the air/soil boundary (m/d) (It
                    is typical to represent the mass transfer coefficient in air as the ratio of the
                    diffusion coefficient in air, Da^ divided by the turbulent boundary
                    compartment thickness, 6air. For many compounds, Dair is on-the-order of
                    0.4 m/d and 6air is on the order of 0.0005 m, so that Uair is on the order of
                    800 m/d.)
       Cair    =     bulk concentration of chemical agent in the lowest compartment of the
                    atmosphere, mol/m3 and given by Cair = Na Za,/[Va ZJ, where Na is the
                    inventory (in mol) of the air compartment above the soil, Za:r is the
                    fugacity capacity of pure air, Va is the volume (in m3) of this compartment,
                    and Za is the total fugacity capacity of the air compartment (includes gas
                    and particle phase of the atmosphere).
       C,(0)   =     chemical concentration at the top of the uppermost soil compartment in a
                    vertical set of soil compartments, ml/m3, as given by Equation 5-6.  There
                    can be several vertical soil compartment sets in a model run.
       Zair    =     fugacity capacity of pure air, = 1/RT, mol/(m3--Pa).

Making the appropriate substitutions, the net flow of mass between air and soil by diffusion is
calculated as:
Net Diffusion Flow (a<->f) (mol/day)
     = Flux x Area, = U
          Areat x Zt
            V. xZ.
•N
                                                         7,
                                                                    Z
•N
(5-12)
       It is important to note that the area used to calculate the flux is Area,, the surface area of
the soil compartment / that is shared with the lowest atmosphere corrpartment. This is not
necessarily the surface area of the lowest atmosphere compartment.

For dry and wet deposition of particles from air to soil, the rate of mass flow is given by:

Particle Advection Flow (a-*i) (mol/d)

                    = Vd(PCIpp}(AreaiIVa}(ZapIZa]Na                     (5-13)

where:
       V
       PC
air-to-soil deposition ratio (includes only deposition that is not intercepted
by plants, and is calculated as the total deposition velocity times one
minus the plant interception fraction (mol/m2/d per mol/m3) ~ 400 m/d;
particulate matter concentration in air ~ 6.0 x 10"8 kg/m3;
density of the particulate matter in air ~ 2600 kg/m3;
NOVEMBER 1999
                      5-8
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                                                                            CHAPTER 5
                                                                       SOIL ALGORITHMS
       Area,  =      area of contact between the surface soil compartment and the lowest air
                    compartment (m2); and
       Va    =      volume of the air compartment (m3).

       For rainfall, the advection flow of chemical from air to the upper surface soil
compartment is given by:                                                  —  -
Rain Advection Flow (a ->/') (mol/d)

                       = rain[ZwalerIZa][Areai/Va]Na

where:

       Zwaier  =    fugacity capacity of pure water (i.e., no suspended sediments)
       Za     =    fugacity capacity of the air compartment (mol/nr'-Pa)
       rain   =    the rate of rainfall (m/d).

       For re-suspension of dust from the first surface soil compartment to the lower
compartment of the atmosphere, the chemical flow from soil to air is given by:

Advection Flow (/' ->d) (mol/d)
where:
       Respnd
       A,
                   = [Respnd/p,l}[ZJZl][ArealIVtt}Nt
                    rate at which dust is resuspended from the soil surface
                    (kg/m2/d); and
                    density of the dust particles (kg/m3).
                                                                         (5-14)
                                                                         (5-15)
       Combining Equations 5-12 through 5-15 provides the following transfer-rate factors for
the exchange of chemical species between the lowest atmosphere compartment and the surface
soil compartment:
                                                                               (5-16)


UairxAreaixZair~
V xZ
a a
,{,
PC
_pp _
1X1
LZJ
+ rain
7
water
. zfl
Ix
J
Area:
va
r... =
u . r
air / i
_[l-exp(-yl.rf,)]_
x,~
Z5
+
Respnd
P»
"Z/
Z, _
X
Ar^a,
Vfl
                                                                               (5-17)
NOVEMBER 1999
                                   5-9
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CHAPTER 5
SOIL ALGORITHMS
5.4.4  VERTICAL MASS EXCHANGE BETWEEN TWO VERTICALLY ADJACENT
      SOIL COMPARTMENTS

      The vertical exchange of a chemical substance between two vertically adjacent soil
compartments occurs through advection and diffusion. Only the net advection in the downward
direction is considered due to long-term infiltration of rainwater.  According to Equation 5-1, the
concentration in each soil compartment i is given by:

                    Ct(x) = C,(0)exp(-7(j:)                    (same as 5-1 above)

where x is measured from the top of the soil compartment /'. Thus, the diffusion flow at the lower
boundary of soil compartment / to compartment/ is given by:
       diffusion flow = -Area xDet-
                                  dC
                                                                          (5-18a)
                                      d.
                                  dx

where:

      De,   -     effective diffusion coefficient in soil compartment /', m2/d
      d,     =     the thickness of soil compartment i, m;

Conservation of mass requires that flow specified by equation 5-18 out of compartment / must
equal the flow into compartment/ at the upper boundary of compartment/, that is:

                                    dC
       diffusion flow = -Area X  De —
                                   1 dx

Combining equations 5-18a and 5-18b gives:
                                          = AreaxDe XC (Q)xy        (5-18b)
                             [pe,xC.(0)xY.«-*-+Pe,xC,(0)XY,]  "
    diffusion flow = Area x-	l    ;

C,(0) is found from the condition:

                                             c (fn   ,
                                                                           (5-20)
                       o

Rearranging gives:
                         C(0) =	7Jj	77T                          (5-21)
                                 Areax(\-e-''d')
NOVEMBER 1999                           5-10            TRIM.FATETSD VOLUME II (DRAFT)

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                                                                            CHAPTER 5
                                                                       SOIL ALGORITHMS
In order to conserve concentration equilibrium at the boundary between two soil compartments,
the following condition must hold:
                                                      xe
                       7   |V~'-        7
                       Li                ^i

Substituting equations 5-21  and 5-22 into equation 5-19 gives
                                                                               (5-22)
diffusion flow -
Then in order to express mass transfer between two compartments, the diffusion flow is
represented in the following form:
                                                                               (5-23)
                   diffusion flow = Area xY
                                                N
                                                                  (5-24)
where:
       Y(J    =      fugacity-capacity adjusted mass transfer coefficient between compartments
                    z and j, mol/(m2-Pa-day).
N the total inventory in compartment y is given by:
N =
                                      = Areax
                                                C,(0)
                       (5-25)
Substituting equation 5-23 in equation 5-25 gives:
             N .= —
                                                                               (5-26)
An expression for 7y is obtained by substituting equation 5-26 for NJ in equation 5-24 and then
setting equation 5-24 equal to equation 5-23:
                                             N
                                             y
   ,x('-
                                                 ,4
                                                                    +J'd>
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CHAPTER 5
SOIL ALGORITHMS
Rearranging gives:
2
~ ( +Y
(e
'•-0
(l-^V0~
YA Y/,
                                                                                (5-28)
The definition of YtJ in equation 5-28 completes the definition of all terms in equation 5-24.

The advection flux from soil compartment i toy at the lower end, d,, of compartment / is given
by:
           advection flow(i to j) = Area x vet x C(
where:
       ve.
                                                            (5-29)
the effective advection velocity of a chemical in the soil compartment, /;
m/d, and equal to the rate of soil-solution movement, v,, multiplied by the
fugacity capacity of the moving phase and divided by the fugacity capacity
of soil compartment /;

            _  ve:  - V|  *

the average velocity of the moving phase (assumed to be water) in the soil
                    compartment, /; m .

Substituting Equation 5-21 for C,(0) in Equation 5-29 gives:
                     advection flow(i to jj =
                                                            (5-30)
Combining Equations 5-24 and 5-30 and multiplying by Area,, gives the flow from / toy as:

          net total flow (mol/d) (/ toy) = [net diffusion flow + advection flow] (i toy)

                                \
                    N
1 V   \ = T. .  N
                                                                 N
                                                                 "
                                                            (5-31)
NOVEMBER 1999
                     5-12
                 TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                              CHAPTER 5
                                                                        SOIL ALGORITHMS
From this equation, we can derive terms for T, ^ and T}.
                           T    =+_                           (5.32)
                             -    dZ
                                           Y
                                  T    = ——                                  (5-33)
                                         dJZJ
5.5    STORM WATER RUNOFF PROCESSES

       Horizontal transport processes included in TRIM.FaTE include solution runoff and
erosion.

5.5.1   AQUEOUS PHASE TRANSPORT PROCESSES

       During a rainfall event, some of the water travels laterally across the soil as runoff. As
the water travels over the soil, the concentration of the water approaches that of the soil pore
water beneath it.  Although the water flowing over the soil does not necessarily reach equilibrium
instantaneously, some researchers use an approximation that runoff is in equilibrium with the soil
pore water (Wallach et al. 1989).  Currently in TRIM.FaTE, a steady-state relationship between
the runoff water and the pore water is used. Runoff water is considered a phase of surface soil
compartment at each spatial location. A mass-balance approach is used to determine the
concentration in run-off water that moves from one soil compartment to a horizontally adjacent
compartment.

       Runoff transport is assumed to carry chemical from the surface soil compartment of one
land unit to the next.  During a rain event the surface soil compartment is assumed to be saturated
with rain water and this water is assumed to be in equilibrium with the soil solids on Jhe surface.
It should be recognized that at times (e.g., short rain events, during very dry periods of the year)
the soil will not necessarily be fully saturated with rain water. However, the assumption of
saturation by rain is not expected to have a large impact on results for events when the soil is not
saturated.  Moreover,  a lack of information on the extent to which soil is saturated during rain
makes this a convenient starting point. The assumption of that chemical equilibrium has more
uncertainty and needs further research. During periods of no rain, the fugacity capacity of the
surface soil compartment is given by:

                       Z, =aZuir+/3Zlia/fr+(l-0)Zs,                        (5-34)

During periods of rain, the fugacity capacity of the surface soil compartment is given by:

              Z,(rain) = [(Rh+dl)Zlialer + (I - d, )Z J / d, *               (5-35)


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CHAPTER 5
SOIL ALGORITHMS
where:

       Zwaur   ~     fugacity capacity of pure water (i.e., no suspended sediments)
       Zs,     =     fugacity capacity of the solids (or solid phase) in the ith soil layer (mol/m3-
                    Pa)
       a      =     volume fraction of the surface soil that is gas;             —  -
       P      =     volume fraction of soil that is water;
       (f)      =     total void fraction in surface soil, (f) = a + /?;
       Rh     =     hydraulic radius of the water flowing over the surface soil during a rain
                    event, assumed to be 0.005 m;
       d,      =     depth of the surface soil compartment during periods of no rain (m); and
       d*     =     effective depth of the saturated surface soil during a rain event (m),
                    d,*=Rh + dr

       The hydraulic radius, Rh, for flow of water on top of the soil surface is site specific and
depends on the hydraulic gradient (slope of the flow), the rainfall rate, and the recharge rate.  It is
considered an uncertain variable, but is assigned a default value of 0.005 m. A hydraulic balance
is needed to determine the flow of the water and the depth of the runoff stream.  From the
Geographic Information System (GIS) data, the runoff is estimated.

       During a rain event, the horizontal flow of chemical from surface soil compartment / to
adjacent compartment 7 is given by:

        Runoff flow (i -> j) = Runoff  x  frun(i ->  j^Z^rain} /Zjd t *         (5-36)

where:
       Runoff       =      flux of water that is transported away from surface soil
                           compartment / (m3/m2-day); and
       frunft ~*J)      =      fraction of water that runs off of surface soil compartment / that is
                           transported to compartment 7 (unitless).

From Equation 5-36, the expression for T, ^(runoff) can be obtained:

           T,^ (runoff ) = Runoff X frun (i ->  ;) x Z, (rain)/(Zldl *)            (5-37)

5.5.2  SOLID PHASE  TRANSPORT PROCESSES

       The algorithm for erosion runoff is based on knowledge of the erosion factor for the
region being modeled. Similar to solution runoff, erosion is also applied only to the surface soil
layer.  Although  erosion  is most likely to occur during rain events, erosion can be modeled as a
continuous event. The flow of chemical (mol/d) from one surface soil compartment to another
by erosion is represented by the following expression:

                Erosion flow (i->j) = erosion xfcro (i->j) *  ZW/Z, x N,/ (p^d)           (5-38)


NOVEMBER 1999                             M4             TRIM. FATE TSD VOLUME II (DRAFT)

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                                                                                 CHAPTER 5
                                                                           SOIL ALGORITHMS
where:

       erosion       =      erosion factor (kg of soil solids eroded per day per m2);
       ferofi ~J')       =      fraction of soil eroded from surface soil compartment / that is
                            transported to compartment y (unitless);
       ZSI            -      fugacity capacity of the soil particles in soil compartment/ (mol/
                            [m3-Pa]);
       psl            =      density of the soil particles,-2600 kg/m3.

From Equation 5-36, the expression for T^(erosion) can be obtained:

                      T_.,/erosion) =  erosion *fji~>j) x ZSI/(Z, psl d)                [5-39]
NOVEMBER 1999                              5-15              TRIM.FATE TSDVOLUML II (DRAFT)

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                                                                                  CHAPTER 6
                                                                   GROUND WATER ALGORITHMS
6.     GROUND WATER ALGORITHMS

       The horizontal flow of pollutants in the saturated zone (ground water) is not expected to
be a significant pathway when considering air pollutants.  Transport has been simulated because
it is a more significant process than diffusion/dispersion.  In the prototype, ground water is
modeled as a receiving cell from the vadose zone and a sending cell to surface water.  The
transfer factors for soil to ground water and for ground water to surface water are based on the
aqueous phase advection only by substituting recharge for flow velocity:
                     soihgrounawater         V         7
                                          soil         total
                                        grounder                                      „

                                                                                      ^    '
and
                                    A                  Z
                                      reroundwater surfacewaler   water  n  ;   _
                    ,       ,         —2	J-	Recharge               (6-2\
               groundwater-surjacewater        i/-              ^           °                V" *•/
                                           groundnaler        total
where:
       A             =      cross section area between cells (m2)
       V             =      volume of cell (m3)
       Recharge     =      annual recharge into ground water (m/h).
NOVEMBER 1999                               6-1              TRIM.FATE TSD VOLUME 11 (DRAFT)

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                                                                             CHAPTER 7
	          BIOTIC ALGORITHMS

7.     BIOTIC ALGORITHMS

       In this section algorithms for transfers between a biotic compartment type and another
biotic or abiotic compartment type are presented. Algorithms are based on diffusive or advective
transfer, and most common instances of the latter are transfers via the wildlife diet. _Mqst
algorithms apply to all air pollutants, though some that involve octanol-water partition
coefficients are only applicable to organic chemicals and mercury species. Some of the equations
represent dynamic processes, and others are simple models for which a time-to-equilibrium is
calculated.  The text box on the next page and continued on the following pages provides a quick
summary of the algorithms developed in this chapter and provides a definition of all parameters
used. The derivation of chemical-specific algorithms and input parameters is presented in
Appendix A.

7.1    SELECTING THE BIOTIC COMPONENTS  OF TRIM.FATE

       The methodology for determining biotic compartment types is described in Section 3.3 of
Volume I of the Technical Support Document for TRIM.FaTE. All major trophic levels in
terrestrial and aquatic systems are represented.  Default, representative species are chosen based
on their prevalence  at the test location and/or the availability of parameters for them.  Additional
species may be chosen based on policy considerations, such as the Endangered Species Act.

       General algorithms for plants (Section 7.2.1). soil detritivores (Section 7.2.2), terrestrial
mammals and birds (Section 7.2.3) and aquatic biota (Section 7.3) are listed below.

7.2    ALGORITHMS FOR TERRESTRIAL AND SEMI-AQUATIC BIOTA

7.2.1   PLANTS

       The plant consists of four compartment types: leaf, stem, root, and the leaf surface
(particulate on leaf Lp).  Although the leaf surface is not in the plant, it is useful to track because:
(1) it is a reservoir of chemical moving to leaves and (2) wildlife diets include particylate matter
on leaves.

       Several problems arise in modeling uptake and emissions of chemicals by plants.

       Little information is available on the transformations of chemicals within plants.

       The volatilization of chemicals from soils and uptake by plant foliage  occurs at a scale
       that is not easy to model  in TRIM.FaTE.

       Little is known about the rate at which chemicals enter plant leaves from  particulate
       matter or rain water on the leaf surface.

       The transport of many chemical species within the plant is not well understood.
NOVEMBER 1999                             7-1              TRIM.FATE TSD VOLUME II (DRAFT)

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CHAPTER 7
BIOTIC ALGORITHMS
               Summary of Transport Algorithms Developed in this Chapter
  PLANTS

  Participate phase of air to surface of plant leaf (when no rain):

                V ,/  , Ar
    /-i             a   a  j
                   y

                   V A
 Surface of plant leaf to particulate phase of air (when no rain)1


   Lp-^fAp  ~    TT
                A

 Vapor phase of air to the leaf surface (during rain):


               1
  Particles in air to the leaf surface (during rain)
  Surface of leaf to surface soil (during rain)
  7^=57.6
  Leaf surface to leaf:


  T       -  k
  1 LP-+L  ~  * LP-L

  Leaf to leaf surface:
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                                                                            CHAPTER 7
                                                                     BIOTIC ALGORITHMS
          Summary of Transport Algorithms Developed in this Chapter (cont.)
 PLANTS (cont.)

 Leaf to air (diffusion):
                                      1    Z,
   ^A = (2LAI x As x gc + As x gs) x — x
                                     V    7
                                     V L   Ll
 Air to leaf (diffusion):
  T
           -ln(l-0.95)
                '0 95
 Root-zone soil to root.
 Root to root-zone soil:
    X
      parea R   K R_Sr
X
      pvolR     dsr
  T.
   r->Sr
            -ln(l-0.95)
                 t,
                  0.95

 Root-zone soil to stem:
  Tc
-xTSCF
 Leaf to stem:
 Stem to leaf:
               V
                Si   St-Xy
NOVEMBER 1999
                  7-3
                    TRIM.FATE TSD VOLUME II (DRAFT)

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CHAPTER 7
BIOTIC ALGORITHMS
            Summary of Transport Algorithms Developed in this Chapter (cont.)
 PLANTS (cont.)

 Leaf to surface soil (litterfall):

  T      -I
  1 t-»Si  ~ ^

 Leaf surface (paniculate matter) to surface soil (litterfall):

   T       =  L
   1 Lp-*Ss    ^
 where:

 VA      =    volume of air volume element (m3)
 va      =    dry deposition velocity of particles (m/d)
 ld      =    fraction of dry-depositing chemical that is intercepted by plant canopy
 As      =   soil area (m2)
 Jrain     =   rain rate (m/d)
 wr      =   washout ratio (mass chemical/volume rain - mass chemical/volume air)
 lw      =   interception fraction for wet deposition (unitless)
 kip-L    =   first-order rate constant for transfer of chemical from particles on leaf surface to leaf
 LAI     =   1-sided leaf-area index (m2 total leaf area / m2 underlying scil area)
 VL      =   volume of leaves (m3)
 Zp      ~   fugacity capacity (Z-factor) of chemicals in plant (mol-Pa"1nr3)
 ZL      -   fugacity capacity (Z-factor) of chemicals in leaf (mol-Pa~1nT3)
 gs      =   conductance of stomatajjiathway, including mesophyll (m/d)
 gc      =   total conductance of the"cuticular path, including the air boundary layer (m/d)
 ZA      =   fugacity capacity of chemicals in the vapor phase of air (mo!Pa"1m3)
 KR-sr    =   root-soil partition coefficient (wet kg/kg per wet kg/kg)
 pareaR =   areal density of root in root-zone soil (kg root fresh wt/m2)
 pvolR  -   wet density of root (kg/m3)
 dsr     =   depth of root-zone soil (m)
 Qxy     =   flow of transpired water in cell area (m3/d, below)
 TSCF  -   transpiration stream concentration factor  (mg/m3 of xylem per mg/m3 of soil pore water)
 VSrW    -   volume of water in root-zone soil (m3)
 Zwater   -   fugacity capacity (Z-value) for water
 2Sr     =   fugacity capacity (Z-value) for root-zone soil
 VSr     -   volume of root-zone soil volume element (m3)
 QP     =   phloem flux into fruit (m3/d), due to advection (assume 5 pe'cent of Q^, Paterson et al.
             1991)
 KLfhh    -   partition coefficient between leaves and phloem water (mass/vol to mass/vol)
 Qxy     =   flow of transpired water (m3/d)
 Vst     =   volume of stem (m3)
 Kst.Xy   -   partition coefficient between stem and xylem water (mass/vol to mass/vol)
 L      =   litterfall rate (d'1)
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                                                                                  CHAPTER 7
                                                                          Biouc ALGORITHMS
           Summary of Transport Algorithms Developed in this Chapter (cont.)
 SOIL DETRITIVORES

 Root-zone soil to earthworm:
  T
   Sr—tworm
               -ln(l-0.95)
                    [0.95
                         A
                                              worm—Sr
                                    Sr
  Earthworm to root-zone soil:
  ' K orrn —>5r
               -ln(l-0.95)
                   '095
  Root-zone soil to soil arthropod:
  T.
   Sr—>arth
              -ln(l-0.95)
'0 95
           xpareaar:h  x As x
                                                  • arlh-Sr
                                                   M
                                                     Sr
 Soil arthropod to root-zone soil:

              -ln(l-0.95)
  1 arth-tSr
 where:
                   [095
  IS
  ^
    areal density of earthworm community in root-zone soil (kg worm fresh wt/m2)
    wet density of earthworm (kg/m3)
    earthworm-soil partition coefficient (wet kg/kg per wet kg/kg)
    depth of root-zone soil (vsr/As)
    soil area (m2)
    arthropod-soil partition coefficient (wet kg/kg per wet kg/kg)
    total mass of root zone soil which contains arthropods  (kg)
    areal density of arthropod community in root-zone soil  (kg arthropod fresh
    wt/m2)
NOVEMBER 1999
                         7-5
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CHAPTER 7
BIOTIC ALGORITHMS
            Summary of Transport Algorithms Developed in this Chapter (cont.)
 TERRESTRIAL WILDLIFE

 Water to terrestrial vertebrate:

                           /,  x A,
        =par«flH./xAJ x
                            H1     H1
                               H


  Surface soil to terrestrial vertebrate:
                                     55      55
  Plant leaf to terrestrial vertebrate:

                        p p X I D X Ap
  Surface of plant leaf to terrestrial vertebrate'
  Earthworm to terrestrial vertebrate:


                                 '
                                  D
  Soil arthropod to terrestrial vertebrate:


                           /^X/DX
  Terrestrial vertebrate to terrestrial vertebrate
NOVEMBER 1999                               7-6              TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                                   CHAPTER 7
                                                                            BIOTIC ALGORITHMS
            Summary of Transport Algorithms Developed in this Chapter (cont.)
 TERRESTRIAL WILDLIFE (cont.)

 Fish to terrestrial vertebrate:

                              pf xID x
      K, = pareaw! x As  x
                              ASH. x pareaf

  Benthic invertebrate or flying insect to terrestrial vertebrate:
       MV, = parea wlxAs x
                              P BI x ID
                                         x
                               Asw x parea
                                             BI
Air to terrestrial vertebrate:

                                1
 TA_+wl = pareawl X  As  x-


Terrestnal vertebrate to surface soil:

 T      —  f   F
 i ,..i  vcc —  j uss £< u
                                   A  x  AA
                                    V,
 Terrestrial vertebrate to water:
  T      -  f  E
   «'/—>«'    J UW  U
 where.
  /ss
  ''ss
  /cvo/sgwef
  /\

  PP
  /n
 pareaL

 Pworm
 A
                     wet wildlife biomass density per unit area (kg/m3, may be calculated as
                     number of animals times average body weight)
                     area of surface soil (m2)
                     water ingestion rate (m3/kg body weight/d)
                     volume of water (m3)
                     assimilation efficiency of chemical from water (unitless)
                     surface soil ingestion rate (kg/kg body weight/d)
                     volume of surface soil (kg)
                     wet bulk density of soil (kg/m3)
                     assimilation efficiency of chemical from surface soil (unitless)
                     proportion of plant matter in diet (unitless)
                     dietary ingestion rate (kg/kg body weight/d)
                     assimilation efficiency of chemical from plant in diet (unitless)
                     areal biomass density of foliage (kg/m2, wet weight)
                     proportion of earthworm in diet (unitless)
                     assimilation efficiency of chemical from earthworm in diet (unitless)
                     areal biomass density of earthworms (kg/m2, wet weight)
NOVEMBER 1999
                                           7-7
TRIM.FATE TSD VOLUME ll (DRAFT)

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CHAPTER 7
BIOTIC ALGORITHMS
            Summary of Transport Algorithms Developed in this Chapter (cont.)
 TERRESTRIAL WILDLIFE (cont.)

 partrt           =       proportion of soil arthropods in diet (unitless)
 Aanh           =       assimilation efficiency of chemical from soil arthropods in diet (uriitless)
 pwl            =       proportion of terrestrial wildlife in diet (unitless)
 Aw,            =       assimilation efficiency of chemical from other wildlife in diet (unitless)
 p,             =       proportion of fish in diet (unitless)
 Af             =       assimilation efficiency of chemical from fish in diet (unitless)
 parea,         =       areal biomass density of fish (kg/m2, wet weight, use correct size range for
                        diet)
 pbl             =       proportion of benthic invertebrates or emergent Hying insects in diet (unitless)
 Abl            =       assimilation efficiency of chemical from benthic invertebrates or flying insects
                        in diet (unitless)
 Asw            =       area of surface of surface water body (m2)
 pareabl        =       areal biomass density of benthic invertebrates (kg/m2, wet weight)
 IA             =       inhalation rate (m3/kg body weight/d)
 VA             =       volume of air (m3)
 AA             -       assimilation efficiency of chemical from air (unitless)
 Eu             =       chemical elimination through excretory processes (urine and feces) (d"1)
 f,,„,             =       fraction of urine and feces excreted to water
  uw
  fuss            =       fraction of urine and feces excreted to surface soil


  AQUATIC BIOTA

  Water to macrophytes'


  _,           mp  mp,acc—sw
    w — >mp          if
                     w
  Macrophytes to water:

  T      -I
     —
              mp,dep-sw


  Water (interstitial or overlying) to benthic invertebrates.



            Hbi mbi Hi.acc-w
                    I/
                     w

  Benthic invertebrates to water (interstitial or overlying)


   T      -k
    bi—*w     bi,dep-w
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                                                                                    CHAPTER 7
                                                                            BIOTIC ALGORITHMS
            Summary of Transport Algorithms Developed in this Chapter (cont.)
  AQUATIC BIOTA (cont.)

  Sediment to benthic invertebrates:
                y
                v sed Psed

  Benthic invertebrates to sediment:


  T       =k
    biased     bi,dep-sed

  Water to a specific fish domain (i.e., herbivore, omnivore, or carnivore), using the bioenergetic-based
  kinetic model for nonionic organic chemicals:
                 _
     water — >fish        TJ
                          IV

  A specific fish domain (i.e., herbivore, omnivore, or carnivore) to water, using the bioenergetic-based
  kinetic model for nonionic organic chemicals:


  T             —  k
    fish — twater       eg

  A specific fish domain (i.e., benthic omnivore, benthic carnivore, water column herbivore, water
  column omnivore, or water column carnivore) to the water domain, using the bioenergetic-based
  kinetic model for mercury:
  T"1                            _ T^"
     receptor ( fish) — > water        E

  Dietary items to a specific fish domain (;.e., benthic omnivore, benthic carnivore, water column
  herbivore, water column omnivore, or water column carnivore), using the bioenergetic-based kinetic
  model:

  „                      n receptor m receptor
  1 diet->receptor(fish) ~                    A Trf  A £,
                             ndiet mdiet
  Dietary items to a specific fish domain (;.e., benthic omnivore, benthic carnivore, water column
  herbivore, water column omnivore, or water column carnivore), using the time to steady-state-based
  kinetic model :
                           receptor    receptor
    diet-^receptor (fish)
                                                '-ln(l-a)
                                                     '«
receptor—diet
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CHAPTER 7
BIOTIC ALGORITHMS
            Summary of Transport Algorithms Developed in this Chapter (cont.)
 AQUATIC BIOTA (cont.)

 A specific fish domain (i.e., benthic omnivore, benthic carnivore, water column herbivore, water
 column omnivore, or water column carnivore) to the associated dietary items, using the-iime_to
 steady-state-based kinetic model:
    receptor (fish)^>diet
 where'
  //
  ^
   receptor-diet
  mp,acc-sw
  I/
  mp.dep-sw
  bi acc-sed
  if
  bi acc-w
 "fci.dep-sed
 receptor
mbl


md,et
m,

  receptor
vsed
V,.,
                          -ln(l-a)
                     receptor-diet partition coefficient
                     accumulation from surface water, for macrophy:es (1/day)
                     depuration to surface water, for macrophytes (1/day)
                     accumulation from sediment, for benthic infauna (1/day)
                     accumulation from water, for benthic infauna (1/day)
                     depuration to sediment, for benthic infauna (1/day)
                     depuration to water, for benthic infauna (1/day)
                     elimination via the gills, for fish (1/day)
                     uptake rate constant for fish from water via the gills  (1/kg-day)
                     number of organisms comprising the benthic invertebrate domain
                     number of contaminated items comprising the potential diet
                     number of organisms comprising a specific fish domain
                     number of receptors
                     mass of individual organisms comprising the benthic invertebrate domain
                       mass of individual items comprising the potential diet (ug)
                       mass of individual organisms comprising a specific fish domain (ug)
                       mass of individual receptors (ug)
                       time required to reach a percent of the steady-state value when the
                       concentration in the source is approximately constant with time (day)
                       volume of the macrophyte in the cell (L)
                       volume of sediment in the cell (L)
                       volume of water in the cell (L)
                       bulk density of sediment (g/L)
                       feeding rate constant (kg[prey]/kg[predator]-day)
                       efficiency of transfer of chemical
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•      The accumulation of chemicals by wood is not well understood; therefore, trees in
       TRIM.FaTE consist of leaves only and not stems or roots, except to the extent that stems
       are conduits of chemicals from leaves.

       7.2.1.1  Transfer of Particles and Rain to Surface of Leaf

       The surface of the leaf includes: dry particulate matter deposited to the plant surface,
particles deposited to the plant surface in rain water, and rain water containing gaseous chemical.
Deposition is defined here as the mass transfer of suspended particulates from air to the plant
surface.  Elsewhere (e.g., Lindberg et al. 1992), the deposition of chemicals to plants is defined
to include the gaseous fraction of the pollutants that come into contact with plants. The uptake of
gaseous pollutants in TRIM.FaTE is treated below.

       Dry or wet deposition to the surface of the leaf is the deposition velocity times the leaf
interception fraction.  The leaf interception fraction (I) is the fraction of particles that land on the
leaf; thus 1-1 is the fraction that lands on soil. It is common for a concentration of a deposited
particulate chemical to be estimated with respect to the leaf or above-ground plant mass.
However, when that concentration is estimated, it is often forgotten that most of the chemical
mass is still on the plant rather than in it.

       Dry Deposition of Particles to Surface of Plant Leaves

       Dry deposition is estimated by multiplying the predicted air concentration at ground level
by the deposition velocity (U.S. EPA 1997a).  Thus, a flux equation that expresses dry deposition
to the leaf, from van de Water (1995) follows. Note that the area of soil and that associated with
an air volume element may be different.
                               dN
                                   LP
                                 dt
                                 N
                                   Ap
                                                                                    (7-1)
where:
*AP
                     mass of chemical depositing on leaf surfaces from particulate matter in air
                     (kg)
                     mass of particle-bound chemical in air (kg)
                     volume of air volume element (m3)
                     dry deposition velocity of particles (m/d)
                     fraction of dry-depositing chemical that is intercepted by plant canopy
                     (unitless, below)
                     soil area (m2)
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       The interception fraction for dry deposition (Ij) may be calculated using the following
equation (Baes et al. 1984):
                               T  _ i _  ( \-WL)(-axparea)                               (7-2}


where:                                                                      __  _

       a     =      vegetation attenuation factor (m2/kg)
       parea  =      wet above-ground non-woody vegetation biomass inventory per unit area
                     (kg/m2)
       WL     =      water content of leaf (mass/mass, unitless)

       The water content adjusts parea to represent dry biomass. The equation was originally
derived for pasture grasses and hay and expanded to other crops.  Foi this reason, the biomass
should not include wood.  The vegetation attenuation factor (sometimes called the foliar
interception constant) is sometimes equivalent to the surface area of leaves divided by plant
biomass (van de Water 1995) or the leaf biomass if the plant is woody.
       Thus,
                                           V ./ , A
                                T           d  *
                                1
where:                           _

       TAp.Lp  =      transfer factor from particulate phase of air to surface of plant leaf (process
                     occurs when it is not raining)

If it is assumed that particles are blown off the plant with wind at a rate that equals the deposition
rate to leaves, and all particles are dispersed in air,
                                                                                    (   }
where:

       TI.P >AP  =      transfer factor from surface of plant leaf to particulate phase of air (process
                     occurs when it is not raining)

       Wet Deposition to Plants

       Rain scavenges some of the chemical mass from the vapor phase and particulate phase of
air. Wet deposition resulting from these processes may be modeled distinctly with the same
equation. The rate of mass transfer of vapor-phase or particulate phase mercury from air to rain

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water and to the surface of the plant leaf is described by the following equation (modified from
van de Water 1995):
                          dt     VA
where:
       NLp    =      mass of chemical on surface of leaf (kg)
       NA    =      mass of chemical in gas phase of air (kg)
       VA     =      volume of air (m3)
       Jram    =      rain rate (m/d)
       wr     =      washout ratio (mass chemical/volume rain + mass chemical/volume air)
       As     =      area of soil (m2)
       Iw     =      interception fraction for wet deposition (unitless)

       The interception fraction may be calculated using the following equation from Muller and
Prohl (1993). The fraction is dependent on how much water the leaf can hold, the total amount
of rainfall, and the ability of the element or compound to stick to the leaf.
                           /.., =
                                 LA/""       '~'n2
                                  ram
                                                           (7-6)
where:
       LAI    =      1-sided leaf-area index (m2 total leaf area / m2 underlying soil area)
       S      =      vegetation-dependent leaf-wetting factor (retention coefficient) (m)
       rain    =      amount of rainfall of a rainfall event (m)
If Iw is calculated to be greater than 1, then the value must be set to 1.  Thus,


                                 V
TA-LP =—XwrxJra,«*AsXlw                         (7-7)
                                   A

where:
       TA_!n   =      the transfer factor from the vapor phase of air to the leaf surface

       The rate of mass transfer of particulate-phase mercury from air to rain water and to the
surface of the plant leaf may be described by an analogous equation:
                                                                                    (7-8)
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where:
       ^
       N
        Ap
       w
       Thus,
mass of chemical on surface of leaf (kg)
mass of chemical in particulate phase of air
volume of air (m3)
washout ratio (mass chemical/volume rain -^ mass chemical/volume air)
rate of rainfall (m/d)
area of soil (m2)
interception fraction (unitless, see equation above)
                       T
                                                                (7-9)
where:
       1 Ap -Lp
 the transfer factor from particles in air to the leaf surface
       Washoff of Chemical from Plant Surface

       It has been observed that particles on the surface of conifer leaves are washed off (during
rain events) according to first-order kinetics with a rate constant of 0.04 per min (McCune and
Lauver 1986). The rate of 0.04 per min is equivalent to 2.4 per hour or 57.6 per day. It may be
assumed that the particles deposited in rain water and the chemical dissolved in rain water is
washed off at the same rate.  Thus,
                                dN
                                   Lp
                                 dt  —57.6XA,,
                                                               (7-10)
and
where:
       T      -
       1 Lp ASs
                                   7^=57.6
transfer factor from surface of leaf to surface soil during rain (d"1)
                                                               (7-11)
An alternative type of transfer would be an instantaneous transfer at the end of a rain event,
where the transfer would also be derived from McCune and Lauver (1986):
                                            -0 0003rain
                                                                                   (7-12)
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where:

       TLp _,&  =      transfer factor from surface of leaf to surface soil during rain
                     (instantaneous)
       rain   =      cumulative amount of rain during rain event (m)

The implementation of this transfer may be required if the high first-order rate constant above
(which is equivalent to 2.4 per hour) causes instability in LSODE, the differential equation
solver.

       Note that it may not be assumed that the transfer factor for loss to soil is the same as the
transfer from the vapor phase of air or particles in air via rain (as is assumed with dry
deposition). In order to have this option, the vapor phase and particulate phase of the chemical in
rain water on the surface of the leaf would have to be tracked separately, and two transfer factors
to surface soil would be required.

       Transfer of Chemical to Leaf from Particles on Plant

       The fraction of deposited chemical that enters the plant cuticle per day is very uncertain.
It depends on the relative concentrations in the plant and particles at equilibrium (which is
unknown),  as well as the time to equilibrium.  It is sometimes assumed that chemicals attached to
particles reach instantaneous solution equilibrium with plant tissues when they land on the plant.
If that assumption is made for some chemicals (e.g., mercury), TRIM.FaTE is likely to
overestimate the contribution of the particles to uptake of the chemical by the plant (Lindberg
1999a). For a chemical that is tightly and chemically bound to particles in air (e.g., Hg), an
initial assumption of 0.2 per day may be appropriate. Because particles cover only a small
fraction of the surface of the plant, it is assumed that the rate of transfer from leaves to particles
is 1 percent of the rate of transfer in the other direction (0.002 per day). The rate may be higher
for the transfer of mercury from the plant to a dissolved state in rain water, but no information is
available on this. Note that these default values will change if units of time change.
where:

       Tlf v   =      transfer factor from leaf surface to leaf
       TL.Lp   =      transfer factor from leaf to leaf surface

       Transformations on the Leaf

       Transformations of chemicals in particulate matter on the surface of plant leaves are
assumed to occur at the same rate as transformations in air.
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       7.2.1.2 Uptake of Gaseous Chemical into Foliage

       The diffusion pathway is valid for all gaseous forms of chemicals, including organic
compounds and mercury species.  The diffusion from air to plants is; based on two resistances in
parallel:  a) the series resistance of stomata and mesophyll and b) the series resistance of air and
cuticle.  It is assumed that a chemical fraction that is in the plant cuticle or mesophyll isJnside of
the plant, but that the chemical inside of the stoma but outside of the mesophyll is outside of the
plant.  It should be noted that the resistance is the inverse of the conductance. Damage to the
plant (e.g., from insect herbivory) can also contribute significantly to the transport of nutrients
from plant leaves (Hargrove 1999). However, the contribution of insect or other sources of
damage to the diffusion of Hg into and out of the plant is unknown and not incorporated into
TRIM.FaTE.

       Stomatal Conductance

       The stomatal conductance of gaseous chemicals into the leaf may be determined based on
the stomatal conductance of water vapor. The only chemical-speciiic parameter that is required
is the molecular weight of the chemical.  One means to estimate the stomatal conductance is the
following
                           e      = Vl8/ MW xe                               (7-15)
                           o stomala   V 1 
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                                                                               CHAPTER 7
                                                                        BIOTIC ALGORITHMS
       Alternatively, the stomatal conductance of water may be calculated (Riederer 1995) using
the following equation. This option has not yet been implemented in TRIM.FaTE:
                                                                                  (7-17)
                                 water     xs+ys

where:

       Swaier   =     conductance of water through the stomata (m/d)
       DAH2°  =     diffusion coefficient of water in air (m2/d)
       nas    =     number of stomata in leaf («) times area of 1 stoma divided by area of leaf
                    (%)
       a      =     mean degree of opening of stomatal pores, between 0 and 1
       xs      =     depth of elliptical pore (m)
       ys      =     mean pore radius (m)

If this latter algorithm is used, it should be noted that conductance varies with temperature.  In
the 20° to 40° C temperature range, the vapor flux from leaves has been observed to double with
a 10° rise  in temperature (Leonard et al. 1998), so variability in temperature could contribute
significantly to the uncertainty in this type of transfer.

       Mesophyll Conductance

       It is suggested that for  most organic chemical species and most plant species, the stomatal
or cuticular conductance is the rate-limiting pathway (Riederer 1995). Therefore, for most
chemicals, there is no need to consider  mesophyll (inner tissue) conductance.  However, some
work with mercury cited in Lindberg et al. (1992) suggests that "resistance on or within
mesophyll surfaces dominates the atmosphere-leaf diffusive path of Hg°." See Section A. 1.1 of
Appendix  A.

       Total Conductance of the Stomatal Pathway

       Thus, the total conductance of the stomatal pathway is:
                                        1       1
                                   V o Stomaia   o m

where:

       gs     =     conductance of stomatal pathway, including mesophyll (m/d)
       Ssiomaia  =     conductance of stomata (m/d)
       Ssiomuiu  =     conductance of mesophyll (m/d)
                                                                                  (7-18)
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       Boundary-layer Conductance

       The boundary-layer conductance is defined by the following equation:
                                          °AP
                                                                                  (7-19)
where:

       gB     =     conductance of the boundary layer (m/d)
       DA     =     diffusion coefficient of chemical through still air (m2/d)
       6AP    =     thickness of air boundary layer over plant (m)

The boundary layer thickness (6^ in m) may be approximated by the following equation (Nobel
1991), or the value may be assumed (e.g., 0.001 m in Riederer 1995, 0.005 m in McKone
1993a,b,c).  The constant of 0.004 is the square root of the viscosity of air at 20 degrees Celsius,
1.51 x 10"5 m2 per second (Wilmer and Fricker  1996).
                                  5,P=0.004V//v                                   (7-20)
where:
       /      =     length of flat leaf (m)
       v      =     wind velocity(m/s)

       Cuticular Conductance

       The cuticular conductance (mass transfer coefficient from air outside of the plant to the
cuticle) is defined by the following equation (Riederer 1995):

                                            Pc                              ,   '
                                  8 cuticle ~  T7                                       (7-21)
                                           A AW

where:

       Scunde  =     conductance of the cuticle (mis)
       P(.    =     permeance of the cuticle (m/s)
       KAW    =     air-water partition coefficient (unitless)

       Cuticular permeance has been measured in Citrus aurantium leaves, and the following
relationship was derived (Riederer 1995).  The variability of this relationship with plant species
is unknown.

                     log Pc -0.704 log Kov- 11..2  (r = 0.91)                       (7-22)

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In addition, KAW is equivalent to ZA,/ZW. Thus,

                              i n 0.704 log *:„-!! 2
                        ,  - ,                 ,x 24x60x60                    (7-23)
                    1 cuncle    >    7    I 7
                                 L MR '  L
where:
       Scuncie  =     conductance of the cuticle (m/d, note change in units)
       2W     -     capacity (Z-factor) of chemicals in water (molPa"'m3)
       Zair    =     capacity (Z-factor) of chemicals in air, including particulates (molPa"1m3)

       The cuticular conductance must be put in series with resistance through the air on the leaf
surface to yield the total cuticular conductance (air to plant), adjusted for capacity (Z-factor) of
the air and leaf. Thus:
                                       B   o cuticle )

where:

       gB     =     conductance of the boundary layer (m/d)
       Scuncie  =     conductance of the cuticle (m/d)
       gc     =     total conductance of the cuticular path, including the air boundary layer
                    (m/d)

Riederer (1995) has derived the flux equation for diffusion in and out of plant leaves.


                  dN L               A^             A^  KAV
                    ,   - A(gc  + gs)-r,~A(gc+gs) —x —(7-25)
                   at                VA              VL   KLW

where:

       NL     =     mass of chemical in leaf compartment (g)
       NA     =     mass of chemical in air compartment (g)
       VA     —     volume of air compartment (nr)
       VA     =     volume of leaf compartment (mj)
       K,w    =     air/leaf partition coefficient (unitless)

       Transfer Factors for Diffusion

       If the Bennett et al. (1998) equation (which is calculated with respect to soil area) is used
for the stomatal conductance, the transfer factor for diffusion from leaf to air is:


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                 TfyA  = (2LAI xAsxgc  + Asxgs)x~x--^                 (7-26)
                                                       V L    LL

where:

       VL    =     volume of leaves (m3)
       LAI   =     Leaf-area index, the area of one side of a leaf (unitless)
       As    =     area of soil (m2)
       Zy>    =     capacity (Z-factor) of chemicals in plant (mol-Pa"'m"3)
       ZL    =     capacity (Z-factor) of chemicals in leaf (mol-Pa^m"3)

       Note that the contact area associated with the cuticular pathway is 2 times the LAI
(because cuticles cover the top and bottom of a leaf).  If the Riederer (1995) equation (which is
calculated with respect to 1-sided leaf area) is used for the stomatal conductance, the transfer
factor is:

                                                            1    ZA
             TdL'!fA = (2LA/xAsxgc + LA/X Asxg5)x--x-^              (7-27)
                                                           v •      p


       Zr may be  calculated using the following equation, which represents plants as mixture of
air, water and nonpolar organic matter analogous to octanol (Paterson and Mackay 1995).  It is
assumed that the fugacity capacity of a plant leaf is equivalent to that of a generic plant that is 18
percent air, 80 percent water, and 2 percent nonpolar organic matter.

                         ZP= 0.18 ZA + 0.80 Zl( + 0.02 Kow x Zw                    (7-28)

       Similarly,  if the Bennett et al. (1998) equation (which is calculated with respect to soil
area) is used for the stomatal conductance, the  transfer factor for diffusion from air to leaf is:
                   T™L =  (2LAI x As x gc + As x gs ) x --            -      (7-29)
                                                           ' A

And if the Riederer (1995) equation (which is calculated with respect to 1 -sided leaf area) is used
for the stomatal conductance, the transfer factor is:


                T^{ = (2LAI xAs x gc +  LAI x A5 xgs)x—                 (7-30)
       7.2.1.3 Uptake from Soil by Root

       The uptake of chemicals by plant roots is treated as an equilibrium process. Two
alternative algorithms may be used to calculate the accumulation of a chemical by plants from

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soil: uptake from soil or uptake from soil water. Both algorithms are derived from an
equilibrium relationship, an estimated time to equilibrium, and the assumption of a first order
rate of uptake. These algorithms do not apply to woody tree roots or tuber crops. Uptake of
chemicals by these types of roots is not considered in TRIM.FaTE at this time.

       Uptake from Whole Soil                                             _  _

       The uptake of chemicals by roots in TRIM.FaTE is described by an equation,in the form
of a time to equilibrium between the roots and soil. Because of the linear relationships in
TRIM.FaTE, uptake is described as proportional to the concentration of the chemical in soil even
though some studies suggest that a log-log regression between soil and root concentrations is a
more precise model of uptake.

                             CR_dn = KRSr_(lf^  xCSr_Jr^                             (7-31)

where:

       CR_dry         =     concentration of chemical in dry root (kg/m3, dry wt)
       KiiSr_dr>,        ~     dry root/root-zone-soil partition coefficient (uptake factor,
                           dimensionless)
       CSr_dry         =     concentration of chemical in root-zone soil (kg/m3, dry wt)

If masses are converted to wet mass, then:

                                   c — n  w  "> x  c                                n-V)\
                                 -. L-R  (.l-ryK) x  (-R^ry                             \l-J<£)

where:

       WR    =      water content of root (kg water/kg worm)
       CR     =      total concentration of chemical in root (kg/m3)

and

                                   c  = c\-w\y.c                                r7-3T\
                                   *^Sr  \L   Sr)   ^Sr-dry                             \'  J J )

where:

       WSr    =      water content of soil (kg water/kg root zone soil)
       CSr    =      total concentration of chemical in root zone soil (kg/m3)

Thus,

                                (\-WK)xKR  Sr(J.
             , -•   it * \   *-^              A'     A —-JMUMI      n»  >   f-.
                                                                                  (7-34)
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and
where:
       K.
        R-Sr
                                  R ~ ^ R-Sr X CSr
                                                                           (7-35)
             root-soil partition coefficient (wet kg/kg per wet kg/kg), calculated to be:
Thus,
                           K
                                   (\-WR)xKR_Sr_dn.
                             R-Sr
                                         \-W
                                              Sr
                                                                           (7-36)
              dt
                     -ln(l-0.95)
                          '095
                                   x KR_Sr x CSr -
                                             -ln(l-0.95)
                                                  '095
                                                                           (7-37)
where:
1095
                    time required to reach 95 percent of the steady-state value when CSr is
                    approximately constant with time (d)
If the areal density of roots is approximately constant with time, ther:
         dN
           dt
           -ln(l-0.95)
                       '095
N.
                                             x
                                         V
                                                 Sr
-ln(l -0.95)
                                                     '095
                                                                           (7-38)
where:
       V
        Sr
and
             mass of chemical in nonwoody roots (kg)
             total mass of chemical in all phases of bulk root-zone soil (kg")
             total volume of root-zone soil, which contains; roots (m3)
             total volume of roots (m3)
                                     pareaR x
                                         pvolR
                                                                           (7-39)
where:
       pareaK =
              area of soil surface (m2)
              areal density of root in root-zone soil (kg root fresh wt/m2)
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pvol R  =      wet density of root (kg/m3)

Transfer Factors


                       ~-ln(l-0.95)

                            ^095
                                              PV°IK
                                                                            - .  (7-40)
where:
                               ' r-Sr
                                        -ln(l-0.95)
                                            '095
                                                                                   (7-41)
       TSr_R   = transfer factor from root-zone soil to root
       TR_Sr   = transfer factor from root to root-zone soil

       Uptake from Soil Water

       An alternative method by which to estimate the root concentration of a chemical is an
equilibrium between root tissue and soil water concentration.  The equilibrium relationship is a
generalization of the Briggs et al. (1982) equation developed in Trapp (1995).
where:
where:
b      —
pvolR  =
pvolsw =
       Thus,
             dC.
                                XJ? ~ K R-SrW X ^ SrW
                                                                            (7-42)
                     concentration in roots (kg [chemical]/m3 [root fresh weight])
                     root - root zone soil water partition coefficient (kg/mj per kg/m3) (below)
                     concentration in soil pore water (kg [chemical]/m3 [soil pore water])
                                        LRKbOH.)pvolRpvol^
                                                                            (7-43)
                     water content of root (mass/mass wet weight)
                     lipid content of root (mass/mass wet weight)
                     correction exponent for the differences between octanol and lipids
                     density of fresh root (g [root]/cm3 [root])
                     density of soil pore water (g [soil pore water]/cm3 [soil pore water])
              dt
              -ln(l-0.95)
                          '095
                                       R-SrW
                                              ' <
-ln(l-0.95)
                                                           0 95
                                                             ct
                             (7-44)
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where:
       '095
            time required to reach 95 percent of the steady-state value when CSr is
            approximately constant with time (d)
If the areal density of roots is approximately constant with time, then:
           dt
                  -ln(l-0.95)
                       '095

                                                 SrW
                                                -ln(l-0.95)
                                                    '0 )5
                                                                     N
                                                                           (7-45)
where:
         rW
       V,
       ve
SrW
mass of chemical in nonwoody roots (kg)
total mass of chemical in root-zone soil water (kg)
volume of root-zone soil water (m3)
total volume of fresh roots in parcel (m3)

                 pareaR x As

             "       PV°1K
                                                                                   (7-46)
where:

       As     =     area of soil surface (m2)
       pareaR =     areal density of root in root-zone soil (kg root fresh wt/m2)
       pvolR  =     wet density of root (kg/m3)

The transfer factors are:
                     • SrW-R
                              -ln(l-0.95)
                                  '095
                                     pareaR   K
                                      pvolR
                                                         K_SrW
                                                                                   (7-47)
where:
                              R-SrW
                                        -ln(l-0.95)
                                             '095
                                                                                   (7-48)
       T      =
       1 SrW-R
       L
        R-SrW
            transfer factor from root-zone soil water to root
            transfer factor from root to root-zone soil water
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       7.2.1.4 Uptake by Stem

       The algorithms for the uptake of chemicals by the stem are taken from Trapp (1995) who
derived them for organic chemicals.
       Contribution from Soil Pore Water via Transpiration Stream (Xylem)    __  _
                                                 N
                      dt
                                                 VSrW
                                                                                 (7-49)
where:
       NSt
       TSCF =
       NSrH,
             mass in all stems in volume element (kg)
             flow of transpired water in cell area (mVd, below)
             transpiration stream concentration factor (mg/m3 of xylem per mg/mj of
             soil pore water)
             mass of chemical in root- zone soil water (kg)
             volume of water in root-zone soil (m3)
       VSrW   =

       According to Crank et al. (1981),
where:
4.8 xlO'3
LAI
As
                        = 4.8xlO~3 x LAlxAs
                           empirical factor with units of m/d
                           leaf-area index
                           area of soil (m2)
Thus,
                                                                                 (7-50)
where:
                                     Sr    Sr
                                         TSCF
                                                                                 (7-51)
leaves,
       TSr_Sl   =      transfer for root-zone soil to stem

       Contribution from Leaves via Phloem

       Assuming that the chemical concentration in phloem sap is in equilibrium with that in
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                             dN.
                              dt
                      VLxK
                                                                                (7-52)
                                                 LPh
where:
       Q?
       K,
        LPh
mass of chemical in stems in volume element (kg)
phloem flux into fruit (m3/d), due to advection (assume 5 percent of Qxy,
Paterson et al. 1991)
mass of chemical in leaves (kg)
volume of leaves (m^)
partition coefficient between leaves and phloem water (mass/vol to
mass/vol)
The following equation, adapted from an equation for sorption of contaminants to plant roots
(Trapp 1995), may be used to calculate KLPh.
                  KLPh=(WL+lLxKbow)xpvolL/pvol
                                         Ph
                                                            (7-53)
where:

       WL    =     - water contentof leaves (mass/mass wet weight)
       /;     =      lipid content of leaves (mass/mass wet weight)
       b     =      correction exponent for differences between foliage lipids and octanol
       pvol,  =      density of leaf (kg/mj)
       pvol,,h =      density of phloem (kg/m3)

       If the chemical in question is ionic, it may be assumed that Kow is close to zero and that
the concentration of the ionic species in phloem is the same as that in leaf water.

       Thus,
                                         VLxK
                                                                                (7-54)
                                                LPh
where:
                    transfer factor for leaf to stem
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       Loss with Xylem to Leaves


                              dNL            Ns,
                              -~=QX) x                                       (7-55)

where:

       NL     =     mass of chemical in leaves (kg)
       Qxy    =     flow of transpired water (equation above)
       NSt    =     mass of chemical in stem (kg)
       VSt    =     volume of stem (m3)
       KS,.\\  =     partition coefficient between stem and xylem water (mass/vol to mass/vol)

The following equation, adapted from an equation for sorption of contaminants to plant roots
(Trapp 1995), may be used to calculate KStXy.

                   KStX  = (Ws, + ls,  x  Kbnw ) x pvolSl / pvolX)                    (7-56)

where:

       WSl    =     water content of stem (mass/mass wet weight)
       ls,     =     lipid content of stem (mass/mass wet weight)
       Kow    =     octanol-water partition coefficient
       b     =     correction exponent for differences between foliage lipids and octanol
       pvols,  =     density of stem (mass wet weight/volume)
       pvolXv =     density of xylem fluid (mass wet weight/volume)

If the chemical in question is ionic, it may be assumed that Km. is zero and that the concentration
of the ionic species in xylem is the same as that in leaf water.

       Thus,


                              TS,-L=Qxi X7^	                              (7-57)


where:

       TSl_,   =     transfer factor for  stem to leaf

       Loss from Phloem to Fruit

       It is not necessary to implement a fruit compartment or this loss term in TRIM.FaTE
unless a) moderate to high concentrations of the chemical have been found in fruit and b) fruit
constitutes a significant portion of the biomass of the vegetation. This algorithm  has not yet been

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implemented in any tests of TRIM.FaTE.  The concentration of any chemical in the phloem
running through the stem is at the same concentration as xylem sap leaving the stem; both are in
equilibrium with the stem.  Thus,
where:

       N,,hF  =     mass of chemical in fruit (kg)
       V,.-    =     volume of fruit (m3)
       QP    =     phloem flux into fruit (m3/d), due to advectioti (assume 5 percent of Qxy,
                    Paterson et al.  1991)
       Nst    =     mass of chemical in stem (kg)
       Fs,    =     volume of stem (m3)
       KSlYv  =     partition coefficient between stem and xylem water (mass/vol to mass/vol)

       Stem Simplifications for Nonionic Organic Chemicals

       The uptake of nonionic organic chemicals by the stem is assumed to originate from the
root. Little if any nonionic organic chemical mass  is transported from leaves to stems. For that
reason, in the PAH test case of TRIM.FaTE, the root and stem were not connected to the leaves.
The algorithm for uptake by the stem was an equilibrium relationship taken from Briggs et al.
(1983):

                      C,,« = SCF x CSrw X pvols!empvol-lrw                       (7-59)

where:

       Cslem         =      concentration of chemical in stem (kg [chemical]/m3 [stem])
       CSrW         =      concentration in soil  water (kg/m3)
       SCF         =      stem concentration factor (kg/kg per kg/kg) (below)
       pvolmem       =      density of stem, kg (fresh stem)/m3 (fresh stem)
       pvolSrW       =      density of soil water, kg (soil water)/rn3 (soil water)

       The stem concentration factor may be calculated by the following equation from Briggs et
al.(1983):
       Thus,
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dCtum
dt
"-ln(l-0.95)"
^0.95
ovol
v c f j? v slem v r1
A OL/' A A C r,u,
PV<*
"-ln(l-0.95)"
^095
Cs,em (7-61)
where:
       '095
                    time required to reach 95 percent of the steady-state value when CSr is
                    approximately constant with time (d)
       If the areal density of stems is approximately constant with time, then:
     dt

where:

                  0.95
                                                             -ln(l-0.95)
                                                                 '095
                    mass of chemical in fresh stems (kg)
                    total mass of chemical in root-zone soil water (kg)
                    volume of root-zone soil water (m3)
                    total volume of fresh stems in parcel (m3)
                                sum
                                     Pareaslem x A,

                                         PV°ls,en,
                                                                                  (7-62)
                                                                                  (7-63)
where:
       pvolsle
                           area of soil surface (m2)
                           areal density of stem in root-zone soil (kg root fresh wt/nr)
                           wet density of stem (kg/m3)
       The transfer factors are:
                            -ln(l-0.95)
                                '0 95
                                                         SCF
                                                     pvolsrw xdsr
                                                                                  (7-64)
                                         -ln(l-0.95)
                                             '0 95
                                                                                  (7-65)
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where:

       Tsrw-*,em      ~      transfer factor from root-zone soil water to stem
       Tslem-xrw      =      transfer factor from stem to root-zone soil water

       7.2.1.5 Uptake by Wood and Tree Bark                               —  _

       Wood is of interest in a mass-balanced chemical transport and fate model because of its
potential for serving as a large reservoir of chemical mass. The few studies that exist suggest
that there is some accumulation of air pollutants in bark and wood. Ralph Turner (1998) has
limited data on the accumulation of mercury in wood, but the mechanism of accumulation is not
understood.  Simonich and Hites (1995) provide data on the accumulation of organochlorine
compounds in tree bark; polycyclic aromatic hydrocarbons would be expected to have similar
properties.  The transfer of chemicals to wood and tree bark is not modeled because of a general
lack of information for persistent air pollutants.

       7.2.1.6 Chemical Transformations

       All transformations are assumed to be first-order processes in TRIM.FaTE. The
derivations of these values for particular chemicals (e.g., PAHs and Hg) are described in
Appendix A of this volume.

       7.2.1.7 Litterfall

       The flux of chemical from leaves to surface  soil may be expressed by the equation:

                            dN,
                           	-  =LxN,+LxN.                             (7-66)
                             d\                      p

where:

       NSs     =     mass of chemical in surface soil in cell (kg)
       L      =     litterfall rate (d'1)
       NL     =     mass of chemical in foliage in cell (kg)
       NLp    =     mass of chemical on surface of leaves in cell (kg)

       It is assumed that all leaves of deciduous trees are dropped to surface soil between the day
of first frost and a date that is 30 days later. Thus, L = 1/30 d"1.

       Conifers drop their leaves at a steady rate, with a complete turnover which lasts 2 to 10 or
11 years (Post 1999). It is assumed for the purpose  of TRIM.FaTE that the leaf turnover is 6
years. Thus, L = 1/2190 d'1.

       It is assumed that herbaceous plants and grasses become "litter" on the surface of the soil
during the 30 day period beginning the day of first frost. Thus, L= 1/30  d"1

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       It is assumed that agricultural plants are harvested and do not become "litter." If
agriculture were dominant, this assumption would need to be revised, based on harvesting
practices (e.g., how much residue is left) for the particular crop. Thus, L = 0 d"1.

       Thus,

                                    TL^S,  = L                                     (7-67)

where:

       TL-+SS   =      transfer factor from leaf to surface soil

Also,

                                           = L                                    (7-68)
where:

       TL_Ss   =      transfer factor from leaf surface (particulate matter) to surface soil

       Note that the transfer of chemical from litter to surface water is not implemented in
TRIM.FaTE at this time.

       7.2.1.8 Senescence

       Senesence is not considered in the current prototype of TRIM.FaTE.  Senescence is the
aging of plants, a process which affects the uptake of chemicals, growth, and plant parameters
such as water content. If a user of TRIM.FaTE wants to include the process of senescence,
candidate algorithms for changes in plant biomass may be found in Whicker and Kirchner
(1987). Senescence is assumed to be negligible prior to August 1  through most of the United
States.

       7.2.1.9 Other Seasonal Issues

       Plants only take up chemicals during the growing season, i.e., the dates in the spring,
summer, and fall between last frost and first frost. Although there may be uptake by conifers
outside of the growing season, it is probably negligible for much of the non-growing season in
cold environments (e.g., in the Maine case study)" (Lindberg  1999b) and is not considered in
TRIM.FaTE modeling purposes.  To limit plant uptake only to the growing season, the user must
specify the  time period considered outside of the growing season.

       An  additional seasonal issue is deposition to the leaf surface compartment type.  Tree
foliage and grasses only intercept deposition when they are present.  TRIM.FaTE assumes that
there is no plant foliage present in the non-growing season, except for conifers. All deposition in
deciduous forests, old fields, and agricultural systems in the non-growing season goes directly to
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soil. Deposition to conifer foliage may continue in the winter, though accumulation of
contaminants from particles or wet deposition is assumed to be negligible.

       Chemical transformation within the plant is also assumed to cease in the non-growing
season.  There is no evidence to support or refute this assumption for most contaminants.

       During the non-growing season, herbivores do not eat plants or make up this portion of
their diet in any way.  For herbivorous or omnivorous animals that do not hibernate or engage in
winter sleep, the accumulation of contaminants from alternative, non-plant dietary sources may
be underestimated in TRIM.FaTE.

7.2.2   SOIL DETRITIVORES

       7.2.2.1 Earthworms

       The uptake of chemicals by earthworms in TRIM.FaTE is described by an equation in the
form of a time to equilibrium between the earthworms and soil.  For simplicity, uptake is
described as proportional to the concentration of the chemical in soil even though some studies
suggest that a log-log regression between soil and earthworm concentrations is a more precise
model of uptake.
                                 \vorm-dr\'
                               — K
                               '
                                          worm-Sr-Jry
                                                 x C
                                                    Sr-
                                                      -dr\'
                                                      (7-69)
where:
       C,
       C
 \vorm-dry
        Sr-dry
       K..
concentration of Hg in earthworm, kg/kg dry weight
concentration of Hg in root-zone soil, kg/kg dry weight
earthworm-soil partition coefficient
If masses are converted to wet mass, then:
                               r   = C 1 -W
                               ^worm  V*  "wor
                                                 ^ worm-dry
                                                                        -  (7-70)
where:
and
                    water content of worm (kg water/kg worm)
where:
                                                                                 (7-71)
WSr    =
                    water content of soil (kg water/kg root zone soil)
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Thus,
a-wBOrjx£Borm^n
        \-we.
                                                      /in/  x
                                                      l      '
                                                               (7-72)
and
where:
       IS
        M'orm-.S>
                                   — jr      v r
                                orm ~ **• worm-Sr   ^ Sr
                                                               (7-73)
         earthworm-soil partition coefficient (wet kg/kg per wet kg/kg),
         calculated to be
      K^-Sr =
     -W^JX *...,„,_„_,„

          1 - H'
                                                                                (7-74)
Thus,
                     -ln(l-0.95)
                         '0 95
                                  -ln(l-0.95)
                                      '0 95
                                                                c,
                                                               (7-75)
where:
       '095
   time required to reach 95 percent of the steady-state value when CSR is
                    approximately constant with time (d"1)

If the areal density of worms is approximately constant with time, then:
       dN.
         dt
-ln(l-0.95)
                      '095
                               xV   K
                                           ,
                                  H orni  w orm — ir
              x
                       -ln(l-0.95)
                                          '0.95
where:
                    mass of chemical in earthworms (kg)
                    total mass of chemical in all phases of bulk root zone soil (kg)
                    total volume of root zone soil, which contains worms (mj)
                                                               (7-76)
                                                                                (7-77)
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where:
Thus,
                           area of soil surface (m2)
                           areal density of earthworm community in root-zone soil (kg worm
                           fresh wt/m2)
                           wet density of earthworm (kg/m3)                  __
                  Sr
                            -ln(l-0.95)
                                '095
                                                       *orm-Sr
                                          1 Sr
                                                                                  (7-78)
where:
       T
        Sr worm
       T
        worm ->Sr
       T..
                                         -ln(l-0.95)
                                             '095
       transfer factor from root-zone soil to worm
       transfer factor from worm to root-zone soil
       depth of root-zone soil (VS/AS)
                                                                                  (7-79)
       7.2.2.2 Soil Arthropods

       An equation for the uptake of chemicals by soil arthropods may be derived similarly to
that for earthworms.  Much of the available data relates the concentration of a chemical in the
fresh (wet weight) arthropod to that in food. The food may be plant matter rather than soil, but
for the purpose of TRIM.FaTE, the uptake factors are assumed to apply to soil.
where:
Thus,
                                 anh
                                        anh-Sr
                                                 Sr
                    arthropod-soil partition coefficient (wet kg/kg per wet kg/kg)
                                                                                  (7-80)
             dC
               dt
  -ln(l-0.95)
                           '095
-ln(l-0.95)
                                    '095
                                                                 c
                                                                   arlh
                                                              (7-81)
where:
        () 95
time required to reach 95 percent of the steady-state value when CSK is
approximately constant with time (d"1)
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Thus,
          dt
                         0.95
                                                 Sr
                                                             095
                                                                      C
                                                                        arlh
                                                              (7-82)
where:
       '095
time required to reach 95 percent of the steady-state value when CSr is
                     approximately constant with time (d'1)

If the areal density of arthropods is approximately constant with time, then:
   dt
where:
                  095
                            xpareaarlhAsKarlh_Sr x
                                                     N
                                                       Sr
                                M
                                         -ln(l-0.95)
                                                                   '0.95
                                                              (7-83)
       pareaarll
       mass of chemical in arthropods (kg)
       total mass of chemical in all phases of bulk root zone soil (kg)
       total mass of root zone soil, which contains arthropods (kg)
       area of soil surface (nr)
       areal density of arthropod community in root-zone soil (kg
       arthrop_pd fresh wt/m2)
Thus.
                T.
                  Sr—>arth
                           -ln(l-0.95)
                                '0 95
                                      K
                                                             arth—Sr
                                                             M
                                                               Sr
                                                              (7-84)
where:
                             ' arlh->Sr
                    -ln(l-0.95)

                         '(] 9^
                                                                                   (7-85)
       Tsr-anh  =      transfer factor from root-zone soil to arthropod
        Tar,h-sr =      transfer factor from arthropod to root-zone soil

       7.2.2.3 Flying Insects

       Flying insects are the food of insectivores (e.g., tree swallows). It may be assumed that
the concentration of a chemical in these organisms is equivalent to the concentration in benthic
invertebrates such as the mayfly (see Section 7.3.2).
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7.2.3   TERRESTRIAL MAMMALS AND BIRDS

       Terrestrial wildlife, including mammals and birds, may be exposed to chemicals through
food, soil, and water ingestion, and through inhalation of chemicals in air. In addition, chemicals
can be taken up dermally, but the rate of sorption to the skin surface is unknown, the rate of
uptake into the organism is unknown, and the quantity absorbed by the body (generally less than
3 percent) is low; thus, dermal uptake is not included in TRIM.FaTEl.  Elimination of chemicals
from body tissues may occur through metabolic transformation of the chemical or excretion of
the parent compound through urine, feces, milk (female mammals  only), eggs (female birds and
reptiles only), and excretion to fur, hair, or feathers. To account for these multiple routes of
exposure and elimination, the generalized model implemented for all terrestrial wildlife is
presented below.  In addition, the algorithm applies to semiaquatic populations, such as loons
and racoons.  If particular rate constants are determined to be insignificant relative to others for a
particular implementation of TRIM.FaTE (e.g., excretion via eggs  compared to excretion in urine
or feces), these may be set to zero.  Similarly, if rate constants for excretion and chemical
transformation are determined with respect to the mass of a contaminant that is taken up in the
diet rather than mass that is assimilated, the dietary assimilation efficiencies may be ignored.
However, the assimilation efficiencies for inhalation must always be greater than zero.
 I s~*
where:

       Cw/    =      total, whole body, internal concentration in wildlife (kg [chemical]/kg
                     [body weight])
       Iw     =      water ingestion rate (m3/kg body weight/d)
       Cw    =      concentration of chemical in water ingested by animal (kg/m3)*
       Av    =      assimilation efficiency of chemical from water (unitless)
       Iss    =      surface soil ingestion rate (kg/kg body weight/d)
       Css    -      concentration of chemical in surface soil (kg/kg)
       ASS    =      assimilation efficiency of chemical from surface soil (unitless)
       pp     =      proportion of plant matter in diet (unitless)
       ID     =      dietary ingestion rate (kg/kg body weight/d)
       C,     =      concentration of chemical in leaf component of diet (kg/kg)
       A,,    =      assimilation efficiency of chemical from plant in diet (unitless)
       Cu,    =      mass of chemical on leaf surface with respect i.o mass of leaf (kg/kg)
       Pw,rm   =      proportion of earthworm in diet (unitless)
       C*<>rm  =      concentration of chemical in earthworm component of diet (kg/kg)
       Av,,rm  ~      assimilation efficiency of chemical from earthworm in diet (unitless)
       Punh    ~      proportion of insect in diet (unitless)

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       Corlh   =      concentration of chemical in insect component of diet (kg/kg)
       Aarlh   =      assimilation efficiency of chemical from insect in diet (unitless)
       pw,     =      proportion of other wildlife in diet (unitless)
       Aw,    =      assimilation efficiency of chemical from other wildlife in diet (unitless)
       pf     -      proportion of fish in diet (unitless)
       Cf     =      concentration of chemical in fish component of diet (kg/kg, use oorrect
                     size range)
       Af     =      assimilation efficiency of chemical from fish in diet (unitless)
       pB1     =      proportion of benthic invertebrates or emergent flying insects in diet
                     (unitless)
       CBI    -      concentration of chemical in benthic invertebrates or flying insect
                     component of diet (kg/kg)
       ABJ    =      assimilation efficiency of chemical from benthic invertebrates or emergent
                     flying insects in diet (unitless)
       IA     =      inhalation rate (m3/kg body weight/d)
       CA     =      concentration of chemical in air, including vapor phase and particles
                     (mg/m3)
       AA     -      assimilation efficiency of chemical from air (unitless)
       Em     =      chemical transformation (d "')
       Eu     =      chemical elimination through excretory processes (urine and feces)(d '')
       E,     =      chemical elimination through lactation (milk production, mammals only)
                     (d-1)
       Ee     -      chemical elimination through egg production, birds only (d "')
       Ef     =      chemical elimination from fur. feathers or hair (d"1)

       Because the source of drinking water is not usually known and may include puddles, the
uptake of the chemical from water may be ignored for all species except the semiaquatic, which
are associated with a single water body.

       Thus, for a population,
                    .   ..,
                     s  x[
                            x
     dt          "'    s         VK       Vss x pvolssvet     Asx pareaL
    PP * 1D x NLP x AP + p..,, x 7D x NHofm x AHorm + Pjrr> x /0 x JVar[> x A,frt
       AsxpareaL           As x pareatiorm            As X pareaanh                   (7-87)
    t P»i xIpXN^xA., + PtxIDxNfxA, + Paf x /0 x JV8; x A,, +IAx N MR x AA
        As xparea^!          AJK x parea/         A,,  x pareaBl            VA
where:

       NM./           =      mass of chemical in all wildlife species in parcel (kg)
       pareaw/       =      wet wildlife biomass density per unit area (kg/m3, may be
                            calculated as number of animals times average body weight)

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       v
       pvolss\vet
       Ass
       Pi'
         P
       pareaL
       NLF
       Jr \vorm
       N
       Parlh
area of surface soil (m2)
water ingestion rate (m3/kg body weight/d)
mass of chemical in water source (kg)
volume of water (m3)
assimilation efficiency of chemical from water (unitless)
surface soil ingestion rate (kg/kg body weight/d)     _  _
mass of chemical in surface soil (kg)
volume of surface soil (kg)
wet bulk density of soil (kg/m3)
assimilation efficiency of chemical from surface soil (unitless)
proportion of plant matter in diet (unitless)
dietary ingestion rate (kg/kg body weight/d)
mass of chemical in plant leaves (kg)
assimilation efficiency of chemical from plant in diet (unitless)
areal biomass density of foliage (kg/m2, wet weight)
mass of chemical on surface of all foliage (kg)
proportion of earthworm in  diet (unitless)
mass of chemical in earthworms (kg)
assimilation efficiency of chemical from earthworm in diet
(unitless)
areal biomass density of earthworms (kg/m2, wet weight)
proportion of soil arthropods in diet (unitless)
mass of chemical in soil arthropods (kg)
assimilation efficiency of chemical from soil arthropods in diet
(unitless)
proportion of terrestrial wildlife in diet (unitless)
mass of chemical in wildlife component of diet (kg)
assimilation efficiency of chemical from other wildlife in diet
(unitless)
proportion offish in diet (unitless)
mass of chemical in fish (kg, use correct size range for diet)
assimilation efficiency of chemical from fish in diet (unitless)
areal biomass density offish (kg/m2, wet weight, use correct size
range for diet)
areal biomass density of insect (kg/m2)
proportion of benthic invertebrates or emergent flying insects in
diet (unitless)
mass of chemical in benthic invertebrates or emergent flying
insects (kg)
assimilation efficiency of chemical from benthic invertebrates or
flying insects in diet (unitless)
area of surface of surface water body (m2)
areal biomass density of benthic invertebrates (kg/m2, wet weight)
inhalation rate (m3/kg body weight/d)
mass of chemical in air, including vapor phase and particles (kg)
volume of air (m3)
       Pf
       "f
       Af
       pareaf
       FBI

       HBI

       ABI

       Aw
       pareah,
       h
       NAIR
        V,,
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       E,
assimilation efficiency of chemical from air (unitless)
chemical transformation (d"1)
chemical elimination through excretory processes (urine and feces)
(d-1)
chemical elimination through lactation (milk production, mammals
only)(d-')                                       -  -
chemical elimination through egg production, birds only (d"1)
chemical elimination from fur, feathers or hair (d"1)
       The TRIM.FaTE model has been parameterized for many wildlife species.  These are
listed in Table 7-1. Species-specific parameters, including body weights; water, soil, and food
ingestion rates; and inhalation rates are presented as means in Appendix A.

                                        Table 7-1
   Terrestrial and Semiaquatic Vertebrate Compartment Types Defined for TRIM.FaTE
Compartment Type (Trophic Functional Group)
Terrestrial Omnivore
Semi-aquatic Piscivore
Terrestrial Insectivore
Semi-aquatic Herbivore —
Terrestrial Predator/Scavenger
Semi-aquatic Insectivore
Terrestrial Vertebrate Herbivore
Semi-aquatic Omnivore
Terrestrial Ground-invertebrate Feeder
Representative Subgroup or Species
White-footed Mouse
Bald Eagle
Common Loon
Mink
Belted Kingfisher
Black-capped Chickadee
Mallard
Red-tailed Hawk
Long-tailed Weasel
Tree Swallow
White-tailed Deer
Mule Deer
Black-tailed Deer
Meadow Vole
Long-tailed Vole
Raccoon
Short-tailed Shrew
Trowbridge Shrew
       It is advisable for the user to turn on and off wildlife algorithms, to reflect:

       Winter sleep or hibernation;
       Migration;
       Timing of egg laying; and
       Timing of lactation.
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These seasonal components of TRIM.FaTE have not yet been implemented.

7.3   ALGORITHMS FOR AQUATIC BIOTA

      Aquatic compartment types in TRIM.FaTE are listed in Table 7-2.

                                     Table 7-2
               Aquatic Compartment Types in the TRIM.FaTE Prototype
Compartment Type (Trophic Functional Group)
Algae
Macrophyte
Water Column Herbivore
Water Column Omnivore
Water Column Carnivore
Benthic Invertebrate (Herbivore)
Benthic Omnivore
Benthic Carnivore
Representative Subgroup or Species
Generalized Algal Species
Elodea densa
Bluegill
Channel Catfish
Largemouth Bass
Mayfly
Channel Catfish
Largemouth Bass
7.3.1   AQUATIC PLANTS

       Aquatic vegetation is included as two separate compartment types, algae and
macrophytes.  Water is assumed to be the primary chemical source for both groups and is the
only pathway  included in TRIM.FaTE. The algal compartment type is considered to be
comprised primarily of phytoplankton, for which water is clearly the primary chemical source.
Although rooted macrophytes derive some nutrients and chemicals from the sediment source,
direct uptake from water is the primary pathway (Ribeyre and Boudou 1994).

       7.3.1.1 Algae

       At present, the only available algorithm for the uptake of contaminants by algae is
specific to mercury. It is presented in Section A. 1.2 of Appendix A.

       7.3.1.2 Macrophytes
                         •
       Uptake by aquatic macrophytes is given by the following concentration-based equation
for the chemical flux rate.
                   P   = k       V  C   - k       V  C
                    mp     rnp an— sw  mp  sw    ftp dep—s\\  tnp   tup
                                      (7-88)
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where:
        mp
       If
        mp,a
        mp
       c.u.
       c,
         mp
                     net flux of chemical in the macrophyte, (ug/day)
                     bioaccumulation rate constant for surface water (day"1)
                     volume of the macrophyte (L)
                     chemical concentration in water (ng/L)             —
                     depuration rate constant for surface water (day"1)
                     chemical concentration in macrophyte (ug/L).
       The rate constants kmpacc_svl and kmpdep_n,, for nonionic organic chemicals are estimated
using the following equations:
                              ,,cc-,w =0.0020 + 5007*.,,

                        •!/*.,,.*,-„= 1-58  + 0.000015Kt
                                                                            (7-89)

                                                                             (7-90)
       The rate constants kmpacc_sw and &m/jA,p_w for chemicals other than nonionic organic
pollutants were derived from bioconcentration factors using the time-to-steady-state conversion
as follows:
                          mp ,acc-sw
                                      -ln(l-a)
                                                      w— mp
                                                                                   (7-91)
where:
       K,
         \v-mp
       a
                             " mp,dep-sw
                                          -ln(l-a)
                                                                                   (7-92)
              water-macrophyte partition coefficient
              time required to reach lOOa percent of the steady-state value when the
              concentration in water is approximately constant with time
              fraction of steady-state attained
        The transfer of chemical mass from water to the macrophyte is given by:
                   dN
                       mp
                     dt
                                    N
                   = k         V    —
                       mp,acc-sw  mp  \!
                                               - k         N
                                                   mp ,dep-;\;    ,-np
                        (7-93)
where:
Nn,
k..,.
        nip
                            mass of chemical in the macrophyte (ug)
                            bioaccumulation rate constant for surface water (day"')
                            volume of the macrophyte (L)
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       Nw           =     mass of chemical in water (ug)
       Vw           =     volume of water in the cell (L)
                    =     depuration rate constant for surface water (day"1)
       The transfer factors for water to macrophytes and for macrophytes to water are given by:


                                       V   k
                                     _  mp  mp^cc-sw
                                            ir                                      \     '
                                                                                   (7-95)
7.3.2   BENTHICINFAUNA

       The benthic community is typically comprised of many different classes and species of
organisms, including those from the phyla Mollusca (e.g., clams and snails), Annelida
(oligochaetes), and Arthropoda (e.g., insects and crustaceans). All trophic levels are represented
within this community. This is true even within some families of insects, such as the mayflies
and chironomids. Although all trophic transfers within the benthic community could be
modeled, that is beyond the scope and needs of TRIM.FaTE.  Rather, all benthic infauna are
considered to represent the lowest heterotrophic level of the benthic food chain. The current
model construct identifies this group as the "Benthic Herbivores."

       An explicit dietary uptake component is not practical, given the highly variable diet
among benthic infauna. Rather, uptake is modeled based on the extraction of chemical  from
water (interstitial or overlying) or sediment.  It should be noted that at this time only one
chemical source (water or sediment) is considered. Selection of the primary source of
contamination is chemical dependent.  Neutral organic chemicals (e.g., PAHs)  are typically
evaluated based on uptake from water. If interstitial water is used the results often are considered
representative of total sediment exposures. Uptake of metals (i.e., mercury) is based on uptake
data from bulk sediments. Sediment chemical concentrations are not apportioned to separate
inorganic and organic (living and detrital matter) compartments in TRIM.FaTE. Thus uptake
from sediment implicitly  includes transfers from algal and detrital matter to the "Benthic
Herbivores."

       Immature burrowing  mayflies (Hexagenia spp.) are used as the representative benthic
invertebrates for both water and sediment exposures. They are common throughout the United
States, represent an important fish  forage resource, and are relatively well studied by aquatic
ecologists and toxicologists.

       7.3.2.1 Water to Benthic Infauna Transfers

       Uptake from water is given  by the following equation:
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                          dC
          - i,        C  ~ If       C
       i.  ~l(-bi,acc-w^w   "•bi.dep-w ^bi
                                                                                    (7-96)
where:
       c
        •bi.acc-w
       If
        •bi.dep-w
benthic invertebrate concentration (ug/g)
water (interstitial or overlying) concentration (ug/L)
uptake rate constant for water (day"1)
depuration rate constant for water.
       The rate constants kt,, acc_w  and kbl dep.w may be derived from the bioconcentration factors
using the time-to-steady-state conversion.
                           ' bi,acc-w
                                      -ln(l-a)
                                                       v-bi
                               ' bi,dep-w
                                          -ln(l-a)
                                                                                    (7-97)
                                                                                    (7-98)
where:

       Kw.b,   ~      water-benthic infauna partition coefficient.

Converting to mass units (N) yields the following equation:
dN
                                            N
                                m
                                  b,  bi,acc-w
        N
^bi,dep-w JV bi
                                                               (7-99)
where:
       "
       V...
mass of chemical in organisms comprising the benthic invertebrate
compartment type (ug)
number of organisms comprising the benthic invertebrate compartment
type
mass of individual organisms comprising the benthic invertebrate
compartment type
mass of chemical in water (|ag)
volume of water in the cell (L)
       Thus the transfer factors for water (interstitial or overlying) to benthic invertebrates and
for benthic invertebrates to water are given by:
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                                        bi
                                            V..
                                  T    -k
                                    hi—>w    bi,dep—v;

       7.3.2.2 Sediment to Benthic Infauna Transfers

       Uptake from sediment is given by the following equation:
                                                                            (7-100)


                                                                            (7-101)
where:
       Q,

       (-•sect
       If
       nbi,ace-sect
       ^
        bi,dep-sed
                       	—-k         C   -k         C
                         jf  ~ K'bi,acc-sed  ^ sed   ^ bi .dep-sed ^ bi
                    benthic invertebrate concentration (|ag/g)
                    Bulk sediment concentration (|ig/g)
                    uptake rate constant for sediment (day"1)
                    depuration rate constant for sediment.
                                                                             (7-102)
The rate constants kbl acc_sed and khl dep.sed may be derived from bioconcentration factors using the
time-to-steady-state conversion.
                         1 fci .QCC— sed
                                      -ln(l-a)
                                              ' sed-bs
                              ^ bt,dep— sed
                                           -ln(l-a)'
                                                                                     (7-103)
                                                                                     (7-104)
where:
^sect-bi
                     sediment-benthic invertebrate partition coefficient
                     time required to reach lOOa percent of the steady-state value when the
                     concentration in water is approximately constant with time
                     fraction of steady-state attained
       Converting to mass units (N) yields the following equation:
                dN

                                   N
                                              sed
                 dt
                                 * sed Psed
                                                  •-If
                                                     "•
                                                       bi,
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where:

       Nb,     =     mass of chemical in organisms comprising the benthic invertebrate
                    compartment type (ug)
       nbl     =     number of organisms comprising the benthic invertebrate compartment
                    type                                                  -  -
       mbl     =     mass of individual benthic invertebrates
       Nsed    =     mass of chemical in sediment (^g)
       Vsed    =     volume of sediment in the cell (L)
       Psed    =     bulk density of sediment (g/L)

       Thus the transfer factors for sediment to benthic invertebrates and for benthic
invertebrates to sediment are given by:

                                   = "». m» **• •«->«                             (7.106)
                                        VserfP,*,

                              Tbiased ~ kbi,dep-sed                               (7-107)
7.3.3   FISH

       Fish represent five of the trophic compartment types originally included in TRIM.FaTE:
the Benthic omnivore and carnivore and the water column herbivore, omnivore, and carnivore.
Two alternative approaches are used to estimate chemical uptake by fish in TRIM.FaTE, a
bioenergetic-based kinetic model and a time-to-steady-state-based kinetic model.  Each type has
strengths and weaknesses which make including both appropriate at this time.  The bioenergetic-
based model is ideal for explicitly incorporating multiple exposure pathways, but
parameterization is more difficult, especially for elimination rates. Parameters for the time-to-
steady-state-based kinetic model are generally available, but multiple pathways cannot be
explicitly incorporated simultaneously and the time required to reach a "steady-state" may be
uncertain for strongly bioaccumulated chemicals.  Currently, the bioenergetic model is
parameterized for PAHs and mercury, whereas the time-to-steady-state model is parameterized
for mercury only.

       The current structure of TRIM.FaTE has five trophic levels that are represented by fish.
They are presented as two separate food chains, one for water column organisms and one for
benthic organisms (see blue print). The water column food chain has no linkages to benthic
organisms, implying that this is a pelagic food chain. However, most applications of
TRIM.FaTE will be better represented by a littoral food chain, which includes linkages between
the water column and benthic food chains. The blue print  shows the benthic food chain linked to
rooted macrophytes and benthic algae, but not to planktonic algae.  Thus, neither food chain
alone adequately represents a littoral food chain.
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       To overcome this with minimal modification of the model architecture, each food chain
was assumed to be linear but individual species were assumed to reside in more than one food
chain or trophic level.  That is, water column carnivores consume 100 percent water column
omnivores, water column omnivores consume 100 percent water column herbivores
(planktivores), benthic carnivores consume 100 percent benthic omnivores, benthic omnivores
consume 100 percent benthic invertebrates.  However, a given piscivore (e.g., largemouth bass)
may consume omnivores from both food chains (e.g., 50 percent water column omnivores and 50
percent benthic omnivores). This is accounted for in the mass transfer formulas by dividing the
total biomass of the given piscivorous species into each food chain. In the largemouth bass
example, 50 percent of the biomass is  counted in each food chain.  The mass offish in each
trophic level is derived from studies of the biomass of individual species in various systems and
studies of feeding strategies of those species.

       7.3.3.1  Bioenergetic-based Kinetic Model

       The following model for estimating pollutant concentrations in fish (Thomann 1989) was
used as a starting point in the derivation of the transfer probabilities associated with the fish
compartment type:


                                     lxCDl-(RE+kl+kE+kc)xCF             (7-108)
where:

       C/.-     =     concentration in fish (ug/kg)
       ku      =     uptake rate constant from water via the gills ( 1 /kg-day)
       CWD    =     dissolved chemical concentration in water (ug/L)
       kD     =     chemical uptake from food (kg food/kg fish/day)
       P,      =     proportion of the diet consisting of food item I
       CD ,    =     chemical concentration in food item i (ug/kg)
       keg     =     rate constant for elimination via the gills (I/day)
       ki:     =     rate constant for elimination via fecal egestion (1 /day)
       RK     -     rate constant for metabolic transformation of chemical (I/day)
       kG     -     rate constant for dilution of chemical concentration from growth (I/day).

       For nonionic organic chemicals (PAHs), the chemical uptake rate constant kv is estimated
using the following formula:
                                                                                 (7-109)

where:

       ku     =     chemical uptake rate constant (L/day-kg[w])
       a)     =     body weight [g(wet)]
       y     =     allometric scaling factor (e.g.. 0.2 (Thomann 1989))

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       p     =     fraction lipid weight (kg[lipid]/kg[wet])
       E     =     efficiency of transfer of chemical.

       There is an apparent increase in assimilation efficiency for smaller organisms; therefore,
organisms have been divided into two weight groups:  less than 10 to 100 g (wet) and more than
100 g (wet) weight (Thomann 1989). The chemical assimilation efficiency (E) can-be -
approximated for these two size classes of organisms as follows.  For smaller organisms, the
following equations should be used to estimate E:

       For chemicals with log Kow = 2-5,   log E = -2.6 + 0.5 log Kow
       For chemicals with log Kow = 5-6,   log E = 0.8
       For chemicals with log Kow = 6-10,  log E = 2.9 - 0.5 log Kow

       For larger organisms, the following equations should be used to estimate E:


       For chemicals with log Kow = 2-5,   log E = -1.5 + 0.4 log Kow
       For chemicals with log Kow = 5-6,   log E = 0.5
       For chemicals with log Kow = 6-10,  log E = 1.2 - 0.25 log Kow

       Thomann (1989) gives the excretion rate from gills using the following equation:
                                         k
                                          OH
       For mercury, the following simplifying assumptions apply: 1) a single elimination rate is
used to describe elimination via the gills and egestion (KF = kE + keg), and 2) uptake from water is
excluded from the mercury transfer equation because it is negligible (Trudel and Rasmussen
1997).
       The mercury elimination rate constant (KE) is given by the following bioenergetic model
(Trudel and Rasmussen 1997) :

                   \nKE = 0.0667 -0.201nW +0.73^-6.56                   (7-111)

where:

       T      =     temperature (°C)
       W     -     weight of fish (g)
       E      =     exposure duration; 0=acute (<90 days), 1 =chronic (>90 days)

       Only chronic exposures apply to TRJM.FaTE. Therefore, the elimination rate constant is
reduced to:


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                      ln££ = 0.0667 -0.201nW -5.83                      (7-112)

       Trudel and Rasmussen (1997) based the elimination rate on the clearance of
methymercury only, because greater than 95 percent of mercury in fish is methymercury and the
elimination of methymercury is much slower than that of inorganic mercury (i.e., the overall rate
is dominated by the elimination of methymercury).                              —  -

       The bioenergetic-based kinetic model is generally used to estimate concentrations in
individual fish of a species. Following is the derivation of the fish model for tfie entire fish
population. Initially the model is derived for a population of two fish and then generalized  for
the case of n fish, where n is the fish population.  Initially, it is assumed that there is no uptake
through other food items, and the elimination via fecal egestion and the metabolic transformation
factors were neglected as they were considered second-order rates. Thus, for two fish with
concentrations Cn, and Cn, the previous equation can be rewritten as:

                           dct\                                                ti n-^
                           —  =k^xCWD-ktg}xC}]                            (7-113)

                          ^--k   xC   -k  xC                             (7-H4)
                                — t., T^^u/n  K .nt ^* *^ t -i                           ^      /
To convert the concentrations to masses, it is assumed that:

                                        Nw
                                ~CWD = VW '
                                                                               (7-115)
                                  Cfl=-^~,                                   (7-116)

                                         N7
                                  Cf2=~^L>                                   (7-H7)


where:

       m,    =     mass offish 1 (kg)
       m2    -     mass of fish 2 (kg)
       N,    -     mass of chemical in fish 1 (ug)
       N2    -     mass of chemical in fish 2 (ug)
       Nw    -     mass of chemical in surface water cell (fig)
       Vw    -     volume of surface water cell (L).

Substituting yields:
                           d(N./m,)      Nw       N,
                              y  "^-JL-&   -L                          (7_118)
                              at         V,,,       tn,
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Adding these equations yields the mass transfer equations for the total fish compartment type, as
follows:

                           d(NJm1)      N
                                            w
                                     -k  — — -it
                               dt     -*"V    *««2m
       Making the simplifying assumptions that individual fish mass is represented_by a
population average mf(m, = m2 = mj), and that ku, = ku2 = &uand kegl = keg2 = keg, yields:
                                             N          N,        N
                                                -
       This equation can be generalized from 2 to % fish, with A^(= N/+N?) being the total mass
in the fish compartment type to yield the following generalized CMT equation for a fish
compartment type:
                            mf            N        N +N                        (7-121)
                                 J = 2 k    w   '     '     2
                           dt           u  Vw
Generalizing this equation to include-feeding yields the following food chain mass transfer
equations for the individual fish species.

                          dN,            Nw
       It is important to note that the equations in their present form exclude dermal uptake as a
significant exposure route. The equations include gill uptake (bioconcentration) and'food uptake
(biomagnification) as the two principal exposure routes. Following are the food web equations:

Aquatic herbivore (fh = fish herbivores) (100 percent macrophyte diet):
                                                          E —^                 (7-123)
                                                             mp
where:
                    feeding rate constant (kg[prey]/kg[predator]-day)
                    efficiency of transfer of chemical.
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       The feeding rate (FD) is given by the following bioenergetic model presented in Gobas
(1993).
                     FA All vx i/ 0 85 . .   (0 06x7")
                 D = U-U^Z xvF   xe
where:
       VF
       T
          mass of the fish (kg)
          temperature (°C)
Aquatic omnivore (f0 - fish omnivore):
                                                                                 (7-124)
       dN
          f°
          -
N

                                                           N
                                                                                 (7-125)
Aquatic carnivore (fc = fish carnivore):
      dN
        dt
•= nfc ku mfc -f- - k
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                                 T           - k
                                  fish-*water   ^ t
                                                                                   (7-129)
       A specific fish domain (i.e., benthic omnivore, benthic carnivore, water column
herbivore, water column omnivore, or water column carnivore) to the water domain, using the
bioenergetic-based kinetic model for mercury is given by:                        — -
                             T                   — K
                              receptor (fish)—twater      E
                                                                                    (7-130)
       7.3.3.2 Time-to-steady-state-based Kinetic Model

       The time-to-steady-state model is based on the assumption that one pathway accounts for
the vast majority of the chemical uptake. Thus, only one chemical source is explicitly considered.
The model is of the general form:
        dC
           receptor
           dt
                    -ln(l-a)
                                x K           x C
                                    receptor-source    source
-ln(l-a)
                                                                     C
                                                                       receptor
                          (7-131)
where:
        v
       ^•recepior-.iource
       r
         receptor
       a
                     =      receptor-source partition coefficient
                     =      concentration in receptor
                            concentration in source
                     =      time required to reach lOOoc percent of the steady-state value when
                            the concentration in the  source is approximately constant with time
                     =      fraction of steady-state attained

       If the sole chemical source is water, then Kreceplor_source is a bioconcentration factor.
Bioaccumulation factors (BAFs) implicitly include uptake from food and water, though water is
the identified source.  This presumes that the concentration in the food item is essentially
constant relative to the concentration in the water.  An alternative approach is the use of dietary
concentrations as the primary source.  Thus, empirically derived accumulation data are used to
derive factors for each trophic transfer and uptake from water is implicitly, rather than explicitly,
included. This alternative is used herein.

       Following this approach requires the dietary sources be restricted to one other trophic
group. Thus intratrophic group transfers and multitrophic group transfers are not explicitly
included. These transfers are implicitly included to the extent that the empirical data used to
derive the transfer factors are from systems possessing those transfers.  Thus, the "fit" of the
model results for any given case study will be partly dependent on how well the food chains at
the sites used to derive the transfer factors match the food chains at the case study site (e g.,
length of the food chains, number of interconnections, degree of intratrophic group transfer, etc.).
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       Restriction of the dietary pathway  was achieved within TRIM.FaTE by redefining the
generic trophic compartment types to represent a straight food chain of three or four segments.
As noted in Section 7.3.2, the benthic herbivore compartment type is; represented by all benthic
invertebrates and the sediment (or interstitial water) is the chemical source. The benthic
omnivore compartment type in this approach is the next trophic level up from the benthic
invertebrates and the benthic carnivore compartment type contains those fish that cettsume the
benthic omnivores. This is in contrast to the bioenergetic model, which accounts for the
fractions of the omnivore diet from plants and herbivores.

       A similar approach is used to configure the water column food chain.  Three trophic
levels are explicitly identified in TRIM.FaTE: the water column herbivore, omnivore, and
carnivore.  These correspond to the first, second, and third heterotrophic levels of the food  chain,
respectively.  Chemical transfer is unidirectional from lower to higher trophic levels. Thus
omnivores  are assumed to consume herbivores only, rather than herbivores and algae.  It is
important to note that zooplankton have been implicitly included in the transfers from algae to
herbivores. That is, the biomass and chemical mass associated with zooplankton are not
explicitly tracked in TRIM.FaTE, but the dietary transfers are based concentration ratios for
planktivorous fish and algae. Some studies provide the intermediate transfer factors for algae to
zooplankton, but that compartment type is not currently maintained within TRIM.FaTE.

       For each trophic level transfer, the general concentration based equation is converted to
the following mass transfer equation:
 dN
    receptor
    dt
            receptor  receptor
   -ln(l-a)
 N
                                                        die!
                                         1 receptor-die!
-ln(l-a)'
                                                                          A'
                                                                            receptt
where:
         receptor

       ^receptor

       "receptor
       N.
         diet
        ld,el
       m.
         diet
   mass of chemical in the receptor
   number of receptors
   mass of individual receptors
   mass of chemical in items comprising the potential diet
   number of contaminated items comprising the potential diet
   mass of individual  items comprising ihe potential diet
For example, the mass transfer equation for water column herbivores is given as:
 dN
    f ."CO
   dt
-ln(l-a)
N
                              f ,»ch
                                       f ,«<•„-/ Hf*
 -ln(l-a)
                                                                               .<„ (7-133)
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                                                                             CHAPTER 7
^__^_	^_	BIOTIC ALGORITHMS

where:

       Kf,Wco-f,Wch      =      fish, water column omnivore - fish, water column herbivore
                           partition
       Nfwco         =      mass of chemical in fish comprising the water column omnivore
                           compartment type                               —•  -
       nfwco         =      number of fish comprising the water column omnivore
                           compartment type
       mfwco         =      mass of individual in fish comprising the water column omnivore
                           compartment type
       Nfwch         =      mass of chemical in fish comprising the water column herbivore
                           compartment type
       nfwch         =      number of fish comprising the water column herbivore
                           compartment type
       mfwch         =      mass of individual fish comprising the water column herbivore
                           compartment type

       For each trophic level transfer, the generalized transfer factors for dietary items to a
specific fish domain (i.e., benthic omnivore, benthic carnivore, water column herbivore, water
column omnivore, or water column carnivore) and for a specific fish domain to dietary items are
given by:
                         ' * V n f n n t n f •' * r a /* o n t n t-        1I1V1   \Jv)
     _                    receptor   receptor
      diel^receptor( fish)
                            "die, md,e,
X Kreceptor_diet      (7-B4)
                       T
                        receptor (fish)—td           .
                                           -ln(l-a)
                                                a
                    (7-135)
       7.3.3.3 Other EPA Models for Bioaccumulation by Fish

       Aquatox is a general ecological risk model that estimates the fate and effects of chemical
and physical stressors in aquatic ecosystems (U.S. EPA 1998c). The model has been developed
by the Office of Pollution Prevention and Toxics (OPPT) and the Office of Water (OW). The
Bioaccumulation and Aquatic System Simulator (BASS), developed by the National Exposure
Research Laboratory (NERL) of the Office of Research and Development (ORD), also simulates
exposure and effects on fish (U.S. EPA 1999c). Aquatox and BASS are designed to predict
effects of chemical contaminants and environmental factors on fish populations, whereas
TRIM.FaTE is designed to estimate the fate and transport of chemicals throughout aquatic and
terrestrial environment, with an emphasis on a collection of identical, individual fish.  This
difference in purpose results in several differences in structure: (1) Aquatox and BASS include
chemical toxicity data; TRIM.FaTE does not (although TRIM.Risk is designed to include such a
database); (2) the toxicological data in Aquatox and BASS are used to predict mortality, which is
used to modify the structures of the models (e.g., age-class structure and predator-prey

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CHAPTER 7
BIOTIC ALGORITHMS
interactions); (3) in Aquatox, decomposition of dead fish and contaminants are linked to the
dissolved oxygen levels in water, which affect populations; and (4) growth estimation offish is
fundamental to the population dynamics component of BASS, and growth is not included in the
current prototype of TRIM.FaTE.

       BASS (U.S. EPA 1999c) and Aquatox (U.S. EPA 1998c) are bioenergetic medels of a
multiple trophic level aquatic ecosystem. Aquatox, like TRIM.FaTE, provides an explicit steady-
state option, whereas BASS does not.  Like TRIM.FaTE, Aquatox has a Monte Carlo component
to permit probabilistic estimates of exposure or risk. The developers of BASS plan to include
metabolism of organic compounds in future versions of the model, but, unlike TRIM.FaTE, these
transformations are not a feature of the current version (U.S. EPA 19'99c). Components of
Aquatox or Bass could be integrated with TRIM.FaTE.  The challenge would be to preserve mass
balance and to provide adequate links to all TRIM.FaTE compartment types that are connected to
surface water and/or fish.

7.4    REVISIONS IN BIOTIC ALGORITHMS

       Changes in algorithms since the PAH test case are identified in Table 7-4. It should be
noted that PAH-specific parameters for generic algorithms have not been obtained and presented
in Appendix A unless the algorithm was used in the 1998 test case.
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                                                                         CHAPTER 7
                                                                   BIOTIC ALGORITHMS
                                     Table 7-4
   Differences Between Algorithms Implemented in the PAH Test Case and New Generic
                    Algorithms that Would be Applicable to PAHs
Process
Deposition of particles to
plant leaf
Particle washoff from plant
Transfer from surface of leaf
to leaf and back
Mesophyll resistance
Uptake by root
Uptake by stem
Uptake by earthworm
Uptake by soil arthropods
Uptake by algae
Uptake by fish
Algorithm or Assumption
Implemented in 1998 PAH Test
Case
Particles deposited to plant leaf, leaf
surface and leaf not separate compartment
types
Particles washed off leaf at rate equal to
oeposition rate; 5 percent participate mass
to air and 95 percent to soil
Not implemented because these were part
of a single compartment type
Not implemented
Uptake from soil water (see below)
Xylem and stem (see below) treated as
compartment types; all uptake from soil via
root
Uptake from soil water (see below)
Not included in model
Not included in model
Bioenergetic model implemented
1999 Generic Algorithm or
Assumption
Particles deposited to plant leaf; leaf surface
and leaf separate compartment.types
Particles washed off plant at rate in McCune
and Lauver (1986), Sect. 7.2.1.1 of this volume;
100 percent of particles to soil
First order rate constant, Sect. 7.2.1.1
Implemented as a generic algorithm, though
assumed to be negligible for PAHs
Uptake from whole soil
Stem treated as a compartment type; exchange
between stem and leaf, and stem and root
Uptake from whole soil
Uptake from whole soil
Uptake from surface water
Bioenergetic model is one of 2 options (other is
time to equilibrium with diet)
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                                                                              CHAPTER 8
	                    REFERENCES

8.     REFERENCES

Ambrose, R.A., Jr., T.A. Wool, and J.L. Martin. 1995. The water quality analysis simulation
program, WASPS.  Part A: Model documentation,  Athens, GA: U.S. EPA National Exposure
Research Laboratory, Ecosystems Division.                                   __

ARS. 1982. Agricultural Research Service.  Analytical solutions of the one-dimensional
convective-dispersive solute transport equation. Washington, DC: U.S. Department of
Agriculture.

Baes, C.F., III, R.D. Sharp, A.L. Sjoreen, and R.W. Shor.  1984. A review and analysis of
parameters for assessing transport of environmentally released radionuclides through agriculture.
ORNL-5786. Oak Ridge, TN:  Oak Ridge National Laboratory.

Bennett, D.H., I.E. McKone, M. Matthies, and W.E. Kastenberg. 1998. General formulation of
characteristic travel distance for semivolatile organic chemicals in a multimedia environment.
Environ. Sci. Technol. 32:4023-4030.

Briggs, G.G., R.H. Bromilow, A.A. Evans, and M.R. Williams. 1983. Relationships between
lipophilicity and the distribution of non-ionised chemicals in barley shoots following uptake by
the roots. Pestic. Sci.  14:492-500.

Briggs, G.G., R.H. Bromilow, and A.A. Evans. 1982.  Relationship between lipophilicity and
root uptake and translocation of non-ionised chemicals by barley.  Pestic. Sci.  13:495-504.

Covar, A.P. 1976.  Selecting the proper reaeration coefficient for use in water quality models.
Presented at the U.S.EPA Conference on Environmental Simulation Modeling, April 19-22,
Cincinnati, OH.

Crank, J., N.R. McFarlane, J.C. Newby, G.D. Paterson, and J.B. Pedley. 1981. Diffusion
processes in environmental systems.  In: Paterson et al. 1991.  London: Macmillan Press, Ltd.

Di Toro, D.M. and J.P. Connolly. 1980. Mathematical Models of water quality in large lakes,
Part 2: Lake Erie. EPA-600/3-80-056. pp. 28-30.

Gobas, Fapc. 1993. A model for predicting the bioaccumulation  of hydrophobic organic-
chemicals in aquatic food-webs - Application to Lake  Ontario.  Ecological Modeling.  69:1-17.

Hargrove, W.W. 1999. Personal communication.  University of Tennessee.  January.

Harner and Bidleman. 1998. Octanol-air coefficient for describing particle/gas partitioning of
aromatic compounds  in urban air. Env. Sci. Tech.  32:1494-1502.

Junge, C.E.  1977.  Basic considerations about trace constituents in the atmosphere as related to
the fate of global pollutants. In: Suffet, I.H., ed. Fate of pollutants in the air and water
environments.  New York: Wiley and Sons, pp. 7-26.

NOVEMBER 1999                               fTi              TRIM.FATE TSD VOLUME II (DRAFT)

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CHAPTER 8
REFERENCES
Jury, W., W. Spencer, and W. Farmer. 1983. Behavior assessment model for trace organics in
soil: I. Model description.  J. Environ. Qual.  12:558-564.

Karickhoff, S.W.  1981.  Semi-emperical estimation of sorption of hydrophobic pollutants on
natural sediments and soils.  Chemosphere. 10:833-846.

Leonard, T.L., G.E. Taylor, Jr., M. S. Gustin, and G.C. J.  Fernandez.  1998.  Mercury and
plants in contaminated soils: 2. Environmental and physiological factors governing mercury
flux to the atmosphere. Environ. Toxicol. Chem. 17:2072-2079.

Lindberg, S. 1999a. Personal communication. Oak Ridge National Laboratory. January.

Lindberg, S. 1999b. Personal communication.  Oak Ridge National Laboratory. September.

Lindberg, S.E., T.P. Meyers, G.E. Taylor, Jr., R.R. Turner, and W.H. Schroeder. 1992.
Atmosphere-surface exchange of mercury in a forest:  Results of modeling and gradient
approaches.  J. Geophys. Res. 97:2519-2528.

Mackay, D.  1991. Multimedia environmental models: The fugacity approach. Chelsea, MI:
Lewis Publishers.

Mackay, D., M. Joy, and S. Paterson. 1983a. A quantitative water, air, sediment interaction
(QWASI) fugacity model for describing fate of chemicals in lakes.  Chemosphere.  12: 981-997.
Mackay, D., S. Paterson, and M. Jo)^ 1983b. A quantitative water, air, sediment interaction
(QWASI) fugacity model for describing fate of chemicals in rivers. Chemosphere. 12: 1193-
1208.

Mackay, D. and P.J. Leinonen.  1975. Rate of evaporation of low-solubility contaminants from
water bodies to atmospheres. Environ. Sci. Technology.  7:61 1-614.

Mackay, D. and A.T.K. Yuen. 1983. Mass transfer coefficients correlations of volatilization of
organic solutes from water.  Environ. Sci. Technol. 17:21 1-216.

McCune, D.C., and T.L. Lauver. 1986. Experimental modeling of the interaction of wet and dry
deposition on conifers.  In: Lee, S. F., T. Schneider, L. D. Grant, and P. J. Verkerk, eds.
Aerosols:  Research, risk assessment, and control strategies. Proceedings of the Second U. S.-
Dutch International Symposium, Williamsburg, VA, pp. 871-878. May 1985.

McKone, T.E. 1993a. CalTOX, A multimedia total-exposure model for hazardous- wastes sites
Parti: Executive summary. Laboratory. UCRL-CR-111456PtI. Livermore, CA: Lawrence
Livermore National.

McKone, T.E. 1993b. CalTOX, A multimedia total-exposure model for hazardous-wastes sites
Part II:  The dynamic multimedia transport and transformation model.  UCRL-CR-1 1 1456PtII.
Livermore, CA:  Lawrence Livermore National Laboratory.

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                                                                              CHAPTER 8
	REFERENCES

McKone, T.E. 1993c. CalTOX, A multimedia total-exposure model for hazardous-wastes sites
Part III: The multiple-pathway exposure model.  UCRL-CR-111456PtIII.  Livermore, CA:
Lawrence Livermore National.

Mill, T., W.R. Mabey, P.C. Bomberger, T.W. Chou, D.G. Herdy, and J.H. Smith. 1982.
Laboratory protocols for evaluating the fate of organic chemicals in air and water. EPA-600/3-
82-0220. U.S. Environmental Protection Agency. Athens, GA.

Millington, R.J. and J.M. Quirk. 1961. Permeability of porous solids. Trans. Faraday Soc.
57:1200-1207. In: Wallachetal. 1989.

Muller, H., and G. Prohl.  1993.  Ecosys-87: A dynamic model for assessing radiological
consequences of nuclear accidents. Health Phys. 64:232-252.

Nobel, P.S. 1991. Physicochemical and environmental plant physiology.  San Diego, CA:
Academic Press.

O'Connor, D.J. 1983. Wind effects on gas-liquid transfer coefficients. J. of Environ. Eng.
109(9):731-752.

Paterson, S., and D. Mackay. 1995.  Interpreting chemical partitioning in soil-plant-air systems
with a fugacity model. In:  Trapp, S. and J.C. McFarlane, eds. Plant contamination:  Modeling
and simulation of organic chemical processes.  Boca Raton, FL: Lewis Publishers, pp. 191-214.

Paterson, S., D. Mackay, and A. Gladman. 1991.  A fugacity model of chemical uptake by plants
from soil and  air.  Chemosphere. 23:539-565.

Post, W.M. 1999. Personal communication. Oak Ridge National Laboratory. January.

Ribeyre, F. and A. Boudou. 1994. Experimental-study of inorganic and methylmercury
bioaccumulation by 4 species of fresh-water rooted macrophytes from water and sediment
contamination sources. Ecotoxicology and Environmental Safety. 28(3):270-286.

Riederer, M.  1995. Partitioning and transport of organic chemicals between the atmospheric
environment and leaves. In:  S. Trapp and J. C. McFarlane, eds. Plant contamination:
Modeling and simulation of organic chemical processes. Boca Raton:  Lewis Publishers, pp.
153-190.

Schnoor, J.L.  1981. Fate and transport of dieldhn in Coraville Reservoir:  Reisdues in fish and
water following a  pesticide ban.  Science. 211:840-842.

Schnoor, J.L.  and  D.C. MacAroy. 1981. A pesticide transport and bioconcentration model. J.
Environmental Engineering Div. American Society of Civil Engineers. 107:1229-1245.

Simonich, S.L. and R.A. Hites. 1995.  Global  distribution of persistent organochlorine
compounds.  Science.  269:1851-1854.

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CHAPTER 8
REFERENCES
Thomann, R.V.  1989.  Bioaccumulation model of organic-chemiccil distribution in aquatic food-
chains. Environmental Science & Technology. 23(6):699-707.

Trapp, S. 1995. Model for uptake of xenobiotics into plants. In:  Trapp, S. and J. C.
McFarlane, eds. Plant contamination: Modeling and simulation of organic chemical processes.
Boca Raton, FL: Lewis Publishers, pp. 107-151.                              —  -

Trudel, M. and J.B. Rasmussen. 1997. Modeling the elimination of mercury by fish.
Environmental Science & Technology. 31:1716-1722.

Tsivoglou, E.E. and J.R. Wallace.  1972.  Characterization of stream reaeration capacity. EPA-
R3-72-012. U.S. Environmental Protection Agency.  Washington, DC.

Turner, R.  1998. Personal communication. Frontier Geosciences. August.

U.S. EPA.  1999a. U.S. Environmental Protection Agency.  The Total Risk Integrated
Methodology: TRIM.FaTE technical support document. Volume I Description of module.
Draft.  EPA-453/D-99-002A.  Office of Air Quality Planning and Standards.

U.S. EPA.  1999b. U.S. Environmental Protection Agency.  The Total Risk Integrated
Methodology: TRIM.Expo Technical Support Document. External Review Draft.  EPA-453/D-
99-001. Research Triangle Park, NC: Office of Air Quality Planning and Standards. November.

U.S. EPA.  1999c. U.S. Environmental Protection Agency.  Bioaccumulation and Aquatic
System Simulator (BASS) user's mamial beta test Version 2.0. Internal Draft as supplied by
Craig Barber.  Research Triangle Park, NC: Office of Research and Development.

U.S. EPA.  1998a. U.S. Environmental Protection Agency.  The Total Risk Integrated
Methodology: Technical support document for the TRIM.FaTE module. Draft. EPA-452/D-98-
001. Office of Air Quality Planning and Standards.

U.S. EPA.  1998b. U.S. Environmental Protection Agency.  The Total Risk Integrated -
Methodology: Implementation of the TRIM conceptual design through the TRIM.FaTE module.
A Status Report. EPA-452/R-98-001. Office of Air Quality Planning and Standards.

U.S. EPA.  1998c. U.S. Environmental Protection Agency.  AQUATOX for Windows: A
modular toxic effects model for aquatic ecosystems. Internal Draft.  Washington,  D.C.: Office
of Pollution Prevention and Toxics.

U.S. EPA.  1997a. U. S. Environmental Protection Agency. Mercury study report to congress.
Volume III: Fate and transport of mercury in the environment. EPA-452/R-97-005. U.S. EPA
Office of Air Quality Planning and Standards and Office of Research and Development.

van de Water, R.B. 1995.  Modeling the transport and fate of vola:ile and semi-volatile organics
in a multimedia environment. Ph.D. Dissertation. Chemical Engineering, University of
California, Los Angeles.

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                                                                              CHAPTER 8
                                                                             REFERENCES
Wallach, R., W.A. Jury, and W.F. Spencer.  1989. The concept of convective mass transfer for
prediction of surface-runoff pollution by soil surface applied chemicals. Transactions of the
ASAE.  May-June. 1989.

Watras, C.J., K.A. Morrison, and J.S. Host.  1995. Concentration of mercury species in
relationship to other site-specific factors in surface water of northern Wisconsin lakes. -
Limnology and Oceanography.  40(3):556-565.

Whicker, F.W. and T.B. Kirchner.  1987. Pathway:  A dynamic food-chain model to predict
radionuclide ingestion after fallout deposition. Health Phys. 52:717-737.

Whitby, K.T. 1978. The physical characteristics of sulfur aerosols. Atmospheric Environment.
12:135-159.

Whitman, R.G.  1923. A preliminary experimental confirmation of the two-film theory of gas
absorption. Chem. Metallurg. Eng.  29:146-148.

Wilmer, C., and M. Flicker. 1996. Stomata. Seconded. New York, NY: Chapman & Hall.
p.121.

Wilson R. and J.D. Spengler, eds. 1996. Particles in our air: Concentrations and health effects.
Cambridge, MA: Harvard School of Public  Health.
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                                                                          APPENDIX A
                              DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                 APPENDIX A
 DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND
                           INPUT PARAMETERS

       This appendix contains derivations of chemical-specific algorithms, paramelers,~and
information used to derive those parameters. The majority of the appendix focuses on chemical
transformations, but information on uptake and distribution of chemicals is also included.

A.I   MERCURY-SPECIFIC ALGORITHMS

A.1.1  PLANT MESOPHYLL RESISTANCE

       A general plant algorithm for mesophyll resistance was added to TRIM.FaTE because of
the properties of mercury. For most organic chemical species and most plant species, the
stomatal or cuticular conductance is the rate-limiting pathway (Riederer 1995). Therefore, for
many chemicals, there is no need to consider mesophyll (inner tissue) conductance.  However,
some work with mercury cited in Lindberg et al. (1992) suggests that "resistance on or within
mesophyll surfaces dominates the atmosphere-leaf diffusive path of Hg(0)."

       In herbaceous species, it may be assumed that this mesophyll resistance is a factor of 2.5
x stomatal resistance (Lindberg et al.  1992) and that mesophyll conductance is a factor of 1/2.5 or
0.4 x stomatal conductance. It is suggested that the following equation be used for elemental
mercury only:                   ^

                                  gm ~ gstomata * 0.4

where:

       gm     =     conductance of chemical through mesophyll (m/d)

       It should be noted that the high mesophyll resistance of elemental Hg may be due to its
assimilation in mesophyll tissue (Lindberg et al. 1992).  It has previously been assumed that the
mesophyll resistance  for divalent mercury is 0 (U.S. EPA 1997a); i.e., that gm is infinite. It is
assumed that mesophyll resistance for methylmercury is also 0, based on a lack of information.

A.1.2  ALGAE

       The uptake of pollutants by algae  is generally assumed to occur by passive diffusion. The
algorithm for chemical uptake by algae in TRIM.FaTE has only been derived for mercury at this
time.

       Passive uptake of uncharged, lipophilic chloride complexes  is the principal accumulation
route of both methylmercury and inorganic mercury in phytoplankton and is determined by water
chemistry, primarily pH and chloride  concentration (Mason et al. 1996). Mason and others


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APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
(Mason et al. 1995, Mason et al. 1996) developed an accumulation model for the marine diatom
(Thalassiosira weissflogii) and modified it for use with "typical" freshwater algae for the
purposes of predicting mercury accumulations in fish. It assumes that uptake via passive
diffusion is determined by the overall Kow (i.e., the Dow) for the neulral mercury complexes
present in solution. The Dow is given as the sum of the individual Kows for each mercury species
by the folio wing equation (Mason etal. 1996):                                 —  -
       Where f, = mole fraction of total mercury present as species i. The fractional amount of
total mercury present as each neutral mercury species was estimated as a function of pH and
chloride concentration. The predicted inorganic mercury (divalent) and methylmercury Dow for
each of five pH levels (pH 4, pH 5, pH 6, pH 7, and pH 8) and for chloride concentrations
ranging approximately from 0.01  mg/1 to 10,000 mg/1 was presented graphically in (Mason et al.
1996). These Dows in TRIM.FaTE were estimated based on those curves.

       Uptake of inorganic mercury (divalent) and methylmercury by algae is given by the
following equation (Mason et al. 1996)

                                     Z)olvXL/x4jtfl2
                                           fr xpxp,

where:
            ac =      concentration in algae (nmol g"1)
            mr =      concentration in water (nM)
       Dow   =      overall KQW for neutral mercury complexes at specified pH and chloride
                     concentrations (unitless)
       U     =      algal surface area-specific uptake rate constant (nmol ^.m"2 d"1 nM"1)
       R      =      average radius of algae ((im)
       p      =      average cell density (g urn"3)
       I*.      =      growth rate constant (d"1)

       Note that this equation uses moles. Gram weights are derived by multiplying the moles
per gram or liter by the chemical-specific molecular weight. Table 7-1 shows the molecular
weights of mercury and methylmercury in the units appropriate for converting the above algae
(nmol g"') and water (nM) concentrations.
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                               DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                       Table 7-1
                   Molecular Weights of Mercury and Methylmercury.
Chemical
Hg
CH3Hg
Molecular Weight
g mol"1
200.59
215.62
ug nmol"1
2.0059 x10'1
2.1562x10'1
mgjinnor1
2.0059 X10"4
2.1562 X10-4
       Uptake is assumed to be  instantaneous relative to the time steps used in TRIM.FaTE,
given that the process occurs in hours rather than days (Mason et al. 1996). Also, uptake of
elemental mercury is assumed to be insignificant in TRIM.FaTE, based on the findings of
(Mason et al. 1996) that the accumulation rates were less than  1 amol cell"1 h'1 nM"1, where amol
equals 1 x 10~'8 moles.

A.1.3  ACCUMULATION OF MERCURY BY FISH

       Mercury concentrations in fish are ultimately determined by methylmercury accumulation
at the base of the food chain (Mason et al. 1995, Mason et al. 1996). Therefore, one alternative
algorithm for the uptake of mercury in fish based on the general equation for the time-to-steady-
state food chain model is presented in Section 7.3.3. Intertrophic level concentration ratios
(K-receptor-diet) were obtained from studies of natural populations offish, zooplankton, and
phytoplankton. Based on studies using MHg/N ratios in whole fish ,the concentration ratio
between two trophic levels was found to generally be around 3 to 4 (studies cited in Lindqvist et
al. (1991).  As noted in Section 7.3.3, mercury transfers from algae to water column herbivores
includes the intermediate transfer from algae to zooplankton. Concentration ratios between
planktivorous fish and phytoplankton were between 9 and 16 (Lindqvist et al. 1991, Watras and
Bloom 1992).  That is, zooplankton were an intermediate trophic level and the transfers between
each trophic level were approximately equal. Taking the geometric mean results in approximate
concentration ratios for methylmercury of 3.5 for one trophic level transfer and 12 for two
trophic level transfers (Mason et al. 1996).
                                                                           *
       Inorganic mercury (divalent) transfer factors between phytoplankton and zooplankton and
between zooplankton and planktivorous fish are given by Watras and Bloom (1992). In the
absence of similar factors for fish to fish transfers of inorganic mercury, the zooplankton to
planktivorous fish transfer factor was used to estimate the concentrations in the water column
omnivore, water column carnivore, benthic omnivore. and benthic carnivore compartment types.

A.2   INPUT PARAMETERS SPECIFIC TO MERCURY
       TRANSFORMATION

       Since there are three species of mercury, there are six possible transformation routes from
one species to another. All but one of these routes will be considered:
NOVEMBER 1999
A-3
TRIM.FATE TSD VOLUME II (DRAFT)

-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
       Reduction                 Hg(2)^ Hg(0)
       Oxidation                 Hg(0) -»• Hg(2)
       Methylation               Hg(2)-> CH3Hg
       Demethylation             CH3Hg -* Hg(2)
•      Mer cleavage demethylation CH3Hg -> Hg(0)

The route not considered is methylation of Hg(0), for which little information has been reported.

       In the case of mercury, the transformation from one chemical species to another is
modeled using a first-order rate constant.  In particular, the following general equations are used
to model transformation.
                                   Reduction, Hg2'-Hg°:
                                                     dM,
                                                      dt
                                   Oxidation, Hg°-Hg2f:
                                Methylation, Hg2t~CH,Hg:
                       dM2
                        dt
                   a'-7"'
                       dM3
                        dt
Demethylation, CH^Hg-Hg2^'.
                    Mer cleavage demethylation, CH3Hg~Hg°:
                                                     dM.
                                                    -~
where:

       M,     =     mass of elemental mercury [Hg(0)] in a compartment type
       M2     =     mass of divalent mercury [Hg(2)] in a compcirtment type
       M3     =     mass of methylmercury (CH3Hg) in a compartment type
       kr      =     reduction rate in compartment type, 1/day
       k0      =     oxidation rate in compartment type, I/day
       km     =     methylation rate in compartment type, I/day
       kdm     =     demethylation rate in compartment type, I/day
       kmc     —     mer cleavage demethylation rate in compartment type, 1/day

The transformation rates may be input directly, or calculated based on other parameters.  If both
algorithms and input values are available, then the user will be able to choose which method to
use.
NOVEMBER 1999                             A-4             TRIM.FATETSD VOLUME II (DRAFT)

-------
                                                                        APPENDIX A
                             DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
A.2.1  ABIOTIC MERCURY TRANSFORMATION PARAMETERS

      The information in Tables A-2 through A-13 is taken primarily from the 1997 Mercury
Report to Congress (U.S. EPA 1997a) and model documentation for EPRI's R-MCM Mercury
Cycling Model (Hudson et al. 1994).

                                    Table A-2
    Issues Related to Reduction of Hg(2) to Hg(0) in Soil, Surface Water, and Sediment
Soil
Decreases in decreasing sunlight
Abiotic reduction (transfer of
electrons from humic acid to
Hg(2)) is dependent on pH
Strong stability complex between
Hg(2) and humic acid
Surface Water
Decreases with decreasing sunlight and temperatures
Has been observed to increase with decreasing dissolved
organic carbon (DOC) conditions (Amyot et al. 1997), and
vice versa, due to reduced light penetration and increased
complexation of Hg(2)

Sediment
Sparse literature on subject


                                    Table A-3
                       Reduction (kr) in Surface Water: Inputs
Input Values (1/day)
5E-1to 3.5
5E-3to 1E-1
2E-2 to 4E-2
1E-2
<5E-3
1 4E-1
2E-1 to 4E-1
2E-2to1.4E-1
1E-1
5E-2
Comment
Experimental value using simulated sunlight, after
normalizing to sunlight in Stockholm, Sweden
Based on mass balances in Wisconsin seepage lakes
Epilimnion
9 m depth
17 m depth
high Arctic lake during 24 hour sunlight period
high Arctic lake, low DOC conditions
high Arctic lake, high DOC conditions
July-August, upper 3 m
July August, upper 6 m
Reference(s)
U.S. EPA (1997a), Xiao et al
(1995)
U.S. EPA (1997a), Mason et al. (1994)
Mason etal (1995)
Mason etal. (1995)
Mason etal (1995)
Amyot etal. (1997)
Amyot etal. (1997)
Amyot etal (1997)
•*
Vandal etal. (1995)
Vandal etal. (1995)
                                    Table A-4
                         Reduction (kr) in Sediment: Inputs
Input Values (1/day)
1E-6
0.216
Comment
Inferred value calculated based on presence of Hg(0)
in sediment porewater
Derived from humic acid from farm pool sediment pH
did not appear to affect the rate of reaction, but does
seem to influence the amount of mercury reduced
Reference(s)
U.S EPA (1997a), Vandal etal (1995)
Alberts etal (1974)
NOVEMBER 1999
A-5
TRIM.FATE ISO VOLUME II (DRAFT)

-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                             Table A-5
                                   Reduction (kr) in Soil: Inputs
Equations
where
e
Used to Calculate Input Values
reduction rate normalized by soil water
content in the surficial 5 mm of soil,
L[soil]/L[water]-day; values range from 1 E-4
for forest site to 1 .3E-3 for field site
soil water content, L[water]/L[soil]
depth of soil surface layer to which reduction
rate is normalized, 5E-3 m
soil layer depth, m
Comment
Formula is derived
from evasion flux
measurements
Reference(s)
U.S. EPA (1997a), Carpi and
                                             Table A-6
              Issues Related to Methylation in Soil, Surface Water, and Sediment
Soil
Anaerobic conditions favor higher
methylation rates"
Biotic methylation may occur due to
bacteria; abiotic methylation by
transmethylation from other
organometals or by humic substances'1
Increases with increasing organic
carbon content and BHT* _
Generally occurs for Hg(2) dissolved in
soil porewater
Abiotic methylation is proportional to
temperature and Hg(2) concentration.
Also, it is inversely proportional to pH (at
pH > 5)9

Surface Water
Anaerobic conditions favor higher
methylation rates*
Photodegradation at surface can lower
the gross methylation rate'
Positively correlated with DOC"
Generally occurs for Hg(2) dissolved in
water column"
Positively correlated with temperature11
Potentially positively correlated with
sulfate concentration in water column'
Sediment
Anaerobic conditions favor higher
methylation rates*
Highest rates may occur at the
sec iment surface (sulfate-reducing
bacteria may be important mediators of
the reaction), Gilmour and Henry (1991)
Positively correlated with TOC (total
organic carbon)"
Generally occurs for Hg(2) dissolved in
sec iment porewater"
Positively correlated with temperature"
Potentially positively correlated with
sullate concentration in sedirfient
porewater"
  a This is generally due to increased bacterial reactions in anaerobic conditions
  b. U.S. EPA (1997a), Gilmour and Henry (1991)
  c Initial reference is Bob Ambrose's discussion of methylation in water column in U S EPA (1997a)
  d Hudson etal. (1994)
  e Watrasetal (1995)
  f Nagase et al (1984), BHT = 2,6, di-tert-butyl-methyl pheno!
  g Bodeketal (1988)
NOVEMBER 1999
A-6
TR1M.FATE ISO VOLUME II (DRAFT)

-------
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-------
                                                                            APPENDIX A
                               DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                      Table A-9
                            Methylation (k^ in Soil: Inputs
Input Values (1 /day)
2E-4
1E-3
7E-5 to 9.7E-4
k
9.2 E-3
Comment
average maximum potential methylation rate
constant under aerobic conditions for 120-day
experiment
average average maximum potential
methylation rate constant under anaerobic
conditions for 120-day experiment
Range for median aerobic reaction rate (from
peat, humus layer, and soil samples,
respectively)
Anaerobic median rate of four inundated soil
samples (range = 4.2E-3 to 1.2E-2/day)
Reference(s)
Porvari and Verta (1995)
Porvari and Verta (1995)
Verta etal( 1994)
Verta etal. (1994)
                                     Table A-10
          Issues Related to Demethylation in Soil, Surface Water, and Sediment
Soil
May increase with increasing
anaerobic conditions

Surface Water
Negatively correlated with light

Sediment
May depend on bacteria processes
Has been reported as maximal at the
sediment/water interface (Gilmour et
al. 1992)
                                     Table A-ll
                      Demethylation (k,,,) in Surface Water: Inputs
Input Values (1/day)
1E-3to25E-2
Equations
Used to Calculate Input Values
(Kds/KL)(1-exp(-KLzw))/zw,
where
K* =
K, =
Zw

demethylation rate constant at the lake
surface, 1/day
light extinction coefficient for use in
demethylation calculations, 1/m
mean depth of water column, m
Comment
Maximum
potential
demethylation
rate constants






Reference(s)
Gilmour and Henry (1991)
*
Hudson etal (1994)




NOVEMBER 1999
A-9
TRIM.FATE ISO VOLUME II (DRAFT)

-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                           Table A-12
                            Demethylation (kdm) in Sediment: Inputs
                Input Values (1/day)
                                     Comment
                        Reference(s)
                     2E-4to1E-1
                                   reported
                                   maximum
                                   potential
                                   demethylation
                                   rate constants
               Gilmourand Henry (1991)
     Equations Used to Calculate Input Values
 where
 fMHg
 1   A



 P,



 Pb
demethylation rate in the sediment, based
on TOC (m2/g TOC/day)
TOC concentration in sediment, g
[organisms] C/m2
fraction of the methylmercury in the
sediment that is dissolved
porosity of the sediment at the
sediment/water interface, dimensionless
porosity of the bottom of the sediment,
dimensionless
Will need to see
what ranges are
for KMS and K,.
Also make sure
porosity
dependence is
correct (seems
odd)
                                                                   Hudson etal  (1994)
                                            Table A-13
                               Demethylation (k^) in Soil: Inputs
Input Values (1/day)
3E-2
6E-2
3.6E-2, 7.6E-2, 1.1E-1
8.9E-2
Comment
Average of maximum
potential demethylation
rate constants in aerobic
conditions
Average of maximum
potential demethylation
rate constants in anaerobic
conditions
Median aerobic rates for
15 inundated soil samples,
1 5 humus layer samples,
and five peat samples,
respectively
Median anaerobic rate for
15 inundated soil samples
Reference(s)
Potvari and Verta (1995)
Porvari and Verta (1995)
Verta etal. (1994)
Veitaetal. (1994)
NOVEMBER 1999
                               A-10
              TRIM.FATE ISO VOLUME II (DRAFT)

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                                                                              APPENDIX A
                                DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
A.2.2  BIOTIC MERCURY TRANSFORMATION PARAMETERS

       A.2.2.1  Plants

       Fortmann et al. (1978) observed that some plants can change the mercury species
accumulated from the environment. However, few studies are available from which-to determine
transformation rates.

                                     Hg(0) -> Hg(2)

       This transfer only occurs in leaves; elemental mercury is probably not taken up by the
root. This rate is apparently very rapid and may be assumed to be instantaneous (U.S. EPA
1997a). No instances have been found where elemental mercury was measured in plants (e.g.,
Cappon 1987).  Thus, elemental mercury in air or on the surface of the leaf can be directly
transferred to divalent mercury in the leaf.

                                 Hg(2) -»• methylmercury

       It may be assumed that  Hg(2) is not transformed. Although the in vivo transformation of
inorganic mercury to methylmercury was observed in Pisum sativum (peas) in one study (Gay
1975), the chemical was ephemeral and quickly  (several hours) decayed to low parts per billion
levels. Methylmercury residues were not detected in mature crops following the addition of
mercuric chloride to soil (Bache et al. 1973). Indeed, most mercury in plants is usually in
inorganic form (Lindberg 1998).

                                 methylmercury -» Hg(2)

       This transfer occurs in leaves and stems, and not in roots (since transformations interfere
with the equilibrium assumption in roots).  It may be assumed that methylmercury is transformed
to Hg(2) according to first-order kinetics, where the first-order rate constant is 0.03 per day,
based on the following calculation.

       Only one study is available in which methylmercury was added to soil, and forms of
mercury (methyl and total) were measured after  a defined period of exposure (Bache et al. 1973).
In the few other studies of speciation of mercury within plants, either it is not known which
species were present in soil (e.g., Heller and Weber 1998), or multiple  Hg species were present in
soil and it is not known which were initially taken up by the plant (Cappon 1987).

       Using data from Bache et al. (1973) Table A-14, it may be assumed that the
methylmercury is readily taken up through the roots or foliage, that equilibrium between soil and
plant is achieved quickly, that methylmercury is not appreciably transformed in soil during a crop
season, that all methylmercury is only transformed to ionic mercury, and that crops were
harvested after 40 days.  Under these assumptions, 1s order rate constants for the transformation
of methylmercury to Hg(2) vary by almost two orders of magnitude in  a single study.  No
mechanistic explanation is available for this high degree of variability.
NOVEMBER 1999                             A-ll             TRIM.FATETSD VOLUME II (DRAFT)

-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS,
                                       Table A-14
 Concentrations of Methylmercury in Foliage and Stems of Crops from Bache et al. (1973)
          and Associated First-order Rate Constants, Using Assumptions in Text
Plant Species
Bush bean
(Phased us
vulgaris)
Bush bean
(Phaseolus
vulgaris)
Carrot (Daucus
carota)
Potato (solanum
tuberosum)
Potato (solanum
tuberosum)
Tomato
(Lycopersicon
esculantum)
Soil
gravelly
loam
gravelly
loam
gravelly
loam
silt loam
silt loam
gravelly
loam
Application
to Soil
(mg/kg)
1
10
10
1
10
10
Total Mercury
in Foliage and
Stem
52
90
214
86
58
341
Methylmercury
in F oliage and
Stem
46
28
1
27
17
3
1st Order Rate
Constant (d1)
0.003
0.03
0.1
0.03
0.03
0 1
       A.2.2.2  Soil Detritivores

       No information is available for transformations of mercury in soil detritivores. In
addition, transformation algorithms cannot be implemented if the mercury in these organisms is
in equilibrium with mercury in root-zone soil.

       A.2.2.3  Terrestrial and Semi-aquatic Wildlife

       Little quantitative information is available on the transformation of mercury in mammals
and birds. Where information is available, calculations of rate constants assume first order
transformations and are calculated on the basis of the total chemical taken up by the organism but
not necessarily assimilated. (The exception is the inhalation pathway, where rate constants are
derived based on the absorbed fraction.)

                                     Hg(0) -> Hg(2)

       No information is available from which to derive transformation rate constants for the
oxidation of elemental mercury to the mercuric ion. Based on the following information, it may
be assumed that the rate  is rapid, and 1 day"'  is a rough estimate of l.he first-order rate constant.
Elemental mercury is readily oxidized to the inorganic divalent species in most tissues following
the hydrogen peroxidase-catalase pathway. This oxidation primarily occurs in the red blood cells
NOVEMBER 1999
A-12
TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                             APPENDIX A
                               DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
and hydrogen peroxide is probably the rate-determining step (ATSDR 1997, U.S. EPA 1997b).
Once it is oxidized to the mercuric ion, it is indistinguishable from Hg(2) from inorganic sources
(ATSDR 1997, U.S. EPA 1997b).

                                     Hg(2)-> Hg(0)

       Mercuric salts primarily remain in their divalent form. However, a small fraction of the
inorganic divalent cation can be reduced to elemental mercury and exhaled as a vapor (ATSDR
1997). However, no information is available from which to derive this transformation rate
constant. For this reason, the transformation is assumed not to occur.

                                organic mercury ->• Hg(2)

       Forms of organic mercury are the most studied species of mercury.  The short-chain alkyl
mercury compounds (e.g. methylmercury) are relatively stable and are more slowly metabolized
to the inorganic form (U.S. EPA 1997b)  The long-chain compounds may be  more readily
metabolized to the mercuric ion (U.S. EPA 1997b). Takeda and Ukita (1970) dosed Donryu rats
with 20 ug Hg/kg ethyl-mercuric chloride via intravenous injection. After 8 days, 58.1 percent of
the mercury excreted in the urine was inorganic mercury and 35 percent of the mercury excreted
in feces was inorganic (Table A-15).  If it is assumed that 1) the excreted chemicals reflect the
transformation rate in the animal (transformation occurred immediately prior to excretion) and 2)
the first-order rate reflects a weighted average of the amount of dose excreted in urine (10.52
percent) and that excreted in feces (6.01  percent), then the transformation rate may be estimated
to be 0.09 day-1.

                                      Table A-15
 Transformation Rate (day"1) of Organic Mercury to the Inorganic Divalent Form (Takeda
                                    and Ukita 1970)
Class
Mammalia


Elimination Type
urine
feces
assumed
transformation for
whole animal
Dose Route
injection
injection

% Organic
after 8
days
41.9
65.0

% Inorganic
after 8 days
58.1
35.0

Transform Rate
Constant
0.1084
0.0539
0.09
NOVEMBER 1999
A-13
TRIM.FATE ISO VOLUME II (DRAFT)

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APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                 Hg(2)-> organic mercury

       No information is available on this transformation. Therefore it is assumed to be zero.

       Miscellaneous Transformations

       Miscellaneous transformations in wildlife are presented for the sake of completeness but
are not included in TRJM.FaTE at this time. Mercurous salts are transformed to the divalent ion
and elemental mercury when in contact with sulfhydryl groups (ATSDR 1997).

       A.2.2.4  Aquatic Species

       Transformations of mercury in algae, macrophytes, and bentibic organisms are assumed
not to occur.

                                 Hg(2)-» organic mercury

       Very little is known about the rate at which transformation of mercury species occurs in
aquatic organisms. A large body of field data suggests that most (> 90 percent) of mercury in
fish is in the form of methylmercury and other organic species. For this reason, it is assumed that
the first-order rate constant for the conversion is 1 day"1.

                                     Hg(0) -> Hg(2)

       This transformation is assumed to occur instantaneously in fish.

                                 Hg(0) ->• organic mercury

       This transformation is assumed not to occur directly in fish.

                                 Hg(2)-> organic mercury

       This transformation is assumed not to occur in fish.

                                 organic mercury -> Hg(2)

       This transformation is assumed not to occur in fish.

                                 organic mercury -* Hg(0)

       This transformation is assumed not to occur in fish.
NOVEMBER 1999                             A-14             TRIM. FATE TSD VOLUME 11 (DRAFT)

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                                                                               APPENDIX A
                                DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
A.3   INPUT PARAMETERS SPECIFIC TO MERCURY EXCRETION BY
       BIOTA

       First-order rate constants for the elimination of mercury from wildlife are summarized in
Table A-l 6. Supporting information is presented below.

                                       Table A-16
    Mean First-order Rate Constants (day"1) for Elimination of Mercury from Birds and
                                       Mammals

mammals
birds
Chemical
Species
Hg(2)
Hg(0)
organic Hg
Hg(2)
Hg(0)
organic Hg
Urine and
Feces (Eu)
0.48a
0.0502"
0.26'
0.48'
0"
0.0282'
Lactation
(E,)
0 00001
ob
0.00001 e
NA
NA
NA
Eggs
(E.)
NA
NA
NA
0'
0"
0.0244
Fur, Feathers, or
Hair (Ef)
0.00001
ob
0.00014"
0.00011s
ob
0.0559
a Averages of elimination rate constants for oral and dietary doses
b Rate constant based on inhalation study
c Assume same as lactation rate constant for Hg(2)
d Averages of elimination rate constants for oral dose and injection
e Assume same as elimination rate constant to mammalian urine and feces
rNo information available             ^
B Assume same as elimination rate constant to mammal fur

A.3.1  ELEMENTAL MERCURY

       Elemental mercury vapor is rapidly absorbed in the lungs (75 to 85 percent in humans),
and to a much lesser extent (three percent), it can be absorbed dermally (ATSDR 1997, U.S. EPA
1997b). Five human subjects inhaled from 107 to 202 u.g/m3 Hg and retained an average of 74
percent of the dose (Teisinger and Fiserova-Bergerova 1965). The inhaled vapor readily
distributes throughout the body and can cross the blood-brain and placental barriers.

       Rats exposed for 5 hours to 1.4 mg/m3 radio-labeled mercury vapor retained an average
body burden of 0.256 mg/kg BW (37 ug Hg/rat) and had excreted (urine and feces) 8.5 percent of
the initial body burden in 1 day, 24.8 percent in 5 days, and 42.9 percent in 15 days (Hayes and
Rothstein 1962).  Cherian et al. (1978) exposed 5 human volunteers to approximately 1  uCi of
radio-labeled Hg vapor for approximately 19 minutes.  Mean cumulative excretion over the first
7 days after exposure was 2.4 percent of the retained dose in urine and 9.2 percent in feces for a
total excretion of 11.6 percent of the retained dose (Cherian et al.  1978).

       Rates of excretion of elemental mercury by mammals (rats and humans) are summarized
in Table A-17. The mean value is presented in Table A-16.  No information on excretion by
avian  species is available.
NOVEMBER 1999
A-15
TRIM.FATE TSD VOLUME II (DRAFT)

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APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
                                       Table A-17
                   Excretion of Elemental Mercury (Hg°) in Mammals.
Test
Species
Rat
Rat
Rat
Human
Dose
0.256
mg/kg
0.256
mg/kg
0.256
mg/kg
1 uCi
Dose
Route1
inh
inh
inh
inh
Elimination
Route
urine + feces
urine + feces
urine + feces
urine + feces

Percent
of Dose
8.5
24.8
42.9
11.6
Days
1
5
15
7
x + SE
Rate
Constant
(Day1)
0.08883
0.05700
0.03736
0.01761
0.05020 +
0.01518
Source
HayerS -
Rothstein 1962
Hayes &
Rothstein 1962
Hayes &
Rothstein 1962
Cherian et al.
1978

' inh = inhalation
A.3.2  Divalent Mercury

       Divalent mercury can be absorbed through oral, dermal, and inhalation routes; however,
absorption is inefficient for all pathways. In mice, only 20 percent of the administered dose is
absorbed from the GI tract, 2-3 percent of the dose was absorbed dermally in exposed guinea
pigs, and limited information on inhalation exposure indicates that 40 percent of the dose was
absorbed in the lungs of dogs (U.S. EPA 1997b). Additionally, the absorption of mercuric salts
varies with the solubility of the specific salt. For example, the less soluble sulfide salt is more
poorly absorbed as mercuric sulfide than the more soluble chloride salt as mercuric chloride
(U.S. EPA 1997b).  Divalent mercury distributes widely throughout the body, however, it cannot
cross the blood-brain or placental barriers.

       The metabolism and distribution of mercuric chloride (HgCl2) has been describe'd in dairy
cows and rats. Potter et al. (1972) orally administered 344 uCi of radio-labeled mercuric
chloride by gelatin capsule using balling gum to 2 Holstein cows. After 6 days, 94.87 percent of
the dose was excreted in feces, 0.044 percent in urine, and 0.0097 percent in milk, for a total
excretion of 94.924 percent of the dose.  The biological half-life was calculated as 28.5 hours.
Rats dosed by intravenous injection with 1 mg/kg mercuric chloride excreted  15.2 percent of the
dose in feces and 16.3 percent in urine over 4 days for a total excretion (fecal and urinary) of 31.5
percent of the administered dose (Gregus and Klaassen 1986).

       The metabolism and distribution of mercuric nitrate [Hg(NO3)2] has also been described
in dairy cows and rats. Four Holstein dairy  cows were given an oral dose of 1.7 mCi radio-
labeled Hg(NO3)2 in a gelatin capsule via balling gum. Urine, feces. and milk were collected for
10 days and analyzed.  Results indicated that 74.91 percent of the dose was  excreted in feces,
0.08 percent in urine, and 0.01 percent in milk with a total excretion of 75 percent of the dose
(Mullen et al. 1975). Mullen et al. (1975) also  reported a biological half-life for the transfer of
NOVEMBER 1999
A-16
TRIM.FATE TSD VOLUME II (DRAFT)

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                                                                                APPENDIX A
                                DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
orally ingested mercury to milk of 5 days. Transfer of mercury to feces was slightly more
complicated with an initial half-life of 15 hr, then a decrease in elimination time which resulted
in a 3 day half-life (Mullen et al.  1975).  Rothstein and Hayes (1960) dosed seven Wistar rats
with 50 ug (0.2 mg/kg BW) radio-labeled mercury as Hg(NO3)2 via intravenous injection. After
52 days the cumulative percent excretion was 25 percent of the administered dose in urine and 37
percent in feces for a total excretion of 62 percent of the dose (Rothstein and Hayes-1960).  In
another study, 6 Holtzman rats were dosed by subcutaneous injection with 20 uCi of radio-
labeled Hg(NO3)2 and 0.018 percent of the dose was recovered in the hair 20 days after
administration (Mansour et al. 1973).  The maternal clearance half-time of 16.2 days was also
reported.

       Fitzhugh et al. (1950) exposed rats (n=20/dose group) to mercuric acetate in the diet at
doses of 0.5, 2.5, 10, 40, and 160 ppm. The average intake of Hg in a 24 hour period was 7.5,
37.5, 150, 600, and 2,400  ug and the 24 hour excretion was 52, 40, 43, 47, and 43 percent of
these doses, respectively, in feces and 4.8, 1.0, 0.5, 0.37, and 1.7 percent, respectively, in urine
(Fitzhugh et al.  1950).

       Divalent mercury is very poorly absorbed from the GI tract, therefore, rates obtained from
oral or dietary exposure may be misleading. Hayes and Rothstein (1962) reported an initial half-
life for fecal excretion of inorganic mercury of 0.6 days in Holstein cows. Later, the half-life
increased to 3 days. This indicates that a large proportion of the dose is initially excreted via the
feces due to lack of absorption. Thus, it may be  necessary to correct the oral and dietary fecal
elimination rates for inorganic mercury using assimilation factors.

       Rates of excretion of divalent mercury by mammals (rats and cows) are summarized in
Table A-18. The mean values for excretion to urin and feces, lactation, and excretion to hair are
presented in Table A-16. No information on excretion by avian species is available.

A.3.3  ORGANIC MERCURY

       Organic mercury was by far the most studied species of mercury. It is rapidly and
extensively absorbed through the GI tract (95 percent of the dose in humans) and is distributed
throughout the body via carrier-mediated transport (U.S. EPA 1997b).  Like elemental mercury,
organic mercury can cross the blood-brain and placental barriers.

       Radio-labeled methylmercuric  chloride was intravenously injected into 6 Holt/man rats at
a dose of 10 uCi, and after 20 days 0.21 percent of the administered  dose was transferred to hair.
The clearance half-life was reported to be 8.4 days (Mansour et al. 1973).  Gregus and Klaassen
(1986) also administered radio-labeled methylmercuric chloride via intravenous injection to
NOVEMBER 1999                              A-17             TRIM.FATETSD VOLUME II (DRAFT)

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-------
                                                                               APPENDIX A
                                DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
Sprague-Dawley rats at a dose of 1 mg/kg. Within 4 days, 5.6 percent of the dose was excreted
in feces and 0.5 percent in urine for a total excretion of 6.1 percent of the administered dose.
Additionally, 2 hr biliary excretion was 0.7, 0.9, 0.7, and 0.5 percent of doses 0.1, 0.3, 1.0, and
3.0 mg/kg, respectively (Gregus and Klaassen 1986).  Syrian Golden hamsters (n=9) were given
an oral dose of 0.32 mg Hg/kg BW as radio-labeled methylmercury chloride, and the elimination
rate was found to follow a first-order rate equation with a half-life of 6.9 days (Nordenhall et al.
1995). Nordenhall et al. (1995) estimated that approximately 5 percent of the dose administered
to the dams was transferred to pups via milk over 21 days. Four days post-administration of
methylmercury chloride, 20 percent of the mercury in milk was inorganic (Nordenhall et al.
1995). Sell and Davison (1975) dosed via intraruminal injection, 1 Nubian goat and 1 Guernsey
cow with  100 and 500 uCi radio-labeled methylmercury chloride, respectively. After 13 days,
0.28, 31.18, and  1.45 percent of the dose administered to the goat were excreted in milk, feces,
and urine, respectively. Conversely, none of the dose was excreted in cow milk, 25.32 percent
was excreted in cow feces, and 1.28 percent was excreted in cow urine after 7 days.

       Takeda and Ukita (1970) exposed Donryu rats to 20 ug Hg/kg BW as radio-labeled ethyl-
mercuric chloride dissolved in olive oil by subcutaneous injection.  Cumulative excretion during
8 days post-exposure was  10.52 percent of dose in urine and 6.01 percent of dose in feces. In
urine, 41.9 percent and 58.1 percent of the total mercury was organic and inorganic, respectively,
on day 8.  In contrast, 65 percent of fecal mercury was organic and 35 percent was inorganic on
day 8 (Takeda and Ukita 1970). Fang and Fallin (1973)  orally dosed 14 rats with 3 umol radio-
labeled ethyl-mercuric chloride in corn oil.  Mercury content was measured in 1-2 rats on days
0.25,  1, 2, 3, 4, 5, 7, 10, and 14 after dosing. Fourteen days after dosing, 32.5 nmole/g hair had
accumulated in the fur. Wistar rats have an estimated 3 g of fur (Talmage 1999), therefore,
approximately 3.25 percent of the original dose was excreted in hair.

       Fitzhugh et al. (1950) exposed rats (n=20/dose group) to phenyl mercuric acetate in the
diet at doses of 0.5, 2.5,  10, 40, and 160 ppm. The average intake of Hg in a 24 hour period was
7.5, 37.5,  150, 600, and 2,400 \ig and the  24 hour excretion was 44, 35, 27, 35, and 30 percent of
these  doses, respectively, in feces  and 9.2, 4.5, 6.2, 4.3, and 2.4 percent, respectively, in urine
(Fitzhugh et al. 1950).

       Humans have also  been used as subjects for determining the metabolism of
methylmercury.  Three subjects were given an oral dose  of 2.6 (iCi radio-labeled methylmercuric
nitrate (Aberg et al. 1969). Mean  cumulative mercury excretion 10 days post-exposure were 13.6
percent (13.6, 13, and 14.2 percent) of dose in feces and 0.24 percent (0.18, 0.26, and 0.27
percent) in urine, and after 49 days, 34.1 percent (33.4 and 34.7 percent) of the initial dose was
excreted via feces and 3.31 percent (3.29 and 3.33 percent) via urine (Aberg et al.  1969).  Aberg
et al. (1969) also reported the biological half-life of methylmercuric chloride to be 70.4, 74.2, and
73.7days (x = 72.8 days) for the three subjects and measured approximately 0.12 percent of the
initial dose in hair approximately 45 days (range 40-50 days) after exposure.

       Two papers contained data suitable for use in determining excretion rates for avian
species. In the first study, Lewis and Furness (1991) orally dosed black-headed gulls with 200,
100, or 20 j_il methylmercuric chloride using gelatin capsules.  The cumulative excretion of
mercury in the 200 \iL group was  26.4 percent of the dose in feces and 51.2 percent in feathers

NOVEMBER 1999                              A-19              TRIM.FATE TSD VOLUME II (DRAFT)

-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
for a total of 77.5 percent in all excreta over 13 days.  At the 100 uL dose, a total of 80.3 percent
of the dose was excreted (37.8 and 44.2 percent in feces and feathers, respectively) in 13 days.
Finally, only 56.3 percent of the low dose was measured in all excreta with 11 percent of the dose
in feces and 52.6 percent in feathers after 13 days (Lewis and Furness 1991).

       In the second study, 4 white-leghorn chickens and 4 Japanese quail were dosed with 20
ppm Hg as methylmercuric chloride in the diet for 21  days (Sell 1977).  The first 7 days of this
dosing period, chickens and quail were also given an oral dose of 2 _iCi of radio-labeled
methylmercuric chloride (Sell 1977).  The rate calculations reported in Table A-17 assume that
the author accounted for the total intake of radio-labeled mercury from both sources when
reporting percent of dose excreted in feces and eggs.  Chickens excreted 64 percent of the dose in
feces and 21.88 percent of the dose in eggs produced during the 21 days post-exposure,  while
quail excreted 41 and 54.08 percent of the dose in feces and eggs, respective, during the same 21
day post-exposure period (Sell 1977).

       Rates of excretion of organic mercury by mammals (humans, goats, cows, and rats) are
summarized in Table A-19. Rates of excretion by birds are summarized in Table A-20.  The
mean values for excretion to urine and feces, fur, feathers, and eggs are presented in Table A-16.
No information on excretion by avian species is available.
NOVEMBER 1999                             A-20             TRIM.FATE TSD VOLUME II (DRAFT)

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-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
A.4   REFERENCES

Aberg, B., L. Ekman, R. Falk, U. Greitz, G. Persson, and J. Snihs.  1969.  Metabolism of methyl
mercury (203Hg) compounds in man.  Arch. Environ. Health 19:478-484.

Alberts, JJ, JE Schindler and RW Miller  1974. Elemental mercury evolution mediaTed'by humic
acid. Science. 184: 895-7.

Amyot, M., G. Mierle, D. Lean, and D.J. McQueen. 1997. Effect of solar radiation on the
formation of dissolved gaseous mercury in temperate lakes. Geochemica et Cosmochimica Acta.
61(5):975987.

ATSDR. 1997.  Agency for Toxic Substances and Disease Registry. Toxicological profile for
mercury. Draft for public comment (Update). ATSDR-7P-97-7 (Draft).  U.S. Department of
Health and Human Services.

Bache, C.A., W.J. Gutenmann, L.E. St. John, Jr., R.D. Sweet, H.H. Hatfield, and D.J. Lisk.
1973. Mercury and methylmercury content of agricultural crops grown on soils treated with
various mercury compounds.  J. Agr. Food Chem.  21:607-613.

Bodek, I, WJ  Lyman, WF Reehl, et al.  1988. Environmental inorgzinic chemistry: Properties,
processes, and estimation methods. Elmsford, NY: Pergammon Press.

Cappon, C.J.  1987.  Uptake and speciation of mercury and selenium in vegetable, crops grown
on compost-treated soil. Water, AirrSoil Pollut. 34:353-361.

Carpi, A. and S.E. Lindberg.  1997. Sunlight mediated emission of elemental mercury from soil
amended with municipal sewage sludge.  Environmental Science and Technology. 31(7):2085-
2091.

Cherian, M.G., J.B. Hursh, T.W. Clarkson, and J. Allen. 1978.  Radioactive mercury distribution
in biological fluids and excretion in human subjects after inhalation of mercury vapor.  Arch.
Environ. Health.  33(May/June): 109-114.

Fang, S.C. and E. Fallin. 1973. Uptake, distribution, and metabolism of inhaled ethylmercuric
chloride in the rat. Arch. Environ. Contam. Toxicol. 1:347-361.

Fitzhugh, O.G., A.A. Nelson, E.P. Laug, and P.M. Kunze.  1950. Chronic oral toxicities of
mercuri-phenyl and mercuric salts.  Arch. Indust. Hyg. Occup. Med. 2:433-442.

Fortmann, L.C., D.D. Gay, and K.O. Wirtz.  1978. Ethylmercury:  Formation in plant tissues and
relation to methylmercury formation. EPA600/378 037. U.S. EPA Ecological Research Series.

Gay, D.D. 1975. Biotransformation and chemical form of mercury in plants. International
Conference on Heavy Metals in the Environment.  Symposium Proceedings, pp. 87-95. Vol. II,
Part 1. October 1975.

NOVEMBER 1999                            A-24            TRIM.FATE TSD VOLUME II (DRAFT)

-------
                                                                             APPENDIX A
                               DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
Gilmour, C.C. and G.S. Riedel. 1995. Measurement of Hg methylation in sediments using high
specific activity 203Hg and ambient incubation.  Water, Air, and Soil Pollution.  80:747-756.

Gilmour, C.C, E.A. Henry, and R. Mitchell. 1992. Sulfate stimulation of mercury methylation
in freshwater sediments. Environmental Science and Technology. 26(11):2281-2287.

Gilmour, C.C. and E.A. Henry. 1991. Mercury methylation in aquatic systems affected by acid
deposition. Environmental Pollution.  71:131-169.

Gregus, Z, and C.D. Klaassen. 1986. Disposition of metals in rats: A comparative study of
fecal, urinary, and biliary excretion and tissue distribution of eighteen metals.  Toxicol. Applied
Pharm. 85:24-38.

Hayes, A.D, and A. Rothstein. 1962. The metabolism of inhaled mercury vapor in the rat
studied by isotope techniques. J. Pharm. Exper. Therap. 138:1-10.

Heller, A.A., and J.H.  Weber. 1998. Seasonal study of speciation of mercury(II) and
monomethylmercury in Spartina alternaflora from the Great Bay Estuary, NH. The Science of
the Total Environment. 221:181-188.

Henry, E.A., L.J. DodgeMurphy, G.N. Bigham, S.M. Klein, and C.C. Gilmour. 1995a. Total
mercury and methylmercury mass balance in an alkaline, hypereutrophic urban lake (Onondaga
Lake, NY). Water, Air, and Soil Pollution. 80:509518.

Henry, E.A., L.J. DodgeMurphy, G.N. Bigham, and S.M. Klein.  1995b. Modeling the transport
and fate of mercury in an urban lake (Onondaga Lake. NY). Water, Air, and Soil Pollution.
80:489498.

Hudson, R., S.A. Gherini, C.J. Watras, and D. Porcella. 1994. Modeling the biogeochemical
cycle of mercury in lakes: The Mercury Cycling Model  (MCM) and its application to the MTL
Study Lakes, in mercury pollution integration and synthesis. Edited by C.J. Watras and J.W.
Huckabee, Lewis Publishers, pp. 473-523.

Jacobs, L.A., S.M. Klein, and E.A. Henry.  1995.  Mercury cycling in the water column of a
seasonally anoxic urban lake (Onondaga Lake, NY).  Water, Air, and Soil Pollution.  80:553-
562.

Lewis, S.A. and R.W. Furness. 1991.  Mercury accumulation and excretion in laboratory reared
black-headed gull Larus ridibundus chicks. Arch. Environ. Contam. Toxicol. 21:316-320.

Lindberg, S.E.  1998. Personal communication.  Oak Ridge National Laboratory. December.

Lindberg, S.E., T.P. Meyers, G.E. Taylor, Jr., R.R. Turner, and W.H. Schroeder.  1992.
Atmosphere-surface exchange of mercury in a forest: Results of modeling and gradient
approaches. J. Geophys. Res.  97:2519-2528.
NOVEMBER 1999                            A-25             TRIM.FATE TSD VOLUME II (DRAFT)

-------
APPENDIX A
DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
Lindqvist, O., K. Johansson, M. Aastrup, A. Andersson, L. Bringmark, G. Hovsenius, L.
Hakanson, A. Iverfeldt, M. Meili and B. Timm. 1991. Mercury in the Swedish environment -
Recent research on causes, consequences and corrective methods. Water Air and Soil Pollution.
Mansour, M.M., N.C. Dyer, L.H. Hoffman, A.R. Schulert, and A.B. Brill. 1973. Maternal-fetal
transfer of organic and inorganic mercury via placenta and milk.  Environ. Res. 6:479-484.

Mason, R.P., J.R. Reinfelder and F.M.M. Morel. 1996. Uptake, toxicity, and trophic transfer of
mercury in a coastal diatom..  Environmental Science & Technology.  30(6):1835-1845.

Mason, R.P., J.R. Reinfelder and F.M.M. Morel. 1995. Bioaccumulation of mercury and
methylmercury. Water Air and Soil Pollution. 80(1-4):915-921.

Mason, R.P., W.F. Fitzgerald, and F.M.M. Morel. 1994. The biogeochemical cycling of
elemental mercury: Anthropogenic influences. Geochemica et Cosrnochimica Acta.
58(15):3191-3198.

Matilainen, T.  1995.  Involvement of bacteria in methymercury formation in anaerobic lake
waters. Water, Air, and Soil Pollution.  80:757-764.

Mullen, A.L., R.E. Stanley, S.R. Lloyd, and A.A. Moghissi.  1975.  Absorption, distribution and
milk secretion of radionuclides by the dairy cow IV. Inorganic radiomercury.  Health Physics.
28:685-691.

Nagase, H, Y Ose, T Sato, et al. 1984. Mercury Methylation by Compounds in Humic Material.
The Science of the Total Environment. 32:  147-156.

Nordenhall, K., L. Dock and M. Vahter. 1995.  Lactational exposure to methylmercury in the
hamster.  Arch Toxicol. 69:235-241.

Porvari, P. and M. Verta.  1995. Methylmercury production in flooded soils: A laboratory study.
Water, Air, and Soil Pollution.  80:765-773.

Potter, G.D., D.R. Mclntyre, and G.M. Vattuone.  1972.  Metabolism of 203Hg administered as
HgCl2 in the dairy cow and calf. Health Physics. 22:103-106.

Riederer, M.  1995. Partitioning and transport of organic chemicals between the atmospheric
environment and leaves. In:  Trapp, S. and J. C. McFarlane, eds.  Plant contamination:
modeling and simulation of organic chemical processes.  Boca Raton, FL: Lewis Publishers, pp.
153-190.

Rothstein, A. and A.D. Hayes.  1960. The metabolism of mercury in the rat studied by isotope
techniques. J. Pharm.  Exper. Therap. 130:166-176.
NOVEMBER 1999                             A-26             TRIM.FATE TSD VOLUME II (DRAFT)

-------
                                                                             APPENDIX A
                               DERIVATION OF MERCURY-SPECIFIC ALGORITHMS AND INPUT PARAMETERS
Sell, J.L. 1977. Comparative effects of selenium on metabolism of methylmercury by chickens
and quail: tissue distribution and transfer into eggs. Poultry Sci. 56:939-948.

Sell, J.L. and K.L. Davison. 1975. Metabolism of mercury, administered as methylmercuric
chloride or mercuric chloride, by lactating ruminants. J. Agric. Food Chem. 23:803-808.

Stordal, M.C. and G.A. Gill.  1985.  Determination of mercury methylation rates using a 203Hg
radiotracer technique.  Water, Air, and Soil Pollution. 80:529-538.

Takeda, Y. and T. Ukita. 1970. Metabolism of ethylmercuric chloride-203Hg in rats. Toxicol.
Applied Pharm. 17:181-188.

Talmage, S.  1999. Personal communication.  Oak Ridge National Laboratory.  February.

Teisinger, J. and V. Fiserova-Bergerova. 1965. Pulmonary retention and excretion of mercury
vapors in man. Indust. Med. Surgery. July:581-584.

U.S. EPA.  1997a. U. S. Environmental Protection Agency. Mercury study report to congress.
Volume III:  Fate and transport of mercury in the environment.  U.S. EPA Office of Air Quality
Planning and Standards, and Office of Research and Development.

U.S. EPA.  1997b. U.S. Environmental Protection Agency. Mercury study report to congress.
Volume V: Health effects of mercury and mercury compounds. U.S. EPA Office of Air Quality
Planning and Standards, and Office of Research and Development.

Vandal, G.M., W.F. Fitzgerald, K.R?Rolihus, and C.H.Lamborg.  1995.  Modeling the elemental
mercury cycle in Pallette Lake, Wisconsin, USA. Water, Air, and Soil Pollution.  80:789-798.

Verta, M, T Matilainen, P Porvari, et al.  1994. Methylmercury sources in boreal lake ecosystem..
In:  Watras and Huckabee, eds.  1996, pp. 119-136.

Watras, C.J. and N.S. Bloom. 1992.  Mercury and methylmercury in individual zooplankton -
Implications for bioaccumulation. Limnology and Oceanography.  37(6):1313-1318.*

Xiao, Z.F., D. Stromberg, and O. Lindqvist.  1995.  Influence of humic substances on photolysis
of divalent mercury in aqueous solution. Water, Air. and Soil Pollution.  80:789-798.
NOVEMBER 1999                            A-27             TRIM.FATETSD VOLUME II (DRAFT)

-------

-------
                                   TECHNICAL REPORT DATA
                               (Please read Instructions on reverse before completing)
 1. REPORT NO.
   EPA-453/D-99-002B
                                                                  3 RECIPIENT'S ACCESSION NO.
 4 TITLE AND SUBTITLE
        Total Risk Integrated Methodology.TRIM.FaTE Technical
        Support Document. Volume II: Description of Chemical
        Transport and Transformation Algorithms.
                 5. REPORT DATE
                   November, 1999
                 6 PERFORMING ORGANIZATION CODE
 7. AUTHOR(S)
                                                                  8. PERFORMING ORGANIZATION REPORT NO.
 9 PERFORMING ORGANIZATION NAME AND ADDRESS

   U.S. Environmental Protection Agency
   Office of Air Quality Planning and Standards
   Research Triangle Park, NC  27711	
                                                                  10 PROGRAM ELEMENT NO.
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 12. SPONSORING AGENCY NAME AND ADDRESS
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                                                                      External Review Draft
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                                                                      EPA/200/04
 15. SUPPLEMENTARY NOTES
     Supplements document EPA-453/D-99-002A
 16 ABSTRACT
   This report is part of a series of documentation for the Total Risk Integrated Methodology (TRIM). TRIM
 is a time series modeling system, with multimedia capabilities, designed for assessing human health and
 ecological risks from hazardous and criteria air pollutants. The detailed documentation of TRIM'S logic,
 assumptions, equations,  and input parameters is provided in comprehensive technical support documents for
 each of the three TRIM modules, as they are developed.  This report documents the Environmental Fate,
 Transport, and Ecological Exposure module of TRIM (TRIM.FaTE) and is divided into two volumes. The
 first volume provides a description  of terminology, model framework, and functionality of TRIM.FaTE and
 the second volume presents a detailed description of the algorithms used in the module.	
 17.
                                     KEY WORDS AND DOCUMENT ANALYSIS
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                                                                                    c. COSATI Field/Group
   Risk assessment
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EPA Form 2220-1 (Rev. 4-77)   PREVIOUS EDITION IS OBSOLETE

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U.S. Environmental Protection
Region 5, Library (PL-12J)
77 West Jackson Boulevard, 12th Floor
Chicago, IL  60604-3590

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