Development of Tools to Improve Exposure ... - Trent University

Development of Tools to Improve Exposure Estimation
for Use in Ecological Risk Assessment
The TaPL3 Upgrade
Report to Environment Canada
CEMC Report No. 200303
Prepared by:
Eva Webster, Jennifer Hubbarde, Don Mackay,
Linda Swanston, Adam Hodge
Canadian Environmental Modelling Centre
Trent University
Peterborough, Ontario K9J 7B8
CANADA

Development of Tools to Improve Exposure Estimation
for Use in Ecological Risk Assessment
Report to Environment Canada
Contract No. K2251-2-0004
Report 1
The TaPL3 Upgrade
September 30, 2003
Prepared by:
Eva Webster, Jennifer Hubbarde, Don Mackay,
Linda Swanston, Adam Hodge
Canadian Environmental Modelling Centre
Trent University
Peterborough, Ontario
K9J 7B8
EC Departmental Representatives:
Don Gutzman
Head, Exposure Section
Chemical Evaluation Division
Existing Substances Branch
Andy Atkinson
Head, New Chemicals Evaluation Section
Chemical Evaluation Division
New Substances Branch
Environment Canada
Place Vincent Massey, 14 th Floor
Hull PQ
K1A 0H3
EC Contracting Authority:
Robert Chenier
Env. Protection Service
Chemical Evaluation Division
351 St. Joseph Blvd 14 th Fl
Hull PQ
K1A 0H3

Table of Contents:
Executive Summary
List of Tables
List of Figures with Captions
Introduction
Study Objectives
Background
TaPL3 Model Upgrades
Temperature Variation
Terrestrial Vegetation
Extent of “Grasshopping”
Application of TaPL3 version 3.00
Conclusion
Chemical Properties
Environmental Properties
Emissions
Results for the Hypothetical Chemicals
Temperature Variation
Partitioning Variants of X
Summary for Chemical X
Results for Selected DSL Chemicals
Future Research Directions
References

List of Tables
Table 1:
Additional information needed for the inclusion of a vegetation compartment.
Table 2:
Foliage-air transport D value calculations.
Table 3:
Properties of selected chemicals.
Table 4:
Environmental properties.
List of Figures with Captions
Figure 1:
The partitioning tendency of X (x), benzo[a]pyrene (square), chlorobenzene (triangle),
hexachlorobenzene (star), and 2,3,7,8-TCDD (circle). The diagonal lines represent lines of
constant log K OA . Chemicals in the upper left tend to partition into air, in the lower left to water,
and in the lower right to octanol.
Figure 2:
The three key model outcomes for chemical X and its partitioning variants. The solid square
symbols indicate the presence of vegetation in the modelled environment; the open triangle
symbols indicate the absence of vegetation.
Figure 3:
The persistence, P, characteristic travel distance in air, L A , and average number of hops
experienced by a single molecule, H, for each of four substances; benzo[a]pyrene,
chlorobenzene, hexachlorobenzene, and 2,3,7,8-TCDD. The open triangle symbols indicate the
case of no vegetation present while the solid square symbols indicate the presence of vegetation.
The horizontal axis represents decreasing temperature (a northward movement) from 25 to 5 C.

EXECUTIVE SUMMARY
As a result of a series of research projects at the CEMC which included collaborations with the
University of Osnabrück, TaPL3, an evaluative model describing the transport and persistence of
organic chemicals, was developed. It has been available from the CEMC website since 2000. As a
result of use by a number of individuals and agencies, the need for certain upgrades or improvements
is apparent.
In this project, the TaPL3 model was upgraded to include provision for temperatures to be varied,
improved treatment of vegetation, and an alternate descriptor for the potential for long-range
transport. Enthalpies of phase change are used to adjust chemical partitioning data to the
temperature of the modelled environment. Reaction activation energies are used to adjust chemical
degradation rate constants. Vegetation was added as a single primary medium with active transport
mechanisms between air and foliage. The average number of air-to-surface cycles, referred to
colloqually as “hops”, experienced by a single molecule is calculated as an estimate of the potential
for long-rang transport. This new version of the model will be made freely and publically available
from the CEMC website (http://www.trentu.ca/cemc/).
Hypothetical chemicals were used to explore the key model outcomes of persistence, P, characteristic
travel distance in air, L A , and extent of hopping, H. This was followed by a similar investigation with
four dissimilar chemicals from the DSL (Domestic Substances List). Several future research
directions are suggested including improved treatment of bioturbation in soil.

1 INTRODUCTION
This report is the first in a series of three reports prepared in fulfilment of Contract K2251-2-0004
“Development of Tools to Improve Exposure Estimation for Use in Ecological Risk Assessment”.
Here, changes to the TaPL3 (Transport and Persistence Level III) model are described. Hypothetical
chemicals and selected substances from the DSL are used to demonstrate the utility of the upgraded
model. In applying the model three key outcomes are examined; the persistence, P, the characteristic
travel distance in air, L A , and the average number of hops experienced by a single molecule, H.
1.1 Study Objectives
The objectives of this work were stated in the contract as follows.
“To improve the Transport and Persistence Level III (TaPL3) Model for the use of
Environment Canada. The TaPL3 model is an evaluative tool to be used in the detailed
assessment of chemicals for persistence and potential for long-range transport in a mobile
medium, either air, or water in a Level III (steady-state) environment. A number of
improvements are to be made to the model including provision for temperatures to be varied,
terrestrial characteristics to be better defined (including, differentiating between prairie,
deciduous and coniferous forests) and an estimate made of the distribution of transport
distances and the extent of "grasshopping". Selected substances from the DSL will be used to
demonstrate the utility of the upgraded model.”
1.2 Background
The persistence, P, of a substance is now widely defined as its longevity in the environment with
removal only by degradation. This is not a directly measurable property of the substance but can be
calculated using a steady-state environmental model as suggested by Webster et al (1998). It has also
been suggested that the potential for long-range transport (LRT) can be calculated by such a model
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as a characteristic travel distance in air, L A (Beyer et al, 2000). While it is not possible to compare
the values calculated for a single substance with any measured value, substances can be ranked based
on either P or L A and this ranking can be compared to either evidence of longevity or to evidence of
transport to remote regions.
The original TaPL3 model was created to facilitate the calculation of P and L A for organic substances
and is based on the following publications: the fugacity concept initially proposed in 1979 (Mackay,
1979) and detailed in Mackay (2001); the calculation of persistence using a Level III model (Webster
et al 1998); and the calculation of L A using a Level III model ( Beyer et al, 2000).
2 TAPL3 MODEL UPGRADES
Since the development of the TaPL3 model (version 2.10, released June 2000), our understanding
of the influence of temperature and of vegetation has increased. With this increased understanding
the model results are refined by reducing the simplicity of the assumptions in the model. In addition,
a new way of describing chemical transport as a “hopping” between mobile and stationary media has
been developed and refined. It is hoped that the inclusion of this new descriptor will improve
understanding of the long-range transport processes.
2.1 Temperature Variation
The temperature of the environment is known to influence both the physical-chemical properties of
substances and their ability to degrade. Properties are typically measured at indoor temperatures
often a standard of 25/C. This focus on property measurement at indoor temperatures is a direct
result of the cost of making such measurements and the large numbers of substances to be analyzed.
In recent years has there been an effort to extend this into more typical outdoor temperatures. The
temperature dependence of the partitioning properties of sets of substances such as the
chlorobenzenes, PCBs, and PAHs have been reported by Bahadur et al (1997, 1999), Shiu et al
(1997), and Shiu and Ma (2000). Beyer et al (2002) produced a more comprehensive study of 50,
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mostly aromatic, substances. The majority of effort in this field has focussed on the temperature
dependence of partitioning properties and thus there is confidence in the correlation and the ability
of users to obtain data. This is not the case for the temperature dependence of degradation rates.
Chemical degradation in the environment is influenced by many factors including the microbial
community present, light intensity and duration, and temperature. These cause the degradation rate
of a substance to vary by as much as an order of magnitude from place to place and from season to
season. The temperature dependence of hydroxyl reaction rates have been measured by Anderson
and Hites (1996), and Brubaker and Hites (1997, 1998a, 1998b) for a small set of substances.
As outlined by Beyer et al (2000) and further detailed in Beyer et al (2003) and Gouin (2003),
temperature has a complex effect on persistence, P, and characteristic travel distance, L A . At lower
temperatures, chemical typically partitions more strongly to water and soil decreasing L A by transport
from the mobile to the stationary media. The persistence tends to increase since, for most chemicals,
their half-life in air is shorter than in other media. In addition, degradation processes in all media
tend to take place more slowly thus further increasing P. An increase in longevity has the opposite
effect on L A . The relative strength of these opposing effects will determine whether L A increases or
decreases with decreasing temperature. Thus if we were to consider only the temperature effects on
partitioning, the increase in P would be under-estimated and neither P nor L A would be correct for
the temperature of the environment. If all chemicals were equally affected, neither correction would
be required since only the relative ranking has meaning. However, the enthalpies of phase change
and reaction activation energies are chemical specific. The relative rankings of substances for P and
L A are expected to be affected by temperature; the direction and magnitude of changes in P and L A
will not be the same for all chemicals.
The TaPL3 model was modified include the following equation which is based on the conventioanl
Arrhenius, or Van’t Hoff, equation.
P e = P o e
(Ea (1 / To - 1 / Te) / R)
where P e is the property at the environment temperature, T e (K), P o is the property at the chemical
data collection temperature, T o , E a (J/mol) is the enthalpy of phase change or reaction activation
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energy, and R is the gas constant (8.314 J/mol.K). This correction is applied separately to each of
the octanol-water partition coefficient, K OW , and the air-water partition coefficient K AW , and to the
degradation rate constants. This represents an implementation of the research of Mackay (2001) and
Beyer et al (2000, 2003).
While the chemical properties are now corrected for the environment temperature, it should be noted
that sub-zero temperatures are not treated. Ice formation and snow cover are expected to control both
chemical partitioning and degradation rates in Canadian winters. The ChemCAN model (version
6.00) provides a simplistic treatment of winter conditions by preventing selected transport
mechanisms (Webster et al, 2003). The effects of snow cover are currently being studied by The
Wania Group (http://www.scar.utotonto.ca/~wania/ ). Sub-zero temperature effects are quite
complex and not yet well-understood. To avoid mis-leading results they were not included in the
TaPL3 model. As the science advances, this can be added to a future version of the model.
2.2 Terrestrial Vegetation
Typically environmental models of chemical fate include three or four primary media: air, water,
soil, and sometimes sediment. While this has been sufficient for most purposes to date, it has been
acknowledged that most of the landmass of the planet is covered by vegetation. This fact has never
been so evident as with the many satellite images now being produced. Introducing vegetation
introduces a degree of complexity, but it is not entirely clear what level of detail and complexity is
most appropriate when examining issues of chemical persistence and tendency to travel large
distances.
In adding vegetation to a steady-state environmental model two extremes have been explored. The
ChemCAN model (Mackay et al, 1991; Webster et al, 2003) includes the simplest assumption of
vegetation; foliage in equilibrium with the air. This assumption produces values for P and L A
identical to a four-compartment model. Recent work by Gouin (2003) has indicated that the a fourcompartment
model fails to explain the extent of long-range transport observed. Other authors have
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suggested the inclusion of as many as four vegetation compartments coupled to soils specific to the
vegetation type and interactions with the soils in addition to the interactions with air (Cousins and
Mackay, 2001; Cahill and Mackay, 2003). With each addition in complexity the model requires
additional information. To avoid increasing the data demands beyond what can be obtained with a
reasonable degree of effort, the increase in complexity was limited to the addition of a single
vegetation compartment as a primary medium. This increased the number of simultaneous equations
from four to five with a separate fugacity being sought for each primary medium. The vegetation is
assumed to have interactions only with the air through foliage by three processes: aerosol deposition,
rain, and diffusion. Chemical is also assumed to be degraded on the leaf surface. No root tissues are
included and there is no runoff from the leaves to the soil. The foliage is considered to “float” above
the soil leaving the entire soil surface available for interactions with the air, and to receive rain
unimpeded by the presence of the vegetation.
Table 1 shows the additional information required by the model and Table 2 details the calculations
performed. The value of the input parameters such as leaf biomass, lipid fraction, and leaf area index
can be used to differentiate between ecosystems such as prairie, deciduous and coniferous forests.
2.3 Extent of “Grasshopping”
In the past, a characteristic travel distance in air, L A , has been used to describe the long-range
transport potential of a substance (Beyer et al 2000). While useful for ranking substances, this is not
an entirely satisfying description. Wania and Mackay (1996, 1997) have described the travel path
of a molecule with seasonal temperature changes as a series of “hops”. The molecule is viewed as
undergoing a series of deposition and evaporation process pairs, each process pair constituting a
single hop. This gives a more realistic and intuitively satisfying description of the events responsible
for long range transport and was further developed in Gouin (2003). Here this “grasshopping”
description is extended from essentially a two-compartment environmental system to the five
primary media of the new TaPL3 model.
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The average number of hops experienced by a single molecule from the time of release into the
environment to degradation, H, is given by
H = (N W,A + N S,A + N V,A ) / E
where N W,A is the water to air transfer rate, N S,A is the soil to air transfer rate, N V,A is the vegetation
to air transfer rate, and E is the rate of emission (to air). Since consistent units are used for all rates,
H is a unitless ratio. Note that this equation applies only when the emission is entirely to air.
A related parameter, “stickiness”, S, is calculated as the fraction of deposited chemical which never
returns to the air.
S W = ( N AW - N WA ) / N AW
where S W is the stickiness of water. This is a measure of the chemical’s tendency to remain in the
water and not return to the air compartment. The stickiness of soil, S S , and of vegetation, S V , are
similarly calculated.
3 APPLICATION OF TAPL3 (VERSION 3.00)
The persistence, P, characteristic travel distance in air, L A , and the average number of hops
experienced by a single molecule, H, are examined for two groups of chemicals, one consists of
hypothetical chemicals, and the other is four chemicals selected from the DSL.
3.1 Chemical Properties
The hypothetical chemical, X, first defined by Webster et al (1998) is used here to explore of the
impact of the changes made to the TaPL3 model. This chemical has properties similar to
tetrachlorobenzene but has degradation half-lives which are set at half the Canadian single-medium
persistence criteria. The degradation half-life in vegetation was assumed to be half that in air to
reflect the tendency of the leaf surface to be oriented such that photolysis will be maximized. By
varying log K OW values from 3 to 7 and vapour pressures from 0.0072 to 72000 Pa two sets of
hypothetical chemicals are produced. With this wide range of partitioning properties simulating
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chemical property space, the key characteristics of P, L A , and H, and the effects of including
vegetation as a primary medium were examined.
Four substances were selected from the DSL to continue the examination of P, L A , and H into the
realm of real chemicals.
The properties of X and the substances from the DSL used here are given in Table 3. The partitioning
tendency of the five chemicals in shown in Figure 1. Chemical-specific enthalpies of phase change
were used to adjust K OW and K AW for temperature, however, activation energies were not available.
The values are typical of organic substances and are sufficient to show temperature effects. However,
for an assessment, values specific to the chemical should be sought.
3.2 Environment Properties
For any set of chemical evaluations, a constant environment should be used, but the user should have
the ability to define that environment. The TaPL3 (version 3.00) model allows an environment to
be defined by the user and saved in a database for future use (as in the previously released version
of the model). For this study the “EQC - standard environment” (Mackay et al 1996) was used but
with vegetation included for half the simulations as noted. The parameters selected to represent
vegetation are considered to be reasonable estimates for typical conditions. For specific regions, field
data should be compiled. Table 4 shows the environmental properties.
As a part of this study, temperatures ranging from 5 to 25 C were examined. Canadian temperatures
are often lower than this, however, as discussed earlier, to avoid the complications of ice formation
and snow cover, only temperatures above freezing were used.
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3.3 Emissions
Two emission scenarios are considered in the TaPL3 model; to air and (separately) to water. In the
case of emission to air, air is considered to be the sole mobile medium and the characteristic travel
distance in air, L A , is calculated. Similarly, in the case of emission to water, water is considered to
be the sole mobile medium and the characteristic travel distance in water, L W is calculated. Since
chemicals are emitted to other media, it would be interesting to consider other scenarios. This will
be the topic of subsequent study. Here, only the more commonly considered and better understood
case of air as the mobile medium is examined.
3.4 Results for the Hypothetical Chemicals
The three key model outcomes (P, L A , H) for hypothetical chemical X and its partitioning variants
are shown in Figure 2 both with and without vegetation. In the absence of vegetation, model results
are consistent with the previously released version 2.10 of the model.
3.4.1 Temperature Variation
Chemical X was assigned enthalpies of phase change and reaction activation energies as shown in
Table 3. Over the range of temperatures from 25 to 5/C as temperature decreases K OW increases, i.e.,
the chemical partitions more strongly to octanol (soil, sediment and vegetation), K AW increases, i.e.,
the chemical partitions less strongly to air, and reaction rate constants decrease, i.e., the half-lives
increase, or degradation happens more slowly. Figure 2 shows the relative change in key model
outcomes with decreasing temperature for chemical X. The horizontal axis shows decreasing
temperature to reflect a molecule’s journey from south to north (in the Northern Hemisphere). As
temperature decreases, P, L A , and H all increase. This can be seen as the combined effect of the
general increase in media half-lives and the partitioning out of the air into media where degradation
happens more slowly. The stickiness of vegetation increases with decreasing temperature. As the
stickiness of the vegetation increases, the average number of hops experienced by a molecule
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decreases. In the presence of vegetation, P and H are greater for chemical X and L A is less. The
temperature effect is enhanced by the presence of vegetation which adds to the total volume of
octanol-like media in the modelled environment.
In summary, a molecule of chemical X has an increased longevity, travels increasing distances, and
experiences more hops as it moves from warmer to cooler regions in its journey northwards.
3.4.2 Partitioning Variants of X
The environment temperature was set at 20/C and two sets of chemicals were used to examine the
effects of partitioning properties on P, L A , and H with and without vegetation included in the
modelled environment.
Using the set of chemicals defined by varying log K OW from 3 to 7 and retaining all other properties
of chemical X, in the absence of vegetation, P increases with K OW while L A and H remain relatively
constant (Figure 2). By contrast, when vegetation is included in the modelled environment, P and
H are seen to peak at log K OW values of 6 and 5 respectively and L A declines after log K OW 5. At
higher K OW values the chemical partitions more strongly into vegetation where the half-life is
shortest, thus reducing P. This partitioning to vegetation is seen in the increased stickiness. With
increased partitioning into vegetation, i.e., out of the mobile medium (air), L A is reduced. Both the
shift in partitioning tendency out of the mobile medium and the increased degradation reduce H.
Similarly, using the set of chemicals defined by varying the vapour pressure from 0.0072 to 72000
Pa and retaining all other properties of chemical X in the presence of vegetation, persistence
declines, L A increases, and H peaks at about 0.72 Pa as shown in Figure 2. The presence of
vegetation enhances the effect on P, but without vegetation no effect is seen for L A and H.
Varying vapour pressure across the above range is equivalent for chemical X to varying log K AW
from -3.3 to 3.7. As K AW increases, these substances partition more into air and less into water
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making them more available for transport to vegetation which is modelled as interacting only with
air. At very low values of K AW , a high stickiness is seen due to the reduced tendency to partition to
air. At very high values of K AW , a high stickiness is seen due to an increased availability of the
substance. Thus the valley-shaped curve seen in Figure 2 results.
3.4.3 Summary for Chemical X
Figure 2 shows the effect of environmental temperature on a single chemical with and without
vegetation included in the modelled environment, and how vegetation interacts on the partitioning
and degradation properties of the chemical. A more complete representation of chemical space,
including a range of degradation half-lives, would further elucidate the effects of vegetation as it is
represented in TaPL3 version 3.00 on the key model outcomes of P, L A , and H and by the stickiness
of vegetation.
3.5 Results for Selected DSL Chemicals
Figure 3 shows P, L A , and H, for each of four substances; benzo[a]pyrene (B[a]p), chlorobenzene
(CB), hexachlorobenzene (HCB), and 2,3,7,8-tetrachloro-dibenzo-p-dioxin (TCDD). The open
triangle symbols indicate the case of no vegetation present while the solid square symbols indicate
the presence of vegetation. The horizontal axis represents decreasing temperature (a northward
movement) from 25 to 5 /C for each chemical in the EQC standard environment.
The two scenarios, with and without vegetation, show a general consistency, but with different scales
for these three chemicals. The change in the stickiness of vegetation is small over the range of
temperatures studied.
B[a]p: 0.99 to 1
CB: 0.009 to 0.002
HCB: 0.0002 to 0.0014
TCDD: 0.94 to 1
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The difference in the values for P, L A , and H between the vegetation scenario and the no vegetation
scenario are in agreement with studies showing the important role of vegetation for some chemicals.
Further study would be needed to ascertain the impact of the inclusion of vegetation in the modelled
environment on any chemical ranking for P, L A , and H. With this small set of very different
chemicals, no change in rank can be expected as the differences between the chemicals are greater
than the influence of vegetation.
4 CONCLUSION
The TaPL3 model was successfully upgraded to include provision for the temperature of the
modelled environment to be varied, vegetation as a primary medium with active chemical exchange
with air, and an estimate of the extent of “grasshopping”. This new version of the model will be
made freely and publically available from the CEMC website (http://www.trentu.ca/cemc/).
The limited application of this model to a set of hypothetical chemicals and four DSL chemicals
demonstrates some of the potential impact of the changes to the model on the key outcomes of
persistence, P, and characteristic travel distance in air, L A , and the average number of hops
experienced by a single molecule, H. For some substances, the inclusion of vegetation as a primary
medium in the model will affect the values of P, L A , and H. Temperature had a smaller effect than
the inclusion of vegetation. Chemical cycling between stationary and mobile media, as described by
H and the stickiness of vegetation, provides further insight into chemical fate in the environment.
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5 FUTURE RESEARCH DIRECTIONS
Several desirable research directions for the future are apparent.
1. The compiling of field data to confirm trends identified by the model and thus contribute to
validation and credibility.
2. Using emission scenarios other than to air only when determining long-range transport.
3. Performing a more detailed investigation of the effects of each vegetation parameter.
4. Investigating the complex processes caused by the presence of snow and including these
processes in models to simulate sub-zero climates.
5. It has been demonstrated that the present treatment of soil as a single well-mixed layer is
excessively simplistic. The calculation of the resistence to uptake and volatilization requires
that the chemical diffuse a distance of half the soil depth. Bioturbation by soil-dwelling
organisms can assist this transport process and can enhance the rates of uptake and release.
6. TaPL3 is a true steady-state model which describes conditions when this steady-state is
reached. For substances of high K OA this time may be very long i.e., decades, thus in the
immediate future the actual values of P, L, and H may be different. Investigating this effect
would require a dynamic, or Level IV, model which is considerably more complex and data
intensive, but could provide additional, valuable insights into chemical’s persistence and
long-range transport.
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Mackay, D. 1979. Finding Fugacity Feasible. Environ. Sci. Technol. 13: 1218.
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Table 1: Additional information needed for the inclusion of a vegetation compartment.
Chemical properties for vegetation
degradation half-life in vegetation (h)
reaction activation energy(kJ/mol)
Environment properties for vegetation
fraction of landmass covered by vegetation
leaf biomass (kg/m 2 )
density of leaf tissue (kg of vegetation / m 3 of vegetation)
lipid fraction (g/g)
leaf area index (m 2 /m 2 )
leaf-air boundary layer mass transfer coefficient (m/h)
fraction of rain intercepted by the foliage

Table 2: Foliage-air transport D value calculations (based on Cousins and Mackay 2001).
Diffusion
Rain
Log P C = ((0.704 log K OW - 11.2) + (-3.47 - 2.79 log MM + 0.970 log K OW ))/2
P C is the cuticle permeance (m/s)
MM is the molar mass (g/mol)
U C = 3600 P C / K AW
U C is the mass transfer coefficient through the cuticle (m/h)
D C = A V L Z V U C
D C is for diffusion into the cutin
L is the leaf area index (m 2 /m 2 )
Z V is the fugacity capacity of vegetation (mol/m 3 Pa)
D B = A V L Z A U B
D B is for boundary layer diffusion
Z W is the fugacity capacity of air (mol/m 3 Pa)
U B leaf-air boundary layer mass transfer coefficient (m/h)
D A = 1/(1/D C +1/D B )
D A is total diffusion
D R = A V v R Z W U R
Aerosol dry deposition
v R is the volume fraction of rain intercepted by the foliage (m 3 /m 3 ), a user input
Z W is the fugacity capacity of water (mol/m 3 Pa)
U R is the rain rate (m/h), a user input
D Q = A V v Q Z Q U Q
Aerosol wet deposition
A V is the area covered by vegetation (m 2 )
v Q is the volume fraction of aerosols in air (m 3 /m 3 ), a user input
Z Q is the fugacity capacity of aerosols (mol/m 3 Pa)
U Q is the aerosol dry deposition rate (m/h), a user input
D Q = A V v R Q v Q Z Q U R
Q is the rain scavenging ratio

Table 3: Properties of selected chemicals.
X B[a]p CB HCB TCDD
Molar mass, g/mol
Data Temperature, C
215.9
25
a
a
252.32
25
b 112.56
25
b 284.79
25
b 322.00
25
b
Partitioning properties
Water Solubility, g/m 3
Vapor Pressure, Pa
Log K OW
Melting Point, /C
1.27
0.72
4.5
140
a
a
a
a
0.0038
7 x 10 -7
5.94
175
b
b
c
b
484
1580
2.80
-45.6
b
b
c
b
0.005
0.0023
5.47
230
b
b
c
b
1.93 x 10 -5
2 x 10 -7
6.83
305
b
b
c
b
Reaction half-lives, hours
Air
Water
Soil
Sediment
Vegetation
24
2184
2184
4380
12
a
a
a
a
d
170
1700
17000
55000
85
b
b
b
b
d
170
1700
5500
17000
85
b
b
b
b
d
17000
55000
55000
55000
8500
b
b
b
b
d
170
550
17000
55000
85
b
b
b
b
d
Temperature dependence parameters
Enthalpies of Phase Change (used to modify partition coefficients) kJ/mol
K OW
-20
K AW 55
-25.40
36.89
c
c
-15.00
28.85
c
c
-16.87
46.35
c
c
-18.22
74.44
c
c
Reaction Activation Energies (used to modify the rate constants) kJ/mol
Air
Water
Soil
Sediment
Vegetation
10
30
30
30
10
10
30
30
30
10
10
30
30
30
10
10
30
30
30
10
10
30
30
30
10
a Webster et al (1998)
b Mackay et al (2000)
c Beyer et al (2002)
d Degradation half-lives in vegetation were estimated at half the value of the degradation halflife
in air.

Table 4: Environmental properties of the “EQC standard environment” (based on Mackay et al
1996).
Area, m 2
Depth, m
Air
Water
Soil
Sediment
10 11
1000
10 10
20
9 x 10 10
0.2
10 10 0.05
Area fraction of vegetation 0.8
Volume Fractions Densities, kg/m 3 Organic Carbon or Lipid Fraction
Aerosols
Suspended particles
Fish
Soil pore air
Soil pore water
Soil solids
Sediment pore water
Sediment solids
Vegetation
2 x 10 -11
5 x10 -6
10 -6
0.2
0.3
0.5
0.8
0.2
2400
1500
1000
2400
2400
900
0.2 g/g
0.05 g/g
0.02 g/g
0.04 g/g
0.01 g/g
Wind velocity
Water velocity
14.4 km/h
36. km/h
Vegetation biomass
Leaf area index
1 kg/m 2
3 m 2 /m 2
Transport velocities
m/h
Air side air-water MTC
Water side air-water MTC
Rain rate
Aerosol dry deposition velocity
Soil air phase diffusion MTC
Soil water phase diffusion MTC
Soil air boundary layer MTC
Sediment-water MTC
Sediment deposition velocity
Sediment resuspension velocity
Soil water runoff rate
Soil solids runoff rate
Leaf-air boundary layer MTC
Scavenging ratio
Fraction of rain intercepted by vegetation
5
0.05
0.0001
10
0.02
0.00001
5
0.0001
0.0000005
0.0000002
0.00005
0.00000001
9
200000
0.1

log Kaw
4
3
2
1
0
-1
-2
-3
-4
-5
-6
-7
-8
-9
-10
0 1 2 3 4 5 6 7 8 9
log Kow
Figure 1:
The partitioning tendency of X (x), benzo[a]pyrene (square), chlorobenzene
(triangle), hexachlorobenzene (star), 2,3,7,8-TCDD (circle). The diagonal lines
represent lines of constant log K OA . Chemicals in the upper left tend to partition
into air, in the lower left to water, and in the lower right to octanol.

Decreasing Environment Temperature
logK OW
Vapour Pressure
100
80
600
P
90
80
70
60
50
70
60
50
40
500
400
300
40
30
20
10
0
25
20
15
10
5
30
20
10
0
3 4 5 6 7
200
100
0
0.0001 0.01 1 100 10000 1000000
700
600
600
650
500
500
LA
600
550
400
300
400
300
500
200
200
450
100
100
0
400
25
20
15
10
5
0
3 4 5 6 7
0.0001 0.01 1 100 10000 1000000
0.5
0.5
0.5
0.45
0.4
0.4
0.4
H
0.35
0.3
0.3
0.3
0.25
0.2
0.2
0.2
0.15
0.1
0.1
0.1
0.05
0
25
20
15
10
5
0
3 4 5 6 7
0
0.0001 0.01 1 100 10000 1000000
0.1
1
1
0.08
0.8
0.8
0.06
0.6
0.6
Sv
0.04
0.4
0.4
0.02
0.2
0.2
0
25
20
15
10
5
0
3 4 5 6 7
0
0.0001 0.01 1 100 10000 1000000
Figure 2:
The three key model outcomes for chemical X and its partitioning variants. The stickiness of vegetation is related
to both potential for long-range transport and the average number of hops experienced by a molecule. The solid
squares indicate the presence of vegetation; the open triangles indicate the absence of vegetation in the
modelled environment.

B[a]p CB HCB TCDD
7.E+04
400
2.E+05
6.E+04
P
6.E+04
5.E+04
4.E+04
3.E+04
2.E+04
1.E+04
350
300
250
2.E+05
1.E+05
5.E+04
5.E+04
4.E+04
3.E+04
2.E+04
1.E+04
0.E+00
25
20
15
10
5
200
25
20
15
10
5
0.E+00
25
20
15
10
5
0.E+00
25
20
15
10
5
La
500
450
400
350
300
250
200
150
100
50
0
25
20
15
10
5
5000
4500
4000
3500
3000
25
20
15
10
5
2.E+05
2.E+05
1.E+05
5.E+04
0.E+00
25
20
15
10
5
900
800
700
600
500
400
300
200
100
0
25
20
15
10
5
0.002
0.15
4
0.03
H
0.0015
0.001
0.1
3
2
0.02
0.0005
0.05
1
0.01
0
25
20
15
10
5
0
25
20
15
10
5
0
25
20
15
10
5
0
25
20
15
10
5
Sv
0.999
0.998
0.997
0.996
0.995
0.994
0.993
0.992
0.991
25
20
15
10
5
0.01
0.008
0.006
0.004
0.002
0
25
20
15
10
5
0.0014
0.0012
0.001
0.0008
0.0006
0.0004
0.0002
0
25
20
15
10
5
1
0.98
0.96
0.94
0.92
0.9
25
20
15
10
5
Figure 3:
The persistence, P, characteristic travel distance in air, La, and average number of hops experienced
by a single molecule, H, for each of four substances; benzo[a]pyrene (B[a]p), chlorobenzene (CB),
hexachlorobenzene (HCB), and 2,4,7,8-TCDD. The open triangle symbols indicate the case of no
vegetation present while the filled square symbols indicate the presence of vegetation. The horizontal
axis represents decreasing temperature.