FATEMOD MODELING FOR RISK

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FATEMOD MODELING FOR RISK EXPOSURE FROM
CHEMICALS Jaakko
Paasivirta, Department of Chemistry,
University, Niilo Paasivirta, Suomen
Postmaster (enterprise),
Jyväskylä, Finland
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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low (chemial accident)
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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low
(chemial accident)
Model Cyclops E high, P low (mass
invasions of non-native species)

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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low
(chemial accident)
Model Cyclops E high, P low (mass
invasions of non-native species)
Model Pythia E uncertain, P uncertain
(gene modification)

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Model Pythia both E and P uncertain
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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low
(chemial accident)
Model Cyclops E high, P low (mass
invasions of non-native species)
Model Pythia E uncertain, P uncertain
(gene modification)
Model Pandora E uncertain, P high (PET
compounds damage is irreversible)

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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low
(chemial accident)
Model Cyclops E high, P low (mass
invasions of non-native species)
Model Pythia E uncertain, P uncertain
(gene modification)
Model Pandora E uncertain, P high (PET
compounds damage is irreversible)
Model Cassandra E high, P high (Climatic
change - people do not believe)
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Cassandra was a profet knowing the future. But
people did not believe her (cource of Ares).
Here Aigistos and Klytaimnestra are murdering
Agamemnon and Kassandra
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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low
(chemial accident)
Model Cyclops E high, P low (mass
invasions of non-native species)
Model Pythia E uncertain, P uncertain
(gene modification)
Model Pandora E uncertain, P high (PET
compounds damage is irreversible)
Model Cassandra E high, P high (Climatic
change - people do not believe)
Model Medusa E low, P low (high frequency
electro- magnetic fields. Many believe that risk
is high).
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Images of Medusa Gorgon
USA a.d. 2001
Syracuse 580 b. Chr.
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RISK CHARACTERIZATION (Germany)
Risk Extend of Damage Probability of its
Occurrence R E x
P
Model Damokles E high, P low
(chemial accident)
Model Cyclops E high, P low (mass
invasions of non-native species)
Model Pythia E uncertain, P uncertain
(gene modification)
Model Pandora E uncertain, P high (PET
compounds damage is irreversible)
Model Cassandra E high, P high (Climatic
change - people do not believe)
Model Medusa E low, P low (high frequency
electro- magnetic fields. Many believe that risk
is high).
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Modeling for prediction of the fate of chemical
in environment
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To predict fate of Machbet Exact witchcraft !
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EXAMPLE OF APPLICATIONS
Use of the FATEMOD model in
the environmental risk
estimation of chemicals in
discharges Jaakko Paasivirta,
Seija Sinkkonen, Markus Soimasuo,
University of Jyväskylä, Finland
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FATEMOD database parametrization of the values
for properties of the environments and chemicals
Properties of the
environments. Instead using unit world box 1 x 1
x 1 Km as suggested by D.Mackay Multimedia
Environmental Models L-242, Lewis, Chelsea, MI,
USA) suitable for general risk estimation of
chemicals, we adopted natural catchment areas as
model environments to achieve more flexibility
for different cases of risk evaluations.
Properties of the chemical
compounds. Molecular properties Name, Group,
Subgroup, CAS register number, Molar mass (WM),
Melting point (Tm K), Entropy of Fusion (?Sf),
Liquid state molar volume (Vb), pKa (for acids or
bases)
Temperature-dependent properties Log(pr) Apr
Bpr. Vapor pressure in liquid state (Pl Pa),
Solubility in water (S mol m-3), Henrys law
function (H Pa m3 mol-1), Hydrophobity LogKow
(where Kow is the octanol-water partition
coefficient) and. Degradation half-life
times HL(i) (i 1 air, 2 water, 3
soil/plants and 4 sediment reference time HLT
(usually 20 or 25 C)
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/ Plants
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FATEMOD window for editing property values of the
environment box
Southwest Finland (SWF) catchment area of the
Finnish Rivers flowing to the Bothnian Sea.
Major compartments for mass balance Air,
surface Water, Soil (including surface plants),
and Sediment. Minor compartments for
concentration data Suspended sediment and Fish
(aquatic biota).
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FATEMOD editing window for substance parameters
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Determination of the compound property as
function of temperature
(SUBCOOLED) LIQUID STATE VAPOR PRESSURE
VPLEST for evaluation the coefficients Apl and
Bpl for Log Pl Apl -
Bpl / T
Method is from Clark F. Grain in Handbook of
Chemical Estimation Methods, W.J.Lyman, W.F.Reehl
and D.H.Rosenblatt (Eds), ACS, Washington, DC
(1990) in Chapter 14. Liquid state vapor
pressures are computed in one Celsius intervals
at environmental range (e.g. -2 to 30C) by
Grains equation 14-25 using one known Vp and
temperature as reference. Then, the coefficients
are determined by linear regression.
The reference Vp can be for either solid or
liquid state (Ps or Pl). They can be converted to
each other by equation
Log Ps Log Pl ?Sf x (1-Tm/T) / (R x Ln10)
0bs. R x Ln10 19.1444
Conversions between temterature coefficients for
Vps are Aps Apl ?Sf / (RxLn10) and Bps
Bpl ?Sf x Tm / (RLn10)
VPLEST result for liquid state Vps of DNOC is
Compound Mp C ?Sf Pl(25) Apl Bpl
Aps Bps DNOC 86.5 57.04
0.243 11.31 3496 14.29 4567
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Herbicide DNOC evaluation of solubility
coefficients for FATEMOD
CAS 534-52-1, WM 198.122, Mp 86.5 C ?Tm 359.65
K Enthalpy of fusion ? Hf 20515 J mol-1 (DSC by
C.Plato (1972) Anal. Chem. 44, 1531-1534). Entropy
of fusion ? Sf ?Hf / Tm 57.04 J K-1 mol-1.
Liquid state molar volume Vb 137.4 cm3 mol-1
from increments of P.Ruelle et al. (1991) Pharm.
Res. 840-850. pKa 4.31
Solubility parameter DB S Fdi / Vb according to
P.Ruelle (2000) Chemosphere 40, 457-512. S Fdi is
the dispersion component of molar attraction
constant calculated from increments of C.W.van
Krevelen (1990) in Properties of Polymers,
Elsevier, Amsterdam, pp. 212-213. Value calcd.
for DNOC 18.20.
Parameters needed for estimation of water
solubility and hydrophobity of the chemicals are
association terms P.Ruelle (2000) Chemosphere
40, 457-512. vAcc and vDon are the numbers of
active sites. KAccW(i) and KDonW(i) are
stability constants for proton acceptor and donor
groups of the compound in the water. Similar
terms for the compound in n-octanol are KAccO(i)
and KDonO(i). The greatest value of these
association terms, MAXW or MAXO are also needed
in evaluation. Additionally, sum of the hydroxyl
groups is NOH, and parameter boh has value of 1,
2 or 2.9 for primary, secondary of tertiary OH
group, respectively.
Example association terms for DNOC are (KAccO
values are zeros) vAcc vDon KAccW(i)
KDonW(i) MAXW KDonO(i) MAXO
2 1 100,100 5000
5000 5000 5000
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Solubility in water S mol m-3
WATSOLU.bas for evaluation the coefficients for
Log S As - Bs / T
WATSOLU is based on mobile order thermodynamics
estimation for log S at 25 C (P.Ruelle et al.
(1997) Int. J. Pharm. 157, 219-232). We have
divided equations to temperature dependent (Bs/T)
and non-dependent (As) parts
As 5.154 ?Sf / (RxLn10) - 0.036xVb-0.217xLnVb
SNOHx(2boh) / Ln10 SvAcc(i)xLog(1KaccW(i)/1
8.1) SvDon(i)xLog(1KDonW(i)/18.1)
Bs ?Sf x Tm / (RxLn10) (DB- 20.5)2 x Vb /
(RxLn10) x Log (1MAXW / 18.1)
Example Output from WATSOLU for DNOC As
4.617, Bs 1071.7
VOLATILITY Henrys law fuction
Simple conversions for Log H Ah Bh /
T At the narrow temperature range of environments
values of Ah and Bh are in fair agreement with
the relation H Pl / S. Therefore, FATEMOD model
automatically calculates them by conversions Ah
Apl As, and Bh Bpl - Bs .

Example conversion result for DNOC Ah 6.693
Bh 2424.3
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Validation of S estimate by two independent
methods
pKa 4.31
WATSOLU
HPLC
pH of the eluent 5.60
Tam D, Varhanikova D, Shiu WY and Mackay D
(1994) J.Chem.Eng.Data 39, 82-86.
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Hydrophobity (lipophility) as Log Kow is also
temperature-dependent!
TDLKOW.bas for octanol/water partition LogKow
Aow Bow / T Is based on thermodynamic
estimation of LogKow at 25 C of P.Ruelle (2000)
Chemosphere 40, 457-512. We have divided Ruelles
equations in two parts to obtain the temperature
coefficients Aow and Bow

Aow ?B ?F ?Acc
?Don ?B (0.5 x Vb x (1/124.2-1/18.1)
0.5 x Ln(18.1/124.2) / Ln10 ?F (vB x
(rw/18.1 ro/124.2) SNOH x (boh rw ro) /
Ln10 ?Acc SvAcc x Log(1 KaccO(i) /
124.2)/(1 KaccW(i) / 18.1) ?Don
SvDon x Log(1 KdonO(i) / 124.2) / (1
KdonW(i) / 18.1) Bow (Vb/(RxLn10)x(DB-20.5)
2/(1MAXW/18.1)(DB-16.38)2/(1MAXO/124.2)
Where 18.1 is the molar volume of pure water,
124.2 the reduced molar volume of water-
saturated n-octanol, rw structuration factor for
water (2.0) and ro structuration factor for
wate-saturated n-octanol. Observe that
association coefficients for water are the same
as those in WATSOLU.bas (see above). The
temperature coefficient Bow is practically
zero for compounds (often POPs) having only one
kind of substituents, but with several polar
and different substituents in structure Bow can
be significant.

Example1 TDLKOW output for DNOC
Aow 3.826 Bow - 0.439
Example 2 Musk xylene parameters from TDLKOW are
Aow 5.022 and Bow 361.6 in fair agreement of
HPLC and literature values /J.Paasivirta,
S.Sinkkonen, A-L.Rantalainen, D.Broman and
Y.Zebühr (2002) Environ Sci Pollut Res 9(5),
345-355/.
Musk xylene
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HLT 20 OC reference values for DNOC are HL(1)
170 h, HL(2) 500 h,
HL(3) 720 h, HL(4) 1000 h
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QSPR estimation of the
reference lifetimes. Example for
polychloronaphthalenes (PCNs). Based on maximal
and minimal HLT 25OC values in NCl classes of
PCDF mode of Mackay et al. and QSPR from
environmental data (J.Falandysz 1998). The most
abundant PCN congeners in Baltic Sea are included
here
Code Cl-subst. NCH-CH NßCls F
HL(1) h HL(2) h HL(3) h HL(4)
h CN42 1,3,5,7 0 2
13 522 1740 26100
87000 CN33 1,2,4,6 2
1 20 483 1610
24150 80500 CN28 1,2,3,5
2 2 26 444
1480 22200 74000 CN27
1,2,3,4 3 2 33
405 1350 20250
67500 CN35 1,2,4,8 2 3
33 405 1350 20250
67500 CN38 1,2,5,8 2
3 33 405 1350
20350 67500 CN46 1,4,5,8
2 4 39 366
1220 18300 61000 CN52
1,2,3,5,7 0 1 7
561 1870 28050
93500 CN58 1,2,4,5,7 0
2 13 522 1740
26100 87000 CN61 1,2,4,6,8
0 2 13 522
1740 26100 87000 CN50
1,2,3,4,6 1 1 13
522 1740 26100
87000 CN51 1,2,3,5,6 1
2 20 483 1610
24150 80500 CN57 1,2,4,5,6
1 2 20 483
1610 24150 80500 CN62
1,2,4,7,8 1 2 20
483 1610 24150
80500 CN53 1,2,3,5,8 1
2 20 483 1610
24150 80500 CN59 1,2,4,5,8
1 3 26 444
1480 22200 74000 CN66
1,2,3,4,6,7 0 0 0
600 2000 30000
100000 CN64 1,2,3,4,5,7 0
1 7 561 1870
28050 93500 CN69 1,2,3,5,7,8
0 1 7 561
1870 28050 93500 CN71
1,2,4,5,6,8 0 2 13
522 1740 26100
87000 CN63 1,2,3,4,5,6 1 1
13 522 1740
26100 87000 CN65 1,2,3,4,5,8
1 2 20 483
1610 24150 80500

F (NCH-CH Nß)6.5 HL(i) HL(i) max
(100 - F) / 100
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FATEMOD level IV concentratios in water after
stop of early May application of 10 Kg DNOC per
hectare on plants (0.7 was leached to water)
in SWF and KemR areas of South- West and North
Finland.
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Guideline determination for industrial emission
Industrial discharge to Coastal Bothnian Bay
Waste water stream (WS) AR(1,2,4) 31250 m2
HT(1)100, HT(2)3, HT(4)0.01 m GA(1)3125000,
GA(2)4167, GA(4)0.00625 m3 h-1 GRA(1)1,
GRA(2)22.5, GRA(3)50000 h OCFr(4) 0.06
Recipient Sea Area (RSA) Ar(1,2,3) 1E6
(1000000) m2 HT(1)500, HT(2) 10, HT(4)0.01
m GA(1)2.5E7, GA(2)2.86E5, GA(4)0.2 m3
h-1 GRA(1)20, GRA(2) 35, GRA(4)50000 h
OCFr(4) 0.04
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The process chemicals emitted to the waste stream
---------?
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Conclusions Guideline values for highest
allowable discharges to the waste stream GE
lowest RE value divided by the safety factor
(10) for each waste compound
GE for CBz 25 GE for IFT(stable
metabolite DNK incl.) 1 kg h-1
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