FATEMOD MODELING FOR RISK
EXPOSURE FROM CHEMICALS
Jaakko Paasivirta,
Department of Chemistry, University,
Niilo Paasivirta, Suomen Postmaster (enterprise),
Jyväskylä, Finland
Risk management scheme (EPA)
Risk management
Risk estimation
Control
decision
Dose/response
assessment
Risk
characterization
Hazard
identification
Acceptable
level determination
Control
options
Exposure
assessment
Feedback
RISK CHARACTERIZATION (Germany)
Risk = Extend of Damage * Probability of its Occurrence
R= E x P
Model Damokles: E high, P low (chemial accident)
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)
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 Pythia: both
E and P uncertain
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)
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)
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
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 electromagnetic fields. Many believe that risk is high).
Images of Medusa Gorgon
USA a.d. 2001
Syracuse 580 b. Chr.
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 electromagnetic fields. Many believe that risk is high).
Environmental risk assessment of chemical
Properties
of the chemical
and the environment
Exposure
assessment
(modelling)
PEC
Predicted
Environmental
Concentration
Tests, QSAR,
Analyses
Effect potency
assessment
(ecotoxicology)
Risk ratio:
Ro = PEC / PNEC
by emission
Eo
RISK EMISSION = Eo / Ro
Modeling for prediction of the
fate of chemical in environment
PNEC
Predicted
No-Effect Conentration
Machbetin kohtalon
ennustaminen:
eksaktia noituutta!
To predict fate
of Machbet:
Exact witchcraft !
CemoS programs: Trapp & Matthies (1996)
English Handbook: Springer 1998.
AIR. Concentrations caused from
continuous point-source emission.
PLUME. Concentration in Air after point emission event.
LEVEL 1. Identical with the Mackay Level 1 model.
LEVEL 2. Concentrations by continous emission, residence
time in system and ("Level 4") recovery from contamination
BUCKETS. Transport of compound in surrounding soil layer.
SOIL. Vertical movement and fate of chemical
in different soil contamination types.
PLANT. Uptake by plants from soil and air.
WATER. Concentrations in River or river-like water system.
CHAIN. Chain reaction ----> bioaccumulation in a food chain.
FATEMOD model
-> Modified Mackay level 1-4 model for fate of chemical in a one box six
compartment catchment area environment (WINDOWS program)
-> Values of the physical properties and degradation lifetimes of the
chemical are automatically adjusted for ambient temperature and pH
values of water and soilwater
-> Level 1 and 2 output can be used as compound property values in
other specific fate models like CemoS and bioaccumulation models
-> Level 3 output gives realistic estimates of levels and residence times
by constant emission in non equilibrium steady state
-> Level 4 output presents concentrations at different times after stop of
emission (a steady state prediction to the future)
-> To include transport of chemical within catchments, FATEMOD for the
joint areas can be run successively. Then, the modelled flows from
one area are considered as emissions to the adjacent neighbour area
-> The properties of environments and compounds including correction
coefficients for temperature adjustments are recorded in the editable
database of FATEMOD. Report to EXEL takes place by push button
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
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
(ΔSf), 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),
Henry’s 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)
Air
FATEMOD environment: catchment area
Water
¤ Sizes etc: Area, Depth, Density,
Soil / Plants
pH, Fraction of organic carbon
Sediment
¤ Processes:Advections (flows), Diffusions,
Suspended Solids
Evaporation, Depositions
¤ Temperature
Fish
Norw ay
o
29
KemR
67
Arctic
o
Kemijoki River catchment area
(51120 Km 2).
Mean annual temperature +1 OC
Circle
km
0
N
100
200
Sw eden
Russia
Bay of
Bothnia
South-West Finland area
(36358 Km 2). Catchment of
the Rivers flowing to the
Bothnian Sea.
Mean annual temperature +8 OC
Finland
SWF
S
Jyväskylä
Bothnian
Sea
Ladoga
Helsinki
Gulf of
Finland
Stockholm
Baltic
Sea
Gotland
Estonia
St.Petersburg
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).
FATEMOD editing window for substance parameters
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 Grain’s 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
OH
Conversions between temterature coefficients for Vp’s are:
Aps = Apl + ∆Sf / (RxLn10) and Bps = Bpl + ∆Sf x Tm / (R*Ln10)
CH3
O2N
VPLEST result for liquid state Vp’s of DNOC is:
NO 2
Compound Mp C ∆Sf Pl(25) Apl
Bpl Aps
DNOC
86.5 57.04 0.243 11.31 3496 14.29
Bps
4567
124578-hexachloronaphthalene:
Pl values by two methods
2
Pl (mPa)
Cl
1.5
Cl
Cl
Cl
Cl
1
0.5
Cl
VPLEST
GC
Lei et al. 1999
0
0
5
10
15
t OC
20
25
30
OH
Herbicide DNOC: evaluation of solubility coefficients for FATEMOD
CAS 534-52-1, WM 198.122, Mp 86.5 C →Tm 359.65 K
O2N
Enthalpy of fusion Δ Hf = 20515 J mol-1 (DSC by C.Plato
(1972) Anal. Chem. 44, 1531-1534).
Entropy of fusion Δ Sf = ΔHf / Tm = 57.04 J K-1 mol-1.
Liquid state molar volume Vb = 137.4 cm3 mol-1 [from increments
NO 2
of P.Ruelle et al. (1991) Pharm. Res. 840-850. pKa = 4.31
Solubility parameter DB = Σ Fdi / Vb according to P.Ruelle (2000) Chemosphere
40, 457-512. Σ 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.
CH3
Example: association terms for DNOC are (KAccO values are zeros)
vAcc
2
vDon
1
KAccW(i)
100,100
KDonW(i)
5000
MAXW
5000
KDonO(i)
5000
MAXO
5000
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
+ ΣNOHx(2+boh) / Ln10 + ΣvAcc(i)xLog(1+KaccW(i)/18.1)
+ ΣvDon(i)xLog(1+KDonW(i)/18.1)
Bs = ∆Sf x Tm / (RxLn10) + (DB- 20.5)2 x Vb / (RxLn10)
x Log (1+MAXW / 18.1)
Example: Output from WATSOLU for DNOC: As = 4.617, Bs = 1071.7
VOLATILITY: Henry’s 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
600
OH
CH3
O 2N
500
400
ry's
n
e
H
Law nt
sta
Con tion
c
Fun
NO2
DNOC
300
200
H
mPa m 3
mol -1
S
(mg L-1) / 10
100
Pl mPa
tC
0
0
5
10
15
20
25
30
Validation of S estimate by two independent methods:
OH
OCH3
Cl
pKa = 4.31
Cl
Cl
WATSOLU
of the
HPLC pH
eluent = 5.60
Tam D, Varhanikova D, Shiu WY and
Mackay D (1994) J.Chem.Eng.Data 39, 82-86.
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 Ruelle’s 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) – ΣNOH x (boh + rw – ro)] / Ln10
ΔAcc = ΣvAcc x Log[(1 + KaccO(i) / 124.2)/(1 + KaccW(i) / 18.1)]
ΔDon = ΣvDon x Log[(1 + KdonO(i) / 124.2) / (1 + KdonW(i) / 18.1)]
Bow = (Vb/(RxLn10)x[(DB-20.5)2/(1+MAXW/18.1)–(DB-16.38)2/(1+MAXO/124.2)]
Where 18.1 is the molar volume of pure water, 124.2 the reduced molar volume of watersaturated 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 POP’s) 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
O2N
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/.
NO2
NO2
Musk xylene
HLT = 20 OC reference values for DNOC are HL(1) = 170 h,
HL(2) = 500 h, HL(3) = 720 h, HL(4) = 1000 h
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 NβCls 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 + Nβ)*6.5 % ; HL(i) = HL(i) max * (100 - F) / 100
Prediction of contents of lindane in SWF
environment after stop of all local uses 1.1.1990
4
3.5
3
Water ng/L
2.5
2
1.5
Fish ng/g
1
Soil ng/g
0.5
Sedim. ng/g
0
1990
91
92
93
94
95
96
97
98
99
2000
400
350
ug/L
KemR 5 OC
300
250
LC50 / fish
200
150
OH
O2N
CH3
SWF 20 OC
100
DNOC
50
NO2
PNEC / fish
0
0
2
4
6
8
10 12 14 16 18 20
Months
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 SouthWest and North
Finland.
Guideline determination for industrial emission
Industrial discharge to Coastal Bothnian Bay
Waste water stream (WS)
Recipient Sea Area (RSA)
Ar(1,2,3) = 1E+6 (=1000000) m2
HT(1)=500, HT(2) =10, HT(4)=0.01 m
GA(1)=2.5E+7, GA(2)=2.86E+5,
GA(4)=0.2 m3 h-1
GRA(1)=20, GRA(2) =35,
GRA(4)=50000 h
OCFr(4) = 0.04
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
CF 3
The process chemicals
emitted to the waste
stream ---------
Cl
H 3CSO2
IFT
O
CBz
CBz
IFT
IFT
DKN
DKN
t C
5
20
5
20
5
20
-1
ug L
C
O
C
CH C
DKN
CBz
Values of ecotoxicity
Toxic level -->
Code
Cmpound
CBz
Chlorobenzene
IFT
Isoxaflutole
DKN
Diketonitrile
RE determination
Code
PEC
O
Daphnia
LC50
PNEC
Fish
LC50
PNEC
Algae
LC50
PNEC
mg L-1
ug L-1
mg L-1
ug L-1
mg L-1
ug L-1
5.8
580
22.0
1.7
1.7*
2200
170
170
12.5
0.33
0.33*
1250
33
33
Daphnia
Ro
RE
Kg h
Fish
Ro
-1
Algae
RE
Kg h
Ro
-1
RE
Kg h-1
2.319
0.004
250
0.0011
949
0.001855
539
2.229
0.00384
260
0.0010
987
0.001783
561
2.529
0.0149
67
0.076636
13
1.566
0.0092
109
0.047455
21
3.458
0.0203
49
0.104788
10
3.386
0.0199
50
0.102606
10
* Assumed toxicity for DKN was the same as for its precursor IFT
PEC = the modelled stationary state concentration in water ("Predicted Environmental Concentration")
-1
Risk ratio Ro = PEC / PNEC (for emission to the first waste basin Eo = 1 Kg h )
Risk emission RE = 1 / R (Kg h -1 to the first waste basin)
N
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:
CF 3
Cl
H 3CSO2
IFT
O
CH C
O
CBz
GE for CBz 25
C
N
C
DKN
GE for IFT(stable metabolite DNK incl.) 1
kg h-1
BIBI
BIoaccumulation via Benthic Invertebrates
SEDIMENT (1)
COC = CON(1) / OCFR
SWR
BENTHIC INVERTEBRATES (3)
CON(3) = SWR x COC x LFR(3)
SWR
WATER (2)
CON(2) =
SWR x COC / Kow
K1(5)
KD(4)
K1(4)
FIRST CONSUMER (4)
CON(4) = * (i=4)
KD(5)
SECOND CONSUMER
CON(5) = * (i=5)
(5)
K2,KE,
KG,KM
*CON(i) = (K1(i)XCON(2)+KD(i)xCON(i-1))/(K2(i)+KE(i)+KG(i)+KM)
mg/cm
3
Fate of TeCP in SWF soils; model SOIL/CemoS
pH 5.5
Concentration profiles 20 years after
OC =0.05
initial contamination of 10 cm
45
40
topsoil layer 100 mg / cm
35
3
pH 6.0
OC =0.05
30
25
pH 6.5
OC = 0.05
20
15
pH 6.0
OC = 0.01
pH 6.5
OC =0.01
10
5
Depth m
0
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
11
Pentachlorophenol in worms (Aporrectoea)
of South-West Finland soil originally
contaminated by 100 ug/g dw
10
9
8
CWURM
ug/g ww
7
6
5
4
3
Time years with no further contamination
2
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Why you dont like rak,
fresh Norrland w orms?
VPLEST, WATSOLU, TDLKOW
and LEVEL3+ predicted that they
contain too much M alathione !