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FATEMOD: Modeling for Risk Exposure from Chemicals

This study presents the FATEMOD model for predicting the fate of chemicals in the environment and assessing their associated risks. The model incorporates various parameters and properties to estimate the extent and probability of damage occurring from chemical exposure.

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FATEMOD: Modeling for Risk Exposure from Chemicals

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  1. FATEMOD MODELING FOR RISK EXPOSURE FROM CHEMICALS Jaakko Paasivirta, Department of Chemistry, University, Niilo Paasivirta, Suomen Postmaster (enterprise), Jyväskylä, Finland

  2. RISK CHARACTERIZATION (Germany) Risk = Extend of Damage * Probability of its Occurrence R = E x P Model Damokles: E high, P low (chemial accident)

  3. 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)

  4. 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)

  5. Model Pythia: both E and P uncertain

  6. 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)

  7. 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)

  8. 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

  9. 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).

  10. Images of Medusa Gorgon USA a.d. 2001 Syracuse 580 b. Chr.

  11. 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).

  12. Modeling for prediction of the fate of chemical in environment

  13. To predict fate of Machbet: Exact witchcraft !

  14. 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

  15. 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)

  16. / Plants

  17. 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).

  18. FATEMOD editing window for substance parameters

  19. 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 Conversions between temterature coefficients for Vp’s are: Aps = Apl + ∆Sf / (RxLn10) and Bps = Bpl + ∆Sf x Tm / (R*Ln10) VPLEST result for liquid state Vp’s of DNOC is: Compound Mp C ∆Sf Pl(25) Apl Bpl Aps Bps DNOC 86.5 57.04 0.24311.31 3496 14.29 4567

  20. 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 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 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. 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

  21. 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

  22. 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.

  23. 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 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 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 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

  24. HLT = 20 OC reference values for DNOC are HL(1) = 170 h, HL(2) = 500 h, HL(3) = 720 h, HL(4) = 1000 h

  25. 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

  26. 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.

  27. 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) = 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

  28. The process chemicals emitted to the waste stream ---------

  29. 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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