1
Supplemental Information for
Elimination half-life as a metric for the bioaccumulation potential of chemicals in aquatic
and terrestrial food chains
Kai-Uwe Gos †, ‡*, Trevor N. Brown †, Satoshi Endo †
† Department of Analytical Environmental Chemistry, UFZ – Helmholtz Centre for
Environmental Research, Permoserstrasse 15, D-04318 Leipzig, Germany
‡
Institute of Chemistry, University of Halle-Wittenberg, Kurt-Mothes-Strasse 2, D-06120 Halle,
Germany
*Corresponding author: Kai-Uwe Goss
Phone: +49 341 235 1411; fax: +49 341 235 450822; e-mail: kai-uwe.goss@ufz.de
S1
Derivation of the analytical solution for eq. 3 :
S2 Derivation of the relationship between the time until a steady-state body
burden is reached and the elimination rate constant.
S3 Information on the up-take efficiency of chemicals in the human GIT
S4 Ringtest for bioaccumulation in fish: variability of BMF and the
elimination rate constant.
S5 Estimations for organism-water and organism-air partition coefficients
for selected chemicals
S6 Comparison of the Tier 1 assessment for human and for an air breathing
animal that is 100 times lighter than a human using allometric scaling
S7 Field data on BMF compared with experimental elimination half-life data
in rat
2
S1
Derivation of the analytical solution for eq. 3 :
Equation 3 from main manuscript.
𝑑Corganism
𝑑𝑡
= 𝑘𝑢𝑝𝑡𝑎𝑘𝑒 𝐶𝑑𝑖𝑒𝑡 − 𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚
Rearrange right side to:
𝑑Corganism
𝑑𝑡
= 𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 [𝑘
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
𝐶𝑑𝑖𝑒𝑡 − 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 ]
Separate differential equation to:
1
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝐶
− 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑑𝑖𝑒𝑡
𝑑Corganism = 𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑑𝑡
Integrate each side and consolidate the constants into a single C
1
∫
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
− ln [𝑘
𝐶𝑑𝑖𝑒𝑡 − 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
𝑑Corganism = ∫ 𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑑𝑡
𝐶𝑑𝑖𝑒𝑡 − 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 ] = 𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑡 + 𝐶
Solve for C with t = 0 and 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 = 0:
𝐶 = − ln [𝑘
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
𝐶𝑑𝑖𝑒𝑡 ]
Substitute for C and invert signs:
ln [𝑘
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
𝐶𝑑𝑖𝑒𝑡 − 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 ] = −𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑡 + ln [𝑘
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
Take the exponential of each side:
[𝑘
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
𝐶𝑑𝑖𝑒𝑡 − 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 ] = 𝑒 −𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑡 × 𝑘
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
Rearrange to get Equation 8 from the main manuscript:
𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 = 𝐶𝑑𝑖𝑒𝑡
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
(1 − 𝑒 −𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑡 )
𝐶𝑑𝑖𝑒𝑡
𝐶𝑑𝑖𝑒𝑡 ]
3
S2 Derivation of the relationship between the time until a steady-state body
burden is reached and the elimination rate constant.
For an organism that starts with zero contamination at t = 0, the concentration will
asymptotically approach the steady-state situation according to the solution of eq. 3 for
Corganism = 0 at t = 0, see above):
𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚 = 𝐶𝑑𝑖𝑒𝑡
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
(1 − 𝑒 −𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑡 )
From eq. 5, which describes the steady state situation, it follows that 90% of the steady-state
concentration equals:
∗
0.9 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚
= 0.9 𝐶𝑑𝑖𝑒𝑡
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
Inserting this into the equation above and solving for t yields an expression for the time until
90% of the steady-state body-burden is reached:
∗
0.9 𝐶𝑜𝑟𝑔𝑎𝑛𝑖𝑠𝑚
= 0.9 𝐶𝑑𝑖𝑒𝑡
ln(−(0.9−1)
𝑡90% = −𝑘
𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
= 𝐶𝑑𝑖𝑒𝑡
𝑘𝑢𝑝𝑡𝑎𝑘𝑒
𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛
(1 − 𝑒 −𝑘𝑒𝑙𝑖𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑡90% )
4
S3 Information on the up-take efficiency of chemicals in the human GIT
Moser and McLachlan 1,2 have found that hydrophobic chemicals such as PCBs and PCDD/Fs show a
maximum absorption efficiency of 95-100% in humans for log Kow up to 7.5. This efficient up-take
occurs as co-absorption with dietary lipids and is facilitated by the transport in micelles. Only for very
hydrophobic chemicals with log Kow > 7.5 these authors report dietary absorption efficiency to
drop to values as low as 50%.
Dulfer 3 concluded from Caco-2 cell permeation studies that the resistance of the membrane was
negligible for all studied PCBs.
Comprehensive data sets from pharmaceutical sciences show that the fraction of a chemical absorbed in
the GIT is larger than 50% for all tested chemicals with a log Kow > 0 and larger than 80% for most
chemicals with log Kow > 0 4. Fraction absorbed values smaller than 90% for log Kow > 0 compounds
likely result from first-pass metabolism or active efflux and are likely not a result of physic-chemical
properties.
This information has two implications that are important in the context of bioaccumulation assessment:
a) it is very reasonable to assume a-priori that most neutral chemicals have an up-take efficiency
close to 100% in the human GIT.
b) the up-take efficiency does not correlate well with the physico-chemical properties of a chemical.
Therefore, an up-take efficiency considerably lower than 100% cannot easily be derived from
physico-chemical data in a Tier 1 assessment.
(1)
Moser, A. G.; Mclachlan, M. S. Modeling digestive tract absorption and desorption of lipophilic
organic contaminants in humans. Environ. Sci. Technol. 2002, 36 3318-3325.
(2)
Moser, G. A.; Mclachlan, M. S. The influence of dietary concentration on the absorption and
excretion of persistent lipophilic organic pollutants in the human intestinal tract. Chemosphere 2001, 45
(2), 201-211.
(3)
Dulfer, W. J.; Govers, H. a. J.; Groten, J. P. Kinetics and conductivity parameters of uptake and
transport of polychlorinated biphenyls in the caco-2 intestinal cell line model. Environmental Toxicology
And Chemistry 1998, 17 (3), 493-501.
(4)
Zhao, Y.-H.; Abraham, M. H.; Le, J.; Hersey, A.; Luscombe, C. N.; Beck, G.; Sherborne, B.;
Cooper, I. Rate-limited steps of human oral absorption and qsar studies. Pharmaceutical Research 2002,
19 (10), 1446-1457.
5
S4 Ringtest for bioaccumulation in fish: variability of BMF and the
elimination rate constant.
Recently a ring test for the validation of the OECD 305 dietary exposure bioaccumulation fish test was
conducted with trout. The report can be downloaded under:
http://www.oecd.org/env/chemicalsafetyandbiosafety/testingofchemicals/49190726.pdf
The results reveal that the resulting BMF tend to show a higher variability between different labs than the
resulting elimination rate constants despite a strict standardization of the feeding scheme (outliers were
excluded from this evaluation). Inherent sources of variability in the BMF determination even under
standardized conditions are the normalization to lipid content and the individual feeding behavior of the
fish.
compound
HCB
Musk xylene
o-terphenyl
methoxychlor
factor difference between the
highest and the lowest BMF value
factor difference between the
highest and the lowest k2-value
2.9
3.7
12.4
18.5
2.7
2.6
2.5
3.3
6
S5 Estimations for organism-water and organism-air partition coefficients
for selected chemicals
Table S5.1 ppLFER equations for 37°C
c
storage lipidwater
membranewater
muscle proteinwater
water-air
s
a
b
v
l
ref
0.55 -1.62
-1.93
-4.15
1.99
0.58
Geisler, 2012
0.53 -0.93
-0.18
-3.75
1.73
0.49
Endo, 2011
-0.94 -0.59
0.21
-3.17
2.13
0.33
Endo, 2012
-0.63 2.26
3.60
4.37
-2.21
0.31
Abraham, 2007 #1205]
Geisler, A.; Endo, S.; Goss, K.-U. Partitioning of organic chemicals to storage lipids: Elucidating the
dependence on fatty acid composition and temperature. Environ. Sci. Technol. 2012, 46 9519-9524
Endo, S.; Escher, B. I.; Goss, K. U. Capacities of membrane lipids to accumulate neutral organic
chemicals. Environ. Sci. Technol. 2011, 45 5912-5921.
Endo, S.; Bauerfeind, J.; Goss, K. U. Partitioning of neutral organic compounds to structural proteins.
Environ. Sci. Technol. 2012, 46 12697–12703.
Abraham, M. H.; Ibrahim, A.; Acree, W. E. Partition of compounds from gas to water and from gas to
physiological saline at 310 k: Linear free energy relationships. Fluid Phase Equilibria 2007, 251 (2), 93109.
7
Table S5.2 Typical body composition for a man (70 kg) from Wang et al. 1992.
water
Storage fats
Membrane fats
Protein
Inorganics (mostly bone
mineral)
other (eg carbohydrates)
Sum
mass kg
42
12
1.5
10.6
3.7
0.2
70
Wang, Z. M.; Pierson, R. N.; Heymsfield, S. B. The 5-level model - a new approach to organizing bodycomposition research. American Journal of Clinical Nutrition 1992, 56 (1), 19-28.
8
Table S5.3 pp-LFER descriptors of various chemicals
S
A
B
V
L
Reference
PCB 52
1.48
0.00
0.15
1.81
8.14
1
PCB 153
1.74
0.00
0.11
2.06
9.59
1
PCB 209
2.26
0.00
0.02
2.55
11.70
1
HCB
0.99
0.00
0.00
1.45
7.39
2
benzene
0.52
0.00
0.14
0.72
2.79
3
toluene
0.52
0.00
0.14
0.86
3.33
3
n-pentylbenzene
0.51
0.00
0.15
1.42
5.23
3
naphthalene
0.92
0.00
0.20
1.09
5.16
3
phenanthrene
1.29
0.00
0.29
1.45
7.63
3
B[a]P
1.96
0.00
0.37
1.95
11.74
4
beta-HCH
1.18
0.12
0.58
1.58
7.63
5
gamma-HCH
1.28
0.00
0.50
1.58
7.57
5
atrazine
1.29
0.17
1.01
1.62
7.78
6
carbaryl
1.30
0.46
0.75
1.54
7.81
6
D4
-0.08
0.00
0.51
2.34
4.47
7
D5
-0.10
0.00
0.65
2.93
5.24
7
D6
-0.12
0.00
0.80
3.52
6.08
7
PBDE 47
1.45
0.00
0.34
2.08
10.66
8
PBDE 153
1.54
0.00
0.52
2.43
12.65
8
propachlor
1.39
-0.03
0.89
1.66
6.83
9
metolachlor
0.95
0.09
1.35
2.28
8.86
9
1.55
0.00
1.28
2.07
10.48
10
diazepam
1.56
0.99
0.91
1.86
9.60
11
bisphenol A
1.82
0.08
1.25
1.36
7.84
3
caffeine
1) Abraham, M. H., Al-Hussaini, A. J. M. (2005) J. Env. Monitor., 7, 295-301.
2) Abraham, M. H., Ibrahim, A., Acree, Jr. W. E. (2007) Fluid Phase Eq., 251, 93.
3) Abraham, M. H., Sanchez-Moreno, R., Gil-Lostes, J., Acree, W. E., Jr., Cometto-Muniz, J. E.,
Cain, W. S. (2010) Toxicol. Vitro, 24, 357-362.
4) Abraham, M. H., Ibrahim, A., Acree, Jr. W. E. (2007) Fluid Phase Eq., 251, 93.
5) Goss, K.-U., Arp, H. P. H., Bronner, G., Niederer, C. (2008) J. Chem. Eng. Data, 53, 750.
6) Bronner, G.; Goss, K. U. Predicting sorption of pesticides and other multifunctional organic
chemicals to soil organic carbon. Environ. Sci. Technol. 2011, 45 1313-1319.
7) Atapattu, S. N.; Poole, C. F. Determination of descriptors for semivolatile organosilicon
compounds by gas chromatography and non-aqueous liquid-liquid partition. Journal of
Chromatography A 2009, 1216 (45), 7882
8) Stenzel, A.; Goss, K.-U., Endo,S. submitted (2012)
9) Tülp, H. C., Goss, K.-U., Schwarzenbach, R. P., Fenner, K. (2008) Environ. Sci. Technol., 42,
2034-2040
10) Abraham, M. H., Ibrahim, A., Acree, W. E. (2008) Eur. J. Med. Chem., 43, 478-485.
11) Abraham, M. H., Acree, W. E., Leo, A. J., Hoekman, D. (2009) New J. Chem, 33, 1685-1692.
9
Table S5.5 Calculated logarithmic tissue-water and water-air partition coefficients at 37°C and
resulting body-water and body-air partition coefficients for a human (male, 70 kg)
PCB 52
PCB 153
PCB 209
HCB
benzene
toluene
n-pentylbenzene
naphthalene
phenanthrene
B[a]P
beta-HCH
gamma-HCH
atrazine
carbaryl
D4
D5
D6
PBDE 47
PBDE 153
propachlor
metolachlor
diazepam
bisphenol A
caffeine
membrane-w
5.73
6.78
8.52
5.75
2.13
2.64
4.52
3.34
4.51
6.47
3.72
3.92
2.14
2.94
4.94
5.85
6.71
6.75
7.57
2.12
2.87
3.03
3.44
0.35
w-a
1.91
2.24
2.60
0.72
0.44
0.30
-0.32
1.54
2.73
4.78
3.90
3.33
6.17
6.29
-2.36
-2.86
-3.26
2.88
3.72
4.78
5.48
7.17
9.33
8.67
storage lipid-w muscle-w
5.86
4.28
6.93
5.25
8.66
6.97
6.12
4.02
2.17
0.76
2.76
1.24
4.96
3.05
3.38
1.91
4.58
3.01
6.53
4.79
3.57
2.45
3.94
2.60
1.68
1.17
2.04
1.89
5.82
3.96
6.90
5.05
7.94
6.09
7.11
5.09
8.07
5.88
1.91
1.21
2.91
2.03
2.93
1.98
1.62
2.62
-0.48
-0.45
body-w
5.14
6.21
7.94
5.38
1.47
2.05
4.22
2.68
3.87
5.82
2.90
3.23
1.14
1.70
5.06
6.14
7.18
6.37
7.32
1.30
2.24
2.27
2.11
-0.12
body-air
7.06
8.45
10.54
6.10
1.91
2.35
3.90
4.22
6.59
10.60
6.80
6.56
7.31
7.98
2.71
3.28
3.92
9.25
11.04
6.08
7.72
9.43
11.44
8.55
10
S6 Comparison of the Tier 1 assessment for human and for an air breathing
animal that is 100 times lighter than a human using allometric scaling.
Humans: A daily feeding rate of 1% of the body weight is representative for humans. This leads
to an EL0.5 value of < 70 d for BMF to stay < 1. With the following representative excretion
rates (breathing rate, 250 Lair kgorganism-1 d-1; urination rate 0.017 Lurine kgorganism-1 d-1; fecal
excretion rate 0.0005 kgfeces-1 kgorganism-1 d-1) one can derive the following table that relates the
physico-chemical properties of a chemical to its EL0.5. EL0.5 values larger than the human
threshold value of 70 days are highlighted in red. This table is equivalent to Figure 2A in the
main text.
log Korganism/air at 37°C
logKorganism/urin
at 37°C
0
0.3
1
2
3
4
5
2
0.3
0.3
0.3
0.3
0.3
0.3
0.3
3
2.6
2.7
2.7
2.8
2.8
2.8
2.8
4
16.3
20.4
25.5
27.0
27.2
27.2
27.2
4.5
27.3
41.0
68.6
80.8
82.3
82.4
82.5
5
34.7
60.2
147.5
218.7
229.7
230.9
231.0
6
39.1
74.8
282.9
753.4
903.7
922.1
924.0
7
39.6
76.6
311.5
997.3
1278.9
1316.0
1319.9
According to allometric scaling the physiological parameters, PP, normalized to body weight,
BW, scale according to the following rule (see main text):
PP / BW = a BW-0.25
Thus the feeding rate but also all excretion rates should become larger by a factor 3.16 for an
organism that is 100 times lighter than a human (e.g. a rat). Accordingly, the rates are: feeding
rate per day 3.16 % of body weight, breathing rate 790 L/d/kg, urination rate 0.054 L/d/kg, fecal
excretion rate 0.00158 kgfeces/kgorganism/d. The higher feeding rate leads to an EL0.5 threshold
value of < 22 d for BMF to stay < 1. However, the excretion rates are also higher so that the
physico-chemical properties of a chemical that still allow efficient excretion are the same as for a
human. EL0.5 values larger than the threshold value of 22 days are highlighted in red.
log Korganism/air at 37°C
logKorganism/urin
at 37°C
0
0.3
1
2
3
4
5
2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
3
0.8
0.8
0.9
0.9
0.9
0.9
0.9
4
5.2
6.4
8.1
8.5
8.6
8.6
8.6
4.5
8.6
12.9
21.7
25.6
26.0
26.1
26.1
5
10.9
19.0
46.6
69.2
72.7
73.1
73.1
6
12.3
23.5
89.2
238.2
286.0
291.8
292.4
7
12.5
24.1
98.2
315.2
404.6
416.5
417.7
11
S7 Field data on BMF compared with experimental elimination half-life data
in rat
Figure S7.1. Field-measured BMF against rat-elimination half-lives. Data are from a review article by
Burkhard 2011. For the sources of rat EL0.5 data, see the Figure 3 caption in the main manuscript.The
terrestrial animals included are mostly mammals and avians.
Figure S7.2. Field-BMF measured by Kelly and Gobas (2001) against lab-measured rat
elimination half-lives. This figure is identical to Figure 3 in the manuscript, but with chemical
names as labels. The data came from the following references:
1.
2.
3.
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